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Mueller-Hinton agar is a microbiological growth medium that is commonly used for antibiotic susceptibility testing. It is also used to isolate and maintain "Neisseria" and "Moraxella" species. It typically contains: Five percent sheep blood and nicotinamide adenine dinucleotide may also be added when susceptibility testing is done on "Streptococcus" species. This type is also commonly used for susceptibility testing of "Campylobacter". It has a few properties that make it excellent for antibiotic use. First of all, it is a nonselective, nondifferential medium. This means that almost all organisms plated on it will grow. Additionally, it contains starch. Starch is known to absorb toxins released from bacteria, so that they cannot interfere with the antibiotics. Second, it is a loose agar. This allows for better diffusion of the antibiotics than most other plates. A better diffusion leads to a truer zone of inhibition. was co-developed by microbiologist John Howard Mueller and veterinary scientist Jane Hinton at Harvard university as a culture for gonococcus and meningococcus, who published the method in 1941.

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Mueller-Hinton agar

Melanism: Evolution in Action () is a book by Dr. Mike Majerus, published in 1998. It is an update of Bernard Kettlewell's book "The Evolution of Melanism". The book contains a very useful summary of Majerus' work on melanism in ladybirds and a review of the peppered moth story, including observations on moth behavior which sparked controversy. It may be criticised for being unevenly edited so as not to suit any one audience in its entirety. For example, it explains the basic principles of evolution such as the Hardy–Weinberg law in earlier sections, and in later sections includes graduate level concepts. Jerry Coyne reviewed the book for "Nature", calling attention to the importance of the new moth behavior observations, and how they shook Bernard Kettlewell's original hypothesis. This review has been criticised by Majerus and others of not being representative of the work. Reviews such as by Laurence Cook discussed Majerus' treatment but did not anticipate the controversy largely provoked by Coyne's review.

Biology

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Melanism: Evolution in Action

PIPES is the common name for piperazine-N,N′-bis(2-ethanesulfonic acid), and is a frequently used buffering agent in biochemistry. It is an ethanesulfonic acid buffer developed by Good et al. in the 1960s. has pKa (6.76 at 25°C) near the physiological pH which makes it useful in cell culture work. Its effective buffering range is 6.1-7.5 at 25° C. has been documented minimizing lipid loss when buffering glutaraldehyde histology in plant and animal tissues. Fungal zoospore fixation for fluorescence microscopy and electron microscopy were optimized with a combination of glutaraldehyde and formaldehyde in buffer. It has a negligible capacity to bind divalent ions.

Biology

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PIPES

HubMed is an alternative, third-party interface to PubMed, the database of biomedical literature produced by the National Library of Medicine. Features include relevance-ranked search results, direct citation export, tagging and graphical display of related articles.

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HubMed

Mating of yeast The yeast "Saccharomyces cerevisiae" is a simple single-celled eukaryote with both a diploid and haploid mode of existence. The mating of yeast only occurs between haploids, which can be either the a or α (alpha) mating type and thus display simple sexual differentiation. Mating type is determined by a single locus, "MAT", which in turn governs the sexual behaviour of both haploid and diploid cells. Through a form of genetic recombination, haploid yeast can switch mating type as often as every cell cycle. "S. cerevisiae" (yeast) can stably exist as either a diploid or a haploid. Both haploid and diploid yeast cells reproduce by mitosis, with daughter cells budding off of mother cells. Haploid cells are capable of mating with other haploid cells of the opposite mating type (an a cell can only mate with an α cell, and vice versa) to produce a stable diploid cell. Diploid cells, usually upon facing stressful conditions such as nutrient depletion, can undergo meiosis to produce four haploid spores: two a spores and two α spores. a cells produce ‘a-factor’, a mating pheromone which signals the presence of an a cell to neighbouring α cells. a cells respond to α-factor, the α cell mating pheromone, by growing a projection (known as a shmoo, due to its distinctive shape resembling the Al Capp cartoon character Shmoo) towards the source of α-factor. Similarly, α cells produce α-factor, and respond to a-factor by growing a projection towards the source of the pheromone

Biology

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Mating of yeast

Mating of yeast The response of haploid cells only to the mating pheromones of the opposite mating type allows mating between a and α cells, but not between cells of the same mating type. These phenotypic differences between a and α cells are due to a different set of genes being actively transcribed and repressed in cells of the two mating types. a cells activate genes which produce a-factor and produce a cell surface receptor (Ste2) which binds to α-factor and triggers signaling within the cell. a cells also repress the genes associated with being an α cell. Similarly, α cells activate genes which produce α-factor and produce a cell surface receptor (Ste3) which binds and responds to a-factor, and α cells repress the genes associated with being an a cell. The different sets of transcriptional repression and activation which characterize a and α cells are caused by the presence of one of two alleles of a locus called "MAT": "MATa" or "MATα" located on chromosome III. The MAT locus is usually divided into five regions (W, X, Y, Z1, and Z2) based on the sequences shared among the two mating types. The difference lies in the Y region (Ya and Yα), which contains most of the genes and promoters. The "MATa" allele of "MAT" encodes a gene called a1, which in haploids direct the transcription of the a-specific transcriptional program (such as expressing "STE2" and repressing "STE3") that defines an a cell

Biology

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Mating of yeast

Mating of yeast The "MATα" allele of "MAT" encodes the α1 and α2 genes, which in haploids direct the transcription of the α-specific transcriptional program (such as expressing "STE3", repressing "STE2") which causes the cell to be an α cell. "S. cerevisiae" has an a2 gene with no apparent function that shares much of its sequence with α2; however, other yeasts like "Candida albicans" do have a functional and distinct MATa2 gene. Haploid cells are one of two mating types (a or α), and respond to the mating pheromone produced by haploid cells of the opposite mating type, and can mate with cells of the opposite mating type. Haploid cells cannot undergo meiosis. Diploid cells do not produce or respond to either mating pheromone and do not mate, but can undergo meiosis to produce four haploid cells. Like the differences between haploid a and α cells, different patterns of gene repression and activation are responsible for the phenotypic differences between haploid and diploid cells. In addition to the specific a and α transcriptional patterns, haploid cells of both mating types share a haploid transcriptional pattern which activates haploid-specific genes (such as "HO") and represses diploid-specific genes (such as "IME1"). Similarly, diploid cells activate diploid-specific genes and repress haploid-specific genes. The different gene expression patterns of haploids and diploids are again due to the "MAT" locus

Biology

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Mating of yeast

Mating of yeast Haploid cells only contain one copy of each of the 16 chromosomes and thus can only possess one allele of "MAT" (either "MATa or "MATα"), which determines their mating type. Diploid cells result from the mating of an a cell and an α cell, and thus possess 32 chromosomes (in 16 pairs), including one chromosome bearing the "MATa allele and another chromosome bearing the "MATα" allele. The combination of the information encoded by the "MATa allele (the a1 gene) and the "MATα" allele (the α1 and α2 genes) triggers the diploid transcriptional program. Similarly, the presence of only a single allele of "MAT", whether it is "MATa or "MATα", triggers the haploid transcriptional program. The alleles present at the "MAT" locus are sufficient to program the mating behaviour of the cell. For example, using genetic manipulations, a "MATa allele can be added to a "MATα" haploid cell. Despite having a haploid complement of chromosomes, the cell now has both the "MATa and "MATα" alleles, and will behave like a diploid cell: it will not produce or respond to mating pheromones, and when starved will attempt to undergo meiosis, with fatal results. Similarly, deletion of one copy of the "MAT" locus in a diploid cell, leaving only a single "MATa" or "MATα" allele, will cause a cell with a diploid complement of chromosomes to behave like a haploid cell. Mating in yeast is stimulated by the presence of a pheromone which binds to either the Ste2 receptor (in a-cells) or the Ste3 receptor (in α-cells)

Biology

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Mating of yeast

Mating of yeast The binding of this pheromone then leads to the activation of a heterotrimeric G protein. The dimeric portion of this G-protein recruits Ste5 (and its related MAPK cascade components) to the membrane, and ultimately results in the phosphorylation of Fus3. The switching mechanism arises as a result of competition between the Fus3 protein (a MAPK protein) and the phosphatase Ptc1. These proteins both attempt to control the 4 phosphorylation sites of Ste5, a scaffold protein with Fus3 attempting to phosphorylate the phosphosites, and Ptc1 attempting to dephosphorylate them. Presence of α-factor induces recruitment of Ptc1 to Ste5 via a 4 amino acid motif located within the Ste5 phosphosites. Ptc1 then dephosphorylates Ste5, ultimately resulting in the dissociation of the Fus3-Ste5 complex. Fus3 dissociates in a switch-like manner, dependant on the phosphorylation state of the 4 phosphosites. All 4 phosphosites must be dephosphorylated in order for Fus3 to dissociate. Fus3's ability to compete with Ptc1 decreases as Ptc1 is recruited, and thus the rate of dephosphorylation increases with the presence of pheromone. Kss1, a homologue of Fus3, does not affect shmooing, and does not contribute to the switch-like mating decision. In yeast, mating as well as the production of shmoos occur via an all-or-none, switch-like mechanism. This switch-like mechanism allows yeast cells to avoid making an unwise commitment to a highly demanding procedure

Biology

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Mating of yeast

Mating of yeast However, not only does the mating decision need to be conservative (in order to avoid wasting energy), but it must also be fast to avoid losing the potential mate. The decision to mate is extremely sensitive. There are 3 ways in which this ultrasensitivity is maintained: [a and α yeast share the same mating response pathway, with the only difference being the type of receptor each mating type possesses. Thus the above description, given for a-type yeast stimulated with α-factor, works equally well for α-type yeast stimulated with a-factor.] Wild type haploid yeast are capable of switching mating type between a and α. Consequently, even if a single haploid cell of a given mating type founds a colony of yeast, mating type switching will cause cells of both a and α mating types to be present in the population. Combined with the strong drive for haploid cells to mate with cells of the opposite mating type and form diploids, mating type switching and consequent mating will cause the majority of cells in a colony to be diploid, regardless of whether a haploid or diploid cell founded the colony. The vast majority of yeast strains studied in laboratories have been altered such that they cannot perform mating type switching (by deletion of the "HO" gene; see below); this allows the stable propagation of haploid yeast, as haploid cells of the a mating type will remain a cells (and α cells will remain α cells), and will not form diploids

Biology

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Mating of yeast

Mating of yeast Haploid yeast switch mating type by replacing the information present at the "MAT" locus. For example, an a cell will switch to an α cell by replacing the "MATa allele with the "MATα" allele. This replacement of one allele of "MAT" for the other is possible because yeast cells carry an additional silenced copy of both the "MATa and "MATα" alleles: the "HML" (homothallic mating left) locus typically carries a silenced copy of the "MATα" allele, and the "HMR" (homothallic mating right) locus typically carries a silenced copy of the "MATa" allele. The silent "HML" and "HMR" loci are often referred to as the silent mating cassettes, as the information present there is 'read into' the active "MAT" locus. These additional copies of the mating type information do not interfere with the function of whatever allele is present at the "MAT" locus because they are not expressed, so a haploid cell with the "MATa" allele present at the active "MAT" locus is still an a cell, despite also having a (silenced) copy of the "MATα" allele present at "HML". Only the allele present at the active "MAT" locus is transcribed, and thus only the allele present at "MAT" will influence cell behaviour. Hidden mating type loci are epigenetically silenced by SIR proteins, which form a heterochromatin scaffold that prevents transcription from the silent mating cassettes. The process of mating type switching is a gene conversion event initiated by the "HO" gene

Biology

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Mating of yeast

Mating of yeast The "HO" gene is a tightly regulated haploid-specific gene that is only activated in haploid cells during the G phase of the cell cycle. The protein encoded by the "HO" gene is a DNA endonuclease, which physically cleaves DNA, but only at the "MAT" locus (due to the DNA sequence specificity of the HO endonuclease). Once HO cuts the DNA at "MAT", exonucleases are attracted to the cut DNA ends and begin to degrade the DNA on both sides of the cut site. This DNA degradation by exonucleases eliminates the DNA which encoded the "MAT" allele; however, the resulting gap in the DNA is repaired by copying in the genetic information present at either "HML" or "HMR", filling in a new allele of either the "MATa or "MATα" gene. Thus, the silenced alleles of "MATa and "MATα" present at "HML" and "HMR" serve as a source of genetic information to repair the HO-induced DNA damage at the active "MAT" locus. The repair of the "MAT" locus after cutting by the HO endonuclease almost always results in a mating type switch. When an a cell cuts the "MATa allele present at the "MAT" locus, the cut at "MAT" will almost always be repaired by copying the information present at "HML". This results in "MAT" being repaired to the "MATα" allele, switching the mating type of the cell from a to α. Similarly, an α cell which has its "MATα" allele cut by the HO endonuclease will almost always repair the damage using the information present at "HMR", copying the "MATa gene to the "MAT" locus and switching the mating type of α cell to a

Biology

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Mating of yeast

Mating of yeast This is the result of the action of a recombination enhancer (RE) located on the left arm of chromosome III. Deletion of this region causes a cells to incorrectly repair using HMR. In a cells, Mcm1 binds to the RE and promotes recombination of the HML region. In α cells, the α2 factor binds at the RE and establishes a repressive domain over RE such that recombination is unlikely to occur. An innate bias means that the default behaviour is repair from HMR. The exact mechanisms of these interactions are still under investigation. Ruderfer et al. analyzed the ancestry of natural "S. cerevisiae" strains and concluded that matings involving out-crossing occur only about once every 50,000 cell divisions. Thus it appears that, in nature, mating is most often between closely related yeast cells. Mating occurs when haploid cells of opposite mating type "MATa" and "MATα" come into contact. Ruderfer et al. pointed out that such contacts are frequent between closely related yeast cells for two reasons. The first is that cells of opposite mating type are present together in the same ascus, the sac that contains the cells directly produced by a single meiosis, and these cells can mate with each other. The second reason is that haploid cells of one mating type, upon cell division, often produce cells of the opposite mating type with which they can mate (see section “Mating type switching”, above)

Biology

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Mating of yeast

Mating of yeast The relative rarity in nature of meiotic events that result from out-crossing appears to be inconsistent with the idea that production of genetic variation is the primary selective force maintaining mating capability in this organism. However this finding is consistent with the alternative idea that the primary selective force maintaining mating capability is enhanced recombinational repair of DNA damage during meiosis, since this benefit is realized during each meiosis subsequent to a mating, whether or not out-crossing occurs. "Schizosaccharomyces pombe" is a facultative sexual yeast that can undergo mating when nutrients are limiting. Exposure of "S. pombe" to hydrogen peroxide, an agent that causes oxidative stress leading to oxidative DNA damage, strongly induces mating, meiosis, and formation of meiotic spores. This finding suggests that meiosis, and particularly meiotic recombination, may be an adaptation for repairing DNA damage. The overall structure of the "MAT" locus is similar to that in "S. cerevisiae". The mating-type switching system is similar, but has evolved independently. "Cryptococcus neoformans" is a basidiomycetous fungus that grows as a budding yeast in culture and in an infected host. "C. neoformans" causes life-threatening meningoencephalitis in immune compromised patients. It undergoes a filamentous transition during the sexual cycle to produce spores, the suspected infectious agent. The vast majority of environmental and clinical isolates of "C. neoformans" are mating type α

Biology

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Mating of yeast

Mating of yeast Filaments ordinarily have haploid nuclei, but these can undergo a process of diploidization (perhaps by endoduplication or stimulated nuclear fusion) to form diploid cells termed blastospores. The diploid nuclei of blastospores can then undergo meiosis, including recombination, to form haploid basidiospores that can then be dispersed. This process is referred to as monokaryotic fruiting. Required for this process is a gene designated "dmc1", a conserved homologue of genes RecA in bacteria, and RAD51 in eukaryotes. "Dmc1" mediates homologous chromosome pairing during meiosis and repair of double-strand breaks in DNA (see Meiosis; also Michod et al.). Lin et al. suggested that one benefit of meiosis in "C. neoformans" could be to promote DNA repair in a DNA damaging environment that could include the defensive responses of the infected host.

Biology

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Mating of yeast

Polyphosphate-accumulating organisms (PAOs) are a group of bacteria that, under certain conditions, facilitate the removal of large amounts of phosphorus from wastewater in a process, called enhanced biological phosphorus removal (EBPR). PAOs accomplish this removal of phosphate by accumulating it within their cells as polyphosphate. PAOs are by no means the only bacteria that can accumulate polyphosphate within their cells and in fact, the production of polyphosphate is a widespread ability among bacteria. However, the PAOs have many characteristics that other organisms that accumulate polyphosphate do not have, that make them amenable to use in wastewater treatment. Specifically, this is the ability to consume simple carbon compounds (energy source) without the presence of an external electron acceptor (such as nitrate or oxygen) by generating energy from internally stored polyphosphate and glycogen. Most other bacteria cannot consume under these conditions and therefore PAOs gain a selective advantage within the mixed microbial community present in the activated sludge. Therefore, wastewater treatment plants that operate for enhanced biological phosphorus removal have an anaerobic tank (where there is no nitrate or oxygen present as external electron acceptor) prior to the other tanks to give PAOs preferential access to the simple carbon compounds in the wastewater that is influent to the plant. A PAO related to the "Betaproteobacteria" has been identified and named Candidatus Accumulibacter Phosphatis

Biology

https://en.wikipedia.org/wiki?curid=3479299

Polyphosphate-accumulating organisms

Polyphosphate-accumulating organisms Accumulibacter has been shown to remove phosphorus from EBPR plants in Australia, Europe and the USA. It can consume a range of carbon compounds, such as acetate and propionate, under anaerobic conditions and store these compounds as polyhydroxyalkanoates (PHA) which it consumes as a carbon and energy source for growth using oxygen or nitrate as electron acceptor. Recently, another PAO related to the "Actinobacteria" has been identified in wastewater treatment plants. These organisms appear to be limited to certain amino acids as carbon and energy source. The storage compound that they use to store the amino acids that these organisms take up under anaerobic conditions has not been identified. These bacteria have been observed in some EBPR plants in Denmark (where they were discovered) but their wider distribution is unknown.

Biology

https://en.wikipedia.org/wiki?curid=3479299

Polyphosphate-accumulating organisms

Kaede (protein) Kaede is a photoactivatable fluorescent protein naturally originated from a stony coral, "Trachyphyllia geoffroyi". Its name means "maple" in Japanese. With the irradiation of ultraviolet light (350–400 nm), Kaede undergoes irreversible photoconversion from green fluorescence to red fluorescence. Kaede is a homotetrameric protein with the size of 116 kDa. The tetrameric structure was deduced as its primary structure is only 28 kDa. This tetramerization possibly makes Kaede have a low tendency to form aggregates when fused to other proteins. The property of photoconverted fluorescence Kaede protein was serendipitously discovered and first reported by Ando et al. in Proceedings of the United States National Academy of Sciences. An aliquot of Kaede protein was discovered to emit red fluorescence after being left on the bench and exposed to sunlight. Subsequent verification revealed that Kaede, which is originally green fluorescent, after exposure to UV light is photoconverted, becoming red fluorescent. It was then named Kaede. The property of photoconversion in Kaede is contributed by the tripeptide, His62-Tyr63-Gly64, that acts as a green chromophore that can be converted to red. Once Kaede is synthesized, a chromophore, 4-(p-hydroxybenzylidene)-5-imidazolinone, derived from the tripeptide mediates green fluorescence in Kaede. When exposed to UV, Kaede protein undergoes un conventional cleavage between the amide nitrogen and the α carbon (Cα) at His62 via a formal β-elimination reaction

Biology

https://en.wikipedia.org/wiki?curid=20723155

Kaede (protein)

Kaede (protein) Followed by the formation of a double bond between His62-Cα and –Cβ, the π-conjugation is extended to the imidazole ring of His62. A new chromophore, 2-[(1E)-2-(5-imidazolyl)ethenyl]-4-(p-hydroxybenzylidene)-5-imidazolinone, is formed with the red-emitting property. The cleavage of the tripeptide was analysed by SDS-PAGE analysis. Unconverted green Kaede shows one band at 28 kDa, where two bands at 18 kDa and 10 kDa are observed for converted red Kaede, indicating that the cleavage is crucial for the photoconversion. A shifting of the absorption and emission spectrum in Kaede is caused by the cleavage of the tripeptide. Before the photoconversion, Kaede displays a major absorption wavelength maximum at 508 nm, accompanied with a slight shoulder at 475 nm. When it is excited at 480 nm, green fluorescence is emitted with a peak of 518 nm. When Kaede is irradiated with UV or violet light, the major absorption peak shifts to 572 nm. When excited at 540 nm, Kaede showed an emission maximum at 582 nm with a shoulder at 627 nm and the 518-nm peak. Red fluorescence is emitted after this photoconversion. The photoconversion in Kaede is irreversible. Exposure in dark or illumination at 570 nm cannot restore its original green fluorescence. A reduced fluorescence is observed in red, photoconverted Kaede when it is intensively exposed to 405 nm light, followed by partial recover after several minutes

Biology

https://en.wikipedia.org/wiki?curid=20723155

Kaede (protein)

Kaede (protein) As all other fluorescent proteins, Kaede can be the regional optical markers for gene expression and protein labeling for the study of cell behaviors. One of the most useful applications is the visualization of neurons. Delineation of an individual neuron is difficult due to the long and thin processes which entangle with other neurons. Even when cultured neurons are labeled with fluorescent proteins, they are still difficult to identify individually because of the dense package. In the past, such visualization could be done conventionally by filling neurons with Lucifer yellow or sulforhodamine, which is a laborious technique.[1] After the discovery of Kaede protein, it was found to be useful in delineating individual neurons. The neurons are transfected by Kaede protein cDNA, and are UV irradiated. The red, photoconverted Kaede protein has free diffusibility in the cell except for the nucleus, and spreads over the entire cell including dendrites and axon. This technique help disentangle the complex networks established in a dense culture. Besides, by labeling neurons with different colors by UV irradiating with different duration times, contact sites between the red and green neurons of interest are allowed to be visualized. The ability of visualization of individual cells is also a powerful tool to identify the precise morphology and migratory behaviors of individual cells within living cortical slices

Biology

https://en.wikipedia.org/wiki?curid=20723155

Kaede (protein)

Kaede (protein) By Kaede protein, a particular pair of daughter cells in neighboring Kaede-positive cells in the ventricular zone of mouse brain slices can be followed. The cell-cell borders of daughter cells are visualized and the position and distance between two or more cells can be described. As the change in the fluorescent colour is induced by UV light, marking of cells and subcellular structures is efficient even when only a partial photoconversion is induced. Due to the special property of photo-switchable fluorescence, Kaede protein possesses several advantages as an optical cell marker. After the photoconversion, the photoconverted Kaede protein emits bright and stable red fluorescence. This fluorescence can last for months without anaerobic conditions. As this red state of Kaede is bright and stable compared to the green state, and because the unconverted green Kaede emits very low intensity of red fluorescence, the red signals provides contrast. Besides, before the photoconversion, Kaede emits bright green fluorescence which enables the visualization of the localization of the non-photoacivated protein. This is superior to other fluorescent proteins such as PA-GFP and KFP1, which only show low fluorescence before photoactivation. In addition, as both green and red fluorescence of Kaede are excited by blue light at 480 nm for observation, this light will not induce photoconversion. Therefore, illumination lights for observation and photoconversion can be separated completely

Biology

https://en.wikipedia.org/wiki?curid=20723155

Kaede (protein)

Kaede (protein) In spite of the usefulness in cell tracking and cell visualization of Kaede, there are some limitations. Although Kaede will shift to red upon the exposure of UV or violet light and display a 2,000-fold increase in red-to-green fluorescence ratio, using both the red and green fluorescence bands can cause problems in multilabel experiments. The tetramerization of Kaede may disturb the localization and trafficking of fusion proteins. This limits the usefulness of Kaede as a fusion protein tag. The photoconversion property of Kaede does not only contribute to the application on protein labeling and cell tracking, it is also responsible for the vast variation in the colour of stony corals, "Trachyphyllia geoffroyi". Under sunlight, due to the photoconversion of Kaede, the tentacles and disks will turn red. As green fluorescent Kaede is synthesized continuously, these corals appear green again as more unconverted Kaede is created. By the different proportion of photoconverted and unconverted Kaede, great diversity of colour is found in corals.

Biology

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Kaede (protein)

History of pathology The history of pathology can be traced to the earliest application of the scientific method to the field of medicine, a development which occurred in the Middle East during the Islamic Golden Age and in Western Europe during the Italian Renaissance. Early systematic human dissections were carried out by the Ancient Greek physicians Herophilus of Chalcedon and Erasistratus of Chios in the early part of the third century BC. The first physician known to have made postmortem dissections was the Arabian physician Avenzoar (1091–1161). Rudolf Virchow (1821–1902) is generally recognized to be the father of microscopic pathology. Most early pathologists were also practicing physicians or surgeons.also see Egyptian mummification as pre modern necropsy might suggest as early embalming and post mortem organ removal. Early understanding of the origins of diseases constitutes the earliest application of the scientific method to the field of medicine, a development which occurred in the Middle East during the Islamic Golden Age and in Western Europe during the Italian Renaissance. The Greek physician Hippocrates, the founder of scientific medicine, was the first to deal with the anatomy and the pathology of human spine. Galen developed an interest in anatomy from his studies of Herophilus and Erasistratus

Biology

https://en.wikipedia.org/wiki?curid=19391193

History of pathology

History of pathology The concept of studying disease through the methodical dissection and examination of diseased bodies, organs, and tissues may seem obvious today, but there are few if any recorded examples of true autopsies performed prior to the second millennium. Though the pathology of contagion was understood by Muslim physicians since the time of Avicenna (980–1037) who described it in "The Canon of Medicine" (c. 1020), the first physician known to have made postmortem dissections was the Arabian physician Avenzoar (1091–1161) who proved that the skin disease scabies was caused by a parasite, followed by Ibn al-Nafis (b. 1213) who used dissection to discover pulmonary circulation in 1242. In the 15th century, anatomic dissection was repeatedly used by the Italian physician Antonio Benivieni (1443-1502) to determine cause of death. Antonio Benivieni is also credited with having introduced necropsy to the medical field. Perhaps the most famous early gross pathologist was Giovanni Morgagni (1682-1771). His magnum opus, "De Sedibus et Causis Morborum per Anatomem Indagatis", published in 1761, describes the findings of over 600 partial and complete autopsies, organised anatomically and methodically correlated with the symptoms exhibited by the patients prior to their demise. Although the study of normal anatomy was already well advanced at this date, "De Sedibus" was one of the first treatises specifically devoted to the correlation of diseased anatomy with clinical illness

Biology

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History of pathology

History of pathology By the late 1800s, an exhaustive body of literature had been produced on the gross anatomical findings characteristic of known diseases. The extent of gross pathology research in this period can be epitomized by the work of the Viennese pathologist (originally from Hradec Kralove in the Czech Rep.) Carl Rokitansky (1804-1878), who is said to have performed 20,000 autopsies, and supervised an additional 60,000, in his lifetime. Rudolf Virchow (1821-1902) is generally recognized to be the father of microscopic pathology. While the compound microscope had been invented approximately 150 years prior, Virchow was one of the first prominent physicians to emphasize the study of manifestations of disease which were visible only at the cellular level. A student of Virchow's, Julius Cohnheim (1839-1884) combined histology techniques with experimental manipulations to study inflammation, making him one of the earliest experimental pathologists. Cohnheim also pioneered the use of the frozen section procedure; a version of this technique is widely employed by modern pathologists to render diagnoses and provide other clinical information intraoperatively. As new research techniques, such as electron microscopy, immunohistochemistry, and molecular biology have expanded the means by which biomedical scientists can study disease, the definition and boundaries of investigative pathology have become less distinct

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History of pathology

History of pathology In the broadest sense, nearly all research which links manifestations of disease to identifiable processes in cells, tissues, or organs can be considered experimental pathology.

Biology

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History of pathology

Introduction to evolution Evolution is the process of change in all forms of life over generations, and evolutionary biology is the study of how evolution occurs. Biological populations evolve through genetic changes that correspond to changes in the organisms' observable traits. Genetic changes include mutations, which are caused by damage or replication errors in organisms' DNA. As the genetic variation of a population drifts randomly over generations, natural selection gradually leads traits to become more or less common based on the relative reproductive success of organisms with those traits. The age of the Earth is about 4.5 billion years. The earliest undisputed evidence of life on Earth dates at least from 3.5 billion years ago. Evolution does not attempt to explain the origin of life (covered instead by abiogenesis), but it does explain how early lifeforms evolved into the complex ecosystem that we see today. Based on the similarities between all present-day organisms, all life on Earth is assumed to have originated through common descent from a last universal ancestor from which all known species have diverged through the process of evolution. All individuals have hereditary material in the form of genes received from their parents, which they pass on to any offspring. Among offspring there are variations of genes due to the introduction of new genes via random changes called mutations or via reshuffling of existing genes during sexual reproduction. The offspring differs from the parent in minor random ways

Biology

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Introduction to evolution

Introduction to evolution If those differences are helpful, the offspring is more likely to survive and reproduce. This means that more offspring in the next generation will have that helpful difference and individuals will not have equal chances of reproductive success. In this way, traits that result in organisms being better adapted to their living conditions become more common in descendant populations. These differences accumulate resulting in changes within the population. This process is responsible for the many diverse life forms in the world. The modern understanding of evolution began with the 1859 publication of Charles Darwin's "On the Origin of Species". In addition, Gregor Mendel's work with plants helped to explain the hereditary patterns of genetics. Fossil discoveries in palaeontology, advances in population genetics and a global network of scientific research have provided further details into the mechanisms of evolution. Scientists now have a good understanding of the origin of new species (speciation) and have observed the speciation process in the laboratory and in the wild. Evolution is the principal scientific theory that biologists use to understand life and is used in many disciplines, including medicine, psychology, conservation biology, anthropology, forensics, agriculture and other social-cultural applications. The main ideas of evolution may be summarised as follows: In the 19th century, natural history collections and museums were popular

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Introduction to evolution

Introduction to evolution The European expansion and naval expeditions employed naturalists, while curators of grand museums showcased preserved and live specimens of the varieties of life. Charles Darwin was an English graduate educated and trained in the disciplines of natural history. Such natural historians would collect, catalogue, describe and study the vast collections of specimens stored and managed by curators at these museums. Darwin served as a ship's naturalist on board HMS "Beagle", assigned to a five-year research expedition around the world. During his voyage, he observed and collected an abundance of organisms, being very interested in the diverse forms of life along the coasts of South America and the neighbouring Galápagos Islands. Darwin gained extensive experience as he collected and studied the natural history of life forms from distant places. Through his studies, he formulated the idea that each species had developed from ancestors with similar features. In 1838, he described how a process he called natural selection would make this happen. The size of a population depends on how much and how many resources are able to support it. For the population to remain the same size year after year, there must be an equilibrium, or balance between the population size and available resources. Since organisms produce more offspring than their environment can support, not all individuals can survive out of each generation. There must be a competitive struggle for resources that aid in survival

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Introduction to evolution

Introduction to evolution As a result, Darwin realised that it was not chance alone that determined survival. Instead, survival of an organism depends on the differences of each individual organism, or "traits," that aid or hinder survival and reproduction. Well-adapted individuals are likely to leave more offspring than their less well-adapted competitors. Traits that hinder survival and reproduction would "disappear" over generations. Traits that help an organism survive and reproduce would "accumulate" over generations. Darwin realised that the unequal ability of individuals to survive and reproduce could cause gradual changes in the population and used the term "natural selection" to describe this process. Observations of variations in animals and plants formed the basis of the theory of natural selection. For example, Darwin observed that orchids and insects have a close relationship that allows the pollination of the plants. He noted that orchids have a variety of structures that attract insects, so that pollen from the flowers gets stuck to the insects' bodies. In this way, insects transport the pollen from a male to a female orchid. In spite of the elaborate appearance of orchids, these specialised parts are made from the same basic structures that make up other flowers. In his book, "Fertilisation of Orchids" (1862), Darwin proposed that the orchid flowers were adapted from pre-existing parts, through natural selection

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Introduction to evolution

Introduction to evolution Darwin was still researching and experimenting with his ideas on natural selection when he received a letter from Alfred Russel Wallace describing a theory very similar to his own. This led to an immediate joint publication of both theories. Both Wallace and Darwin saw the history of life like a family tree, with each fork in the tree's limbs being a common ancestor. The tips of the limbs represented modern species and the branches represented the common ancestors that are shared amongst many different species. To explain these relationships, Darwin said that all living things were related, and this meant that all life must be descended from a few forms, or even from a single common ancestor. He called this process "descent with modification". Darwin published his theory of evolution by natural selection in "On the Origin of Species" in 1859. His theory means that all life, including humanity, is a product of continuing natural processes. The implication that all life on Earth has a common ancestor has met with objections from some religious groups. Their objections are in contrast to the level of support for the theory by more than 99 percent of those within the scientific community today. Natural selection is commonly equated with "survival of the fittest", but this expression originated in Herbert Spencer's "Principles of Biology" in 1864, five years after Charles Darwin published his original works

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Introduction to evolution

Introduction to evolution "Survival of the fittest" describes the process of natural selection incorrectly, because natural selection is not only about survival and it is not always the fittest that survives. Darwin's theory of natural selection laid the groundwork for modern evolutionary theory, and his experiments and observations showed that the organisms in populations varied from each other, that some of these variations were inherited, and that these differences could be acted on by natural selection. However, he could not explain the source of these variations. Like many of his predecessors, Darwin mistakenly thought that heritable traits were a product of use and disuse, and that features acquired during an organism's lifetime could be passed on to its offspring. He looked for examples, such as large ground feeding birds getting stronger legs through exercise, and weaker wings from not flying until, like the ostrich, they could not fly at all. This misunderstanding was called the inheritance of acquired characters and was part of the theory of transmutation of species put forward in 1809 by Jean-Baptiste Lamarck. In the late 19th century this theory became known as Lamarckism. Darwin produced an unsuccessful theory he called pangenesis to try to explain how acquired characteristics could be inherited. In the 1880s August Weismann's experiments indicated that changes from use and disuse could not be inherited, and Lamarckism gradually fell from favour

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Introduction to evolution

Introduction to evolution The missing information needed to help explain how new features could pass from a parent to its offspring was provided by the pioneering genetics work of Gregor Mendel. Mendel's experiments with several generations of pea plants demonstrated that inheritance works by separating and reshuffling hereditary information during the formation of sex cells and recombining that information during fertilisation. This is like mixing different hands of playing cards, with an organism getting a random mix of half of the cards from one parent, and half of the cards from the other. Mendel called the information "factors"; however, they later became known as genes. Genes are the basic units of heredity in living organisms. They contain the information that directs the physical development and behaviour of organisms. Genes are made of DNA. DNA is a long molecule made up of individual molecules called nucleotides. Genetic information is encoded in the sequence of nucleotides, that make up the DNA, just as the sequence of the letters in words carries information on a page. The genes are like short instructions built up of the "letters" of the DNA alphabet. Put together, the entire set of these genes gives enough information to serve as an "instruction manual" of how to build and run an organism. The instructions spelled out by this DNA alphabet can be changed, however, by mutations, and this may alter the instructions carried within the genes

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Introduction to evolution

Introduction to evolution Within the cell, the genes are carried in chromosomes, which are packages for carrying the DNA. It is the reshuffling of the chromosomes that results in unique combinations of genes in offspring. Since genes interact with one another during the development of an organism, novel combinations of genes produced by sexual reproduction can increase the genetic variability of the population even without new mutations. The genetic variability of a population can also increase when members of that population interbreed with individuals from a different population causing gene flow between the populations. This can introduce genes into a population that were not present before. Evolution is not a random process. Although mutations in DNA are random, natural selection is not a process of chance: the environment determines the probability of reproductive success. Evolution is an inevitable result of imperfectly copying, self-replicating organisms reproducing over billions of years under the selective pressure of the environment. The outcome of evolution is not a perfectly designed organism. The end products of natural selection are organisms that are adapted to their present environments. Natural selection does not involve progress towards an ultimate goal. Evolution does not strive for more advanced, more intelligent, or more sophisticated life forms

Biology

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Introduction to evolution

Introduction to evolution For example, fleas (wingless parasites) are descended from a winged, ancestral scorpionfly, and snakes are lizards that no longer require limbs—although pythons still grow tiny structures that are the remains of their ancestor's hind legs. Organisms are merely the outcome of variations that succeed or fail, dependent upon the environmental conditions at the time. Rapid environmental changes typically cause extinctions. Of all species that have existed on Earth, 99.9 percent are now extinct. Since life began on Earth, five major mass extinctions have led to large and sudden drops in the variety of species. The most recent, the Cretaceous–Paleogene extinction event, occurred 66 million years ago. Genetic drift is a cause of allelic frequency change within populations of a species. Alleles are different variations of specific genes. They determine things like hair colour, skin tone, eye colour and blood type; in other words, all the genetic traits that vary between individuals. Genetic drift does not introduce new alleles to a population, but it can reduce variation within a population by removing an allele from the gene pool. Genetic drift is caused by random sampling of alleles. A truly random sample is a sample in which no outside forces affect what is selected. It is like pulling marbles of the same size and weight but of different colours from a brown paper bag

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Introduction to evolution

Introduction to evolution In any offspring, the alleles present are samples of the previous generations alleles, and chance plays a role in whether an individual survives to reproduce and to pass a sample of their generation onward to the next. The allelic frequency of a population is the ratio of the copies of one specific allele that share the same form compared to the number of all forms of the allele present in the population. Genetic drift affects smaller populations more than it affects larger populations. The Hardy–Weinberg principle states that under certain idealised conditions, including the absence of selection pressures, a large population will have no change in the frequency of alleles as generations pass. A population that satisfies these conditions is said to be in Hardy–Weinberg equilibrium. In particular, Hardy and Weinberg showed that dominant and recessive alleles do not automatically tend to become more and less frequent respectively, as had been thought previously. The conditions for Hardy-Weinberg equilibrium include that there must be no mutations, immigration, or emigration, all of which can directly change allelic frequencies. Additionally, mating must be totally random, with all males (or females in some cases) being equally desirable mates. This ensures a true random mixing of alleles. A population that is in Hardy–Weinberg equilibrium is analogous to a deck of cards; no matter how many times the deck is shuffled, no new cards are added and no old ones are taken away

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Introduction to evolution

Introduction to evolution Cards in the deck represent alleles in a population's gene pool. In practice, no population can be in perfect Hardy-Weinberg equilibrium. The population's finite size, combined with natural selection and many other effects, cause the allelic frequencies to change over time. A population bottleneck occurs when the population of a species is reduced drastically over a short period of time due to external forces. In a true population bottleneck, the reduction does not favour any combination of alleles; it is totally random chance which individuals survive. A bottleneck can reduce or eliminate genetic variation from a population. Further drift events after the bottleneck event can also reduce the population's genetic diversity. The lack of diversity created can make the population at risk to other selective pressures. A common example of a population bottleneck is the Northern elephant seal. Due to excessive hunting throughout the 19th century, the population of the northern elephant seal was reduced to 30 individuals or less. They have made a full recovery, with the total number of individuals at around 100,000 and growing. The effects of the bottleneck are visible, however. The seals are more likely to have serious problems with disease or genetic disorders, because there is almost no diversity in the population. The founder effect occurs when a small group from one population splits off and forms a new population, often through geographic isolation

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Introduction to evolution

Introduction to evolution This new population's allelic frequency is probably different from the original population's, and will change how common certain alleles are in the populations. The founders of the population will determine the genetic makeup, and potentially the survival, of the new population for generations. One example of the founder effect is found in the Amish migration to Pennsylvania in 1744. Two of the founders of the colony in Pennsylvania carried the recessive allele for Ellis–van Creveld syndrome. Because the Amish tend to be religious isolates, they interbreed, and through generations of this practice the frequency of Ellis–van Creveld syndrome in the Amish people is much higher than the frequency in the general population. The modern evolutionary synthesis is based on the concept that populations of organisms have significant genetic variation caused by mutation and by the recombination of genes during sexual reproduction. It defines evolution as the change in allelic frequencies within a population caused by genetic drift, gene flow between sub populations, and natural selection. Natural selection is emphasised as the most important mechanism of evolution; large changes are the result of the gradual accumulation of small changes over long periods of time. The modern evolutionary synthesis is the outcome of a merger of several different scientific fields to produce a more cohesive understanding of evolutionary theory. In the 1920s, Ronald Fisher, J.B.S

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Introduction to evolution

Introduction to evolution Haldane and Sewall Wright combined Darwin's theory of natural selection with statistical models of Mendelian genetics, founding the discipline of population genetics. In the 1930s and 1940s, efforts were made to merge population genetics, the observations of field naturalists on the distribution of species and sub species, and analysis of the fossil record into a unified explanatory model. The application of the principles of genetics to naturally occurring populations, by scientists such as Theodosius Dobzhansky and Ernst Mayr, advanced the understanding of the processes of evolution. Dobzhansky's 1937 work "Genetics and the Origin of Species" helped bridge the gap between genetics and field biology by presenting the mathematical work of the population geneticists in a form more useful to field biologists, and by showing that wild populations had much more genetic variability with geographically isolated subspecies and reservoirs of genetic diversity in recessive genes than the models of the early population geneticists had allowed for. Mayr, on the basis of an understanding of genes and direct observations of evolutionary processes from field research, introduced the biological species concept, which defined a species as a group of interbreeding or potentially interbreeding populations that are reproductively isolated from all other populations. Both Dobzhansky and Mayr emphasised the importance of subspecies reproductively isolated by geographical barriers in the emergence of new species

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Introduction to evolution

Introduction to evolution The palaeontologist George Gaylord Simpson helped to incorporate palaeontology with a statistical analysis of the fossil record that showed a pattern consistent with the branching and non-directional pathway of evolution of organisms predicted by the modern synthesis. Scientific evidence for evolution comes from many aspects of biology and includes fossils, homologous structures, and molecular similarities between species' DNA. Research in the field of palaeontology, the study of fossils, supports the idea that all living organisms are related. Fossils provide evidence that accumulated changes in organisms over long periods of time have led to the diverse forms of life we see today. A fossil itself reveals the organism's structure and the relationships between present and extinct species, allowing palaeontologists to construct a family tree for all of the life forms on Earth. Modern palaeontology began with the work of Georges Cuvier. Cuvier noted that, in sedimentary rock, each layer contained a specific group of fossils. The deeper layers, which he proposed to be older, contained simpler life forms. He noted that many forms of life from the past are no longer present today. One of Cuvier's successful contributions to the understanding of the fossil record was establishing extinction as a fact

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Introduction to evolution

Introduction to evolution In an attempt to explain extinction, Cuvier proposed the idea of "revolutions" or catastrophism in which he speculated that geological catastrophes had occurred throughout the Earth's history, wiping out large numbers of species. Cuvier's theory of revolutions was later replaced by uniformitarian theories, notably those of James Hutton and Charles Lyell who proposed that the Earth's geological changes were gradual and consistent. However, current evidence in the fossil record supports the concept of mass extinctions. As a result, the general idea of catastrophism has re-emerged as a valid hypothesis for at least some of the rapid changes in life forms that appear in the fossil records. A very large number of fossils have now been discovered and identified. These fossils serve as a chronological record of evolution. The fossil record provides examples of transitional species that demonstrate ancestral links between past and present life forms. One such transitional fossil is "Archaeopteryx", an ancient organism that had the distinct characteristics of a reptile (such as a long, bony tail and conical teeth) yet also had characteristics of birds (such as feathers and a wishbone). The implication from such a find is that modern reptiles and birds arose from a common ancestor. The comparison of similarities between organisms of their form or appearance of parts, called their morphology, has long been a way to classify life into closely related groups

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Introduction to evolution

Introduction to evolution This can be done by comparing the structure of adult organisms in different species or by comparing the patterns of how cells grow, divide and even migrate during an organism's development. Taxonomy is the branch of biology that names and classifies all living things. Scientists use morphological and genetic similarities to assist them in categorising life forms based on ancestral relationships. For example, orangutans, gorillas, chimpanzees and humans all belong to the same taxonomic grouping referred to as a family—in this case the family called Hominidae. These animals are grouped together because of similarities in morphology that come from common ancestry (called "homology"). Strong evidence for evolution comes from the analysis of homologous structures: structures in different species that no longer perform the same task but which share a similar structure. Such is the case of the forelimbs of mammals. The forelimbs of a human, cat, whale, and bat all have strikingly similar bone structures. However, each of these four species' forelimbs performs a different task. The same bones that construct a bat's wings, which are used for flight, also construct a whale's flippers, which are used for swimming. Such a "design" makes little sense if they are unrelated and uniquely constructed for their particular tasks. The theory of evolution explains these homologous structures: all four animals shared a common ancestor, and each has undergone change over many generations

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Introduction to evolution

Introduction to evolution These changes in structure have produced forelimbs adapted for different tasks. However, anatomical comparisons can be misleading, as not all anatomical similarities indicate a close relationship. Organisms that share similar environments will often develop similar physical features, a process known as "convergent evolution". Both sharks and dolphins have similar body forms, yet are only distantly related—sharks are fish and dolphins are mammals. Such similarities are a result of both populations being exposed to the same selective pressures. Within both groups, changes that aid swimming have been favoured. Thus, over time, they developed similar appearances (morphology), even though they are not closely related. In some cases, anatomical comparison of structures in the embryos of two or more species provides evidence for a shared ancestor that may not be obvious in the adult forms. As the embryo develops, these homologies can be lost to view, and the structures can take on different functions. Part of the basis of classifying the vertebrate group (which includes humans), is the presence of a tail (extending beyond the anus) and pharyngeal slits. Both structures appear during some stage of embryonic development but are not always obvious in the adult form. Because of the morphological similarities present in embryos of different species during development, it was once assumed that organisms re-enact their evolutionary history as an embryo

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Introduction to evolution

Introduction to evolution It was thought that human embryos passed through an amphibian then a reptilian stage before completing their development as mammals. Such a re-enactment, often called "recapitulation theory", is not supported by scientific evidence. What does occur, however, is that the first stages of development are similar in broad groups of organisms. At very early stages, for instance, all vertebrates appear extremely similar, but do not exactly resemble any ancestral species. As development continues, specific features emerge from this basic pattern. Homology includes a unique group of shared structures referred to as "vestigial structures". "Vestigial" refers to anatomical parts that are of minimal, if any, value to the organism that possesses them. These apparently illogical structures are remnants of organs that played an important role in ancestral forms. Such is the case in whales, which have small vestigial bones that appear to be remnants of the leg bones of their ancestors which walked on land. Humans also have vestigial structures, including the ear muscles, the wisdom teeth, the appendix, the tail bone, body hair (including goose bumps), and the semilunar fold in the corner of the eye. Biogeography is the study of the geographical distribution of species. Evidence from biogeography, especially from the biogeography of oceanic islands, played a key role in convincing both Darwin and Alfred Russel Wallace that species evolved with a branching pattern of common descent

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Introduction to evolution

Introduction to evolution Islands often contain endemic species, species not found anywhere else, but those species are often related to species found on the nearest continent. Furthermore, islands often contain clusters of closely related species that have very different ecological niches, that is have different ways of making a living in the environment. Such clusters form through a process of adaptive radiation where a single ancestral species colonises an island that has a variety of open ecological niches and then diversifies by evolving into different species adapted to fill those empty niches. Well-studied examples include Darwin's finches, a group of 13 finch species endemic to the Galápagos Islands, and the Hawaiian honeycreepers, a group of birds that once, before extinctions caused by humans, numbered 60 species filling diverse ecological roles, all descended from a single finch like ancestor that arrived on the Hawaiian Islands some 4 million years ago. Another example is the Silversword alliance, a group of perennial plant species, also endemic to the Hawaiian Islands, that inhabit a variety of habitats and come in a variety of shapes and sizes that include trees, shrubs, and ground hugging mats, but which can be hybridised with one another and with certain tarweed species found on the west coast of North America; it appears that one of those tarweeds colonised Hawaii in the past, and gave rise to the entire Silversword alliance

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Introduction to evolution

Introduction to evolution Every living organism (with the possible exception of RNA viruses) contains molecules of DNA, which carries genetic information. Genes are the pieces of DNA that carry this information, and they influence the properties of an organism. Genes determine an individual's general appearance and to some extent their behaviour. If two organisms are closely related, their DNA will be very similar. On the other hand, the more distantly related two organisms are, the more differences they will have. For example, brothers are closely related and have very similar DNA, while cousins share a more distant relationship and have far more differences in their DNA. Similarities in DNA are used to determine the relationships between species in much the same manner as they are used to show relationships between individuals. For example, comparing chimpanzees with gorillas and humans shows that there is as much as a 96 percent similarity between the DNA of humans and chimps. Comparisons of DNA indicate that humans and chimpanzees are more closely related to each other than either species is to gorillas. The field of molecular systematics focuses on measuring the similarities in these molecules and using this information to work out how different types of organisms are related through evolution. These comparisons have allowed biologists to build a "relationship tree" of the evolution of life on Earth

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Introduction to evolution

Introduction to evolution They have even allowed scientists to unravel the relationships between organisms whose common ancestors lived such a long time ago that no real similarities remain in the appearance of the organisms. "Artificial selection" is the controlled breeding of domestic plants and animals. Humans determine which animal or plant will reproduce and which of the offspring will survive; thus, they determine which genes will be passed on to future generations. The process of artificial selection has had a significant impact on the evolution of domestic animals. For example, people have produced different types of dogs by controlled breeding. The differences in size between the Chihuahua and the Great Dane are the result of artificial selection. Despite their dramatically different physical appearance, they and all other dogs evolved from a few wolves domesticated by humans in what is now China less than 15,000 years ago. Artificial selection has produced a wide variety of plants. In the case of maize (corn), recent genetic evidence suggests that domestication occurred 10,000 years ago in central Mexico. Prior to domestication, the edible portion of the wild form was small and difficult to collect. Today "The Maize Genetics Cooperation • Stock Center" maintains a collection of more than 10,000 genetic variations of maize that have arisen by random mutations and chromosomal variations from the original wild type

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Introduction to evolution

Introduction to evolution In artificial selection the new breed or variety that emerges is the one with random mutations attractive to humans, while in natural selection the surviving species is the one with random mutations useful to it in its non-human environment. In both natural and artificial selection the variations are a result of random mutations, and the underlying genetic processes are essentially the same. Darwin carefully observed the outcomes of artificial selection in animals and plants to form many of his arguments in support of natural selection. Much of his book "On the Origin of Species" was based on these observations of the many varieties of domestic pigeons arising from artificial selection. Darwin proposed that if humans could achieve dramatic changes in domestic animals in short periods, then natural selection, given millions of years, could produce the differences seen in living things today. Coevolution is a process in which two or more species influence the evolution of each other. All organisms are influenced by life around them; however, in coevolution there is evidence that genetically determined traits in each species directly resulted from the interaction between the two organisms. An extensively documented case of coevolution is the relationship between "Pseudomyrmex", a type of ant, and the "acacia", a plant that the ant uses for food and shelter. The relationship between the two is so intimate that it has led to the evolution of special structures and behaviours in both organisms

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Introduction to evolution

Introduction to evolution The ant defends the acacia against herbivores and clears the forest floor of the seeds from competing plants. In response, the plant has evolved swollen thorns that the ants use as shelter and special flower parts that the ants eat. Such coevolution does not imply that the ants and the tree choose to behave in an altruistic manner. Rather, across a population small genetic changes in both ant and tree benefited each. The benefit gave a slightly higher chance of the characteristic being passed on to the next generation. Over time, successive mutations created the relationship we observe today. Given the right circumstances, and enough time, evolution leads to the emergence of new species. Scientists have struggled to find a precise and all-inclusive definition of "species". Ernst Mayr defined a species as a population or group of populations whose members have the potential to interbreed naturally with one another to produce viable, fertile offspring. (The members of a species cannot produce viable, fertile offspring with members of "other" species). Mayr's definition has gained wide acceptance among biologists, but does not apply to organisms such as bacteria, which reproduce asexually. Speciation is the lineage-splitting event that results in two separate species forming from a single common ancestral population. A widely accepted method of speciation is called "allopatric speciation". Allopatric speciation begins when a population becomes geographically separated

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Introduction to evolution

Introduction to evolution Geological processes, such as the emergence of mountain ranges, the formation of canyons, or the flooding of land bridges by changes in sea level may result in separate populations. For speciation to occur, separation must be substantial, so that genetic exchange between the two populations is completely disrupted. In their separate environments, the genetically isolated groups follow their own unique evolutionary pathways. Each group will accumulate different mutations as well as be subjected to different selective pressures. The accumulated genetic changes may result in separated populations that can no longer interbreed if they are reunited. Barriers that prevent interbreeding are either "prezygotic" (prevent mating or fertilisation) or "postzygotic" (barriers that occur after fertilisation). If interbreeding is no longer possible, then they will be considered different species. The result of four billion years of evolution is the diversity of life around us, with an estimated 1.75 million different species in existence today. Usually the process of speciation is slow, occurring over very long time spans; thus direct observations within human life-spans are rare. However speciation has been observed in present-day organisms, and past speciation events are recorded in fossils. Scientists have documented the formation of five new species of cichlid fishes from a single common ancestor that was isolated fewer than 5,000 years ago from the parent stock in Lake Nagubago

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Introduction to evolution

Introduction to evolution The evidence for speciation in this case was morphology (physical appearance) and lack of natural interbreeding. These fish have complex mating rituals and a variety of colorations; the slight modifications introduced in the new species have changed the mate selection process and the five forms that arose could not be convinced to interbreed. The theory of evolution is widely accepted among the scientific community, serving to link the diverse speciality areas of biology. Evolution provides the field of biology with a solid scientific base. The significance of evolutionary theory is summarised by Theodosius Dobzhansky as "nothing in biology makes sense except in the light of evolution." Nevertheless, the theory of evolution is not static. There is much discussion within the scientific community concerning the mechanisms behind the evolutionary process. For example, the rate at which evolution occurs is still under discussion. In addition, there are conflicting opinions as to which is the primary unit of evolutionary change—the organism or the gene. Darwin and his contemporaries viewed evolution as a slow and gradual process. Evolutionary trees are based on the idea that profound differences in species are the result of many small changes that accumulate over long periods. Gradualism had its basis in the works of the geologists James Hutton and Charles Lyell

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Introduction to evolution

Introduction to evolution Hutton's view suggests that profound geological change was the cumulative product of a relatively slow continuing operation of processes which can still be seen in operation today, as opposed to catastrophism which promoted the idea that sudden changes had causes which can no longer be seen at work. A uniformitarian perspective was adopted for biological changes. Such a view can seem to contradict the fossil record, which often shows evidence of new species appearing suddenly, then persisting in that form for long periods. In the 1970s palaeontologists Niles Eldredge and Stephen Jay Gould developed a theoretical model that suggests that evolution, although a slow process in human terms, undergoes periods of relatively rapid change (ranging between 50,000 and 100,000 years) alternating with long periods of relative stability. Their theory is called "punctuated equilibrium" and explains the fossil record without contradicting Darwin's ideas. A common unit of selection in evolution is the organism. Natural selection occurs when the reproductive success of an individual is improved or reduced by an inherited characteristic, and reproductive success is measured by the number of an individual's surviving offspring. The organism view has been challenged by a variety of biologists as well as philosophers. Richard Dawkins proposes that much insight can be gained if we look at evolution from the gene's point of view; that is, that natural selection operates as an evolutionary mechanism on genes as well as organisms

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Introduction to evolution

Introduction to evolution In his 1976 book, "The Selfish Gene", he explains: Others view selection working on many levels, not just at a single level of organism or gene; for example, Stephen Jay Gould called for a hierarchical perspective on selection.

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Introduction to evolution

Vredefort crater The is the largest verified impact crater on Earth. More than across when it was formed, what remains of it is in the present-day Free State province of South Africa. It is named after the town of Vredefort, which is near its centre. Although the crater itself has long since been eroded away, the remaining geological structures at its centre are known as the Vredefort Dome or Vredefort impact structure. The crater is calculated to be 2.023 billion years old (± 4 million years), with impact being in the Paleoproterozoic Era. It is the third-oldest known crater on Earth. In 2005, the Vredefort Dome was added to the list of UNESCO World Heritage sites for its geologic interest. The asteroid that hit Vredefort is estimated to have been one of the largest ever to strike Earth (at least since the Hadean Eon some four billion years ago), thought to have been approximately in diameter. The bolide that created the Sudbury Basin could have been even larger. The original crater is estimated to have had a diameter of roughly , but that has been eroded. It would have been larger than the Sudbury Basin and the Chicxulub crater. The remaining structure, the "Vredefort Dome", consists of a partial ring of hills in diameter, and is the remains of a dome created by the rebound of rock below the impact site after the collision. The crater's age is estimated to be 2.023 billion years (± 4 million years), which places it in the Paleoproterozoic Era

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Vredefort crater

Vredefort crater It is the second-oldest known crater on Earth, a little less than 300 million years younger than the Suavjärvi crater in Russia. In comparison, it is about 10% older than the Sudbury Basin impact (at 1.849 billion years). The dome in the centre of the crater was originally thought to have been formed by a volcanic explosion, but in the mid-1990s, evidence revealed it was the site of a huge bolide impact, as telltale shatter cones were discovered in the bed of the nearby Vaal River. The crater site is one of the few multiple-ringed impact craters on Earth, although they are more common elsewhere in the Solar System. Perhaps the best-known example is Valhalla crater on Jupiter's moon Callisto. Earth's Moon has some as well. Geological processes, such as erosion and plate tectonics, have destroyed most multiple-ring craters on Earth. The impact distorted the Witwatersrand Basin which was laid down over a period of 250 million years between 950 and 700 million years before the Vredefort impact. The overlying Ventersdorp lavas and the Transvaal Supergroup which were laid down between 700 and 80 million years before the meteorite strike, were similarly distorted by the formation of the crater. The rocks form partial concentric rings around the crater centre today, with the oldest, the Witwatersrand rocks, forming a semicircle from the centre. Since the Witwatersrand rocks consist of several layers of very hard, erosion-resistant sediments (e.g

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Vredefort crater

Vredefort crater quartzites and banded ironstones), they form the prominent arc of hills that can be seen to the northwest of the crater centre in the satellite picture above. The Witwatersrand rocks are followed, in succession, by the Ventersdorp lavas at a distance of about from the centre, and the Transvaal Supergroup, consisting of a narrow band of the Ghaap Dolomite rocks and the Pretoria Subgroup of rocks, which together form a band beyond that. From about halfway through the Pretoria Subgroup of rocks around the crater centre, the order of the rocks is reversed. Moving outwards towards where the crater rim used to be, the Ghaap Dolomite group resurfaces at from the centre, followed by an arc of Ventersdorp lavas, beyond which, at between from the centre, the Witwatersrand rocks re-emerge to form an interrupted arc of outcrops today. The Johannesburg group is the most famous one because it was here that gold was discovered in 1886. It is thus possible that if it had not been for the Vredefort impact this gold would never have been discovered. The centre of the consists of a granite dome (where it is not covered by much younger rocks belonging to the Karoo Supergroup) which is an exposed part of the Kaapvaal craton, one of the oldest microcontinents which formed on Earth 3.9 billion years ago. This central peak uplift, or dome, is typical of a complex impact crater, where the liquefied rocks splashed up in the wake of the meteor as it penetrated the surface

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Vredefort crater

Vredefort crater The Vredefort Dome World Heritage Site is currently subject to property development, and local owners have expressed concern regarding sewage dumping into the Vaal River and the crater site. The granting of prospecting rights around the edges of the crater has led environmental interests to express fear of destructive mining. The Vredefort Dome in the centre of the crater is home to four towns: Parys, Vredefort, Koppies and Venterskroon. Parys is the largest and a tourist hub; both Vredefort and Koppies mainly depend on an agricultural economy. On 19 December 2011, a broadcasting license was granted by ICASA to a community radio station to broadcast for the Afrikaans- and English-speaking members of the communities within the crater. The Afrikaans name "Koepel" Stereo (Dome Stereo) refers to the dome and announces its broadcast as KSFM. The station broadcasts on 94.9 MHz FM.

Biology

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Vredefort crater

Supertoys Last All Summer Long "Supertoys Last All Summer Long" is a science fiction short story by Brian Aldiss, first published in UK edition of "Harper's Bazaar", in December 1969 issue. The story deals with humanity in an age of intelligent machines and of the aching loneliness endemic in an overpopulated future where child creation is controlled. In a dystopian future where only 1/4th of the world's overcrowded population is fed and living comfortably, families must request permission to bear children. Monica Swinton lives with her husband Henry and her young son David, whom she struggles to bond with. She seeks help from Teddy, a robot toy companion of sorts, to try to understand why she feels unable to communicate with David, let alone feel compassion for him. David also questions Teddy about whether his mother truly loves him and wonders whether he is truly real. He attempts to write letters of his own to explain how he feels about his mother and the inner conflict he faces but all of his letters remain unfinished. Meanwhile, the story jumps to Henry Swinton who is in a meeting with a company he is associated with known as Synthank. They are discussing artificial life forms and bio-electronic beings for future developments. He discusses that the new AI under production will finally solve humanity's problems with experiencing personal isolation and loneliness

Biology

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Supertoys Last All Summer Long

Supertoys Last All Summer Long Monica Swinton discovers David's unfinished letters that portray lines about love and a jealous contempt for Teddy, whom Monica always seemed to connect with more than David himself. Monica is horrified by the letters but overjoyed when Henry arrives home and she is able to share with him that the family has been chosen to give birth to a child by the Ministry of Population. It is then revealed that David is an artificial human, used as a replacement for a real child. Monica privately tells Henry that David is having verbal "malfunctioning" problems and must be sent back to the factory at once. The story ends with David thinking of the love and warmth of his mother, unaware of what's to happen next. The short story was used as the basis for the first act of the feature film "A.I. Artificial Intelligence" (2001). Stanley Kubrick originally obtained the rights in the 1970s to produce a film adaptation. However, the project was bogged down in development hell and was repeatedly postponed. After Kubrick died in 1999, his wife asked Steven Spielberg to direct and complete the film, which was released in 2001. In the same year, the short story was re-published in the eponymous Aldiss short-story collection "and Other Stories of Future Time", along with the tie-in stories "Supertoys When Winter Comes" and "Supertoys in Other Seasons". The collection also contained a number of stories not tied to the Supertoys theme

Biology

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Supertoys Last All Summer Long

Supertoys Last All Summer Long Monica Swinton: A troubled, lonely woman and less-than-compassionate mother, Monica struggles to understand her A.I. son David. Throughout the story, she seeks a way to communicate with him and understand him. While Monica may appear selfish in the beginning as it is admitted that she is unable to love David, she is simply unable to feel love for a child that is not truly her own. Monica enjoys gardening and experiencing only the beautiful and serene parts of life which suggests she is unable to cope with a reality that doesn't appear perfect. This may be why she is unable to love David, as she is unable to accept that he is not her own, born child. Monica seeks comfort and connection in Teddy, David's robot toy companion. It would appear that she cares for this logical, basic A.I. toy more than David, but her exact feelings for Teddy remain questionable. She's portrayed by Frances O'Connor in the movie adaptation. David Swinton: The A.I. son of Monica and Henry Swinton. David struggles to feel accepted and loved by his mother, and rightly so, as she is devoid of most feelings for him. David's personality is similar to that of an average 5- to 10-year-old boy, as he is curious, slightly mischievous, and very loving towards Monica. Although David sees Teddy as a companion, he is also jealous that he is treated more as a son than David himself is. It is difficult to say how much of David's "feelings" are programmed, but the questioning of his own reality defines the character as more than an average android

Biology

https://en.wikipedia.org/wiki?curid=3835922

Supertoys Last All Summer Long

Supertoys Last All Summer Long He's portrayed by Haley Joel Osment in the movie adaptation. Henry Swinton: The husband of Monica Swinton and father to David. Little is known about this character other than that he works for a company called "Synthank" and helps to develop bio-electronic and bioengineered creations. His character appears somewhat distant from Monica, as she doesn't accompany him to the important meeting he attends in the story. However, little is known about his relationship with David and whether he shares the detachment issues Monica experiences. He's portrayed by Sam Robards in the movie adaptation. Teddy: David's robot toy companion. He is unable to tell lies and helps to guide both David and Monica, despite not understanding either of their situations. His knowledge is limited and his personality is simplistic, but Monica finds Teddy easier to communicate with than David. This could be for a number of reasons, including the possibility that Monica is not used to dealing with a robot that acts human, and Teddy does not provide this feature. He only speaks when spoken to, and seeks to comfort always. He's voiced by Jack Angel in the movie adaptation.

Biology

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Supertoys Last All Summer Long

Phytogeography (from Greek φυτόν, "phytón" = "plant" and γεωγραφία, "geographía" = "geography" meaning also distribution) or botanical geography is the branch of biogeography that is concerned with the geographic distribution of plant species and their influence on the earth's surface. is concerned with all aspects of plant distribution, from the controls on the distribution of individual species ranges (at both large and small scales, see species distribution) to the factors that govern the composition of entire communities and floras. Geobotany, by contrast, focuses on the geographic space's influence on plants. is part of a more general science known as biogeography. Phytogeographers are concerned with patterns and process in plant distribution. Most of the major questions and kinds of approaches taken to answer such questions are held in common between phyto- and zoogeographers. in wider sense (or geobotany, in German literature) encompasses four fields, according with the focused aspect, environment, flora (taxa), vegetation (plant community) and origin, respectively: is often divided into two main branches: ecological phytogeography and historical phytogeography. The former investigates the role of current day biotic and abiotic interactions in influencing plant distributions; the latter are concerned with historical reconstruction of the origin, dispersal, and extinction of taxa

Biology

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Phytogeography

Phytogeography The basic data elements of phytogeography are occurrence records (presence or absence of a species) with operational geographic units such as political units or geographical coordinates. These data are often used to construct phytogeographic provinces (floristic provinces) and elements. The questions and approaches in phytogeography are largely shared with zoogeography, except zoogeography is concerned with animal distribution rather than plant distribution. The term phytogeography itself suggests a broad meaning. How the term is actually applied by practicing scientists is apparent in the way periodicals use the term. The "American Journal of Botany", a monthly primary research journal, frequently publishes a section titled "Systematics, Phytogeography, and Evolution." Topics covered in the "American Journal of Botany"'s "Systematics and Phytogeography" section include phylogeography, distribution of genetic variation and, historical biogeography, and general plant species distribution patterns. Biodiversity patterns are not heavily covered. A flora is the group of all plant species in a specific period of time or area, in which each species is independent in abundance and relationships to the other species. The group or the flora can be assembled in accordance with floral element, which are based on common features. A flora element can be a genetic element, in which the group of species share similar genetic information i.e

Biology

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Phytogeography

Phytogeography common evolutionary origin; a migration element has a common route of access into a habitat; a historical element is similar to each other in certain past events and an ecological element is grouped based on similar environmental factors. A population is the collection of all interacting individuals of a given species, in an area. An area is the entire location where a species, an element or an entire flora can occur. Aerography studies the description of that area, chorology studies their development. The local distribution within the area as a whole, as that of a swamp shrub, is the topography of that area. Areas are an important factor is forming an image about how species interaction result in their geography. The nature of an area’s margin, their continuity, their general shape and size relative to other areas, make the study of area crucial in identifying these types of information. For example, a relict area is an area surviving from an earlier and more exclusive occurrence. Mutually exclusive plants are called vicarious (areas containing such plants are also called vicarious). The earth’s surface is divided into floristic region, each region associated with a distinctive flora. has a long history. One of the subjects earliest proponents was Prussian naturalist Alexander von Humboldt, who is often referred to as the "father of phytogeography". Von Humboldt advocated a quantitative approach to phytogeography that has characterized modern plant geography

Biology

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Phytogeography

Phytogeography Gross patterns of the distribution of plants became apparent early on in the study of plant geography. For example, Alfred Russel Wallace, co-discoverer of the principle of natural selection, discussed the Latitudinal gradients in species diversity, a pattern observed in other organisms as well. Much research effort in plant geography has since then been devoted to understanding this pattern and describing it in more detail. In 1890, the United States Congress passed an act that appropriated funds to send expeditions to discover the geographic distributions of plants (and animals) in the United States. The first of these was The Death Valley Expedition, including Frederick Vernon Coville, Frederick Funston, Clinton Hart Merriam, and others. Research in plant geography has also been directed to understanding the patterns of adaptation of species to the environment. This is done chiefly by describing geographical patterns of trait/environment relationships. These patterns termed ecogeographical rules when applied to plants represent another area of phytogeography. Recently, a new field termed macroecology has developed, which focuses on broad-scale (in both time and space) patterns and phenomena in ecology. Macroecology focuses as much on other organisms as plants. Floristics is a study of the flora of some territory or area. Traditional phytogeography concerns itself largely with floristics and floristic classification, see floristic province

Biology

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Phytogeography

Phytogeography China has been a focus to botanist for its rich biota as it holds the record for the earliest known angiosperm megafossil.

Biology

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Phytogeography

Defense physiology is a term used to refer to the symphony of body function (physiology) changes which occur in response to a stress or threat. When the body executes the "fight-or-flight" reaction or stress response, the nervous system initiates, coordinates and directs specific changes in how the body is functioning (physiology), preparing the body to deal with the threat. (See also General adaptation syndrome.) stress : As it pertains to the term "defense physiology", the term "stress" refers to a "perceived threat" to the continued functioning of the body / life according to its current state. threat : What constitutes a "threat" as it pertains to "defense physiology"? A "threat" may be consciously recognized or not. A physical event (a loud noise or car collision), a chemical or a biological agent which alters (or has the possibility to alter) body function (physiology) away from optimum or healthy functioning (or away from its current state of functioning) may be perceived as a "threat" (also called a stressor). Life circumstances, though posing no immediate physical danger, could be perceived as a threat. Anything that could change the continuing of the person’s life as they are currently experiencing it could be perceived as a "threat". A threat may be either "empirical" (an outside observer may agree that the event or circumstance poses a threat) or "a priori" (an outside observer would not agree that the event or circumstance poses a threat)

Biology

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Defense physiology

Defense physiology What is important to the individual, in terms of the body’s response, is that a threat is perceived. The perception of a "threat" may also trigger an associated ‘feeling of distress’. Physiological reactions triggered by mind cannot differentiate both the physical or mental threat separately, Hence the "fight-or-flight" response of mind for the both reactions will be same. Acute Stress Reaction - The body executes the “Fight-or-flight” reaction to get the body out of danger quickly. When the timing between the "threat" and the resolution of the "threat" are close, the “fight-or-flight" reaction is executed, the "threat" is handled, and the body returns to its previous state (taking care of the business of life - digestion, relaxation, tissue repair etc.). The body has evolved to stay in this mode for only a short time. Chronic Stress State - When the timing between the "threat" and the resolution of the "threat" are more distant (the "threat" or the perception of "threat" is prolonged or other "threats" occur before the body has recovered), the “fight-or-flight" reaction continues and becomes the new ‘standard operating condition’ of the body, chronic Defense Physiology. Continuing in this mode produces significant negative effects (distress) in many aspects of body functioning (physical, mental and emotional distress).

Biology

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Defense physiology

Homology modeling Homology modeling, also known as comparative modeling of protein, refers to constructing an atomic-resolution model of the ""target"" protein from its amino acid sequence and an experimental three-dimensional structure of a related homologous protein (the ""template""). relies on the identification of one or more known protein structures likely to resemble the structure of the query sequence, and on the production of an alignment that maps residues in the query sequence to residues in the template sequence. It has been shown that protein structures are more conserved than protein sequences amongst homologues, but sequences falling below a 20% sequence identity can have very different structure. Evolutionarily related proteins have similar sequences and naturally occurring homologous proteins have similar protein structure. It has been shown that three-dimensional protein structure is evolutionarily more conserved than would be expected on the basis of sequence conservation alone. The sequence alignment and template structure are then used to produce a structural model of the target. Because protein structures are more conserved than DNA sequences, detectable levels of sequence similarity usually imply significant structural similarity. The quality of the homology model is dependent on the quality of the sequence alignment and template structure

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Homology modeling

Homology modeling The approach can be complicated by the presence of alignment gaps (commonly called indels) that indicate a structural region present in the target but not in the template, and by structure gaps in the template that arise from poor resolution in the experimental procedure (usually X-ray crystallography) used to solve the structure. Model quality declines with decreasing sequence identity; a typical model has ~1–2 Å root mean square deviation between the matched C atoms at 70% sequence identity but only 2–4 Å agreement at 25% sequence identity. However, the errors are significantly higher in the loop regions, where the amino acid sequences of the target and template proteins may be completely different. Regions of the model that were constructed without a template, usually by loop modeling, are generally much less accurate than the rest of the model. Errors in side chain packing and position also increase with decreasing identity, and variations in these packing configurations have been suggested as a major reason for poor model quality at low identity. Taken together, these various atomic-position errors are significant and impede the use of homology models for purposes that require atomic-resolution data, such as drug design and protein–protein interaction predictions; even the quaternary structure of a protein may be difficult to predict from homology models of its subunit(s)

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Homology modeling

Homology modeling Nevertheless, homology models can be useful in reaching "qualitative" conclusions about the biochemistry of the query sequence, especially in formulating hypotheses about why certain residues are conserved, which may in turn lead to experiments to test those hypotheses. For example, the spatial arrangement of conserved residues may suggest whether a particular residue is conserved to stabilize the folding, to participate in binding some small molecule, or to foster association with another protein or nucleic acid. can produce high-quality structural models when the target and template are closely related, which has inspired the formation of a structural genomics consortium dedicated to the production of representative experimental structures for all classes of protein folds. The chief inaccuracies in homology modeling, which worsen with lower sequence identity, derive from errors in the initial sequence alignment and from improper template selection. Like other methods of structure prediction, current practice in homology modeling is assessed in a biennial large-scale experiment known as the Critical Assessment of Techniques for Protein Structure Prediction, or CASP. The method of homology modeling is based on the observation that protein tertiary structure is better conserved than amino acid sequence. Thus, even proteins that have diverged appreciably in sequence but still share detectable similarity will also share common structural properties, particularly the overall fold

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Homology modeling

Homology modeling Because it is difficult and time-consuming to obtain experimental structures from methods such as X-ray crystallography and protein NMR for every protein of interest, homology modeling can provide useful structural models for generating hypotheses about a protein's function and directing further experimental work. There are exceptions to the general rule that proteins sharing significant sequence identity will share a fold. For example, a judiciously chosen set of mutations of less than 50% of a protein can cause the protein to adopt a completely different fold. However, such a massive structural rearrangement is unlikely to occur in evolution, especially since the protein is usually under the constraint that it must fold properly and carry out its function in the cell. Consequently, the roughly folded structure of a protein (its "topology") is conserved longer than its amino-acid sequence and much longer than the corresponding DNA sequence; in other words, two proteins may share a similar fold even if their evolutionary relationship is so distant that it cannot be discerned reliably. For comparison, the function of a protein is conserved much "less" than the protein sequence, since relatively few changes in amino-acid sequence are required to take on a related function. The homology modeling procedure can be broken down into four sequential steps: template selection, target-template alignment, model construction, and model assessment

Biology

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Homology modeling

Homology modeling The first two steps are often essentially performed together, as the most common methods of identifying templates rely on the production of sequence alignments; however, these alignments may not be of sufficient quality because database search techniques prioritize speed over alignment quality. These processes can be performed iteratively to improve the quality of the final model, although quality assessments that are not dependent on the true target structure are still under development. Optimizing the speed and accuracy of these steps for use in large-scale automated structure prediction is a key component of structural genomics initiatives, partly because the resulting volume of data will be too large to process manually and partly because the goal of structural genomics requires providing models of reasonable quality to researchers who are not themselves structure prediction experts. The critical first step in homology modeling is the identification of the best template structure, if indeed any are available. The simplest method of template identification relies on serial pairwise sequence alignments aided by database search techniques such as FASTA and BLAST. More sensitive methods based on multiple sequence alignment – of which PSI-BLAST is the most common example – iteratively update their position-specific scoring matrix to successively identify more distantly related homologs

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Homology modeling

Homology modeling This family of methods has been shown to produce a larger number of potential templates and to identify better templates for sequences that have only distant relationships to any solved structure. Protein threading, also known as fold recognition or 3D-1D alignment, can also be used as a search technique for identifying templates to be used in traditional homology modeling methods. Recent CASP experiments indicate that some protein threading methods such as RaptorX indeed are more sensitive than purely sequence(profile)-based methods when only distantly-related templates are available for the proteins under prediction. When performing a BLAST search, a reliable first approach is to identify hits with a sufficiently low "E"-value, which are considered sufficiently close in evolution to make a reliable homology model. Other factors may tip the balance in marginal cases; for example, the template may have a function similar to that of the query sequence, or it may belong to a homologous operon. However, a template with a poor "E"-value should generally not be chosen, even if it is the only one available, since it may well have a wrong structure, leading to the production of a misguided model. A better approach is to submit the primary sequence to fold-recognition servers or, better still, consensus meta-servers which improve upon individual fold-recognition servers by identifying similarities (consensus) among independent predictions. Often several candidate template structures are identified by these approaches

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Homology modeling

Homology modeling Although some methods can generate hybrid models with better accuracy from multiple templates, most methods rely on a single template. Therefore, choosing the best template from among the candidates is a key step, and can affect the final accuracy of the structure significantly. This choice is guided by several factors, such as the similarity of the query and template sequences, of their functions, and of the predicted query and observed template secondary structures. Perhaps most importantly, the "coverage" of the aligned regions: the fraction of the query sequence structure that can be predicted from the template, and the plausibility of the resulting model. Thus, sometimes several homology models are produced for a single query sequence, with the most likely candidate chosen only in the final step. It is possible to use the sequence alignment generated by the database search technique as the basis for the subsequent model production; however, more sophisticated approaches have also been explored. One proposal generates an ensemble of stochastically defined pairwise alignments between the target sequence and a single identified template as a means of exploring "alignment space" in regions of sequence with low local similarity

Biology

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Homology modeling

Homology modeling "Profile-profile" alignments that first generate a sequence profile of the target and systematically compare it to the sequence profiles of solved structures; the coarse-graining inherent in the profile construction is thought to reduce noise introduced by sequence drift in nonessential regions of the sequence. Given a template and an alignment, the information contained therein must be used to generate a three-dimensional structural model of the target, represented as a set of Cartesian coordinates for each atom in the protein. Three major classes of model generation methods have been proposed. The original method of homology modeling relied on the assembly of a complete model from conserved structural fragments identified in closely related solved structures. For example, a modeling study of serine proteases in mammals identified a sharp distinction between "core" structural regions conserved in all experimental structures in the class, and variable regions typically located in the loops where the majority of the sequence differences were localized. Thus unsolved proteins could be modeled by first constructing the conserved core and then substituting variable regions from other proteins in the set of solved structures. Current implementations of this method differ mainly in the way they deal with regions that are not conserved or that lack a template. The variable regions are often constructed with the help of fragment libraries

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Homology modeling

Homology modeling The segment-matching method divides the target into a series of short segments, each of which is matched to its own template fitted from the Protein Data Bank. Thus, sequence alignment is done over segments rather than over the entire protein. Selection of the template for each segment is based on sequence similarity, comparisons of alpha carbon coordinates, and predicted steric conflicts arising from the van der Waals radii of the divergent atoms between target and template. The most common current homology modeling method takes its inspiration from calculations required to construct a three-dimensional structure from data generated by NMR spectroscopy. One or more target-template alignments are used to construct a set of geometrical criteria that are then converted to probability density functions for each restraint. Restraints applied to the main protein internal coordinates – protein backbone distances and dihedral angles – serve as the basis for a global optimization procedure that originally used conjugate gradient energy minimization to iteratively refine the positions of all heavy atoms in the protein. This method had been dramatically expanded to apply specifically to loop modeling, which can be extremely difficult due to the high flexibility of loops in proteins in aqueous solution

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Homology modeling

Homology modeling A more recent expansion applies the spatial-restraint model to electron density maps derived from cryoelectron microscopy studies, which provide low-resolution information that is not usually itself sufficient to generate atomic-resolution structural models. To address the problem of inaccuracies in initial target-template sequence alignment, an iterative procedure has also been introduced to refine the alignment on the basis of the initial structural fit. The most commonly used software in spatial restraint-based modeling is MODELLER and a database called ModBase has been established for reliable models generated with it. Regions of the target sequence that are not aligned to a template are modeled by loop modeling; they are the most susceptible to major modeling errors and occur with higher frequency when the target and template have low sequence identity. The coordinates of unmatched sections determined by loop modeling programs are generally much less accurate than those obtained from simply copying the coordinates of a known structure, particularly if the loop is longer than 10 residues. The first two sidechain dihedral angles (χ and χ) can usually be estimated within 30° for an accurate backbone structure; however, the later dihedral angles found in longer side chains such as lysine and arginine are notoriously difficult to predict

Biology

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Homology modeling

Homology modeling Moreover, small errors in χ (and, to a lesser extent, in χ) can cause relatively large errors in the positions of the atoms at the terminus of side chain; such atoms often have a functional importance, particularly when located near the active site. Assessment of homology models without reference to the true target structure is usually performed with two methods: statistical potentials or physics-based energy calculations. Both methods produce an estimate of the energy (or an energy-like analog) for the model or models being assessed; independent criteria are needed to determine acceptable cutoffs. Neither of the two methods correlates exceptionally well with true structural accuracy, especially on protein types underrepresented in the PDB, such as membrane proteins. Statistical potentials are empirical methods based on observed residue-residue contact frequencies among proteins of known structure in the PDB. They assign a probability or energy score to each possible pairwise interaction between amino acids and combine these pairwise interaction scores into a single score for the entire model. Some such methods can also produce a residue-by-residue assessment that identifies poorly scoring regions within the model, though the model may have a reasonable score overall. These methods emphasize the hydrophobic core and solvent-exposed polar amino acids often present in globular proteins. Examples of popular statistical potentials include Prosa and DOPE

Biology

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Homology modeling

Homology modeling Statistical potentials are more computationally efficient than energy calculations. Physics-based energy calculations aim to capture the interatomic interactions that are physically responsible for protein stability in solution, especially van der Waals and electrostatic interactions. These calculations are performed using a molecular mechanics force field; proteins are normally too large even for semi-empirical quantum mechanics-based calculations. The use of these methods is based on the energy landscape hypothesis of protein folding, which predicts that a protein's native state is also its energy minimum. Such methods usually employ implicit solvation, which provides a continuous approximation of a solvent bath for a single protein molecule without necessitating the explicit representation of individual solvent molecules. A force field specifically constructed for model assessment is known as the Effective Force Field (EFF) and is based on atomic parameters from CHARMM. A very extensive model validation report can be obtained using the Radboud Universiteit Nijmegen ""What Check"" software which is one option of the Radboud Universiteit Nijmegen ""What If"" software package; it produces a many page document with extensive analyses of nearly 200 scientific and administrative aspects of the model. ""What Check"" is available as a free server; it can also be used to validate experimentally determined structures of macromolecules

Biology

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Homology modeling

Homology modeling One newer method for model assessment relies on machine learning techniques such as neural nets, which may be trained to assess the structure directly or to form a consensus among multiple statistical and energy-based methods. Results using support vector machine regression on a jury of more traditional assessment methods outperformed common statistical, energy-based, and machine learning methods. The assessment of homology models' accuracy is straightforward when the experimental structure is known. The most common method of comparing two protein structures uses the root-mean-square deviation (RMSD) metric to measure the mean distance between the corresponding atoms in the two structures after they have been superimposed. However, RMSD does underestimate the accuracy of models in which the core is essentially correctly modeled, but some flexible loop regions are inaccurate. A method introduced for the modeling assessment experiment CASP is known as the global distance test (GDT) and measures the total number of atoms whose distance from the model to the experimental structure lies under a certain distance cutoff. Both methods can be used for any subset of atoms in the structure, but are often applied to only the alpha carbon or protein backbone atoms to minimize the noise created by poorly modeled side chain rotameric states, which most modeling methods are not optimized to predict

Biology

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Homology modeling

Homology modeling Several large-scale benchmarking efforts have been made to assess the relative quality of various current homology modeling methods. CASP is a community-wide prediction experiment that runs every two years during the summer months and challenges prediction teams to submit structural models for a number of sequences whose structures have recently been solved experimentally but have not yet been published. Its partner CAFASP has run in parallel with CASP but evaluates only models produced via fully automated servers. Continuously running experiments that do not have prediction 'seasons' focus mainly on benchmarking publicly available webservers. LiveBench and EVA run continuously to assess participating servers' performance in prediction of imminently released structures from the PDB. CASP and CAFASP serve mainly as evaluations of the state of the art in modeling, while the continuous assessments seek to evaluate the model quality that would be obtained by a non-expert user employing publicly available tools. The accuracy of the structures generated by homology modeling is highly dependent on the sequence identity between target and template. Above 50% sequence identity, models tend to be reliable, with only minor errors in side chain packing and rotameric state, and an overall RMSD between the modeled and the experimental structure falling around 1 Å. This error is comparable to the typical resolution of a structure solved by NMR

Biology

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Homology modeling

Homology modeling In the 30–50% identity range, errors can be more severe and are often located in loops. Below 30% identity, serious errors occur, sometimes resulting in the basic fold being mis-predicted. This low-identity region is often referred to as the "twilight zone" within which homology modeling is extremely difficult, and to which it is possibly less suited than fold recognition methods. At high sequence identities, the primary source of error in homology modeling derives from the choice of the template or templates on which the model is based, while lower identities exhibit serious errors in sequence alignment that inhibit the production of high-quality models. It has been suggested that the major impediment to quality model production is inadequacies in sequence alignment, since "optimal" structural alignments between two proteins of known structure can be used as input to current modeling methods to produce quite accurate reproductions of the original experimental structure. Attempts have been made to improve the accuracy of homology models built with existing methods by subjecting them to molecular dynamics simulation in an effort to improve their RMSD to the experimental structure. However, current force field parameterizations may not be sufficiently accurate for this task, since homology models used as starting structures for molecular dynamics tend to produce slightly worse structures. Slight improvements have been observed in cases where significant restraints were used during the simulation

Biology

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Homology modeling

Homology modeling The two most common and large-scale sources of error in homology modeling are poor template selection and inaccuracies in target-template sequence alignment. Controlling for these two factors by using a structural alignment, or a sequence alignment produced on the basis of comparing two solved structures, dramatically reduces the errors in final models; these "gold standard" alignments can be used as input to current modeling methods to produce quite accurate reproductions of the original experimental structure. Results from the most recent CASP experiment suggest that "consensus" methods collecting the results of multiple fold recognition and multiple alignment searches increase the likelihood of identifying the correct template; similarly, the use of multiple templates in the model-building step may be worse than the use of the single correct template but better than the use of a single suboptimal one. Alignment errors may be minimized by the use of a multiple alignment even if only one template is used, and by the iterative refinement of local regions of low similarity. A lesser source of model errors are errors in the template structure. The PDBREPORT database lists several million, mostly very small but occasionally dramatic, errors in experimental (template) structures that have been deposited in the PDB

Biology

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Homology modeling

Homology modeling Serious local errors can arise in homology models where an insertion or deletion mutation or a gap in a solved structure result in a region of target sequence for which there is no corresponding template. This problem can be minimized by the use of multiple templates, but the method is complicated by the templates' differing local structures around the gap and by the likelihood that a missing region in one experimental structure is also missing in other structures of the same protein family. Missing regions are most common in loops where high local flexibility increases the difficulty of resolving the region by structure-determination methods. Although some guidance is provided even with a single template by the positioning of the ends of the missing region, the longer the gap, the more difficult it is to model. Loops of up to about 9 residues can be modeled with moderate accuracy in some cases if the local alignment is correct. Larger regions are often modeled individually using ab initio structure prediction techniques, although this approach has met with only isolated success. The rotameric states of side chains and their internal packing arrangement also present difficulties in homology modeling, even in targets for which the backbone structure is relatively easy to predict

Biology

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Homology modeling

Homology modeling This is partly due to the fact that many side chains in crystal structures are not in their "optimal" rotameric state as a result of energetic factors in the hydrophobic core and in the packing of the individual molecules in a protein crystal. One method of addressing this problem requires searching a rotameric library to identify locally low-energy combinations of packing states. It has been suggested that a major reason that homology modeling so difficult when target-template sequence identity lies below 30% is that such proteins have broadly similar folds but widely divergent side chain packing arrangements. Uses of the structural models include protein–protein interaction prediction, protein–protein docking, molecular docking, and functional annotation of genes identified in an organism's genome. Even low-accuracy homology models can be useful for these purposes, because their inaccuracies tend to be located in the loops on the protein surface, which are normally more variable even between closely related proteins. The functional regions of the protein, especially its active site, tend to be more highly conserved and thus more accurately modeled. Homology models can also be used to identify subtle differences between related proteins that have not all been solved structurally. For example, the method was used to identify cation binding sites on the Na/K ATPase and to propose hypotheses about different ATPases' binding affinity

Biology

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Homology modeling

Homology modeling Used in conjunction with molecular dynamics simulations, homology models can also generate hypotheses about the kinetics and dynamics of a protein, as in studies of the ion selectivity of a potassium channel. Large-scale automated modeling of all identified protein-coding regions in a genome has been attempted for the yeast "Saccharomyces cerevisiae", resulting in nearly 1000 quality models for proteins whose structures had not yet been determined at the time of the study, and identifying novel relationships between 236 yeast proteins and other previously solved structures.

Biology

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Homology modeling

Tony Bradshaw Anthony David Bradshaw FRS (17 January 1926 - 21 August 2008) was a British evolutionary ecologist He was born the son of an architect in Kew, Surrey and educated at St Pauls School, Hammersmith. He read Botany at Jesus College, Cambridge and in 1947 moved to the University College of Wales, first as a research student in Aberystwyth and then as a lecturer in the Department of Agricultural Botany at Bangor. There he worked on the adaptation of plants to heavy metal pollution, demonstrating the ability of natural selection to bring about rapid evolutionary changes in natural grasses, even in very localised situations. In 1958 he accepted the Chair of Botany at the University of Liverpool where he pioneered novel ideas of restoration ecology to help recover polluted sites without the need to cover them in imported topsoil. His work on the revegetation of china clay tips in Cornwall formed the basis of the techniques behind the Eden Project. In 1982 he was elected a Fellow of the Royal Society. He was President of the British Ecological Society for 1982–83 and the Inaugural President of the Institute of Ecology and Environmental Management in 1991–94. In 1991 he delivered the Croonian Lecture to the Royal Society on "Genostasis and the limits to Evolution". He married Betty Alliston and had 3 daughters.

Biology

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Tony Bradshaw

Darlington Lecture The is a lectureship of the John Innes Centre named after its former director, the geneticist C. D. Darlington. Source: John Innes Centre

Biology

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Darlington Lecture

Epitope binning is a competitive immunoassay used to characterize and then sort a library of monoclonal antibodies against a target protein. Antibodies against a similar target are tested against all other antibodies in the library in a pairwise fashion to see if antibodies block one another's binding to the epitope of an antigen. After each antibody has a profile created against all of the other antibodies in the library, a competitive blocking profile is created for each antibody relative to the others in the library. Closely related binning profiles indicate that the antibodies have the same or a closely related epitope and are "binned" together. is referenced in the literature under different names such as epitope mapping and epitope characterization. Regardless of the naming, epitope binning is prevalent in the pharmaceutical industry. Epitope Binning is used in the discovery and development of new therapeutics, vaccines, and diagnostics.

Biology

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Epitope binning

Mark Hay Mark Edward Hay (born May 3, 1952) is an American marine ecologist. He is Regents Professor and Harry and Linda Teasley Chair in the School of Biological Sciences at the Georgia Institute of Technology. A fellow of the American Association for the Advancement of Science, he is known for his research on the coral reefs of Fiji. He received the Cody Award from the Scripps Institution of Oceanography in 2012, the Lowell Thomas Award from the Explorers Club in 2015, and the Gilbert Morgan Smith Medal from the National Academy of Sciences in 2018.

Biology

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Mark Hay

Fauna of Romania The fauna of Romania comprises all the animal species inhabiting the country of Romania and its coastal territory in the Black Sea. According to a systematic list of the Romanian vertebrate fauna, there are 732 species of vertebrates living in Romania. When grouped into classes, the largest number of these species are birds, with 382 species, followed by fish with 184. 110 of these species are mammals, 31 are reptiles, 20 are amphibians, while only four belong to the Cyclostomata class of jawless fish. The cyclostomata superclass of vertebrates is represented in Romania by four species of lampreys that live in fast, mountains streams, particularly in Transylvania, in rivers such as Criș, Mureș, Someș and Vișeu. Romania's rivers, lakes and ponds are home to numerous species of freshwater fish, most importantly carp, Prussian carp, chub, trout, perch, zander, bream, pike, roach and the Wels catfish. Additionally, six species of sturgeon live in the Black Sea, but travel upriver on the Danube in order to mate. Five of the six Danube sturgeon species are critically endangered, with only the sterlet being considerable vulnerable. The most well known of these six species is probably the beluga sturgeon, which is heavily fished for the female's valuable roe - known as beluga caviar. The saltwater fish of Romania are the Black Sea species of fish that live in the territorial waters of Romania. A 2005 biodiversity inventory of the Romanian waters identified around 140 species and subspecies of marine fish

Biology

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Fauna of Romania

Fauna of Romania Many of the species have seen their stocks plummet in the last 50 years due to commercial exploitation. The six species that are the most commercially viable today are all small-sized fish: the red mullet, the sand smelt, the round goby, the European anchovy, the merling and the sprat. According to recent reports, dozens of species of fish that were believed to be extinct in the Black Sea have reappeared in the area in the last few years, most likely travelling from the Mediterranean, due to the improved water quality and regeneration of the Black Sea ecosystem. Other species that can be found on the Romanian coast include two species of rays, two species of sharks and dozens of species of teleostean fish. The amphibian population of Romania includes more than a dozen species of frogs and toads, several species of newts and the fire salamander, out of which nine species are not found anywhere else outside of Romania. The most common amphibians are the common toad, the yellow-belled toad, the European green toad, the agile frog and the smooth newt. There are a total of ten species of snakes living in Romania, of which three, the common European viper, the meadow viper and the horned viper, are venomous. The horned viper in particular is considered to be extremely dangerous and possibly the most venomous snake in Europe. The javeline sand boa, the rarest species of snake in Europe and the only species of boa on the continent, was believed extinct in the Romania, with the last live specimen being reported in 1937

Biology

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Fauna of Romania

Fauna of Romania An entire stable population of the species was discovered by experts in 2014 along the banks of the Danube, with the exact location being kept a secret to avoid trophy hunting. Four species of turtle and tortoise call Romania their home: The European pond turtle, the common tortoise, Hermann's tortoise and the marine loggerhead sea turtle. In recent years, a number of exotic species such as the Mississippi map turtle and even the Chinese softshell turtle were spotted in ponds and rivers around Bucharest, but their presence has not been extensively documented and their impact on the environment is not yet clearly understood. Over a dozen species of lizard can be found in the country, with the most common one being the European green lizard. While not yet present in Romania, the Pallas's glass lizard and Kotschy's gecko are considered likely to join the list of reptiles in Romania in the near future, both being present in Bulgaria, near the Romanian border. Romania is home to a few dozen species of birds of prey, which includes hawks, eagles, kites, harriers, falcons, owls and Old World vultures. The golen eagle is seen as a symbol of Romania and it appears on the country's coat of arms. The last bearded vulture in Romania was shot in Sibiu in 1927 and there would not be another credible sighting of the bird until 2009. In 2016, researchers managed to provide the first photographic evidence of bearded vulture activity in Romania in almost 90 years

Biology

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Fauna of Romania

Fauna of Romania The water-dwelling birds of Romania are mainly concentrated on the lower Danube, in the Danube Delta, and the littoral area of the Black Sea. The Dobruja region in general and the Danube Delta in particular are hotspots for nesting migratory birds. These include numerous species of ducks, geese, cormorants, shags, herons, storks, ibises, pelicans, swans and, occasionally, flamingos. Several species of seagulls can be found not only on the coast, but hundreds of kilometers inland, becoming somewhat of a pest in cities such as Bucharest and Brașov. The great white pelican is sometimes mentioned in the media as being the national bird of Romania, despite the lack of any official decision in this regard. Among small birds, the most numerous species in Romania is probably the chaffinch, with an estimated 5 million adult individuals, followed by the robin, the goldcrest, the great tit, the white wagtail, the song thrush, the red-backed shrike and several species of sparrow. The great bustard, the world's largest flying animal, was common in Central and South-Eastern Romania until the early 20th century, when agrarian reform severely restricted its habitat. They were considered extinct in Romania, with no sightings between 1981 and 2002, but can now be found in two small, isolated groups in Bihor and Timiș, near the border with Hungary. The first conservationist measures regarding the great bustard populations in Western Romania began in 2018

Biology

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Fauna of Romania

Fauna of Romania Rodents make up a large proportion of the mammals in Romania, especially in the low-lying plains. This includes species of hamsters, field mice, ground squirrels, voles, dormice, red squirrels, nutrias and beavers. Other common small mammals include shrews, rabbits, hedgehogs, polecats, martens and badgers. The bat population in Romania is particularly plentiful with a total of 32 species present in the country. The Huda lui Papară cave in the Trascău Mointains is home to the largest known bat colony in Europe, while the Topolnița Cave in Mehedinți hosts the largest colony of greater horseshoe bat on the continent. Several other caves display extraordinary biodiversity, with up to 20 species of bats living in the same cave system. Romania is also home to the greater noctule bat ("Nyctalus lasiopterus)," a rare species that is Europe's largest and least studied bat, as well as probably its most threatened. It is a carnivorous bat that eats insects and even regularly preys on birds. Large species of non-carnivorous mammals in Romania include the Carpathian boar, fallow deer, red deer, roe deer and the chamois. The endangered saiga antelope was once common in Moldavia and Eastern Wallachia, but has gone all but existent in the 18th century. Today only a few specimens survive in a small natural reserve in the northeastern county of Botoșani. The chamois is a protected species in Romania and is the subject of several conservation efforts

Biology

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Fauna of Romania

Fauna of Romania The European bison, the largest European land mammal, became extinct in the region in the 18th century, However, in 1958, Romania began the reintroduction of the bison into its nature reserves. In the 21st century, Romania also began reintroducing the European bison in the wild, the ninth country to do so as part of a continent-wide effort that saw the total number of bison in Europe go from 54 captive individuals in 1927 to more than 7000 in 2018. In 2016, there were over 100 bison living in wild or semi-wild areas in different regions of Romania. Romania is also home to the Danube Delta horses, a population of feral horses that has lived for hundreds of years in and around Letea Forest in the Danube Delta and is possibly the last sizable population of wild horses in Europe. After collective farms were closed down in the 1990s, the population was supplanted by freed horses and by the beginning of the 21st century, it increased to around 4000 individuals, turning them into a threat to the protected flora of the region. Following media and public outrage in 2011, authorities walked back on the initial plan of killing the horses and the population is now controlled through birth-control vaccines. The large species of carnivores living in Romania are the European wildcat, the Eurasian lynx, the red fox, the golden jackal, the grey wolf and the brown bear. There are over 6000 brown bears living in Romania, in one of the largest concentrations in Europe

Biology

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Fauna of Romania

Fauna of Romania Because of the increasing number of interactions with settled areas, including a number of attacks, but also because the "optimum size of the population of brown bear, from an ecological, social and economic point of view" is around 4000, the Romanian government announced plans in 2018 for a culling of about 2000 of the country's brown bears. This measured was met with hostility by many conservationist organisations and the public. One species of porpoise (Phocoena phocoena) and several species of dolphins live in the Black Sea off the cost of Romania. While the endangered Mediterranean monk seal still occurs in the Black Sea, it has not been recorded in Romanian waters for several decades. Several non-native species of mammals were introduced to Romania during the 20th Century. Among these the most notable are the East-Asian raccoon dog, which spread to Europe through the USSR and was first seen in Romania in 1951, the European mouflon, which was introduces starting with 1966 in game reserves and later in the wilderness, and the North-American muskrat, which was introduced to Romania accidentally, after individuals which escaped captivity in Czech and Russian farms spread across the continent around the middle of the century. Due to the low level of research done in Romania in this regard and the rapid pace of environmental changes that the country went through in the last decades, there is no definitive list of endangered species in Romania

Biology

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Fauna of Romania

Fauna of Romania According to a 2013 paper on biodiversity, The incomplete and biased species inventory in Romania may have several causes: difficult access due to low road density, complex landscape (with 15% of the territory above 800 m), limited funds available for large-scale inventory and monitoring projects, and lack of institutional support. For instance, no species distribution databases are publicly available at the Romanian Ministry of the EnvironmentSome species, such as the chamois, the Eurasian lynx, the European bison, the wood grouse and the Danube salmon have been the subject of some high-profile conservation efforts and are protected by national laws. One species that only lives in Romania and might soon become extinct is the Romanian darter, a species of perch that was once common in the waters of the Argeș river and its tributaries, Râul Doamnei and Vâlsan, but is now only extant in a 1 km stretch of the Vâlsan. A 2017 study identified 390 alien species of terrestrial animals with (of which 90% are invertebrates) and 102 species of aquatic organisms (44 freshwater and 58 marine) in Romania. Most of these originate in North America and Southeast Asia and have been introduced accidentally. Despite being a signatory of the Berne Convention on the Conservation of European Wildlife and Natural Habitats, Romania is behind many other countries when it comes to protecting its ecosystems from invasive alien species

Biology

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Fauna of Romania

Fauna of Romania There is currently no official list of alien species or invasive species provided by the Romanian Ministry of Environment. Some of the invasive alien species, such as the veined rapa whelk"," the sea walnut or the soft-shell clam have been well documented, but the impact of most invasive species on the Romanian ecosystems has not been properly researched, with serious academic research into the topic only beginning in the last decade.

Biology

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Fauna of Romania