Thiol

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https://en.wikipedia.org/wiki/Thiol

Thiol with a   blue highlighted sulfhydryl group.

In organic chemistry, a thiol (/ˈθaɪɒl/; from Ancient Greek θεῖον (theion) 'sulfur'), or thiol derivative, is any organosulfur compound of the form R−SH, where R represents an alkyl or other organic substituent. The −SH functional group itself is referred to as either a thiol group or a sulfhydryl group, or a sulfanyl group. Thiols are the sulfur analogue of alcohols (that is, sulfur takes the place of oxygen in the hydroxyl (−OH) group of an alcohol), and the word is a blend of "thio-" with "alcohol".

Many thiols have strong odors resembling that of garlic or rotten eggs. Thiols are used as odorants to assist in the detection of natural gas (which in pure form is odorless), and the "smell of natural gas" is due to the smell of the thiol used as the odorant. Thiols are sometimes referred to as mercaptans (/mərˈkæptæn/) or mercapto compounds, a term introduced in 1832 by William Christopher Zeise and is derived from the Latin mercurio captāns ('capturing mercury') because the thiolate group (RS⁻), also termed as Mercaptide, bonds very strongly with mercury compounds.

Structure and bonding

Thiols having the structure R−SH, in which an alkyl group (R) is attached to a sulfhydryl group (SH), are referred to as alkanethiols or alkyl thiols. Thiols and alcohols have similar connectivity. Because sulfur atoms are larger than oxygen atoms, C−S bond lengths – typically around 180 picometres – are about 40 picometers longer than typical C−O bonds. The C−S−H angles approach 90° whereas the angle for the C−O−H group is more obtuse. In solids and liquids, the hydrogen-bonding between individual thiol groups is weak, the main cohesive force being Van der Waals interactions between the highly polarizable divalent sulfur centers.

The S−H bond is much weaker than the O−H bond as reflected in their respective bond dissociation energies (BDE). For CH₃S−H, the BDE is 366 kJ/mol (87 kcal/mol), while for CH₃O−H, the BDE is 440 kJ/mol (110 kcal/mol).

An S−H bond is moderately polar because of the small difference in the electronegativity of sulfur and hydrogen. In contrast, O−H bonds in hydroxyl groups are more polar. Thiols have a lower dipole moment relative to their corresponding alcohols.

Nomenclature

There are several ways to name the alkylthiols:

• The suffix -thiol is added to the name of the alkane. This method is nearly identical to naming an alcohol and is used by the IUPAC, e.g. CH₃SH would be methanethiol.
• The word mercaptan replaces alcohol in the name of the equivalent alcohol compound. Example: CH₃SH would be methyl mercaptan, just as CH₃OH is called methyl alcohol.
• The term sulfhydryl- or mercapto- is used as a prefix, e.g. mercaptopurine.

Physical properties

Odor

Many thiols have strong odors resembling that of garlic. The odors of thiols, particularly those of low molecular weight, are often strong and repulsive. The spray of skunks consists mainly of low-molecular-weight thiols and derivatives. These compounds are detectable by the human nose at concentrations of only 10 parts per billion. Human sweat contains (R)/(S)-3-methyl-3-mercapto-1-ol (MSH), detectable at 2 parts per billion and having a fruity, onion-like odor. (Methylthio)methanethiol (MeSCH₂SH; MTMT) is a strong-smelling volatile thiol, also detectable at parts per billion levels, found in male mouse urine. Lawrence C. Katz and co-workers showed that MTMT functioned as a semiochemical, activating certain mouse olfactory sensory neurons, attracting female mice. Copper has been shown to be required by a specific mouse olfactory receptor, MOR244-3, which is highly responsive to MTMT as well as to various other thiols and related compounds. A human olfactory receptor, OR2T11, has been identified which, in the presence of copper, is highly responsive to the gas odorants (see below) ethanethiol and t-butyl mercaptan as well as other low molecular weight thiols, including allyl mercaptan found in human garlic breath, and the strong-smelling cyclic sulfide thietane.

Thiols are also responsible for a class of wine faults caused by an unintended reaction between sulfur and yeast and the "skunky" odor of beer that has been exposed to ultraviolet light.

Not all thiols have unpleasant odors. For example, furan-2-ylmethanethiol contributes to the aroma of roasted coffee, whereas grapefruit mercaptan, a monoterpenoid thiol, is responsible for the characteristic scent of grapefruit. The effect of the latter compound is present only at low concentrations. The pure mercaptan has an unpleasant odor.

In the United States, natural gas distributors were required to add thiols, originally ethanethiol, to natural gas (which is naturally odorless) after the deadly New London School explosion in New London, Texas, in 1937. Many gas distributors were odorizing gas prior to this event. Most currently-used gas odorants contain mixtures of mercaptans and sulfides, with t-butyl mercaptan as the main odor constituent in natural gas and ethanethiol in liquefied petroleum gas (LPG, propane). In situations where thiols are used in commercial industry, such as liquid petroleum gas tankers and bulk handling systems, an oxidizing catalyst is used to destroy the odor. A copper-based oxidation catalyst neutralizes the volatile thiols and transforms them into inert products.

Boiling points and solubility

Thiols show little association by hydrogen bonding, both with water molecules and among themselves. Hence, they have lower boiling points and are less soluble in water and other polar solvents than alcohols of similar molecular weight. For this reason also, thiols and their corresponding sulfide functional group isomers have similar solubility characteristics and boiling points, whereas the same is not true of alcohols and their corresponding isomeric ethers.

Bonding

The S−H bond in thiols is weak compared to the O−H bond in alcohols. For CH₃X−H, the bond enthalpies are 365.07±2.1 kcal/mol for X = S and 440.2±3.0 kcal/mol for X = O. Hydrogen-atom abstraction from a thiol gives a thiyl radical with the formula RS^•, where R = alkyl or aryl.

Characterization

Volatile thiols are easily and almost unerringly detected by their distinctive odor. Sulfur-specific analyzers for gas chromatographs are useful. Spectroscopic indicators are the D₂O-exchangeable SH signal in the ¹H NMR spectrum (³³S is NMR-active but signals for divalent sulfur are very broad and of little utility). The ν_SH band appears near 2400 cm⁻¹ in the IR spectrum. In the nitroprusside reaction, free thiol groups react with sodium nitroprusside and ammonium hydroxide to give a red colour.

Preparation

In industry, methanethiol is prepared by the reaction of hydrogen sulfide with methanol. This method is employed for the industrial synthesis of methanethiol:

CH₃OH + H₂S → CH₃SH + H₂O

Such reactions are conducted in the presence of acidic catalysts. The other principal route to thiols involves the addition of hydrogen sulfide to alkenes. Such reactions are usually conducted in the presence of an acid catalyst or UV light. Halide displacement, using the suitable organic halide and sodium hydrogen sulfide has also been used.

Another method entails the alkylation of sodium hydrosulfide.

RX + NaSH → RSH + NaX (X = Cl, Br, I)

This method is used for the production of thioglycolic acid from chloroacetic acid.

Laboratory methods

In general, on the typical laboratory scale, the direct reaction of a haloalkane with sodium hydrosulfide is inefficient owing to the competing formation of sulfides. Instead, alkyl halides are converted to thiols via an S-alkylation of thiourea. This multistep, one-pot process proceeds via the intermediacy of the isothiouronium salt, which is hydrolyzed in a separate step:

CH₃CH₂Br + SC(NH₂)₂ → [CH₃CH₂SC(NH₂)₂]Br

[CH₃CH₂SC(NH₂)₂]Br + NaOH → CH₃CH₂SH + OC(NH₂)₂ + NaBr

The thiourea route works well with primary halides, especially activated ones. Secondary and tertiary thiols are less easily prepared. Secondary thiols can be prepared from the ketone via the corresponding dithioketals. A related two-step process involves alkylation of thiosulfate to give the thiosulfonate ("Bunte salt"), followed by hydrolysis. The method is illustrated by one synthesis of thioglycolic acid:

ClCH₂CO₂H + Na₂S₂O₃ → Na[O₃S₂CH₂CO₂H] + NaCl

Na[O₃S₂CH₂CO₂H] + H₂O → HSCH₂CO₂H + NaHSO₄

Organolithium compounds and Grignard reagents react with sulfur to give the thiolates, which are readily hydrolyzed:

RLi + S → RSLi

RSLi + HCl → RSH + LiCl

Phenols can be converted to the thiophenols via rearrangement of their O-aryl dialkylthiocarbamates.

Thiols are prepared by reductive dealkylation of sulfides, especially benzyl derivatives and thioacetals.

Thiophenols are produced by S-arylation or the replacement of diazonium leaving group with sulfhydryl anion (SH⁻):

ArN⁺
₂ + SH⁻ → ArSH + N₂

Reactions

Akin to the chemistry of alcohols, thiols form sulfides, thioacetals, and thioesters, which are analogous to ethers, acetals, and esters respectively. Thiols and alcohols are also very different in their reactivity, thiols being more easily oxidized than alcohols. Thiolates are more potent nucleophiles than the corresponding alkoxides.

S-Alkylation

Thiols, or more specific their conjugate bases, are readily alkylated to give sulfides:

RSH + R′Br + B → RSR′ + [HB]Br  (B = base)

Acidity

Thiols are easily deprotonated. Relative to the alcohols, thiols are more acidic. The conjugate base of a thiol is called a thiolate. Butanethiol has a pK_a of 10.5 vs 15 for butanol. Thiophenol has a pK_a of 6, versus 10 for phenol. A highly acidic thiol is pentafluorothiophenol (C₆F₅SH) with a pK_a of 2.68. Thus, thiolates can be obtained from thiols by treatment with alkali metal hydroxides.

Synthesis of thiophenolate from thiophenol

Redox

Thiols, especially in the presence of base, are readily oxidized by reagents such as bromine and iodine to give an organic disulfide (R−S−S−R).

2 R−SH + Br₂ → R−S−S−R + 2 HBr

Oxidation by more powerful reagents such as sodium hypochlorite or hydrogen peroxide can also yield sulfonic acids (RSO₃H).

R−SH + 3 H₂O₂ → RSO₃H + 3 H₂O

Oxidation can also be effected by oxygen in the presence of catalysts:

2 R–SH + 1⁄2 O₂ → RS−SR + H₂O

Thiols participate in thiol-disulfide exchange:

RS−SR + 2 R′SH → 2 RSH + R′S−SR′

This reaction is important in nature.

Metal ion complexation

With metal ions, thiolates behave as ligands to form transition metal thiolate complexes. The term mercaptan is derived from the Latin mercurium captans (capturing mercury) because the thiolate group bonds so strongly with mercury compounds. According to hard/soft acid/base (HSAB) theory, sulfur is a relatively soft (polarizable) atom. This explains the tendency of thiols to bind to soft elements and ions such as mercury, lead, or cadmium. The stability of metal thiolates parallels that of the corresponding sulfide minerals.

Thioxanthates

Thiolates react with carbon disulfide to give thioxanthate (RSCS⁻
₂).

Thiyl radicals

Main article: Thiyl radical

Free radicals derived from mercaptans, called thiyl radicals, are commonly invoked to explain reactions in organic chemistry and biochemistry. They have the formula RS^• where R is an organic substituent such as alkyl or aryl. They arise from or can be generated by a number of routes, but the principal method is H-atom abstraction from thiols. Another method involves homolysis of organic disulfides. In biology thiyl radicals are responsible for the formation of the deoxyribonucleic acids, building blocks for DNA. This conversion is catalysed by ribonucleotide reductase (see figure). Thiyl intermediates also are produced by the oxidation of glutathione, an antioxidant in biology. Thiyl radicals (sulfur-centred) can transform to carbon-centred radicals via hydrogen atom exchange equilibria. The formation of carbon-centred radicals could lead to protein damage via the formation of C−C bonds or backbone fragmentation.

Because of the weakness of the S−H bond, thiols can function as scavengers of free radicals.

Biological importance

The catalytic cycle for ribonucleotide reductase, demonstrating the role of thiyl radicals in producing the genetic machinery of life.

Cysteine and cystine

As the functional group of the amino acid cysteine, the thiol group plays a very important role in biology. When the thiol groups of two cysteine residues (as in monomers or constituent units) are brought near each other in the course of protein folding, an oxidation reaction can generate a cystine unit with a disulfide bond (−S−S−). Disulfide bonds can contribute to a protein's tertiary structure if the cysteines are part of the same peptide chain, or contribute to the quaternary structure of multi-unit proteins by forming fairly strong covalent bonds between different peptide chains. A physical manifestation of cysteine-cystine equilibrium is provided by hair straightening technologies.

Sulfhydryl groups in the active site of an enzyme can form noncovalent bonds with the enzyme's substrate as well, contributing to covalent catalytic activity in catalytic triads. Active site cysteine residues are the functional unit in cysteine protease catalytic triads. Cysteine residues may also react with heavy metal ions (Zn²⁺, Cd²⁺, Pb²⁺, Hg²⁺, Ag⁺) because of the high affinity between the soft sulfide and the soft metal (see hard and soft acids and bases). This can deform and inactivate the protein, and is one mechanism of heavy metal poisoning.

Drugs containing thiol group 6-Mercaptopurine (anticancer) Captopril (antihypertensive) D-penicillamine (antiarthritic) Sodium aurothiolate (antiarthritic)

Cofactors

Many cofactors (non-protein-based helper molecules) feature thiols. The biosynthesis and degradation of fatty acids and related long-chain hydrocarbons is conducted on a scaffold that anchors the growing chain through a thioester derived from the thiol Coenzyme A. The biosynthesis of methane, the principal hydrocarbon on Earth, arises from the reaction mediated by coenzyme M, 2-mercaptoethyl sulfonic acid. Thiolates, the conjugate bases derived from thiols, form strong complexes with many metal ions, especially those classified as soft. The stability of metal thiolates parallels that of the corresponding sulfide minerals.

In skunks

The defensive spray of skunks consists mainly of low-molecular-weight thiols and derivatives with a foul odor, which protects the skunk from predators. Owls are able to prey on skunks, as they lack a sense of smell.

Examples of thiols

• Methanethiol – CH₃SH [methyl mercaptan]
• Ethanethiol – C₂H₅SH [ethyl mercaptan]
• 1-Propanethiol – C₃H₇SH [n-propyl mercaptan]
• 2-Propanethiol – CH₃CH(SH)CH₃ [2C3 mercaptan]
• Allyl mercaptan – CH₂=CHCH₂SH [2-propenethiol]
• Butanethiol – C₄H₉SH [n-butyl mercaptan]
• tert-Butyl mercaptan – (CH₃)₃CSH [t-butyl mercaptan]
• Pentanethiols – C₅H₁₁SH [pentyl mercaptan]
• Thiophenol – C₆H₅SH
• Dimercaptosuccinic acid
• Thioacetic acid
• Coenzyme A
• Glutathione
• Metallothionein
• Cysteine
• 2-Mercaptoethanol
• Dithiothreitol/dithioerythritol (an epimeric pair)
• 2-Mercaptoindole
• Grapefruit mercaptan
• Furan-2-ylmethanethiol
• 3-Mercaptopropane-1,2-diol
• 3-Mercapto-1-propanesulfonic acid
• 1-Hexadecanethiol
• Pentachlorobenzenethiol

Mathematical statistics

From Wikipedia, the free encyclopedia

https://en.wikipedia.org/wiki/Mathematical_statistics

Illustration of linear regression on a data set. Regression analysis is an important part of mathematical statistics.

Introduction

Statistical data collection is concerned with the planning of studies, especially with the design of randomized experiments and with the planning of surveys using random sampling. The initial analysis of the data often follows the study protocol specified prior to the study being conducted. The data from a study can also be analyzed to consider secondary hypotheses inspired by the initial results, or to suggest new studies. A secondary analysis of the data from a planned study uses tools from data analysis, and the process of doing this is mathematical statistics.

Data analysis is divided into:

• descriptive statistics – the part of statistics that describes data, i.e. summarises the data and their typical properties.
• inferential statistics – the part of statistics that draws conclusions from data (using some model for the data): For example, inferential statistics involves selecting a model for the data, checking whether the data fulfill the conditions of a particular model, and with quantifying the involved uncertainty (e.g. using confidence intervals).

While the tools of data analysis work best on data from randomized studies, they are also applied to other kinds of data. For example, from natural experiments and observational studies, in which case the inference is dependent on the model chosen by the statistician, and so subjective.

Topics

The following are some of the important topics in mathematical statistics:

Probability distributions

Main article: Probability distribution

A probability distribution is a function that assigns a probability to each measurable subset of the possible outcomes of a random experiment, survey, or procedure of statistical inference. Examples are found in experiments whose sample space is non-numerical, where the distribution would be a categorical distribution; experiments whose sample space is encoded by discrete random variables, where the distribution can be specified by a probability mass function; and experiments with sample spaces encoded by continuous random variables, where the distribution can be specified by a probability density function. More complex experiments, such as those involving stochastic processes defined in continuous time, may demand the use of more general probability measures.

A probability distribution can either be univariate or multivariate. A univariate distribution gives the probabilities of a single random variable taking on various alternative values; a multivariate distribution (a joint probability distribution) gives the probabilities of a random vector—a set of two or more random variables—taking on various combinations of values. Important and commonly encountered univariate probability distributions include the binomial distribution, the hypergeometric distribution, and the normal distribution. The multivariate normal distribution is a commonly encountered multivariate distribution.

Special distributions

• Normal distribution, the most common continuous distribution
• Bernoulli distribution, for the outcome of a single Bernoulli trial (e.g. success/failure, yes/no)
• Binomial distribution, for the number of "positive occurrences" (e.g. successes, yes votes, etc.) given a fixed total number of independent occurrences
• Negative binomial distribution, for binomial-type observations but where the quantity of interest is the number of failures before a given number of successes occurs
• Geometric distribution, for binomial-type observations but where the quantity of interest is the number of failures before the first success; a special case of the negative binomial distribution, where the number of successes is one.
• Discrete uniform distribution, for a finite set of values (e.g. the outcome of a fair die)
• Continuous uniform distribution, for continuously distributed values
• Poisson distribution, for the number of occurrences of a Poisson-type event in a given period of time
• Exponential distribution, for the time before the next Poisson-type event occurs
• Gamma distribution, for the time before the next k Poisson-type events occur
• Chi-squared distribution, the distribution of a sum of squared standard normal variables; useful e.g. for inference regarding the sample variance of normally distributed samples (see chi-squared test)
• Student's t distribution, the distribution of the ratio of a standard normal variable and the square root of a scaled chi squared variable; useful for inference regarding the mean of normally distributed samples with unknown variance (see Student's t-test)
• Beta distribution, for a single probability (real number between 0 and 1); conjugate to the Bernoulli distribution and binomial distribution

Statistical inference

Main article: Statistical inference

Statistical inference is the process of drawing conclusions from data that are subject to random variation, for example, observational errors or sampling variation. Initial requirements of such a system of procedures for inference and induction are that the system should produce reasonable answers when applied to well-defined situations and that it should be general enough to be applied across a range of situations. Inferential statistics are used to test hypotheses and make estimations using sample data. Whereas descriptive statistics describe a sample, inferential statistics infer predictions about a larger population that the sample represents.

The outcome of statistical inference may be an answer to the question "what should be done next?", where this might be a decision about making further experiments or surveys, or about drawing a conclusion before implementing some organizational or governmental policy. For the most part, statistical inference makes propositions about populations, using data drawn from the population of interest via some form of random sampling. More generally, data about a random process is obtained from its observed behavior during a finite period of time. Given a parameter or hypothesis about which one wishes to make inference, statistical inference most often uses:

• a statistical model of the random process that is supposed to generate the data, which is known when randomization has been used, and
• a particular realization of the random process; i.e., a set of data.

Regression

Main article: Regression analysis

In statistics, regression analysis is a statistical process for estimating the relationships among variables. It includes many ways for modeling and analyzing several variables, when the focus is on the relationship between a dependent variable and one or more independent variables. More specifically, regression analysis helps one understand how the typical value of the dependent variable (or 'criterion variable') changes when any one of the independent variables is varied, while the other independent variables are held fixed. Most commonly, regression analysis estimates the conditional expectation of the dependent variable given the independent variables – that is, the average value of the dependent variable when the independent variables are fixed. Less commonly, the focus is on a quantile, or other location parameter of the conditional distribution of the dependent variable given the independent variables. In all cases, the estimation target is a function of the independent variables called the regression function. In regression analysis, it is also of interest to characterize the variation of the dependent variable around the regression function which can be described by a probability distribution.

Many techniques for carrying out regression analysis have been developed. Familiar methods, such as linear regression, are parametric, in that the regression function is defined in terms of a finite number of unknown parameters that are estimated from the data (e.g. using ordinary least squares). Nonparametric regression refers to techniques that allow the regression function to lie in a specified set of functions, which may be infinite-dimensional.

Nonparametric statistics

Main article: Nonparametric statistics

Nonparametric statistics are values calculated from data in a way that is not based on parameterized families of probability distributions. They include both descriptive and inferential statistics. The typical parameters are the mean, variance, etc. Unlike parametric statistics, nonparametric statistics make no assumptions about the probability distributions of the variables being assessed.

Non-parametric methods are widely used for studying populations that take on a ranked order (such as movie reviews receiving one to four stars). The use of non-parametric methods may be necessary when data have a ranking but no clear numerical interpretation, such as when assessing preferences. In terms of levels of measurement, non-parametric methods result in "ordinal" data.

As non-parametric methods make fewer assumptions, their applicability is much wider than the corresponding parametric methods. In particular, they may be applied in situations where less is known about the application in question. Also, due to the reliance on fewer assumptions, non-parametric methods are more robust.

One drawback of non-parametric methods is that since they do not rely on assumptions, they are generally less powerful than their parametric counterparts. Low power non-parametric tests are problematic because a common use of these methods is for when a sample has a low sample size. Many parametric methods are proven to be the most powerful tests through methods such as the Neyman–Pearson lemma and the Likelihood-ratio test.

Another justification for the use of non-parametric methods is simplicity. In certain cases, even when the use of parametric methods is justified, non-parametric methods may be easier to use. Due both to this simplicity and to their greater robustness, non-parametric methods are seen by some statisticians as leaving less room for improper use and misunderstanding.

Statistics, mathematics, and mathematical statistics

Mathematical statistics is a key subset of the discipline of statistics. Statistical theorists study and improve statistical procedures with mathematics, and statistical research often raises mathematical questions.

Mathematicians and statisticians like Gauss, Laplace, and C. S. Peirce used decision theory with probability distributions and loss functions (or utility functions). The decision-theoretic approach to statistical inference was reinvigorated by Abraham Wald and his successors, and makes extensive use of scientific computing, analysis, and optimization; for the design of experiments, statisticians use algebra and combinatorics. But while statistical practice often relies on probability and decision theory, their application can be controversial.

Dopamine hypothesis of schizophrenia

From Wikipedia, the free encyclopedia

https://en.wikipedia.org/wiki/Dopamine_hypothesis_of_schizophrenia 

The dopamine hypothesis of schizophrenia or the dopamine hypothesis of psychosis is a model that attributes the positive symptoms of schizophrenia to a disturbed and hyperactive dopaminergic signal transduction. The model draws evidence from the observation that a large number of antipsychotics have dopamine-receptor antagonistic effects. The theory, however, does not posit dopamine overabundance as a complete explanation for schizophrenia. Rather, the overactivation of D2 receptors, specifically, is one effect of the global chemical synaptic dysregulation observed in this disorder.

Introduction

Some researchers have suggested that dopamine systems in the mesolimbic pathway may contribute to the 'positive symptoms' of schizophrenia, whereas problems concerning dopamine function within the mesocortical pathway may be responsible for the 'negative symptoms', such as avolition and alogia. Abnormal expression, thus distribution of the D₂ receptor between these areas and the rest of the brain may also be implicated in schizophrenia, specifically in the acute phase. A relative excess of these receptors within the limbic system means Broca's area, which can produce illogical language, has an abnormal connection to Wernicke's area, which comprehends language but does not create it.^{[citation needed]} Note that variation in distribution is observed within individuals, so abnormalities of this characteristic likely play a significant role in all psychological illnesses. Individual alterations are produced by differences within glutamatergic pathways within the limbic system, which are also implicated in other psychotic syndromes. Among the alterations of both synaptic and global structure, the most significant abnormalities are observed in the uncinate fasciculus and the cingulate cortex. The combination of these creates a profound dissymmetry of prefrontal inhibitory signaling, shifted positively towards the dominant side. Eventually, the cingulate gyrus becomes atrophied towards the anterior, due to long-term depression (LTD) and long-term potentiation (LTP) from the abnormally strong signals transversely across the brain. This, combined with a relative deficit in GABAergic input to Wernicke's area, shifts the balance of bilateral communication across the corpus callosum posteriorly. Through this mechanism, hemispherical communication becomes highly shifted towards the left/dominant posterior. As such, spontaneous language from Broca's can propagate through the limbic system to the tertiary auditory cortex. This retrograde signaling to the temporal lobes that results in the parietal lobes not recognizing it as internal results in the auditory hallucinations typical of chronic schizophrenia.

In addition, significant cortical grey matter volume reductions are observed in this disorder. Specifically, the right hemisphere atrophies more, while both sides show a marked decrease in frontal and posterior volume. This indicates that abnormal synaptic plasticity occurs, where certain feedback loops become so potentiated, others receive little glutaminergic transmission. This is a direct result of the abnormal dopaminergic input to the striatum, thus (indirectly) disinhibition of thalamic activity. The excitatory nature of dopaminergic transmission means the glutamate hypothesis of schizophrenia is inextricably intertwined with this altered functioning. 5-HT also regulates monoamine neurotransmitters, including dopaminergic transmission. Specifically, the 5-HT2A receptor regulates cortical input to the basal ganglia and many typical and atypical antipsychotics are antagonists at this receptor. Several antipsychotics are also antagonists at the 5-HT2C receptor, leading to dopamine release in the structures where 5-HT2C is expressed; striatum, prefrontal cortex, nucleus accumbens, amygdala, hippocampus (all structures indicated in this disease), and currently thought to be a reason why antipsychotics with 5HT2C antagonistic properties improves negative symptoms. More research is needed to explain the exact nature of the altered chemical transmission in this disorder.

Recent evidence on a variety of animal models of psychosis, such as sensitization of animal behaviour by amphetamine, or phencyclidine (PCP, Angel Dust), or excess steroids, or by removing various genes (COMT, DBH, GPRK6, RGS9, RIIbeta), or making brain lesions in newborn animals, or delivering animals abnormally by Caesarian section, all induce a marked behavioural supersensitivity to dopamine and a marked rise in the number of dopamine D₂ receptors in the high-affinity state for dopamine. This latter work implies that there are multiple genes and neuronal pathways that can lead to psychosis and that all these multiple psychosis pathways converge via the high-affinity state of the D2 receptor, the common target for all antipsychotics, typical or atypical. Combined with less inhibitory signalling from the thalamus and other basal ganglic structures, from hyoptrophy the abnormal activation of the cingulate cortex, specifically around Broca's and Wernicke's areas, abnormal D₂ agonism can facilitate the self-reinforcing, illogical patterns of language found in such patients. In schizophrenia, this feedback loop has progressed, which produced the widespread neural atrophy characteristic of this disease. Patients on neuroleptic or antipsychotic medication have significantly less atrophy within these crucial areas. As such, early medical intervention is crucial in preventing the advancement of these profound deficits in bilateral communication at the root of all psychotic disorders. Advanced, chronic schizophrenia can not respond even to clozapine, regarded as the most effective antipsychotic, as such, a cure for highly advanced schizophrenia is likely impossible through the use of any modern antipsychotics, so the value of early intervention cannot be stressed enough.

Discussion

Evidence for the dopamine hypothesis

Stimulants such as amphetamine and cocaine increase the levels of dopamine in the synaptic space and exacerbate acute psychotic episodes in schizophrenic patients. It should be noted, however, that this does not occur when patients with schizophrenia are not in an acute psychotic state. In fact, low-dose amphetamine (10mg) has been shown to improve auditory discrimination training in patients with schizophrenia. Repeated, high doses of amphetamine are neurotoxic to dopamine neurons, and can cause a psychotic syndrome resembling schizophrenia. Similarly, those treated with dopamine enhancing levodopa for Parkinson's disease can experience psychotic side effects mimicking the symptoms of schizophrenia. Up to 75% of patients with schizophrenia have increased signs and symptoms of their psychosis upon challenge with moderate doses of methylphenidate or amphetamine or other dopamine-like compounds, all given at doses at which control normal volunteers do not have any psychologically disturbing effects.

Some functional neuroimaging studies have also shown that, after taking amphetamine, patients diagnosed with schizophrenia show greater levels of dopamine release (particularly in the striatum) than non-psychotic individuals. However, the acute effects of dopamine stimulants include euphoria, alertness and over-confidence; these symptoms are more reminiscent of mania than schizophrenia. Since the 2000s, several PET studies have confirmed an altered synthesis capacity of dopamine in the nigrostriatal system demonstrating a dopaminergic dysregulation.

A group of drugs called the phenothiazines, including antipsychotics such as chlorpromazine, has been found to antagonize dopamine binding (particularly at receptors known as D₂ dopamine receptors) and reduce positive psychotic symptoms. This observation was subsequently extended to other antipsychotic drug classes, such as butyrophenones including haloperidol. The link was strengthened by experiments in the 1970s which suggested that the binding affinity of antipsychotic drugs for D₂ dopamine receptors seemed to be inversely proportional to their therapeutic dose. This correlation, suggesting that receptor binding is causally related to therapeutic potency, was reported by two laboratories in 1976.

People with Schizophrenia appear to have a high rate of self-medication with nicotine; the therapeutic effect likely occurs through dopamine modulation by nicotinic acetylcholine receptors.

However, there was controversy and conflicting findings over whether postmortem findings resulted from drug tolerance to chronic antipsychotic treatment. Compared to the success of postmortem studies in finding profound changes of dopamine receptors, imaging studies using SPECT and PET methods in drug naive patients have generally failed to find any difference in dopamine D₂ receptor density compared to controls. Comparable findings in longitudinal studies show: " Particular emphasis is given to methodological limitations in the existing literature, including lack of reliability data, clinical heterogeneity among studies, and inadequate study designs and statistic," suggestions are made for improving future longitudinal neuroimaging studies of treatment effects in schizophrenia A recent review of imaging studies in schizophrenia shows confidence in the techniques, while discussing such operator error. In 2007 one report said, "During the last decade, results of brain imaging studies by use of PET and SPECT in schizophrenic patients showed a clear dysregulation of the dopaminergic system."

Recent findings from meta-analyses suggest that there may be a small elevation in dopamine D₂ receptors in drug-free patients with schizophrenia, but the degree of overlap between patients and controls makes it unlikely that this is clinically meaningful. While the review by Laruelle acknowledged more sites were found using methylspiperone, it discussed the theoretical reasons behind such an increase (including the monomer-dimer equilibrium) and called for more work to be done to 'characterise' the differences. In addition, newer antipsychotic medication (called atypical antipsychotic medication) can be as potent as older medication (called typical antipsychotic medication) while also affecting serotonin function and having somewhat less of a dopamine blocking effect. In addition, dopamine pathway dysfunction has not been reliably shown to correlate with symptom onset or severity. HVA levels correlate trendwise to symptoms severity. During the application of debrisoquin, this correlation becomes significant.

Giving a more precise explanation of this discrepancy in D₂ receptor has been attempted by a significant minority. Radioligand imaging measurements involve the monomer and dimer ratio, and the 'cooperativity' model. Cooperativitiy is a chemical function in the study of enzymes. Dopamine receptors interact with their own kind, or other receptors to form higher order receptors such as dimers, via the mechanism of cooperativity. Philip Seeman has said: "In schizophrenia, therefore, the density of [11C] methylspiperone sites rises, reflecting an increase in monomers, while the density of [11C] raclopride sites remains the same, indicating that the total population of D₂ monomers and dimers does not change." (In another place Seeman has said methylspiperone possibly binds with dimers.) With this difference in measurement technique in mind, the above-mentioned meta-analysis uses results from 10 different ligands. Exaggerated ligand binding results such as SDZ GLC 756 (as used in the figure) were explained by reference to this monomer-dimer equilibrium.

According to Seeman, "...Numerous postmortem studies have consistently revealed D₂ receptors to be elevated in the striata of patients with schizophrenia". However, the authors were concerned the effect of medication may not have been fully accounted for. The study introduced an experiment by Anissa Abi-Dargham et al. in which it was shown medication-free live people with schizophrenia had more D₂ receptors involved in the schizophrenic process and more dopamine. Since then another study has shown such elevated percentages in D₂ receptors is brain-wide (using a different ligand, which did not need dopamine depletion). In a 2009 study, Abi-Dargham et al. confirmed the findings of her previous study regarding increased baseline D₂ receptors in people with schizophrenia and showing a correlation between this magnitude and the result of amphetamine stimulation experiments.

Some animal models of psychosis are similar to those for addiction – displaying increased locomotor activity. For those female animals with previous sexual experience, amphetamine stimulation happens faster than for virgins. There is no study on male equivalent because the studies are meant to explain why females experience addiction earlier than males.

Even in 1986 the effect of antipsychotics on receptor measurement was controversial. An article in Science sought to clarify whether the increase was solely due to medication by using drug-naive people with schizophrenia: "The finding that D₂ dopamine receptors are substantially increased in schizophrenic patients who have never been treated with neuroleptic drugs raises the possibility that dopamine receptors are involved in the schizophrenic disease process itself. Alternatively, the increased D₂ receptor number may reflect presynaptic factors such as increased endogenous dopamine levels (16). In either case, our findings support the hypothesis that dopamine receptor abnormalities are present in untreated schizophrenic patients." (The experiment used 3-N-[11C]methylspiperone – the same as mentioned by Seeman detects D₂ monomers and binding was double that of controls.)

It is still thought that dopamine mesolimbic pathways may be hyperactive, resulting in hyperstimulation of D₂ receptors and positive symptoms. There is also growing evidence that, conversely, mesocortical pathway dopamine projections to the prefrontal cortex might be hypoactive (underactive), resulting in hypostimulation of D₁ receptors, which may be related to negative symptoms and cognitive impairment. The overactivity and underactivity in these different regions may be linked, and may not be due to a primary dysfunction of dopamine systems but to more general neurodevelopmental issues that precede them. Increased dopamine sensitivity may be a common final pathway. Gründer and Cumming assert that of those living with schizophrenia and other dopaminergic related illnesses, up to 25% of these patients may appear to have dopaminergic markers within the normal range.

Another finding is a six-fold excess of binding sites insensitive to the testing agent, raclopride; Seeman said this increase was probably due to the increase in D₂ monomers. Such an increase in monomers may occur via the cooperativity mechanism which is responsible for D₂^High and D₂^Low, the supersensitive and lowsensitivity states of the D₂ dopamine receptor. More specifically, "an increase in monomers, may be one basis for dopamine supersensitivity".

Genetic and other biopsychosocial risk factors

Genetic evidence has suggested that there may be genes, or specific variants of genes, that code for mechanisms involved in dopamine function, which may be more prevalent in people experiencing psychosis or diagnosed with schizophrenia. Advanced technology has led to the possibility of performing Genome-Wide Association (GWA) studies. These studies identify frequently seen single nucleotide polymorphisms (SNP) that are associated with common, yet complex disorders. Genetic variants found due to GWA studies may offer insight concerning impairments in dopaminergic function. Dopamine-related genes linked to psychosis in this way include COMT, DRD4, and AKT1.

While genetics play an important role in the occurrence of schizophrenia, other biopsychosocial factors must also be taken into consideration. While focusing on the risk of schizophrenia in second generation migrants, Hennsler and colleagues relay that the dopamine hypothesis of schizophrenia may be an explanation. Some migrants who have had adverse experiences in their host country, such as racism, xenophobia, and poor living conditions, were found to have high stress levels, which increased dopaminergic neurotransmission. This increase in dopaminergic neurotransmission can be seen in the striatum and amygdala, both of which are areas in the brain that process aversive stimuli.

Evidence against the dopamine hypothesis

Further experiments, conducted as new methods were developed (particularly the ability to use PET scanning to examine drug action in the brain of living patients) challenged the view that the amount of dopamine blocking was correlated with clinical benefit. These studies showed that some patients had over 90% of their D₂ receptors blocked by antipsychotic drugs, but showed little reduction in their psychoses. This primarily occurs in patients who have had the psychosis for ten to thirty years. At least 90-95% of first-episode patients, however, respond to antipsychotics at low doses and do so with D₂ occupancy of 60-70%. The antipsychotic aripiprazole occupies over 90% of D₂ receptors, but this drug is both an agonist and an antagonist at D₂ receptors.

Furthermore, although dopamine-inhibiting medications modify dopamine levels within minutes, the associated improvement in patient symptoms is usually not visible for at least several days, suggesting that dopamine may be indirectly responsible for the illness.

Similarly, the second generation of antipsychotic drugs – the atypical antipsychotics – were found to be just as effective as older typical antipsychotics in controlling psychosis, but more effective in controlling the negative symptoms, despite the fact that they have lower affinity for dopamine receptors than for various other neurotransmitter receptors. More recent work, however, has shown that atypical antipsychotic drugs such as clozapine and quetiapine bind and unbind rapidly and repeatedly to the dopamine D₂ receptor. All of these drugs exhibit inverse agonistic effects at the 5-HT_2A/2C receptors, meaning serotonin abnormalities are also involved in the complex constellation of neurologic factors predisposing one to the self reinforcing language-based psychological deficits found in all forms of psychosis.

The excitatory neurotransmitter glutamate is now also thought to be associated with schizophrenia. Phencyclidine (also known as PCP or "Angel Dust") and ketamine, both of which block glutamate (NMDA) receptors, are known to cause psychosis at least somewhat resembling schizophrenia, further suggesting that psychosis and perhaps schizophrenia cannot fully be explained in terms of dopamine function, but may also involve other neurotransmitters.

Similarly, there is now evidence to suggest there may be a number of functional and structural anomalies in the brains of some people diagnosed with schizophrenia, such as changes in grey matter density in the frontal and temporal lobes. It appears, therefore, that there are multiple causes for psychosis and schizophrenia, including gene mutations and anatomical lesions. Many argue that other theories concerning the cause of schizophrenia may be more reliable in some cases, such as the glutamate hypothesis, GABA hypothesis, dysconnection hypothesis, and Bayesian inference hypothesis.

Psychiatrist David Healy has argued that drug companies have inappropriately promoted the dopamine hypothesis of schizophrenia as a deliberate and calculated simplification for the benefit of drug marketing.

Relationship with glutamate

Research has shown the importance of glutamate receptors, specifically N-methyl-D-aspartate receptors (NMDARs), in addition to dopamine in the etiology of schizophrenia. Abnormal NMDAR transmission may alter communication between cortical regions and the striatum. Mice with only 5% of the normal levels of NMDAR's expressed schizophrenic-like behaviors seen in animal models of schizophrenia while mice with 100% of NMDAR's behaved normally. Schizophrenic behavior in low NMDAR mice has been effectively treated with antipsychotics that lower dopamine. NMDAR's and dopamine receptors in the prefrontal cortex are associated with the cognitive impairments and working memory deficits commonly seen in schizophrenia. Rats that have been given a NMDAR antagonist exhibit a significant decrease in performance on cognitive tasks. Rats given a dopamine antagonist (antipsychotic) experience a reversal of the negative effects of the NMDAR antagonist. Glutamate imbalances appear to cause abnormal functioning in dopamine. When levels of glutamate are low dopamine is overactive and results in the expression schizophrenic symptoms.

Combined networks of dopamine, serotonin, and glutamate

Psychopharmacologist Stephen M. Stahl suggested in a review of 2018 that in many cases of psychosis, including schizophrenia, three interconnected networks based on dopamine, serotonin, and glutamate - each on its own or in various combinations - contributed to an overexcitation of dopamine D2 receptors in the ventral striatum.

Standard Libraries (CLI)

From Wikipedia, the free encyclopedia

https://en.wikipedia.org/wiki/Standard_Libraries_(CLI)

The Standard Libraries is a set of libraries included in the Common Language Infrastructure (CLI) in order to encapsulate many common functions, such as file reading and writing, XML document manipulation, exception handling, application globalization, network communication, threading, and reflection, which makes the programmer's job easier. It is much larger in scope than standard libraries for most other languages, including C++, and is comparable in scope and coverage to the standard libraries of Java.

The Standard Libraries are the Base Class Library (BCL), Runtime Infrastructure Library (both part of the kernel profile), Network Library, Reflection Library, XML Library (which with the first two listed libraries form the compact profile), Extended Array Library, Parallel Library, Floating Point Library and Vararg Library.

The Framework Class Library (FCL) is the original implementation of the Standard Libraries as the .NET Framework, which includes it, is the first implementation of the CLI.

Profiles

The main standard libraries are organized into two Standard Profiles, the Kernel Profile, and the Compact Profile. The following standard libraries do not belong to any profile: the Extended Array Library, the Extended Numerics Library, the Parallel Library and the Vararg Library.

Kernel Profile

The Kernel Profile is a subset of the Compact Profile. The Kernel Profile contains the Base Class Library (BCL) and Runtime Infrastructure Library.

Compact Profile

The Compact Profile contains those libraries in the Kernel Profile as well as the Network Library, the Reflection Library and the XML Library.

Libraries

Base Class Library

See also: Data types of the Base Class Library

The Base Class Library is a simple runtime library for modern programming languages. It serves as the Standard for the runtime library for the language C# as well as one of the CLI Standard Libraries. It provides types to represent the built-in data types of the CLI, simple file access, custom attributes, security attributes, string manipulation, formatting, streams, collections, among other things. It defines types in the following namespaces:

System

Defines the Object class which all reference type objects derive from (including value-type objects) and the ValueType class which all value type objects derive from. It also defines the base data types like integers, floating point numbers, character, strings, Boolean, enumeration and more. Support for the environment and platform and a command-line interface is provided along with base classes for exceptions and attributes. It defines arrays and delegates, mathematical functions and many other types.

System.Collections

Defines many common container types used in programming, such as dictionaries, hashtables, lists, queues and stacks.

System.Collections.Generic

Defines generic types of the container types in the System.Collections namespace.

System.Diagnostics

Defines types that provide the ability to diagnose applications. It includes event logging, performance counters, tracing and interaction with system processes.

System.Globalization

Defines types that define culture-related information, including language, country/region, calendars in use, format patterns for dates, currency and numbers and sort order for strings.

System.IO

Defines type that enable reading from and writing to different streams, such as files or other data streams. Also provides a connection to the file system.

System.Security

Defines types that represent the security system and permissions.

System.Security.Permissions

Defines types that control access to operations and resources based on policy.

System.Text

Defines types that support various character encodings, regular expressions and a more efficient mechanism for manipulating strings.

System.Threading

Defines types that enable multithreaded programming.

UML package diagram of the stream hierarchy in .NET

Runtime Infrastructure Library

See also: Data types of the Runtime Infrastructure Library

The Runtime Infrastructure Library provides the services needed by a compiler to target the CLI and the facilities needed to dynamically load types from a stream in a specified file format. It defines types in the following namespaces:

System

Defines types for the application domain, pointers, handles and more.

System.Reflection

Defines types that provide a managed view of loaded types, methods and fields, and that can dynamically create and invoke types. These types are relevant to the program runtime.

System.Runtime.CompilerServices

Defines types that provide functionality for compiler writers who use managed code to specify attributes in metadata that affect the run-time behavior of the Virtual Execution System.

System.Runtime.InteropServices

Defines types that support Platform Invocation Services (P/Invoke).

Network Library

See also: Data types of the Network Library

The Network Library provides simple networking services including direct access to network ports as well as HTTP support. It defines types in the following namespaces:

System

Defines types that provide an object representation of a uniform resource identifier (URI) and easy access to the parts of the URI.

System.Collections.Specialized

Defines specialized and strongly-typed collections; for example, a linked list dictionary, a bit vector, and collections that contain only strings.

System.Net

Defines types that provide a simple programming interface for a number of network protocols.

System.Net.Sockets

Defines type that provide a managed implementation of the Windows Sockets (Winsock) interface for developers who need to tightly control access to the network.

Reflection Library

See also: Data types of the Reflection Library

The Reflection Library provides the ability to examine the structure of types, create instances of types and invoke methods on types, all based on a description of the type. It defines types in the following namespaces:

System

Defines the void type, a return value type for a method that does not return a value.

System.Globalization

Defines type that provide information about a specific culture (called a locale for unmanaged code development). The information includes the names for the culture, the writing system, the calendar used and formatting for dates and sort strings.

System.Reflection

Defines types that provide a managed view of loaded types, methods and fields, and that can dynamically create and invoke types.

System.Security.Permissions

Defines types that control access to operations and resources based on policy. These types are relevant to the reflection.

XML Library

See also: Data types of the XML Library

The XML Library provides a simple "pull-style" parser for XML. It is designed for resource-constrained devices, yet provides a simple user model. It defines types in the following namespace.

System.Xml

Defines types for processing XML.

Extended Array Library

See also: Data types of the Extended Array Library

The Extended Array Library provides support for non-vector arrays. That is, arrays that have more than one dimension or arrays that have non-zero lower bounds. The Extended Array Library doesn't add any extra types, but it does extend the array-handling mechanism.

Extended Numerics Library

See also: Data types of the Extended Numerics Library

The Extended Numerics Library provides support for floating-point (System.Single, System.Double) and extended-precision (System.Decimal) data types. Like the Base Class Library, this library is directly referenced by the C# standard.

Parallel Library

See also: Data types of the Parallel Library

The Parallel Library provides easy parallelism for non-expert programmers, so that multithreaded CPUs can be exploited.

Vararg Library

See also: Data types of the Vararg Library

The Vararg Library provides support for dealing with variable-length argument lists.