A-PVT

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We introduce a linguistically motivated approach based on patterns defined over the constituency and dependency parse trees of sentences. Besides the presence of a relation between a pair of brain regions, the proposed method also identifies the directionality of the relation, which enables the creation and analysis of a directional brain region connectivity graph. The approach is evaluated over the manually annotated data sets of the WhiteText Project. In addition, as a case study, the method is applied to extract and analyze the connectivity graph of PVT, which is an important brain region that is considered to influence many functions ranging from arousal, motivation, and drug-seeking behavior to attention. The results of the PVT connectivity graph show that PVT may be a new target of research in mood assessment.

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α-Pyrro​lidino​pentio​thiophenone ((PVT) is a synthetic stimulant of the cathinone class that has been sold online as a designer drug. It is an analogue of α-PVP where the phenyl ring has been replaced by thiophene. α-PVT was first identified in Japan in 2013. Its metabolism has been described in literature.Stimulants excite the nervous system and increase physiological function.

N-Pyrrolidinyl-cathinones, like pyrovalerone are designer drugs which act as stimulants. Pyrovalerone is an inhibitor of the transporters for certain monoamine neurotransmitters, including dopamine and norepinephrine, preventing their uptake. α-Pyrrolidinopentiothiophenone is an analog of pyrovalerone in which the benzene ring has been replaced with a thiophene ring. Like pyrovalerone, this compound is expected to be a psychoactive stimulant. Its neurotoxic potential is unknown. This product is intended for forensic and research applications.

Identifying the relations among different regions of the brain is vital for a better understanding of how the brain functions. While a large number of studies have investigated the neuroanatomical and neurochemical connections among brain structures, their specific findings are found in publications scattered over a large number of years and different types of publications. Text mining techniques have provided the means to extract specific types of information from a large number of publications with the aim of presenting a larger, if not necessarily an exhaustive picture. By using natural language processing techniques, the present paper aims to identify connectivity relations among brain regions in general and relations relevant to the paraventricular nucleus of the thalamus (PVT) in particular.

he PVT corpus is used in two different ways during the evaluation. The abstracts of 451 publications (for which the full text was not publicly available) and 107 publicly available full text publications constituted the first data set and provided the basis for our application on the PVT case study. Secondly, 14 of these full text papers were selected by neuroscience domain experts and fully annotated with brain region mentions and connectivity statements. These 14 papers were selected randomly from a set of publications, which were known to be PVT related and included review papers. As the annotation guideline, we applied three steps. First, all brain region entities mentioned in the articles were annotated without regard to connectivity. Then all types of relations including neuroanatomical, neurochemical, and functional connections were marked. Lastly, we identified and evaluated only the neuroanatomical relations at the sentence level, when the text specifically mentioned identifiable connectivity between brain structures. Table 1 shows sample sentences from the annotated PVT corpus.

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