Whole exome sequencing links dental tumor to an autosomal-dominant mutation in ANO5 gene associated with gnathodiaphyseal dysplasia and muscle dystrophies

Tumors of the jaws may represent different human disorders and frequently associate with pathologic bone fractures. In this report, we analyzed two affected siblings from a family of Russian origin, with a history of dental tumors of the jaws, in correspondence to original clinical diagnosis of cementoma consistent with gigantiform cementoma (GC, OMIM: 137575). Whole exome sequencing revealed the heterozygous missense mutation c.1067G \u3e A (p.Cys356Tyr) in ANO5 gene in these patients. To date, autosomal-dominant mutations have been described in the ANO5 gene for gnathodiaphyseal dysplasia (GDD, OMIM: 166260), and multiple recessive mutations have been described in the gene for muscle dystrophies (OMIM: 613319, 611307); the same amino acid (Cys) at the position 356 is mutated in GDD. These genetic data and similar clinical phenotypes demonstrate that the GC and GDD likely represent the same type of bone pathology. Our data illustrate the significance of mutations in single amino-acid position for particular bone tissue pathology. Modifying role of genetic variations in another gene on the severity of the monogenic trait pathology is also suggested. Finally, we propose the model explaining the tissue-specific manifestation of clinically distant bone and muscle diseases linked to mutations in one gene

日本語の二重目的語構文の基本語順について

National Institute for Japanese Language and LinguisticsMonash UniversityKeio University会議名: 言語資源活用ワークショップ2018, 開催地: 国立国語研究所, 会期: 2018年9月4日-5日, 主催: 国立国語研究所 コーパス開発センター本稿では日本語の二重目的語構文の基本語順について予測する統計モデルについて議論する。『現代日本語書き言葉均衡コーパス』コアデータに係り受け構造・述語項構造・共参照情報を悉皆付与したデータから、二重目的語構文を抽出し、格要素と述語要素に分類語彙表番号を付与したうえで、ベイジアン線形混合モデルにより分析を行った。結果、名詞句の情報構造の効果として知られている旧情報が新情報よりも先行する現象と、モーラ数が多いものが少ないものに先行する現象が確認された。分類語彙表番号による効果は、今回の分析では確認されなかった

Online Processing of Wh-Dependencies in English by Native Speakers of Spanish

This study investigated if, Spanish-speaking learners of English are capable of processing wh-dependencies incrementally and observing the grammatical constraints that regulate wh-extraction in English, similar to native speakers. The study included two self-paced reading experiments run in a word-by-word non-cumulative moving window paradigm (Just et al., 1982). Experiment 1 tested if second language (L2) learners process wh-dependencies incrementally by looking at wh-extraction from positions licensed by the grammar. Experiment 2 focused on testing if learners respect syntactic constraints that forbid wh-extraction from positions not licensed by the grammar, to be specific, extraction out of relative clause islands. The data collected in both experiments were subject to a residual reading times analysis. The results of the two experiments suggest that Spanish-speaking learners of English process wh-dependencies incrementally and that they abide by grammatical constraints in the course of online processing which prevent them from extracting a wh-element outside of a relative clause island. At the theoretical level, our findings suggest that the claim of the Shallow Structures Hypothesis (Clahsen & Felser, 2006 a,b) that adult second language learners are `shallow processors' who do not have access to abstract syntax during parsing is too strong

Spartan Daily, September 21, 1995

Volume 105, Issue 15https://scholarworks.sjsu.edu/spartandaily/8730/thumbnail.jp

Individual Differences in Comprehending Japanese Scrambled Sentences

This study’s aim is to investigate further into the relationship between individual differences—working memory and sound recognition ability—and sentence processing of Japanese scrambled sentences for second language (L2) Japanese learners. L2 Japanese learners drawn from 3rd year college-level courses or above were tested on their listening comprehension accuracy in identifying case marking particles in canonical and scrambled sentences. Participants demonstrated a significant slowdown in reaction time and low accuracy rates for scrambled sentences compared with canonical sentences. In addition, even participants with high working memory and proficiency had difficulty in comprehending scrambled sentences and could not process case markings efficiently and accurately in a timed setting. This study is significant in that it is one of the first to examine the relationship between individual differences and comprehending Japanese case markings

Mustang Daily, September 24, 1990

Student newspaper of California Polytechnic State University, San Luis Obispo, CA.https://digitalcommons.calpoly.edu/studentnewspaper/5194/thumbnail.jp

Automating Pharmacokinetic Predictions in \u3cem\u3eArtemisia\u3c/em\u3e

Pharmacokinetics (PK) is the time course of a compound in the body that is dependent on mechanisms of absorption, distribution, metabolism, and excretion or ADME. A thorough understanding of PK is essential to predict the consequences of organisms exposed to chemicals. In medicine, predictions of PK of drugs allows us to properly prescribe drug treatments. In toxicology, PK allows us to predict the potential exposure of environmental contaminants and how they may affect organisms at the time of exposure or in the future. Chemical ecology could benefit from computational predictions of PK to better understand which plants are consumed or avoided by wild herbivores. A limitation in computational predictions of PK in chemical ecology is the large quantities of biodiverse natural products involved in complex plant-herbivore-microbial interactions compared to biomedical and environmental toxicology studies that focus on a select number of chemicals. The objective of this research was to automate the process of mining predicted PK of known chemical structures in plants consumed by herbivores and to use predicted PK output to test hypotheses. The first hypothesis is that because monoterpenes are smaller in molecular weight and have relatively high lipophilicity when compared to phenolics and sesquiterpenes, they would have higher absorption, be more likely to be substrates for efflux transporters that regulate absorption, and be more likely to inhibit metabolizing enzymes than phenolics and sesquiterpenes. The second hypothesis is that monoterpenes that are induced or avoided by foraging herbivores would have higher absorption, be less likely to be substates for efflux transporters, and be more likely to inhibit metabolizing enzymes compared to the individual monoterpenes that are not induced or avoided by herbivores. This automated approach used Python packages to obtain chemical notations from the PubChem website and mine predicted PK information for chemical input from the SwissADME website. The PK output from SwissADME was analyzed using ANOVAs to test for differences in molecular weight and lipophilicity among chemical classes (monoterpenes, phenolics, and sesquiterpenes). Chi-squared tests were used to assess if chemical groups had high or low absorption, were substrates of efflux transporters, or inhibited metabolizing enzymes. Mined PK data for chemicals can be used to understand drug-drug interactions in pharmacology, predict exposure to environmental contaminants in toxicology, and identify mechanisms mediating plant-microbe-herbivore interactions. However, the broad benefits of mining predicted PK across disciplines requires a workforce with competency in chemistry, physiology, and computing who can validate the automation process and test hypotheses relative to different disciplines. Course-based and Lab-based Undergraduate Research Experiences (CUREs and LUREs) have been proven to not only improve grades but also increase engagement diversity and inclusion. As a graduate teaching assistant, I created and taught a PK LURE module in an undergraduate Animal Physiology and Nutrition course to create a sustainable quality control step to validate input of chemical structures and PK output generated from the automated process. The course simultaneously provided students with an authentic research experience where they integrated chemistry, pharmacology, computing, public databases, and literature searches to propose and test new hypotheses. Students gained indispensable interdisciplinary research skills that can be transferred to jobs in veterinary and human medicine, pharmaceutics, and natural sciences. Moreover, undergraduates used existing and new PK data to generate and test novel hypotheses that go beyond the work of any single graduate student or discipline. Overall, the integration of computing and authentic research experiences has advanced the research capacity of a diverse workforce who can predict exposure and consequences of chemicals in organisms

Molecular simulations on proteins of biomedical interest : A. Ligand-protein hydration B. Cytochrome P450 2D6 and 2C9 C. Myelin associated glycoprotein (MAG)

TOPIC 1: Water molecules mediating polar interactions in ligand–protein complexes contribute to both binding affinity and specificity. To account for such water molecules in computer-aided drug discovery, we performed an extensive search in the Cambridge Structural Database (CSD) to identify the geometrical criteria defining interactions of water molecules with ligand and protein. In addition, ab initio calculations were used to derive the propensity of ligand hydration. Based on these information we developed an algorithm (AcquaAlta) to reproduce water molecules bridging polar interactions between ligand and protein moieties. This approach was validated using 20 crystal structures and yielded a match of 76% between experimental and calculated water positions. The solvation algorithm was then applied to the docking of oligopeptides to the periplasmic oligopeptide binding protein A (OppA), supported by a pharmacophore-based alignment tool. TOPIC 2: Drug metabolism, toxicity, and interaction profile are major issues in the drug discovery and lead optimization processes. The Cytochromes P450 (CYPs) 2D6 and 2C9 are enzymes involved in the oxidative metabolism of a majority of the marketed drugs. By identifying the binding mode using pharmacophore pre-alignement and automated flexible docking, and quantifying the binding affinity by multi-dimensional QSAR, we validated a model family of 56 compounds (46 training, 10 test) and 85 (68 training, 17 test) for CYP2D6 and CYP2C9, respectively. The correlation with the experimental data (cross- validated r2 = 0.811 for CYP2D6 and 0.687 for CYP2C9) suggests that our approach is suited for predicting the binding affinity of compounds towards the CYP2D6 and CYP2C9. The models were challenged by Y-scrambling, and by testing an external dataset of binding compounds (15 compounds for CYP2D6 and 40 for CYP2C9) and not binding compounds (64 compounds for CYP2D6 and 56 for CYP2C9). TOPIC 3: After injury, neurites from mammalian adult central nervous systems are inhibited to regenerate by inhibitory proteins such as the myelin-associated glycoprotein (MAG). The block of MAG with potent glycomimetic antagonists could be a fruitful approach to enhance axon regeneration. Libraries of MAG antagonists were derived and synthesized starting from the (general) sialic acid moiety. The binding data were rationalized by docking studies, molecular dynamics simulations and free energy perturbations on a homology model of MAG. The pharmacokinetic profile (i.e. stability in cerebrospinal fluid, logD, and blood-brain barrier permeation) of these compounds has been thoroughly investigated to evaluate the drug-likeness of the identified antagonists