bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Correlation between Maternal Age and Fetal Sex Chromosome Aneuploidies: A 8-year Single Institution Experience in China
Authors: Hongge Li , Jin Jinglei 
Published: December 2020

Abstract
Background: Although a few studies have investigated the association between maternal age and fetal sex chromosome aneuploidies (SCAs), most of these studies were limited to advanced age women and the results were conflicting. This study aimed to investigate maternal age-specific rates for common fetal SCAs (including 45,X, 47,XXY, 47,XXX and 47,XYY) in pregnant women of different ages that not only limited to advanced age women. We retrospectively investigated a 8-year experience of prenatal diagnosis for fetal chromosome aberrations by second-trimester amniocentesis at a university teaching hospital in China. 20,409 amniotic fluid specimens collected at 19–22+6 gestational weeks were included in this study. The women were categorized into five age groups (≤23, 24-28, 29-33, 34-38, 39+ years) based on maternal age at the time of amniocentesis and entered as a categorical variable in all samples. The correlation between fetal SCAs and maternal age was determined using the logistic regression analysis. A chi-square test was performed to compare the incidence of fetal SCAs among age groups. Results: A total of 179 cases of fetal SCAs were detected, and the incidence was 8.77‰ (about 1/114). The incidence of all SCAs increased significantly with advancing maternal age (SE, 0.014; odds ratio, 1.044; P=0.002), from 5.81 per 1,000 fetuses at the 24-28 years to 10.92 per 1,000 at the 39+ years. The incidence of all SCAs was also significantly different among age groups (χ2=10.197, P=0.037<0.05). Specifically, the incidence of 45,X (SE, 0.037; odds ratio, 0.916; P=0.017) and 47,XXY (SE, 0.024; odds ratio, 1.127; P=0.000) had significant correlation with maternal age, while the incidence of 47,XXX and 47,XYY had no correlation with maternal age (P=0.473; P=0.272, respectively). Conclusions: Maternal age was ascertained to be a strong risk factor for fetal SCAs.
A Novel&nbsp;Missense Mutation in NALCN&nbsp;cause CLIFAHDD Syndrome&nbsp;and Prenatal&nbsp;Diagnosis&nbsp;in China
Authors: Li Yuping , Zhou Chenglong , Chen Yangran , Shi Haihong , Chen Qiang , Li Ning , Zeng Qinlong , Hong Yan , Li Qing , Deng Choufen , Zhou Feng , Tan Jieliang , Yang Mei , Li Qiuli , Yang Yingsong , Feng Jianjiang , Sun Shuxiang , Tang Ziqian , Luo Liangping , Tang Jia 
Published: December 2020

Abstract
Background : CLIFAHDD is caused by mutation in NALCN and characterized by facial malformation, hypotonia, and developmental delay. Recently rare mutations in NALCN associated with of CLIFAHDD syndrome have been reported. Methods : Whole exome sequencing (WES) was applied to a diagnosis suspected CLIFAHDD syndrome proband based on clinical symptoms. Blood samples were taken from the parents of the proband for co-segregation analysis using Sanger sequencing. In addition, prenatal gene diagnosis was performed to the family. Finally bioinformatics analysis was utilized to predict the pathogenesis of novel variant. Result : We reported a 24-hour-old proband with a novel missense variant c.3016G>T (p.Val1006Phe) in NALCN by WES. The proband showed clinical symptoms of head abnormalities, neck shortage, thumbs adduction, positional foot deformities and elbows contracture. Prenatal diagnosis revealed that the proband’s sibling did not carry c.3016G>T. Conclusion : Our findings indicate c.3016G>T is a novel pathogenic mutation, while extending new phenotype CLIFAHDD syndrome and enriching the mutation spectrum of the NALCN gene.
Identification of an Anti-Plant-Virus Molecule in Alpinia Zerumbet
Authors: Hatanaka Tadashi , Narusaka Mari , Uraji Misugi , Yamaji Yasuyuki , Narusaka Yoshihiro 
Published: December 2020

Abstract
In plants, viral diseases are second only to fungal diseases in terms of occurrence, causing substantial damage to agricultural crops. The aqueous extract of Alpinia zerumbet exhibits inhibitory effect against virus infection in Solanaceae members. In this study, we isolated an anti-plant-virus molecule from the extract using a conventional method of a combination of reversed phase column chromatography, dialysis, and lyophilization. The anti-plant-virus molecule was identified as proanthocyanidin, which mostly consisted of epicatechin and showed more than 40 degrees of polymerization.
Nonadditivity in Public and Inhouse Data – Implications for Drug Design
Authors: Gogishvili Dea , Nittinger Eva , Margreitter Christian , Tyrchan Christian 
Published: December 2020

Abstract
Numerous ligand-based drug discovery projects are based on structure-activity relationship (SAR) analysis, such as Free-Wilson (FW) or matched molecular pair (MMP) analysis. Intrinsically they assume linearity and additivity of substituent contributions. These techniques are challenged by nonadditivity (NA) in protein-ligand binding where the change of two functional groups in one molecule results in much higher or lower activity than expected from the respective single changes. Identifying nonlinear cases and possible underlying explanations is crucial for a drug design project since it might influence which lead to follow. By systematically analyzing all AstraZeneca (AZ) inhouse compound data and publicly available ChEMBL25 bioactivity data, we show significant NA events in almost every second assay among the inhouse and once in every third assay in public data sets. Furthermore, 9.4% of all compounds of the AZ database and 5.1% from public sources display significant additivity shifts indicating important SAR features or fundamental measurement errors. Using NA data in combination with machine learning showed that nonadditive data is challenging to predict and even the addition of nonadditive data into training did not result in an increase in predictivity. Overall, NA analysis should be applied on a regular basis in many areas of computational chemistry and can further improve rational drug design.
ChemTables: A Dataset for Semantic Classification of Tables in Chemical Patents
Authors: Zhai Zenan , Druckenbrodt Christian , Thorne Camilo , Akhondi Saber A , Nguyen Dat Quoc , Cohn Trevor , Verspoor Karin 
Published: December 2020

Abstract
Chemical patents are a commonly used channel for disclosing novel compounds and reactions, and hence represent important resources for chemical and pharmaceutical research. Key chemical data in patents is often presented in tables. Both the number and the size of tables can be very large in patent documents. In addition, various types of information can be presented in tables in patents, including spectroscopic and physical data, or pharmacological use and effects of chemicals. Since images of Markush structures and merged cells are commonly used in these tables, their structure also shows substantial variation. This heterogeneity in content and structure of tables in chemical patents makes relevant information difficult to find. We therefore propose a new text mining task of automatically categorising tables in chemical patents based on their contents. Categorisation of tables based on the nature of their content can help to identify tables containing key information, improving the accessibility of information in patents that is highly relevant for new inventions. For developing and evaluating methods for the table classification task, we developed a new dataset, called ChemTables, which consists of 7,886 chemical patent tables with labels of their content type. We introduce this data set in detail. We further establish strong baselines for the table classification task in chemical patents by applying state-of-the-art neural network models developed for natural language processing, including TabNet, ResNet and Table-BERT on ChemTables. The best performing model, Table-BERT, achieves a performance of 88.66 micro F1 score on the table classification task. Availability: A 10% sample of the ChemTables dataset has been made publicly available, subject to a data usage agreement.
AR&nbsp;Deficiency Inhibits LPS-induced M1 Response in Macrophages by Activating Autophagy
Authors: Cheng Peng , Xie Jianwei , Liu Zhiyong , Wang Jian 
Published: December 2020

Abstract
Macrophage M1 polarization mediates inflammatory responses and tissue damage. Recently, aldose reductase (AR) has been shown to play a critical role in of M1 polarization in macrophages. However, the underlying mechanisms are unknown. Here, we demonstrated, for the first time, that AR deficiency repressed the induction of inducible nitric oxide synthase in lipopolysaccharide (LPS)-stimulated macrophages via activation of autophagy. This suppression was related to a defect in the inhibitor of nuclear factor κB (NF-κB) kinase (IKK) complex in the classical NF-κB pathway. However, the mRNA levels of the IKKβ and IKKγ were not reduced in LPS-treated AR knockout (KO) macrophages, indicating that their proteins were downregulated at the post-transcriptional level. We discovered that LPS stimuli induced the recruitment of more beclin1 and increased autophagosome formation in AR-deficient macrophages. Blocking autophagy by 3-methyladenine and ammonium chloride treatment restored IKKβ and IKKγ protein levels and increased nitric oxide synthase production in LPS-stimulated AR-deficient macrophages. More assembled IKKβ and IKKγ undergo ubiquitination and recruit the autophagic adaptor p62 in LPS-induced AR KO macrophages, promoting their delivery to autophagosomes and lysosomes. Collectively, these findings suggest that AR deficiency involves in the regulation of NF-κB signaling, and extends the role of selective autophagy in ﬁne-tuned M1 macrophage polarization.
Acteoside Repressed Microglia M1 Polarization Through Inhibited NF-κB Signalling Pathway and AMPK-Mediated Mitochondria Function Recovery
Authors: Li Ying-Qi , Chen Yi , Jiang Si-Qi , Shi Yuan-Yuan , Jiang Xiao-Li , Wu Shan-Shan , Zhou Ping , Wang Hui-Ying , Li Ping , Li Fei 
Published: December 2020

Abstract
Background: Alzheimer's disease (AD) is the most frequent type of dementia. While acteoside (ACT), a compound isolated from Cistanche tubulosa, possesses neuroprotective properties. However, the underlying mechanism in regulating microglia polarization remains ill-defined. Methods: Herein, AlCl3-induced AD model in zebrafish larvae was applied to uncover the therapeutic efficacy of ACT. BV-2 cells were used to demonstrate the role of ACT on microglia polarization. RNA-Sequence, HPLC-Q-TOF-MS, western blot and molecular docking were combined to confirm its mechanism. Results: ACT significantly ameliorated the experimental dyskinesia and nervous system disorders in zebrafish. Subsequently, it suppressed M1 polarization and promoted to the M2 phenotype in LPS-induced BV-2 cells. We first demonstrated that ACT exerted profound transcriptomic impact, which involved regulation of key signaling pathways in inflammation, arginine biosynthesis, as well as pantothenate and CoA biosynthesis, correlating with mitochondria function. ACT treatment reduced microglia M1 polarization by inhibiting the NF-κB signalling pathway. And the metabolic pathways were further confirmed by HPLC-Q-TOF-MS. In addition, ACT rectified excessive ROS to restore mitochondria function through AMPK-mediated PGC-1α and UCP-2 upregulation, consistent with metabolic changes. Intriguingly, ACT may directly bind to both NF-κB and AMPKα, as evidenced by molecular docking. Conclusions: The research provided an infusive mechanism of ACT and illustrated a new perspective based on mitochondrial dysfunction to reveal the connection between metabolism and microglia polarization.
Carbon Status and Regression Model for Tree Carbon by Crown Cover for Sal Forest of Nepal
Authors: Paudel Prashant , Kalakheti Rupesh , Maraseni Tek 
Published: December 2020

Abstract
Background: Volume, biomass and carbon of forest ecosystem are generally estimated using lookup tables or allometric equations known as models. These general equation-based models are usually exclusively based on dimensional measurement such as diameter at breast height (DBH) and/or height, which sometimes makes it difficult to judge applicability of equation to given forest condition or types. It is therefore important to estimate carbon stock and develop models to predict biomass or carbon stock with stratification by categorical variables like crown cover, slope, forest types, etc. Stratification of forest by remote sensing approach while designing forest inventory not only improves the reliability of the estimation but also reduces the cost of measurement and uncertainty in estimation. Taking crown coverage (<25%, 25-50%, 50-75% and >75%) and slope (0-8.5%, 8.5-19%, 19-31% and >31%) as a categorical variable, this study assessed the status of carbon stock and develop a regression model to predict carbon stock for each canopy class of Sal (Shorea robusta) forest in Nepal. DBH and height were measured for trees with more than 7 cm DBH in 82 sample plots (18, 22, 22 and 20 for <25%, 25-50%, 50-75% and >75 % respectively).Results: On average 297 stands per hectare were recorded with 94.80 m3/ha growing stock. Carbon stock was highest for >75% crown cover class (89.83 ton C/ha) and lowest for <25% crown cover class (27.47 ton C/ha) with average 60.41 ton C/ha, where per tree carbon stock was lowest in crown cover class 25-50% (0.16 ton C/tree). TukeyHSD shows that four pairs of crown cover classes have significant difference in carbon stock at 95% confidence interval. However, with increase in slope carbon stock per hectare was decreasing. Regression model with natural logarithm of DBH2 and total tree height (i.e. log transformed polynomial equation) was best fitted for estimation of carbon stock per tree in different crown cover class with adjusted R2 >0.99 and residuals were normally distributed. Conclusions: Adjustment of model (natural logarithm of DBH2 and height) with high accuracy (R2 >0.99) shows the importance of stratification especially by crown cover for accurate estimation of carbon stock for optimization of carbon benefits.
Exploration of Binary Protein-Protein Interactions Between Tick-Borne Flaviviruses and Ixodes Ricinus
Authors: LEMASSON Manon , CAIGNARD Grégory , UNTERFINGER Yves , ATTOUI Houssam , BELL-SAKYI Lesley , HIRCHAUD Edouard , MOUTAILLER Sara , JOHNSON Nicholas , VITOUR Damien , RICHARDSON Jennifer , LACOUR Sandrine A. 
Published: December 2020

Abstract
BackgroundLouping ill virus (LIV) and tick-borne encephalitis virus (TBEV) are tick-borne flaviviruses that are both transmitted by the major European tick, Ixodes ricinus. Despite the importance of I. ricinus as an arthropod vector, its capacity to acquire and subsequently transmit viruses, known as vector competence, is poorly understood. At the molecular scale, vector competence is governed in part by binary interactions established between viral and cellular proteins within infected tick cells.MethodsTo investigate virus-vector protein-protein interactions (PPIs), the entire set of open reading frames for LIV and TBEV was screened against an I. ricinus cDNA library established from three embryonic tick cell lines using yeast two-hybrid methodology (Y2H). PPIs revealed for each viral bait were retested in yeast by applying a gap repair (GR) strategy and notably against the cognate protein of both viruses, to determine whether the PPIs were specific for a single virus or common to both. The interacting tick proteins were identified by automatic BLASTX and in silico analyses were performed to expose the biological processes targeted by LIV and TBEV.ResultsFor each virus, we identified 24 different PPIs involving six viral proteins and 22 unique tick proteins, with all PPIs being common to both viruses. According to our data, several viral proteins (pM, M, NS2A, NS4A, 2K and NS5) target multiple tick protein modules implicated in critical biological pathways. Of note, the NS5 and pM viral proteins establish PPI with several tumor necrosis factor (TNF) receptor-associated factor (TRAF) proteins, which are essential adaptor proteins at the nexus of multiple signal transduction pathways.ConclusionWe provide the first description of the TBEV/LIV-I. ricinus PPI network, and indeed of any PPI network involving a tick-borne virus and its tick vector. While further investigation will be needed to elucidate the role of each tick protein in the replication cycle of tick-borne flaviviruses, our study provides a foundation for understanding the vector competence of I. ricinus at the molecular level. Indeed, certain PPIs may represent molecular determinants of vector competence of I. ricinus for TBEV and LIV, and potentially for other tick-borne flaviviruses.
Hypoxic ADSCs-derived EVs&nbsp;Promote the Proliferation and Chondrogenic Differentiation of Cartilage Stem/progenitor Cells
Authors: xue ke , Jiang Yongkang , Zhang Xiaodie , Wu Jun , Qi Lin , Liu Kai 
Published: December 2020

Abstract
Background： Cartilage tissue engineering is a promising option for repairing cartilage defects caused by trauma, inflammation and osteoarthritis, although harvesting a large number of seeding cells with stable phenotypes remains a major challenge. Cartilage stem/progenitor cells (CSPCs) seem to be a promising cell source. Hypoxic extracellular vesicles secreted by mesenchymal stem cells may play a major role in cell-cell and tissue-tissue communication by transporting various RNAs and proteins in mesenchymal stem cell-based therapy. In the current study, we aimed to evaluate the effect of hypoxic adipose-derived stem cells (ADSCs)-derived extracellular vesicles (EVs) on CSPCs proliferation and differentiation. Methods: The characteristics of ADSCs-derived EVs were identified by and flow cytometric analysis. Proliferation, migration, and cartilage-related gene expression of CSPCs were measured with or without the presence of hypoxic ADSCs-derived EVs. The effect of ADSC-derived EVs on CSPCs were evaluated in alginate hydrogel culture, and SEM, histological staining, biochemical and biomechanical analysis were performed to evaluate the effect of hypoxic ADSCs-derived EVs on CSPCs in alginate hydrogel culture. Results: The results indicated that the majority of ADSC-derived EVs exhibited a round-shaped or cup-shaped morphology with a diameter of 40–1000 nm and expressed CD9, CD63, and CD81. CSPCs migration and proliferation were enhanced by hypoxic ADSCs-derived EVs, which also increased the expression of cartilage-related genes. The hypoxic ADSCs-derived EVs induced CSPCs to produce significantly more cartilage matrix and proteoglycan. Conclusions: The present study indicated that hypoxic ADSCs-derived EVs improved the proliferation and chondrogenic differentiation of CSPCs for cartilage tissue engineering.
Geomineralogical, Physiochemical, Thermal and Kinetic Characterisation of Selected Coals From the Benue Trough and Anambra Basins in Nigeria
Authors: Nyakuma Bemgba B. , Jauro Aliyu , Akinyemi Segun A. , Wong Syie L. , Oladokun Olagoke , Abdullah Tuan Amran T. 
Published: December 2020

Abstract
This study examined the geomineralogical, physiochemical, thermal, and kinetic characteristics of selected coals from Chikila (CHK), Lafia Obi (LFB) and Okaba (OKB) in the Benue Trough and Anambra Basins of Nigeria. Physicochemical characterisation revealed significant quantities of carbon, volatiles, fixed carbon, and heating values (25–30 MJ/kg) but low moisture, and ash contents. The fuel properties indicate subbituminous to bituminous rank coals. The morphological, microstructure and elemental analyses revealed heterogeneous sized coal particles with a glassy sheen due to clay and aluminosilicate minerals such as quartz, alumina, kaolinite, and hematite. Based on thermal analysis, the coal samples are highly reactive and experienced significant thermal degradation as evident in the high mass losses (ML = 91.59 – 94.04%) and low residual masses (RM = 5.96% - 8.41%), which are observed in the orders LFB > OKB > CHK for ML and CHK > OKB > LFB for RM. LFB experienced the highest ML and lowest RM indicating it is more thermally reactive compared to OKB and CHK. Kinetic analysis by Coats-Redfern model revealed low values of activation energy, Ea (30.07 – 43.91) kJ/mol and frequency factor A (1.16×10-02 – 6.73×10-02) min-1 deduced at high R2 (0.98-0.99). The kinetic parameters demonstrated that the selected coal samples are highly reactive under oxidative conditions which are suited for energy recovery through pulverised coal combustion.
An Analysis of Economic Burden of Hypertensive Patients Based on “System of Health Accounts 2011” and Multiple Layer Perceptron Neural Network
Authors: Liu Guojie , Ji Xinyu , Yang Jingou , Zhu Yalan , Wang Leying , Wang Xin 
Published: December 2020

Abstract
Background: Hypertension requires long-term treatment and medication, which not only affects people’s health, but also brings heavy economic burden for families and society. Therefore, it is meaningful to reveal the actual personal and socio-economic burdens of hypertension based on a tool recognized internationally to improve management of hypertensive patients and provide more information for policy makers, analysts, and international comparisons. Methods: We collected expense records of 180441 hypertensive outpatients and 14763 inpatients in Shanxi Province of China in 2017. Curative care expenditure for hypertension(CCEht) were analyzed based on System of Health Accounts 2011, and influencing factors were analyzed by multiple layer perceptron (MLP) neural network.Results: In 2017, CCEht was US$ 307.71 million, accounted for 3.63% of the total CCE and 0.14% of GDP in Shanxi Province of China. CCE of hypertensive outpatients (CCEht-out) and inpatients (CCEht-in) accounted for 44.49% and 55.51% of the CCEht, drug fee accounted for 81.55% of CCEht-out and 22.50% of CCEht-in, respectively. CCEht increased from the age of 30, and the highest occured in age 60-69. The patients with the age of 40-79 accounted for 86.49% of total CCEht. CCEht of male patients were generally higher than that of female, and there is a significant difference between CCEht for male and female in terms of age. The diagnosis and treatment capacity of primary health care system had been enhanced. New rural cooperation medical insurance and urban employee basic medical insurance had the trend of overusing, and burden of family healthcare expenditure was still very heavy. In the MLP neural network, the top three influencing factors were drug fee, surgical fee and hospitalization days for inpatients, drug fee, examination fee and test fee for outpatients. Conclusions: To ease the economic burden of hypertensive patients and improve the utilization efficiency of social resources , the policy makers should pay more attention to the hypertensive patients aging 40-79, strengthen prevention and outpatient treatment for young men and the inpatient treatment for women at older ages, further increase support for primary health care system, standardize the treatment and reimbursement of hypertension, and incline the reimbursement policy to outpatient service.