bluuebunny/crossref_metadata_2025_split huggingface dataset:
Investigation of de novo mutations in a schizophrenia case-parent trio by induced pluripotent stem cell based in vitro disease-modeling: Convergence of schizophrenia and autism-related cellular phenotypes
Authors: Hathy Edit , Varga Nóra , Erdei Zsuzsa , Szabó Eszter , Tordai Csongor , Czehlár Boróka , Baradits Máté , Jezsó Bálint , Koller Júlia , Nagy László , Molnár Mária Judit , Nemoda Zsófia , Homolya László , Apáti Ágota , Réthelyi János M 
Published: January 2020

Abstract
Background: De novo mutations (DNMs) have been implicated in the etiology of schizophrenia, a chronic debilitating psychiatric disorder characterized by hallucinations, delusions, cognitive dysfunction and poor community functioning. Several DNMs have been shown by examining schizophrenia cases and their unaffected parents, however in most cases the biological significance of these mutations remains elusive. To overcome this limitation we have developed an approach of using somatic cell reprogramming to generate induced pluripotent stem cell (iPSC) lines from each member of a schizophrenia case-parent trio, in order to investigate the effects of DNMs in cellular progenies of interest, particularly in dentate gyrus neuronal progenitors. Methods: We identified a male schizophrenia patient characterized by early disease onset and negative symptoms, who is a carrier of 3 non-synonymous DNMs in genes LRRC7, KHSRP, and KIR2DL1. iPSC lines were generated from his and his parents’ peripheral blood mononuclear cells using Sendai virus-based reprogramming. After characterization the iPSCs were differentiated into neuronal progenitor cells (NPCs) and hippocampal dentate gyrus granule cells for the investigation of various cellular phenotypes. We used RNASeq to investigate and transcriptomic differences, calcium (Ca 2+ ) imaging, cell proliferation, migration, oxidative stress, and mitochondrial assays to characterize the investigated NPC lines. Results: NPCs derived from the schizophrenia patient exhibited transcriptomic differences related to Wnt-signaling, axonal guidance and synapse formation, and decreased Ca 2+ reactivity to glutamate. Moreover we could observe increased cellular proliferation and migration, accelerated neurite outgrowth rates, and alterations in mitochondrial quantity and morphology. Conclusions: The approach of reprograming case-parent trios represents a possibility of investigating disease-causing mutations and comparing cell lines with reduced variation in genetic background. Our results are indicative of an overlap between schizophrenia and autism-related phenotypes in the investigated family.
Renal dysfunction decreases specificity and overturns cutoff value of serum CC16 while prohibiting 7-day mortality prediction in diagnosing acute respiratory distress syndrome in intensive care unit.
Authors: Lin Jinle , Tao Wuyuan , Wei Jian , Jian Wu , Zhang Wenwu , Ye Jianbing , Fu Xuan , Dou Qingli , Wang Lijun , Tian Fang 
Published: January 2020

Abstract
Background: A contradictory tendency between occurrence of acute respiratory distress syndrome (ARDS) and serum club cell protein 16 (CC16) level, However, renal dysfunction (RD) separately raised serum CC16 in our current observation. The purpose of this study was to find the limitation caused by renal dysfunction in the diagnostic performance of CC16 on ARDS in intensive care unit (ICU) patients. Method: We measured serum CC16 in 479 ICU patients. Patients were divided into six subgroups: control, acute kidney injury (AKI), chronic kidney dysfunction (CKD), ARDS, ARDS+AKI, and ARDS+CKD. The cutoff value, sensitivity and specificity of serum CC16 were assessed by receiver operating characteristic curves. Result: Serum CC16 increased among the ARDS group when compared to the control group, which helps identify ARDS and predicts the outcome in patients with normal renal function. However, level of serum CC16 was similar among ARDS+AKI, ARDS+CKD, AIK and CKD groups. Consequently, when compare to AKI and CKD, specificity for diagnosing whether ARDS or ARDS with renal failure decreased from 86.62% to 2.82% or 81.70% to 2.12%. Consistently, a cutoff value of 11.57 ng/mL was overturned from previously at 32.77 ng/mL or 33.72 ng/mL. Moreover, its predictive value for mortality is prohibited before 7 day but works after 28 day. Conclusion: Renal dysfunction limits the specificity, cutoff point, and predictive value at 7-day mortality of CC16 in diagnosing ARDS among ICU patients.
A multifactorial evaluation for the effects of air pollution and meteorologic factors on asthma exacerbation
Authors: Yu Hong-Ren , Lin Chun-Hung Richard , Tsai Jui-Hsiu , Hsieh Yun-Ting , Tsai Ti-An , Tsai Chang-Ku , Lee Yi-Chen , Liu Ta-Yu , Tsai Chih-Min , Chen Chih-Cheng , Chang Chih-Hao , Hsu Te-Yao , Niu Chen-Kuang 
Published: January 2020

Abstract
Background: Study identify individual effect of single pollutants on asthma acute exacerbation (AE) may overlook the health effect of the mixture overall. In real world, dynamic changes of air pollutants and meteorologic factors coexist simultaneously. A comprehensive study was carried out to examine the influence of air pollution and meteorologic factors on asthma AE. Materials and methods: The asthma AE data from emergency room visits were collected from the Taiwan National Health Insurance Research Database from 2005 to 2013. Complete monitoring data for the air pollutants (sulfur dioxide, SO2; nitrogen dioxide, NO2; ozone, O3; carbon monoxide, CO; PM2.5; and PM10) and meteorologic factors (relative humidity, rainfall, and daily average temperature) were collected from Environmental Protection Agency monitoring stations. A bi-directional case-crossover analysis was used to investigate the effects of air pollution and meteorological factors on asthma exacerbation. Result: Along age group divisions, a 1 ℃ temperature increase was a protective factor for asthma ER visits, with OR = 0.981 (95% CI 0.971–0.991) and 0.985 (95% CI, 0.975–0.994) for pediatric and young adult patients, respectively. Each 1 mg/m3 increase in the 48-h averages of PM2.5 was associated with asthma ER visit for patients older than 65 years of age (OR = 1.008 (95% CI, 1.003–1.014). Conclusion: In Taiwan, asthma AE is closely related to low temperature and certain air pollution. Patients can take appropriate protective strategies to minimize risk of asthma AE related to air pollution/meteorological factors according to relevant gender and age.
Comprehensive Analysis of Evolutionary, Characterization and Expression for Sugar Transporter Family Genes in Nelumbo nucifera&nbsp;
Authors: Wu Peng , Zhang Yongyan , Li Liangjun 
Published: January 2020

Abstract
BackgroundThe sugar transporter , an important class of transporter for sugars function, play regulators of many processes associated with growth, maturation and senescence processes in plant.ResultsIn this study, a total of 35NNUSTs were identified in the Nelumbo nucifera genome. Furthermore, all NNUSTs genes identified were grouped according to conserved domains and phylogenetic analysis. Additionally, we identified 316 ST genes in other10 representative plants, and performed a comparative analysis with Nelumbo nucifera, including evolutionary trajectory, gene duplication, and expression pattern. A large-scale analysis across plants and alga suggested that the ST family could have been originated from STP and Glct, expanding to form STP and SFP by dispersed duplication. Finally, quantitative real-time polymerase chain reaction and cis-elements analysis showed that the NNUSTs were response to abiotic stresses. ConclusionsThis provides useful resources when exploring the molecular evolution and mechanisms of NNUSTs in plants.
Construction of a High-Density Genetic Map and Mapping of Major Flowering Time QTLs in Rapeseed (Brassica napus L.) Based on Whole-Genome Re-sequencing
Authors: Li Xin , Du Dezhi , Ma Qianru , Li Linfang , Zhao Zhi , Tang Guoyong , Liu Haidong , Xiao Lu 
Published: January 2020

Abstract
BackgroundFlowering time is an important trait impacting the performance of Brassica napus L. cultivars, but the interaction of all the loci controlling this trait in spring-type oilseed rape is not fully understood.ResultsIn this study, we conducted a genome-wide quantitative trait locus (QTL) analysis of a recombinant inbred line (RIL) population composed of 215 lines and constructed a high-density linkage map with 4523 recombination bin markers and of 92,627 single-nucleotide polymorphisms (SNPs). After phenotypic measurements across four different fields environments were collected for 2 years, at least 27 flowering time QTLs were identified; these were distributed mainly on linkage groups (LGs) A02 (11 QTLs), A10 (1 QTL), C02 (12 QTLs), C05 (2 QTLs) and C08 (1 QTL). Of these QTLs, five major QTLs for flowering time were detected, and three of them, sqFT-A02-3, sqFT-A02-4, and sqFT-A10-1, were identified only in winter ecological conditions; thus, these QTLs were environment specific. The QTL cqFT-C02-2 was detected in all 3 spring environments, showing strong spring environmental specificity. The major QTL cqFT-C02-3, which is an environmentally stable QTL, was detected in all 4 environments and was expressed both in spring and winter ecological conditions. The winter ecological condition-specific major QTL sqFT-A02-4 was delimited to a region of approximately 216 kb, between 6.302 Mb and 6.518 Mb on A02. In this region, the BnaA02g12130D/GSBRNA2T00090951001 gene was identified as a homologue of the Arabidopsis thaliana FLOWERING LOCUS T (FT) gene by a BLASTn analysis of the candidate region.ConclusionsFive major novel QTLs for flowering time were discovered in spring Brassica napus: 1 environmentally stable QTL and 4 environment-specific QTLs. The major QTL sqFT-A02-4 was delimited to a candidate region of approximately 216 kb, and BnaA02g12130D was determined to be a potential gene
Prediction key genes and the potential molecular mechanism for early recurrent pregnancy loss by Multi-Omics analysis
Authors: Huang Le , Wei Changqiang , Zhang Zhao , Cen Jiao , Zhu Zhiwei , Deng Lingjie , Pang Lihong 
Published: January 2020

Abstract
BackgroundThe potential mechanism of early recurrent pregnancy loss (ERPL) has not been fully elucidated, a multi-omics analysis can help us find key genes.ResultsWe download data from Gene Expression Omnibus (GEO), 90 hypermethylation-down regulated genes and 49 hypomethylation-up regulated genes were identified by intersection. Compared with the normal early pregnancy group, the expression of ERCC2 and MLH1 was lower in ERPL group, but the expression of PLEK and FOS was higher, and the expression of MLH1 was statistically significant (p<0.05). Compared with the anembryonic (empty sac) miscarriage group, the expression of MLH1, PLEK, FOS decreased, and that of ERCC2 increased in the embryonic miscarriage group. TF-MDEGs networks predicted SP1, POLR2A, YY1, CREM and CREB1 were involved in methylation regulation of DNA promoter with MDEGs. Among them, YY1, FOXP3 and p53 may be related to the mechanism of MLH1 in ERPL.ConclusionsOur study identified possible aberrant MDEGs, and TF- MDEGs regulatory networks may be related to its mechanism. MLH1 may play an important role in early embryonic development.
Prioritising key motivators and challenges influencing informal carers’ decisions for participating in randomised trials: a Study Within A Trial (SWAT-55)
Authors: Smith Valerie , Corry Margarita , Devane Declan , Treweek Shaun , Hunter Andrew , Grylka-Baeschlin Susanne , Hannon Kathleen 
Published: January 2020

Abstract
Background: Family members, or others, often assume the role of informal (unpaid) carers of people with chronic illnesses. Care-giving, however, can impact profoundly on the quality of life of caregivers and can cause carer worry, stress and guilt. Implementing interventions that positively affect the lives of carers is important, however, carers as a group are often difficult to reach. We embedded a study within a pilot-feasibility study of a mindfulness based intervention for carers of people with chronic illness to determine the key motivators and challenges influencing informal carers’ decisions for participating in a trial, and to prioritise these to inform future trial design and conduct. Methods: We conducted a Study Within A Trial using a multi-method approach involving interviews with participants from the ‘host trial’ and data from systematic reviews to develop a survey that was distributed to informal carers across Ireland. The survey consisted of 28 motivator and 17 challenge statements. Participants rated how important they thought each statement was when deciding to take part in a trial on a 5-point Likert Scale (1-very unimportant to 5-very important). Mean scores and standard deviations were calculated for each statement and arranged in descending order to provide the final priority lists. Results: Thirty-six carers responded to the survey. Helping to create awareness about carers was the top ranked motivator, followed by four study design statements related to the time at which the study occurs, the study location, format of delivery and venue. The least important motivator related to how carers were invited to take part in a study. Difficulties in planning due to the caring role emerged as the most important challenge for carers, followed by being unable to leave the care recipient on his/her own. Conclusions: Insight into decision-making for research participation will assist trial developers tailor trial processes for informal caregiver populations. We recommend that trialists consider these motivators and challenges when designing future trials involving informal caregivers so as to enhance trial feasibility and success.
Gut Microbes and Microbial Metabolites in Colorectal Cancer Complicated with Different Serum Albumin Levels
Authors: Han Shuwen , Wu Wei , Da Miao , Zhou Qing , Xu Jiamin , Zhuang Jing , Liu Jin , Yang Xi 
Published: January 2020

Abstract
Background: Patients with colorectal cancer (CRC) are at risk of malnutrition. Gut microbes and microbial metabolites are involved in the initiation and development of CRC.Purpose:　To investigate serum protein levels in CRC patients and explore the role of gut microbes and microbial metabolites in CRCs complicated with different serum albumin levels.Methods: Overall, 398 CRC patients and same number of healthy volunteers in Huzhou Central Hospital from January 2016 to December 2018 were recruited to compare serum protein levels. The serological indicators were detected by Abbott Automatic Biochemical Analyzer(HCHL-YQ-SH-01). A total of 30 and 56 stool samples from CRC patients were used to detect intestinal microbes and microbial metabolites, respectively. Bacterial 16S V3-V4 and fungal ITS ribosomal DNA genes were sequenced and gas chromatography/mass spectrometry (GC/MS) was performed to detect microbial metabolites. Results: Some serum protein-related indicators in the CRC group were lower than those in the control group (p＜0.05). The total protein and albumin levels in colon cancer patients were lower than those in rectal cancer patients (p＜0.05). The higher abundance of Sutterella is correlated with lower serum albumin level in CRCs. There were statistically significant differences in the abundance of fungi including Agaricomycetes， Simplicillium, Sclerotiniaceae, and Exophiala among patients with different serum albumin levels. Multiple gut bacteria and fungi are closely related to serum albumin levels.We found some characteristic microbial metabolites in CRCs complicated with different serum protein levels.Conclusions: The different serum albumin levels were associated with the gut microbes and microbial metabolites in CRCs. It may provide novel ideas for basic research and clinical application.
Bots Recognition in Social Networks Using the Random Forest Algorithm
Authors: Khachatrian M. G. , Klyucharev P. G. 
Published: January 2020

Online social networks are of essence, as a tool for communication, for millions of people in their real world. However, online social networks also serve an arena of information war. One tool for infowar is bots, which are thought of as software designed to simulate the real user’s behaviour in online social networks.The paper objective is to develop a model for recognition of bots in online social networks. To develop this model, a machine-learning algorithm “Random Forest” was used. Since implementation of machine-learning algorithms requires the maximum data amount, the Twitter online social network was used to solve the problem of bot recognition. This online social network is regularly used in many studies on the recognition of bots.For learning and testing the Random Forest algorithm, a Twitter account dataset was used, which involved above 3,000 users and over 6,000 bots. While learning and testing the Random Forest algorithm, the optimal hyper-parameters of the algorithm were determined at which the highest value of the F1 metric was reached. As a programming language that allowed the above actions to be implemented, was chosen Python, which is frequently used in solving problems related to machine learning.To compare the developed model with the other authors’ models, testing was based on the two Twitter account datasets, which involved as many as half of bots and half of real users. As a result of testing on these datasets, F1-metrics of 0.973 and 0.923 were obtained. The obtained F1-metric values are quite high as compared with the papers of other authors.As a result, in this paper a model of high accuracy rates was obtained that can recognize bots in the Twitter online social network.
Designing Desorber for MEA Regeneration after Associated Petroleum Gas Treatment. Part 2
Authors: Golovastov S. V. , Alexandrova D. M. 
Published: January 2020

The paper presents a desorption-based method for treating a waste mono-ethanolamine (MEA) solution to extract hydrogen sulfide. The process is used in the associated petroleum gas (APG) treatment unit to remove hydrogen sulphide together with the MEA solution process of hydrogen sulfide absorption from the APG that comes from the well. Extracted hydrogen sulfide can be used to obtain elemental sulfur. The object of development is a stripper for APG treating to remove hydrogen sulfide.Such a treating system is, as a rule, unavailable separately from the absorber and represents an integrated system to treat APG from hydrogen sulfide. Thus, the work objective was to determine parameters, and develop and design desorption column where mono-ethanolamine purification from hydrogen sulphide occurs.The paper presents calculation of desorption column that allows us to close the treatment process, thereby ensuring the regeneration of the mono-ethanolamine solution through treatment by the desorption process. The waste amine is returned to the gas treatment process, and the extracted hydrogen sulfide goes to the Claus process for elemental sulphur production. The column calculation was performed taking into account chemical and thermal processes. The APG treatment unit option to extract hydrogen sulfide with further elemental sulfur produced through the Claus process has been obtained to solve this problem by using the APG as an industrial and domestic gas.
Modified Method of State Variables
Authors: Trudonoshin V. A. , Fedoruk V. G. 
Published: January 2020

Formal mathematical model development of an object with lumped parameters is an integral part of CAE systems. The computer-aided design (CAD) system functionality largely depends on the formation method used. The article proposes to modify a method of state variables, which is a pioneer in formal mathematical models development of technical objects whose behaviour is described by a system of ordinary differential equations.The classical method of state variables uses a graph-based representation of the object structure and allows development of its mathematical model in the normal Cauchy form without incorrect locations. The incorrect locations mean situations when capacitance-type branches fall in the graph chords or inductance-type branches fall in the graph tree branches. If there are incorrect locations in the object’s scheme then, to have a model of correct development, additional elements are included to eliminate them. Such an approach is possible if the object description is performed at the level of the basic two-poles, but it is assumed that in all modern CAD systems there is a pre-processor in which it is possible (and as a rule) to use multi-pole components. In this case, it is challenging for an unsophisticated user to make scheme correction.The modified method of state variables proposed in the article is free from this drawback and allows us to obtain a mathematical model in the normal Cauchy form and with incorrect locations available. This will allow us to use both explicit and implicit integration methods, conduct modal analysis, and simply have a model version in the FMI standard.
Topological Optimization of Microstructure of Adhesives under Thermal and Mechanical Loads
Authors: Bodyagina K. S. , Pavlov S. P. 
Published: January 2020

The paper presents a mathematical model and method for solving a wide class of problems in topological optimization of an adhesive joint to obtain an optimal microstructure and gradient properties in order to reduce the level of stresses arising from both thermal and mechanical loads therein.Adhesive joints have advantages over alternative bonding methods. The paper shows that the introduction of graduating properties in thickness or along the adhesive layer is the most promising strategy to optimize the adhesive. The approach is to modify the material properties or the geometry of the adhesive, varying along the joint.In all the papers known to authors, the shape of the elements to be joined, or the shape and location of the adhesive layer, were subject to optimization. The topological optimization methods to determine the optimal distribution / change of the gradient properties of the adhesive layer itself were not used.In the paper, the stresses arising in the solder joints are analyzed; it is shown that due to the small solder thickness, shear stresses are basic in it. The shear stresses are concentrated near the ends of the solder, and have the lowest values in the middle. The objective of the optimization problem is to reduce the peak values of the shear and peeling stresses in the solder layer. The topological optimization of the solder microstructure is to find the best distribution of a given amount of solder in the region in order to reach minimum peak values of stresses. The advantage of using topological optimization is that the microstructure of the solder should not be known a priori, and, thus, any designs can be optimized without first studying the effect of the original geometric parameters on the strength of the joint.The algorithm is implemented using the finite element method and the method of movable asymptotes. A number of examples are considered in order to obtain the solder microstructure to be optimal for reducing the peak values of shear stresses and delamination in a three-layer package.The results show that optimal microstructures significantly reduce peak stresses compared to a uniform layer. The obtained results reveal the potential of the developed algorithm and show that it can find practical use.