Miracle-dz/UniFAR-FTUs huggingface dataset:
PHYSICAL INTERACTIONS BETWEEN NEUROPILIN AND VEGFRS, INTEGRINS IN REGULATING ENDOTHELIAL CELL FUNCTIONS

PHYSICAL INTERACTIONS BETWEEN NEUROPILIN AND VEGFRS, INTEGRINS IN REGULATING ENDOTHELIAL CELL FUNCTIONS The neuropilin (Nrp) family consists of multifunctional cell surface receptors with critical roles in a number of different cell and tissue types. A core aspect of Nrp function is ligand-dependent cellular adhesion and migration, where it controls the multistep process of cellular motility through integration of ligand binding, receptor coupling and signaling via the coordinated action of its extracellular and intracellular domains. While Nrp regulates cellular adhesion and motility in the cardiovascular and nervous systems under physiological conditions, the emerging pathological role of Nrp in tumor cell migration and metastasis has been identified and provides motivation for continued efforts toward developing Nrp inhibitors. At the molecular level, the role of Nrp in adhesion and migration is intimately connected to the control of adhesive interactions and cytoskeletal reorganization. The adhesive “interactome” for Nrp draws much attention because of its lack of enzymatic activity and inability to transduce signals on its own. It is an active area of research and is still expanding dramatically. Nrp has been well defined as a co-receptor for vascular endothelial growth factor receptor (VEGFR)/vascular endothelial growth factor (VEGF) signaling through enhancing receptor-ligand interaction in angiogenesis. Here, we contribute to this concept through characterization in more biochemical detail about Nrp-1/VEGF physical interactions. VEGF has been shown to compete with Sema3 for binding to Nrp-1 b1 ligand binding pocket. This competition fine-tunes VEGF-induced angiogenesis. Our data provides a molecular mechanism for high affinity Sema3F binding to Nrp-1 in the b1 domain. As to the VEGFR-independent function, Nrp/integrin association has been demonstrated. The functional integration has been shown for Nrp/integrin in angiogenic sprouting. Both proteins are highly expressed in endothelial tip cells to mediate endothelial cell migration during angiogenesis and knockdown of either one in mice leads to embryonic lethality due to similar defects in vascular development. To identify the structure and function correlation, we characterized in more detail about Nrp1/integrin physical interactions with biochemical and cell-based assays. Through an integrated approach of biochemical, molecular and cellular methods, we defined the direct physical interactions between Nrp-1 and integrins. We have also extended this work to demonstrate the functional importance and contribution of the interactions in integrin-mediated cell adhesion on extracellular matrix (ECM) in angiogenesis and platelet function during wound healing and provide a molecular basis for the integration of Nrps/integrins in cell migration, adhesion to ECM, breast cancer initiation and breast cancer stem cell fate determination.
SIMULTANEOUS ADSORPTION AND DEGRADATION OF ANILINE USING MAGNETIC MULTIWALLED CARBON NANOTUBES LIM JIA XIN

Aniline which is widely used as raw material in different industries is one of the main industrial pollutants leading to the deterioration of water quality. Thus, removal of aniline by simultaneous adsorption and degradation using magnetic multiwalled carbon nanotubes, MWCNTs-Fe3O4 was investigated in this study. MWCNTs-Fe3O4 were synthesised using direct doping method and characterized using X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), scanning electron microscopy coupled with energy dispersive X-ray (SEM-EDX), Brunauer–Emmett–Teller (BET) and thermogravimetric analysis (TGA). The effects of several process parameters such as solution pH (pH 2-10), MWCNTs-Fe3O4 dosage (5-20 mg) and H2O2 dosage (4-16 mM) were studied. Solution pH of pH 6 was found to be the best for aniline adsorption while aniline degradation efficiency decreased with increasing pH. Both adsorption and degradation efficiency increased with increasing MWCNTs-Fe3O4 dosage. Adsorption was not affected by H2O2 dosage because H2O2 dosage was found to be an insignificant factor for aniline adsorption. For degradation of aniline, low H2O2 dosage (6.43 mM) was sufficient. Response surface methodology (RSM) was applied to optimize the aniline adsorption and degradation efficiency. The optimum condition was found at solution pH of 3.71, MWCNTs-Fe3O4 dosage of 14.47 mg and H2O2 dosage of 6.43 mM. The actual adsorption and degradation efficiency obtained at this condition was 59.61 % and 21.21 % respectively. It could be concluded that simultaneous adsorption and degradation using MWCNTs-Fe3O4 could be one of the feasible methods to remove aniline from wastewater.
On a Proper Tensorial Subgrid Heat Flux Model

In this work, we aim to shed light to the following research question: can we find a nonlinear tensorial subgrid-scale (SGS) heat flux model with good physical and numerical properties, such that we can obtain satisfactory predictions for buoyancy-driven turbulent flows? This is motivated by our findings showing that the classical (linear) eddy-diffusivity assumption, q ∝ ∇T , fails to provide a reasonable approximation for the actual SGS heat flux, q = uT − uT : namely, a priori analysis for airfilled Rayleigh-Bénard convection (RBC) clearly shows a strong misalignment. In the quest for more accurate models, we firstly study and confirm the suitability of the eddy-viscosity assumption for RBC carrying out a posteriori tests for different models at very low Prandtl numbers (liquid sodium, Pr = 0.005) where no heat flux SGS activity is expected. Then, different (nonlinear) tensor-diffusivity SGS heat flux models are studied a priori using DNS data of an air-filled (Pr = 0.7) RBC at Rayleigh numbers up to 10. Apart from having good alignment trends with the actual SGS heat flux, we also restrict ourselves to models that are numerically stable per se and have the proper cubic near-wall behavior. This analysis leads to a new family of SGS heat flux models based on the symmetric positive semi-definite tensor GG where G ≡ ∇u, i.e. q ∝ GG ∇T , and the invariants of the GG tensor. Finally, relevant numerical aspects regarding the implementation of this type of models are discussed in detail. A list of physical and numerical properties is identified and subsequently imposed, leading to a symmetrypreserving discretization that is based on discrete operators already available in any CFD code.
Cell Cycle-related Expression of p120 NucÃ- colar Antigen in Normal Human Lymphocytes and in Cells of HL-60 and MOLT-4 Leukemic Lines: Effects of Methotrexate, Camptothecin, and Teniposide1

Expression of the proliferation-associated nucleolar antigen pi 20 was studied by flow cytometry in human quiescent and phytohemagglutininstimulated lymphocytes, as well as in human lymphocytic (MOLT-4) and promyelocytic (HL-60) cell lines. Divariate analysis of pl20 and DNA content made it possible to correlate p120 expression with cell position in the cycle. Proliferating lymphocytes and MOLT-4 and HL60 cells had a similar pattern of pi 20 expression. Populations of Gt cells, in all three cell types, were very heterogenous with respect to p120, and a threshold in (., was observed. The cells with a pi20 level below the threshold value did not enter S phase. An increase in pi 20 was observed during progression through S phase, and the antigen was maximally expressed in (. cells. The pi 20/1)\. A content ratio, however, was highest in late Ci cells (<HB)and was declining during S and (,Â¡. The data thus suggest that p120 may be degraded during mitosis and that the post mitot k-cells inherit little, if any, of this protein; the antigen then accumulates predominantly during (â€¢,, and must reach a threshold level to enable the cells to enter S phase. Antigen p120 could not be detected in noncycling lymphocytes nor in HL-60 cells induced to myeloid differentiation by growth in the presence of dimethyl sulfoxide. Treatment of MOLT-4 cells with pharmacological concentrations of methotrexate, camptothecin, or teniposide induced cell arrest in S or (Ã-? ; expression of pi 20 in the arrested cells was unchanged from that of untreated MOLT-4 controls at the same phase of the cycle. The level of pi 20 was minimal in MOLT4 or HL-60 cells arrested in M phase by vinblastine, but vinblastine had no effect on p120 fluorescence of interphase cells. Camptothecin or teniposide induced apoptosis selectively in S phase of HL-60 cells; apoptotic cells from camptothecin-treated cultures, however, despite the marked nucleolysis, still expressed p120. The data on the drug-treated cells indicate that the pi 20 level in tumors of patients may be used as a marker of tumor/malignancy even in clinical samples obtained during treatment.
Two Case Studies of Profit Sharing in Global Supply Chains: Catracha Coffee Company & Thrive Farmers International, Inc

Far too often, global supply chains distribute value in ways that contribute to income inequality and the uneven accumulation of wealth. Despite a surge of innovations to address this problem—such as fair trade, corporate social responsibility, and creating shared value—the issue of value distribution persists as a pressing priority for the international development and business communities. This article puts forth a first attempt at theorizing profit sharing as a potential mechanism for more equitable value distribution in global value chains. Drawing on two in-depth, multi-method case studies of companies that share profits in the coffee sector, we develop eight theoretical propositions about the applicability and efficacy of profit sharing as a tool for redistribution. Our research suggests that profit sharing can distribute value without requiring suppliers to compromise price stability, profit maximization, value creation, or alternative economic opportunities. This conclusion challenges extant theory which asserts (based on studies of fair trade certification, direct trade, and solidarity trade) that these tradeoffs are often necessary or inevitable. We also extend the literature on profit sharing. Extant literature examines firm-level attempts to maximize productivity and minimize dissent, while we are theorizing profit sharing’s fitness for redistributive objectives in the context of value chains. The implication of our findings is that, in some contexts, companies may be able to increase prices and improve income stability without requiring suppliers to compromise other economic priorities. See, also, our article in 25 Magazine, an official publication of the Specialty Coffee Association, coming out in spring 2021.
Syntheses and Structural Characterizations of Two Three-Dimensional Polymers: [{(n-C4H9)3Sn}3M(CN)6] (M = Fe, Co)

The three-dimensional coordination polymers [{(n-C4H9)3Sn}3M(CN)6] (M = Fe, Co) were synthesized by slow interdiffusion of aqueous solutions of K3[M(CN)6] and THF solutions of (C4H9)3SnCl. The stru.
NATIONWIDE SNOW LEOPARD POPULATION ASSESSMENT OF MONGOLIA Key

Spatial Capture-Recapture method is widely used to estimate animal abundance and density. Method is based on recognizable particular individual’s records/captures at certain locations/areas repeatedly to determine the home range center and its size. It also assesses the effect of factors, such as topography, elevation, food source and so on, to species density and home range, thus allowing researchers to obtain spatially dependent more reliable density and abundance results.
PREDICTING TRAVEL MODE CHOICE WITH 86 MACHINE LEARNING 1 CLASSIFIERS: AN EMPIRICAL BENCHMARK STUDY 2

1 Researchers are applying a large number of machine learning (ML) classiﬁers to predict travel 2 behavior, but the results are data-speciﬁc and the selection of ML classiﬁers is author-speciﬁc. To 3 obtain generalizable results, this paper provides an empirical benchmark by using 86 classiﬁers 4 from 14 model families to predict the travel mode choice based on the National Household Travel 5 Survey (NHTS) 2017 dataset. The 86 ML classiﬁers from 14 model families incorporate all the 6 important ML classiﬁers discussed in previous studies. The large number of observations (about 7 800 , 000) in the NHTS2017 dataset enables us to analyze the effect of different sample sizes as 8 a meta-dimension on prediction accuracy. We found that ensemble models , including boosting, 9 bagging, and random forests, perform the best among all the classiﬁers, and that deep neural 10 networks (DNNs) perform the best among all the non-ensemble models. Classical discrete choice 11 models (DCMs) only predict at the medium or relatively low range of prediction accuracy among 12 all the models. Particularly, mixed logit model cannot be trained in a reasonable amount of time 13 owing to its computational difﬁculty in sampling. Larger sample size generally leads to higher 14 prediction accuracy, particularly for the models with high model complexity. Overall, this study 15 provides an empirical benchmark result for the future, and future studies can build upon our results 16 by testing more ML classiﬁers on the same NHTS2017 dataset, thus yielding more comparable, 17 replicable, and generalizable knowledge shared by the whole research community. 18
The Effect of Contextual Teaching and

February 2019 ABSTRACT The implementation of Contextual Teaching and Learning (CTL) based on lesson study aimed to determine its effect on the biology learning achievement of high school students. This referred to a quasi experimental research by applying CTL learning based on lesson study to the experimental class and conventional learning in the control class. The population in this study amounted to 286 students (Science X class students of SMA Negeri 2 Jember). The sample in this study was determined through homogeneity test, normality test, and random sampling to determine the control class and the experimental class. The students' affective learning achievement were analyzed by using the independent sample ttest, while their cognitive learning achievement was analyzed by using ANAKOVA test. Based on the test results of the independent sample t-test, it was found that the students' affective learning achievement differed significantly between the students in experimental class and control class. Based on the results of ANAKOVA test, it was known that the application of CTL learning based on Lesson Study has a significant effect on students' cognitive learning achievement.
Fast and continuous processing of a new sub-micronic lanthanide-based metal–organic framework

Processing strategies for the synthesis of hybrid materials stand as relevant ways to modulate the particle size and morphology. We present herein the use of a continuous high temperature–high pressure (HT–HP) process for the synthesis of a new cerium based metal–organic framework (MOF). The HT–HP harsh thermodynamic synthesis conditions lead to MOF nanostructures exhibiting the same phase as for microparticles obtained under conventional batch solvothermal conditions but in exceptional much shorter residence times, opening avenues towards production scaling-up. The HT–HP process also tailors down the size of the particles, which still presents a major issue for most MOF applications.
Atlas of epistasis

We performed a genome-wide epistasis search across 502 phenotypes in case control matched cohorts from the UK Biobank. We identified 152,519 genome wide significant interactions in 68 distinct phenotypes, and 3,398 interactions in 19 phenotypes were successfully replicated in independent cohorts from the Finngen consortium. Most interactions (79%) involved variants that did not present significant marginal association and might explain part of the missing heritability for these diseases. In 10 phenotypes we show the presence of epistasis between common variants with intermediate to large effect size (OR>2) supporting the hypothesis that common diseases are modulated by common variants. Most of the variants in interactions (82%) were more than 1Mb apart and cis-epistasis was hardly found outside the HLA region. Functional annotation of the variants suggests that most mechanisms behind epistasis occurs at the supra pathway level and that intra-gene or intra-pathway epistasis is rare. Surprisingly we find a significant biais toward antagonistic epistasis, representing 60% to 95% of interactions. In type 1 diabetes, hypothyroidism, disorders of mineral absorption, rheumatoid arthritis, asthma, and multiple sclerosis more than 50% of interactions were completely compensating the effect of the marginally associated variant. In psoriasis we identified an interaction between a stop gain variant in CCHCR1 with two missense variants in MUC22 and HSPA1L leading to a 3 fold increase of the effect of CCHCR1 variant on disease risk. Our study shows that there is still much to discover in epistasis and we provide the full summary statistics results to researchers interested in studying epistasis.
Using Random Forests with Asymmetric Costs to Predict Hospital Readmissions

Objective: Sufficiently accurate predictions of hospital readmissions are necessary for the allocation of scare clinical resources to reduce preventable readmissions. We describe the use of a data-driven approach that relies on machine learning algorithms to predict readmission at the time of discharge. Materials and Methods: We employ random forests to clinical and administrative electronic health record data available from a cohort of 103,688 patients discharged from the acute inpatient settings of the University of Pennsylvania Health System between June 25th, 2011 and June 30th, 2013. We predict both 30-day all-cause readmissions and 7-day unplanned readmissions using only predictors available by the time of discharge. Using oversampling and undersampling of the different outcome classes of readmission and no readmission, we incorporate into our models the asymmetric costs of a false negative relative to a false positive from the perspective of a hospital. We calculate variable importance scores for included predictors. Our approach was derived and validated using split-sample internal validation. Results: We developed a machine learning-based model using random forests with a 5:1 relative cost ratio for 30-day all-cause readmissions that achieves a sensitivity of 65% and specificity of 71% on validation data, as well as a random forests model with a 20:1 cost ratio for 7-day unplanned readmissions that achieves a sensitivity of 62% and specificity of 66% on validation data. Prior health system utilization, clinical discharging service, and vital sign information were most predictive of readmissions. Conclusion: By modeling the complex relationships between many predictor variables and readmission data for a large health system, we demonstrate successful predictive models that can be used upon discharge to flag patients at high risk of readmission.
A Spatiotemporal Analysis of Socio-Environmental Patterns in Severe Maternal Morbidity: A Retrospective Birth Cohort

Objectives. Severe Maternal Morbidity (SMM) is a group of pregnancy complications in which a woman nearly dies. Despite its increasing prevalence, there is little research that evaluates geographic patterns of SMM and the underlying social determinants that influence excess risk. This study examines the spatial clustering of SMM across South Carolina, US, and its associations with place-based social and environmental factors. Methods. Hospitalized deliveries from 1999 to 2017 were analyzed using Kulldorff's spatial scan statistic to locate areas with abnormally high rates of SMM. Patients inside and outside risk clusters were compared using Generalized Estimating Equations (GEE) to determine underlying risk factors. Results. Final models revealed that the odds of living in a high-risk cluster were 84% higher among Black patients (OR=1.84, p<.001), 30% higher among Hispanic and Latina patients (OR=1.3, p<.05), and 1.51 times more likely among women living in highly segregated and poorer minority communities (OR=1.51 p<.001). Odds for residing in a high-risk cluster were 23% higher for those who gave birth during a period with temperatures above 30.65C/87.3F (OR=1.23, p<.001). Conclusions. This study is the first to characterize the geographic clustering of SMM risk in the US. Our geospatial approach contributes a novel understanding to factors which influence SMM beyond patient-level characteristics and identifies the impact of systemic racism on maternal morbidity. Findings address an important literature gap surrounding place-based risk factors by explaining the contextual social and built environment variables that drive SMM risk.
Characterisation of the mechanism by which a nonsense variant in RYR2 results in ventricular arrhythmia

Background: Heterozygous variants in the cardiac ryanodine receptor gene (RYR2) cause catecholaminergic polymorphic ventricular tachycardia (CPVT). Most pathogenic RYR2 variants are missense variants which result in a gain of function, causing ryanodine receptors to be increasingly sensitive to activation by calcium, have an increased open probability and an increased propensity to develop calcium waves. However, some RYR2 variants can lead to arrhythmias by a loss of function mechanism. Objective: To understand the mechanism by which a novel nonsense variant in RYR2 p.(Arg4790Ter) leads to ventricular arrhythmias. Methods: Human induced pluripotent stem cells (hiPSCs) harbouring the novel nonsense variant in RYR2 were differentiated into cardiomyocytes (RYR2-hiPSC-CMs) and molecular and calcium handling properties were studied. Results: RYR2-hiPSC-CMs displayed significant calcium handling abnormalities at baseline and following treatment with isoproterenol. Treatment with carvedilol and nebivolol resulted in a significant reduction in calcium handling abnormalities in the RYR2-hiPSC-CMs. Expression of the mutant RYR2 allele was confirmed at the mRNA level and partial silencing of the mutant allele resulted in a reduction in calcium handling abnormalities at baseline. Conclusion: The nonsense variant behaves similarly to other gain of function variants in RYR2. Carvedilol and nebivolol may be suitable treatments for patients with gain of function RYR2 variants.
A major population resource of 474,074 participants in UK Biobank to investigate determinants and biomedical consequences of leukocyte telomere length.

The determinants and biomedical consequences of variation in leukocyte telomere length (LTL), a proposed marker of biological age, are only partially understood. Here we report the creation and initial characterization of LTL measurements in 474,074 participants in UK Biobank. We confirm that older age and male sex associate with shorter LTL, with women on average ~7 years younger in "biological age" than men. Compared to white Europeans, LTL is longer in African, Chinese and other major ancestries. Older paternal age at birth is associated with longer individual LTL. Higher white cell count is associated with shorter LTL, but proportions of white cell subtypes have weaker associations. Age, ethnicity, sex and white cell count explain ~5.5% of LTL variance. Using paired samples from 1351 participants taken ~5 years apart, we show the regression-dilution ratio for LTL is ~0.65. This novel resource provides major opportunities to investigate LTL and multiple biomedical phenotypes.