bluuebunny/crossref_metadata_2025_split huggingface dataset:
Implicit Stereotypes: Evidence from Teachers’ Gender Bias*
Authors: Carlana Michela 
Published: March 2019

AbstractI study whether exposure to teacher stereotypes, as measured by the Gender-Science Implicit Association Test, affects student achievement. I provide evidence that the gender gap in math performance, defined as the score of boys minus the score of girls in standardized tests, substantially increases when students are assigned to math teachers with stronger gender stereotypes. Teacher stereotypes induce girls to underperform in math and self-select into less demanding high schools, following the track recommendation of their teachers. These effects are at least partially driven by lower self-confidence on math ability of girls exposed to gender-biased teachers. Stereotypes impair the test performance of girls, who end up failing to achieve their full potential. I do not detect statistically significant effects on student outcomes of literature teacher stereotypes.
Sums of Linear Transformations in Higher Dimensions
Authors: Mudgal Akshat 
Published: March 2019

AbstractIn this paper, we prove the following two results. Let d be a natural number and q, s be co-prime integers such that 1<qs<|q|. Then there exists a constant δ>0 depending only on q, s and d such that for any finite subset A of ℝd that is not contained in a translate of a hyperplane, we have |q⋅A+s⋅A|≥(|q|+|s|+2d−2)|A|−Oq,s,d(|A|1−δ).The main term in this bound is sharp and improves upon an earlier result of Balog and Shakan. Secondly, let L∈GL2(ℝ) be a linear transformation such that L does not have any invariant one-dimensional subspace of ℝ2. Then, for all finite subsets A of ℝ2, we have |A+L(A)|≥4|A|−O(|A|1−δ), for some absolute constant δ>0. The main term in this result is sharp as well.
MicroRNA-21-5p as a novel therapeutic target for osteoarthritis
Authors: Wang Xiao-bo , Zhao Feng-chao , Yi Lin-hong , Tang Jin-long , Zhu Zheng-ya , Pang Yong , Chen Ye-shuai , Li Dong-ya , Guo Kai-jin , Zheng Xin 
Published: March 2019

Abstract

Objective
Growing evidence indicates that microRNAs (miRNA) play a critical role in the pathogenesis of OA, and overexpressing or silencing miRNA expression in OA models can contribute to the development of miRNA-based therapeutics. The objective of this study was to determine whether intra-articular injection of miRNA can inhibit OA progression.

Methods
The miRNA expression profile was determined in OA cartilage tissues and controls. Functional analysis of the miRNAs on extracellular matrix degradation was performed after miRNA mimic or inhibitor transfection. Luciferase reporter assays and western blotting were employed to determine miRNA targets. To investigate the functional mechanism of miR-21-5p in OA development, miR-21-5pfl/flCol2a1-CreER and wild-type mice were subject to surgical destabilization of the medial meniscus. Therapeutically, wild-type mice undergoing surgical destabilization of the medial meniscus were treated with intra-articular injection of agomir- and antagomir-21-5p.

Results
We found that expression of miR-21-5p was significantly up-regulated in OA cartilage tissues. The articular cartilage degradation of miR-21-5p conditional knockout mice was significantly alleviated compared with that of wild-type mice in spontaneous and destabilization of the medial meniscus models. Through gain-of-function and loss-of-function studies, miR-21-5p was shown to significantly affect matrix synthesis genes expression, and chondrocyte proliferation and apoptosis. Further, fibroblast growth factor 18 (FGF18) was identified as a target of miR-21-5p. Intra-articular injection of antagomir-21-5p significantly attenuated the severity of experimental OA. Clinically, FGF18 expression level was correlated with miR-21-5p expression and a modified Mankin scale.

Conclusion
Our findings reveal a miRNA functional pathway important for OA development, highlighting miRNA-21-5p silencing as an attractive therapeutic regimen in future clinical trials involving patients with OA.
Patterns, Profiles, and Parsimony: dissecting transcriptional signatures from minimal single-cell RNA-seq output with SALSA
Authors: Lozoya Oswaldo A. , McClelland Kathryn S. , Papas Brian , Li Jian-Liang , Yao Humphrey H-C 
Published: March 2019

AbstractSingle-cell RNA sequencing (scRNA-seq) technologies have precipitated the development of bioinformatic tools to reconstruct cell lineage specification and differentiation processes with single-cell precision. However, start-up costs and data volumes currently required for statistically reproducible insight remain prohibitively expensive, preventing scRNA-seq technologies from becoming mainstream. Here, we introduce single-cell amalgamation by latent semantic analysis (SALSA), a versatile workflow to address those issues from a data science perspective. SALSA is an integrative and systematic methodology that introduces matrix focusing, a parametric frequentist approach to identify fractions of statistically significant and robust data within single-cell expression matrices. SALSA then transforms the focused matrix into an imputable mix of data-positive and data-missing information, projects it into a latent variable space using generalized linear modelling, and extracts patterns of enrichment. Last, SALSA leverages multivariate analyses, adjusted for rates of library-wise transcript detection and cluster-wise gene representation across latent patterns, to assign individual cells under distinct transcriptional profiles via unsupervised hierarchical clustering. In SALSA, cell type assignment relies exclusively on genes expressed both robustly, relative to sequencing noise, and differentially, among latent patterns, which represent best-candidates for confirmatory validation assays. To benchmark how SALSA performs in experimental settings, we used the publicly available 10X Genomics PBMC 3K dataset, a pre-curated silver standard comprising 2,700 single-cell barcodes from human frozen peripheral blood with transcripts aligned to 16,634 genes. SALSA identified at least 7 distinct transcriptional profiles in PBMC 3K based on <500 differentially expressed Profiler genes determined agnostically, which matched expected frequencies of dominant cell types in peripheral blood. We confirmed that each transcriptional profile inferred by SALSA matched known expression signatures of blood cell types based on surveys of 15 landmark genes and other supplemental markers. SALSA was able to resolve transcriptional profiles from only ∼9% of the total count data accrued, spread across <0.5% of the PBMC 3K expression matrix real estate (16,634 genes × 2,700 cells). In conclusion, SALSA amalgamates scRNA-seq data in favor of reproducible findings. Furthermore, by extracting statistical insight at lower experimental costs and computational workloads than previously reported, SALSA represents an alternative bioinformatics strategy to make single-cell technologies affordable and widespread.
TraitCorr – correlating gene expression measurements with phenotypic data
Authors: Nussbaumer Thomas , Wagner Christian , Heidari Parviz 
Published: March 2019

AbstractToday, transcriptomes and microarrays can be generated and analysed in high quantity. In addition, experiments often include descriptive information about each sample which needs to be compared to the gene expression profiles. The understanding of the relationships between gene expression and phenotype is introduced as new challenge in system biology. Combining expression (RNA-seq and microarray) and phenotype data could reveal the role or effects of each gene on traits. To address all these needs, the user-interface TraitCorr was developed which allows to determine genes that are significantly correlating with a selected trait. Furthermore, it allows to determine significantly correlated genes among different traits and provides visualisation and analysis possibilities.
Optimised prophylactic vaccination in metapopulations
Authors: Teo Mingmei , Bean Nigel , Ross Joshua V. 
Published: March 2019

AbstractA highly effective method for controlling the spread of an infectious disease is vaccination. However, there are many situations where vaccines are in limited supply. The ability to determine, under this constraint, a vaccination strategy which minimises the number of people that become infected over the course of a potential epidemic is essential. Two questions naturally arise: when is it best to allocate vaccines, and to whom should they be allocated? We address these questions in the context of metapopulation models of disease spread. We discover that it is optimal to distribute all vaccines prophylactically, rather than withholding until infection is introduced. For small metapopulations, we provide a method for determining the optimal allocation. As the optimal strategy becomes computationally intensive to obtain when the population size increases, we detail an approximation method to determine an approximately optimal vaccination scheme. Through comparisons with other strategies in the literature, we find that our approximate strategy is superior.
Hypothesis, analysis and synthesis: it’s all Greek to me!
Authors: Iliopoulos Ioannis , Ananiadou Sophia , Danchin Antoine , Ioannidis John P. A. , Katsikis Peter D. , Ouzounis Christos A. , Promponas Vasilis J. 
Published: March 2019

AbstractThe linguistic foundations of science and technology have relied on a range of terms many of which are borrowed from ancient languages, a known but little researched fact from a statistical perspective. Precise definitions and novel concepts are often crafted with those — frequently used — terms, yet their etymology from Greek or Latin might not always be fully appreciated. Herein, we demonstrate that frequently used terms span almost the entire PubMed®database, while a handful of terms of Greek origin retrieve 80% of all entries. We argue that the etymology of those critical terms needs to be fully grasped to ensure correct use, in conjunction with other concepts. We further propose a number of terms for genomics, using prepositions that can accurately define subtle sub-disciplines of this ever-expanding field. Finally, we invite commentary by both the science community and the humanities, for possible adoption of suggested terms, not least to avoid inaccurate usage or inappropriate notions that may compromise clarity of meaning.
The Microbial Metagenome and Tissue Composition in Mice with Microbiome-Induced Reductions in Bone Strength
Authors: Guss Jason D , Taylor Erik , Rouse Zach , Roubert Sebastian , Higgins Catherine H , Thomas Corinne J , Baker Shefford P , Vashishth Deepak , Donnelly Eve , Shea M Kyla , Booth Sarah L , Bicalho Rodrigo C , Hernandez Christopher J 
Published: March 2019

ABSTRACTThe genetic components of microbial species that inhabit the body are known collectively as the microbiome. Modifications to the microbiome have been implicated in disease processes throughout the body and have recently been shown to influence bone. Prior work has associated changes in the microbial taxonomy (phyla, class, species, etc.) in the gut with bone phenotypes but has provided limited information regarding mechanisms. With the goal of achieving a more mechanistic understanding of the effects of the microbiome on bone, we perform a metagenomic analysis of the gut microbiome that provides information on the functional capacity of the microbes (all microbial genes present) rather than only characterizing the microbial taxa. Male C57Bl/6 mice were subjected to disruption of the gut microbiota (ΔMicrobiome) using oral antibiotics (from 4-16 weeks of age) or remained untreated (n=6-7/group). Disruption of the gut microbiome in this manner has been shown to lead to reductions in tissue mechanical properties and whole bone strength in adulthood with only minor changes in bone geometry and density. ΔMicrobiome led to modifications in the abundance of microbial genes responsible for the synthesis of the bacterial cell wall and capsule; bacterially synthesized carbohydrates; and bacterially synthesized vitamins (B and K) (p <0.01). Follow up analysis focused on vitamin K, a factor that has previously been associated with bone health. The vitamin K content of the cecum, liver and kidneys was primarily microbe-derived forms of vitamin K (menaquinones) and was decreased by 32-66% in ΔMicrobiome mice compared to untreated animals (p < 0.01). Bone mineral crystallinity was decreased (p=0.01) was decreased in ΔMicrobiome mice (p < 0.001) and matrix carbonate-phosphoate ratio was increased. This study illustrates the use of metagenomic analysis to link the microbiome to bone phenotypes and implicates microbially synthesized vitamin-K as a regulator of bone matrix quality.
Large-scale multivariate multi-ancestry Interaction analyses point towards different genetic mechanisms by population and exposure
Authors: Laville Vincent , Majarian Timothy , Sung Yun J , Schwander Karen , Feitosa Mary F , Chasman Daniel , Bentley Amy R , Rotimi Charles N , Cupples L Adrienne , de Vries Paul S , Brown Michael R , Morrison Alanna C , Kraja Aldi T , Province Mike , Gu C. Charles , Gauderman James , Rao DC , Manning Alisa , Aschard Hugues ,   on behalf of the CHARGE Gene-Lifestyle Interactions Working Group
Published: March 2019

AbstractTheCHARGE Gene-Lifestyle Interactions Working Groupis a unique initiative formed to improve our understanding of the role and biological significance of gene-environment interactions in human traits and diseases. The consortium published several multi-ancestry genome-wide interaction studies (GWIS) involving up to 610,475 individuals for three lipids and four blood pressure traits while accounting for interaction effects with drinking and smoking exposures. Here we used GWIS summary statistics from these studies to decipher potential differences in genetic associations and GxE interactions across phenotype-exposure-population trios, and to derive new insights on the potential mechanistic underlying GxE through in-silico functional analyses. Our comparative analysis shows first that interaction effects likely contribute to the commonly reported ancestry-specific genetic effect in complex traits, and second, that some phenotype-exposures pairs are more likely to benefit from a greater detection power when accounting for interactions. It also highlighted a negligible correlation between main and interaction effects, providing material for future methodological development and biological discussions. We also estimated contributions to phenotypic variance, including in particular the genetic heritability conditional on the exposure, and heritability partitioned across a range of functional annotations and cell-types. In these analyses, we found multiple instances of heterogeneity of functional partitions between exposed and unexposed individuals, providing new evidence for likely exposure-specific genetic pathways. Finally, along this work we identified potential biases in methods used to jointly meta-analyses genetic and interaction effects. We performed a series of simulations to characterize these limitations and to provide the community with guideline for future GxE studies.
Multi-site sampling and risk prioritization reveals the public health relevance of antibiotic resistance genes found in wastewater environments
Authors: Dai Chengzhen L. , Duvallet Claire , Zhang An Ni , Matus Mariana G. , Ghaeli Newsha , Park Shinkyu , Endo Noriko , Isazadeh Siavash , Jamil Kazi , Ratti Carlo , Alm Eric J. 
Published: March 2019

AbstractThe spread of bacterial antibiotic resistance across human and environmental habitats is a global public health challenge. Wastewater has been implicated as a major source of antibiotic resistance in the environment, as it carries resistant bacteria and resistance genes from humans into natural ecosystems. However, different wastewater environments and antibiotic resistance genes in wastewater do not all present the same level of risk to human health. In this study, we investigate the public health relevance of antibiotic resistance found in wastewater by combining metagenomic sequencing with risk prioritization of resistance genes, analyzing samples across urban sewage system environments in multiple countries. We find that many of the resistance genes commonly found in wastewater are not readily present in humans. Ranking antibiotic resistance genes based on their potential pathogenicity and mobility reveals that most of the resistance genes in wastewater are not clinically relevant. Additionally, we show that residential wastewater resistomes pose greater risk to human health than those in wastewater treatment plant samples, and that residential wastewater can be as risky as hospital effluent. Across countries, differences in antibiotic resistance in residential wastewater can, in some cases, reflect differences in antibiotic drug consumption. Finally, we find that the flow of antibiotic resistance genes is influenced by geographical distance and environmental selection. Taken together, we demonstrate how different analytical approaches can provide greater insights into the public health relevance of antibiotic resistance in wastewater.
A knowledge–based scoring function to assess the stability of quaternary protein assemblies
Authors: Dhawanjewar Abhilesh S. , Roy Ankit , Madhusudhan M.S. 
Published: March 2019

AbstractMotivationElucidation of protein-protein interactions is a necessary step towards understanding the complete repertoire of cellular biochemistry. Given the enormity of the problem, the expenses and limitations of experimental methods, it is imperative that this problem is tackled computationally. In silico predictions of protein interactions entail sampling different conformations of the purported complex and then scoring these to assess for interaction viability. In this study we have devised a new scheme for scoring protein-protein interactions.ResultsOur method, PIZSA (Protein Interaction Z Score Assessment) is a binary classification scheme for identification of stable protein quaternary assemblies (binders/non-binders) based on statistical potentials. The scoring scheme incorporates residue-residue contact preference on the interface with per residue-pair atomic contributions and accounts for clashes. PIZSA can accurately discriminate between native and non-native structural conformations from protein docking experiments and outperform other recently published scoring functions, demonstrated through testing on a benchmark set and the CAPRI Score_set. Though not explicitly trained for this purpose, PIZSA potentials can identify spurious interactions that are artefacts of the crystallization process.AvailabilityPIZSA is implemented as awebserverat http://cospi.iiserpune.ac.in/pizsa/.Contactmadhusudhan@iiserpune.ac.in
Engineered probiotics for local tumor delivery of checkpoint blockade nanobodies
Authors: Gurbatri Candice , Coker Courtney , Hinchliffe Taylor E. , Lia Ioana , Castro Samuel , Treuting Piper M. , Arpaia Nicholas , Danino Tal 
Published: March 2019

ABSTRACTImmunotherapies such as checkpoint inhibitors have revolutionized cancer therapy yet lead to a multitude of immune-related adverse events, suggesting the need for more targeted delivery systems. Due to their preferential colonization of tumors and advances in engineering capabilities from synthetic biology, microbes are a natural platform for the local delivery of cancer therapeutics. Here, we present an engineered probiotic bacteria system for the controlled production and release of novel immune checkpoint targeting nanobodies from within tumors. Specifically, we engineered genetic lysis circuit variants to effectively release nanobodies and safely control bacteria populations. To maximize therapeutic efficacy of the system, we used computational modeling coupled with experimental validation of circuit dynamics and found that lower copy number variants provide optimal nanobody release. Thus, we subsequently integrated the lysis circuit operon into the genome of a probioticE. coliNissle 1917, and confirmed lysis dynamics in a syngeneic mouse model usingin vivobioluminescent imaging. Expressing a nanobody against PD-L1 in this strain demonstrated enhanced efficacy compared to a plasmid-based lysing variant, and similar efficacy to a clinically relevant monoclonal antibody against PD-L1. Expanding upon this therapeutic platform, we produced a nanobody against cytotoxic T-lymphocyte associated protein -4 (CTLA-4), which reduced growth rate or completely cleared tumors when combined with a probiotically-expressed PD-L1 nanobody in multiple syngeneic mouse models. Together, these results demonstrate that our engineered probiotic system combines innovations in synthetic biology and immunotherapy to improve upon the delivery of checkpoint inhibitors.SENTENCE SUMMARYWe designed a probiotic platform to locally deliver checkpoint blockade nanobodies to tumors using a controlled lysing mechanism for therapeutic release.
Occurrence ofCryptosporidium hominisin cattle bordering the Lake Mburo National Park in Kiruhura district, Western Uganda
Authors: Witto Sarah Gift , Kankya Clovice , Kazibwe Anne , Akurut Gloria , Ochwo Sylvester 
Published: March 2019

AbstractBackgroundCryptosporidiumis an emerging opportunistic zoonotic pathogen that causes diarrheal illness in a wide range of hosts including livestock and humans. Globally there is exponential increase in livestock production to meet the worlds’ demand for animal protein as well as for financial reasons. However, there is raised concern of the public health threat due to contamination of the environment by livestock waste carrying zoonotic pathogens such asCryptosporidium. This study set out to establish the prevalence ofCryptosporidiumas well as the circulating genotypes in order to elucidate the potential role of cattle in the spread of human cryptosporidiosis. We collected rectal coprological samples from 363 cattle in 11 households in Kiruhura district, Southwestern Uganda. The samples were screened for presence ofCryptosporidiumoocysts using the phenol auramine staining method followed by fluorescent microscopy. DNA was then extracted from the microscopy positive samples and the COWP gene amplified using PCR. Amplified gene products were sequenced and subjected to phylogenetic analysis.ResultsThe overall animal level prevalence ofCryptosporidiumwas 7.7% (95% CI: 5.1-10.9), and herd level prevalence was 33.3% (95% CI: 18.5-52.2). We found a statistically significant difference (p=0.02) between infection in bulls as compared to cows. There was however no significant difference in the prevalence among the different cattle breeds sampled, with the following prevalence’s observed in Crosses 9.2%, Ankole 5.7%, Friesian 7.1%, and Boran 2.8% respectively. The COWP gene was successfully amplified from 20 of the 28 microscopy positive samples. All the sequenced DNA amplicons were confirmed to beC. hominis, with 98%-100% identity to sequences in the GenBank.C. hominiswas the only genotype isolated from this study, further asserting that cattle could be a potential high risk source of human cryptosporidiosis.ConclusionThis study represents the first time naturally occurringC. hominishas been isolated from cattle in Uganda. This further provides evidence of cattle possibly being biological reservoirs forC. hominisand cattle could be a potential high risk source of human cryptosporidiosis.