bluuebunny/crossref_metadata_2025_split huggingface dataset:
Seroprevalence of SARS-CoV-2 and risk factors in Bantul Regency, Yogyakarta, Indonesia
Authors: Ahmad Riris Andono , Indriani Citra , Arisanti Risalia Reni , Nanda Ratih Oktri , Mahendradhata Yodi , Wibawa Tri 
Published: June 2022

AbstractCOVID-19 case counts in Indonesia inevitably underestimate the true cumulative incidence of infection due to limited barriers to testing accessibility and asymptomatic infections. Therefore, community-based serological data are essential for understanding the true prevalence of infections. This study aims to estimate the seroprevalence of SARS-CoV-2 infection and factors related to the seropositivity in Bantul Regency, Yogyakarta, Indonesia. A cross-sectional study involving 425 individuals in 40 clusters was conducted between March and April 2021. Participants were interviewed using an e-questionnaire developed in the Kobo toolbox to collect information on socio-demographic, COVID-19 suggestive symptoms, history of COVID-19 diagnosis and COVID-19 vaccination status. A venous blood sample was collected from each participant and tested for immunoglobulin G (Ig-G) SARS-CoV-2 antibody titers using the enzyme-linked immunosorbent assay (ELISA). Seroprevalence was 31.1% in the Bantul Regency: 34.2% in semi-urban and 29.9% in urban villages. However, there is no significant proportion difference between both areas. A significant difference was reported in the age group. Participants in the 55-64 age group demonstrated the highest seroprevalence (43.7%; p=0.00), with a higher risk compared to the other age group (aOR= 3.79; 95% CI, 1.46-9.85, p<0.05). Seroprevalence in the unvaccinated participants was 29.9%. Family clusters accounted for 10.6% of the total seropositive cases. No significant difference was observed between individual preventive actions and their mobility with seropositivity status. This study observed a discrepancy with COVID-19 confirmed cumulative incidence data reported in the same period (11 out of 1000 population), indicating silent transmission may have occurred within the community. Higher seroprevalence in semi-urban areas rather than urban areas suggests a gap in health services access. Surveillance improvement through testing, tracing, and treatment, particularly in areas with lower access to health services, are necessary, along with more robust implementations of health protocols.
Structural conversion of α-synuclein at the mitochondria induces neuronal toxicity
Authors: Choi Minee L. , Chappard Alexandre , Singh Bhanu P. , Maclachlan Catherine , Rodrigues Margarida , Fedotova Evgenia , Berezhnov Alexey V. , De Suman , Peddie Chris , Athauda Dilan , Virdi Gurvir S. , Zhang Weijia , Evans James R. , Wernick Anna , Zanjani Zeinab Shadman , Angelova Plamena R. , Esteras Noemi , Vinikurov Andrey , Morris Katie , Jeacock Kiani , Tosatto Laura , Little Daniel , Gissen Paul , Clarke David J. , Kunath Tilo , Collinson Lucy , Klenerman David , Abramov Andrey Y. , Horrocks Mathew H. , Gandhi Sonia 
Published: June 2022

AbstractAggregation of α-Synuclein (α-Syn) drives Parkinson’s disease, although the initial stages of self-assembly and structural conversion have not been captured inside neurons. We track the intracellular conformational states of α-Syn utilizing a single-molecule FRET biosensor, and show that α-Syn converts from its monomeric state to form two distinct oligomeric states in neurons in a concentration dependent, and sequence specific manner. 3D FRET-CLEM reveals the structural organization, and location of aggregation hotspots inside the cell. Notably multiple intracellular seeding events occur preferentially on membrane surfaces, especially mitochondrial membranes. The mitochondrial lipid, cardiolipin triggers rapid oligomerization of A53T α-Syn, and cardiolipin is sequestered within aggregating lipid-protein complexes. Mitochondrial aggregates impair complex I activity and increase mitochondrial ROS generation, which accelerates the oligomerization of A53T α-Syn, and ultimately causes permeabilization of mitochondrial membranes, and cell death. Patient iPSC derived neurons harboring A53T mutations exhibit accelerated oligomerization that is dependent on mitochondrial ROS, early mitochondrial permeabilization and neuronal death. Our study highlights a mechanism of de novo oligomerization at the mitochondria and its induction of neuronal toxicity.
Wilcoxon rank-sum test still outperforms dearseq after accounting for the normalization impact in semi-synthetic RNA-seq data simulation
Authors: Li Yumei , Ge Xinzhou , Peng Fanglue , Li Wei , Li Jingyi Jessica 
Published: June 2022

AbstractIn this response to the correspondence by Hejblum et al. [1], we clarify the reasons why we ran the Wilcoxon rank-sum test on the semi-synthetic RNA-seq samples without normalization, and why we could only run dearseq with its built-in normalization, in our published study [2]. We also argue that no normalization should be performed on the semi-synthetic samples. Hence, for a fairer method comparison and using the updated dearseq package by Hejblum et al., we re-run the six differential expression methods (DESeq2, edgeR, limma-voom, dearseq, NOISeq, and the Wilcoxon rank-sum test) without normalizing the semi-synthetic samples, i.e., under the “No normalization” scheme in [1]. Our updated results show that the Wilcoxon rank-sum test is still the best method in terms of false discovery rate (FDR) control and power performance under all settings investigated.
The efficacy of EphA2 tyrosine phosphorylation increases with EphA2 oligomer size
Authors: Zapata-Mercado Elmer , Biener Gabriel , McKenzie Daniel , Wimley William C. , Pasquale Elena B. , Raicu Valerica , Hristova Kalina 
Published: June 2022

AbstractThe receptor tyrosine kinase (RTK) EphA2 is expressed in epithelial and endothelial cells and controls the assembly of cell-cell junctions. EphA2 has also been implicated in many diseases, including cancer. Unlike most RTKs, which signal predominantly as dimers, EphA2 readily forms higher order oligomers upon ligand binding. Here we investigated if a correlation exists between EphA2 signaling properties and the size of the EphA2 oligomers induced by multiple ligands, including the widely used ephrinA1-Fc ligand, the soluble monomeric m-ephrinA1, and novel engineered peptide ligands. We used Fluorescence Intensity Fluctuation (FIF) spectrometry to characterize the EphA2 oligomer populations induced by the different ligands. Interestingly, we found that different monomeric and dimeric ligands induce EphA2 oligomers with widely different size distributions. Comparison of FIF brightness distribution parameters and EphA2 signaling parameters reveals that the efficacy of EphA2 phosphorylation on tyrosine 588, which is indicative of receptor activation, correlates with EphA2 mean oligomer size. However, other characteristics, such as the efficacy of AKT inhibition and ligand bias coefficients, appear to be independent of EphA2 oligomer size. This work highlights the utility of FIF in RTK signaling research and demonstrates a quantitative correlation between the architecture of EphA2 signaling complexes and signaling features.
Long-read RNA Sequencing Improves the Annotation of the Equine Transcriptome
Authors: Peng S. , Dahlgren AR. , Hales EN. , Barber A.M. , Kalbfleisch T. , Petersen JL. , Bellone RR. , Mackowski M. , Cappelli K. , Capomaccio S. , Coleman SJ. , Distl O. , Giulotto E. , Waud B. , Hamilton N.A. , Leeb T. , Lindgren G. , Lyons LA. , McCue M. , MacLeod JN. , Metzger J. , Mickelson JR. , Murphy BA. , Orlando L. , Penedo C. , Raudsepp T. , Strand E. , Tozaki T. , Trachsel DS. , Velie BD. , Wade CM. , Cieslak J. , Finno CJ. 
Published: June 2022

1AbstractA high-quality reference genome assembly, a biobank of diverse equine tissues from the Functional Annotation of the Animal Genome (FAANG) initiative, and incorporation of long-read sequencing technologies, have enabled efforts to build a comprehensive and tissue-specific equine transcriptome. The equine FAANG transcriptome reported here provides up to 45% improvement in transcriptome completeness across tissue types when compared to either RefSeq or Ensembl transcriptomes. This transcriptome also provides major improvements in the identification of alternatively spliced isoforms, novel noncoding genes, and 3’ transcription termination site (TTS) annotations. The equine FAANG transcriptome will empower future functional studies of important equine traits while providing future opportunities to identify allele-specific expression and differentially expressed genes across tissues.
The Maximum Entropy Principle For Compositional Data
Authors: Weistuch Corey , Zhu Jiening , Deasy Joseph O. , Tannenbaum Allen R. 
Published: June 2022

AbstractIn this work, we provide a general method for inferring the stochastic behavior of compositional systems. Our approach is guided by the principle of maximum entropy, a data-driven modeling technique. In particular, we show that our method can accurately capture stochastic, inter-species relationships with minimal model parameters. We provide two proofs of principle. First, we measure the relative abundances of different bacteria and infer how they interact. Second, we show that our method outperforms a common alternative for the extraction of gene-gene interactions in triple-negative breast cancer.Author summaryCompositional systems, represented as proportions of some whole, are ubiquitous. They encompass the abundances of proteins in a cell, the distribution of organisms in nature, and the stoichiometry of the most basic chemical reactions. Thus, a central goal is to understand how such processes emerge from the behaviors of their components and their pairwise interactions. Such a study, however, is challenging for two key reasons. Firstly, such systems are complex and depend, often stochastically, on their constituent parts. Secondly, the data lie on a simplex which influences their correlations. We provide a general and data-driven modeling tool for compositional systems to resolve both of these issues. We achieve this through the principle of maximum entropy, which requires only minimal assumptions and limited experimental data in contrast to current alternatives. We show that our approach provides novel and biologically-intuitive insights and is promising as a comprehensive quantitative framework for compositional data.
Deciphering Hematopoiesis at single cell level through the lens of reduced dimensions
Authors: Singh Prashant , Zhai Yanan 
Published: June 2022

AbstractHematopoiesis plays a critical role in maintaining a diverse pool of blood cells throughout human life. Despite recent efforts with single-cell data analyses, the nature of the early cell fate decisions and compartmentalization of progenitors remains contentious due to the sparsity and noise of the data. Using publically available single-cell RNA-Seq hematopoietic data from bone marrow, with three different matrix factorization approaches to recover associated gene modules from cell clusters reveals a tri-directional and hierarchically-structured transcriptional landscape of hematopoietic differentiation. We also devised a bootstrap method, which in combination with the above can better characterize the progenitor compartments and retrieve cellular hierarchies.
Quantifying the Human Cost of Global Warming
Authors: Lenton Timothy M. , Xu Chi , Abrams Jesse F. , Ghadiali Ashish , Loriani Sina , Sakschewski Boris , Zimm Caroline , Ebi Kristie L. , Dunn Robert R. , Svenning Jens-Christian , Scheffer Marten 
Published: June 2022

AbstractThe costs of climate change are often estimated in monetary terms1,2but this raises ethical issues3. Here we express them in terms of numbers of people left outside the ‘human climate niche’4– defined as the historically highly-conserved distribution of relative human population density with respect to mean annual temperature (MAT). We show that climate change has already put ∼8% of people (>500 million) outside this niche. By end-of-century (2080-2100), current policies leading to around 2.7 °C global warming5-9could leave one third (21-42% or 2-4 billion) of a future 9.5 billion population outside the niche. Limiting global warming to 1.5 °C could halve this exposure, reducing it by ∼1.5 billion people. For the two countries with the most people affected – India and Nigeria – reducing global warming from 2.7 to 1.5 °C results in a >6-fold decrease in the population exposed to unprecedented temperatures, MAT ≥29 °C. The lifetime emissions of ∼3.5 global average citizens today (or ∼1.2 average US citizens) expose 1 future person to MAT ≥29 °C by end-of-century. That person comes from a place where emissions today are around half of the global average. These results highlight the need for more decisive policy action to limit the human costs and inequities of climate change.
Investigating mouse motor coordination using quantitative trait locus analysis to model the genetic underpinnings of developmental coordination disorder
Authors: Gill Kamaldeep , Rajan Jeffy Rajan Soundara , Chow Eric , Ashbrook David G. , Williams Robert W. , Zwicker Jill G. , Goldowitz Daniel 
Published: June 2022

ABSTRACTThe fundamental skills for motor coordination and motor control emerge through development, from infancy to late childhood years. Neurodevelopmental disorders such as Developmental Coordination Disorder (DCD) lead to impaired acquisition of motor skills. This study investigated motor behaviors that reflect the core symptoms of human DCD through the use of BXD recombinant inbred lines of mice that are known to have divergent phenotypes in many behavioral traits, including motor activity. We sought to correlate behavior in basic motor control tasks with the known genotypes of these reference populations of mice using quantitative trait locus (QTL) mapping. We used twelve BXD lines with an average of 16 mice per group to assess the onset of reflexes during the early neonatal stage of life and differences in motor coordination using the open field, rotarod, and gait analyses during the adolescent/young adulthood period. Results indicated significant variability between lines in as to when neonatal reflexes appeared as well as significant line differences for all measures of motor coordination. Five lines (BXD15, BXD27, BXD28, BXD75, and BXD86) struggled with sensorimotor coordination as seen in gait analysis, rotarod, and open field, similar to human presentation of DCD. We identified three significant quantitative trait loci for gait on proximal Chr 3, Chr 4 and distal Chr 6. Based on expression, function, and polymorphism within the mapped QTL intervals, 7 candidate genes(Gpr63, Spata5, Trpc3, Cntn6, Chl1, Grm7andOgg1)emerged. This study offers new insights into mouse motor behavior which promises to be a first murine model to explore the genetics and neural correlates of DCD.
EZH2/ hSULF1 axis mediates receptor tyrosine kinase signaling to shape cartilage tumor progression
Authors: Lin Zong-Shin , Chung Chiao-Chen , Liu Yu-Chia , Chang Chu-Han , Liu Hui-Chia , Liang Yung-Yi , Huang Teng-Le , Chen Tsung-Ming , Lee Che-Hsin , Tang Chih-Hsin , Chen Ya-Huey , Hung Mien-Chie 
Published: June 2022

AbstractBackgroundChondrosarcomas are primary cancers of cartilaginous tissue and capable of alteration to highly aggressive, metastatic, and treatment-refractory states, leading to a poor prognosis with a five-year survival rate at 11 months for the dedifferentiated subtype. At present, the surgical resection of chondrosarcoma is the only effective treatment, and no other treatment options including targeted therapies, conventional chemotherapies, or immunotherapies are available for these patients.MethodsA non-biased ChIP sequence, cDNA microarray analysis, and validation of chondrosarcoma cell lines identified sulfatase 1(SULF1) as the top EZH2-targeted gene to regulate chondrosarcoma progression. Receptor tyrosine kinase (RTK) array of chondrosarcoma cells with vector control or ectopically expressed SULF1 revealed that cMET was the downstream signal. The regulation of the EZH2/SULF1/cMET axis was further validated in mice and patient samples with mice models and chondrosarcoma tissue array, respectively.ResultsThe EZH2/SULF1/cMET axis is identified, which contributes to the malignancy of chondrosarcoma and provides a potential therapeutic option for the disease. Ectopically expressed SULF1 or pharmaceutical inhibition of the cMET pathway significantly retards the chondrosarcoma growth and extends mice survival.ConclusionsThe results not only established a signal pathway promoting the malignancy of chondrosarcoma but also provided a therapeutic potential for further development of effective target therapy to treat chondrosarcoma.
MARSY: A multitask deep learning framework for prediction of drug combination synergy scores
Authors: El Khili Mohamed Reda , Memon Safyan Aman , Emad Amin 
Published: June 2022

AbstractMotivationCombination therapies have emerged as a treatment strategy for cancers to reduce the probability of drug resistance and to improve outcome. Large databases curating the results of many drug screening studies on preclinical cancer cell lines have been developed, capturing the synergistic and antagonistic effects of combination of drugs in different cell lines. However, due to the high cost of drug screening experiments and the sheer size of possible drug combinations, these databases are quite sparse. This necessitates the development of transductive computational models to accurately impute these missing values.ResultsHere, we developed MARSY, a deep learning multi-task model that incorporates information on gene expression profile of cancer cell lines, as well as the differential expression signature induced by each drug to predict drug-pair synergy scores. By utilizing two encoders to capture the interplay between the drug-pairs, as well as the drug-pairs and cell lines, and by adding auxiliary tasks in the predictor, MARSY learns latent embeddings that improve the prediction performance compared to state-of-the-art and traditional machine learning models. Using MARSY, we then predicted the synergy scores of 133,722 new drug-pair cell line combinations, which we have made available to the community as part of this study. Moreover, we validated various insights obtained from these novel predictions using independent studies, confirming the ability of MARSY in making accurate novel predictions.Availability and ImplementationAn implementation of the algorithms in Python and cleaned input datasets are provided inhttps://github.com/Emad-COMBINE-lab/MARSY.Contactamin.emad@mcgill.caSupplementary InformationOnline-only supplementary data is available at the journal’s website.
Uncovering features of synapses in primary visual cortex through contrastive representation learning
Authors: Wilson Alyssa M. , Babadi Mehrtash 
Published: June 2022

SUMMARY3D EM connectomics image volumes are now surpassing sizes of 1 mm3, and are therefore beginning to contain multiple meaningful spatial scales of brain circuitry simultaneously. However, the sheer density of information in such datasets makes the development of unbiased, scalable machine learning techniques a necessity for extracting novel insights without extremely time-consuming, intensive labor. In this paper, we present SynapseCLR, a self-supervised contrastive representation learning method for 3D electron microscopy (EM) data, and use the method to extract feature representations of synapses from a 3D EM dataset from mouse visual cortex. We show that our representations separate synapses according to both their overall physical appearance and structural annotations of known functional importance. We further demonstrate the utility of our methodology for several valuable downstream tasks for the growing field of 3D EM connectomics. These include one-shot identification of defective synapse segmentations, dataset-wide similarity-based querying, and accurate imputation of annotations for unlabeled synapses, using only manual annotation of 0.2% of synapses in the dataset. In particular, we show that excitatory vs. inhibitory neuronal cell types can be assigned to individual synapses and highly truncated neurites with accuracy exceeding 99.8%, making this population accessible to connectomics analysis. Finally, we present a data-driven and unsupervised study of the manifold of synaptic structural variation, revealing its intrinsic axes of variation and showing that synapse structure is also strongly correlated with inhibitory neuronal subtypes.
The potent Toxoplasma gondii growth inhibitor QQ-437 does not bind to its predicted target, parasite adaptin3β, in yeast three-hybrid assays
Authors: Tran Fanny , Foderaro Jenna E. , Westwood Nicholas J. , Ward Gary E. 
Published: June 2022

AbstractNew drugs are needed to treat infections with Toxoplasma gondii, a ubiquitous protozoan parasite that can cause miscarriage, blindness, and life-threatening encephalitis in its human hosts. A novel N-benzoyl-2-hydroxybenzamide named QQ-437 was recently shown to be a potent inhibitor of T. gondii growth in vitro (EC50 = 16nM), and to reduce parasite load in a mouse model of infection. Intriguingly, mutations in the parasite protein TgAP3β, which is thought to play an important role in intracellular protein trafficking, confer resistance to QQ-437. In this report, we use yeast three-hybrid analysis to test the hypothesis that QQ-437 inhibits parasite growth via a direct effect on TgAP3β. We see no evidence for the ability of QQ-437 to bind directly to TgAP3β, suggesting that the mutation in TgAP3β that confers resistance does so through an indirect mechanism. Further studies are needed to identify the direct molecular target(s) of this promising class of compounds.