bluuebunny/crossref_metadata_2025_split huggingface dataset:
Four Years of COVID-19: Saudi Arabia, Egypt and Pakistan Have the Highest Research Growth Rates From 2020-2023
Authors: Hassan Waseem , Zafar Mehreen 
Published: January 2024

AbstractWe tried to assess the global research scholarly output after COVID-19 (from 2020 to 2023). Based on Scopus record, the world has produced 15, 041, 579 publications with 86, 165, 933 citations. We analyzed those countries, which have published at least 150, 000 research papers. For each country, we retrieved total number of publications, % growth rate, total citations, citations per paper, Field Weighted Citation Impact (FWCI), and % international collaboration. Twenty-seven (n=27) countries were found to be highly productive, with China leading the way in number of publications. Citation metrics are dominated by the USA, China, and European countries. Specifically, Switzerland, Netherlands, and Australia are notable for their high impact and influence. Saudi Arabia achieved the highest growth rate of 53.5%, and highest international collaboration (76.5%). Infact Saudi Arabia also attained high citations per article (8.8), and an FWCI of 1.63. While, Pakistan exhibited an 8.4 citations per article, FWCI of 1.54, growth rate of 34.9%, and collaborative percentage of 64.9%. Egypt also attained the 2ndhighest growth rate (n=36.1). Based on four (n=4) distinct performance metrics, Pakistan and Saudi Arabia were in the top ten group.
Metatranscriptomic analysis indicates prebiotic effect of Isomalto/malto-polysaccharides on human colonic microbiotain-vitro
Authors: Borewicz Klaudyna , Hornung Bastian , Gu Fangjie , van der Zaal Pieter H. , Schols Henk A. , Schaap Peter J. , Smidt Hauke 
Published: January 2024

AbstractIsomalto/malto-polysaccharides (IMMPs) are a novel type of soluble dietary fibres with a prebiotic potential promoting growth of beneficial microbes in the gut. However, the mode of action of IMMPs remains unknown. Previous studies on IMMPs showed an increase in total bacteria, especially lactobacilli, and higher production of short chain fatty acids (SCFA) when IMMPs were fed to rats or used duringin vitrofermentation. Here we investigated with metatranscriptomics how IMMPs with different amounts of α-(1→6) glycosidic linkages affected microbial function during incubation with human faecal inoculum. We showed that active microbial community dynamics during fermentation varied depending on the type of IMMP used and that the observed changes were reflected in the community gene expression profiles. Based on metatranscriptome analysis, members ofBacteroides,LactobacillusandBifidobacteriumwere the predominant degraders of IMMPs, and the increased gene expression in these bacteria correlated with high amounts of α-(1→6) glycosidic linkages. We also noted an increase in relative abundance of these bacteria and an activation of pathways involved in SCFA synthesis. Our findings could provide a baseline for more targeted approaches in designing prebiotics for specific bacteria and to achieve more controlled modulation of microbial activity towards desired health outcomes.
GTPase-activating protein ARAP1 regulates circular dorsal ruffles as a nutrient uptake mechanism in the Hep3B hepatocellular carcinoma cell line
Authors: Sun Xiaowei , Li Yanan , He Yuxin , Cheng Longjiao , Wei Jinzi , Du Linxuan , Shen Zhongyang , Yoshida Sei 
Published: January 2024

ABSTRACTCircular dorsal ruffles (CDRs), large-scale rounded membrane ruffles, function as precursors of macropinocytosis. We recently reported that CDRs are exposed in the Hep3B hepatocellular carcinoma cell line, while not in other hepatocellular carcinoma cell lines, indicating that the CDRs in Hep3B are associated with malignant potential. In this study, we investigated the cellular function of CDRs in Hep3B cells by focusing on the molecular mechanisms of the GTPase-activating protein ARAP1. ARAP1 was localized to the CDRs, the sizes of which were reduced by deletion of this protein. High-resolution scanning electron micrographs revealed that CDRs comprise small vertical lamellipodia, the expression pattern of which was disrupted in ARAP1 KO cells. Extracellular solute uptake, rate of cell growth, and malignant potential were attenuated in the KO cells. ARAP1 is also localized in Hep3B cell mitochondria, although not in those of the Huh7 hepatocellular carcinoma cell line. On the basis of these findings, we propose that the aberrant expression of ARAP1 in Hep3B cells modulates CDRs, thereby resulting in an excess uptake of nutrients as an initial event in cancer development.SUMMARY STATEMENTARAP1 regulates circular dorsal ruffles (CDRs) in the Hep3B HCC cell line and deletion of this protein attenuates malignant potential, thereby indicating the involvement of CDRs in cancer development.
Imaging spectroscopy reveals topographic variability effects on grassland functional traits and drought responses
Authors: Dao Phuong D. , He Yuhong , Lu Bing , Axiotis Alexander 
Published: January 2024

AbstractFunctional traits and their variations are essential indicators of plant metabolism, growth, distribution, and survival and determine how a plant and an ecosystem function. Under the same climatic condition, traits can vary largely between species and within the same species growing in different topographic conditions. When drought stress occurs, plants that grow in these conditions may respond differently as their topography-driven tolerance and adaptability differ. Insights into topographic variability-driven trait variation and drought response can improve our prediction of ecosystem functioning and ecological impacts. Imaging spectroscopy allows accurate detection of plant species, retrieval of functional traits, and characterization of topography-driven and drought impacts on trait variation across space. However, the use of this data in a heterogeneous grassland ecosystem is challenging as species are small, high mixed, spectrally and texturally similar, and highly varied with small-scale variation in topography. In this paper, we introduce the first study that explores the use of high-resolution airborne imaging spectroscopy to characterize the variation of common traits, including chlorophylls (Chl), carotenoids (Car), Chl/Car ratio, water content (WC), and leaf area index (LAI), across topographic gradients and under drought stress at the species level in a heterogeneous grassland. The results reveal that there were significant relationships between functional traits and topographic variability, and the degree of the relationships deferred among species and under different environmental conditions. The results also show that drought-induced trait responses varied significantly within and between species, especially between drought-tolerant invasive species and native species, between lower and upper slope positions. The study contributes greatly to the advancement in understanding biological and ecological processes for a better prediction of ecosystem functioning under stressed environments.
Beige adipose tissue-derived extracellular vesicles: a potent metabolic regulator and a novel remedy for nonalcoholic fatty liver disease
Authors: Zhang Kai , Zhang Sha , Sui Bing-Dong , Yuan Yuan , Liu Lu , Ying Si-Qi , Li Cheng-Han , Zhang Kai-Chao , Xing Shu-Juan , Yang Zhi-Wei , Sun Yang , Yu Li-Juan , Liu Jin , Jin Yan , Zheng Chen-Xi , Kong Liang 
Published: January 2024

AbstractAdipose tissue (AT) is an essential metabolic and endocrine organ, which are categorized into the white adipose tissue (WAT) and the brown adipose tissue (BAT), as well as the beige adipose tissue (BeAT) that derives from WAT browning. Notably, extracellular vesicles (EVs), especially tissue-produced EVs, have been recognized to be critical players in multiple physiological and pathophysiological settings and provide efficient strategy for disease treatment. However, little is known about the BeAT-derived EVs (BeEVs). In this study, we induced BeEV formation by cold stimulation and extracted EVs from three kinds of ATviaenzyme digestion combined with gradient centrifugation. The isolated BeEVs possess typical morphological, structural and marker characteristics of EVs. Proteomics analysis further demonstrated that the BeEVs hold a distinct protein profile while are enriched with multiple metabolic regulatory proteins. Importantly, systemic injection of BeEVs into mice improved metabolic dysfunction in a nonalcoholic fatty liver disease (NAFLD) model induced by high-fat diet (HFD). Moreover, we demonstrated that the BeEVs alleviated liver steatosisviadecreasing the lipogenesis. These findings promote the understanding of AT-EVs and shed light on the isolation, identification and applications of BeEVs as a potent metabolic regulator and novel remedy for metabolic diseases.
Transoceanic pathogen circulation in the age of sail and steam
Authors: Blackmore Elizabeth N. , Lloyd-Smith James O. 
Published: January 2024

AbstractIn the centuries following Christopher Columbus’s 1492 voyage to the Americas, transoceanic travel opened unprecedented pathways for global pathogen circulation. Yet no biological transfer is a single, discrete event. We use mathematical modeling to quantify historical risk of shipborne pathogen introduction, exploring the respective contributions of journey time, ship size, population susceptibility, transmission intensity, density dependence, and pathogen biology. We contextualize our results using port arrivals data from San Francisco, 1850–1852, and from a selection of historically significant voyages, 1492–1918. We offer numerical estimates of introduction risk across historicallyrealistic ranges of journey time and ship population size, and show that both steam travel and shipping regimes that involved frequent, large-scale movement of people substantially increased risk of transoceanic pathogen circulation.
Image-Based Recognition of Parasitoid Wasps Using Advanced Neural Networks
Authors: Shirali Hossein , Hübner Jeremy , Both Robin , Raupach Michael , Schmidt Stefan , Pylatiuk Christian 
Published: January 2024

AbstractHymenoptera have some of the highest diversity and number of individuals among insects. Many of these species potentially play key roles as food sources, pest controllers, and pollinators. However, little is known about their diversity and biology, and about 80% of the species have not been described yet. Classical taxonomy based on morphology is a rather slow process, but DNA barcoding has already brought considerable progress in identification. Innovative methods such as image-based identification and automation can even further speed up the process. We present a proof of concept for image data recognition of a parasitic wasp family, the Diapriidae (Hymenoptera), obtained as part of the GBOL III project. These tiny (1.2 - 4.5 mm) wasps were photographed and identified using DNA barcoding to provide a solid ground truth for training a neural network. Subsequently, three different neural network architectures were trained, evaluated, and optimized. As a result, 11 different classes of diaprids and one class of “other Hymenoptera ’’ can be classified with an average accuracy of 96%. Additionally, the sex of the specimen can be classified automatically with an accuracy of > 96%.
Identifying Factors Important for Conservation at Sites of Synonymous Variations
Authors: Ramasubramanian Abhirami , Sunderam Uma , Srinivasan Rajgopal 
Published: January 2024

AbstractSynonymous mutations can have a deleterious effect leading to disease, even though they are not protein altering. Variations at genomic sites leading to synonymous variants are frequently highly conserved across species. Several prediction methods have been developed to assess the impact of synonymous mutations and are highly dependent on having validated sets of both deleterious and benign synonymous mutations. However, validated data available for deleterious synonymous mutations is sparse unlike for missense mutations. Rather than develop a model for predicting pathogenicity of synonymous variants, we seek to understand the relative importance of various factors that lead to conservation at sites of synonymous variants. Our study built machine learning models using various features on a large set of reported and generated synonymous variants (Zeng Z et al, 2019) to predict conservation (Genomic Evolutionary Rate Profiling – Rejected Substitution (GERP RS) base scores and Phylogenetic p-values for 100 vertebrates (PP100)) at genomic sites. We used the extreme gradient boosting classifier to classify sites as high, medium and low conservation at different cutoffs. Our experiments report an AUC between 0.74-0.79 and the sensitivity was significant. Of the features we explored, a few alternate allele independent properties were repeatedly flagged as having high impact. These findings provide information for predictors to further improve models for synonymous variant impact.
Disruption of consciousness depends on insight in OCD and on positive symptoms in schizophrenia
Authors: Tumkaya Selim , Yücens Bengü , Gündüz Muhammet , Maheu Maxime , Berkovitch Lucie 
Published: January 2024

ABSTRACTDisruption of conscious access contributes to the advent of psychotic symptoms in schizophrenia but could also explain lack of insight in other psychiatric disorders.In this study, we explored how insight and psychotic symptoms related to disruption of consciousness. We explored consciousness in patients with schizophrenia, patients with obsessive-compulsive disorder (OCD) with good vs. poor insight and matched controls. Participants underwent clinical assessments and performed a visual masking task allowing us to measure individual consciousness threshold. We used a principal component analysis to reduce symptom dimensionality and explored how consciousness measures related to symptomatology.We found that clinical dimensions could be well summarized by a restricted set of principal components which also correlated with the extent of consciousness disruption. More specifically, positive symptoms were associated with impaired conscious access in patients with schizophrenia whereas the level of insight delineated two subtypes of OCD patients, those with poor insight who had consciousness impairments similar to patients with schizophrenia, and those with good insight who resemble healthy controls.Our study provides new insights about consciousness disruption in psychiatric disorders, showing that it relates to positive symptoms in schizophrenia and with insight in OCD. In OCD, it revealed a distinct subgroup sharing neuropathological features with schizophrenia. Our findings refine the mapping between symptoms and cognition, paving the way for a better treatment selection.
Patient-Derived Tumor Organoid and Fibroblast Assembloid Models for interrogation of the tumor microenvironment in Esophageal Adenocarcinoma
Authors: Sharpe Benjamin P. , Nazlamova Liliya A. , Tse Carmen , Johnston David A. , Blyth Rhianna , Pickering Oliver J. , Grace Ben , Harrington Jack , Rajak Rushda , Rose-Zerilli Matthew , Walters Zoe S. , Underwood Tim J. 
Published: January 2024

AbstractThe tumor microenvironment (TME) comprises all non-tumor elements of cancer and strongly influences disease progression and phenotype. To understand tumor biology and accurately test new therapeutic strategies, representative models should contain both tumor cells and normal cells of the TME. Here we describe and characterize co-culture tumor-derived organoids and cancer-associated fibroblasts (CAFs), a major component of the TME, in matrix-embedded assembloid models of esophageal adenocarcinoma (EAC). We demonstrate that the assembloid models faithfully recapitulate the differentiation status of EAC and different CAF phenotypes found in the EAC patient TME. We evaluate cell phenotypes by combining tissue clearing techniques with wholemount immunofluorescence and histology, providing a practical framework for characterization of cancer assembloids.
Beyond benchmarking: towards predictive models of dataset-specific single-cell RNA-seq pipeline performance
Authors: Fang Cindy , Selega Alina , Campbell Kieran R 
Published: January 2024

AbstractThe advent of single-cell RNA-sequencing (scRNA-seq) has driven significant computational methods development for all steps in the scRNA-seq data analysis pipeline, including filtering, normalization, and clustering. The large number of methods and their resulting parameter combinations has created a combinatorial set of possible pipelines to analyze scRNA-seq data, which leads to the obvious question: which is best? Several benchmarking studies have sought to compare methods to answer this, but frequently find variable performance depending on dataset and pipeline characteristics. Alternatively, the large number of publicly available scRNA-seq datasets along with advances in supervised machine learning raise a tantalizing possibility: could the optimal pipeline be predicted for a given dataset? Here we begin to answer this question by applying 288 scRNA-seq analysis pipelines to 86 datasets and quantifying pipeline success via a range of measures evaluating cluster purity and biological plausibility. We build supervised machine learning models to predict pipeline success given a range of dataset and pipeline characteristics. We find both that prediction performance is significantly better than random and that in many cases pipelines predicted to perform well provide clustering outputs similar to expert-annotated cell type labels. Finally, we identify characteristics of scRNA-seq datasets that correlate with strong prediction performance that could guide when such prediction models may be useful.
Experimental evaluation of Eastern box turtle (Terrapene carolina carolina) detectability in visual search surveys
Authors: Heinle William , Beswick Noelle , Wapman Emily , Royle J. Andrew 
Published: January 2024

AbstractUnderstanding how detection probability varies over time, space, or in response to measurable covariates is important to inform the monitoring and assessment of many species. A standard model to understand detectability – the availability/perception model – admits that detection probability is the composite of two components: availability and perception. Availability is largely affected by environmental and behavioral factors, whereas perception is primarily affected by attributes of individual observers and survey protocols, and thus can potentially be partially controlled by survey design. We designed and implemented a field study to understand the perception component of detection for Eastern box turtles (Terrapene carolina carolina) using visual encounter surveys. We obtained and deployed museum specimens of Eastern box turtle shells and subjected them to visual search surveys by observers in realistic field situations. Overall, about 50% of the box turtle shells were detected by observers including, 41.5% in the ‘partially visible’ state and 63% in the ‘fully visible’ state. There were significant differences among observers, which may be due to observer-specific variation in search technique -- the observers varied in how well they achieved the protocol guidance.
FinaleMe: Predicting DNA methylation by the fragmentation patterns of plasma cell-free DNA
Authors: Liu Yaping , Reed Sarah C. , Lo Christopher , Choudhury Atish D. , Parsons Heather A. , Stover Daniel G. , Ha Gavin , Gydush Gregory , Rhoades Justin , Rotem Denisse , Freeman Samuel , Katz David , Bandaru Ravi , Zheng Haizi , Fu Hailu , Adalsteinsson Viktor A. , Kellis Manolis 
Published: January 2024

AbstractAnalysis of DNA methylation in cell-free DNA (cfDNA) reveals clinically relevant biomarkers but requires specialized protocols and sufficient input material that limits its applicability. Millions of cfDNA samples have been profiled by genomic sequencing. To maximize the gene regulation information from the existing dataset, we developed FinaleMe, a non-homogeneous Hidden Markov Model (HMM), to predict DNA methylation of cfDNA and, therefore, tissues-of-origin directly from plasma whole-genome sequencing (WGS). We validated the performance with 80 pairs of deep and shallow-coverage WGS and whole-genome bisulfite sequencing (WGBS) data.
Deciphering the molecular mechanisms underlying anti-pathogenic potential of a polyherbal formulation Enteropan®against multi-drug resistantPseudomonas aeruginosa
Authors: Parmar Sweety , Gajera Gemini , Thakkar Nidhi , Palep Hanmanthrao S , Kothari Vijay 
Published: January 2024

AbstractAnti-pathogenic potential of a polyherbal formulation Enteropan®was investigated against a multidrug resistant strain of the bacteriumPseudomonas aeruginosa. Enteropan-pre-exposedP. aeruginosadisplayed reduced (∼70%↓) virulence towards the model hostCaenorhabditis elegans. Enteropan affected various traits like biofilm formation, protein synthesis and secretion, quorum-modulated pigment production, antibiotic susceptibility, nitrogen metabolism etc. in this pathogen.P. aeruginosacould not develop complete resistance to the virulence-attenuating activity of Enteropan even after repeated exposure to this polyherbal formulation. Whole transcriptome analysis showed 17% ofP. aeruginosagenome to get differentially expressed under influence of Enteropan. Major mechanisms through which Enteropan exerted its anti-virulence activity were found to be generation of nitrosative stress, oxidative stress, envelop stress, quorum modulation, disturbance of protein homeostasis and metal homeostasis. Network analysis of the differently expressed genes resulted in identification of 10 proteins with high network centrality as potential targets from among the down-regulated genes. Differential expression of genes coding for five (rpoA, tig, rpsB, rpsL, andrpsJ) of these targets was validated through RT-PCR too, and they can further be pursued as potential targets by various drug discovery programmes.