bluuebunny/crossref_metadata_2025_split huggingface dataset:
Analogies between the periphery of cancer and the leading edge of pulmonary fibrosis
Authors: Pernia Marin Monica , Salvatore Mary 
Published: April 2023

AbstractThe periphery of malignant tumors and the leading edge of fibrotic tissue have analogous metabolic pathways. Both use glycolysis as the primary source of energy to produce biomass with consequential acidification of the microenvironment. A low PH has been shown to increase the ability of cancer cells to invade the surrounding tissue in both in vitro and in vivo studies. The pH-dependent activation of TGF-B leading to myofibroblast activation is an important step in the initiation and progression of fibrosis. Markers of accelerated cell proliferation have also been reported in the periphery of malignant tumors and the leading edge of fibrosis. Understanding the shared molecular and metabolic characteristics of these conditions may explain the increased prevalence of cancer among patients with fibrosis.
Size matters: the impact of nucleus size on results from spatial transcriptomics
Authors: Mohammadi Elyas , Chojnowska Katarzyna , Bieńkowski Michał , Kostecka Anna , Koczkowska Magdalena , Żmijewski Michał A. , Jąkalski Marcin , Ingelsson Martin , Filipowicz Natalia , Olszewski Paweł , Davies Hanna , Wierzbicka Justyna M. , Hyman Bradley T. , Dumanski Jan P. , Piotrowski Arkadiusz , Mieczkowski Jakub 
Published: April 2023

Abstract
Background
Visium Spatial Gene Expression (ST) is a method combining histological spatial information with transcriptomics profiles directly from tissue sections. The use of spatial information has made it possible to discover new modes of gene expression regulations. However, in the ST experiment, the nucleus size of cells may exceed the thickness of a tissue slice. This may, in turn, negatively affect comprehensive capturing the transcriptomics profile in a single slice, especially for tissues having large differences in the size of nuclei.

Methods
Here, we defined the effect of Consecutive Slices Data Integration (CSDI) on unveiling accurate spot clustering and deconvolution of spatial transcriptomic spots in human postmortem brains. By considering the histological information as reference, we assessed the improvement of unsupervised clustering and single nuclei RNA-seq and ST data integration before and after CSDI.

Results
Apart from the escalated number of defined clusters representing neuronal layers, the pattern of clusters in consecutive sections was concordant only after CSDI. Besides, the assigned cell labels to spots matches the histological pattern of tissue sections after CSDI.

Conclusion
CSDI can be applied to investigate consecutive sections studied with ST in the human cerebral cortex, avoiding misinterpretation of spot clustering and annotation, increasing accuracy of cell recognition as well as improvement in uncovering the layers of grey matter in the human brain.
A methodological exploration to study 2D arm kinematics in Ophiuroidea (Echinodermata)
Authors: Goharimanesh Mona , Stöhr Sabine , Ghassemzadeh Fereshteh , Mirshamsi Omid , Adriaens Dominique 
Published: April 2023

AbstractBrittle stars, unlike most other echinoderms, do not use their small tube feet for locomotion but instead use their flexible arms to produce a rowing or reverse rowing movement. They are among the fastest-moving echinoderms with the ability of complex locomotory behaviors. Considering the high species diversity and variability in morphotypes, a proper understanding of intra- and interspecies variation in arm flexibility and movement is lacking. This study focuses on the exploration of the methods to investigate the variability in brittle star locomotion and individual arm use. We performed a two-dimensional (2D) image processing on horizontal movement only. The result indicated that sinuosity, disc displacement and arm angle are important parameters to interpret ophiuroid locomotion. A dedicated Python script to calculate the studied movement parameters and visualize the results applicable to all 5-armed brittle stars was developed. These results can serve as the basis for further research in robotics inspired by brittle star locomotion.
Identification of a sub-group of critically ill patients with high risk of intensive care unit-acquired infections and poor clinical course using a transcriptomic score
Authors: Bodinier Maxime , Monneret Guillaume , Casimir Marie , Fleurie Aurore , Conti Filippo , Venet Fabienne , Cazalis Marie-Angélique , Cerrato Elisabeth , Peronnet Estelle , Rimmelé Thomas , Lukaszewicz Anne-Claire , Brengel-Pesce Karen , Llitjos Jean-François 
Published: April 2023

Abstract
Background
The development of stratification tools based on the assessment of circulating mRNA of genes involved in the immune response is constrained by the heterogeneity of septic patients. The aim of this study is to develop a transcriptomic score based on a pragmatic combination of immune-related genes detected with a prototype multiplex PCR tool.

Methods
As training cohort, we used the gene expression dataset obtained from 176 critically ill patients enrolled in the REALISM study (NCT02638779) with various etiologies and still hospitalized in intensive care unit (ICU) at day 5–7. Based on the performances of each gene taken independently to identify patients developing ICU-acquired infections (ICU-AI) after day 5–7, we built an unweighted score assuming the independence of each gene. We then determined the performances of this score to identify a subgroup of patients at high risk to develop ICU-AI, and both longer ICU length of stay and mortality of this high-risk group were assessed. Finally, we validated the effectiveness of this score in a retrospective cohort of 257 septic patients.

Results
This transcriptomic score (TScore) enabled the identification of a high-risk group of patients (49%) with an increased rate of ICU-AI when compared to the low-risk group (49% vs. 4%, respectively), with longer ICU length of stay (13 days [95% CI 8–30] vs. 7 days [95% CI 6–9], p < 0.001) and higher ICU mortality (15% vs. 2%). High-risk patients exhibited biological features of immune suppression with low monocytic HLA-DR levels, higher immature neutrophils rates and higher IL10 concentrations. Using the TScore, we identified 160 high-risk patients (62%) in the validation cohort, with 30% of ICU-AI (vs. 18% in the low-risk group, p = 0.06), and significantly higher mortality and longer ICU length of stay.

Conclusions
The transcriptomic score provides a useful and reliable companion diagnostic tool to further develop immune modulating drugs in sepsis in the context of personalized medicine.
CasKAS: direct profiling of genome-wide dCas9 and Cas9 specificity using ssDNA mapping
Authors: Marinov Georgi K. , Kim Samuel H. , Bagdatli S. Tansu , Higashino Soon Il , Trevino Alexandro E. , Tycko Josh , Wu Tong , Bintu Lacramioara , Bassik Michael C. , He Chuan , Kundaje Anshul , Greenleaf William J. 
Published: April 2023

AbstractDetecting and mitigating off-target activity is critical to the practical application of CRISPR-mediated genome and epigenome editing. While numerous methods have been developed to map Cas9 binding specificity genome-wide, they are generally time-consuming and/or expensive, and not applicable to catalytically dead CRISPR enzymes. We have developed CasKAS, a rapid, inexpensive, and facile assay for identifying off-target CRISPR enzyme binding and cleavage by chemically mapping the unwound single-stranded DNA structures formed upon binding of a sgRNA-loaded Cas9 protein. We demonstrate this method in both in vitro and in vivo contexts.
Consequences and opportunities arising due to sparser single-cell RNA-seq datasets
Authors: Bouland Gerard A. , Mahfouz Ahmed , Reinders Marcel J. T. 
Published: April 2023

AbstractWith the number of cells measured in single-cell RNA sequencing (scRNA-seq) datasets increasing exponentially and concurrent increased sparsity due to more zero counts being measured for many genes, we demonstrate here that downstream analyses on binary-based gene expression give similar results as count-based analyses. Moreover, a binary representation scales up to ~ 50-fold more cells that can be analyzed using the same computational resources. We also highlight the possibilities provided by binarized scRNA-seq data. Development of specialized tools for bit-aware implementations of downstream analytical tasks will enable a more fine-grained resolution of biological heterogeneity.
DMC reports in the 21st century: towards better tools for decision-making
Authors: Vandemeulebroecke Marc , Baillie Mark , Mirshani Ardalan , Lesaffre Emmanuel 
Published: April 2023

Abstract
Data Monitoring Committees (DMCs) have the important task to protect the safety of current and future patients during the conduct of a clinical study. Unfortunately, their work is often made difficult by voluminous DMC reports that are poorly structured and difficult to digest. In this article, we suggest improved solutions. Starting from a principled approach and building upon previous proposals, we offer concrete and easily understood displays, including related computer code. While leveraging modern tools, the most important is that these displays support the DMC’s workflow in answering the relevant questions of interest. We hope that the adoption of these proposals can ease the task of DMCs, and importantly, lead to better decision-making for the benefit of patients.
Genetic and environmental contributions to co-occurring physical health conditions in autism spectrum condition and attention-deficit/hyperactivity disorder
Authors: Pan Pei-Yin , Taylor Mark J. , Larsson Henrik , Almqvist Catarina , Lichtenstein Paul , Lundström Sebastian , Bölte Sven 
Published: April 2023

Abstract
Background
Autism spectrum condition and attention-deficit/hyperactivity disorder (ADHD) are associated with a range of physical health conditions. The aim of this study was to examine the etiological components contributing to co-occurring physical health conditions in autism and ADHD.

Methods
In this nationwide Child and Adolescent Twin Study in Sweden, we analyzed data from 10,347 twin pairs aged 9 and 12. Clinical diagnoses of autism, ADHD, and physical health conditions were identified through the Swedish National Patient Register. Subclinical phenotypes of autism and ADHD were defined by symptom thresholds on a standardized parent-interview, the Autism–Tics, ADHD, and Other Comorbidities inventory. Associations between physical health conditions and autism/ADHD phenotypes were examined using generalized estimating equations. Bivariate twin models were applied to estimate the extent to which genetic and environmental risk factors accounted for physical health comorbidities.

Results
Similar patterns of association with physical health conditions were found in clinical and subclinical autism/ADHD, with odds ratios ranging from 1.31 for asthma in subclinical ADHD to 8.03 for epilepsy in clinical autism. The estimated genetic correlation (ra) with epilepsy was 0.50 for clinical autism and 0.35 for subclinical autism. In addition, a modest genetic correlation was estimated between clinical autism and constipation (ra = 0.31), functional diarrhea (ra = 0.27) as well as mixed gastrointestinal disorders (ra = 0.30). Genetic effects contributed 0.86 for mixed gastrointestinal disorders in clinical ADHD (ra = 0.21). Finally, subclinical ADHD shared genetic risk factors with epilepsy, constipation, and mixed gastrointestinal disorders (ra = 0.30, 0.17, and 0.17, respectively).

Limitations
Importantly, since medical records from primary care were not included in the registry data used, we probably identified only more severe rather than the full range of physical health conditions. Furthermore, it needs to be considered that the higher prevalence of physical health conditions among autistic children and children with ADHD could be associated with the increased number of medical visits.

Conclusions
Shared genetic effects contribute significantly to autism and ADHD phenotypes with the co-occurring physical health conditions across different organ systems, including epilepsy and gastrointestinal disorders. The shared genetic liability with co-occurring physical health conditions was present across different levels of autism and ADHD symptom severity.
Socio-demographic and economic inequity in the use of insecticide-treated bed nets during pregnancy: a survey-based case study of four sub-Saharan African countries with a high burden of malaria
Authors: Haileselassie Werissaw , Adam Ruth , Habtemichael Mizan , David Randy E. , Solomon Nabel , Workineh Salle , Haider Jemal , Belachew Ayele , Deressa Wakgari , Yan Guiyun , Kassaw Nigussie Assefa , Parker Daniel M. 
Published: April 2023

AbstractDespite global investments in malaria eradication and mitigation efforts, including the dissemination of ITNs to vulnerable communities, the goal of widespread malaria control among pregnant women has yet to be realized in many African countries. One of the explanations forwarded for this is related to the adoption and regular use of ITNs by pregnant women. Based on the available DHS and MIS data from four malaria high burden African countries– according to WHO malaria report 2020– inequality was measured by applying both relative and absolute summary measures for the four dimensions of inequality: economic status, education, place of residence and region. By considering the number of subgroups in each variable, simple and complex summary measures were used.ITN utilization by pregnant women showed an increasing trend over time in all the four countries. There was also significant inequality (variability) in the ITN utilization among population groups. DRC, Mozambique and Uganda showed noticeable inequality that favors the richest population, whereas in Nigeria the inequality was observed among both the rich and the poor during different survey yearsIn conclusion, in all the four countries, there were significant regional variations or differences in ITN use among pregnant mothers across all dimensions of inequality in the survey years. Tailored cost-effective interventions could be considered to improve ITN utilization among pregnant women.
Some novel peptides containing a modified pyrazolopyrimidine moiety: design, synthesis, and in vitro antibacterial screening
Authors: Al-Mohammadi Abdul-Raouf , Zayda Mohamed Ge , Zayda Mahmoud Ge , Abdel-Rahman Adel A.-H. , Yousef Einas , Magdy Amina 
Published: April 2023

AbstractNumerous peptide drugs are currently undergoing advanced phases of clinical testing to determine their efficacy in combating antibiotic-resistant bacterial pathogens. Our aim was to prepare some novel peptides containing a modified pyrazolopyrimidine moiety and assess their activity against a set of selected bacteria in comparison to a widely used antibiotic, ciprofloxacin. In this study, eight new peptide compounds incorporating a modified pyrazolopyrimidine moiety were synthesized. Our results revealed that compounds 4 and 5, which contained only the pyrazolopyrimidine scaffold were less active than the peptide-conjugated pyrazolopyrimidines 10, 11, 13, 14, 15, and 17. The antibacterial activities of the eight novel compounds 4, 5, 10, 11, 13, 14, 15, and 17 were evaluated against a panel of bacterial strains. All the novel compounds exhibited potent antibacterial activity against Staphylococcus aureus, Enterococcus faecalis, and Pseudomonas aeruginosa strains compared to the reference antibiotic ciprofloxacin. The tested Escherichia coli strain displayed resistance against the newly synthesized compounds. Moreover, P. aeruginosa strain displayed resistance against ciprofloxacin and six of the newly synthesized compounds. Compounds 15 and 17 effectively inhibited the growth of the P. aeruginosa strain at MIC ≥ 1 μg/mL. Our results are encouraging and urge additional biological and pharmacological screening of the most active compounds against drug-resistant microbial strains.
Disentangling temporal associations in marine microbial networks
Authors: Deutschmann Ina Maria , Krabberød Anders K. , Latorre Francisco , Delage Erwan , Marrasé Cèlia , Balagué Vanessa , Gasol Josep M. , Massana Ramon , Eveillard Damien , Chaffron Samuel , Logares Ramiro 
Published: April 2023

Abstract
Background
Microbial interactions are fundamental for Earth’s ecosystem functioning and biogeochemical cycling. Nevertheless, they are challenging to identify and remain barely known. Omics-based censuses are helpful in predicting microbial interactions through the statistical inference of single (static) association networks. Yet, microbial interactions are dynamic and we have limited knowledge of how they change over time. Here, we investigate the dynamics of microbial associations in a 10-year marine time series in the Mediterranean Sea using an approach inferring a time-resolved (temporal) network from a single static network.

Results
A single static network including microbial eukaryotes and bacteria was built using metabarcoding data derived from 120 monthly samples. For the decade, we aimed to identify persistent, seasonal, and temporary microbial associations by determining a temporal network that captures the interactome of each individual sample. We found that the temporal network appears to follow an annual cycle, collapsing, and reassembling when transiting between colder and warmer waters. We observed higher association repeatability in colder than in warmer months. Only 16 associations could be validated using observations reported in literature, underlining our knowledge gap in marine microbial ecological interactions.

Conclusions
Our results indicate that marine microbial associations follow recurrent temporal dynamics in temperate zones, which need to be accounted for to better understand the functioning of the ocean microbiome. The constructed marine temporal network may serve as a resource for testing season-specific microbial interaction hypotheses. The applied approach can be transferred to microbiome studies in other ecosystems.
Gauge your phage: benchmarking of bacteriophage identification tools in metagenomic sequencing data
Authors: Ho Siu Fung Stanley , Wheeler Nicole E. , Millard Andrew D. , van Schaik Willem 
Published: April 2023

AbstractBackgroundThe prediction of bacteriophage sequences in metagenomic datasets has become a topic of considerable interest, leading to the development of many novel bioinformatic tools. A comparative analysis of ten state-of-the-art phage identification tools was performed to inform their usage in microbiome research.MethodsArtificial contigs generated from complete RefSeq genomes representing phages, plasmids, and chromosomes, and a previously sequenced mock community containing four phage species, were used to evaluate the precision, recall, and F1 scores of the tools. We also generated a dataset of randomly shuffled sequences to quantify false-positive calls. In addition, a set of previously simulated viromes was used to assess diversity bias in each tool’s output.ResultsVIBRANT and VirSorter2 achieved the highest F1 scores (0.93) in the RefSeq artificial contigs dataset, with several other tools also performing well. Kraken2 had the highest F1 score (0.86) in the mock community benchmark by a large margin (0.3 higher than DeepVirFinder in second place), mainly due to its high precision (0.96). Generally, k-mer-based tools performed better than reference similarity tools and gene-based methods. Several tools, most notably PPR-Meta, called a high number of false positives in the randomly shuffled sequences. When analysing the diversity of the genomes that each tool predicted from a virome set, most tools produced a viral genome set that had similar alpha- and beta-diversity patterns to the original population, with Seeker being a notable exception.ConclusionsThis study provides key metrics used to assess performance of phage detection tools, offers a framework for further comparison of additional viral discovery tools, and discusses optimal strategies for using these tools. We highlight that the choice of tool for identification of phages in metagenomic datasets, as well as their parameters, can bias the results and provide pointers for different use case scenarios. We have also made our benchmarking dataset available for download in order to facilitate future comparisons of phage identification tools.
The patterns and driving forces of dengue invasions in China
Authors: Zhao Zhe , Yue Yujuan , Liu Xiaobo , Li Chuanxi , Ma Wei , Liu Qiyong 
Published: April 2023

Abstract
Background
Global connectivity and environmental change pose continuous threats to dengue invasions from worldwide to China. However, the intrinsic relationship on introduction and outbreak risks of dengue driven by the landscape features are still unknown. This study aimed to map the patterns on source-sink relation of dengue cases and assess the driving forces for dengue invasions in China.

Methods
We identified the local and imported cases (2006–2020) and assembled the datasets on environmental conditions. The vector auto-regression model was applied to detect the cross-relations of source-sink patterns. We selected the major environmental drivers via the Boruta algorithm to assess the driving forces in dengue outbreak dynamics by applying generalized additive models. We reconstructed the internal connections among imported cases, local cases, and external environmental drivers using the structural equation modeling.

Results
From 2006 to 2020, 81,652 local dengue cases and 12,701 imported dengue cases in China were reported. The hotspots of dengue introductions and outbreaks were in southeast and southwest China, originating from South and Southeast Asia. Oversea-imported dengue cases, as the Granger-cause, were the initial driver of the dengue dynamic; the suitable local bio-socioecological environment is the fundamental factor for dengue epidemics. The Bio8 [odds ratio (OR) = 2.11, 95% confidence interval (CI): 1.67–2.68], Bio9 (OR = 291.62, 95% CI: 125.63–676.89), Bio15 (OR = 4.15, 95% CI: 3.30–5.24), normalized difference vegetation index in March (OR = 1.27, 95% CI: 1.06–1.51) and July (OR = 1.04, 95% CI: 1.00–1.07), and the imported cases are the major drivers of dengue local transmissions (OR = 4.79, 95% CI: 4.34–5.28). The intermediary effect of an index on population and economic development to local cases via the path of imported cases was detected in the dengue dynamic system.

Conclusions
Dengue outbreaks in China are triggered by introductions of imported cases and boosted by landscape features and connectivity. Our research will contribute to developing nature-based solutions for dengue surveillance, mitigation, and control from a socio-ecological perspective based on invasion ecology theories to control and prevent future dengue invasion and localization.

Graphical Abstract