bluuebunny/crossref_metadata_2025_split huggingface dataset:
Ethnic Inequalities in Palliative Care Prescribing – A Rapid Systematic Review
Authors: Kunonga Tafadzwa Patience , Johnson Eugenie Evelynne , Din Usvah , Westhead Elizabeth , Dewhurst Felicity , Hanratty Barbara 
Published: November 2024

AbstractContextEffective palliative care involves managing the many symptoms commonly experienced towards the end-of-life. Appropriate prescribing is key to this care, and ethnic inequalities may lead to unequal treatment and poorer outcomes for minority groups. Understanding these disparities is critical to ensuring equitable care.ObjectivesTo investigate ethnic inequalities in palliative care prescribing amongst adults residing in high-income countries.MethodsThe review was registered with the International Prospective Register of Systematic Reviews (PROSPERO) under registration number CRD42023476977. We conducted searches across three electronic databases (MEDLINE, Embase, and CINAHL) from January 2000 to November 2023. Screening, data extraction and quality assessment were conducted independently by two reviewers. Quality was assessed using various JBI Critical Appraisal tools. Due to the heterogeneity of included studies, a narrative review was undertaken without a meta-analysis.ResultsOut of 7880 references identified, 10 studies met the inclusion criteria, all conducted in the United States. Overall, five studies were deemed to be high quality and five were fair quality. The studies highlighted ethnic disparities in palliative care prescribing. Minority populations were less likely to receive pain management medications, particularly opioids, compared to non-Hispanic whites. Increased age, female gender, lower socioeconomic status, and place of residence were also related to differences in prescribing practices.ConclusionsThis rapid systematic review suggests that there are ethnic inequalities in palliative care symptom management prescribing, highlighting a possible gap in care for ethnic minority patients. Research beyond the USA is needed to understand if there are international disparities in palliative care prescribing.Key messageThis article reports a rapid systematic review on ethnic inequalities in palliative care prescribing for symptom control in high-income countries. Findings highlight a gap in care for ethnic minority patients. Further investigation is needed to understand how widespread disparities in palliative care prescribing are, across the world.
Clickable PEG-norbornene microgels support suspension bioprinting and microvascular assembly
Authors: Zhang Irene W. , Choi Lucia S. , Friend Nicole E. , McCoy Atticus J. , Midekssa Firaol S. , Alsberg Eben , Lesher-Pérez Sasha Cai , Stegemann Jan P. , Baker Brendon M. , Putnam Andrew J. 
Published: November 2024

AbstractThe development of perfusable and multiscale vascular networks remains one of the largest challenges in tissue engineering. As such, there is a need for the creation of customizable and facile methods to produce robustly vascularized constructs. In this study, secondarily crosslinkable (clickable) poly(ethylene glycol)-norbornene (PEGNB) microbeads were produced and evaluated for their ability to sequentially support suspension bioprinting and microvascular self-assembly towards the aim of engineering hierarchical vasculature. The clickable PEGNB microbead slurry exhibited mechanical behavior suitable for suspension bioprinting of sacrificial bioinks, could be UV crosslinked into a granular construct post-print, and withstood evacuation of the bioink and subsequent perfusion of the patterned void space. Endothelial and stromal cells co-embedded within jammed RGD-modified PEGNB microbead slurries assembled into capillary-scale vasculature after secondary crosslinking of the beads into granular constructs, with endothelial tubules forming within the interstitial space between microbeads and supported by the perivascular association of the stromal cells. Microvascular self-assembly was not impacted by printing sacrificial bioinks into the cell-laden microbead support bath before UV crosslinking. Collectively, these results demonstrate that clickable PEGNB microbeads are a versatile substrate for both suspension printing and microvascular culture and may be the foundation for a promising methodology to engineer hierarchical vasculature.
Peroxidasin expression is increased in intratumoural capillaries and in proximal tubular cells adjacent to clear cell renal cell carcinoma
Authors: Silva Roberto , Almeida Jorge Reis , Coelho Ana Rita , Brandão Isabel , Gomes Bárbara , Alencastre Inês Soares , Oliveira João Paulo 
Published: November 2024

AbstractPeroxidasin (PXDN), is a heme peroxidase with a critical role in the crosslinking of type IV collagen, being essential for basement membrane integrity. In many cancers, PXDN overexpression has been linked with processes associated with poor disease outcomes, namely the impairment of endothelial functions, pathogenesis of vascular diseases, vascular remodelling, apoptosis, and tissue fibrosis. In RCC, almost nothing is so far known. In this work we characterized the expression of PXDN in tumour and non-neoplastic adjacent tissue from clear cell renal cell carcinoma (ccRCC) and renal oncocytoma by immunohistochemistry. Results showed a significant increase of PXDN expression in intratumoural capillaries of ccRCC in comparison with oncocytoma, and an increase in the proximal tubular epithelial cells of non-neoplastic adjacent parenchyma from ccRCC cases, in comparison with the same area from oncocytomas. Overall, our results suggest, for the first time, that PXDN may have a role in tumour angiogenesis that may favour metastases and tumour malignity, being also enrolled in the crosstalk between the tumour and adjacent tissue, that deserves further investigation.HighlightsPeroxidasin is increased in ccRCC microvasculature comparing to oncocytoma.Peroxidasin is increased in proximal tubules of ccRCC kidney adjacent parenchyma.Is Peroxidasin a modulator of tumour microenvironment promoting angiogenesis?
Pan-Cancer Drug Sensitivity Prediction from Gene Expression using Deep Learning
Authors: Ocasio Beronica A. , Hu Jiaming , Stathias Vasileios , Martinez Maria J. , Burnstein Kerry L. , Schürer Stephan C. 
Published: November 2024

ABSTRACTCancer is a group of complex diseases, with tumor heterogeneity, durable drug efficacy, emerging resistance, and host toxicity presenting major challenges to the development of effective cancer therapeutics. While traditionally used methods have remained limited in their capacity to overcome these challenges in cancer drug development, efforts have been made in recent years toward applying “big data” to cancer research and precision oncology. By curating, standardizing, and integrating data from various databases, we developed deep learning architectures that use perturbation and baseline transcriptional signatures to predict efficacious small molecule compounds and genetic dependencies in cancer. A series of internal validations followed by prospective validation in prostate cancer cell lines were performed to ensure consistent performance and model applicability. We reportSensitivitySeq, a novel bioinformatics tool for prioritizing small molecule compounds and gene dependenciesin silicoto drive the development of targeted therapies for cancer. To the best of our knowledge, this is the first supervised deep learning approach, validatedin vitro, to predict drug sensitivity using baseline cancer cell line gene expression alongside cell line-independent perturbation-response consensus signatures.GRAPHICAL ABSTRACT
Rapid and In-situ Detection of Biological Agents via Near-Infrared Spectroscopy and Cloud-Powered Neural Networks
Authors: Leseigneur Chloé , Radgen-Morvant Isabelle , Metzger César , Esseiva Pierre , Croll Daniel , Miéville Pascal 
Published: November 2024

ABSTRACTThe contagious nature of certain biological agents and the difficulty in treating infections render them a significant threat to public health and safety. In situations involving chemical, biological, radiological, and nuclear (CBRN) agents, effective detection is of paramount importance to prevent the undetected spread of these agents and enable swift and targeted responses tailored to the specific threat. Although portable detection tools are effective for chemical and nuclear detection, current biological detection methods face several challenges, including limited mobility, extended processing times, and varying accuracy. In the context of biological threats, where agents such as anthrax can be rapidly dispersed due to environmental factors and human activities, rapid detection is of paramount importance. It is imperative to develop field-applicable detection devices that are highly selective, capable of differentiating between biological and non-biological agents, as well as benign and harmful microorganisms. This study examines the potential of near-infrared (NIR) spectroscopy in conjunction with machine learning as a rapid in-situ biological detection method. The objective is to distinguish between biological agents and common white powders that are used as confounding agents in suspect letters. The non-pathogenic surrogates employed are safe and representative of typical biological warfare agents. The near-infrared (NIR) spectra of lyophilized bacterial and fungal surrogates, along with common white powders, were subjected to analysis and processing through the application of principal component analysis (PCA) and hierarchical clustering analysis (HCA). This resulted in the successful classification of the samples into distinct groups. The classification model demonstrated high accuracy in its prediction, thereby emphasizing the potential of the method for field detection of solid biological agents. These promising results suggest that NIR spectroscopy combined with machine learning could be further investigated as a rapid in-situ tool for biological detection in CBRN contexts.
Utilizing protein structure graph embeddings to predict the pathogenicity of missense variants
Authors: Danner Martin , Begemann Matthias , Elbracht Miriam , Kurth Ingo , Krause Jeremias 
Published: November 2024

AbstractBackgroundGenetic variants can impact the structure of the corresponding protein, which can have detrimental effects on protein function. While the effect of protein truncating variants is often easier to evaluate, most genetic variants are missense variants. These variants are mostly single nucleotide variants which result in the exchange of a single amino acid. The effect on protein function of these variants can be challenging to deduce. To aid the interpretation of missense variants a variety of bioinformatic algorithms have been developed, yet current algorithms rarely directly use the protein structure as a feature to consider.ResultsWe developed a machine learning workflow that utilizes the protein-language-model ESMFold to predict the protein structure of missense variants, which is subsequently embedded using graph autoencoders. The generated embeddings are used in a classifier model which predicts pathogenicity. We provide evidence that the generated graph embeddings improve classification accuracy of a XGBoost pathogenicity predictor, which should lead to a wide applicability for human genetic diseases. Additionally, we explored different levels of abstraction of the graph embeddings and their influence on the classifier. Finally, we compare the utility of graph embeddings from different protein-folding models.
Integrated proteome and lipidome analyses place OCIAD1 at mitochondria-peroxisome intersection balancing lipid metabolism
Authors: Linke Vanessa , Chodkowski Mateusz , Kaszuba Kacper , Radkiewicz Mariusz , Rana Vikas , Stadnik Dorota , Dadlez Michał , Chacinska Agnieszka 
Published: November 2024

ABSTRACTOCIAD1 (Ovarian Cancer Immunoreactive Antigen Domain Containing 1) is a membrane protein largely localized to mitochondria, however, its function in health or disease is not well understood. To comprehensively characterize the molecular changes upon lack of OCIAD1, we used mass spectrometry to study the mitochondrial and cellular proteome and lipidome. We find extensive lipidome rearrangement in OCIAD1 KO cells, characterized by two main phenotypes of decreased ether phospholipids and decreased phospholipids with an odd number of carbons. The lipidomic changes suggest alterations in peroxisomal lipid metabolism. At the same time, proteins responsible for mitochondrial fatty acid β oxidation are significantly increased. Together with a global loss in peroxisomal proteins and a meta-analysis of proximity labeling data, this gives a function to the previously observed partial localization of OCIAD1 to peroxisomes. We suggest a role for OCIAD1 in balancing mitochondrial and peroxisomal lipid metabolism, and a direct impact on the key enzymes FAR1 and ACBD3.Summary StatementLipidomics and proteomics of mitochondrial fractions and whole cells lacking the membrane protein OCIAD1 suggest a role as a dually localized protein balancing mitochondrial and peroxisomal lipid metabolism.
Evaluating the Fidelity of Data-Driven Predator-Prey Models: A Dynamical Systems Analysis
Authors: Frank Anna-Simone J. , Zhang Jiawen , Subbey Sam 
Published: November 2024

AbstractIn empirical predator-prey systems, understanding the inherent dynamics typically comes from analyzing a structural model fitted to observation data. However, determining an appropriate model structure and its parameters is often complex and highly uncertain. A promising alternative is to learn the model structure directly from time series data of both predator and prey.This study explores the capability of a data-driven algorithm, Sparse Identification of Nonlinear Dynamics (SINDy), to accurately capture the dynamics of a predator-prey system. We apply SINDy to derive a Learned Model (LM) from data generated by a Reference Model (RM), whose predator-prey dynamics are well understood. The study compares the dynamics of the LM to the RM using criteria such as equilibrium points, stability, sensitivity, and bifurcation analysis.Our results demonstrate general consistency between the RM and LM dynamics, though notable differences remain. We discuss the implications of these differences in the broader context of using learned models to uncover the inherent drivers of predator-prey dynamics and ecological implications.2010 MSC37M05, 37N25, 92B05, 92D25, 92D40, 65L05, 37G15HighlightsEvaluates data-driven model’s ability to replication of predator-prey dynamics using SINDy frameworkLearned Model captures core dynamics but shows parameter sensitivity and bifurcation differencesAnalysis reveals need for extensive data for effective model learningSuggests combining data-driven methods with biological priors to improve model accuracy
Dynamically arrested condensate fusion creates complex structures with varying material properties
Authors: Erkamp Nadia A. , Sanchez-Burgos Ignacio , Zhou Alexandra , Krug Tommy J. , Qamar Seema , Sneideris Tomas , Zhang Ellie , Nakajima Kichitaro , Chen Anqi , Collepardo-Guevara Rosana , van Hest Jan , St George-Hyslop Peter , Weitz David A. , Espinosa Jorge R. , Knowles Tuomas P. J. 
Published: November 2024

AbstractThe cell nucleus and cytosol contain numerous biomolecular condensates which dynamically reshape, fuse and split to accomplish precise compartmentalization of the cell material. While it has been observed that some condensates rapidly coalesce, some others only attach to each other, or do not establish persistent interactions over time. Here, we explain these observations through optical tweezers and Molecular Dynamics simulations focusing on two condensate-forming, RNA-binding proteins—FUS and G3BP1—strongly involved in RNA metabolism and stress responses. We find that the fusion of pure droplets formed by these proteins can give rise to multiphase single-component condensates exhibiting notably different densities, architectures, and material properties. Such behaviour is dictated by the relative timescales of condensate fusion and protein internal mixing. A critical parameter controlling this interplay is the extent of ageing that condensates display; e.g., their progressive hardening driven by the accumulation of inter-proteinβ-sheet assemblies over time. Strikingly, different degrees of ageing in fusing droplets can lead single-component condensates to form diverse architectures including concentric drops or two-sided condensates. Overall, our results highlight a mechanism, based on the temporal coupling between ageing, fusion, and mixing rate, by which biomolecular condensates form multiphasic structures with markedly different material properties, and hence potentially distinct biological roles.
Urban tree diversity fosters bird insectivory despite a loss in bird diversity with urbanization
Authors: Schillé Laura , Paquette Alain , Marcotte Gabriel , Ouellet Hugo , Cobus Swane , Barbaro Luc , Castagneyrol Bastien 
Published: November 2024

AbstractUrbanization is one of the main drivers of biotic homogenization in bird communities worldwide. Yet, only a few studies have addressed its functional consequences on the top-down control birds exert on insect herbivores. We hypothesized that their inconsistent results reflect the overlooked heterogeneity of the urban habitat for birds, and in particular the distribution and diversity of urban trees.We monitored tree diversity, bird diversity, avian predation attempts on artificial prey, and the effect of bird exclusion on insect herbivory in 97 trees distributed among 24 urban experimental plots in the city of Montreal, Canada. We characterized urbanization levels through a combination of variables related to tree density, impervious surfaces, anthropic noise, and human population density.Bird diversity decreased with increasing urbanization, whereas the frequency of generalist synurbic species increased. We found no significant relationship between predation and urbanization or between predation and bird diversity. However, tree diversity was positively correlated with predation attempts on artificial prey, irrespective of bird diversity.We revealed a mismatch between the effects of urbanization on bird diversity and on the regulation service and unraveled the functional importance of tree diversity in shaping the avian predation function in urban ecosystems. Our study advocates for the consideration of intra-urban heterogeneity in the investigation of trophic cascades within cities.
Deletion of epithelial HKDC1 decelerates cellular proliferation and impairs mitochondrial function of tumorous epithelial cells thereby protecting from intestinal carcinogenesis in mice
Authors: Järke Lea , Weber-Stiehl Saskia , Shima Kensuke , Moors Karlis Arturs , Genth Jerome , Schuran Fenja Amrei , Best Lena , Tschurtschenthaler Markus , Flemer Burkhardt , Tholey Andreas , Kaleta Christoph , Rupp Jan , Rosenstiel Philip , Sommer Felix 
Published: November 2024

AbstractBackgroundA metabolic switch favoring glycolysis over aerobic oxidative phosphorylation, namely the “Warburg effect”, represents a hallmark of cancer cells. Hexokinases (HK) catalyze the first step of glycolysis, thereby regulating its rate. Dysregulated HKDC1 (HK domain containing 1) expression has been associated with various cancer types and blocking HKDC1 prevents disease progression for hepatic carcinoma T cell lymphoma and lung adenocarcinoma, but its implication for colorectal cancer (CRC) remained unknown. Here, we functionally investigated the role of HKDC1 for intestinal carcinogenesis.MethodsFirst, we analyzed HKDC1 expression in the intestinal mucosa of healthy controls (HC) and CRC patients and in different tumor tissues using transcriptomic data from publicly available databases. We then generated HKDC1-deficient human and murine colonic epithelial cell lines as well as intestinal organoids and profiled their phenotypic functions. Next, we screened for proteins interacting with HKDC1 by immunoprecipitation. Finally, we generated tumor-bearingApcMin/+mice with a conditional deletion of HKDC1 in intestinal epithelial cells and also performed a xenograft mouse model to test the role of HKDC1 for intestinal carcinogenesisin vivo.ResultsHKDC1 was found to be overexpressed in tumor compared to normal tissue of CRC patients.In vitro,HKDC1-deficient human Caco-2 and murine CMT-93 cells displayed reduced proliferation, altered susceptibility to cell death induction, and disrupted mitochondrial functions, particularly mitochondrial respiration. These altered cancer hallmarks were then corroborated in HKDC1-deficient normal and tumor-derivedApcMin/+intestinal organoids. Immunoprecipitation and mass spectometry proteomic analyses revealed interactions of HKDC1 with several mitochondria-related proteins.In vivo, two distinct mouse models demonstrated that epithelial deletion of HKDC1 protected from carcinogenesis. First,ApcMin/+-Hkdc1ΔIECmice showed mildly improved disease phenotypes in the colon accompanied with reduced numbers of Ki67-positive proliferating epithelial cells. Finally, HKDC1-deficient Caco-2 cells completely failed to form any tumor mass in a xenograft model when implanted into immunodeficient mice.ConclusionsWe demonstrate that HKDC1 influences cancer cell proliferation and susceptibility to cell death, potentially through interactions with mitochondrial proteins that regulate membrane permeability, ultimately impacting intestinal carcinogenesis. Collectively, these findings highlight the significance of HKDC1 for CRC pathobiology, presenting it as a promising target for further investigation and potential therapeutic interventions.
Secreted cytokines from inflammatory macrophages modulate sex differences in valvular interstitial cells on hydrogel biomaterials
Authors: Félix Vélez Nicole E. , Tu Kristi , Guo Peng , Reeves Ryan R. , Aguado Brian A. 
Published: November 2024

AbstractPatients with aortic valve stenosis (AVS) experience fibrosis and/or calcification in valve tissue, which leads to heart failure if left untreated. Inflammation is a hallmark of AVS and secreted cytokines from pro-inflammatory macrophages are thought to contribute to valve fibro-calcification by driving the activation of valvular interstitial cells (VICs) to myofibroblasts. However, the molecular mechanisms by which inflammatory cytokines differentially regulate myofibroblast activation as a function of biological sex are not fully defined. Here, we developed anin vitrohydrogel culture platform to culture male and female valvular interstitial cells (VICs) and characterize the sex-specific effects of inflammatory cytokines on VIC activation to myofibroblasts and osteoblast-like cells. Our data reveal that tumor necrosis factor alpha (TNF-α) modulates female-specific myofibroblast activation via MAPK/ERK signaling, nuclear chromatin availability, and osteoblast-like differentiation via RUNX2 nuclear localization. Collectively, hydrogel biomaterials as cell culture platforms are critical for distinguishing sex differences in cellular phenotypes.
Orthrus: an AI-powered, cloud-ready, and open-source hybrid approach for metaproteomics
Authors: Chiang Yun , Collins Matthew James 
Published: November 2024

AbstractWhile metaproteomics provides invaluable insight into microbial communities and functions, significant bioinformatics challenges persist due to data complexity and the limitations of database searching. We introduceOrthrus, a hybrid approach combining transformer-basedde novosequencing (Casanovo) and database searching with rescoring (Sage+Mokapot). Benchmarking againstPEAKS®11,MaxQuant, andMetaNovo,Orthrusdemonstrates high peptide outputs, taxonomic diversity, and proteome coverage.Orthrusis Python-based and accessible to all via Google Colaboratory.