bluuebunny/crossref_metadata_2025_split huggingface dataset:
SP1 MEDIATES OGD/R-INDUCED CARDIOMYOCYTE INJURY VIA ENHANCING THE TRANSCRIPTION OF USP46
Authors: Ma Xuming , Wang Luzhen , Li Wanpeng , Huang Yan , Zhu Yan , Li Jing 
Published: May 2024

ABSTRACT

Background: One of the mechanisms responsible for the high mortality rate of acute myocardial infarction is myocardial ischemia-reperfusion injury (MI-RI). The present study focused on the role and regulatory mechanisms of specificity protein 1 (SP1) and ubiquitin-specific protease 46 (USP46) in oxygen-glucose deprivation/reperfusion (OGD/R)-induced cardiomyocyte injury. Methods: OGD/R was used to treat cardiomyocytes AC16 to mimic ischemia-reperfusion in vitro. Cell viability, proliferation, and apoptosis were determined by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide, 5-ethynyl-2′-deoxyuridine, and flow cytometry assays. Enzyme-linked immunosorbent assays analyzed the concentrations of TNF-α and IL-1β. Several protein levels were analyzed by western blotting. The levels of iron (Fe2+), reactive oxygen species, malondialdehyde, and the activities of superoxide dismutase were analyzed by commercial kits. Chromatin immunoprecipitation and dual-luciferase report assays assessed the relationship between USP46 and SP1. Results: USP46 and SP1 were upregulated in serum from MI patients and they had a positive correlation. OGD/R stimulation suppressed cardiomyocyte viability and proliferation, as well as induced cardiomyocyte inflammation, oxidative stress (OxS) injury, apoptosis, and ferroptosis, but these effects were impaired by USP46 or SP1 knockdown. SP1 could enhance the transcription of USP46, and USP46 overexpression reversed SP1 silencing-mediated effects on OGD/R-induced cardiomyocytes. SP1 mediated the AMPK signaling via USP46. Conclusion: SP1 mediated OGD/R-induced cardiomyocyte inflammation, OxS injury, apoptosis, and ferroptosis by inactivating the AMPK signaling via enhancing the transcription of USP46.
Mechanistic insights into behavioral clusters associated with cancer-related systemic inflammatory response
Authors: Goto Taichi , Saligan Leorey N. 
Published: May 2024

Purpose of review
This focused, narrative review mostly describes our team’s investigations into the potential inflammatory mechanisms that contribute to the development of cancer-related gastrointestinal (GI) mucositis and its associated symptoms. This review summarizes details of our clinical and preclinical findings to test the role of inflammation in the development and occurrence of these cancer-related conditions.

Recent findings
GI mucositis (GIM) is a common, distressing condition reported by cancer patients. GIM is often clustered with other behaviors including fatigue, pain, anorexia, depression, and diarrhea. It is hypothesized that there is a common biologic mechanism underpinning this symptom cluster. Our multi-platform investigations revealed that GIM and its associated cluster of behaviors may be triggered by local inflammation spreading systemically causing pro-inflammatory-mediated toxicities, leading to alterations in immune, metabolic, and nervous system functions and activities. For example, behavioral toxicities related to local irradiation for non-metastatic cancer may be triggered by mGluR5 activation influencing prolonged T cell as well as NF-κB transcription factor activities. Thus, interventions targeting inflammation and associated pathways may be a reasonable strategy to alleviate GIM and its symptom cluster.

Summary
GIM may be a sign of a broader systemic inflammatory response triggered by cancer or its treatment. Addressing GIM and its associated symptoms primarily involves supportive care strategies focused on relieving symptoms, promoting healing, and preventing complications.
Cosine Similarity Estimation Using FracMinHash: Theoretical Analysis, Safety Conditions, and Implementation
Authors: Hera Mahmudur Rahman , Koslicki David 
Published: May 2024

AbstractMotivationThe increasing number and volume of genomic and metagenomic data necessitates scalable and robust computational models for precise analysis. Sketching techniques utilizingk-mers from a biological sample have proven to be useful for large-scale analyses. In recent years, FracMinHash has emerged as a popular sketching technique and has been used in several useful applications. Recent studies on FracMinHash proved unbiased estimators for the containment and Jaccard indices. However, theoretical investigations for other metrics, such as the cosine similarity, are still lacking.Theoretical contributionsIn this paper, we present a theoretical framework for estimating cosine similarity from FracMinHash sketches. We establish conditions under which this estimation is sound, and recommend a minimum scale factorsfor accurate results. Experimental evidence supports our theoretical findings.Practical contributionsWe also presentfrac-kmc, a fast and efficient FracMinHash sketch generator program.frac-kmcis the fastest known FracMinHash sketch generator, delivering accurate and precise results for cosine similarity estimation on real data. We show that by computing FracMinHash sketches usingfrac-kmc, we can estimate pairwise cosine similarity speedily and accurately on real data.frac-kmcis freely available here:https://github.com/KoslickiLab/frac-kmc/.2012ACM Subject ClassificationApplied computing → Computational biology
Semi-Supervised Learning to Boost Cardiotoxicity Prediction by Mining a Large Unlabeled Small Molecule Dataset
Authors: Arab Issar , Laukens Kris , Bittremieux Wout 
Published: May 2024

AbstractPredicting drug toxicity is a critical aspect of ensuring patient safety during the drug design process. Although conventional machine learning techniques have shown some success in this field, the scarcity of annotated toxicity data poses a significant challenge in enhancing models’ performance. In this study, we explore the potential of leveraging large unlabeled datasets using semi-supervised learning to improve predictive performance for cardiotoxicity across three targets: the voltage-gated potassium channel (hERG), the voltage-gated calcium channel (Cav1.2), and the voltage-gated sodium channel (Nav1.5). We extensively mined the ChEMBL database, comprising approximately 2 million small molecules, then employed semi-supervised learning to construct robust classification models for this purpose. We achieved a performance boost on highly diverse (i.e. structurally dissimilar) test datasets across all three targets. Using our built models, we screened the whole ChEMBL database and a large set of FDA-approved drugs, identifying several compounds with potential cardiac channel activity. To ensure broad accessibility and usability for both technical and non-technical users, we developed a cross-platform graphical user interface that allows users to make predictions and gain insights into the cardiotoxicity of drugs and other small molecules. The software is made available as open source under the permissive MIT license athttps://github.com/issararab/CToxPred2.
Cliffy: robust 16S rRNA classification based on a compressed LCA index
Authors: Ahmed Omar , Boucher Christina , Langmead Ben 
Published: May 2024

AbstractTaxonomic sequence classification is a computational problem central to the study of metagenomics and evolution. Advances in compressed indexing with ther-index enable full-text pattern matching against large sequence collections. But the data structures that link pattern sequences to their clades of origin still do not scale well to large collections. Previous work proposed the document array profiles, which use𝒪(rd) words of space whereris the number of maximal-equal letter runs in the Burrows-Wheeler transform anddis the number of distinct genomes. The linear dependence ondis limiting, since real taxonomies can easily contain 10,000s of leaves or more. We propose a method called cliff compression that reduces this size by a large factor, over 250x when indexing the SILVA 16S rRNA gene database. This method uses Θ(rlogd) words of space in expectation under a random model we propose here. We implemented these ideas in an open source tool called Cliffy that performs efficient taxonomic classification of sequencing reads with respect to a compressed taxonomic index. When applied to simulated 16S rRNA reads, Cliffy’s read-level accuracy is higher than Kraken2’s by 11-18%. Clade abundances are also more accurately predicted by Cliffy compared to Kraken2 and Bracken. Overall, Cliffy is a fast and space-economical extension to compressed full-text indexes, enabling them to perform fast and accurate taxonomic classification queries.2012 ACM Subject ClassificationApplied computing→Computational genomics
Distinct mechanisms of non-autonomous UPRERmediated by GABAergic, glutamatergic, and octopaminergic neurons
Authors: Coakley Aeowynn J. , Hruby Adam J. , Wang Jing , Bong Andrew , Nair Tripti , Ramos Carmen M. , Alcala Athena , Hicks Daniel , Averbukh Maxim , Dutta Naibedya , Moaddeli Darius , Siebrand Cynthia , de los Rios Rogers Mattias , Sahay Arushi , Curran Sean P. , Mullen Peter J. , Benayoun Bérénice A , Garcia Gilberto , Higuchi-Sanabria Ryo 
Published: May 2024

AbstractThe capacity to deal with stress declines during the aging process, and preservation of cellular stress responses is critical to healthy aging. The unfolded protein response of the endoplasmic reticulum (UPRER) is one such conserved mechanism, which is critical for the maintenance of several major functions of the ER during stress, including protein folding and lipid metabolism. Hyperactivation of the UPRERby overexpression of the major transcription factor,xbp-1s, solely in neurons drives lifespan extension as neurons send a neurotransmitter-based signal to other tissue to activate UPRERin a non-autonomous fashion. Previous work identified serotonergic, dopaminergic, and tyraminergic neurons in this signaling paradigm. To further expand our understanding of the neural circuitry that underlies the non-autonomous signaling of ER stress, we activated UPRERsolely in glutamatergic, octopaminergic, and GABAergic neurons inC. elegansand paired whole-body transcriptomic analysis with functional assays. We found that UPRER-induced signals from glutamatergic neurons increased expression of canonical protein homeostasis pathways and octopaminergic neurons promoted pathogen response pathways; while minor, statistically significant changes were observed in lipid metabolism-related genes with GABAergic UPRERactivation. These findings provide further evidence for the distinct role neuronal subtypes play in driving the diverse response to ER stress.
Chromatin profiling identifies putative dual roles for H3K27me3 in regulating transposons and cell type-specific genes in choanoflagellates
Authors: Gahan James M. , Helfrich Lily W. , Wetzel Laura A. , Bhanu Natarajan V. , Yuan Zuo-Fei , Garcia Benjamin A. , Klose Rob , Booth David S. 
Published: May 2024

AbstractGene expression is tightly controlled during animal development to allow the formation of specialized cell types. Our understanding of how animals evolved this exquisite regulatory control remains elusive, but evidence suggests that changes in chromatin-based mechanisms may have contributed. To investigate this possibility, here we examine chromatin-based gene regulatory features in the closest relatives of animals, choanoflagellates. UsingSalpingoeca rosettaas a model system, we examined chromatin accessibility and histone modifications at the genome scale and compared these features to gene expression. We first observed that accessible regions of chromatin are primarily associated with gene promoters and found no evidence of distal gene regulatory elements resembling the enhancers that animals deploy to regulate developmental gene expression. Remarkably, a histone modification deposited by polycomb repressive complex 2, histone H3 lysine 27 trimethylation (H3K27me3), appeared to function similarly inS. rosettato its role in animals, because this modification decorated genes with cell type-specific expression. Additionally, H3K27me3 marked transposons, retaining what appears to be an ancestral role in regulating these elements. We further uncovered a putative new bivalent chromatin state at cell type-specific genes that consists of H3K27me3 and histone H3 lysine 4 mono-methylation (H3K4me1). Together, our discoveries support the scenario that gene-associated histone modification states that underpin development emerged before the evolution of animal multicellularity.
Photoactivatable Plasma Membrane Probe Through Self-Triggered Photooxidation Cascade for Live Super-Resolution Microscopy
Authors: Pfister Sonia , Le Berruyer Valentine , Fam Kyong , Collot Mayeul 
Published: May 2024

AbstractSuper-resolution imaging based on the localization of single emitters requires a spatio-temporal control of the ON and OFF state. To this end, photoactivatable fluorophores are adapted as they can be turned on upon light irradiation. Here we present a concept called Self-Triggered Photooxidation Cascade (STPC) based on the photooxidation of a plasma membrane targeted leuco-rhodamine (LRhod-PM), a non-fluorescent reduced form of a rhodamine probe. Upon visible light irradiation the small number of oxidized rhodamines, Rhod-PM, acts as a photosensitizer to generate singlet oxygen capable to oxidize the OFF state LRhod-PM. We showed that this phenomenon is kinetically favored by a high local concentration and propagates quickly when the probe is embedded in membrane bilayers. In addition, we showed that the close proximity of the dyes favors the photobleaching. At the single-molecule level, the concomitant activation/bleaching phenomena allow reaching a single-molecule blinking regime enabling single-molecule localization microscopy for super-resolution of live cellular membranes.
LiF-MS+, a revised technique for mapping peptide-protein interactions
Authors: Parker Benjamin , Weiss Eric 
Published: May 2024

ABSTRACTShort linear motifs are sequences of amino acids present in unstructured polypeptide regions that function as ligands for specific sites on folded protein domains. These interactions, which often occur with low to modest affinity, modulate dynamic biological processes such as signal transduction and membrane trafficking. We recently described Ligand Footprinting-Mass Spectrometry (LiF-MS), a technique that rapidly and precisely maps sites at which short peptide ligands bind their biologically relevant recognition sites on folded protein domains. This approach marks the binding location of a peptide ligand on a structured protein using a cleavable crosslinker appended to the ligand that leaves behind a stable chemical modification following cleavage. This modification serves as a mass tag detectable by mass spectrometry, pinpointing sites of peptide ligand binding. Here we present LiF-MS+, an improved version of the footprinting technique that replaces the butanol mass tag with 1-butylpyrrolidine, which is positively charged at neutral pH and thus aids in ionization of the crosslinked peptide for analysis by mass spectrometry. We show ligand-mediated butylpyrrolidine footprinting effectively maps the well characterized binding interaction of the p38α mitogen-activated protein kinase (MAPK) with a MKK6 D-motif short linear motif peptide ligand, uncovering additional binding site information not observed in our original experiment. LiF-MS+ is thus a straightforward improvement of our previously published methodology for mapping the binding of short linear motifs to folded protein domains.
LiveLattice: Real-time visualization of tilted light-sheet microscopy data using a memory-efficient transformation algorithm
Authors: Wang Zichen , Hakozaki Hiroyuki , McMahon Gillian , Medina-Carbonero Marta , Schöneberg Johannes 
Published: May 2024

ABSTRACTLight-sheet fluorescence microscopy (LSFM), a prominent fluorescence microscopy technique, offers enhanced temporal resolution for imaging biological samples in four dimensions (4D; x, y, z, time). Some of the most recent implementations, including inverted selective plane illumination microscopy (iSPIM) and lattice light-sheet microscopy (LLSM), rely on a tilting of the sample plane with respect to the light sheet of 30-45 degrees to ease sample preparation. Data from such tilted-sample-plane LSFMs require subsequent deskewing and rotation for proper visualization and analysis. Such transformations currently demand substantial memory allocation. This poses computational challenges, especially with large datasets. The consequence is long processing times compared to data acquisition times, which currently limits the ability for live-viewing the data as it is being captured by the microscope. To enable the fast preprocessing of large light-sheet microscopy datasets without significant hardware demand, we have developed WH-Transform, a novel GPU-accelerated memory-efficient algorithm that integrates deskewing and rotation into a single transformation, significantly reducing memory requirements and reducing the preprocessing run time by at least 10-fold for large image stacks. Benchmarked against conventional methods and existing software, our approach demonstrates linear scalability. Processing large 3D stacks of up to 15 GB is now possible within one minute using a single GPU with 24 GB of memory. Applied to 4D LLSM datasets of human hepatocytes, human lung organoid tissue, and human brain organoid tissue, our method outperforms alternatives, providing rapid, accurate preprocessing within seconds. Importantly, such processing speeds now allow visualization of the raw microscope data stream in real time, significantly improving the usability of LLSM in biology. In summary, this advancement holds transformative potential for light-sheet microscopy, enabling real-time, on-the-fly data processing, visualization, and analysis on standard workstations, thereby revolutionizing biological imaging applications for LLSM, SPIM and similar light microscopes.
GWAS reveals Genetic Susceptibility to Air Pollution-Related Asthma Exacerbations in Children of African Ancestry
Authors: Kelchtermans Jelte , March Michael E. , Mentch Frank , Liu Yichuan , Nguyen Kenny , Hakonarson Hakon 
Published: May 2024

AbstractBackgroundThe relationship between ambient air pollution (AAP) exposure and asthma exacerbations is well-established. However, mitigation efforts have yielded mixed results, potentially due to genetic variability in the response to AAP. We hypothesize that common single nucleotide polymorphisms (SNPs) are linked to AAP sensitivity and test this through a Genome Wide Association Study (GWAS).MethodsWe selected a cohort of pediatric asthma patients frequently exposed to AAP. Patients experiencing exacerbations immediately following AAP spikes were deemed sensitive. A GWAS compared sensitive versus non-sensitive patients. Findings were validated using data from the All of Us program.ResultsOur study included 6,023 pediatric asthma patients. Due to the association between AAP exposure and race, GWAS analysis was feasible only in the African ancestry cohort. Seven risk loci reached genome-wide significance, including four non-intergenic variants. Two variants were validated: rs111970601 associated with sensitivity to CO (odds ratio [OR], 6.58; PL=L1.63L×L10−8; 95% CI, 3.42-12.66) and rs9836522 to PM2.5 sensitivity (OR 0.75; PL=L3,87 ×L10−9; 95% CI, 0.62-0.91).InterpretationWhile genetic variants have been previously linked to asthma incidence and AAP exposure, this study is the first to link specific SNPs with AAP-related asthma exacerbations. The identified variants implicate genes with a known role in asthma and established links to AAP. Future research should explore how clinical interventions interact with genetic risk to mitigate the effects of AAP, particularly to enhance health equity for vulnerable populations.What is already known on this topicThe relationship between ambient air pollution (AAP) exposure and asthma exacerbations is well-established. However, efforts to mitigate the impact of AAP on children with asthma have yielded mixed results, potentially due to genetic variability in response to AAP.What this study addsUsing publicly available AAP data, we identify which children with asthma experience exacerbations immediately following spikes in AAP. We then conduct a Genome Wide Association Study (GWAS) comparing these patients with those who have no temporal association between AAP spikes and asthma exacerbations, identifying several Single Nucleotide Polymorphisms (SNPs) significantly associated with AAP sensitivity.How this study might affect research, practice, or policyWhile genetic variants have previously been linked to asthma incidence and AAP exposure, this study is the first to link specific SNPs with AAP-related asthma exacerbations. This creates a framework for identifying children especially at risk when exposed to AAP. These children should be targeted with policy interventions to reduce exposure and may require specific treatments to mitigate the effects of ongoing AAP exposure in the interim.
More Than Words: An Integrative Review of Innovative Elicitation Techniques for Qualitative Interviews
Authors: Kahlke Renate , Maggio Lauren A. , Lee Mark , Cristancho Sayra , LaDonna Kori , Abdallah Zahra , Khehra Aakashdeep , Kshatri Kushal , Horsley Tanya , Varpio Lara 
Published: May 2024

AbstractIntroductionInterviews are central to many qualitative studies in health professions education (HPE). However, researchers often rely only on oral questioning despite the existence of techniques tailored to elicit the rich data needed to address complex problems and meaningfully engage participants. Elicitation techniques are strategies – e.g. participant photography, neighbourhood walks – used to generate rich conversations, but guidance on these techniques is scattered across literatures from diverse fields. In this synthesis, we offer an overview of the elicitation techniques available and advice about how to choose between them.MethodsWe conducted an integrative review, drawing on methodological literature from across the health and social sciences. Our interdisciplinary searches yielded 3056 citations. We included 293 citations that were methodologically focused and discussed elicitation techniques used in interviews with adults. We then extracted specific elicitation techniques, summarizing each technique to capture key features, as well as strengths and weaknesses. From this, we developed a framework to help researchers identify challenges in their interview-based research, and to select elicitation techniques that address their challenges.ResultsElicitation techniques serve two main purposes: they can enrich data and engage participants in new ways. To enrich data, researchers might seek to shift conversations away from participants’ entrenched narratives, to externalize conversations on sensitive topics, or to elicit affect, tacit knowledge, or contextual details. When engaging participants in new ways, researchers might seek to increase equity between the researcher and participant or interview accessibility across diverse participant populations.DiscussionWhen chosen with study goals in mind, elicitation techniques can enrich interview data. To harness this potential, we need to re-conceptualize interviews as co-production of knowledge by researcher(s) and participant(s). To make interviews more accessible, we need to consider flexibility so that each participant can engage in ways that best suit their needs and preferences.