bluuebunny/crossref_metadata_2025_split huggingface dataset:
Enhancing SARS-CoV-2 Lineage surveillance through the integration of a simple and direct qPCR-based protocol adaptation with established machine learning algorithms
Authors: Aksenen Cleber Furtado , Ferreira Débora Maria Almeida , Jeronimo Pedro Miguel Carneiro , Costa Thais de Oliveira , de Souza Ticiane Cavalcante , Lino Bruna Maria Nepomuceno Sousa , de Farias Allysson Allan , Miyajima Fabio 
Published: August 2024

ABSTRACTThe emergence of the SARS-CoV-2 and continuous spread of its descendent lineages have posed unprecedented challenges to the global public healthcare system. Here we present an inclusive approach integrating genomic sequencing and qPCR-based protocols to increment monitoring of variant Omicron sublineages. Viral RNA samples were fast tracked for genomic surveillance following the detection of SARS-CoV-2 by diagnostic laboratories or public health network units in Ceara (Brazil) and analyzed using paired-end sequencing and integrative genomic analysis. Validation of a key structural variation was conducted with gel electrophoresis for the presence of a specific ORF7a deletion within the “BE.9” lineages. A simple intercalating dye-based qPCR assay protocol was tested and optimized through the repositioning primers from the ARTIC v.4.1 amplicon panel, which was able to distinguish between “BE.9” and “non-BE.9” lineages, particularly BQ.1. Three ML models were trained with the melting curve of the intercalating dye-based qPCR that enabled lineage assignment with elevated accuracy. Amongst them, the Support Vector Machine (SVM) model had the best performance and after fine-tuning showed ∼96.52% (333/345) accuracy in comparison to the test dataset. The integration of these methods may allow rapid assessment of emerging variants and increment molecular surveillance strategies, especially in resource-limited settings. Our approach not only provides a cost-effective alternative to complement traditional sequencing methods but also offers a scalable analytical solution for enhanced monitoring of SARS-CoV-2 variants for other laboratories through easy-to-train ML algorithms, thus contributing to global efforts in pandemic control.
Digital technology as a tool to provide social support to individuals with cancer in low- and middle-income countries: a scoping review
Authors: Dau Hallie , Kassam Fazila , Payne Beth A. , Miller Hana , Ogilvie Gina 
Published: August 2024

AbstractBACKGROUNDCancer is a rising cause of morbidity and mortality in low- and middle-income countries (LMICs). Individuals diagnosed with cancer in LMICs often have limited access to cancer prevention, diagnosis, and treatment services. Social support after a cancer diagnosis is associated with positive health outcomes in the long term. Digital technologies, such as the Internet and mobile phones, could be used to provide support to individuals with cancer in a more accessible way. This scoping review aims to understand how digital technology is currently being utilized by individuals with cancer for social support in LMICs.METHODSFour electronic databases were searched up to June 2024 to identify studies that reported on the use of digital technology for cancer social support in LMICs. Articles were included if they were published in English, included adults diagnosed with any type of cancer, and reported the use of digital technology for social support. Study characteristics, population demographics, and technological interventions reported were extracted.RESULTSIn all, 15 articles from 12 studies were included in the scoping review. The results were centralized in four countries, and the most common cancer type reported was breast. Online health communities, Internet-based resources, mobile applications, and telecommunication were the four digital technologies reported. Overall, the articles demonstrated that the use of digital technology for social support can be beneficial for individuals diagnosed with cancer in LMICs.CONCLUSIONThere is a limited understanding of how digital technology can be used to support individuals with cancer in LMICs. Future research is needed to explore how digital technology can be utilized by underrepresented regions to offer avenues of support for regionally common cancer types such as cervical. Fundamentally, this scoping review highlights the need for additional research on the use of digital technology to support individuals with a cancer diagnosis in LMICs.
Efficacy, Safety and Cost-effectiveness of Atorvastatin 40mg versus 80 mg in South Asian Patients with acute coronary syndrome: A protocol for randomised clinical trial
Authors: Fernando Kavindya , Fernando Nilshan , Welhenge Chiranthi , Liyanage Shashima , Dayanath B.K.T.P. , De Silva Shamila , Mettananda Chamila 
Published: August 2024

AbstractIntroductionMost guidelines recommend high-intensity statins for the secondary prevention of Acute Coronary Syndrome (ACS). However, it has been observed that South Asians are responsive to lower doses of statins to achieve the recommended target levels of low-density lipoprotein cholesterol (LDL-C). However, published data on this subject is limited. Therefore, we aim to compare the efficacy, safety and cost effectiveness of atorvastatin doses (80mg vs 40mg) in lowering the LDL-c levels to the less than 70 mg/dL within 12 weeks, among patients with incident ACS.Methods and analysisThis single-centre, prospective, randomised, controlled, open-labelled clinical trial is being conducted among patients naïve for statins presenting with incident ACS to the Colombo North Teaching Hospital, Ragama, Sri Lanka. All participants are randomised to two groups, to receive oral atorvastatin 40 mg nocte, or 80 mg nocte. The percentage of patients achieving treatment goals, the percentage with statin induced adverse drug reactions and the mean cost to achieve treatment goals will be compared between the two groups in 6,12 and 24 weeks. Outcome will be analysed for the intention-to-treat population.Ethics and disseminationEthical approval for this study has been obtained from the Ethics Review Committee of the Faculty of Medicine, University of Kelaniya (P/28/05/2022). This trial is registered in the Sri Lanka Clinical Trial Registry (SLCTR/2023/003). The results from this study will be disseminated as scientific publications in reputed journals.Key points of this studyWhat is already known on this topic?While the European guideline recommendation is to initiate atorvastatin at 80 mg dose for ACS, it has been observed that South Asians respond well to lower dose. Additionally, South Asians tend to experience more adverse effects with higher doses of statins. However, reports on differential action of atorvastatin in South Asians is limited.What this study adds?This study explores the efficacy, safety, and cost-effectiveness of a lower dose of atorvastatin (40 mg daily) compared to guideline recommended dose of 80mg in a South Asian cohort.How might this study affect research, practice or policy?The findings may influence statin dose recommendation for South Asians/Sri Lankans which will help to reduce unnecessary side effects and be cost saving as well in secondary prevention of ACS.
Using pet insurance claims to predict occurrence of vector-borne and zoonotic disease in humans
Authors: O’Brien Janice , McCullough Aliya , Debes Christian , Ruple Audrey 
Published: August 2024

AbstractTaking a One Health approach to infectious diseases common to both dogs and people, pet insurance claims from 2008-2022 in the United States were compared to publicly available CDC-based data on human cases for Lyme disease, giardia, and Valley Fever (coccidioidomycosis). Despite having very different causative agents and etiologies, the disease trends for these three diseases were very similar between people and dogs both geographically and temporally. We furthermore demonstrated that adding dog data to the human data improves prediction models for those same diseases. With machine learning prediction tools for the pet insurance to increase prediction times and alert public health officials, pet insurance data could be a helpful tool to predict and detect diseases by estimating even earlier the effects of these common exposure diseases on human health. We also show the spatiotemporal distribution of intestinal worm diagnoses in dogs, and while it could not be directly compared to human data because the corresponding disease in humans (soil-transmitted helminths) has not been well monitored recently. However, these data can help inform researchers and public health workers.
Preliminary Development of a Multidomain Behavioral Intervention for Primary Prevention of Dementia in Midlife
Authors: Korthauer L.E. , Rosen R.K. , Arias I. , Tremont G. , Davis J.D. 
Published: August 2024

AbstractBackgroundAn estimated 40% of global cases of Alzheimer’s disease and related dementias (ADRD) may be prevented through modification of 12 risk factors. Midlife risk reduction is particularly important given the long prodromal period for ADRD. However, population adherence to these health behaviors is low, and large, multidomain behavioral interventions have suffered from poor adherence. The goal of this study was to use qualitative methods to develop a personalized health education intervention (TEACH: Tailored Education for Aging and Cognitive Health), which is grounded in the Health Belief Model.MethodWe conducted six focus groups in which we presented health information about a fictitious person, including images conveying ADRD risk and descriptions of personal health belief factors. Participants provided feedback about the images, their understanding of ADRD risk, and interpretation of the health belief concepts. Results were summarized using a framework matrix.ResultsGroups found the presented risk information to be understandable and relevant to health behaviors. They had strong reactions to presented images and descriptions, and they provided alternative language and suggestions to improve clarity. Participants noted some overlap between health belief constructs but were able to identify connections between health beliefs and personal behaviors.ConclusionsResults guided the TEACH intervention development project, which includes creating an explanatory framework for disclosing individuals’ ADRD risk factors and health belief profile. The long-term goal is to develop a multi-domain intervention to promote sustained health behavior change for primary prevention of ADRD.
Spatial assessment of stromal B cell aggregates predicts response to checkpoint inhibitors in unresectable melanoma
Authors: Smithy James W. , Peng Xiyu , Ehrich Fiona D. , Moy Andrea P. , Yosofvand Mohammad , Maher Colleen , Aleynick Nathaniel , Vanguri Rami , Zhuang Mingqiang , Lee Jasme , Bleile MaryLena , Li Yanyun , Postow Michael A. , Panageas Katherine S. , Hollmann Travis J. , Callahan Margaret K. , Shen Ronglai 
Published: August 2024

SUMMARYQuantitative assessment of multiplex immunofluorescence (mIF) data represents a powerful tool for immunotherapy biomarker discovery in melanoma and other solid tumors. In addition to providing detailed phenotypic information of immune cells of the tumor microenvironment, these datasets contain spatial information that can reveal biologically relevant interactions among cell types.To assess quantitative mIF analysis as a platform for biomarker discovery, we used a 12-plex mIF panel to characterize tumor samples collected from 50 patients with melanoma prior to treatment with immune checkpoint inhibitors (ICI). Consistent with prior studies, we identified a strong association between stromal B cell percentage and response to ICI therapy. We then compared pathologist assessment of lymphoid aggregates with a density based clustering algorithm, DBSCAN, to both automatically detect B cell aggregates and quantify their size, morphology, and distance to tumor. Spatial neighborhood analysis identified TCF1+ and LAG3-T cell subpopulations enriched near stromal B cells. These analyses provide a roadmap for the further development and validation of spatial immunotherapy biomarkers in melanoma and other diseases.
Enhancing Stroke Awareness and Activation among High-Risk Populations: A Randomized Direct Mail Intervention in Diverse Healthcare Settings
Authors: Groves Christine C. , Damush Teresa M. , Myers Laura J. , Baye Fitsum , Daggy Joanne K. , Martin Holly , Mounsey Layne , Clark Daniel O. , Williams Linda S. 
Published: August 2024

AbstractBackgroundMany patients are unaware of their stroke risk. The purpose of this research was to compare the effect of behaviorally tailored mailed messages on patient activation to reduce stroke risk.MethodsWe used electronic health records to construct Framingham Stroke Risk Scores (FSRS) in primary care patients from one Veterans Health Administration (VA) and one non-VA healthcare system, Eskenazi Health System (EHS). Four stroke risk messages were developed through patient interviews: standard, incentive ($5 gift card), salience, and incentive plus salience. Patients in the highest FSRS quintile were randomly assigned to receive one of the messages. All letters asked the patient to call a stroke prevention coordinator. Response to the messages was modeled separately in the two cohorts using logistic regression.ResultsFrom 6,695 eligible patients, 2,084 EHS patients (mean age 65.6, 36% male, 68% Black, mean FSRS 13.1) and 1,759 VA patients (mean age 75.6, 99% male, 86% White, mean FSRS 18.6) received a letter. Rates of calls to the coordinator were 13% among the EHS and 23% among the VA cohort. The EHS cohort was significantly more likely to respond to the incentive message compared to the standard message (OR = 1.97 [1.17, 3.09]), and the VA cohort was more likely to respond to the incentive plus salience message (OR = 1.50 [1.02, 2.22]). Older age (for VA) and Black race (for EHS) were also significantly associated with response. Among individuals calling the coordinator, 30% of the EHS cohort and 26% of the VA cohort were unaware they had stroke risk factors.ConclusionsA mailed message including a $5 incentive was more effective than a standard message in engaging high-risk patients with their healthcare system; including a salience message may also be important in some patient populations. Many primary care patients are unaware of their stroke risk.
Evaluating the accuracy and reliability of large language models in assisting with pediatric differential diagnoses: A multicenter diagnostic study
Authors: Mansoor Masab A. , Ibrahim Andrew F. , Grindem David J. , Baig Asad 
Published: August 2024

AbstractImportanceLarge language models, such as GPT-3, have shown potential in assisting with clinical decision-making, but their accuracy and reliability in pediatric differential diagnosis in rural healthcare settings remain underexplored.ObjectiveEvaluate the performance of a fine-tuned GPT-3 model in assisting with pediatric differential diagnosis in rural healthcare settings and compare its accuracy to human physicians.MethodsRetrospective cohort study using data from a multicenter rural pediatric healthcare organization in Central Louisiana serving approximately 15,000 patients. Data from 500 pediatric patient encounters (age range: 0-18 years) between March 2023 and January 2024 were collected and split into training (70%, n=350) and testing (30%, n=150) sets.InterventionsGPT-3 model (DaVinci version) fine-tuned using OpenAI API on training data for ten epochs.Main Outcomes and MeasuresAccuracy of fine-tuned GPT-3 model in generating differential diagnoses, evaluated using sensitivity, specificity, precision, F1 score, and overall accuracy. The model’s performance was compared to human physicians on the testing set.ResultsThe fine-tuned GPT-3 model achieved an accuracy of 87% (131/150) on the testing set, with a sensitivity of 85%, specificity of 90%, precision of 88%, and F1 score of 0.87. The model’s performance was comparable to human physicians (accuracy 91%; P = .47).Conclusions and RelevanceThe fine-tuned GPT-3 model demonstrated high accuracy and reliability in assisting with pediatric differential diagnosis, with performance comparable to human physicians. Large language models could be valuable tools for supporting clinical decision-making in resource-constrained environments. Further research should explore implementation in various clinical workflows.
Universal dynamics of cohesin-mediated loop extrusion
Authors: Sabaté Thomas , Lelandais Benoît , Robert Marie-Cécile , Szalay Michael , Tinevez Jean-Yves , Bertrand Edouard , Zimmer Christophe 
Published: August 2024

AbstractMost animal genomes are partitioned into Topologically Associating Domains (TADs), created by cohesin-mediated loop extrusion and defined by convergently oriented CTCF sites. The dynamics of loop extrusion and its regulation remains poorly characterizedin vivo. Here, we tracked TAD anchors in living human cells to visualize and quantify cohesin-dependent loop extrusion across multiple endogenous genomic regions. We show that TADs are dynamic structures whose anchors are brought in proximity about once per hour and for 6-19 min (∼16% of the time). TADs are continuously subjected to extrusion by multiple cohesin complexes, extruding loops at ∼0.1 kb/s. Remarkably, despite strong differences of Hi-C patterns between the chromatin regions, their dynamics is consistent with the same density, residence time and speed of cohesin. Our results suggest that TAD dynamics is governed primarily by CTCF site location and affinity, which allows genome-wide predictive models of cohesin-dependent interactions.
taxmyPHAGE: Automated taxonomy of dsDNA phage genomes at the genus and species level
Authors: Millard Andrew , Denise Remi , Lestido Maria , Thomas Moi , Turner Deven , Turner Dann , Sicheritz-Pontén Thomas 
Published: August 2024

AbstractBackgroundBacteriophages are now classified into genera and species based on genomic similarity. To identify new species and genera requires comparison against all phage genomes currently defined by the International Committee on the Taxonomy of Viruses. With increasing amounts of phage genomic data there is a clear need to fully automate the classification of phages into existing and new genera and species.Materials and MethodsWe created a MASH database for rapid searching of closely related phages, to then be compared with BLASTn to compute intergenomic similarity between bacteriophages (https://github.com/amillard/tax_myPHAGE/tree/main).ResultsTaxmyphage is provided as a conda repository and via a user-friendly website, that allows rapid classification of phages into existing taxa at the genus and species level.ConclusionsTaxmyphage allows the rapid and accurate classification of phage genomes into existing genera and species, at a scale that is compatible with existing sequencing output.
4D bioprinting shape-morphing tissues in granular support hydrogels: Sculpting structure and guiding maturation
Authors: Pramanick Ankita , Hayes Thomas , McEvoy Eoin , Pandit Abhay , Daly Andrew C. 
Published: August 2024

AbstractDuring embryogenesis, organs undergo dynamic shape transformations that sculpt their final shape, composition, and function. Despite this, current organ bioprinting approaches typically employ bioinks that restrict cell-generated morphogenetic behaviours resulting in structurally static tissues. Here, we introduce a novel platform that enables the bioprinting of tissues that undergo programmable and predictable 4D shape-morphing driven by cell-generated forces. Our method utilises embedded bioprinting to deposit collagen-hyaluronic acid bioinks within yield-stress granular support hydrogels that can accommodate and regulate 4D shape-morphing through their viscoelastic properties. Importantly, we demonstrate precise control over 4D shape-morphing by modulating factors such as the initial print geometry, cell phenotype, bioink composition, and support hydrogel viscoelasticity. Further, we observed that shape-morphing actively sculpts cell and extracellular matrix alignment along the principal tissue axis through a stress-avoidance mechanism. To enable predictive design of 4D shape-morphing patterns, we developed a finite element model that accurately captures shape evolution at both the cellular and tissue levels. Finally, we show that programmed 4D shape-morphing enhances the structural and functional properties of iPSC-derived heart tissues. This ability to design, predict, and program 4D shape-morphing holds great potential for engineering organ rudiments that recapitulate morphogenetic processes to sculpt their final shape, composition, and function.
Tracing Endometriosis: Coupling deeply phenotyped, single-cell based Endometrial Differences and AI for disease pathology and prediction
Authors: Duempelmann Lea , Sheppard Shaoline , Duo Angelo , Skrabalova Jitka , McKinnon Brett , Andrieu Thomas , Goehlsdorf Dennis , Muzumdar Sukalp , Donato Cinzia , Lusby Ryan , Solass Wiebke , Bösmüller Hans , Nestorov Peter , Mueller Michael D. 
Published: August 2024

AbstractEndometriosis, affecting 1 in 9 women, presents treatment and diagnostic challenges. To address these issues, we generated the biggest single-cell atlas of endometrial tissue to date, comprising 466,371 cells from 35 endometriosis and 25 non-endometriosis patients without exogenous hormonal treatment. Detailed analysis reveals significant gene expression changes and altered receptor-ligand interactions present in the endometrium of endometriosis patients, including increased inflammation, adhesion, proliferation, cell survival, and angiogenesis in various cell types. These alterations may enhance endometriosis lesion formation and offer novel therapeutic targets. Using ScaiVision, we developed neural network models predicting endometriosis of varying disease severity (median AUC = 0.83), including an 11-gene signature-based model (median AUC = 0.83) for hypothesis-generation without external validation. In conclusion, our findings illuminate numerous pathway and ligand-receptor changes in the endometrium of endometriosis patients, offering insights into pathophysiology, targets for novel treatments, and diagnostic models for enhanced outcomes in endometriosis management.
Reverse development in the ctenophoreMnemiopsis leidyi
Authors: Soto-Angel Joan J. , Burkhardt Pawel 
Published: August 2024

AbstractReverse development, or the ability to rejuvenate by morphological reorganization into the preceding life cycle stage is thought to be restricted to a few species within Cnidaria. To date, the cnidarianTurritopsis dohrniiis the only known species capable of undergoing reverse development after the onset of sexual reproduction. Here, we demonstrate that the ctenophoreMnemiopsis leidyiis capable of reversal from mature lobate to early cydippid when fed following a period of stress. Our findings illuminate central aspects of ctenophore development, ecology, and evolution, and show the high potential ofM. leidyias a new model system to study reverse development and rejuvenation. Besides shedding light on the plasticity of developmental programs, our results raise fundamental questions about early animal development, body plans and life cycles.