bluuebunny/crossref_metadata_2025_split huggingface dataset:
Optimisation of explant-specific isolation, culture, and micro-callus induction of sesame (Sesamum indicumL.) protoplasts
Authors: Debnath Anirban Jyoti , Basu Debabrata , Sikdar Samir Ranjan 
Published: October 2024

AbstractThe low yield of sesame (Sesamum indicumL.) compared to other oilseed crops hinders its successful commercialisation process. Sesame yield improvement using molecular-biotechnological tools involving gene manipulation is a better alternative than traditional breeding because it requires less time, effort, and labour. Protoplasts are plant cells devoid of the cell wall. Protoplast systems are deployed as versatile cell-based tools for tissue culture, genomics, transcriptomics, proteomics, metabolomics, and epigenetics studies leading to crop improvement. Inadequate reports of sesame protoplasts restrict its potential use in this crop. In the present study, we are reporting the successful isolation and purification of sesame protoplasts from four different sesame explants: hypocotyl, internode, leaf, and hypocotyl-derived callus using the one-step enzymatic digestion method. We have carefully optimised enzyme combinations, digestion durations, temperatures, and shaking speeds for every tested explant to obtain the highest protoplast yield and viability. Maximum yield (9.9 x 106protoplasts/gm fresh weight) and viability (92.1%) were achieved from callus explants. We purified isolated protoplasts by floating them over a 20% (w/v) sucrose solution. Among tested media, callus-derived protoplasts divided rapidly in Murashige and Skoog broth medium supplemented with 17.77 μM 6-benzylaminopurine (BAP) and 0.54 μM α-naphthalene acetic acid (NAA). In the same medium, protoplasts divided into the 2-cell stage after 2-3 days of culture and progressed to the micro-callus stage at 0.24 ± 0.05% frequency within 16-20 days of culture. Sesame protoplasts could be an excellent system for investigating potential avenues for biotechnological improvements of sesame including transient gene expression and CRISPR-based studies.
Visualizing nucleation, condensation and propagation of β-tubulin folding in chaperonin TRiC
Authors: Zhao Yanyan , Schmid Michael F. , Chiu Wah 
Published: October 2024

AbstractThe folding nucleus (FN) initiates protein folding and enables an efficient folding pathway. Here we directly visualize the tubulin FN consisting of a nonnative, partially assembled Rossmann fold, in the closed chamber of human chaperonin TRiC. Chaperonin TRiC interacts with non-natively folded secondary structural elements, stabilizing the nucleus for transition into its first native domain. Through progressive folding, the unfolded sequence goes through drastic spatial arrangement in the TRiC chamber to sample the conformational space, mediated by the highly dynamic CCT tails. The observed presence of individual nonnative secondary structures first in the nonnative FN and then around the incrementally folded native domains supports the hypothesis that tubulin folding in TRiC is a hierarchical process of nucleation, condensation and propagation in cooperation with TRiC subunits.
Retinoid X Receptor Signaling Mediates Cancer Cell Lipid Metabolism in the Leptomeninges
Authors: Tong Xinran , Remsik Jan , Brook Jeanette , Petrova Boryana , Xu Lele , Li Min Jun , Snyder Jenna , Chabot Kiana , Estrera Rachel , Osei-Gyening Isaiah , Nobre Ana Rita , Wang Helen , Osman Ahmed M , Wong Alan Y.L. , Sidharta Mega , Piedrafita-Ortiz Sofia , Manoranjan Branavan , Zhou Ting , Murali Rajmohan , Hamard Pierre-Jacques , Koche Richard , He Ye , Kanarek Naama , Boire Adrienne 
Published: October 2024

SummaryCancer cells metastatic to the leptomeninges encounter a metabolically-challenging extreme microenvironment. To understand adaptations to this space, we subjected leptomeningeal-metastatic (LeptoM) mouse breast and lung cancers isolated from either the leptomeninges or orthotopic primary sites to ATAC-and RNA-sequencing. When inhabiting the leptomeninges, the LeptoM cells demonstrated transcription downstream of retinoid-X-receptors (RXRs). We found evidence of local retinoic acid (RA) generation in both human leptomeningeal metastasis and mouse models in the form of elevated spinal fluid retinol and expression of RA-generating dehydrogenases within the leptomeningeal microenvironment. Stimulating LeptoM cells with RA induced expression of transcripts encodingde novofatty acid synthesis pathway enzymesin vitro.In vivo, while deletion ofStra6did not alter cancer cell leptomeningeal growth, knockout ofRxra/b/ginterrupted cancer cell lipid biosynthesis and arrested cancer growth. These observations illustrate a mechanism whereby metastatic cancer cells awake locally-generated developmental cues for metabolically reprograming, suggesting novel therapeutic approaches.
The role of theADRB2Thr164Ile variant in lung function determination, plasma proteome variability and other phenotypes in UK Biobank
Authors: Fawcett Katherine A , Hall Robert J , Packer Richard , Coley Kayesha , Shrine Nick , Wain Louise V , Tobin Martin D , Hall Ian P 
Published: October 2024

AbstractIntroductionThe effect of coding polymorphisms of the beta-2 adrenergic receptor gene (ADRB2) on functional properties of the receptor is well-established. We recently reported a genome-wide significant association between Thr164Ile and lung function, but the contribution of this variant to other traits remains unclear.MethodsTo identify pleiotropic effects ofADRB2Thr164Ile and other coding variants, we performed respiratory-focused and phenome-wide association studies in UK Biobank. In addition, we used available Olink proteomic data to characterise enriched pathways and upstream regulators of proteins associated withADRB2polymorphisms.ResultsThe minor allele of Thr164Ile was associated with reduced lung function, but not COPD or asthma defined using self-report and diagnostic codes in healthcare records. It was also associated with non-respiratory traits including increased eosinophil counts and blood lipid measurements, including increased cholesterol, reduced triglycerides and reduced apolipoprotein A. Proteins associated with Thr164Ile (P-value≤0.01) were enriched for various pathways, with the eosinophil-raising allele associated with reduced neutrophil degranulation, immunoregulatory interactions between a Lymphoid and a non-Lymphoid cells, TNF binding and DAP12 interactions, as well as activation of lipid metabolism pathways, including FXR/RXR activation and LXR/RXR activation. A gene-based analysis of rare, non-synonymousADRB2variants, identified a novel association with non-rheumatic pulmonary valve disorders, but no association with lung function.DiscussionIn conclusion, the lung function-lowering allele of Thr164Ile is associated with traits and proteins indicative of a role in immune and lipid metabolism pathways, but not COPD or asthma. In contrast,ADRB2rare coding variants are not associated with lung function.
Validity, Reliability, and Framing Effects in Equity-Efficiency Trade-Off Studies: A Systematic Review
Authors: Chechulina Victoria , Chu Andrew , Lam Quang Hung , Kabir-Bahk Camryn , Ali Shehzad 
Published: October 2024

AbstractObjectivesHealth system resources are limited, and decision makers often need to make trade-offs between equity and efficiency. Such trade-offs are guided by public values that are elicited using choice experiments. There is no standard approach to elicit equity-efficiency trade-offs. Previous studies have found significant variability in public values, raising concerns about the robustness of trade-off experiments. The objective of this systematic review was to determine whether and how equity-efficiency trade-off studies consider validity, reliability and framing effects.MethodsWe searched Medline, EMBASE, and Web of Science in January 2024 for health-related equity-efficiency trade-off studies. Two reviewers independently screened titles and abstracts, followed by full-text review, data extraction, and quality assessment.Results115 equity-efficiency trade-off studies were identified, of which 29 studies (25.2%) investigated validity, reliability, and/or framing effects. 14 (12.2%) studies assessed validity, 9 (7.8%) studies assessed reliability, and 10 (8.7%) assessed framing or cognitive effects. Validity was most frequently assessed by comparing results to hypothesized expectations, while reliability was commonly assessed by providing a repeated test or questionnaire. Framing and cognitive effects were assessed by varying question order or changing the wording or framing of the scenario. 19 of 23 studies reported high or acceptable validity or reliability, and 5 of 10 studies found no significant framing or cognitive effects.ConclusionThis systematic review highlights the need to consider robustness of elicited values in choice experiments. It will also guide future choice experiments that aim to estimate inequity aversion.
The Humanitarian-Development Nexus and Sexual and Reproductive Health Interventions in Fragile Settings: A Scoping Review
Authors: Qaddour Amany , Tappis Hannah , Lazieh Stefany , Ward Ava , Spiegel Paul 
Published: October 2024

ABSTRACTThe concurrent need for both humanitarian and development assistance in fragile settings and protracted emergencies has been termed the humanitarian-development nexus (HDN) or the humanitarian-development-peace nexus (HDpN). We undertook a scoping review on the operationalization of the HDpN for sexual, reproductive, maternal, newborn, child, and adolescent health interventions in fragile settings. We screened 2,183 publications, of which 29 peer-reviewed and 16 grey literature publications met inclusion criteria. No included studies focused on peace aspects within the HDpN and very few focused on child and adolescent health. Publications by humanitarian authors often classified maternal and newborn health as a component of sexual and reproductive health (SRH). Data extraction and analysis focused on three overarching themes: SRH prioritization across the HDN, the transition between minimum and comprehensive services, and health systems strengthening. This review provides concrete guidance on how to operationalize the HDN for SRH interventions in fragile settings. Expansion of SRH preparedness measures is necessary given the current trajectory of the climate emergency and other destabilizing events. The ability to flexibly transition between minimum and comprehensive services is important for maintaining service continuity in crisis-affected settings. COVID-19 proved to be a significant disruptor of SRH services, and a key inflection point in the collaboration between humanitarian and development practitioners. The use of task-shifting, decentralization, and telemedicine were approaches that may be adopted to maintain service delivery according to different contexts. Lastly, strengthening health systems was identified as essential across the HDN. With more crises extending for years, the wider literature has emphasized the necessity of health systems strengthening for reaching the Sustainable Development Goals, including in fragile settings.
Pathologic subtyping of Alzheimer’s disease brain tissue reveals disease heterogeneity
Authors: Lam Tiffany G. , Ross Sophie K. , Ciener Benjamin , Xiao Harrison , Flaherty Delaney , Lee Annie J. , Dugger Brittany N. , Reddy Hasini , Teich Andrew F. 
Published: October 2024

AbstractIn recent years, multiple groups have shown that what is currently thought of as "Alzheimer’s Disease" (AD) may be usefully viewed as several related disease subtypes. As these efforts have continued, a related issue is how common co-pathologies and ethnicity intersect with AD subtypes. The goal of this study was to use a dataset constituting 153 pathologic variables recorded on 666 AD brain autopsies to better define how co-pathologies and ethnicity relate to established AD subtypes. Pathologic clustering suggests 8 subtypes within this cohort, and further analysis reveals that the previously described continuum from hippocampal predominant to hippocampal sparing is well represented in our data. Small vessel disease is overall highest in a cluster with a low hippocampal/cortical tau ratio, and across all clusters small vessel disease segregates separately from Lewy body disease. Two AD clusters are identified with extensive Lewy bodies outside amygdala (one with a high hippocampal/cortical tau ratio and one with a low ratio), and we find an inverse relationship between cortical tau and Lewy body pathology across these two clusters. Finally, we find that brains from persons of Hispanic descent have significantly more AD pathology in multiple neuroanatomic areas. We find that Hispanic ethnicity is not uniformly distributed across clusters, and this is particularly pronounced in clusters with significant Lewy body pathology, where Hispanic donors are only found in a cluster with a low hippocampal/cortical tau ratio. In summary, our analysis of recorded pathologic data across two decades of banked brains reveals new relationships in the patterns of AD-related proteinopathy, co-pathology, and ethnicity, and highlights the utility of pathologic subtyping to classify AD pathology.Abbreviated summaryMultiple groups have shown that what is currently thought of as "Alzheimer’s Disease" (AD) may be usefully viewed as several related disease subtypes. Here, we utilize two decades of banked cases to demonstrate how co-pathology and ethnicity intersect with one of the most widely used methods of pathologic subtyping.
Comparison of immunogenicity of adjuvanted and high dose influenza vaccination in long-term care facility residents
Authors: Didion Elise M. , Kass Joseph D. , Wilk Dennis J. , Buss Emily , Frischmann Sarah-Michelle , Rubeck Sabina , Banks Richard , Wilson Brigid M. , Gravenstein Stefan , Canaday David H. 
Published: October 2024

AbstractBackgroundThe CDC recommends the more immunogenic adjuvanted and high-dose flu vaccines over standard-dose, non-adjuvanted vaccines for individuals above 65 years old. The current study compares adjuvanted trivalent inactivated flu vaccine (aTIV, FLUAD) versus high-dose flu vaccine (HD-IIV3, FLUZONE HD) to determine if they met non-inferiority standards for older long-term care facility (LTCF) residents.MethodsWe collected blood from long-term care facility residents participating in a randomized 1:1 active control trial comparing MF59C.1 adjuvanted trivalent inactivated flu vaccine, aTIV versus HD-IIV3 over the course of two flu seasons, 2018-2019 and 2019-2020 (Trial,NCT03694808). We assessed humoral immunity at set time points via hemagglutinin inhibition assays (HAI) and anti-neuraminidase (enzyme-linked lectin assays (ELLA)). The recombinant influenza vaccine (RIV, Flublok) was assessed similarly in year two for a small number of participants who were carried over from year 1 (n=32).ResultsWe enrolled 387 volunteers and administered either aTIV (n=194), HD-IIV3 (n=193) over the course of the 2018-2019 and 2019-2020 flu seasons. Among those enrolled and randomized in year one, a subset were administered RIV and studied in year two (n = 32). At 28 days post-vaccination, aTIV exhibited non-inferiority to HD-IIV3 for HAI for both H1N1 and H3N2 strains (GMT ratios (95% CI) for HD-IIV3/aTIV of 1.03(0.76, 1.4) and 1.04(0.73, 1.48), respectively; both 95% CI upper bounds < 1.5 to meet non-inferiority criteria) but not for Influenza B (GMT ratio (95% CI) = 1.21 (0.91, 1.61)). Non-inferiority criteria for HAI seroconversion were not met for any of the three strains. Applying the same non-inferiority criteria to neuraminidase inhibition (NI), both day 28 titer and seroconversion in aTIV were non-inferior to HD-IIV3 for H1N1 and H3N2 strains.ConclusionsBoth aTIV and HD-IIV3 elicited similar immune responses with robust antibody responses. For the primary outcome, aTIV is non-inferior to HD-IIV3 for HAI titer of H1N1 and H3N2 but failed to meet non-inferiority criteria for Influenza B and seroconversion for all assessed strains. For the secondary outcome, aTIV was non-inferior to HD-IIV3 for both titer and seroconversion of anti-neuraminidase for both H1N1 and H3N2.
Machine learning to classify left ventricular hypertrophy using ECG feature extraction by variational autoencoder
Authors: Gupta Amulya , Harvey Christopher J. , DeBauge Ashley , Shomaji Sumaiya , Yao Zijun , Noheria Amit 
Published: October 2024

ABSTRACTBackgroundTraditional ECG criteria for left ventricular hypertrophy (LVH) have low diagnostic yield. Machine learning (ML) can improve ECG classification.MethodsECG summary features (rate, intervals, axis), R-wave, S-wave and overall-QRS amplitudes, and QRS/QRST voltage-time integrals (VTIs) were extracted from 12-lead, vectorcardiographic X-Y-Z-lead, and root-mean-square (3D) representative-beat ECGs. Latent features were extracted by variational autoencoder from X-Y-Z and 3D representative-beat ECGs. Logistic regression, random forest, light gradient boosted machine (LGBM), residual network (ResNet) and multilayer perceptron network (MLP) models using ECG features and sex, and a convolutional neural network (CNN) using ECG signals, were trained to predict LVH (left ventricular mass indexed in women >95 g/m², men >115 g/m²) on 225,333 adult ECG-echocardiogram (within 45 days) pairs. AUROCs for LVH classification were obtained in a separate test set for individual ECG variables, traditional criteria and ML models.ResultsIn the test set (n=25,263), AUROC for LVH classification was higher for ML models using ECG features (LGBM 0.790, MLP 0.789, ResNet 0.788) as compared to the best individual variable (VTIQRS-3D0.677), the best traditional criterion (Cornell voltage-duration product 0.647) and CNN using ECG signal (0.767). Among patients without LVH who had a follow-up echocardiogram >1 (closest to 5) years later, LGBM false positives, compared to true negatives, had a 2.63 (95% CI 2.01, 3.45)-fold higher risk for developing LVH (p<0.0001).ConclusionsML models are superior to traditional ECG criteria to classify—and predict future—LVH. Models trained on extracted ECG features, including variational autoencoder latent variables, outperformed CNN directly trained on ECG signal.
LABOR DURATION IS DEFINED BY THE TIME OF DAY OF LABOR INDUCTION
Authors: Cataldo Kylie , Long Robert , Olomnu Isoken , Cortese Rene , Hoffmann Hanne M. 
Published: October 2024

ABSTRACTBACKGROUNDSpontaneous labor and birth peak during the late evening and early morning hours, indicating an endogenous rhythm in labor onset and birth. We hypothesize that the time-of-day of labor induction will define labor duration and the risk of cesarian section.METHODSIn a retrospective study of pregnant women who were induced for labor (n =3,688), time-of- day of labor induction was studied across maternal phenotypes. Survival analysis and Cox Proportional Hazards model were used to identify differences in time-to-birth as a result of inducing labor at a specific time-of-day.RESULTSLabor induction was circadian (p<0.05, Lomb-Scargle test), with a gradual lengthening in labor duration when labor induction was initiated later in the day, peaking at 23:00 hours (average labor duration of 20.72 hours) as compared to induction at 5:00 hours (average labor duration of 14.74 hours, p<0.01, Kruskal-Wallis test). The optimal time-of-day of labor induction was conditioned by maternal phenotype with significant differences in probability of giving birth as a result of the time-of-day labor was induced for nulliparous obese (p<0.05, Two-way ANOVA), and parous obese women (p<0.05).CONCLUSIONSLabor duration in response to induction is circadian, with the shortest labor duration when induced during early morning hours. The optimal time-of-day of labor induction is conditioned by maternal phenotype and should be considered as a labor management practice.
The Use of Machine Learning in Occupational Risk Communication for Healthcare Workers – Protocol for scoping review
Authors: de Oliveira Gabriela Laudares Albuquerque , Bonow Clarice Alves , de Oliveira Castellano Rodrigues Itiberê , Geraldo Amanda Xavier 
Published: October 2024

ABSTRACTIntroductionWith the development of technology, the use of machine learning (ML), a branch of computer science that aims to transform computers into decision-making agents through algorithms, has grown exponentially. This protocol arises from the need to explore the best practices for applying ML in the communication and management of occupational risks for healthcare workers.Methods and analysisThis scoping review protocol1details a search to be conducted in the academic databases Public Medical Literature Analysis and Retrieval System Online (PUBMED), through the Virtual Health Library (BVS): Medical Literature Analysis and Retrieval System (MEDLINE), Latin American and Caribbean Literature in Health Sciences (LILACS), West Pacific (WPRIM), Nursing Database (BDENF) and Scientific Electronic Library Online (SciELO), SCOPUS, Web of Science, IEEE Xplore Digital Library and Excerpta Medica Database (EMBASE). This scoping review protocol outlines the objectives, methods, and timeline for a review that will explore and map the existing scientific evidence and knowledge on the use of machine learning (ML) in risk communication for healthcare workers. This protocol follows the PRISMA-ScR2and JBI guidelines3for conducting scoping reviews. The guiding question of the review is: How is machine learning used in risk communication for healthcare workers? The search will use PCC (Population, Concept, Context) terms and the specific descriptors defined by each database. The narrative synthesis will describe the main themes and findings of the review.The results of this scoping review will be disseminated through publication in an international peer-reviewed scientific journal.Ethics and disseminationEthical approval is not required; data will rely on published articles. Findings will be published open access in an international peer-reviewed journal.Strengths and limitations of this studyStrengthsThe study allows for comprehensive mapping of existing evidence on ML in occupational risk communication.The methodology follows PRISMA-ScR and JBI guidelines, ensuring transparency and replicability.The research employs a broad search strategy across multiple databases to capture relevant studies.LimitationsThe accuracy of ML models is dependent on the quality of the data used.The implementation of ML in healthcare requires careful evaluation of ethical, legal, and privacy issues.Registration details OSF Registries:The protocol for this review was registered in the Open Science Framework under DOI 10.17605/OSF.IO/92SK4 (available athttps://osf.io/92SK4).