bluuebunny/crossref_metadata_2025_split huggingface dataset:
Viral rebound among patients receiving COVID-19 convalescent plasma for treatment of Covid-19 in Uganda
Authors: Alupo Patricia , Muttamba Winters , Mugenyi Levi , Kimuli Ivan , Winceslaus Katagira , Kirenga Bruce 
Published: May 2023

AbstractBackgroundViral rebound has been reported in people infected with COVID-19 treated with nirmatrelvir/ritonavir, and some cases been reported in patients who did not receive any antiviral treatment. Since the course of COVID-19 has not yet been well defined, we evaluated the incidence of viral rebound among COVID-19 patients treated with COVID-19 Convalescent Plasma (CCP) in Uganda.MethodsIn the CCP trail, 136 patients were enrolled between 21stSeptember 2020 and 2ndDecember 2020 who presented to the Mulago National Referral COVID-19 treatment unit. Patients with a positive SARS-CoV-2 reverse transcriptase (RT)-PCR test irrespective of disease severity were hospitalised and randomised to receive either COVID-19 CCP plus standard of care (SOC) or SOC alone. SARS-CoV-2 RT-PCR was done at baseline and on days 3, 5, 7, 14 and 28 post randomisation or until two consecutive negative RT-PCR results were obtained, whichever occurred first. We analysed for occurrence of viral rebound. Viral rebound was defined as a positive SARS-CoV-2 RT-PCR test following a prior negative test.Findings20% of the participants had viral rebound. Viral rebounders were predominantly male. The median age was 45-64 years and they had at least one co-morbidity. There was no difference in the rebound rates in the study arms, and participants with hypertension had more rebound rates compared to those with other co-morbidities.InterpretationViral RNA rebound was common among patients receiving CCP. Viral rebound may be a result of the biphasic nature of COVID-19 infection, and not a consequence of the therapeutic interventions.
Prescribing pre- and post-operative physical activity interventions for people undergoing breast cancer surgery: a qualitative systematic review
Authors: Howe Lauren , Husband Andy , Robinson-Barella Anna 
Published: May 2023

ABSTRACTIntroductionUndertaking physical activity, pre- and post-operatively, can benefit recovery time and improve post-surgical outcomes. One cohort of patients that have reported these benefits are those undergoing surgery for breast cancer. Yet, what remains unclear is the level to which physical activity interventions are implemented into standard surgical care for patients with breast cancer.AimsThis systematic review aimed to examine existing qualitative evidence focusing on pre- and post-operative physical activity interventions to better understand the benefits and shortcomings of physical activity within the surgical journey.MethodsA systematic literature search was undertaken in November 2022, across five databases: MEDLINE, PsycINFO, Embase, CINAHL and Scopus. Qualitative studies involving people with breast cancer who had undertaken a physical activity intervention, either pre- and/or post-operatively, were included for analysis. The review was registered on PROSPERO: CRD42022372466 and performed according to PRISMA guidelines. The Critical Appraisal Skills Programme qualitative study checklist was used to assess study quality.ResultsFourteen studies were included, comprising the perspectives of 418 people receiving surgery for breast cancer. One study implemented pre-operative physical activity interventions; the remaining studies focused on post-operative interventions. A narrative systematic review was undertaken due to heterogeneity in reported results. Four themes were developed by thematic analysis, centring on: (i) factors promoting engagement with physical activity interventions; (ii) factors preventing engagement with physical activity interventions; (iii) the impact of pre- and post-operative interventions on physical and psychological health; and (iii) participant recommendations for pre- and post-operative interventions.Conclusionpre- and post-operative physical activity interventions were well-accepted. Patients recognised factors which promoted or prevented engagement with interventions, as well as pre- and post-operative physical and psychological benefits that arose as a result. Evidence based co-design studies may further inform successful implementation of physical activity into standard care for surgical breast cancer patients.
Predicting the public health impact of bivalent vaccines and nirmatrelvir-ritonavir against COVID-19
Authors: Park Hailey J. , Tan Sophia T. , León Tomás M. , Jain Seema , Schechter Robert , Lo Nathan C. 
Published: May 2023

AbstractBackgroundUptake of COVID-19 bivalent vaccines and oral medication nirmatrelvir-ritonavir (Paxlovid) has remained low across the United States. Assessing the public health impact of increasing uptake of these interventions in key risk groups can guide further public health resources and policy.MethodsThis modeling study used person-level data from the California Department of Public Health on COVID-19 cases, hospitalizations, deaths, and vaccine administration from July 23, 2022 to January 23, 2023. We modeled the impact of additional uptake of bivalent COVID-19 vaccines and nirmatrelvir-ritonavir during acute illness in different risk groups defined by age (50+, 65+, 75+ years) and vaccination status (everyone, primary series only, previously vaccinated). We predicted the number of averted COVID-19 cases, hospitalizations, and deaths and number needed to treat (NNT).ResultsFor both bivalent vaccines and nirmatrelvir-ritonavir, the most efficient strategy (based on NNT) for averting severe COVID-19 was targeting the 75+ years group. We predicted that perfect coverage of bivalent boosters in the 75+ years group would avert 3,920 hospitalizations (95%UI: 2,491-4,882; 7.8% total averted; NNT 387) and 1,074 deaths (95%UI: 774-1,355; 16.2% total averted; NNT 1,410). Perfect uptake of nirmatrelvir-ritonavir in the 75+ years group would avert 5,644 hospitalizations (95%UI: 3,947-6,826; 11.2% total averted; NNT 11) and 1,669 deaths (95%UI: 1,053-2,038; 25.2% total averted; NNT 35).ConclusionsThese findings suggest prioritizing uptake of bivalent boosters and nirmatrelvir-ritonavir among the oldest age groups would be efficient and have substantial public health impact in reducing the burden of severe COVID-19, but would not address the entire burden of severe COVID-19.
Group comparison based on genetic information reveals lineage-specific therapeutic vulnerabilities in acute myeloid leukemia
Authors: Nakahara Jakushin , Yamamoto Keita , Yabushita Tomohiro , Chinen Takumi , Ito Kei , Takeda Yutaka , Kitagawa Daiju , Goyama Susumu 
Published: May 2023

ABSTRACTCancer is a genetic disease with specific mutations or fusions. Therapies targeting cancer cell-specific essential genes are expected to have efficient anticancer effects with fewer side effects. To explore such cancer cell-specific vulnerabilities, we established a two-group comparison system to predict essential genes in each cancer subtype using the data from the Cancer Dependency Map (DepMap). We applied this analytical method to acute myeloid leukemia (AML) and identified PCYT1A and BCL2L1 as a specific vulnerability in MLL-rearranged AML andTP53-mutated AML, respectively. Interestingly, further investigation revealed that PCYT1A is in fact a critical regulator in monocytic AML including those with MLL-rearrangements, and BCL2L1 is essential in acute erythroid leukemia in whichTP53is frequently mutated. These results highlighted the importance of cell of origin, rather than the genetic aberrations alone, to identify subtype-specific vulnerabilities in AML. The DepMap-based two-group comparison approach could accelerate the discovery of subtype-specific therapeutic targets in diverse cancers.
Utilizing tumor microenvironment microbial profiles and host gene expressions for survival subtyping in diverse types of cancers
Authors: Zhang Haohong , Cheng Mingyue , Ji Lei , Ning Kang 
Published: May 2023

AbstractThe tumor microbiome, a complex community of microbes found in tumors, has been found to be linked to cancer development, progression, and treatment outcome. However, it remains a bottleneck in distangling the relationship between the tumor microbiome and patient survival. In this study, we aimed to decode this complex relationship by developing ASD-cancer (autoencoder-based subtypes detector for cancer), a semi-supervised deep learning framework that could extract survival-related features from tumor microbiome and transcriptome data, and identify patients’ survival subtypes. By using samples from The Cancer Genome Atlas database, we identified two statistically distinct survival subtypes across all 20 types of cancer. Our framework provided improved risk-stratification (e.g., for Liver hepatocellular carcinoma, LIHC, log-rank test,P= 8.12E-6) compared to PCA (e.g., for LIHC, log-rank test,P= 0.87), predicted survival subtypes accurately, and identified biomarkers for survival subtypes. Additionally, we identified potential interactions between microbes and genes that may play roles in survival. For instance, in LIHC,Arcobacter,Methylocella, andIsoptericolamay regulate host survival through interactions with host genes enriched in the HIF-1 signaling pathway, indicating these species as potential therapy targets. Further experiments on validation dataset have also supported these patterns. Collectively, ASD-cancer has enabled accurate survival subtyping and biomarker discovery, which could facilitate personalized treatment for a broad-spectrum types of cancers.
Molecular Evolution and Interaction of 14-3-3 Proteins with H+-ATPases in Plant Abiotic Stresses
Authors: Jiang Wei , He Jing , Babla Mohammad , Wu Ting , Tong Tao , Riaz Adeel , Zeng Fanrong , Qin Yuan , Chen Guang , Deng Fenglin , Chen Zhong-Hua 
Published: May 2023

AbstractEnvironmental stresses severely affect plant growth and crop productivity. Regulated by 14-3-3 proteins (14-3-3s), H+-ATPases (AHA) are important proton pumps that can induce diverse secondary transport via channels and co-transporters for the abiotic stress response of plants. Many studies demonstrated the roles of 14-3-3s and AHAs in coordinating the processes of plant growth, phytohormone signaling, and stress responses. However, the molecular evolution of 14-3-3s and AHAs has not been summarized in parallel with insights across multiple plant species. Here, we review the roles of 14-3-3s and AHAs in cell signaling to enhance plant responses to diverse environmental stresses. We analyzed the molecular evolution of key proteins that are associated with 14-3-3s and AHAs in plant growth and hormone signaling. The results revealed evolution, duplication, contraction, and expansion of 14-3-3s and AHAs in green plants. We also discussed the stress-specific expression of those14-3-3sandAHAsin a eudicot (Arabidopsis thaliana), a monocot (Hordeum vulgare) and a moss (Physcomitrium patens) under abiotic stresses. We propose that 14-3-3s and H+-ATPases respond to abiotic stresses through many important targets and signaling components of phytohormones, which could be promising to improve plant tolerance to single or multiple environmental stresses.HighlightWe review the response and adaptation of 14-3-3s and AHAs to diverse environmental stimuli and we analyze the evolutionary features and molecular functions of 14-3-3s and AHAs.
Fibroblast-specific inflammasome activation predisposes to atrial fibrillation
Authors: Li Luge , Coarfa Cristian , Yuan Yue , Abu-Taha Issam , Wang Xiaolei , Song Jia , Koirala Amrit , Grimm Sandra L , Kamler Markus , Mullany Lisa K , Tallquist Michelle , Nattel Stanley , Dobrev Dobromir , Li Na 
Published: May 2023

ABSTRACTBackgroundRecent work has shown that the NLR-family-pyrin-domain-containing 3 (NLRP3) inflammasome is expressed in cardiomyocytes and when specifically activated causes atrial electrical remodeling and arrhythmogenicity. Whether the NLRP3-inflammasome system is functionally important in cardiac fibroblasts (FBs) remains controversial. In this study, we sought to uncover the potential contribution of FB NLRP3-inflammasome signaling to the control of cardiac function and arrhythmogenesis.MethodsDigital-PCR was performed to determine the expression of NLRP3-pathway components in FBs isolated from human biopsy samples of AF and sinus rhythm patients. NLRP3-system protein expression was determined by immunoblotting in atria of canines with electrically maintained AF. Using the inducible, resident fibroblast (FB)-specific Tcf21-promoter-Cre system (Tcf21iCre as control), we established a FB-specific knockin (FB-KI) mouse model with FB-restricted expression of constitutively active NLRP3. Cardiac function and arrhythmia susceptibility in mice were assessed by echocardiography, programmed electrical stimulation, and optical mapping studies.ResultsNLRP3 and IL1B were upregulated in atrial FBs of patients with persistent AF. Protein levels of NLRP3, ASC, and pro-Interleukin-1β were increased in atrial FBs of a canine AF model. Compared with the control mice, FB-KI mice exhibited enlarged left atria (LA) and reduced LA contractility, a common determinant of AF. The FBs from FB-KI mice were more transdifferentiated, migratory, and proliferative compared to the FBs from control mice. FB-KI mice showed increased cardiac fibrosis, atrial gap junction remodeling, and reduced conduction velocity, along with increased AF susceptibility. These phenotypic changes were supported by single nuclei (sn)RNA-seq analysis, which revealed enhanced extracellular matrix remodeling, impaired communication among cardiomyocytes, and altered metabolic pathways across multiple cell types.ConclusionsOur results show that the FB-restricted activation of the NLRP3-inflammasome system leads to fibrosis, atrial cardiomyopathy, and AF. Activation of NLRP3-inflammasome in resident FBs exhibits cell-autonomous function by increasing the activity of cardiac FBs, fibrosis, and connexin remodeling. This study establishes the NLRP3-inflammasome as a novel FB-signaling pathway contributing to AF pathogenesis.
How accurately can one predict drug binding modes using AlphaFold models?
Authors: Karelina Masha , Noh Joseph J. , Dror Ron O. 
Published: May 2023

AbstractComputational prediction of protein structure has been pursued intensely for decades, motivated largely by the goal of using structural models for drug discovery. Recently developed machine learning methods such as AlphaFold 2 (AF2) have dramatically improved protein structure prediction, with reported accuracy approaching that of experimentally determined structures. To what extent do these advances translate to an ability to predict more accurately how drugs and drug candidates bind to their target proteins? Here we carefully examine the utility of AF2 protein structure models for predicting binding poses of drug-like molecules at the largest class of drug targets, the G protein–coupled receptors. We find that AF2 models capture binding pocket structures much more accurately than traditional homology models, with errors nearly as small as differences between structures of the same protein determined experimentally with different ligands bound. Strikingly, however, the accuracy of ligand binding poses predicted by computational docking to AF2 models is not significantly higher than when docking to traditional homology models and is much lower than when docking to structures determined experimentally without these ligands bound. These results have important implications for all those who might use predicted protein structures for drug discovery.
Elucidating disease-associated mechanisms triggered by pollutants via the epigenetic landscape using large-scale ChIP-Seq data
Authors: Zou Zhaonan , Yoshimura Yuka , Yamanishi Yoshihiro , Oki Shinya 
Published: May 2023

ABSTRACTBackgroundDespite well-documented effects on human health, the action modes of environmental pollutants are incompletely understood. Although transcriptome-based approaches are widely used to predict associations between chemicals and disorders, the molecular cues regulating pollutant-derived gene expression changes remain unclear. Therefore, we developed a data-mining approach, termed “DAR-ChIPEA,” to identify transcription factors (TFs) playing pivotal roles in the action modes of pollutants.MethodsLarge-scale public ChIP-Seq data (human,n= 15,155; mouse,n= 13,156) were used to predict TFs that are enriched in the pollutant-induced differentially accessible genomic regions (DARs) obtained from epigenome analyses (ATAC-Seq). The resultant pollutant–TF matrices were then cross-referenced to a repository of TF–disorder associations to account for pollutant modes of action. We subsequently evaluated the performance of the proposed method using a chemical perturbation dataset to compare the outputs of the DAR-ChIPEA and our previously developed differentially expressed gene (DEG)-ChIPEA methods using pollutant-induced DEGs as input. We then adopted the proposed method to predict disease-associated mechanisms triggered by pollutants.ResultsThe proposed approach outperformed other methods using the area under the receiver operating characteristic curve score. The mean score of the proposed DAR-ChIPEA was significantly higher than that of our previously described DEG-ChIPEA (0.7287 vs. 0.7060;Q= 5.278 × 10−42; two-tailed Wilcoxon rank-sum test). The proposed approach further predicted TF-driven modes of action upon pollutant exposure, indicating that (1) TFs regulating Th1/2 cell homeostasis are integral in the pathophysiology of tributyltin-induced allergic disorders; (2) fine particulates (PM2.5) inhibit the binding of C/EBPs, Rela, and Spi1 to the genome, thereby perturbing normal blood cell differentiation and leading to immune dysfunction; and (3) lead induces fatty liver by disrupting the normal regulation of lipid metabolism by altering hepatic circadian rhythms.ConclusionHighlighting genome-wide chromatin change upon pollutant exposure to elucidate the epigenetic landscape of pollutant responses outperformed our previously described method that focuses on gene-adjacent domains only. Our approach has the potential to reveal pivotal TFs that mediate deleterious effects of pollutants, thereby facilitating the development of strategies to mitigate damage from environmental pollution.
MyeloDB: A multi-omics resource for Multiple Myeloma
Authors: Kumar Ambuj , Kumar Keerthana Vinod , Kundal Kavita , Sengupta Avik , R Kunjulakshmi , Kumar Rahul 
Published: May 2023

AbstractMultiple myeloma (MM) is a common type of blood cancer affecting plasma cells originating from the lymphoid B-cell lineage. It accounts for about 10% of all haematological malignancies and can cause significant end-organ damage. The emergence of genomic technologies such as next-generation sequencing and gene expression analysis has opened new possibilities for early detection of multiple myeloma and identification of personalized treatment options. However, there remain significant challenges to overcome in MM research, including integrating multi-omics data, achieving a comprehensive understanding of the disease, and developing targeted therapies and biomarkers. The extensive data generated by these technologies presents another challenge for data analysis and interpretation. To bridge this gap, we have developed a multi-omics open-access database called MyeloDB. It includes gene expression profiling, high throughput CRISPR-Cas9 screens, drug sensitivity resources profile, and biomarkers. MyeloDB contains 47 expression profiles, 3 methylation profiles comprising a total of 5630 patient samples and 15 biomarkers which were reported in previous studies. In addition to this, MyeloDB can provide significant insight of gene mutations in MM on drug sensitivity. Furthermore, users can download the datasets and conduct their own analyses. Utilizing this database, we have identified five novel genes i.e.,CBFB, MANF, MBNL1, SEPHS2andUFM1as potential drug targets for MM. We hope MyeloDB will serve as a comprehensive platform for researchers and foster novel discoveries in MM. MyeloDB is freely accessible at: (https://project.iith.ac.in/cgntlab/myelodb/)
Dismantling cognitive-behavioural therapy for chronic insomnia in adults with or without comorbidities: a systematic review and component network meta-analysis
Authors: Furukawa Yuki , Sakata Masatsugu , Yamamoto Ryuichiro , Nakajima Shun , Kikuchi Shino , Inoue Mari , Ito Masami , Noma Hiroku , Takashina Hikari Nishimura , Funada Satoshi , Ostinelli Edoardo G. , Furukawa Toshi A. , Efthimiou Orestis , Perlis Michael 
Published: May 2023

ABSTRACTBackgroundChronic insomnia disorder is highly prevalent, disabling and costly. Cognitive-behavioural therapy for insomnia (CBT-I) is recommended as the first-line treatment. CBT-I may contain various educational, cognitive and behavioural strategies delivered in a range of formats, but the effect of each component remains unclear.MethodsWe performed a systematic review and component network meta-analysis (cNMA) of CBT-I trials for chronic insomnia. We searched PubMed, CENTRAL, PsycINFO and ICTRP for randomised controlled trials published from database inception to 14thMay 2022, comparing any form of CBT-I against each other or a control condition for chronic insomnia disorder in adults (aged ≥18 years). We included insomnia both with and without comorbidities. Concomitant treatments were allowed if they were equally distributed among the arms. Two independent reviewers identified components, extracted data, and assessed trial quality. Primary outcome of interest in this study was treatment efficacy (remission defined as reaching a satisfactory state at endpoint measured by any validated self-reported scale) at post-treatment. (PROSPERO; CRD42022324233)FindingsWe identified 226 trials, including 29,982 participants. Mean age was 45·7 years and 71% were women. The results suggests that critical components of CBT-I are cognitive restructuring (incremental odds ratio[iOR] 1·63 [95% confidence interval 1·25 to 2·14]), sleep restriction (iOR 1·44 [1·00 to 2·06]) and stimulus control (iOR 1·44 [1·00 to 2·07]) Sleep hygiene education was not essential (iOR 1·05 [0·79 to 1·38]) and relaxation procedures may be counterproductive (iOR 0·81 [0·64 to 1·03]). Face-to-face, therapist-led program was found to be most beneficial (iOR 1·86 [1·21to 2·85]). The overall risk of bias was low in 8% of the trials, some concerns in 56%, and high in 36%.InterpretationThis cNMA suggests that effective and efficient CBT-I packages can include cognitive restructuring, sleep restriction and stimulus control, but not relaxation.FundingNone.