bluuebunny/crossref_metadata_2025_split huggingface dataset:
Replication stress increases de novo CNVs across the malaria parasite genome
Authors: Brown Noah , Luniewski Aleksander , Yu Xuanxuan , Warthan Michelle , Liu Shiwei , Zulawinska Julia , Ahmad Syed , Congdon Molly , Santos Webster , Xiao Feifei , Guler Jennifer L 
Published: December 2024

ABSTRACTChanges in the copy number of large genomic regions, termed copy number variations (CNVs), contribute to important phenotypes in many organisms. CNVs are readily identified using conventional approaches when present in a large fraction of the cell population. However, CNVs that are present in only a few genomes across a population are often overlooked but important; if beneficial under specific conditions, a de novo CNV that arises in a single genome can expand during selection to create a larger population of cells with novel characteristics. While the reach of single cell methods to study de novo CNVs is increasing, we continue to lack information about CNV dynamics in rapidly evolving microbial populations. Here, we investigated de novo CNVs in the genome of thePlasmodiumparasite that causes human malaria. The highly AT-richP. falciparumgenome readily accumulates CNVs that facilitate rapid adaptation to new drugs and host environments. We employed a low-input genomics approach optimized for this unique genome as well as specialized computational tools to evaluate the de novo CNV rate both before and after the application of stress. We observed a significant increase in genome-wide de novo CNVs following treatment with a replication inhibitor. These stress-induced de novo CNVs encompassed genes that contribute to various cellular pathways and tended to be altered in clinical parasite genomes. This snapshot of CNV dynamics emphasizes the connection between replication stress, DNA repair, and CNV generation in this important microbial pathogen.
Fibrotic pulmonary dust foci is an advanced pneumoconiosis lesion in rats induced by titanium dioxide nanoparticles in a 2-year inhalation study
Authors: Yamano Shotaro , Umeda Yumi 
Published: December 2024

AbstractBackgroundWe have previously reported that inhalation exposure to titanium dioxide nanoparticles (TiO2NPs) for 13 weeks causes early pneumoconiosis lesions in the alveolar region of F344 rats. We defined these characteristic lesions as pulmonary dust foci (PDF). In this report, we re-evaluate and detail the histopathological data regarding particle-induced pneumoconiosis lesions, including progressive lesions of the early PDF lesions, that developed in F344 rats exposed TiO2NPs by whole body inhalation over a period of two years.MethodsMale and female F344 rats were exposed to 0.5, 2, and 8 mg/m3anatase type TiO2NPs for 6 hours/day, 5 days/week for 104 weeks using a whole-body inhalation exposure system. After the final exposure, the rats were euthanized. In the present study, the collected lungs were re-evaluated macroscopically and histopathologically.ResultsRats exposed to TiOL NPs developed macroscopic white lesions, primarily in the subpleural and hilar regions of the lung, which increased in size and number with exposure concentration. Histologically, two lesion types were identified: (1) Fibrotic Pulmonary Dust Foci (fPDF), characterized by collagen deposition, inflammatory infiltration, and disrupted alveolar epithelial differentiation, and (2) Dust Macules (DM), characterized by macrophage accumulation without significant fibrosis or inflammation. Immunohistochemical analysis revealed abnormal alveolar epithelial differentiation and reduced capillary density within fPDFs. Importantly, no histological connection was found between the pneumoconiosis lesions and the observed lung tumors, which resembled spontaneous, age-related neoplasms.ConclusionsChronic inhalation of TiOL NPs induces advanced pneumoconiosis characterized by fPDF and DM, with distinct pathological features. However, these lesions were not directly linked to lung tumor development. Therefore, in this study PDF lesions developed into fPDF lesions but did not lead to tumorigenesis. This study provides critical insights into the long-term pulmonary effects of TiOL NP exposure and the progression of pneumoconiosis lesions in the rats.
P2Y2 purinergic receptor and DNA sensor cGAS dictate ionizing radiation-mediated proinflammatory macrophage activation
Authors: Mostefa-Kara Ali , Nathan Aurélia Deva , Paoletti Audrey , Chapel Anais , Gutierrez-Mateyron Emie , Cao-Pham Thanh Trang , Ghosn Yara Bou , Allouch Awatef , Perfettini Jean-Luc 
Published: December 2024

AbstractThe reprogramming of tumor-associated macrophages (TAMs) by radiotherapy is associated with cancer patient’s response and sensitization to immune checkpoint blockade, but the molecular mechanisms involved remain largely unknown. Here, we show that following ionizing radiation (IR), macrophages accumulate single and double strand-DNA breaks and fragmented mitochondria in their cytosol, and stabilize the DNA sensor cyclic GMP-AMP synthase (cGAS). We demonstrate that mitochondrial fragmentation is induced by the activation of the dynamin-related protein 1 (DRP1), and controls the stabilization of cGAS and the proinflammatory activation of irradiated macrophages. Furthermore, pharmacological and genetic inhibitions of cGAS impair the proinflammatory activation of irradiated macrophages, thus revealing that cGAS is a central effector of IR-mediated proinflammatory macrophage activation. Interestingly, we also report that the purinergic receptor P2Y2 acts as an endogenous repressor of the proinflammatory macrophage activation and demonstrate that P2Y2 inactivation enhances the capacity of irradiated macrophages to undergo a proinflammatory activation. Our results thus define a new signaling pathway elicited in macrophages by IR directing mitochondrial dynamics, cytosolic DNA recognition by cGAS and proinflammatory phenotype, which is enhanced following P2Y2 inactivation.
Development of a novel risk prediction tool for emergency department patients with symptoms of coronary artery disease: A research study protocol
Authors: McRae Andrew D. , Macci Aysha J. , Holodinsky Jessalyn K. , Sajobi Tolulope , Andruchow James E. , Borgundvaag Bjug , Brooks Steven , Cheng Ivy , Deb Saswata , Fok Patrick , Kavsak Peter , Graham Michelle M. , Lee Jacques , McLeod Shelley L , Scheuermeyer Frank , Thiruganasambandamoorthy Venkatesh , Wiemer Hana , Yan Justin W. , Hohl Corinne M. ,   the Canadian Emergency Department Research Network (CEDRN) and the Network of Canadian Emergency Researchers (NCER)
Published: December 2024

AbstractPatients with chest pain and symptoms of acute coronary syndromes (ACS) account for over 600,000 emergency department (ED) visits annually in Canada. Over 80% of these patients do not have ACS, and most are discharged from the ED after a thorough evaluation. However, a large proportion of these patients are referred for outpatient objective cardiac testing after ED discharge, even though their short-term risk for major adverse cardiac events (MACE) such as death, new myocardial infarction or need for revascularization is very small. This contributes to substantial low-value healthcare utilization, and limits access for those patients who are more likely to benefit from objective testing.Existing risk prediction tools were developed prior to the advent of high-sensitivity cardiac troponin assays, were derived in non-representative populations and, when applied to ED patients with low cardiac troponin concentrations, systematically overestimate short-term risk of (MACE).This multicenter prospective cohort study will enrol ED patients with chest pain to derive and validate a novel risk prediction tool to accurately identify patients at low risk of MACE and not requiring additional cardiac testing from patients who are likely to benefit from additional cardiac testing. We will enroll 6500 patients at 13 Canadian EDs nd prospectively follow them for 30 days to ascertain a primary outcome of MACE. The risk prediction tool developed in this project will guide safe, efficient, appropriate referrals of ED patients with chest pain.
Evaluating digitally-enabled self-experiments in general practice to support patients managing persistent pain
Authors: Sturman Nancy , Nikles Jane , Worthy Peter , Fjaagesund Shauna , Elphinston Rachel , Andrews Nicole , Sterling Michele , Konigorski Stefan 
Published: December 2024

AbstractBackgroundDespite somewhat limited evidence, non-pharmacological, self-management interventions are often recommended for general practice patients with persistent pain. StudyU is an open-source digital platform designed to help patients undertake self-experiments, using a single case experimental design, to test whether these interventions are personally effective.AimTo investigate the feasibility and acceptability of integrating digitally-enabled self-experiments in the general practice care of patients with persistent pain.Design and settingWe will recruit 50 patients from a large Australian general practice. Participants trial a self-selected, self-management intervention (such as a physical activity, mindfulness practice, or online, self-guided cognitive behavioural therapy) approved by their general practitioner (GP), and use the StudyU app to rate the daily impact of their pain over the 10-week study period. The primary clinical outcome of the self-experiments is mean difference in pain interference (measured using the modified Brief Pain Inventory) between baseline (usual routine) and intervention conditions. Clinical reports are generated for the patient and their GP.MethodWe use validated measures of app usability and acceptance, pre/post measures of patient self-efficacy, quality of life, health service use and self-reported health, individual interviews informed by Normalisation Process Theory, and a nested process evaluation to examine the feasibility and acceptability for patients and practice staff of embedding these self-experiments in general practice care.ConclusionDigitally-enabled self-experiments testing non-pharmacological treatment effectiveness may empower patients to self-manage persistent pain, in partnership with their GPs, and provide a model for integrating other new technology for patients with other chronic conditions.HOW THIS FITS INIn spite of somewhat limited evidence, non-pharmacological, self-management interventions are generally recommended for general practice patients with persistent pain, a distressing and costly condition. Digitally-enabled single-case experimental designs may be a useful approach to assessing the individual effectiveness of self-management interventions. This research will provide evidence about the acceptability and feasibility (for patients, clinicians and other practice staff) of integrating digitally enabled self-experiments into general practice care.
PULSE PRESSURE IMPAIRS COGNITION VIA WHITE MATTER DISRUPTION
Authors: King Deborah L. O. , Henson Richard N. , Correia Marta , Rowe James B. , Tsvetanov Kamen A. 
Published: December 2024

ABSTRACTBACKGROUNDIn older adults, elevated pulse pressure predicts cognitive decline, irrespective of overall blood pressure. It is proposed to compromise cerebrovascular integrity, potentially leading to brain damage, though the underlying mechanisms remain unclear. We hypothesized that pulse pressure affects cognition by disrupting white matter microstructure, and that it does so independently of other cardiovascular risk factors.METHODSIndices of pulse pressure, overall blood pressure and heart rate variability were estimated in a cross-sectional population-based cohort (n=708, aged 18-88 years). An indicator of white matter microstructure was derived from diffusion-weighted imaging, termed the “peak width of skeletonised mean diffusivity” (PSMD). Cognitive function was assessed using measures of processing speed.RESULTSIn robust multiple linear regressions, pulse pressure significantly predicted PSMD. We also found that PSMD significantly predicted processing speed. Thus higher pulse pressure was associated with greater white matter disruption, and greater white matter disruption was associated with slower processing abilities.This motivated testing whether PSMD mediates the effects of pulse pressure on processing speed. We tested this using a number of structural equation models. PSMD significantly and substantially mediated the effect of pulse pressure on processing speed, over and above age and other cardiovascular factors. We then expanded the model to show that vascular-related changes in processing speed in turn drive changes in higher cognitive functions.CONCLUSIONSHigh pulse pressure disrupts microstructural integrity of white matter in the brain, leading to slower processing speed. We propose that better manament of pulse pressure could help to preserve white matter integrity and reduce cognitive decline in later life.
Quantifying the impact of the COVID-19 pandemic on the Scottish accident and emergency landscape
Authors: Teoh Hui Pheng , Banas Kasia , Oldnall Christopher Aldous 
Published: December 2024

AbstractBackgroundThe COVID-19 pandemic, declared in March 2020, is suspected to have greatly impacted Scotland’s accident and emergency (A&E) services. Stringent public health measures, including lockdowns, heightened pressures on A&E departments, but their long-term effects remain understudied. This study examines how the pandemic influenced A&E attendances over a broader time-frame.MethodsSecondary data from Public Health Scotland (2018–2022) on monthly A&E attendances was analysed, standardised per 1,000 population using census data. Choropleth maps visualised A&E attendances and wait times across health boards during key pandemic periods. A Poisson generalised linear model (GLM) assessed the influence of COVID restrictions, demographics, and service factors on attendance rates.ResultsA&E attendances dropped from 2018 to 2022, with NHS Lanarkshire (-32.7%) and NHS Borders (-27.9%) seeing the largest declines. Despite reduced attendances, the percentage of patients seen within four hours also dropped (-29.4% in NHS Lanarkshire). The Poisson GLM confirmed that COVID-19 restrictions influenced attendance rates with a lower incident rate (IRR: 0.89, 95% CI: 0.88–0.90) during lockdowns and an increased incident rate (IRR: 1.04, 95% CI: 1.03–1.05) during easing periods. Health board-level effects varied substantially.DiscussionCOVID-19 disrupted A&E services, causing fluctuating attendances and worsening wait times. Large health board-level variations suggest local policies, behaviours, and existing pressures significantly influenced outcomes. These findings highlight the need to address systemic issues alongside localised strategies for future resilience.
HepatoPredict accurately selects hepatocellular carcinoma patients for liver transplantation regardless of tumor heterogeneity
Authors: Andrade Rita , Perez-Rojas Judith , Gomes da Silva Sílvia , Miskinyte Migla , Quaresma Margarida C. , Frazão Laura P. , Peixoto Carolina , Cubells Almudena , Montalva Eva M. , Figueiredo António , Cipriano Augusta , Gonçalves-Reis Maria , Proença Daniela , Folgado André , Pereira-Leal José B. , Oliveira Rui Caetano , Pinto-Marques Hugo , Tralhão José Guilherme , Berenguer Marina , Cardoso Joana 
Published: December 2024

AbstractBackground/ObjectivesHepatocellular carcinoma (HCC) is a major cause of cancer-related deaths rising worldwide. This is leading to an increased demand for liver transplantation (LT), the most effective treatment for HCC in its initial stages. However, current patient selection criteria are limited in predicting recurrence and raise ethical concerns about equitable access to care. This study aims to enhance patient selection by refining the HepatoPredict (HP) tool, a machine learning-based model that combines molecular and clinical data to forecast LT outcomes.MethodsThe updated HP algorithm was trained on a two-center dataset and assessed against standard clinical criteria. Its prognostic performance was evaluated through accuracy metrics, with additional analyses considering tumor heterogeneity and potential sampling bias.ResultsHP outperformed all clinical criteria, particularly regarding negative predictive value, addressing critical limitations in existing selection strategies. It also demonstrated improved differentiation of recurrence-free and overall survival outcomes. Importantly, the prognostic accuracy of HP remained largely unaffected by intra-nodule and intra-patient heterogeneity, indicating its robustness even when biopsies were taken from smaller or non-dominant nodules.ConclusionsThese findings support the usage of HP as a valuable tool for optimizing LT candidate selection, promoting fair organ allocation, and enhancing patient outcomes through integrated analysis of molecular and clinical data.Simple SummaryLiver cancer is a leading cause of death, and liver transplants (LT) offer the best chance of survival for many patients. However, current methods to decide who should receive a transplant often fall short, leaving some patients without access to life-saving care. This research focuses on improving these decisions with HepatoPredict (HP). This new tool uses technology to combine tumor and patient data to predict how well someone will do after a transplant. HP was tested on a large group of patients and proved to be more accurate than current methods. It also performed well even when samples came from different parts of the tumor. These findings could help medical teams make fairer and more reliable transplant decisions, ultimately improving patient outcomes and advancing how liver cancer is managed in the medical community.
Integrative cross-omics analysis identifies DNA methylation signatures associated with bilateral hippocampal volume, asymmetry and atrophy rate in the general population
Authors: Liu Dan , Talevi Valentina , Tavares Juliana F. , Wang Ruiqi , Imtiaz Mohammed A , Melas Konstantinos , Teumer Alexander , Wittfeld Katharina , Hillary Robert F , Vojinovic Dina , Beekman Marian , Armstrong Nicola J , Estrada Santiago , Völzke Henry , Bülow Robin , Royle Natalie A. , Wardlaw Joanna M. , Wen Wei , Sachdev Perminder S. , Mather Karen A. , Slagboom P. Eline , Cox Simon R. , Grabe Hans Jörgen , Yang Qiong , Aziz N. Ahmad , Breteler Monique M.B. 
Published: December 2024

AbstractThe hippocampus exhibits volumetric differences between the left and right hemispheres (LHCV and RHCV) and asymmetry, yet the molecular mechanisms underlying these features remain unclear. In this study, we performed a meta-analysis of epigenome-wide association studies (EWAS) across six population-based cohorts (n=8,156; 53% women; mean age: 60.7 years) to identify blood-based methylation signatures associated with LHCV, RHCV, and hippocampal asymmetry. Integrative cross-omics analyses using individual-level genetic, methylation, and gene expression data (n > 2,624 participants from the Rhineland Study) revealed 15 CpG/DMR-gene expression pairs linked to LHCV and 18 pairs to RHCV, implicating pathways involved in neuronal differentiation and immune processes. Notably, baseline methylation at these loci predicted bilateral hippocampal atrophy rates, explaining over 10% of the variation. Four CpGs were consistently associated with hippocampal asymmetry cross-sectionally and longitudinally, exhibiting sex-specific differences. Additionally, adherence to healthy dietary patterns was associated with these methylation signatures, highlighting modifiable influences on hippocampal health and atrophy.
Integrating Ambient Mass Spectrometry Imaging and Spatial Transcriptomics on the Same Cancer Tissues to Identify Gene-Metabolite Correlations
Authors: Godfrey Trevor M. , Shanneik Yasmin , Zhang Wanqiu , Tran Thao , Verbeeck Nico , Patterson Nathan H. , Jackobs Faith E. , Nagi Chandandeep , Ramineni Maheshwari , Eberlin Livia S. 
Published: December 2024

AbstractThe combination of spatial metabolomics and spatial transcriptomics can reveal powerful connections between gene expression and metabolism in heterogeneous tissues, but section-to-section variability can convolute data integration. We present a novel method combining Desorption Electrospray Ionization Mass Spectrometry Imaging spatial metabolomics and spatial transcriptomics on the same tissue sections. We demonstrate this workflow on human breast and lung cancer tissues identifying correlations between metabolites and cancer-related RNA transcripts.
A quantum compatible classical continuum model explains mechanical responses of cell membranes and membrane crosslinkers
Authors: Kim Jichul 
Published: December 2024

AbstractBoth classical mechanics and quantum mechanics explain the Brownian motion. However, it is unclear whether they are compatible with each other as the physical and mathematical identity of the wavefunction in quantum mechanics has been elusive. Here, a continuum theory using grammars in classical mechanics modeling but compatible with the quantum wavefunction is introduced. The theory explains the confined Brownian motion of cell membrane inclusions interacting with extracellular matrices or cytoskeletons via elastic molecular crosslinkers. This crosslinker theory is combined into the Canham-Helfrich-Evans model for fluid membranes. Calculations through the provision of a finite element method for the combined theory reproduced measured data from adhesion molecular machineries and cell membranes. Overall, by providing physical and mathematical interpretations of the quantum wavefunction, the presented theoretical model provides improved capabilities for the realistic simulation of classical and quantum biomechanical aspects of cell membranes and membrane linker proteins.
Amyloid forming human lysozyme intermediates are stabilised by non-native amide-π interactions
Authors: Ahn Minkoo , Streit Julian O. , Waudby Christopher A. , Włodarski Tomasz , Figueiredo Angelo Miguel , Christodoulou John , Kumita Janet R. 
Published: December 2024

AbstractMutational variants of human lysozyme cause a rare but fatal hereditary form of systemic amyloidosis by populating an intermediate state that self-assembles into amyloid fibrils. Despite its significance in lysozyme amyloidosis, the intermediate state has been recalcitrant to detailed structural investigation as it is only transiently and sparsely populated. Here, we investigated the intermediate state of a mutational variant of human lysozyme (I59T) using CEST and CPMG RD NMR at low pH.15N CEST profiles probed the thermal unfolding of the native state into the denatured ensemble and revealed an additional state distinct from the two major states. Global fitting of15N CEST and CPMG data provided kinetic and thermodynamic parameters for the exchange between all three states, characterising the intermediate state populated at 0.6%.1H CEST data also confirmed the presence of the intermediate state displaying unusually high or low1HNchemical shifts. To further investigate the structural details of the intermediate state we used molecular dynamics (MD) simulations, which recapitulated the experimentally observed folding pathway and free energy landscape. A high-energy intermediate state with a locally disordered β-domain and C-helix was observed, revealing non-native hydrogen bonding and amide-π interactions. These interactions account for the anomalous1H chemical shifts and likely stabilise the transient intermediate state structure. Together, our NMR and MD data provide the first direct structural information on the intermediate state, offering insights into targeting lysozyme amyloidosis.