bluuebunny/crossref_metadata_2025_split huggingface dataset:
Impact of Scabies on Quality of Life and Recent Advances in Management: A Systematic Review
Authors: Kumari Sakshi , Srinivas Swathi , Siddiqua Zainab , Qazi Muhammad Saeed , Sheikh Mahin , Rath Shree , Khan Maham , Jawaid Muhammad Daim , Tummala Nayanika , Mal Madho 
Published: November 2024

AbstractIntroductionScabies are a highly transmittable disease of the skin. It is caused by a specific mite named Sarcoptes scabiei. Individuals who are infected with scabies have a miserable life, and their quality of life is poor. It impacts the quality of life by causing physical discomfort due to itching. Not only does it lead to the mental distress of a diseased individual, but it also leads to social isolation due to the stigma associated with this condition. This systematic review highlights the profound effect of scabies on the lives of affected individuals and the recent breakthroughs in the management of scabies.PurposeThe purpose of this article is to shed light on the impact of scabies on the quality of life. We also discussed the advancements in the management of this disease, which impacts life physically and socially.MethodWe included randomized controlled trials, clinical trials, and observational studies. Studies with full-text access were included. Case reports, letters, and systematic/narrative reviews were excluded from the search. 180 records were screened up to March 2024, of which 129 articles were from PubMed and 51 from Google Scholar. 22 articles were thoroughly screened by two different reviewers independently and included in the review. Studies were carried out with no restrictions on age or sex, including the pediatric and adult populations.ConclusionFindings indicate a significant correlation between scabies and poor quality of life. Scabies most commonly affect children of lower socioeconomic status and in resource-limited settings. Scabies can lead to severe complications such as rheumatic heart disease, kidney diseases, and a variety of secondary bacterial infections; therefore, advances in treatment strategies are needed. Currently, permethrin and ivermectin have been used for treatment. Moxidectin, a new drug, is undergoing clinical trials to replace permethrin in regions with high resistance. The interventions need to be patient-centered, and new drugs need to be developed that have anti-parasitic actions and also lead to the prevention of secondary bacterial infections.
Computational modeling enables individual assessment of postprandial glucose and insulin responses after bariatric surgery
Authors: Poyraz Onur , Heinonen Sini , John S. T. , Saarinen Tuure , Juuti Anne , Marttinen Pekka , Pietiläinen Kirsi H. 
Published: November 2024

AbstractBariatric surgery enhances glucose metabolism, yet the detailed postprandial joint glucose and insulin responses, variability in individual outcomes and differences in surgical approaches remain poorly understood. To address this, we used hierarchical multi-output Gaussian process (HMOGP) regression to model the individual postprandial glucose and insulin responses and to estimate the average response curves from individual data. Our study included 44 patients with obesity who underwent either Roux-en-Y gastric bypass (RYGB) (n=24) or One-Anastomosis gastric bypass (OAGB) (n=20) surgery. The patients were followed up at 6th and 12th months after the operation, during which they underwent an oral glucose tolerance test (OGTT) and a mixed meal test (MMT). A marked reduction in glycaemia, an earlier glucose peaking time and increase and sharpening in the postprandial glucose and insulin responses were evident in both metabolic tests after the operations. MMT resulted in higher postprandial glucose and insulin peaks compared with OGTT and higher glucose and insulin responses were observed after RYGB compared with OAGB. Women and persons without T2DM had a healthier postprandial response before and after surgery. Computational modeling with HMOGP regression can be used to, in detail, predict the combined responses of patient cohorts to ingested glucose or a mixed meal, and help in assessing individual metabolic improvement after weight loss. This can lead to new knowledge in personalized metabolic interventions.
Bayesian Mendelian Randomization Analysis for Latent Exposures Leveraging GWAS Summary Statistics for Traits Co-Regulated by the Exposures
Authors: Yu Yue , Lakkis Andrew , Zhao Bingxin , Jin Jin 
Published: November 2024

AbstractMendelian Randomization analysis is a popular method to infer causal relationships between exposures and outcomes, utilizing data from genome-wide association studies (GWAS) to overcome limitations of observational research by treating genetic variants as instrumental variables. This study focuses on a specific problem setting, where causal signals may exist among a series of correlated traits, but the exposures of interest, such as biological functions or lower-dimensional latent factors that regulate the observable traits, are not directly observable. We propose a Bayesian Mendelian randomization analysis framework that allows joint analysis of the causal effects of multiple latent exposures on a disease outcome leveraging GWAS summary-level association statistics for traits co-regulated by the exposures. We conduct simulation studies to show the validity and superiority of the method in terms of type I error control and power due to a more flexible modeling framework and a more stable algorithm compared to an alternative approach and traditional single- and multi-exposure analysis approaches not specifically designed for the problem. We have also applied the method to reveal evidence of the causal effects of psychiatric factors, including compulsive, psychotic, neurodevelopmental, and internalizing factors, on neurodegenerative, autoimmune, digestive, and cardiometabolic diseases.
Demographic Representation of a Decentralized Long COVID Trial: A Comparison with the 2023 National Health Interview Survey
Authors: Sawano Mitsuaki , Warner Frederick , Henriquez Yashira , Bhattacharjee Bornali , Iwasaki Akiko , Krumholz Harlan M. 
Published: November 2024

ABSTRACTImportanceClinical trials can be a chokepoint to progress in medicine. They are commonly expensive, slow, and not participant-centric. Ensuring patient-centric, equitable trials with diverse demographic representation is essential for developing generalizable treatments and reducing healthcare disparities. Thus, there is an urgent need to test new ways of conducting clinical trials. The PAX LC trial is a novel Phase II decentralized, digital, and participant-centric double-blind randomized trial of Paxlovid for long COVID and is a test case for a new approach. There is a need to determine how well the trial enrolled a representative population with long COVID.ObjectiveTo compare the demographic characteristics of participants in the PAX LC trial with those reported in the National Health Interview Survey (NHIS) to assess how well the decentralized recruitment reflects the broader population in the US with long COVID.DesignDescriptive analysis comparing 2 databases: a Phase 2, 1:1 randomized, double-blind, superiority, placebo-controlled trial conducted in community-dwelling adults with long COVID, and a nationwide observational cross-sectional survey.SettingDecentralized clinical trial with participants recruited from 48 contiguous states in the US. The NHIS survey participants were recruited from all 50 states.Participants100 highly symptomatic adults with long COVID in the PAX LC trial, compared with 575 from NHIS.Intervention(s) or Exposure(s)None.Main Outcome(s) and Measure(s)Percentage distribution by age group, gender, race and ethnicity, and region for each group.ResultsPAX LC included 100 participants and NHIS 575, with PAX LC participants being younger (median 42 vs. 53 years). There was an equal proportion of women. Non-Hispanic White representation was higher in PAX LC (89% vs. 61% in NHIS), while the Hispanic and Non-Hispanic Black groups were underrepresented (5% vs. 20% and 1% vs. 12%, respectively). More PAX LC participants were from the Northeast (51% vs. 15%) due to earlier enrollment in this region.Conclusions and RelevanceThe PAX LC trial highlights the potential of decentralized trials to achieve geographic diversity and balanced age and gender representation. However, to maximize the benefits of this approach, further efforts are warranted to improve racial and ethnic diversity.Trial RegistrationNCT05668091.
Long-term Outcomes of Poor-grade Aneurysmal Subarachnoid Haemorrhage: A Multicentre Observational Cohort Study
Authors: Wang Bangyue , Li Tianxing , Zhao Yan , Zhou Tian , Wang Ruyi , Li Yang , An Xiuhu , Hao Jiheng , Wang Kaijie , Yang Xinyu 
Published: November 2024

AbstractBACKGROUNDDespite advancements in neurosurgery and intensive care that reduce overall mortality, poor-grade aneurysmal subarachnoid haemorrhage (aSAH) (World Federation of Neurosurgical Societies [WFNS] grades IV and V) remains a significant clinical challenge and is associated with persistently high mortality rates. The aim of this study was to assess the long-term outcomes of poor-grade aSAH and to identify factors influencing patient prognosis to guide clinical management.METHODSA multicentre, observational cohort study was conducted across 12 regional centres in northern China. The study included patients with poor-grade aSAH admitted from 2017 to 2020. The baseline data included demographics, clinical presentation, aneurysm characteristics, and treatment modalities. Outcome data, including survival status, mortality along with its associated causes and timing, and modified Rankin scale (mRS) scores, were collected prospectively at the last medical follow-up. Changes in case fatality over time were quantified with weighted linear regression. Survival analysis was performed to estimate survival and hazard ratios for death. Binary logistic regression was performed to estimate the odds ratio for dependency (mRS=3-5).RESULTSAmong the 1,589 enrolled patients, 1,339 were successfully followed, with an average follow-up of 26.37 months. Among them, 61.5% (824/1,339) were dependent or died. The overall mortality rate was 51% (684/1,339), and 21.3% (140/655) of the survivors were dependent. The risk factors for mortality included age ≥65 years, previous history of stroke, and WFNS grade V. Additionally, conservative treatment and endovascular treatment were identified as risk factors and protective factors, respectively, compared with surgical treatment. WFNS grade V and middle cerebral artery aneurysms are independent risk factors for dependency.CONCLUSIONSAlthough there has been a downward trend in recent years, the long-term mortality rate for poor-grade aSAH has remained significantly high at 51%, with 21.3% of survivors being dependent. Active aneurysm treatment, to the extent possible, is crucial for improving the prognosis of these patients.
Structured and random interactions interplay in complex ecosystems dynamics
Authors: Martínez Juan Giral , Barbier Matthieu , De Monte Silvia 
Published: November 2024

AbstractMinimal models for complex ecosystems often assume random interactions, whose statistics suffice to predict dynamical and macroecological patterns. However, interaction networks commonly possess large-scale structures, such as hierarchies or functional groups. Here, we ask how conclusions from random interaction models are altered by the presence of such large-scale network structures. We consider a simple superposition of structured and random interactions in a classic population dynamics model, and study macroscopic observables, abundance distributions and dynamical regimes. Randomness and structure combine in a surprisingly yet deceptively straightforward way: contributions from each component to the patterns are largely independent, and yet their interplay has non-trivial consequences, notably out of equilibrium. We conclude that whether interaction structure matters depends on the pattern: conclusions from randomly interacting models are less robust when considering static patterns of species presence and abundance, and more robust in the dynamical nature of their ecological regimes.
Aspergillus latus: a cryptic causative agent of aspergillosis emerging in Japan
Authors: Shibata Saho , Uchida Momotaka , Ban Sayaka , Kamei Katsuhiko , Watanabe Akira , Yaguchi Takashi , Hubka Vit , Takahashi Hiroki 
Published: November 2024

AbstractAllodiploid hybrid species,Aspergillus latus, belonging to sectionNidulantes, is a hybrid ofA. spinulosporusand unknown species closely related toA. quadrilineatusandA. subltus. This hybrid has often been misidentified as the species in sectionNidulantes, such asA. nidulans,A. spinulosporus,A. sublatus, or other cryptic species. A. latushas not been reported in Japan as well as Asia so far. In this study, we screened 23 clinical strains identified asA. spinulosporusisolated in Japan from 2012 to 2023 and found sevenA. latusstrains. To characterize theA. latusstrains, we conducted comprehensive phenotyping including morphological observation, whole genome sequences and phylogenetic analysis based on calmodulin (CaM) gene. In addition, we conducted antifungal susceptibility testing forA. latusstrains. As a result, the morphological characters ofA. latuswere more similar to those ofA. spinulosporuscompared toA. sublatus. However, the ascospore ofA. latusdiffered from that ofA. spinulosporus.A. latusphylogenetically clustered withA. spinulosporusandA. sublatus. Furthermore,A. latusstrains showed reduced susceptibility to caspofungin and amphotericin B compared toA. spinulosporus, while they were susceptible to azoles. Our results suggest thatA. latushas been a causative pathogen of aspergillosis in Japan since 2013.
Identification of the differences in molecular networks between idiopathic pulmonary fibrosis and lung squamous cell carcinoma using machine learning
Authors: Nojima Yosui , Mizuguchi Kenji 
Published: November 2024

AbstractIdiopathic pulmonary fibrosis (IPF), a form of idiopathic interstitial pneumonia, is an independent risk factor for lung cancer. The prognosis of IPF patients with lung cancer is poorer than that of IPF patients without lung cancer, and preventive measures for lung cancer remain elusive in patients with IPF. To mitigate lung cancer onset in patients with IPF, understanding the distinct mechanisms that induce both diseases is crucial. We developed highly accurate machine learning (ML) models to classify patients with IPF and lung cancer using public RNA sequencing data. To construct the ML models, the random restart technique was applied to five algorithms, namely,k-nearest neighbors, support vector machines (SVM) with radial basis function kernel, SVM with linear kernel, eXtreme gradient boosting, and random forest. To identify differentially expressed genes between IPF and lung cancer, feature importance was calculated in the classification models. Furthermore, we detected somatic mutations impacting gene expression using lung cancer data. The ML models identifiedVCX2,TMPRSS11B,PRUNE2,PRG4,PZP,SCARA5,DES,HPSE2,HOXD11,S100A7A, andPLA2G2A11as differentially expressed genes. Somatic mutations were detected in four transcription factors,BHLHE40,MYC,STAT1, andE2F4, that regulate the expression of the abovementioned 11 genes. Furthermore, a molecular network was discovered, comprising the four transcription factors and 11 downstream genes. The newly identified molecular network enhances our understanding of the distinct mechanisms underlying IPF and lung cancer onset, providing new insights into the prevention of lung cancer complications in patients with IPF.
DockFormer: Efficient Multi-Modal Receptor-Ligand Interaction Prediction using Pair Transformer
Authors: Shor Ben , Schneidman-Duhovny Dina 
Published: November 2024

AbstractProtein-small molecule interactions, or receptor-ligand interactions, are essential for understanding biological processes and advancing drug design. In this paper, we introduce DockFormer, a method that leverages multi-modal learning to predict both the binding affinity and structure of these interactions. DockFormer employs fully flexible docking, where no part of the receptor remains rigid, by adapting the AlphaFold2 architecture. Instead of relying on protein sequences and Multiple Sequence Alignments, DockFormer uses predicted receptor structures as input. This modification enables the model to concentrate on ligand docking prediction rather than protein folding, while preserving full receptor flexibility. The streamlined design also reduces the model size to just 8 layers, compared to AlphaFold2’s 48 layers, greatly accelerating the inference process and making it more efficient for large-scale screening. Benchmark tests on the PoseBusters dataset demonstrated a 27% success rate, while on an affinity benchmark, DockFormer achieved a Pearson correlation of 0.91. This optimized architecture offers a valuable tool for rapid and accurate virtual screening in drug discovery.
Single-cell metabolic oscillations are pervasive and may alleviate a proteome constraint
Authors: Wongprommoon Arin , Muñoz Alán F. , Oyarzún Diego A. , Swain Peter S. 
Published: November 2024

AbstractBiological rhythms not only coordinate cellular activity with external signals, but may also enable internal coordination. The metabolic cycle in budding yeast is perhaps the most well-studied example. Historically researchers have investigated this cycle in populations growing in chemostats, but more recently time-lapse microscopy has revealed single-cell oscillations in the redox state of enzyme cofactors and in ATP levels. How to relate the results of these two types of assays is however unclear. Here we report single-cell rhythms too in intracellular pH and show that oscillations in the redox state of flavin molecules occur in auxotrophic and prototrophic strains, in nutrients favouring respiration or fermentation, and in deletion mutants for which oscillations in chemostats are either unobservable or disrupted. To explain the pervasiveness of these rhythms, we postulate that cells generate oscillations to alleviate a proteome constraint – amino acids cells use for one class of enzymes are unavailable for others. Using flux balance analysis with an enzyme-constrained genome-scale metabolic model, we show that, with a finite proteome, sequential synthesis of biomass components typically generates a shorter doubling time than synthesising components in parallel. Our results suggest that the metabolic cycle drives growth and is potentially widespread because all cells grow within a proteome constraint.
De novoassembled databases enable species-specific protein-based stable isotope probing of microbiomes without prior knowledge of the community composition
Authors: Klaes Simon , White Christian , Alvarez-Cohen Lisa , Adrian Lorenz , Ding Chang 
Published: November 2024

AbstractBackgroundProtein-based stable isotope probing (Protein-SIP) is a powerful approach that can directly link individual taxa to activity and substrate assimilation, elucidating metabolic pathways and trophic relationships within microbiomes. In Protein-SIP, peptides and corresponding taxa are identified by database matches. Thus, database quality is crucial for accurate Protein-SIP analyses. For samples with unknown community composition, Protein-SIP usually employs broad-spectrum or metagenome-derived databases. However, broad-spectrum databases require advanced post-processing strategies and metagenome-derived databases can be costly to acquire. Further, both can inflate database size, negatively impacting peptide identification.ResultsHere, an approach in which we usede novoassembled databases for Protein-SIP on microbiomes with unknown community compositions is introduced. This approach enables databases to be directly generated from the mass spectrometry raw data usingde novopeptide sequencing. We then use the mass spectrometric data from labeled cultures to quantify isotope incorporation into specific peptides. We benchmark our approach against the canonical approach in which a sample-matching database is generated by DNA sequencing on three different datasets: 1) a proteome analysis from a defined microbial community containing13C-labeledE. colicells, 2) time-course data of an anammox-dominated continuous reactor after feeding with13C-labeled bicarbonate, and 3) a model of the human distal gut simulating a high-protein and high-fiber diet cultivated in either2H2O or H218O. Our results show thatde novodatabase assembly is applicable to different isotopes and detects similar amounts of labeled peptides compared to sample-matching databases. Furthermore, we show that peptide-centric Protein-SIP allows species-specific resolution, enabling the assessment of activity related to individual biological processes. Finally, we provide access to our modular Python pipeline to assist thede novoassembly of databases and subsequent peptide-centric Protein-SIP data analysis (https://git.ufz.de/meb/denovo-sip).ConclusionsDe novoassembled databases enable species-specific Protein-SIP of microbiomes without prior knowledge of the community composition.
High-resolution 3-dimensional micro-CT imaging of the nucleus pulposus using a novel contrast agent
Authors: Buckles Madison M , Warda Nada H. , Moncher Jacob C. , Ansari Mohammad Yunus 
Published: November 2024

AbstractObjectiveThe nucleus pulpous (NP) in the intervertebral disc (IVD) is the first structure to exhibit degenerative changes during IVD degeneration (IDD). Currently, micro-computed tomography (micro-CT) imaging of the NP is a limiting factor in detecting IDD at an early stage. In this study, we used potassium iodide (KI) as a contrast agent to stain the NP in the IVDs of the tails and spines of mice and rats and imaged them with a micro-CT scanner.MethodsWe collected tails and spines from 12-week-old mice and rats and stained them with KI followed by micro-CT imaging. To induce IDD, we performed caudal disc needle puncture surgery (NPS) in age and sex-matched mice (n=5) and stained the tail with KI for imaging with micro-CT to study disc degeneration.ResultsKI successfully stained and helped visualize the 3D structure of the NP, with X-ray attenuation properties comparable to bone. Contrast staining with KI enabled accurate and reproducible quantification of disc height and NP volume. The cross-sectional micro-CT images of NPS discs were indistinguishable from the histological findings of the same sample and showed similar degenerative changes in the NP. Additionally, we estimated that up to 15 sagittal sections, each 5μm thick with 75μm spacing, would be needed to fully assess disc degeneration.ConclusionThis study demonstrated that KI can be used to positively stain NP in the intact tail or spine and provide qualitative and quantitative data without any adverse effect on the histological processing of the samples.