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Dynamic lysine acetylation and succinylation of platelet proteins regulates platelet storage lesion: mechanistic insights from multi-omics.

OBJECTIVES: Platelet storage lesion (PSL) severely impairs platelet function during storage, presenting a major hurdle in transfusion medicine; however, the dynamic interplay between global proteomic changes and post-translational modifications (PTMs) underlying these functional deteriorations remains insufficiently characterized. Here, we report the first comprehensive multi-omics analysis integrating global proteomics, acetylomics, and succinylomics to dissect the molecular dynamics during platelet storage. METHODS: We performed quantification of global proteomics, acetylome and succinylome based on TMT-labeled LC-MS/MS analysis, combined with antibody-affinity enrichment and purification. Dynamic molecular changes and functional transformation of platelet were also characterized under proper conditions stored for 1, 3, 5, 7 days, respectively. RESULTS: We systematically characterized 3,609 proteins, 1,308 acetylation sites, and 1,947 succinylation sites across multiple storage time points (D1, D3, D5, D7). We distinct temporal patterns of post-translational modifications, with succinylation showing more extensive coverage than acetylation in platelets. Pathway enrichment analysis revealed extensive metabolic reprogramming involving complement activation, energy metabolism, and cellular detoxification processes. The identification of specific motif patterns provided mechanistic insights into the functional specificity of these modifications. Random forest machine learning identified 20 core regulatory proteins representing critical nodes in PSL development. Furthermore, we employed real - time quantitative polymerase chain reaction (RT - QPCR) to measure the expression levels of key genes related to platelet function and PTM - associated pathways. CONCLUSION: By mapping the interplay between proteomic abundance shifts and PTM dynamics, this study provides a multidimensional understanding of PSL, establishing a foundational framework for optimizing storage protocols and enhancing transfusion safety.

Blood Platelets

Toward real-time quantification of driving risks: a systematic review and research agenda of risk field theory.

In complex traffic systems, driving risk often evolves in a continuous and progressive manner prior to crash occurrence. How to effectively represent and analyze such latent risk states remains a central challenge in traffic safety research. In recent years, risk field-based approaches have introduced spatial and spatiotemporal continuous modeling paradigms, providing new perspectives for characterizing the distribution of traffic risk and its dynamic evolution. Motivated by the rapid growth of this research area and the lack of a systematic synthesis, this paper presents a comprehensive review of studies applying risk field theory to driving safety and traffic risk analysis. Following the PRISMA guidelines, relevant literature was collected through multi-database searches and analyzed using a combination of bibliometric analysis and qualitative review. The review systematically summarizes the theoretical foundations, modeling elements, data sources, analytical methods, and application domains of risk field-related research. Particular attention is given to studies that conceptualize traffic risk as a continuous field, complemented by a broader review of traffic risk factor literature to identify key elements and analytical dimensions involved in risk field modeling. On this basis, the paper synthesizes research progress in major application areas, including traffic safety state representation, driving behavior analysis, traffic conflict assessment, and autonomous driving and human-machine cooperative systems. Differences and commonalities among existing studies are compared in terms of modeling strategies, data support, and application scenarios. Through this systematic review, the paper clarifies the main research themes and methodological trends of risk field-based studies, providing a structured framework for understanding the evolution and application of this approach and offering methodological insights for risk perception modeling and safety-oriented decision support in intelligent transportation systems (ITS).

Humans

Natural products alleviate exercise-induced fatigue by modulating gut microbiota: a systematic review.

BACKGROUND: Exercise-induced fatigue critically impairs athletic performance and training quality. The gut microbiota, as a key regulator of the "gut-muscle axis," has emerged as a promising anti-fatigue target. Natural products - owing to their diverse sources, structural complexity, and favorable safety profiles - have attracted growing research interest. However, a systematic synthesis comparing their anti-fatigue effects via gut microbiota modulation across different sources is lacking. SCOPE AND APPROACH: We systematically searched PubMed, Web of Science, the Cochrane Library, and CNKI for original studies that administered natural products and concurrently assessed gut microbiota changes and anti-fatigue outcomes. Twenty-six studies (25 animal experiments and 1 human trial) were included and categorized into seven groups by source and chemical characteristics. A descriptive systematic review was conducted to identify common mechanisms and source-specific differentiations. KEY FINDINGS AND CONCLUSIONS: The enrichment of short-chain fatty acid (SCFA)-producing bacteria and the activation of the SCFA-AMPK/PGC-1α axis were shared core events across all product categories. However, source-dependent mechanistic divergences emerged: polysaccharides acted primarily as fermentable substrates with an optimal dose window; polyphenols and saponins exerted dual modulation on both microbiota and host signaling pathways; compound extracts achieved systemic synergy through functional complementation; marine- and animal-derived products exhibited unique targeting profiles and rapid action. Intestinal barrier maintenance and brain-gut axis regulation further extended the anti-fatigue repertoire. Collectively, natural products possess a solid mechanistic basis for alleviating exercise-induced fatigue via gut microbiota remodeling. The differentiated characteristics of these methods in targeting precision and pathway engagement provide a theoretical foundation for designing precision intervention strategies tailored to specific fatigue contexts.

Humans

Migration intentions among nigerian neurosurgeons: a national survey of workforce retention.

Physician emigration from low- and middle-income countries creates critical workforce shortages. This study explored factors influencing migration intentions among Nigerian neurosurgeons and trainees. We conducted an anonymized survey of consultant neurosurgeons, fellows, and residents practicing in Nigeria. Invitations were sent by email and professional messaging platforms, and snowball sampling was used to increase participation. The survey included quantitative and open-ended questions on demographics, income, migration plans, and retention factors. Seventy-nine respondents participated (61.5 % consultants; 93.7 % male; median age: 44 years). Nearly all practiced general neurosurgery (97.3 %), and many also performed trauma (65.3 %) and spine (61.3 %) neurosurgery. Most (85.7 %) reported that their earnings were insufficient to support their families. Nearly 40 % were considering emigration, most often citing financial pressures (88.5 %) and poor working conditions (63.5 %) as push factors. By contrast, personal or family ties (63.0 %) and relocation costs (45.2 %) were cited as reasons to stay. Respondents identified higher salaries (58.1 %) and greater investment in the health sector (51.4 %) as key measures to improve retention. In univariable analyses, younger age, income insufficiency, income dissatisfaction, and feeling undervalued at work were associated with migration intention. Financial insecurity emerged as the dominant driver of migration intentions among Nigerian neurosurgeons. In addition to salary increases, sustained investment in healthcare infrastructure and workforce support is essential to improve retention. International partnerships may complement these efforts by building neurosurgical capacity and mitigating brain drain.

Humans

A narrative review of what cohorts have taught us and how they have laid the foundation for much of our understanding of type 2 diabetes.

This narrative review provides a historical perspective on how observational research on type 2 diabetes has been developed and consolidated over the last 50 years and how well-designed cohort studies will provide us with knowledge for research and practice in the future and aid guideline development. We have included data from a large number of cohorts from every continent that have been used to study the development and/or progression of type 2 diabetes, including cohorts that are general population-based, disease-based, intervention-based and registry-based. We have structured the results from the past 50 years based on the following themes: diagnosis and screening, complications, risk factors and pathophysiology. We also discuss the strengths and weaknesses of observational research when compared with other research designs. Finally, we discuss the emerging and future directions for type 2 diabetes research using cohorts, which include novel developments, such as artificial intelligence, precision health and the exposome. We conclude that cohort research has significantly advanced our understanding of type 2 diabetes and aided guideline development, and complements experimental work, such as human randomised controlled trials and animal studies. Both approaches are essential and complementary in our pursuit to provide a more comprehensive understanding of the development and progression of type 2 diabetes, and to change dogma, practice and policies for better outcomes.

Humans

Phase 1 Study Evaluating Gefurulimab Pharmacokinetics and Safety Following Delivery Via Autoinjector or Prefilled Syringe With Needle Safety Device in Healthy Adults.

PURPOSE: Gefurulimab, a novel dual-binding nanobody targeting complement component 5 (C5), is in clinical development for anti-acetylcholine receptor antibody-positive generalized myasthenia gravis. Gefurulimab has a low molecular weight, enabling subcutaneous (SC) self-administration by autoinjector (AI) or prefilled syringe with needle safety device (PFS-SD). We compared gefurulimab pharmacokinetic (PK) exposure and safety in healthy adults following a single SC dose administered by AI versus PFS-SD. METHODS: In this phase 1, open-label, randomized, parallel-group study (NCT06208488), healthy participants aged 18 to 65 years were stratified by weight and randomized equally to 1 of 6 combination groups of device and injection site (abdomen/thigh/upper arm). Participants received a single SC dose of gefurulimab on day 1 and were assessed throughout the 92-day evaluation period. Primary endpoints were PK parameters for each device: maximum observed concentration (Cmax) and area under the serum concentration-time curve (AUCinf, AUClast). PK across injection sites, pharmacodynamics, safety, immunogenicity, and device performance were also assessed. FINDINGS: Overall, 175 participants were randomized: AI (n = 87), PFS-SD (n = 88). Geometric least squares mean ratios (90% CI) comparing AI/PFS-SD for Cmax, AUCinf, and AUClast were 97.6% (94.5-100.8), 99.6% (96.1-103.3), and 98.8% (95.2‒102.6), respectively. Secondary analyses found no meaningful differences in PK parameters across injection sites. Serum-free C5 concentrations over time, treatment-emergent adverse event (TEAE) profiles, and antidrug antibody responses were similar between cohorts. Most TEAEs were mild; none led to study discontinuation. IMPLICATIONS: SC administration of gefurulimab by AI and PFS-SD was well tolerated with comparable exposure, meeting bioequivalence criteria.

Humans

Factors associated with successful integration of pharmacists into residential aged care teams: A qualitative study.

BACKGROUND: Australia's Aged Care Onsite Pharmacist program aims to support quality use of medicines in residential aged care homes. This is a novel role introduced into existing teams in a complex environment. Factors associated with successful integration since implementation are currently unknown. AIM: This study aims to explore the perspectives of pharmacists and other stakeholders within aged care homes regarding successful integration of the novel aged care pharmacist service into healthcare teams. METHODS: A qualitative approach, using interpretive descriptive methodology, was used to explore perspectives. Semi-structured focus groups and interviews with pharmacists, nursing and care staff, allied health professionals, general practitioners, residents, and family members were undertaken. Data were collected via Zoom™, audio- and video-recorded, and transcribed verbatim. Two researchers undertook inductive thematic analysis to identify key themes. RESULTS: 30 participants across focus groups, focus-group interviews, interviews, and member-checking processes contributed. An overarching theme of proactivity and showing a genuine interest in others underpinned three key themes. Theme 1: Pharmacists needed to be seen, through physical presence and availability, as well as developing a distinct identity. Theme 2: Pharmacists needed to build trust, through collaboration in real time and demonstrating value. Theme 3: Pharmacists needed to develop an understanding of the aged care home environment, including social and contextual norms, as well as procedures, routines and roles. DISCUSSION: This research complements existing understandings of interprofessional collaboration and teamwork amongst healthcare professionals. Themes were interlinked; we used a sensitising framework, social cognitive theory, to present and explain the findings and interactions that can support pharmacist integration into existing teams. Aged care services should structure onboarding to prioritise early visibility, clarify roles and organisational needs, and foster in-person collaboration. Pharmacists should demonstrate proactivity and an authentic interest in all staff, residents and families.

Humans

Meta-PseU: A meta-classifier for robust prediction of RNA pseudouridine modification sites from long sequences.

BACKGROUND AND OBJECTIVES: Pseudouridine (Ψ) represents one of the most abundant and conserved RNA modifications. Ψ provides an additional hydrogen-bond donor that enhances RNA structural stability and modulates translation. It participates in diverse biological processes, including RNA-protein interactions, splicing, translational control, and stress responses. Aberrant pseudouridylation is implicated in cancer, neurodegenerative disorders, and autoimmune diseases. Despite its biological importance, experimental identification of Ψ sites remains time-consuming and costly, limiting the feasibility of transcriptome-wide profiling. Computational approaches have therefore become essential complements to experimental techniques. However, state-of-the-art machine-learning and deep-learning predictors often suffer from limited generalizability due to small training datasets. To overcome these issues, we aim at constructing new long-sequence datasets and developing a novel Ψ site predictor. METHODS: New long-sequence datasets were constructed as benchmarks for RNA Ψ-site prediction. The Ψ modification sites in RMBase 3.0 were mapped to the reference genomes across three species of human, mouse, and yeast, and the RNA sequences with a length of 201 were generated by extending the upstream and downstream from the mapped, central sites. To eliminate sequence redundancy, the sequences were clustered using CD-HIT with a 70% sequence identity threshold. We developed Meta-PseU, a logistic regression-based meta-classifier that considered 118 machine learning and deep learning classifiers. The datasets and programs are freely accessible at https://github.com/kuratahiroyuki/MetaPseU. RESULTS: By optimizing model configuration, we proposed the Meta-PseU model stacking 32 machine learning and deep learning classifiers out of 118 classifiers. Meta-PseU substantially improved model generalizability, overcoming a key limitation of existing approaches. It greatly outperformed state-of-the-art predictors and achieved increasing accuracy with increasing sequence length. CONCLUSIONS: Long-sequence datasets were newly constructed as benchmarks for RNA Ψ-site prediction. Meta-PseU offers a new framework for robust Ψ-site identification by using long sequences.

Pseudouridine

A Conserved 3'UTR Stem-loop Directs UPF1/eIF4AIII-Dependent Regulation of GABARAPL1 mRNA.

RNA-binding proteins (RBP) interact with mRNA untranslated regions containing cis-regulatory elements to govern mRNA localization, stability, and translational efficiency. Among these trans-regulatory factors, RNA helicase UPF1 is a central factor which play a role in multiple mRNA decay pathways, including nonsense-mediated mRNA decay (NMD). NMD is triggered when an exon-junction complex (EJC) is located downstream of a premature termination codon. However, in some cases, NMD can be activated in an EJC-independent manner through mechanisms involving the 3'UTR. In the present study, we focused on the GABARAPL1 3'UTR, as previous studies had shown that this region plays a key role in NMD targeting, although the underlying molecular mechanism had not yet been elucidated. Unlike canonical NMD targets such as SC35, we found that the chemical inhibition of eIF4AIII helicase activity did not affect GABARAPL1 transcript levels, indicating that this transcript is regulated through its 3'UTR via an EJC-independent mechanism. We therefore investigated the potential presence of cis-regulatory element within the 3'UTR of GABARAPL1 which can regulate mRNA and protein levels in a UPF1-dependent manner. Furthermore, we identified a conserved RNA region spanning nucleotides 364-421 involved in GABARAPL1 targeting and used biochemical analysis to demonstrate the direct binding of UPF1 and eIF4AIII to this RNA region, to analyse its secondary structure in solution, and to map the protein-binding sites. By complementing these approaches with molecular modelling, we showed that this stem-loop adopts a stable global fold but a local flexibility and dynamic behaviour properties. Together, our results support the role of UPF1 and eIF4AIII as specific regulators of GABARAPL1 transcript and reveal a novel RNA regulatory element within its 3'UTR, which provides a completely unexpected binding site for these factors.

3' Untranslated Regions

From prediction to mechanism: Explainable AI uncovers plasma and CSF proteomic signatures of Alzheimer's disease.

Alzheimer's disease (AD) plasma and cerebrospinal fluid (CSF) proteomics can distinguish AD from cognitively normal controls, but the generalizability of machine learning performance and the recurrence of biological signals across datasets require cautious interpretation. We developed an explainable artificial intelligence framework spanning two fluids and four ADNI proteomic datasets, covering 2082 modality specific samples, all analysed internally within ADNI. Phase 1 analysed plasma using a 119 analyte NULISA and targeted UPENN panel (n&#xa0;=&#xa0;727; 216&#xa0;CE, 511 controls). Phase 2 extended the analysis to CSF using SOMAscan7k, TMT-MS and targeted SET2, with Elecsys A&#x3b2;42, A&#x3b2;40, total tau and p-tau181 as anchor biomarkers. Only SOMAscan was subject-independent relative to Phase 1 plasma; TMT-MS and SET2 overlapped with Phase 1 for 96.0% and 97.7% of subjects and therefore are not independent replication cohorts. Under subject-level splits with fold internal preprocessing, we compared Elastic Net, Explainable Boosting Machines and gradient boosted trees with SHAP-based explanations. Among the candidate pipelines, we selected the pipeline with the highest held-out test ROC AUC for each platform; the selected values were 0.927 in plasma and 0.954-0.973 across the three CSF datasets. Because the same held out test performance was used for pipeline selection and headline reporting, these are optimistically selected single-holdout estimates, not unbiased estimates of generalizable or clinical performance. Explanations identified five recurring biological axes within ADNI: cholinergic (ACHE), tau/14-3-3 (YWHAG, YWHAZ, YWHAB, YWHAE), neuro-axonal (NEFL, NEFH), microglial/complement (CHIT1, SMOC1, CHI3L1, C7, CFH) and synaptic (NPTXR, NPTX2, DLG4, SYT5, VSNL1, ELAVL2). CSF analyses showed synaptic vesicle-cycle enrichment (q&#xa0;=&#xa0;2&#xa0;&#xd7;&#xa0;10-6), and CSF YWHAG correlated strongly with total tau (&#x3c1;&#xa0;=&#xa0;0.87). Cross-fluid directional concordance was modest overall (54-57%) but increased to 73-80% among mapped analyte/protein rows reaching q&#xa0;<&#xa0;0.05 in CSF. These findings provide hypothesis-generating, internally supported evidence within ADNI. Independent external cohorts with locked pipelines are required to evaluate generalizable performance and biological reproducibility; the overlapping TMT-MS and SET2 analyses should not be interpreted as independent replication.

Alzheimer Disease