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Integrated exome and mitochondrial genome sequencing reveals the genetic landscape of primary mitochondrial diseases: findings from a large Tunisian cohort.

Primary mitochondrial diseases are a heterogeneous group of neurometabolic disorders recognized as the most common metabolic genetic diseases. They manifest at any age, affecting any tissue or organ, especially those with high energy demands, and are caused by pathogenic variants in both mitochondrial and nuclear genomes. Here, we aimed to describe the genetic spectrum of a Tunisian pediatric cohort with suspected mitochondrial diseases. We recruited 47 unrelated families who underwent exome sequencing as a first-tier test followed by whole mitochondrial genome sequencing for unsolved cases. Dedicated bioinformatic pipelines and prediction tools were used to determine the potential disease-causing variants. Sanger sequencing confirmed the presence and segregation within parents. For the newly identified variants, structural modeling was conducted to study the impact of these variants on protein structure and motions. Dual genome sequencing yielded a molecular diagnosis in 33/47 families (70%) and 18/47 (38%) showed disease-causing variants in genes encoding mitochondrial proteins. Among them, four families disclosed novel variants in FASTKD2, SERAC1 and GATB, which were supported by in-depth in silico and structural analyses demonstrating their deleterious effect. The remaining families (32%, 15/47) disclosed other metabolic and neurological disorders. An exome-first strategy delivers a high diagnostic yield in Tunisia, where consanguinity remains high and simultaneously captures mitochondrial and non-mitochondrial etiologies. Mitochondrial sequencing remains indispensable in the case of an inconclusive exome. Thus, our data expand the clinical and genetic spectrum of primary mitochondrial diseases in Tunisia, an underrepresented and admixed population.

Humans

Comparative assessment of post-transport disease susceptibility in Asian seabass (Lates calcarifer): Associations with oxidative stress, immune responses, gut microbiota, and tissue pathology.

Stress is a crucial factor that affects aquaculture systems, particularly during transportation, which often leads to deteriorated fish health and reduced survival rates. This study aimed to investigate the comparative differences in physiological changes, oxidative stress parameters, and immune responses between clinically healthy and diseased Asian seabass (Lates calcarifer) following commercial transportation. The study compared the health status of fish after transportation, categorized into healthy (Healthy) and diseased (Disease) groups. Assessments were conducted on oxidative stress parameters, immune responses, gut microbiota composition, and tissue pathology. The results showed that diseased fish exhibited significantly higher oxidative stress levels (P&#xa0;<&#xa0;0.05), as indicated by an increase in malondialdehyde (MDA) levels and altered antioxidant and redox-related markers, including superoxide dismutase (SOD), nitric oxide (NO), catalase (CAT), glutathione (GSH), glutathione reductase (GR), and glutathione peroxidase (GPx), measured across multiple target tissues (head kidney, gills, liver, intestine, and brain), compared with healthy fish. Furthermore, the expression of immune-related genes was significantly downregulated in diseased fish after transportation, indicating immune suppression. In contrast, healthy fish maintained a more balanced immune response, which may partially mitigate the adverse effects of transport-induced stress. Gut microbiota analysis revealed that diseased fish had a significant reduction in beneficial bacteria such as Cetobacterium somerae and Bacillus spp., accompanied by a significant (P&#xa0;<&#xa0;0.05) increase in opportunistic pathogens including Aeromonas spp., Photobacterium spp., and Vibrio spp. Histopathological examination showed severe damage in the gills, liver, and intestines of diseased fish (P&#xa0;<&#xa0;0.05), while only minor tissue alterations were observed in healthy fish. Overall, the findings indicate that post-transport diseased Asian seabass exhibit marked oxidative stress, impaired antioxidant defense, altered immune responses, gut microbial dysbiosis, and multi-organ tissue damage compared with clinically healthy post-transport fish. These results suggest that deterioration of transport conditions may contribute to post-transport morbidity and disease susceptibility.

Animals

Prioritizing Parkinson's disease risk-associated mitochondrial candidate genes via multi-omics integrative analysis.

BACKGROUND: Mitochondrial dysfunction has been implicated in Parkinson's disease (PD), but the genetically regulated mitochondrial genes associated with PD risk remain incompletely defined. METHODS: We conducted a summary-data-based genetic epidemiology study integrating summary-based Mendelian randomization (SMR), Heterogeneity in dependent instruments (HEIDI) filtering, and Bayesian colocalization to prioritize mitochondrial-related molecular features associated with PD risk. Mitochondrial-related genes were defined using MitoCarta3.0. Genetically predicted gene expression and plasma protein abundance were evaluated using expression quantitative trait loci (eQTL) data from eQTLGen and GTEx v8, and protein quantitative trait loci (pQTL) data was assessed using International Parkinson's Disease Genomics Consortium (IPDGC) as the discovery genome-wide association study (GWAS) and FinnGen as the replication dataset. Prespecified QTL analyses were interpreted using FDR correction, HEIDI filtering, and colocalization support. DNA methylation QTL analysis, mitochondrial phenotype MR, and single-nucleus RNA-seq analysis were performed as complementary analyses. RESULTS: In the primary eQTL analysis, higher genetically predicted TTC19 expression was associated with lower PD risk (OR = 0.80, 95% CI: 0.74-0.87, PPH4&#x202f;= 0.80), whereas higher MALSU1 expression was associated with increased PD risk (OR = 2.21, 95% CI: 1.59-3.06, PPH4&#x202f;= 0.96). Both associations survived FDR correction, passed HEIDI filtering, and showed colocalization support. GTEx whole-blood data supported the direction of the TTC19 association. No mitochondrial protein reached significance after FDR correction and colocalization filtering in the primary pQTL analysis. Complementary methylation analysis highlighted cg06270993 as an exploratory regulatory signal for MALSU1. CONCLUSIONS: This MR-colocalization study prioritizes TTC19 and MALSU1 as genetically supported mitochondrial-related candidate genes associated with PD risk. Further validation is required to define their functional roles in PD pathogenesis.

Humans

GPR3 in neuro-metabolic-immune-reproductive nexus - a potential therapeutic target for Multi-System diseases.

BACKGROUND: GPR3(G-protein-coupled receptor 3), an orphan G-protein-coupled receptor (GPCR) with constitutive Gs activity, is expressed in the brain, liver, ovary, and other tissues, regulating cell proliferation, differentiation, and apoptosis across the nervous, reproductive, immune, and metabolic systems. This review synthesizes evidence on its integrated signaling and physiological functions to address the lack of a comprehensive multisystem pathophysiology overview. METHODS: A systematic literature search was conducted on PubMed and Web of Science, using keywords such as "GPR3", "GPCR", "neurodegeneration", "metabolism", "immune", "reproduction", "agonist", "inhibitor", and "therapeutic target". This search identified GPR3's roles in neurodegenerative diseases, immune inflammation, reproduction, and energy metabolism. The analysis focused on signaling pathways, ligand regulation, and therapeutic potential. RESULTS: The research indicates that GPR3 is involved in neuronal survival, synaptic plasticity, and microglial activity via the cAMP/PKA, PI3K/Akt, and &#x3b2; - arrestin pathways. It promotes amyloid - &#x3b2; formation in Alzheimer's disease (AD), yet provides neuroprotection in Parkinson's disease (PD) models. It may contribute to anxiety/depression - like states, maintain oocyte meiotic arrest in the ovary, and activate thermogenic genes in adipose tissue. GPR3 modulates immune responses. Using oleic acid (OA) and diphenyleneiodonium (DPI) as activators, and AF64394 and cannabidiol (CBD) as antagonists, it shows potential in disease models. CONCLUSION: GPR3 acts as a central molecular hub integrating neural, metabolic, immune, and reproductive signaling, highlighting its potential as a therapeutic target for chronic multisystem disorders. However, its dual roles in certain pathologies and translation challenges necessitate further research.

Humans

Biologic-biologic and biologic-JAK inhibitor combination therapy in refractory systemic autoinflammatory diseases.

OBJECTIVES: Systemic autoinflammatory diseases (SAIDs) arise from genetic defects in innate immunity, leading to dysregulated activation of inflammatory pathways, including interleukin (IL)-1, IL-6, TNF, and JAK/STAT. Clinical manifestations range from recurrent fever to severe complications such as encephalitis and AA amyloidosis. Management aims to control inflammation using immunosuppressive agents and targeted monotherapies (biologics or JAK inhibitors). Advanced combination therapy (ACT), defined as the use of biologics and/or JAK inhibitors in combination, has emerged as a strategy for refractory disease. METHODS: In this observational retrospective longitudinal cohort study, patients with SAIDs treated with ACT were included. Demographic, clinical, treatment, and safety data were collected. Treatment response was assessed using a composite outcome incorporating corticosteroid dose, C-reactive protein (CRP), and clinical improvement and categorized as non-response, partial response, or complete response. RESULTS: Thirty-eight patients (median age 30 years [range 4-76]) were included. The most common indications for ACT were pyogenic arthritis, pyoderma gangrenosum and acne (PAPA), mevalonate kinase deficiency (MKD), and undifferentiated SAIDs. Most patients had disease-related complications and were dependent on glucocorticoids and/or opioids to control inflammation and pain, respectively. Following multiple ACT trials, complete response was observed in 21 patients (55.3%), partial response in 12 (31.6%), and no response in 5 (13.1%). Overall, 65 ACT regimens were administered, most commonly combining IL-1 and TNF inhibitors. Thirty-nine regimens were discontinued because of lack of efficacy, secondary loss of response, or adverse events. At the final follow-up, 26 patients (68%) remained on ACT, with a median treatment duration of 60 months (range, 11-186). CONCLUSIONS: ACT offers significant clinical benefits for patients with difficult-to-treat SAIDs, though challenges such as secondary loss of efficacy and infection risks remain.

Humans

Genetic risk stratification of common diseases in breast cancer survivors: a population-based cohort study.

IMPORTANCE: Patients diagnosed with breast cancer (BCa) are at increased risk of multiple common diseases; however, the spectrum of these diseases and the contribution of inherited genetic susceptibility remain incompletely characterized. METHODS: We evaluated 15 common diseases and tested their associations with BCa exposure and disease-specific polygenic risk scores (PRS) in the UK Biobank (UKB; N&#x2009;=&#x2009;254,736). Analyses were performed using cause-specific Cox proportional hazards models within a full-cohort framework, with time-updated BCa status, delayed entry at study recruitment, and age as the underlying time scale. RESULTS: After recruitment, incident BCa was diagnosed in 11,386 women (4.47%), including 2,742 (24.08%) with metastatic BCa. Patients with BCa had an increased risk of nine diseases spanning cardiovascular, metabolic, and neuropsychiatric domains (P<0.003, Bonferroni-corrected). Elevated risks were generally observed among patients with both early staged and advanced BCa. Inherited susceptibility further stratified disease risk, with the highest risks observed among patients with BCa with elevated disease-specific PRS. For example, compared with women without BCa, the hazard ratio (HR; 95% CI) for osteoporosis was 2.33 (2.15-2.52) among women with any BCa, 2.38 (2.18-2.59) among those with non-metastatic BCa, and 2.12 (1.78-2.54) among those with metastatic BCa; the HR was 4.48 (3.99-5.02) among patients with BCa in the highest quartile of osteoporosis-specific PRS (all P<0.001). In contrast, BCa was not significantly associated with risk of coronary artery disease. CONCLUSION: BCa and inherited genetic susceptibility jointly contribute to increased risk of multiple common diseases, supporting the integration of genetic risk stratification into survivorship care.

Complications

Reliability-aware hierarchical learning for Chagas disease screening from 12-lead ECGs: tackling label uncertainty and class imbalance.

Objective.Chagas disease, a neglected tropical disease (NTD) with significant cardiovascular impact, remains underdiagnosed in resource-limited regions. Electrocardiogram (ECG) screening offers a low-cost tool for detecting cardiac involvement, yet algorithm development is challenged by label noise, data scarcity, and the latent nature of infection. This study proposes a robust ECG-based screening framework that explicitly addresses these constraints.Approach.We introduce aReliability-Aware Hierarchical Learningstrategy that calibrates supervision according to data provenance, prioritizing serology-confirmed labels over noisy self-reports. To mitigate data scarcity, we compare a specialized convolutional neural network (CNN) trained from scratch with a transfer learning approach based on a Spatio-Temporal ECG foundation Model (FM). Performance is evaluated across varying data scales, and the representation structure is analyzed to interpret model behavior.Main results.On the official hidden test set of the George B. Moody PhysioNet/Computing in Cardiology Challenge 2025, our approach achieved a Challenge Score of 0.163. We observe that while the specialized CNN performs competitively in data-rich regimes, the FM exhibits superior robustness in extreme low-resource settings. Furthermore, performance reaches a plateau imposed by underlying disease physiology. Bimodal score distributions suggest that models distinguish established cardiomyopathy from indeterminate infection, which remains electrophysiologically indistinguishable from healthy controls.Significance.These findings clarify both the potential and intrinsic limits of ECG-based AI screening for NTD-associated cardiac involvement. Reliability-aware supervision and data-efficient transfer learning provide a practical framework toward scalable and clinically meaningful ECG screening systems in resource-constrained environments.

Humans

Bi-compartmental CSF-serum analysis of NfL and GFAP differentiates central and peripheral pathology in neuroinfectious diseases: A monocentric real-world cohort study.

Neurofilament light chain (NfL) and glial fibrillary acidic protein (GFAP), established biomarkers of neuroaxonal injury and astroglial pathology, are frequently only assessed in blood, which limits conclusions regarding their origin. Bi-compartmental analyses of CSF and serum may help differentiate central or peripheral origin of biomarker elevation. Moreover, studies on NfL and GFAP in distinct neuroinfectious disease (NID) phenotypes, particularly those based on real-world cohorts, are limited. This retrospective monocentric study analyzed CSF and serum from patients with (meningo-)encephalitis/myelitis (TI+; n&#xa0;=&#xa0;48), meningitis (TI-; n&#xa0;=&#xa0;80), (cranial) nerve palsies/polyradiculitis (PND; n&#xa0;=&#xa0;61), and 113 non-neuroinflammatory/non-neurodegenerative controls. A bi-compartmental model using scatter plots and simple linear regression was applied to assess the origin of blood biomarker levels and discriminate between central and peripheral pathology. CSF and serum NfL and GFAP z-scores were significantly higher in TI+ compared with TI- (CSF-GFAP p&#xa0;<&#xa0;0.001/sGFAP p&#xa0;=&#xa0;0.0083; CSF-NfL p&#xa0;=&#xa0;0.003/sNfL p&#xa0;=&#xa0;0.0004). TI+ and PND differed only in GFAP levels, which were higher in TI+ (CSF-GFAP p&#xa0;=&#xa0;0.0049/sGFAP p&#xa0;=&#xa0;0.003). The overall group effect (p&#xa0;&#x2264;&#xa0;0.003) and principal findings remained significant after adjustment for age, sex, QAlb, and time since (symptom) onset to LP. Bi-compartmental analysis revealed simultaneous elevation of CSF and serum NfL in TI+, indicating predominantly central origin, whereas PND demonstrated a shift toward higher sNfL levels suggesting peripheral origin. Higher clinical severity (modified Rankin Scale 3-5) was associated with elevated serum and CSF GFAP and NfL (sGFAP p&#xa0;=&#xa0;0.012/sNfL p&#xa0;=&#xa0;0.002; CSF-GFAP p&#xa0;<&#xa0;0.0001/CSF-NfL p&#xa0;=&#xa0;0.0001), which also predicted unfavorable outcome at discharge (sGFAP p&#xa0;=&#xa0;0.006/sNfL p&#xa0;=&#xa0;0.004; CSF-GFAP p&#xa0;=&#xa0;0.003/CSF-NfL p&#xa0;=&#xa0;0.012). NfL and GFAP were associated with brain/myelon involvement in NID, predominantly reflecting central pathology. Despite strong CSF-serum correlations, bi-compartmental approaches provide additional insight into biomarker origin and disease compartment.

Humans

The Role of Artificial Intelligence for Intimate Partner Violence Prevention: A Systematic Review.

INTRODUCTION: Intimate partner violence (IPV), encompassing physical, sexual, emotional and economic abuse, remains a pervasive global health concern. Traditional prevention efforts face obstacles such as underreporting, delayed detection and limited personalised support. Emerging artificial intelligence (AI) approaches offer new opportunities to enhance IPV prevention. AIM: This systematic review maps and synthesises evidence on AI-driven tools in IPV prevention based on studies published between 2004 and 2024. METHODS: Following PRISMA 2020 guidelines and PROSPERO registration, we searched PubMed, Embase, CINAHL, PsycINFO, IEEE Xplore and Web of Science. Eligible studies explicitly evaluated AI technologies targeting IPV prediction, screening, intervention or support delivery. Study quality was appraised using the Mixed Methods Appraisal Tool (MMAT). RESULTS: Of 1304 records initially identified, 41 studies met eligibility criteria. AI applications ranged from machine learning (ML) for risk prediction and natural language processing (NLP) for IPV detection in clinical and social media data, to image analysis for forensic evaluation and chatbot-based support. Predictive modelling demonstrated strong discriminative performance, while NLP-based screening detected IPV with notable sensitivity. Chatbots showed feasibility and user acceptability, but evidence of their direct impact on reducing IPV incidence was limited, with one randomised controlled trial showing a modest reduction. Key challenges identified included algorithmic bias, data privacy risks and barriers to integration across health and social care systems. DISCUSSION: AI-informed interventions show promise for improving IPV detection, risk assessment, and scalable support, but questions remain about long-term effectiveness, ethical fairness, transparency and equitable implementation. Future interdisciplinary research should address these concerns to responsibly deploy AI in IPV prevention. RELEVANCE TO CLINICAL PRACTICE: The findings highlight the importance of trauma-informed, culturally responsive care and provider training in AI applications. Nurse-led innovation and policy advocacy will be crucial for safe, equitable integration of AI in IPV prevention.

Artificial Intelligence

Proteomic serum profiles before and after lipoprotein apheresis in patients with peripheral artery disease with ulceration.

INTRODUCTION: The efficacy of lipoprotein apheresis (LA) in peripheral arterial disease (PAD) has been primarily attributed to its anti-atherosclerotic effects through the adsorption of lipoproteins. However, the other potential effects of LA remain unknown. We evaluated changes in serum profiles before and after LA using a comprehensive analysis to explore the underlying mechanism. METHODS: Ten patients with leg ulcers were included from the LETS-PAD study, in which patients with lipoprotein-controlled PAD underwent LA. Serum samples collected at baseline and 1&#x2009;month after LA were analyzed for proteomic changes. RESULTS: Six patients exhibited ulcer epithelialization and skin perfusion pressure improvement. Proteomic analysis identified 2033 proteins. Fifty-five proteins showed significant differences. B-cell lymphoma protein-2 associated X (BAX) and C-X-C motif chemokine 10 (CXCL10) were downregulated. CONCLUSION: Serum BAX and CXCL10 levels significantly decreased after LA, which may be involved in the ulcer epithelialization mechanism of LA, which potentially acts through angiogenesis promotion.

Humans

Combining neuromelanin-sensitive MRI and quantitative susceptibility mapping for enhanced diagnosis and differentiation of parkinson's disease: A systematic review.

BACKGROUND: Loss of dopaminergic neurones and iron deposition in the substantia nigra pars compacta (SNpc) are two major pathological hallmarks of Parkinson's disease (PD). Such changes can be visualised by advanced techniques including neuromelanin-sensitive MRI (NM-MRI) and quantitative susceptibility mapping (QSM). This systematic review investigates the diagnostic performance and methodological development of the integrated use of NM-MRI and QSM in PD. METHODS: The systematic search was performed in four databases (Scopus, PubMed, ScienceDirect, and Web of Science) according to the PRISMA 2020 guidelines until July 2026. Bias was assessed using QUADAS-2 and certainty of evidence was assessed using GRADE. RESULTS: Seventeen studies with 2228 participants were included. Combined NM-MRI and QSM consistently showed reduced neuromelanin volume/contrast and increased iron deposition in the SNpc of PD patients compared to healthy controls. Multimodal integration yielded a significant improvement in diagnostic accuracy (AUC values 0.86-0.99), and was able to successfully differentiate PD. Recent methodological advances included simultaneous acquisition sequences (e.g. MTC-GRE, STAGE, setMag) and AI-driven automated segmentation, which led to significantly reduced scan times and improved reproducibility. CONCLUSION: The combination of NM-MRI and QSM has a synergistic effect and provides powerful complementary biomarkers for the diagnosis and differential diagnosis of PD.

Humans

Power as equal ability, knowledge and resistance: Systematic review of experiences of adults with noncommunicable diseases.

PURPOSE: To analyse subjective experiences of power of adults with noncommunicable diseases in relationships with healthcare practitioners as well as underlying facilitators and barriers of these experiences. METHODS: Systematic review (4 databases) of experiences using reflexive thematic analysis underpinned by critical realist approach. The analysis was conducted with an abductive reasoning using previous theories on social power as well as retroduction. RESULTS: Based on 24 studies, we formed three themes, which depict experiences of power as 1) the position, equal ability and freedom to make one's own choices and (re)negotiate within shared dialogue, 2) the ability to use knowledge to claim one's rights, 3) resistance. Facilitators were connected to acknowledgement as an equally valuable individual, positive healthcare practitioner attitudes and actions towards patient activity and views, safety in the relationship as well as to sufficient, clear and varied information. Main barriers were experiences of dehumanisation, negative healthcare practitioner attitudes and actions, perceived or assumed practitioner domination in interactions, lack of or incomprehensible knowledge and testimonial smothering. CONCLUSION: Results suggest that adults with noncommunicable diseases may experience power primarily as a positive power: being acknowledged as having legitimate position to make decisions and being in possession of varied knowledge through which they can gain agency to protect and claim their rights, by resisting, if necessary. Healthcare practitioners are in key position to support these experiences through positive transforming actions, while knowledge asymmetries, persistent inequality and paternalistic structures continue to hinder it.

Humans

Long-term glycemic variability and risk of peripheral artery disease: a systematic review and meta-analysis of cohort studies.

BACKGROUND: A systematic review and meta-analysis to evaluate the impact of long-term glucose variability (GV) on the risk of developing peripheral artery disease (PAD). METHODS: The protocol was prospectively registered in PROSPERO (ID: CRD420251148763). Relevant longitudinal studies were identified through comprehensive searches of PubMed, Embase, and Web of Science. The primary outcome was the risk ratio (RR) of PAD comparing participants with high versus low GV. Summary effect sizes were calculated using a random-effects model to account for between-study heterogeneity. RESULTS: Eleven cohorts were included. Higher GV showed a positive association with PAD risk (RR: 1.42; 95% CI [1.21-1.66] p&#xa0;<&#xa0;0.001), although substantial heterogeneity was present (I 2&#xa0;=&#xa0;91%). This association was consistent across subgroups defined by region (Asian vs. Western), study design, diabetic status, GV metrics, PAD diagnostic methods, and adjustment for HbA1c (all p for subgroup differences > 0.05), except for follow-up duration. Studies with follow-up < 8 years showed a stronger association than those with &#x2265; 8 years (RR: 1.64 vs. 1.19; p for subgroup difference = 0.006). CONCLUSIONS: Elevated long-term GV appears to be associated with an increased risk of PAD. However, substantial heterogeneity across studies suggests that the magnitude of this association should be interpreted with caution.

Humans

Future promise, current clinical ambiguity: a systematic review of machine learning algorithm outputs predicting risk of cardiovascular disease.

OBJECTIVE: To examine whether the outputs of machine learning algorithms designed to predict risk of cardiovascular disease (CVD) address known deficiencies of the Framingham Risk Score (FRS) and improve risk estimates. METHODS: For this critical review, Medline, Embase and IEEE were searched from inception to 1 January 2025. Included were studies describing machine learning algorithms designed to specifically compare output of cardiovascular risk assessment with the FRS. Commentaries, letters, unpublished work or non-peer-reviewed papers were excluded.Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, two reviewers screened titles and abstracts independently, then populated a purpose-built data extraction form. A subsequent qualitative thematic analysis focused on algorithms' strengths, added value, potential harms, unintended consequences and equity implications.The main outcome assessed was whether, among healthy adults, the algorithm improved CVD risk prediction relative to the FRS. RESULTS: Of 707 studies retrieved, 29 met inclusion criteria. 23 reported improved predictive ability relative to the FRS. Most datasets and/or medical records used included sociodemographic predictors of CVD not included among FRS inputs. Some added costly diagnostic tests like CT angiography to FRS screening indicators. When they were defined, inputs and outcomes such as hypertension or myocardial infarction did not always adhere to FRS values. Statistical significance was generally taken as a proxy for clinical significance. Some algorithms overestimated the number at risk compared with the FRS without discussing whether that larger proportion might be at risk of overdiagnosis rather than CVD, while a few decreased the proportion found to be at risk. CONCLUSIONS: Use of artificial intelligence to improve accuracy of risk assessment for CVD demonstrates the technological capacity to merge known sociodemographic predictors with biologic variables and examine non-linear interactions among these. Still needed to achieve patient benefit is clinical insight, adherence to screening principles and cost-benefit assessment of inputs selected.

Humans

Major cardiovascular event risk of advanced therapies in inflammatory bowel diseases: systematic review and meta-analysis.

BACKGROUND: Patients with chronic immune-mediated disorders (IMIDs), including inflammatory bowel disease (IBD), are at increased risk of cardiovascular disease. While advanced therapies show cardioprotective effects in other IMIDs, their impact on major adverse cardiovascular events (MACE) in IBD remains unclear. We conducted a meta-analysis of randomized controlled trials (RCTs) and observational studies evaluating MACE risk with advanced therapies in IBD. METHODS: Systematic search of PubMed, Embase, and Cochrane Central Register of Controlled Trials identified 43 studies (36 RCTs, including 9 long-term follow-up (LTF) studies, and 7 observational studies) published between 2002 and 2024. Primary analyses estimated odds ratios (OR) for MACE comparing advanced therapy to placebo, with secondary analyses stratifying studies by drug class and length of follow-up. Sensitivity analyses were conducted using alternative methods to account for zero-event data. RESULTS: Placebo-controlled RCTs showed a nonsignificant trend toward reduced MACE risk (OR 0.60; 95% CI 0.24-1.51), with similar findings across sensitivity analyses accounting for sparse and zero-event data. Class-specific trends suggested lower MACE risk with IL-12/IL-23 inhibitors (OR 0.35; 95% CI 0.05-2.21), JAK inhibitors (OR 0.57; 95% CI 0.16-2.06), and a potential increase with Anti-TNF agents (OR: 3.04; 95% CI 0.31-29.47), though none reached statistical significance. LTF studies showed consistent findings. Observational studies suggested lower MACE risk with Anti-TNF therapies (OR 0.29; 95% CI 0.21-0.40), but not with IL-12/IL-23 (OR 4.41; 95% CI 0.49-39.28) or JAK inhibitors (OR 1.57; 95% CI 0.86-2.84). CONCLUSION: Advanced therapies did not demonstrate a clear increase or decrease in cardiovascular risk in IBD. The discrepancies between RCTs and observational studies underscore the urgent need for rigorous-designed observational research with long-term follow-up to evaluate the real-world impact of advanced therapies on MACE risk.

Humans

An overview of the use of proteomics and peptidomics to characterize alternative protein foods.

The global protein transition is accelerating the development of alternative protein foods, mainly derived from plants, insects, algae, fungi, and cellular agriculture. Ensuring the authenticity, safety, and nutritional adequacy of these emerging protein matrices requires molecular-level characterization beyond traditional compositional analyses. Proteomics and peptidomics have emerged as transformative analytical platforms capable of decoding the molecular signatures that define protein origin, structural integrity, digestibility, functionality, and health potential. The review comprehensively examines the application of proteomics, and peptidomics for profiling alternative protein foods. Further, the source authentication strategies based on species-specific protein and peptide biomarkers, detection of adulteration in complex matrices, and allergenicity assessment is discussed. Special attention is also given to nutritional proteomics with protein digestibility, gastrointestinal peptide release, and identification of bioactive sequences. SIGNIFICANCE: The importance of this review is that proteomics and peptidomics are becoming central in the management of the fast-growing environment of alternative protein foods, such as plant-based, insect, algal, fungal, and cultured meat products. It provides an explanation of the application of mass spectrometry-based processes to decode molecular signatures defining the origin of proteins, their structural integrity, digestibility, allergenicity, and bioactive properties, and thus directly contribute to safety, nutritional analysis, and authenticity of the product. Presentation of the article includes the integration of the knowledge of traditional muscle foods with alternative systems of proteins, where validated protein and peptide biomarkers are used in authentication, fraud detection, and allergy risk assessment in a wide variety of matrices. It also indicates the role of nutritional proteomics and peptidomics in informing the formulation strategy to promote digestibility and release of health-promoting peptides. In general, this review will guide scientists, the food industry, and regulatory bodies to use modern proteomic technologies in quality assurance, and decision-making, for the advancementof sustainable protein-based foods.

Proteomics

A Duty to Act.

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