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PubMed2026

Systemic biomarkers of treatment response to methotrexate in people with painful knee osteoarthritis: A biological substudy of the PROMOTE randomised controlled clinical trial.

OBJECTIVE: Stratification of therapeutic responses may help identify efficacious therapies for osteoarthritis (OA). In the PROMOTE randomised trial, participants with elevated baseline high-sensitivity C-reactive protein (hs-CRP) showed greater pain reduction after methotrexate treatment. We set out to interrogate a broader panel of serum/plasma inflammatory response markers relevant to methotrexate actions as potential biomarkers of therapeutic effect. Our objectives were to: (i) characterize changes in these systemic markers during methotrexate treatment; determine whether (ii) baseline levels or (iii) changes in any marker during treatment were associated with treatment response; and (iv) compare these findings with the more established clinical inflammatory marker, hs-CRP. DESIGN: Plasma/serum samples from participants in PROMOTE's biological substudy were analysed for 35 inflammatory markers at baseline (pre-treatment) and at 6-months (post-treatment), by MesoScale V-plex multiplex assay. Those with paired biological and clinical data at both baseline and 6-months were included in the substudy analysis set. Relationships between markers and overall data structure were assessed by Pearson correlation and Principal Component analysis. Associations between markers (baseline levels or change over time) and change in average knee pain severity in past week (numerical rating scale, NRS) were evaluated by univariable linear regression, adjusting for baseline age, sex, and body mass index. Least Absolute Shrinkage and Selection Operator (LASSO) regression with bootstrap resampling enabled marker selection. Benjamini-Hochberg correction adjusted for multiple testing (Padj). RESULTS: 87 participants with paired blood marker and clinical data were eligible for substudy analysis. 18/35 markers were quantifiable and analysed. Systemic IL-8 and TNF-α levels decreased (Padj=0.015, 0.048 respectively) while IL-15 increased (Padj=0.033) with methotrexate treatment over 6-months. Analysing within this active treatment randomised arm, higher baseline IFN-γ was associated with greater reduction in NRS pain change (0.66 [0.01, 1.31], P=0.047), as was decreasing TNF-α over 6-months (2.25 [0.00, 4.5], P=0.049). LASSO identified higher IFN-γ, lower plasma IL-15 and IL-16, and younger age as the most important baseline predictors of pain improvement. hs-CRP was highly selected by LASSO for treatment response in both arms. In a secondary univariate treatment arm-by-biomarker interaction analysis, of the 19 markers, only hs-CRP showed consistent effects in adjusted models (at baseline, coeffic. 2.34 [0.53, 4.15], P=0.001; change over 6-months, (0.36 [0.06, 0.66], P=0.018). CONCLUSIONS: Blood measurement of IFN-γ, TNF-α, IL-15 and IL-16 as well as hs-CRP could act as potential markers to stratify the treatment response by average knee pain to methotrexate in knee osteoarthritis.

Humans↗

PubMed2026

Molecular mechanisms of neuroendocrine regulation of molting in the Chinese mitten crab (Eriocheir sinensis): A transcriptomic analysis based on eyestalk ablation model.

Molting disability severely restricts the sustainable aquaculture of the Chinese mitten crab, yet the neuroendocrine mechanisms coordinating physiological responses remain poorly understood. Using unilateral eyestalk ablation to remove the primary source of molt-inhibiting hormone (MIH), we performed time-resolved transcriptomic profiling of the thoracic ganglion at 24 h (early premolt) and 48 h (ecdysis) post-ablation. We identified 2825 differentially expressed genes and uncovered a biphasic molecular response. At 24 h, the thoracic ganglion activates pathways associated with neuromuscular adaptation, oxidative stress, and cardiac muscle contraction. Notably, the arachidonic acid metabolism pathway is selectively rewired: cytochrome P450 ω-hydroxylases (CYP2J2, CYP4V2) are upregulated, while competing branches (epoxide hydrolase, cyclooxygenase) are suppressed, promoting local synthesis of the potent vasoconstrictor 20-HETE within the thoracic ganglion. This enzymatic switch provides a mechanistic link between MIH withdrawal and the local generation of elevated hemolymph pressure required for molting. By 48 h, the transcriptional program shifts toward chitin-based extracellular matrix remodeling, glycosphingolipid biosynthesis, and synaptic reorganization. Collectively, our findings redefine the thoracic ganglion as an active neuroendocrine integrator that translates reduced MIH signaling into phased physiological outputs, revealing a "neuro-endocrine-hemolymph pressure" regulatory axis. This study provides novel molecular targets (e.g., CYP2J2, CHS1, UGCG) for mitigating molting disability in E. sinensis aquaculture.

Animals↗

PubMed2026

Effect of Semaglutide on the Inflammatory Biomarker High-Sensitivity CRP in Patients With Established Cardiovascular Disease and Overweight or Obesity in SELECT: A Prespecified Secondary Analysis.

BACKGROUND: In SELECT (Semaglutide Effects on Heart Disease and Stroke in Patients With Overweight or Obesity), among 17 604 patients with known atherosclerotic cardiovascular disease and overweight or obesity, but not diabetes, randomization to the glucagon-like peptide-1 receptor agonist semaglutide significantly reduced the primary outcome of major adverse cardiovascular events (MACE; cardiovascular death, nonfatal myocardial infarction, or nonfatal stroke) compared with placebo (mean follow-up, 39.8 months). Inflammation, as indicated by plasma hsCRP (high-sensitivity C-reactive protein) level, is implicated as a biomarker predicting cardiovascular risk in obesity and atherosclerotic cardiovascular disease. SELECT provides a unique opportunity to study the relationship among hsCRP, obesity, weight loss, and MACE outcomes in semaglutide versus placebo groups. METHODS: In this prespecified SELECT substudy, we evaluated whether baseline hsCRP levels predicted MACE risk and examined the relationships between changes in hsCRP levels and time to first MACE, baseline body weight, weight loss, and other clinical measures among treatment groups over time (104, 208 weeks) using multiple approaches, including Cox modeling. RESULTS: Baseline hsCRP level, which was similar in the semaglutide (geometric mean 1.96 mg/L) and placebo (geometric mean 1.91 mg/L) groups, was prognostic of future MACE. The risk of MACE increased across baseline hsCRP level <2, 2-<10, and ≥10 mg/L subgroups, including significant associations with cardiovascular and all-cause death. Semaglutide reduced hsCRP levels (-37.8% [104 weeks]) and risk of MACE across all hsCRP subgroups. Greater reductions in ratio-to-baseline hsCRP with semaglutide were associated with greater weight loss, but preceded major weight loss, evident by 4 and 8 weeks, and occurred among those without weight loss. Semaglutide-associated changes in hsCRP were independent of low-density lipoprotein cholesterol levels, statin use, and atherosclerotic cardiovascular disease entry criteria. hsCRP reductions were found to be prognostic of decreased risk of MACE. Modeling suggests decreased inflammation as contributing in part to the benefits seen with semaglutide in SELECT. CONCLUSIONS: In SELECT, hsCRP data at baseline and in response to treatment with semaglutide support inflammation as a potential prognostic factor associated with cardiovascular risk in these generally well-treated patients with atherosclerotic cardiovascular disease and overweight or obesity but not diabetes. These findings suggest that the MACE reduction observed with semaglutide versus placebo in SELECT may have partially involved a decrease in inflammation. REGISTRATION: URL: https://www.clinicaltrials.gov; Unique identifier: NCT03574597.

Humans↗

PubMed2026

Epigenetics and In Silico Transcriptome Analysis of Pediatric Acute Myeloid Leukemia.

Pediatric acute myeloid leukemia (AML) is a heterogeneous hematologic malignancy that accounts for about 15%-20% of childhood leukemias. Despite therapeutic advances, relapses remain common, and survival for high-risk patients is below 60%. Unlike adult AML, pediatric AML displays distinct genetic mutations, including FLT3-ITD, NPM1, KMT2A rearrangements, and core-binding factors (CBF) fusions, as well as extensive epigenetic dysregulation. Aberrant DNA methylation, histone modifications, and altered non-coding RNA expressions disrupt hematopoietic differentiation and activate oncogenic transcriptional networks. Recent advances in silico transcriptomic analysis have transformed the study of pediatric AML by integrating gene expression and epigenetic data to identify molecular drivers and regulatory networks. Computational RNA-seq pipelines and pathway analyses have highlighted key epigenetic regulators, including DNMT3A, TET2, and HDACs, as potential therapeutic targets. Multi-omics approaches combining transcriptomic, methylomic, and chromatin accessibility data are increasingly used to define biomarkers for diagnosis, prognosis, and therapeutic response. This review provides a comprehensive overview of the molecular and epigenetic landscape of pediatric AML, emphasizing the power of in silico transcriptome analysis to uncover disease mechanisms, refine patient stratification, and guide the development of precision-based epigenetic therapies aimed at improving long-term outcomes in children with AML.

Humans↗

PubMed2026

Identification of CD55 as a downstream factor of EP4 receptor signaling in colorectal cancer cells.

Prostaglandin E2 (PGE2) signaling through the E-type prostanoid 4 (EP4) receptor has been implicated in the pathophysiology of colorectal cancer (CRC). We herein identified decay-accelerating factor, also known as CD55, as a novel CRC-associated downstream factor of the EP4 receptor. The integration of transcriptomic profiling of PGE2-stimulated HCA-7 human colon cancer cells with analyses of cancer genomic databases predicted CD55 as a potential EP4 receptor-regulated target. Inhibitor-based experiments showed the induction of CD55 after a PGE2 stimulation required the EP4 receptor and Gi protein in HCA-7 cells, whereas protein kinase A signaling was dispensable. In combination with a toxicogenomic database analysis, p38 mitogen-activated protein kinase (MAPK) was identified as the predominant effector connecting the EP4 receptor to CD55 upregulation. A single-cell RNA-seq re-analysis of human CRC tissues revealed CD55 upregulation and p38 MAPK-related gene set enrichment in epithelial cells expressing the EP4 receptor, suggesting that this induction mechanism may operate in a subset of epithelial cells in clinical specimens. Collectively, these results delineate a PGE2/EP4 receptor/Gi protein/p38 MAPK signaling axis that induces CD55 expression in HCA-7 cells and epithelial tumor cells, provide new mechanistic clues for understanding the regulation of complement regulatory molecule CD55 expression by prostaglandin signaling.

Humans↗

PubMed2026

Efficacy and safety of once-weekly semaglutide 2·4 mg in Chinese adults with overweight or obesity (STEP 12): a randomised, double-blind, placebo-controlled, multicentre, phase 3b trial.

BACKGROUND: Semaglutide 2·4 mg is a GLP-1 receptor agonist that reduces bodyweight, and provides other cardiometabolic benefits, among people with a BMI at least 30 kg/m2 or at least 27 kg/m2 and with weight-related comorbidities. This trial aimed to evaluate the efficacy, tolerability, and safety of semaglutide 2·4 mg in adults from mainland China and Taiwan with overweight or obesity according to locally defined, BMI thresholds. METHODS: This completed randomised, double-blind, placebo-controlled, multicentre, two-armed, parallel-group, phase 3b trial (STEP 12) was conducted at 19 sites across mainland China and Taiwan. Adults with a BMI of 24-<28 kg/m2 and at least one weight-related comorbidity, or a BMI of 28-<30 kg/m2, with or without type 2 diabetes, were randomly assigned (2:1) to once-weekly subcutaneous semaglutide 2·4 mg or placebo, plus lifestyle intervention, for 44 weeks. Randomisation was performed by the study sponsor using the Randomisation Trial Supplies Management System. Coprimary endpoints were percentage change in bodyweight and the proportion of participants achieving at least 5% bodyweight reduction. Safety was analysed descriptively in all participants who received the trial intervention. Missing data at week 44 were imputed with washout multiple imputation. This study is registered with ClinicalTrials.gov, NCT06041217, and is completed. FINDINGS: Between Sept 15, 2023, and May 7, 2025, of 254 screened participants, 161 (66·5%) of 242 participants were randomly assigned to semaglutide 2·4 mg and 81 (33·5%) to placebo; 121 (50·0%) participants were female, and 47 (19·4%) participants had type 2 diabetes. Bodyweight reduction was greater with semaglutide versus placebo (-12·1% [SE 0·6] vs -2·2% [0·8]; estimated treatment difference -9·9 percentage points [95% CI -11·8 to -8·0]; p<0·0001), with a greater proportion of participants achieving at least 5% bodyweight reduction (80·5% vs 24·4%; odds ratio [OR] 14·8 [95% CI 7·4 to 29·6]; p<0·0001). Adverse events were reported in 141 (87·6%) of 161 participants in the semaglutide 2·4 mg group and 61 (75·3%) of 81 participants in the placebo group, with gastrointestinal disorders being the most common. INTERPRETATION: Semaglutide 2·4 mg provided a superior reduction in bodyweight versus placebo in Chinese adults with overweight or obesity. The safety profile was consistent with the known profile of semaglutide. FUNDING: Novo Nordisk A/S. TRANSLATION: For the Mandarin translation of the abstract see Supplementary Materials section.

Adult↗

PubMed2026

Artificial Intelligence Technologies in Nursing Clinical Decision-Making: An Umbrella Review.

AIM: To describe contemporary peer-reviewed literature on artificial intelligence in nurses' clinical decision-making. METHODS: An umbrella review of literature reviews. DATA SOURCES: Four major databases were searched for reviews published between 2019 and 2024. RESULTS: Sixteen literature reviews reported on 965 nursing artificial intelligence primary studies. The studies focused on technology development and emerging performance evaluations, whilst real-world testing or implementation in nursing clinical settings was rare. Rigorous comparative analyses were lacking. While artificial intelligence demonstrates promise in decision-making, challenges such as a lack of controlled studies, algorithmic bias, limited reproducibility and insufficient clinical trials hinder its practical impact. Ethical concerns, transparency and patient data privacy issues pose barriers to AI integration in nursing practice. Ethical and legal guidelines for patient privacy are needed and should be taught along with AI literacy training for nurses. CONCLUSIONS: Artificial intelligence has the potential to enhance clinical nursing decision-making, although evidence is limited by too few examples of nurse participation during development. Underutilisation in administrative nursing functions hinders implementation. Nurses should assume a central role in the design and development of AI applications to ensure that these technologies address the realities of nursing practice. With such improvements, artificial intelligence can transform nursing practice, improve nurses' clinical decision-making and ultimately enhance consumer healthcare outcomes. PATIENT OR PUBLIC INVOLVEMENT: No Patient or Public Involvement. REPORTING METHOD: While there is no reporting checklist for umbrella reviews, the PRISMA guide for systematic reviews was followed.

Artificial Intelligence↗

PubMed2026

Multi-omics analysis reveals coordinated epigenetic dysregulation in atrazine-induced dopaminergic neurotoxicity.

Atrazine (ATR), a widely used triazine herbicide, has been linked to neurotoxicity, yet the epigenetic mechanisms underlying its dopaminergic effects remain unclear. This study investigated whether coordinated miRNA dysregulation and DNA methylation alterations contribute to ATR-induced Parkinson's disease (PD)-like neurotoxicity. Male Sprague-Dawley rats were administered ATR (50 mg/kg/day) for 90 days, resulting in motor and cognitive deficits with dopaminergic dysfunction, including increased α-synuclein and reduced tyrosine hydroxylase expression. Small RNA sequencing identified 72 differentially expressed miRNAs in the substantia nigra, enriched in PI3K-Akt, MAPK, and Ras signaling pathways. In a cohort of six PD patients and six matched controls, genome-wide DNA methylation profiling revealed 4694 differentially methylated positions, predominantly hypomethylated, with overlapping enrichment in neuronal signaling pathways. Weighted gene co-expression network analysis identified a PD-associated module strongly correlated with disease status (r = -0.95, P < 0.001). Multi-omics integration identified CASP3 as a central hub gene. External validation supported CASP3 relevance in PD (AUC = 0.833), and molecular docking suggested potential ATR-CASP3 interaction. Further analysis predicted upregulated miR-3552 as a potential upstream regulator of CASP3. These findings indicate that ATR-induced neurotoxicity may be mediated through the miR-3552/CASP3 signaling axis, ultimately regulating apoptosis and contributing to neurodegeneration.

Animals↗

PubMed2026

Association of Baloxavir Treatment Timing with Serial Interval and Household Transmission of Influenza through a Likelihood-Based Analysis.

BACKGROUND: Baloxavir treatment is associated with reduced influenza transmission within households, and the serial interval varies by treatment status. However, it remains unclear how baloxavir-induced changes in the serial interval relate to household transmission. We aimed to quantify the model-based association between baloxavir treatment timing and the serial interval and household transmission risk. METHODS: We conducted a household survey of influenza cases in Japan between October 2018 and February 2019. We defined the likelihood-based model integrating the serial interval distribution by treatment status and the secondary attack rate (SAR) using individual-level data from index cases. Using this model, we estimated the reduction in the serial interval associated with baloxavir treatment. RESULTS: Compared with untreated index cases, baloxavir-treated cases were estimated to have a serial interval density reduced by 21.42% following treatment. Treatment within 24 hours was associated with a 0.1685 reduction in the area under the curve, with smaller reductions as treatment was delayed. Earlier treatment was associated with a shorter, more concentrated distribution, whereas treatment 72 hours after onset resembled untreated cases. CONCLUSIONS: Our findings highlight that baloxavir treatment is associated with a shorter serial interval and lower estimated secondary household transmission risk. We provide model-based estimates suggesting that earlier administration is associated with a greater reduction in serial interval density and estimated transmission risk, which may inform public health strategies for infection control.

Influenza↗

PubMed2026

The mighty microproteins: from versatile cellular regulators to precision medicine therapeutics.

Microproteins, are tiny proteins encoded by small open reading frame (sORF), translation of these non-canonical open reading frames (ncORFs) has been implicated in diverse biological processes and diseases. This review summarizes recent developments in the discovery, biogenesis, and functional characterization of microproteins, and their involvement in various disease, with special focus on their roles in cancer, cardiovascular, metabolic, neurodegenerative and immune-related disorders. We emphasize the regulation of key cellular pathways by microproteins, including mitochondrial homeostasis, apoptosis, metabolic reprogramming, and immune signaling, all of which affect disease initiation and progression. Emerging evidence also supports their potential as disease biomarkers and therapeutic candidates for precision medicine. Finally, the review critically discusses the current challenges including discrepancies in microprotein annotation, the limitations of ribosome profiling and proteogenomic approaches, the gap between computationally predicted and experimentally validated microproteins, and the need for rigorous orthogonal validation by means of CRISPR-based genome editing, ribosome release assays, mutational analysis, high-resolution mass spectrometry, and functional studies. Finally, we review recent development of AI-assisted ORF prediction, single-cell translatomics, spatial proteomics, and integrated multi-omics as emerging technologies reshaping. Microprotein discovery and functional annotation. Finally, we discuss the translational potential of microproteins and highlight the remaining challenges to clinical application, including peptide stability, pharmacokinetics, tissue-specific delivery, immunogenicity, and the need for rigorous preclinical and clinical validation. Together, this review provides an updated and critical overview of the rapidly evolving microprotein field and highlights future research priorities for translating these molecules into clinically useful biomarkers and precision therapeutics.

Microproteins↗

PubMed2026

A mechanism-guided framework for prioritizing membrane-interaction anti-Vibrio peptides from peptidomics data.

A mechanism-guided framework for prioritizing membrane-interaction antimicrobial peptide candidates from proteomics-derived peptide mixtures is presented. The framework integrates conservative machine-learning-based antimicrobial peptide (AMP) screening with a literature-derived membrane-interaction plausibility (MAP) assessment and a data-driven membrane-interaction ranking function (AIPx), followed by structural visualization for interpretability. MAP encodes physicochemical characteristics commonly associated with peptide-membrane interaction and provides a graded plausibility assessment. Building upon this physicochemically interpretable framework, AIPx ranks peptides using feature weights calibrated from experimentally characterized anti-Vibrio peptides, where minimum inhibitory concentration (MIC) values are used as a coarse-grained ranking reference rather than a direct prediction target. In a peptidomics-based peptide fractionation study targeting Vibrio spp., AIPx exhibited a consistent relationship with experimentally observed antibacterial activity. Distributional analysis revealed that peptide fractions exhibiting high anti-Vibrio activity are characterized by enrichment of high-ranking peptides rather than by AMP abundance alone. By structuring AMP identification and prioritization as sequential stages, the MAP + AIPx framework enables interpretable and experimentally actionable candidate selection by reducing biologically implausible candidates. The framework facilitates species-oriented prioritization of AMP candidates, addressing a key challenge in antimicrobial peptide discovery where activity may depend on target-specific membrane characteristics. Moreover, the approach is extensible through species-specific calibration and supports interpretable, mechanism-informed prioritization in antimicrobial peptide discovery.

Proteomics↗

PubMed2026

Surface shaving proteomics reveals a parasite-encoded protein embedded in the spore filaments of Ameson portunus.

The surfaces of microsporidian spores are frequently adorned with filamentous appendages of unknown origin and function. Although some studies suggest that these structures may be host-acquired, the absence of identified parasite-encoded components has hindered our understanding of their biogenesis and role in infection. Here, we applied surface shaving proteomics to profile the surface-exposed proteins of Ameson portunus -a microsporidian pathogen causing severe myopathy in portunid crabs. Our analysis identified 120 candidate surface proteins. Nineteen of these were highly enriched by both direct shaving and SDS-assisted methods, representing a high-confidence surfome. Among these, a previously uncharacterized protein, designated 8-2.11, was confirmed via immunofluorescence assay and immunoelectron microscopy. It was expressed early in development stage and specifically localized to the spore wall and hair-like projections (HLPs) of microsporidia. Notably, polyclonal antibodies against recombinant 8-2.11 recognized a native protein in spores, specifically labeled the HLP structures, and showed no cross-reactivity with host cells. Our results provide the first evidence of a parasite-encoded protein that is integral to HLP formation, challenging the prevailing hypothesis that these surface filaments are solely host-derived. This study establishes surface shaving as a powerful tool for microsporidian research and highlights 8-2.11 as a promising candidate for future functional studies on spore surface biology and host-parasite interactions.

Animals↗

PubMed2026

Age- and sex-adjusted genomic differences between Korean and Beat AML cohorts.

Genomic profiling plays a central role in risk stratification and therapeutic decision-making in acute myeloid leukemia (AML), yet the clinical implications of population-specific genomic architectures remain incompletely defined. We conducted a prospective, multicenter study of 603 adults with newly diagnosed AML in Korea, integrating targeted sequencing of 83 recurrently mutated genes with comprehensive clinical annotation across treatment intensities, including allogeneic hematopoietic stem cell transplantation (allo-HSCT). For contextual comparison, genomic profiles were evaluated against the Beat AML cohort. The overall genomic landscape was broadly conserved, supporting shared core disease biology across populations. However, RUNX1::RUNX1T1, CEBPA, GATA2, KIT, and DDX41 mutations were more frequent in the Korean cohort, whereas FLT3 and NPM1 mutations were less common. These differences translated into a distinct distribution of European LeukemiaNet (ELN) 2022 risk categories, with implications for therapeutic stratification. Notably, most DDX41 alterations were germline (3.2%), highlighting the need for systematic germline evaluation with implications for genetic counseling and donor selection. Although unadjusted overall survival appeared longer in the Korean cohort, this difference was not significant after adjustment for key clinical variables. These findings indicate that population-specific genomic distributions reshape the clinical application of risk stratification and support population-aware precision medicine strategies in AML.

Journal Article↗

PubMed2026

Smartphone Apps for Preventing Adolescent Health Problems Among Health Care Professionals: Systematic Search and Quality Assessment.

BACKGROUND: Health care professionals must consider multiple dimensions of prevention when consulting with adolescents. Identifying risky behaviors early in adolescence is crucial for reducing both morbidity and mortality. General practitioners are increasingly eager to incorporate digital tools for prevention into their consultations with adolescents; however, the relevance and clinical validity of these digital tools are not always established or well-known. Consequently, primary care professionals require guidance and support in selecting relevant mobile health (mHealth) tools. OBJECTIVE: The aim of this study is to identify relevant and useful digital apps to help primary care professionals detect at-risk adolescents across all recommended areas of prevention: orthopedics, mental health, substance abuse, risk behaviors, sexual health, vaccinations, social relationships, and nutrition. METHODS: A systematic review of smartphone apps, with an analysis of content quality, was carried out by 4 researchers using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) checklist. The App Store and Google Play Store platforms were surveyed. The inclusion criteria were as follows: free of charge, date of last update, availability in French or English, relevance of the preventive approach to adolescents, and scientific validation. Four health care professionals assessed the apps: 2 selected the apps relevant to health care professionals, then 3 analyzed these apps using the French version of the Mobile App Rating Scale (MARS-F). Intraclass correlation coefficient, model (2,1) (2-way random effects, absolute agreement, single measures); standard error of measurement; and mean absolute error were also calculated. RESULTS: A total of 976 apps were identified, 49 of which had disappeared from the platforms prior to analysis. Nine apps were retained. Seven (0.72%) were included after evaluation using the MARS-F: 2 on mental health and 5 on sexual health (including 3 on contraception only). The mean MARS-F interrater score ranged from 2.5/5 to 3.8/5. The global MARS-F score demonstrated a pooled SD of 0.60 and an intraclass correlation coefficient (2,1) of 0.0003, resulting in a calculated standard error of measurement of 0.60. The average discrepancy between raters was a mean absolute error of 0.53. CONCLUSIONS: No similar studies have been identified in the literature that specifically focus on mobile apps designed to support health care professionals in delivering preventive care to adolescents. Of the 8 areas of prevention identified as relevant for adolescents, only 3 are addressed by the apps validated through our methodology (5 focus on sexual health). Consequently, current apps are insufficient to support health care professionals in their overall preventive work with adolescents. Such a review should be conducted systematically prior to the development of any new tool to prevent duplication and channel creative efforts toward truly innovative digital solutions. Furthermore, a thorough analysis of relevant, recommended websites is essential, as these resources complement the use of mobile apps designed for health care professionals.

Humans↗

PubMed2026

Venomous Lepidoptera: defensive toxin systems, venom composition, and clinical significance.

Venomous Lepidoptera constitute an underrecognized yet medically significant group of toxin-producing arthropods that employ contact-mediated defensive envenomation through specialized integumentary structures such as setae, spines, and scoli. Unlike actively stinging arthropods, these insects deliver venom passively upon contact, eliciting a diverse spectrum of clinical manifestations collectively termed lepidopterism. Clinical outcomes range from localized pain and dermatitis to severe systemic effects, including hemorrhagic syndromes, complement activation, and chronic inflammatory disorders. Recent advances in proteomic and transcriptomic technologies have transformed our understanding of lepidopteran venoms, revealing unexpectedly complex toxin repertoires comprising serine proteases, phospholipases, pore-forming proteins, disulfide-rich peptides, neuroactive RF-amide peptides, and immune-modulating components. These findings have provided new insights into the molecular basis of toxicity, host-pathogen interactions, and the evolutionary diversification of venom systems within Lepidoptera. This review synthesizes current knowledge on the morphology of venom-delivery structures, venom composition, mechanisms of action, and associated clinical manifestations, while highlighting medically important taxa, particularly species of the genus Lonomia. The successful development of antivenom against Lonomia envenomation underscores the translational relevance of lepidopteran toxin research and its potential for therapeutic innovation. By integrating molecular, clinical, and evolutionary perspectives, this review repositions venomous Lepidoptera as a legitimate and important component of arthropod toxinology. Furthermore, it identifies critical methodological limitations and key knowledge gaps, providing a framework for future investigations aimed at advancing our understanding of toxin biology, immunopathology, and the development of novel biomedical applications.

Animals↗

PubMed2026

Proteomic responses of the oil palm pest Metisa plana (Psychidae) to farnesyl acetate exposure.

Metisa plana Walker (Lepidoptera: Psychidae) is a major defoliator of oil palm in Malaysia, causing substantial economic losses. Farnesyl acetate (FA), a sesquiterpenoid compound, has been proposed as a potential insecticidal agent against M. plana, yet its molecular impact on larval physiology remains poorly understood. Here, we employed label-free quantitative proteomics, functional enrichment analysis, and targeted transcript assessment to characterize the temporal proteomic response of M. plana larvae at 7 and 14 days after treatment (DAT) with FA. Principal component analysis revealed robust separation between treated and control samples at both time points, indicating sustained treatment-driven proteomic restructuring. Early exposure (7 DAT) elicited a heterogeneous response involving stress-associated proteins, redox enzymes, and cytoskeletal regulators, whereas later exposure (14 DAT) produced a consolidated profile characterized by metabolic reprogramming, downregulation of ribosomal proteins, induction of heat shock proteins, and enrichment of RNA surveillance and mitochondrial pathways. Targeted transcript analysis qualitatively supported proteomic trends for HSP83 and aldehyde dehydrogenase X, although limited amplification precluded quantitative inference. Collectively, these findings demonstrate that FA exposure drives a shift from acute proteomic perturbation toward a maintenance-oriented physiological state, prioritizing proteostasis, energy management, and stress adaptation over growth and development. This integrated molecular perspective provides mechanistic insight into the chronic effects of FA, highlighting its potential to suppress larval performance and informing the development of biorational, physiology-based pest management strategies in non-model insects.

Animals↗

PubMed2026

A genome-wide coverage-based pipeline for the identification of host-derived candidate DNA biomarkers from cell-free blood.

We have created a new data-analysis pipeline for the discovery of host-specific candidate DNA biomarkers derived from sequencing data of cell-free blood. Unlike approaches that rely on specific molecular or genetic signatures, our method leverages the coverage distribution of cell-free DNA sequences mapped to a reference genome, applying statistical analyses to identify informative short genomic regions for biomarker discovery. The pipeline is applicable to diverse diseases and can be used to analyze cell-free DNA sequences from plasma or serum to identify candidate biomarkers that are characteristic of disease states in mammals. Core functionalities were developed in Java and integrated with open-source software tools for the preprocessing of raw sequencing data, complemented by Python scripts for the machine-learning analysis and statistical validation. The pipeline is designed for HPC use and users can access the pipeline through a Galaxy workflow, which offers a user-friendly web interface for input selection prior to execution and analysis progress monitoring. Performance tests, carried out using duplicate sets of COVID-19 samples and controls, showed linear scalability of execution time with an increasing dataset size, as well as a substantial reduction in execution time through parallelized computation, whereby each HPC node is used to process the data of one chromosome. Further statistical tests confirmed the quality of the pipeline's results by showing that the set of identified candidate biomarkers remained stable across varying dataset sizes.

Biomarkers↗

PubMed2026

Inducible flocculation in Komagataella phaffii enables enhanced biomass separation for biopharmaceutical production.

Biomass separation represents a critical bottleneck in Komagataella phaffii-based biopharmaceutical processes, as typically high cell densities of 40 - 50 % create significant operational, technical and economic challenges for harvest operations. Yeast cell aggregation (flocculation) provides a solution to accelerate cell sedimentation by increasing particle size, thus allowing to improve biomass-supernatant separation efficiency during both natural gravity settling and (continuous) centrifugation operations. This study demonstrates successful engineering of K. phaffii strains with an inducible flocculation phenotype using CRISPR/Cas9-based genome editing to integrate the Saccharomyces cerevisiae FLO1 (ScFLO1) gene under control of various regulatory elements, including methanol-inducible and derepressible promoters. Flocculation strength could be enhanced by implementing transcriptional positive feedback circuits based on the methanol-inducible AOX1 promoter. To address methanol-free production requirements, we developed alternative systems to retrofit PAOX1-based ScFLO1 expression and exploited the derepressible PDF promoter, offering broader compatibility with biopharmaceutical manufacturing facilities. Flocculating cells cultivated in a bioreactor demonstrated significantly improved sedimentation behavior, with considerably lower supernatant turbidity after short low-speed centrifugation or gravity sedimentation compared to non-flocculating controls. Crucially, cell flocculation had no negative impact on product amount and quality when expressing a multivalent NANOBODY® VHH molecule with pharmaceutical relevance. Thus, this work establishes the first genetically engineered flocculation system in K. phaffii compatible with recombinant protein production, providing the basis for an innovative approach to streamline harvest operations in biopharmaceutical processes.

Flocculation↗