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PubMed2026

Comparative safety of lipid-lowering drugs alone or in combination: insights from a systematic review and network meta-analysis.

BACKGROUND AND AIMS: Although the safety profile of lipid-lowering therapies (LLTs) is known, there are no comprehensive comparative assessments. We aimed to compare the risk of muscle-related events, diabetes, liver dysfunction, and cognitive disorders among LLTs through a network meta-analysis. METHODS AND RESULTS: Databases were searched from inception to May 2025. Eligible studies included adult patients, using statins, ezetimibe, PCSK9 monoclonal antibodies (PCSK9mAbs), inclisiran, bempedoic acid, or their combinations as intervention, reporting the information about any of the selected adverse events, a total sample size of ≥200 subjects, and had ≥1 month of intervention. Pooled estimates were assessed by fixed effects model within a frequentist setting. Pooled relative risks (RR) and their 95% confidence interval were estimated. A total of 303,397 subjects from 153 RCTs were included. Bempedoic acid ranked the lowest risk of myalgia (vs PCSK9mAbs, RR 0.80 [0.69, 0.93]). PCSK9mAbs were associated with lower incidence of creatine kinase (CK) elevation, diabetes, and liver dysfunction comparing to statins (statins vs PCSK9mAbs, RR 1.44 [1.14, 1.81], RR 1.13 [1.05, 1.22], and RR 1.38 [1.17, 1.62], respectively). In terms of muscle-related events and cognitive disorders, no significant risk differences were found among treatments and their combinations. CONCLUSIONS: PCSK9mAbs appear to have a more favourable safety profile regarding the risk of CK elevation, diabetes, and liver dysfunction. Bempedoic acid seem to be a better choice for subjects with high risk of myalgia. This information can be valuable when selecting therapy for specific patient subgroups at higher risk of certain adverse events.

Humans↗

PubMed2026

Biomarker Analysis from Patients with Metastatic PDAC Treated with TGFβ Antibody NIS793 plus Abraxane + Gemcitabine versus Abraxane + Gemcitabine Alone in a Phase II, Open-Label, Randomized Study.

PURPOSE: Transforming growth factor β (TGFβ) plays a dual role in cancer, acting as a tumor suppressor early in the disease but promoting progression and immune evasion when dysregulated. In pancreatic ductal adenocarcinoma (PDAC), TGFβ-driven desmoplasia fosters chemoresistance and immunosuppression, limiting therapeutic efficacy. NIS793, a fully human mAb targeting TGFβ, demonstrated antifibrotic and immunomodulatory activity in preclinical models and early-phase trials. PATIENTS AND METHODS: We conducted a randomized, open-label, phase II study in treatment-naïve patients with metastatic PDAC (mPDAC) to evaluate NIS793 ± spartalizumab (anti-PD-1) combined with nab-paclitaxel (or Abraxane)/gemcitabine (ABRA/GEM) versus ABRA/GEM alone. The primary endpoint was progression-free survival (PFS); secondary endpoints included overall survival (OS), safety, pharmacokinetics, and biomarker analyses. Exploratory assessments included paired tumor RNA sequencing, cell-free DNA profiling, and plasma proteomics. RESULTS: NIS793 demonstrated target engagement and suppression of TGFβ signaling, confirmed by transcriptomic and proteomic analyses. Stromal remodeling was evident, with significant downregulation of cancer-associated fibroblast markers (Acta2, Fap) and collagen-related signatures. Despite proof of mechanism, clinical efficacy was not observed: Median PFS and OS were comparable or numerically worse in the NIS793 arm versus control (HR for OS in NIS793 + ABRA/GEM vs. ABRA/GEM: 1.32; 95% confidence interval, 0.84-2.07). The safety profile was manageable, with no unexpected toxicities. Biomarker data revealed increased expression of neutrophil-related genes after treatment, suggesting potential induction of tumor-promoting inflammation. CONCLUSIONS: NIS793 effectively inhibited TGFβ signaling and led to stromal remodeling but failed to improve outcomes in mPDAC. These findings highlight the complexity of TGFβ biology and caution against its blockade in combination with chemotherapy for PDAC. Future strategies should consider context-dependent effects of TGFβ inhibition.

Humans↗

PubMed2026

Nebivolol treatment improves hypertension-induced endothelial cell dysfunction by reducing TGF-β1-dependent senescence and normalizing mitochondrial indices.

OBJECTIVES: Serum from patients with hypertension (HT) causes endothelial cell (EC) damage, leading to senescence and dysfunctional phenotype. This study investigated whether serum from patients treated with the antihypertensive drugs could normalize EC activity. METHODS: This study involved 71 patients with newly diagnosed HT, who were randomly assigned to one of three groups based on the antihypertensive treatment: amlodipine, nebivolol, or perindopril. Serum samples collected before and 6 weeks after treatment were applied to ECs in vitro to assess their angiogenic activity, cellular senescence, mitochondrial metabolism, and oxidative stress. RESULTS: Results showed that exposure of ECs to serum from patients treated for 6 weeks significantly altered EC function, with varying effects among the drugs. Serum from nebivolol-treated patients produced the most consistent benefits, reducing EC proliferation and HIF-1α expression, likely due to lower levels of angiogenic factors such as angiopoietin-1, basic fibroblast growth factor (bFGF), insulin-like growth factor 1 (IGF-1), and vascular endothelial growth factor (VEGF). Additionally, this serum contained reduced levels of pro-inflammatory cytokines (E-selectin, P-selectin, monocyte chemoattractant protein-1 (MCP-1), and tumor necrosis factor α (TNFα)) and lower TGF-β1, which are linked to HT-related EC senescence. Nebivolol treatment decreased senescence biomarkers such as SA-β-Gal, 53BP1, and p16, with SA-β-Gal reduction comparable to that of TGF-β1 neutralizing antibodies. Oxidative stress was reduced, indicated by lower oxidized DNA product levels. CONCLUSIONS: Nebivolol was the most effective at reducing the factors, associated with HT induced cellular senescence of endothelium, through reducing TGF-β1.

Humans↗

PubMed2026

Comparison between measured and synthesized posterior lead electrocardiograms during percutaneous coronary intervention-induced myocardial ischemia.

BACKGROUND: Posterior/inferolateral myocardial ischemia is frequently underrecognized on standard 12‑lead electrocardiography (ECG). Synthesized posterior leads derived from the standard 12‑lead ECG have been proposed as an alternative to directly measured posterior leads; however, their accuracy under controlled ischemic conditions has not been fully validated. METHODS: We prospectively enrolled 26 consecutive patients undergoing percutaneous coronary intervention (PCI) in whom simultaneously recorded measured and synthesized posterior lead ECGs (V7-V9) were obtained during balloon-induced myocardial ischemia. ST-segment deviation was measured at the ST junction (STJ), 40 ms (ST1), and 80 ms (ST2) thereafter. Agreement between measured and synthesized posterior leads was assessed using Pearson correlation and Bland-Altman analyses. As an exploratory patient-level analysis, diagnostic performance was compared with reciprocal anterior ST-segment depression (V1-V4). RESULTS: Strong correlations were observed between measured and synthesized posterior lead ST-segment deviations (V7: r = 0.89; V8: r = 0.86; V9: r = 0.83; all P < 0.001). Bland-Altman analysis demonstrated minimal systematic bias (within ±0.004 mV) and narrow limits of agreement. Synthesized posterior leads showed higher diagnostic performance than reciprocal anterior ST-segment depression (AUC 0.917 vs. 0.708), although the difference was not statistically significant (DeLong test, P = 0.197). Using a 0.05 mV threshold, synthesized posterior leads demonstrated 83.3% sensitivity, 100% specificity, and 96.2% overall accuracy. CONCLUSIONS: Synthesized posterior leads closely reproduced measured posterior lead ST-segment deviations during percutaneous coronary intervention (PCI)-induced myocardial ischemia, supporting the technical validity of posterior lead reconstruction. Larger prospective studies are warranted to determine whether synthesized posterior leads provide incremental diagnostic value beyond careful interpretation of the standard 12‑lead ECG.

Humans↗

PubMed2026

Meta-analysis of growth and inactivation kinetics of Legionella.

Quantitative risk assessments intended to inform evidence-based water management plans and public health targets for Legionella in engineered water systems are constrained by fragmented and heterogeneous growth and inactivation kinetics. We conducted a meta-analysis of 25 growth and 39 thermal- and chemical-inactivation studies, fitting microbial persistence models to harmonize parameters. Nonlinear models outperformed first-order formulations, indicating that lag phases and resistant or protected subpopulations are central to Legionella persistence. Random forest analysis identified environmental and methodological drivers of variability based on 226 growth rates and reduction times for thermal (209) and chemical (135) inactivation. Growth was primarily governed by temperature, nutrient availability, and compatible Legionella-host pairings; thermal inactivation by quantification method, temperature, and turbidity; and chemical inactivation by inoculum size, disinfectant type, concentration, and host-associations. Accordingly, temperature-dependent growth parameters and exposure metrics for heat, free-chlorine, and monochloramine, expressed as TT (Temperature×time) and CT (Concentration×time), were derived as condition-specific inputs for predictive models. Growth optima around 37-40 °C, together with lag-time estimates, indicate that hot-water temperature setbacks and energy-saving practices may favor Legionella proliferation under repeated or prolonged lukewarm exposure. Culture- and viability-based TT differences highlight the need to consider viable‑but-non-culturable persistence in monitoring programs. CT comparisons suggest monochloramine may be advantageous because of its lower apparent sensitivity to host-associated protection. Although limited by restricted experimental conditions, the findings show that predictive models should account for microbial ecology, water matrix effects, and quantification endpoints. Future kinetic studies should prioritize realistic multi-host systems, strain pre-adaptation, complementary viability measurements, and standardized protocols and reporting to ensure reproducibility and enable robust system-level predictive modeling.

Legionella↗

PubMed2026

Antennal transcriptome analysis of chemosensory proteins in the raspberry weevil, Aegorhinus superciliosus (Coleoptera: Curculionidae).

Aegorhinus superciliosus (Coleoptera: Curculionidae) is a polyphagous pest of economic importance in southern Chile, the chemical ecology of which remains poorly characterized. Across insect species, chemosensory proteins, including odorant receptors (ORs), gustatory receptors (GRs), ionotropic receptors (IRs), odorant-binding proteins (OBPs), chemosensory proteins (CSPs), and sensory neuron membrane proteins (SNMPs), mediate the detection of chemical cues involved in host selection, reproduction, and other ecologically relevant behaviors. In this study, the antennal transcriptome of adult A. superciliosus was sequenced and analyzed using a de novo RNA-seq approach. Three independent biological replicates per sex were used for RNA-seq, and the same number of independent biological replicates was used for RT-qPCR validation; sequencing yielded 147,409,936 high-quality reads after quality filtering. A total of 112 candidate chemosensory genes were identified, comprising 43 ORs, 34 OBPs, 10 CSPs, 18 IRs, 5 GRs, and 2 SNMPs. Phylogenetic analyses assigned these candidate proteins to established clades, providing a comparative framework for functional inference for ORs and OBPs. Sex- and tissue-biased expression analyses revealed that several ORs, including AsupOR4, AsupOR19, and AsupOBP13, exhibit antennal enrichment and sex-specific expression patterns. Notably, AsupOR19 and AsupOBP13 displayed strong female-biased expression. In addition, transcripts of selected ORs and OBPs were detected in non-antennal tissues, such as the rostrum and legs, suggesting potential functional versatility beyond canonical olfaction. Together, these findings represent the first molecular identification of the chemosensory repertoire of A. superciliosus. This study establishes a foundation for reverse chemical ecology approaches aimed at identifying behaviorally active volatile organic compounds (VOCs) toward environmentally sustainable strategies for integrated pest management.

Animals↗

PubMed2026

Cooperative anaerobic catabolism of chlorinated organic compounds: implications for sustainable bioremediation.

Biodegradation research historically followed a reductionist approach focused on axenic (pure) cultures capable of catabolizing the specific contaminant(s) of interest. While this approach has substantially advanced our understanding of the microbiology, physiology, biochemistry, and genetics of contaminant degradation under laboratory conditions, it does not capture the complexity of natural and engineered environments. During in situ bioremediation, microbiomes are exposed to mixtures of contaminants, and microbial interactions profoundly influence contaminant transformation and fate. In anoxic environments, degradation of chlorinated compounds is often sustained by metabolic cooperation among taxonomically and physiologically distinct microorganisms. Through the exchange of metabolites such as hydrogen, formate, acetate, and other nutrients, microbial populations establish interdependent networks that overcome thermodynamic and physiological constraints, enabling self-sustaining systems of contaminant transformations that would be inefficient or impossible with individual organisms. We highlight examples of microbial interactions that underpin anaerobic catabolism of chlorinated contaminants, including systems resulting in self-sustained anaerobic bioremediation.

Biodegradation, Environmental↗

PubMed2026

Flux rewiring enables native D-glucosamine production in Escherichia coli.

D-Glucosamine is an industrially important amino sugar used in pharmaceuticals, nutraceuticals, and functional materials, yet its production remains dominated by chemical extraction from chitinous biomass, raising sustainability and allergen concerns. Escherichia coli natively synthesizes D-glucosamine directly from D-glucose through endogenous metabolism, revealing an underutilized amino sugar biosynthetic capability. Building on this native pathway, D-glucosamine production was enhanced through targeted genetic modifications and systematic optimization of nitrogen metabolism and cultivation conditions, reaching 9.2 g L-1 under shake-flask conditions. This work extends a phosphorylation-dephosphorylation strategy previously developed for neutral rare sugars to amino sugar biosynthesis, demonstrating the broader applicability of this metabolic design principle. Phosphatase identity emerged as a key control point for product formation: YbiV was the most effective phosphatase for selective D-glucosamine production, whereas alternative phosphatases redirected flux toward D-sedoheptulose. This enzyme-dependent flux partitioning further enabled tunable co-production of D-glucosamine and D-sedoheptulose. Native amino sugar biosynthesis in E. coli provides a controllable framework for producing chemically distinct sugars through endogenous metabolism and establishes a generalizable strategy for engineering amino sugar and other nitrogen-containing metabolite biosynthesis.

Escherichia coli↗

PubMed2026

Molecular mechanisms of natural de novo shoot organogenesis and their applications.

Natural de novo shoot organogenesis (DNSO) is the spontaneous regeneration of shoots from wound sites outside the shoot apical region through endogenous developmental programs. This regenerative capacity enables plants to recover from severe tissue damage by re-establishing the shoot-root axis. Here, we review current knowledge about the molecular mechanisms of natural DNSO, focusing on transcriptomic and physiological studies in model plants. Accumulating evidence suggests that natural DNSO proceeds through three sequential phases: (i) early wound responses, characterized by the activation of the WIND1-ESR1 module and the establishment of apical-basal auxin asymmetry; (ii) cellular proliferation driven by metabolic and cell-cycle reprogramming; and (iii) cytokinin-mediated establishment of shoot apical meristem identity. We also discuss how these mechanistic insights have been harnessed for practical applications, including tissue culture-free transformation systems such as the cut-dip-budding (CDB) method, and developmental reprogramming strategies that employ ectopic expression of developmental regulator (DR) genes to induce DNSO in otherwise recalcitrant species. Together, these advances illustrate how understanding natural regeneration can guide the development of simplified, broadly applicable plant transformation technologies.

Plant Shoots↗

PubMed2026

Innovations in microbial physical mutagenesis for food fermentation: An overview from traditional to emerging technologies.

Microbial strains serve as an important factor affecting fermentation efficiency and product quality. To obtain superior strains, mutation breeding is a classic strategy. Compared to chemical mutagenesis, physical mutagenesis directly induces genomic changes, providing notable advantages such as the elimination of chemical residues and environmental sustainability, hence rendering it a favored method for enhancing food-grade microorganisms. Conventional physical mutagenesis mostly depends on UV, rays, high pressure, or space radiation. As physical technologies advance, emerging methods such as ion implantation, plasma, microwave, ultrasound, and pulsed light are widely utilized for genetic modification. Mutagenesis technologies are progressively transitioning from single-effect to multi-effect synergy. Recent evaluations indicate that emerging technologies can enhance microbial mutation efficiency at the application level relative to established technologies. Nonetheless, the systematic clarification and comparative analysis at the mechanistic level remain inadequate, hindering intuitive comprehension of the qualities and distinctions across techniques. Furthermore, physical mutagenesis encounters several significant obstacles, such as cellular damage, limited rates of advantageous mutations, and laborious screening processes. This review carefully elucidates the mechanisms and properties of physical mutagenesis technology and delineates the distinctions among approaches through comparative analysis. Simultaneously, solutions for optimizing mutagenesis are presented to tackle the principal challenges mentioned above. This review aims to offer a theoretical foundation and practical guidance for the enhanced application of physical mutagenesis technologies in microbial breeding.

Mutagenesis↗

PubMed2026

Decoding the spatiotemporal patterns of food spoilage microbial communities: Integrating multi-omics and artificial intelligence to enable precision preservation.

In the global food supply chain, food wastage caused by spoilage has resulted in significant economic losses, food shortages, and environmental pressure. This process is fundamentally driven by the spatiotemporal dynamics of microbial communities. However, traditional research methods struggle to elucidate the complex mechanisms of spatial heterogeneity, interspecies interactions, and functional succession. This limits the development of effective preservation strategies. This review systematically reviews the cutting-edge progress of integrating multi-omics technologies and artificial intelligence (AI) to study food spoilage microbial communities, breaking through this bottleneck. We propose an intelligent theoretical framework that could potentially analyze microbial metabolic activities and predict dynamic shelf life if implemented. The conceptual framework integrates multidimensional data, including spatial metabolomics, temporal metatranscriptomics, single-cell transcriptomics, and longitudinal metagenomics. It can also be combined with AI models, such as graph neural networks. The article elaborates on the principles and applications of spatio-temporal monitoring technologies, such as nano secondary ion mass spectrometry, hyperspectral imaging, and the Internet of Things sensing. Through illustrative cases of typical perishable foods, it also explores how such a multi-omics - AI system might be applied to spoilage warning and precise intervention. Additionally, the article addresses the current challenges in data coverage, model generalization, and federated learning implementation. Then the research further explores emerging areas such as engineered probiotics, edge AI, and microfluidic sensing. These areas are targeted at transforming food preservation from an empirical control approach to a data-driven, precise regulatory framework. This transformation provides theoretical support and technical approaches for developing a smart, sustainable food preservation system.

Multiomics↗

PubMed2026

GATA2 deficiency: enhancer deregulation, immune surveillance failure, and clonal evolution.

Germline mutations in GATA2 cause a syndromic inborn error of immunity characterized by cytopenia, infections, immune dysregulation, and a marked predisposition to myelodysplastic syndrome and acute myeloid leukemia. Initially defined by the DCML phenotype-dendritic cell, monocyte, B- and NK-cell deficiency-GATA2 deficiency is now recognized as a disorder of global immune-hematopoietic homeostasis. Recent multi-omics and experimental models reveal enhancer-driven inflammatory rewiring, IRF8-dependent lineage imbalance, and premature hematopoietic aging. In parallel, adaptive immune defects, including impaired B- and T-cell development and function, contribute to defective immune surveillance. These alterations not only explain susceptibility to infection but also shape clonal evolution and malignant transformation. Clinically, improved risk stratification and transplant outcomes underscore the importance of early recognition and monitoring of immune dysfunction. GATA2 deficiency thus represents a paradigm linking immune dysregulation, inflammatory stress, and cancer predisposition.

Humans↗

PubMed2026

The science of Arabic coffee (Qahwa): from phytochemistry and nutritional profile to health benefits and safety evaluation.

Arabic coffee (Qahwa), a traditional beverage widely consumed in the Middle East, has attracted increasing scientific attention due to its distinctive phytochemical composition and associated health effects. This review provides an integrated analysis of Qahwa's nutritional profile, focusing on its key bioactive constituents, including chlorogenic acids, caffeine, diterpenes (cafestol and kahweol), and phenolic compounds. These constituents contribute to a range of biological activities, notably antioxidant, anti-inflammatory, hepatoprotective, and metabolic regulatory effects. The influence of technological variables, including roasting degree, brewing method, and bean origin, on the chemical composition and functional properties is critically examined. Safety concerns, particularly acrylamide formation and mycotoxin contamination, are also discussed. Although emerging data support Qahwa's potential as a functional beverage, further research is required to clarify dose-response relationships, synergistic interactions, and long-term health outcomes. This work highlights Qahwa as a promising candidate for food and nutraceutical applications, warranting standardized compositional profiling and toxicological evaluation.

Humans↗

PubMed2026

Comprehensive study on pesticide residues and mycotoxins in freeze-dried strawberries and raspberries.

Freeze-dried fruit has gained popularity because it preserves the flavour and nutritional value of fresh fruit while providing extended shelf life. Despite this, there are concerns regarding its chemical safety. This study evaluated 58 freeze-dried fruit products from the Czech retail market, focusing on potential contamination. Pesticide residues and mycotoxins were determined using LC-MS/MS and GC-MS/MS. Overall, 111 pesticide residues (or their metabolites) and 3 mycotoxins were quantified. After applying processing factors, 12 pesticide residues exceeded EU maximum residue limits. Prohibited substances, including carbofuran, omethoate, and haloxyfop, were detected. Tenuazonic acid was found in 71% of samples, while alternariol and tentoxin were detected less frequently. More than half (54%) of strawberry samples contained 10 or more pesticide residues, indicating potential cumulative exposure concerns, particularly for children with lower body weight. These findings highlight the need for continued monitoring of freeze-dried fruits and further assessment of dietary exposure.

Pesticide Residues↗

PubMed2026

A review on the environmental distribution, toxic effects, bioaccumulation characteristics and risk assessment of short-chain chlorinated paraffins.

Chlorinated paraffins (CPs) are synthetic chemicals, widely used as flame retardants and plasticizers. As emerging contaminants, short chain chlorinated paraffins (SCCPs) have attracted tremendous attention due to their persistence, chronic toxicity, long-range transport potential and bioaccumulation potential. This review synthesizes global data on SCCPs' environmental occurrence, toxicological impacts, and bioaccumulation characteristics. SCCPs are ubiquitously detected in various environmental media, including water, sediment, air, soil, and biota. Ecotoxicological studies reveal that SCCPs have lethality, carcinogenicity, growth and developmental toxicities, organs toxicities and endocrine-disrupting effects across species, which pose risks to ecological systems and human health. In addition, the bioaccumulation effects of SCCPs in terrestrial and aquatic ecosystems were analyzed, and proposed the key factors affecting the bioaccumulation of SCCPs. Finally, the risk assessment of SCCPs contamination in the surface water and the soil was carried out, and all soil and most water bodies were found to be low risk. The present study could provide scientific basis and reference for environmental management of CPs products.

Paraffin↗

PubMed2026

From fear to empowerment: the impact of employees AI awareness on workplace well-being - a new insight from the JD-R model.

PURPOSE: The primary purpose of the study was to explore the impact of health workers' awareness of artificial intelligence (AI) on their workplace well-being, addressing a critical gap in the literature. By examining this relationship through the lens of the Job demands-resources (JD-R) model, the study aimed to provide insights into how health workers' perceptions of AI integration in their jobs and careers could influence their informal learning behaviour and, consequently, their overall well-being in the workplace. The study's findings could inform strategies for supporting healthcare workers during technological transformations. DESIGN/METHODOLOGY/APPROACH: The study employed a quantitative research design using a survey methodology to collect data from 420 health workers across 10 hospitals in Ghana that have adopted AI technologies. The study was analysed using OLS and structural equation modelling. FINDINGS: The study findings revealed that health workers' AI awareness positively impacts their informal learning behaviour at the workplace. Again, informal learning behaviour positively impacts health workers' workplace well-being. Moreover, informal learning behaviour mediates the relationship between health workers' AI awareness and workplace wellbeing. Furthermore, employee learning orientation was found to strengthen the effect of AI awareness on informal learning behaviour. RESEARCH LIMITATIONS/IMPLICATIONS: While the study provides valuable insights, it is important to acknowledge its limitations. The study was conducted in a specific context (Ghanaian hospitals adopting AI), which may limit the generalizability of the findings to other healthcare settings or industries. Self-reported data from the questionnaires may be subject to response biases, and the study did not account for potential confounding factors that could influence the relationships between the variables. PRACTICAL IMPLICATIONS: The study offers practical implications for healthcare organizations navigating the digital transformation era. By understanding the positive impact of health workers' AI awareness on their informal learning behaviour and well-being, organizations can prioritize initiatives that foster a learning-oriented culture and provide opportunities for informal learning. This could include implementing mentorship programs, encouraging knowledge-sharing among employees and offering training and development resources to help workers adapt to AI-driven changes. Additionally, the findings highlight the importance of promoting employee learning orientation, which can enhance the effectiveness of such initiatives. ORIGINALITY/VALUE: The study contributes to the existing literature by addressing a relatively unexplored area - the impact of AI awareness on healthcare workers' well-being. While previous research has focused on the potential job displacement effects of AI, this study takes a unique perspective by examining how health workers' perceptions of AI integration can shape their informal learning behaviour and, subsequently, their workplace well-being. By drawing on the JD-R model and incorporating employee learning orientation as a moderator, the study offers a novel theoretical framework for understanding the implications of AI adoption in healthcare organizations.

Humans↗

PubMed2026

Multi-omic biomarkers in cardiovascular disease: Discovery to clinical translation.

Cardiovascular disease (CVD) remains the leading cause of mortality worldwide, necessitating improved risk stratification and early detection strategies. Multiomics approaches that integrate genomics, transcriptomics, proteomics, metabolomics, and epigenomics offer unprecedented opportunities for biomarker discovery and precision medicine in cardiovascular care. This narrative review examines the current landscape of multiomics biomarkers for CVD, tracing their evolution from discovery to clinical translation. We synthesize evidence from recent studies evaluating the clinical utility of integrated omics approaches across diverse cardiovascular conditions, including atherosclerotic cardiovascular disease, heart failure, and atrial fibrillation. High-throughput proteomics has identified novel protein signatures that enhance cardiovascular risk prediction beyond traditional risk factors. Metabolomics has revealed pathway-specific biomarkers, including trimethylamine N-oxide and lipid species, associated with atherogenesis. Polygenic risk scores derived from genomic data demonstrate incremental value when combined with clinical risk scores. Multiomics biomarkers represent a transformative approach to cardiovascular risk assessment and disease management.

Humans↗

PubMed2026

Metabolic engineering of Candida yeasts for biotechnological applications.

Candida yeasts represent a versatile yet underexploited platform for industrial biotechnology. These yeasts utilize a remarkably broad range of carbon sources, particularly for hydrophobic carbon sources, coupled with robust growth and diverse biosynthetic capacities, making them promising hosts for sustainable production of chemicals, fuels, and proteins. Despite these advantages, industrial deployment of Candida species has been hindered by concerns regarding opportunistic pathogenicity and the historical lack of efficient genetic manipulation tools, leading to a substantial gap between metabolic potential and practical utilization. Recent advances in functional genomics, genome editing, and systems metabolic engineering are rapidly overcoming these barriers, enabling more precise and efficient strain development. In this review, we systematically summarize recent progress in the metabolic engineering of Candida species as microbial cell factories, with particular emphasis on expanding genetic toolkits, utilizting renewable and non-conventional carbon sources, and biosynthesizing high-value compounds. In addition, we propose a biosafety-oriented classification framework to support their safe industrial deployment. Finally, we discuss current challenges and emerging opportunities, emphasizing that the synergy of synthetic biology and artificial intelligence-driven design holds the key to unlocking the biotechnological potential of Candida yeasts.

Candida↗