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PubMed2026

A system-level metastable model of cancer evolution: integrating replication stress, cell cycle deregulation and chromosomal instability.

INTRODUCTION: Cancer cell proliferation occurs within the context of persistent genomic instability. In this review, we propose the RS-CCD-CIN axis as a systems-level framework in which replication stress (RS), cell cycle deregulation (CCD) and chromosomal instability (CIN) form an interdependent triad that shapes tumour evolution. This axis represents a constrained metastable state in which genomic instability is tolerated and buffered. The objective of this review is to synthesize the current understanding of how the RS-CCD-CIN axis contributes to tumour heterogeneity, adaptability and therapy response. DISCUSSION: Evidence indicates that RS, CCD and CIN operate as a dynamic, interconnected network rather than as independent processes. Replication stress induces DNA damage and mutagenesis, while partial checkpoint disruption permits cells with unresolved lesions to proliferate. Chromosomal instability generates both structural and numerical alterations, contributing to intratumoural heterogeneity. Together, these processes facilitate adaptation to environmental and therapeutic pressures. Extrachromosomal DNA, micronuclei formation and cytosolic DNA signalling, including the cGAS-STING pathway, connect genomic instability to adaptive responses and immune modulation. Single-cell and spatial profiling reveal temporal and spatial variability in RS, CCD and CIN states, highlighting the limitations of static biomarkers. Therapeutically, targeting individual components often yields limited durability, whereas approaches that simultaneously perturb multiple aspects of the RS-CCD-CIN axis may improve clinical outcomes. CONCLUSIONS: This review highlights the RS-CCD-CIN axis as a fragile and metastable architecture that supports cancer evolution, while also being susceptible to collapse. A deeper understanding of this interconnected framework may inform the development of therapeutic strategies and enhance the management of resistance.

Humans↗

PubMed2026

Comparing trajectories of cognitive functioning in treatment-resistant and non-resistant depression: a multicentre linear mixed-effects analysis.

BACKGROUND: Impaired cognitive functioning is a severe symptom in major depressive disorder (MDD). Recent evidence suggests it may be a central characteristic in its treatment resistant form (TRD), potentially constituting a clinical marker for treatment resistance and a target amenable to intervention. To date, cognitive functioning in TRD remains poorly understood and longitudinal investigations are scarce. METHODS: This observational prospective cohort study, including 320 patients diagnosed with MDD from the multicentre PROMPT study, examined differences in cognitive functioning between 118 TRD and 202 non-TRD patients over a period of twelve weeks in a real-world setting, using linear mixed modelling. Patients that failed to respond to at least two prior antidepressants trials at baseline were classified as TRD. RESULTS: TRD patients showed significantly poorer baseline performances than non-TRD patients in attention/processing speed (β = -0.45; 95%CI[-0.70, -0.19]; FDR-p = 0.003) and verbal memory (β = -0.45; 95%CI[-0.72, -0.18]; FDR-p = 0.003). Significant time × group interactions were observed in motor speed and verbal fluency tasks. Post-hoc-analyses revealed stagnation in TRD patients and significant improvement in non-TRD patients. Across all other tasks improvement was observed in both groups, and random effects showed large heterogeneity between patients, indicating notable individual differences in cognitive performances. CONCLUSIONS: The results suggest distinct recovery patters between non-TRD and TRD patients, and diminished functioning in TRD patients at the domain level. However, intact and diminished performances likely occur in both groups, warranting further investigation of cognitive heterogeneity. These short-term findings highlight the need for more comprehensive longitudinal research on cognition in TRD.

Humans↗

PubMed2026

Single-cell transcriptome revealed the aberrant keratinocytes activation in antigen presentation in atopic dermatitis.

BACKGROUND: Atopic dermatitis (AD), a common chronic inflammatory skin disease, has been extensively studied using single-cell genomics. However, keratinocytes, as key effector cells in AD, have underlying mechanisms remain incompletely understood and require further investigation. METHODS: We integrated single-cell transcriptomic data from skin tissues of healthy controls, chronic active AD patients, spontaneously healed AD (SHAD) patients, and an ovalbumin-induced AD mouse model. The study particularly emphasized the gene expression and cellular dynamics of keratinocytes across the different groups, as well as their interactions with immune cells. RESULTS: Compared to healthy controls, we observed significant changes in the keratinocyte transcriptome, cellular state, and keratinocyte-immune cell ligand-receptor interactions in AD skin, particularly the marked activation of genes involved in antigen processing and presentation. Interestingly, such gene activation was not observed in keratinocytes from the ovalbumin-induced AD mouse model, despite its phenotype closely resembling human AD. Furthermore, in SHAD, we identified a recovery of both the ligand-receptor interaction patterns and antigen processing and presentation genes, accompanied by a notable shift in the transcriptome. This involved a significant downregulation of genes related to cytoplasmic transcription and oxidative phosphorylation. Notably, this pattern was not observed in the self-healing mouse model following the removal of ovalbumin stimulation. CONCLUSION: Our results suggest that the persistent activation of antigen processing and presentation pathways in keratinocytes may be a key driver of chronic inflammation in AD. Therefore, redirecting anti-allergic therapeutic strategies from solely targeting immune cells to targeting of keratinocyte-mediated antigen presentation may offer a more effective approach. Furthermore, we raise concerns about the use of ovalbumin-induced mouse models to recapitulate human chronic AD, as the underlying mechanisms may differ significantly.

Dermatitis, Atopic↗

PubMed2026

Pre-clinical evaluation of the anticaries effect of an experimental Malva sylvestris extract mouthwash using a cariogenic model in situ.

OBJECTIVE: The aim of this study was to evaluate the antimicrobial and anticariogenic potential of Malva sylvestris extract on enamel and dentin in situ. METHODS: A double-blind crossover in situ study was conducted with 12 participants wearing palatal appliances containing two bovine enamel and two dentin specimens per 3 phases, a total of 72 enamel and dentin specimens. Biofilm formation and daily sucrose exposure were allowed. Treatments were applied twice daily in three phases: Malva sylvestris (2.5%, MS); fluoride (225 ppm, F); and placebo (P). After seven days, biofilm was collected from the bovine specimens for analysis of Lactobacillus spp. and mutans streptococci by Colony Forming Unit counts (CFU log₁₀/mL). Dental demineralization of the bovine specimens was assessed by transverse microradiography (TMR). RESULTS: MS did not reduce Lactobacillus spp. counts (CFU log₁₀/mL: enamel 6.63±0.81; dentin 6.68±0.92) compared to P (6.63±0.70; 6.62±0.51). F also did not differ (6.29±0.75; 6.32±0.41; ANOVA/Tukey, p>0.38). Mutans streptococci data were inconclusive. In enamel, both MS (2320.8±768.2 %vol·µm; 101.6±27.0 µm) and F (1777.3±733.3 %vol·µm; 95.8±23.5 µm) significantly reduced integrated mineral loss and lesion depth compared to P (3517.2±1119.9 %vol·µm; 138.6±19.5 µm; ANOVA/Tukey, p≤0.0003). In dentin, MS significantly reduced integrated mineral loss (322.5 [250-580] %vol·µm) and lesion depth (30.1 [15-42.2] µm) compared to P (880 [580-1705]; 58.3 [32.2-88.6] µm; Kruskal-Wallis/Dunn, p≤0.001), while F (587.5 [305-720]; 25.2 [16.5-38.8] µm) did not differ significantly (p>0.05). CONCLUSIONS: Malva sylvestris extract had no antimicrobial effect on Lactobacillus spp. counts, but significantly reduced enamel and dentin demineralization, showing anticaries effect comparable to fluoride. CLINICAL RELEVANCE: Malva sylvestris has demonstrated promising biological activity. This study investigates the antimicrobial efficacy of Malva sylvestris against cariogenic microorganisms in situ. Our findings provide relevant evidence that M. sylvestris exert significant anticaries effects using an in situ model.

Biofilms↗

PubMed2026

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

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

Pseudouridine↗

PubMed2026

A conserved distal-tail helical extension defines a tailspike attachment architecture in Gram-negative siphophages.

Rapid growth of bacteriophage genome collections has outpaced functional annotation of tail-tip proteins, limiting comparative analysis of host-recognition structures. Starting from a shared distal-tail gene organization in the Salmonella phages 9NA and Jersey, I developed a morphogenetic bioinformatic framework integrating gene synteny, sequence comparison, profile hidden Markov model (HMM) screening, structural evidence, structure-aware searching, and AlphaFold modeling. Comparison with the experimentally characterized lambda and Sf11 tail assemblies identified a predominantly alpha-helical C-terminal extension of the distal-tail (DT) protein associated with tailspike attachment, termed the distal-tail helical extension (DT-helix). Screening 541,986 proteins from 5167 complete NCBI RefSeq tailed-phage genomes, followed by evidence-based evaluation of sequence, genomic context, and structural architecture, identified 165 curated DT-helical-extension-associated phages. Their DT proteins segregated into six sequence groups. In the four principal multi-member groups, cognate tailspikes showed group-specific conservation in proximal N-terminal regions but substantially greater downstream diversity, consistent with sequence constraint at the DT-tailspike attachment boundary. A complementary ProstT5/Foldseek search supported the established groups but revealed no convincing additional highly divergent family. Together with the experimentally characterized Sf11 attachment interface, these findings define a recurrent morphogenetic architecture linking conserved distal-tail scaffolds to more variable receptor-binding proteins across siphophages infecting Gram-negative bacteria. Although universal exchangeability is not established, the identified scaffold-receptor-binding boundaries provide a framework for molecular characterization and rational phage engineering. Accession-level information for the 165 curated phages is available through PhageTailDB.

Viral Tail Proteins↗

PubMed2026

Comprehensive source-risk assessment of organophosphate esters in surface water of the Dianchi Lake Basin, Yunnan, China.

Organophosphate esters (OPEs), widely used as flame retardants and plasticizers, have been increasingly detected in aquatic environments. However, investigations of their distribution in high-altitude plateau lakes remain scarce. Identifying and quantifying the sources and associated risks of OPEs are crucial for subsequent water environment management. In this study, an integrated source-risk analysis approach was employed by combining the Positive Matrix Factorization (PMF) model, the Geodetector (GD) model, and risk quotient (RQ). Analysis of 14 OPEs in surface waters of the Dianchi Lake Basin (DLB) revealed 12 detectable compounds, with total OPEs concentrations (ΣOPEs) ranging from not detected (ND)-64.6 ng/L during the wet season and ND-35.8 ng/L during the dry season. Elevated ΣOPEs were primarily observed at inflow sites in the northern part of the lake and in urban rivers. Source apportionment indicated four major contributing sources: agricultural films containing flame-retardant and plasticizer additives, traffic-related particulate emissions, releases from household and personal care products, and industrial production and applications of flame retardants in plastics, electronics, and related products (the predominant source). The ecological impact caused by OPEs ranges from no risk to low risk, with tris(2-chloroethyl) phosphate emitted from industrial source being the primary driver of potential environmental risk. These findings highlight the necessity of prioritizing industrial sources in future management strategies. Overall, this study provides a methodological framework for source apportionment and risk assessment of OPEs and offers scientific evidence to support environmental management of OPEs in the DLB.

Environmental Monitoring↗

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

Factors associated with additional intervention requirement following ESWL in pediatric patients with urolithiasis.

OBJECTIVE: To identify predictors of additional intervention following extracorporeal shock wave lithotripsy (ESWL) in pediatric patients and to develop a clinically applicable predictive model. MATERIALS AND METHODS: This retrospective cohort study included 647 pediatric patients who underwent ESWL between 2015 and 2025. Demographic, clinical, and radiological variables were analyzed. Univariable and multivariable logistic regression analyses were performed to identify independent predictors of additional intervention. Model performance was evaluated using receiver operating characteristic curve analysis. RESULTS: Additional intervention was required in 65 patients (10.0%). On multivariable analysis, stone size 10-20 mm (OR: 3.04, p = 0.003), moderate (OR: 2.16, p = 0.049) and severe hydronephrosis (OR: 6.05, p < 0.001), and multiple stones (OR: 3.52, p = 0.030) were identified as independent risk factors. Increasing age (OR: 0.84, p = 0.026), history of urolithiasis (OR: 0.41, p = 0.006), and lower calyx location (OR: 0.14, p = 0.034) were associated with a reduced risk. The model demonstrated good discriminative performance (AUC: 0.794), with a sensitivity of 72% and specificity of 75%. Internal validation using bootstrap resampling demonstrated stable model performance, yielding a corrected AUC of 0.732. CONCLUSION: Stone burden, hydronephrosis severity, and stone multiplicity are key determinants of additional intervention after ESWL in pediatric patients. The proposed model shows good predictive performance and may support individualized risk stratification and clinical decision-making.

Humans↗

PubMed2026

Bioprospecting microbial genomes to expand the biocatalytic toolbox of rubber oxygenases.

A set of rubber oxygenases was discovered through phylogenetic analysis and AI-based structural modeling of complexes of the putative enzymes with a substrate mimicking cis-1,4-polyisoprene. Sixteen candidate proteins were selected from thermophilic microorganisms, all sequence-related to the Latex clearing protein from Streptomyces sp. K30 (LcpK30). Sequence truncation and solubility tags were then evaluated to enhance protein expression, with the SUMO tag proving to be the most effective. Including LcpK30, nine heme-containing oxygenases were successfully expressed in E. coli NEB 10-beta cells, purified (35-157 mg L-1 yield) and characterized. Steady-state kinetics revealed significant rubber latex-degrading properties for six of them, with the truncated SUMO-fused LcpK30 (SUMO-LcpK30T) showing activity in agreement with literature. Notably, the catalytic efficiencies of all the expressed homologs lay within one order of magnitude and the oxygenase from Thermomonospora echinospora was found to be particularly promising in terms of activity, especially at high latex concentrations (more than 1% w/v). The analysis of reaction mixtures by both HPLC and HPLC-MS confirmed the oxidation of cis-1,4-polyisoprene to form the expected isoprenoid oligomers (n = 2-12), whose distribution was consistent with the usual endo-type cleavage pattern in all but one case. This bioprospecting effort afforded a platform of new rubber-degrading enzymes with diverse efficiencies and product profiles, capable of adapting to targeted applications.

Oxygenases↗

PubMed2026

Three-dimensional source apportionment and quantitative characterization of horizontal and vertical transport fluxes of O3 and its precursors in the Beijing-Tianjin-Hebei region, China.

Persistent surface ozone (O3) pollution in the Beijing-Tianjin-Hebei (BTH) region is driven by coupled precursor emissions and multi-scale transport, yet its altitude-dependent transport and source contributions remain insufficiently quantified. Here we integrated the Weather Research and Forecasting and the Comprehensive Air Quality Model with Extensions with the Ozone Source Apportionment Technology and a quantitative transport-flux framework to characterize three-dimensional source apportionment and horizontal/vertical fluxes of O3, Volatile Organic Compounds‌ (VOCs), and Nitrogen Oxides (NOx) across dynamic meteorological scenarios. Simulations showed that VOCs and NOx were dominated by local emissions near the surface (73.61 %-82.18 %), whereas surface O3 was primarily controlled by regional transport, with local contributions of only 11.01 %-13.75 %. Notably, the transport dominance further strengthened with altitude, exceeding 93 % at 1.8 km. Industrial and transportation emissions together contributed more than 75 % of precursor emissions and account for approximately 80 % of O3 formation, while favorable/unfavorable meteorological years modulated long-range transport efficiency and the vertical distribution of contributions. Horizontal flux analysis highlighted three major pathways (Northwest-Southeast, Southeast-Northwest, and Southwest-Northeast), with Shijiazhuang serving as a critical pollutant "sink" across altitude layers. Vertical fluxes revealed an altitude transition near 600 m: net downward transport dominated below 600 m, whereas enhanced summer convection promoted upward transport above 600 m. These results support altitude-dependent, scenario-specific strategies for coordinated regional O3 mitigation in the BTH region.

Ozone↗

PubMed2026

Internet-based acceptance and commitment therapy (iACT) improves professional psychological help-seeking attitudes: A randomized controlled trial.

BACKGROUND: Professional psychological help-seeking attitudes are crucial for addressing mental health challenges, yet the mechanisms underlying their improvement through internet-based interventions remain poorly understood. OBJECTIVE: This randomized controlled trial aimed to (1) evaluate the efficacy of Internet-based Acceptance and Commitment Therapy (iACT) in enhancing professional help-seeking attitudes, and (2) elucidate the longitudinal mediating roles of psychological rigidity and self-stigma. METHODS: A total of 91 male participants (Mean Age = 21.09) were randomly assigned to either a 12-day iACT intervention group (n = 46) using a self-developed mobile application or a waitlist control group (n = 45). Psychological flexibility, rigidity, self-stigma, and help-seeking attitudes were measured at four time points: baseline, mid-intervention (Day 6), post-intervention (Day 12), and 1-month follow-up. Data were analyzed using repeated-measures ANOVA and latent growth modeling. RESULTS: Intention-to-treat analysis revealed the iACT group showed greater improvements in help-seeking attitudes than controls (F (3,87) = 5.95, p < 0.001), with medium-to-large between-group effects at post-test for reducing psychological rigidity (d = -0.77, 95% CI [-1.19, -0.34]) and self-stigma (d = -0.88, 95% CI [-1.31, -0.45]). Latent growth modeling revealed a sequential mediation effect: the iACT intervention reduced psychological rigidity (β = -0.53, SE = 0.12), which in turn reduced self-stigma (β = 0.61, SE = 0.09) and improved help-seeking attitudes (β = 0.47, SE = 0.08). CONCLUSION: This study provides the first evidence that a self-guided iACT mobile intervention can effectively enhance professional help-seeking attitudes by reducing psychological rigidity, which in turn alleviates self-stigma. The developed app offers a scalable solution to overcoming stigma-related barriers to mental health care.

Humans↗

PubMed2025

Enhanced fracture detection on radiographs with AI assistance for clinicians: a systematic review and meta-analysis.

BACKGROUND: Emergency radiographic interpretation for fractures is prone to missed or misdiagnoses. Artificial intelligence (AI) is expected to become a powerful tool to assist clinicians in fracture detection. PURPOSE: A systematic review and meta-analysis was performed to assess whether AI improves clinicians' ability to detect fractures on radiographs. MATERIALS AND METHODS: A literature search was conducted in PubMed, Web of Science, and Cochrane Library for studies published between January 1, 2010, and October 10, 2025. A meta-analysis of diagnostic accuracy studies was performed using a Summary Receiver Operating Characteristic (SROC) curve. The quality of included studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) tool. Subgroup analysis and meta-regression were conducted to explore potential sources of heterogeneity. RESULTS: A total of 26 studies were included . The pooled sensitivity of clinicians increased from 77% (95% CI: 72-81) to 87% (95% CI: 83-90) with AI assistance, while the pooled specificity improved from 88% (95% CI: 85-90) to 92% (95% CI: 89-94). The corresponding AUC values were 0.90 (95% CI: 0.87-0.92) before and 0.95 (95% CI: 0.93-0.97) after AI assistance. Eight studies were rated as high risk of bias. Subgroup analysis and meta-regression identified potential sources of heterogeneity, including fracture location, AI model type, high risk of bias, and reference standards. CONCLUSION: AI assistance significantly improves clinicians' diagnostic performance in detecting fractures on radiographs for extremity and trunk fractures.

Humans↗

PubMed2026

An individualized nomogram for predicting progression-free survival in systemic anaplastic large cell lymphoma: a multicenter, retrospective, and internally validated study.

OBJECTIVES: To develop an individualized nomogram for predicting disease progression risk in systemic anaplastic large cell lymphoma (sALCL). METHODS: Independent predictors of progression-free survival (PFS) were identified using Cox regression in a multicenter retrospective cohort of 109 sALCL patients (2010-2022). These were incorporated into a three-factor nomogram, evaluated via bootstrapped internal validation (1000 resamples), ROC analysis, C-index, decision curve analysis (DCA), and clinical impact curve (CIC). RESULTS: A total of 29 PFS events occurred during a median follow-up of 31 months. Multivariable modelling selected serum β2-microglobulin elevation, extranodal disease, and front-line chemotherapy choice (CHOP versus CHOPE or BV+CHP) as autonomous progression drivers. Upon internal bootstrap validation, the nomogram yielded strong prognostic accuracy, achieving AUCs of 0.81, 0.85 and 0.87 for 1-, 3- and 5-year progression-free survival, alongside a corrected C-index of 0.779 (95% CI: 0.699 - 0.861). Calibration plots showed close agreement between predicted and observed outcomes, while DCA confirmed superior net clinical benefit versus conventional IPI or Ann Arbor stratification across multiple decision thresholds. CONCLUSION: This first sALCL-specific nomogram integrates clinical and treatment variables to provide personalized PFS risk estimation. While internally validated, this exploratory, observation-based tool requires external validation and recalibration in prospective cohorts before clinical implementation.

Humans↗

PubMed2026

Enhancement of secondary organic aerosol formation from isoprene photooxidation by ammonia.

Ammonia (NH3) can participate in atmospheric secondary organic aerosol (SOA) formation by reacting with organic acids and carbonyl compounds in particle phase, but its influence on the gas phase chemistry remains unclear. This study performed a series of smog chamber experiments to investigate the influence of NH3 on the formation of SOA from isoprene photooxidation by OH radicals. Both gas and particle phase products were measured with a series of state-of- art instruments including a nitrate ion chemical ionization mass spectrometer (nitrate-CIMS) and high-resolution time-of-flight aerosol mass spectrometer (HR-TOF-AMS). Our results showed that in the presence of NH3 SOA in the chamber significantly increased, along with an enhanced oxidation of isoprene. CIMS analysis further showed that NH3 in the chamber homogeneously reacts not only with gas-phase organic acids but also with gaseous low volatility oxygenated organic molecules (OOMs) to generate extremely low volatility and ultralow volatility NH3-OOMs clusters. Quantum chemical calculation showed that NH3 can spontaneously interact with OOMs to form NH3-OOMs clusters by forming hydrogen bonds with RCOOH, R-OOH, and R-OH. These clusters can promote new particles formation and particle growth through nucleation and condensation, directly enhancing the isoprene SOA production with a contribution of 78% to the enhanced SOA. Moreover, the formation of NH3-OOMs clusters also results in more isoprene consumed by OH radicals, indirectly increasing the SOA production with a contribution of 22 % to the enhanced SOA. Our work for the first time clarified a synergetic effect of NH3 on isoprene SOA formation, which should be accounted for by models.

Aerosols↗

PubMed2026

Glymphatic dysfunction mediates inflammation-driven vascular burden and cognitive decline in cerebral small vessel disease.

BACKGROUND: Cerebral small vessel disease (CSVD) is increasingly recognized as a disorder involving microvascular dysfunction, impaired perivascular clearance, and inflammatory processes. However, how systemic inflammatory burden, neurovascular coupling (NVC), glymphatic MRI markers, vascular lesion burden, and cognition are interrelated remains unclear. MATERIALS AND METHODS: In this prospective study, 155 patients with CSVD and 70 healthy controls (HCs) underwent multimodal MRI. NVC was quantified using the cerebral blood flow/fractional amplitude of low-frequency fluctuations ratio. Glymphatic function was assessed via the diffusion tensor image analysis along the perivascular space (ALPS) index, choroid plexus volume (CPV), and perivascular space (PVS) fractions. Structural equation modeling (SEM) was employed to evaluate the direct and indirect effects of inflammatory markers on vascular burden and cognitive performance. RESULTS: Patients with CSVD exhibited significantly diminished NVC (specifically in the right median cingulate and left frontal gyri) and impaired glymphatic function (lower ALPS-index; higher CPV and PVS fractions) compared to HCs. SEM revealed that inflammatory biomarkers exerted both a direct effect on vascular burden and a substantial indirect effect (accounting for 66.3% of the total effect) mediated through two pathways: a single-mediation path via glymphatic function (42.8%) and a serial-mediation path via NVC and glymphatic function (23.5%). Increased vascular burden was significantly associated with poorer cognitive performance. CONCLUSION: Inflammation drives CSVD progression and cognitive decline primarily through the disruption of NVC and glymphatic clearance mechanisms. These findings highlight glymphatic dysfunction as a critical mediator of inflammation-related structural brain damage.

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

Psychological distress and incident cardiovascular disease independent of life's essential 8: a prospective cohort study.

BACKGROUND: Although psychological stress has emerged as an important determinant of cardiovascular disease (CVD) risk, it remains excluded from the recently updated cardiovascular health (CVH) metrics, known as Life's Essential 8 (LE8). This study aimed to examine the association between psychological distress and the incidence of CVD, independent of Life's Essential 8 metrics, in a large Korean adult population. METHODS: This study included 6,410 participants from the Korean Genome and Epidemiology Study Ansan-Ansung cohort, who had no history of CVD and had complete baseline data on psychological distress and Life's Essential 8 cardiovascular health (LE8 CVH) metrics. Psychological distress was assessed using the Psychosocial Wellbeing Index Short Form (PWI-SF). CVD events were identified based on participants' self-reports of physician-diagnosed conditions: myocardial infarction, stroke, coronary artery disease, and congestive heart failure. Cox proportional hazards models were used to examine the association between PWI-SF scores and incident CVD, adjusting for age, sex, residential area, educational attainment, household income, and LE8 CVH metrics. RESULTS: During a median follow-up of 13.8 years, 500 new cases of CVD were identified. Higher PWI-SF scores were independently associated with an increased risk of CVD after adjusting for LE8 CVH metrics and other potential confounders (hazard ratio: 1.321; 95% confidence interval: 1.067-1.636; p = 0.011). CONCLUSION: These findings suggest that higher levels of psychological distress are independently associated with an increased risk of CVD, even after accounting for established LE8 CVH metrics. Incorporating psychological distress into future CVH assessments may enhance risk stratification and prevention strategies.

Humans↗