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PubMed2026

Long-term safety of oral orforglipron in Japanese participants with type 2 diabetes (ACHIEVE-J): a multicentre, randomised, open-label, parallel-group phase 3 trial.

BACKGROUND: Orforglipron, an oral GLP-1 receptor agonist, requires further evaluation in east Asian populations with type 2 diabetes, given this group's distinct pathophysiological characteristics. This study aimed to assess orforglipron as add-on treatment to diet and exercise alone or to oral antihyperglycaemic medications in Japanese participants with type 2 diabetes. METHODS: This multicentre, randomised, open-label phase 3 study was conducted in 40 medical research centres and hospitals in Japan. Adults with type 2 diabetes and elevated glucose levels managing their condition with diet and exercise alone or with one or two oral antihyperglycaemic medications were assigned (1:1:1) via computer-generated random sequence to receive once-daily oral orforglipron (3 mg, 12 mg, or 36 mg). Randomisation was stratified by background therapy, baseline HbA1c (≤8·5% or >8·5%), and metformin use (yes vs no; applied only to α-glucosidase inhibitors, thiazolidinedione, and glinides). Investigators, participants, and site staff were not masked to treatment. The primary endpoint was safety for 52 weeks, assessed in all randomly assigned participants who received at least one dose of orforglipron. This study is registered with ClinicalTrials.gov, NCT06010004 (ACHIEVE-J). FINDINGS: Between Sept 28, 2023, and June 5, 2025, 450 participants were screened and 401 were randomly assigned to three groups (3 mg, n=132; 12 mg, n=135; and 36 mg, n=134). 352 (88%) completed study treatment. 339 participants (85%, 95% CI 80·7-87·8) had at least one treatment-emergent adverse event (TEAE), more frequently in the 36-mg group (118 [88%, 95% CI 81·5-92·5]) than in the 3-mg (107 [81%, 73·5-86·8]) and 12-mg (114 [84%, 77·4-89·6]) groups. Most TEAEs were of mild (267 [67%, 61·8-71·0]) or moderate (63 [16%, 12·5-19·6]) severity. Discontinuations due to an adverse event occurred in 19 of 134 participants (14%, 95% CI 9·3-21·1) in the 36-mg group compared with seven of 132 (5%, 2·6-10·5) in the 3-mg group and 11 of 135 (8%, 4·6-14·0) in the 12-mg group. Across treatment groups, gastrointestinal symptoms were the most common TEAEs leading to study treatment discontinuation (3 mg: 5 [3·8%, 1·6-8·6]; 12 mg: 8 [5·9%, 3·0-11·3]; and 36 mg: 11 [8·2%, 4·7-14·1]). Level 2 (blood glucose <54 mg/dL) hypoglycaemia events occurred in three of 135 participants in the 12-mg group (2%, 0·8-6·3) and in three of 134 in the 36-mg group (2%, 0·8-6·4) groups. No level 3 (severe) hypoglycaemia events occurred. Outcomes were generally similar across background therapies. INTERPRETATION: Treatment with orforglipron in combination with diet and exercise alone or one or two oral antihyperglycaemic medications for 52 weeks demonstrated an acceptable safety profile in Japanese adults with type 2 diabetes. FUNDING: Eli Lilly. TRANSLATION: For the Japanese translation of the abstract see Supplementary Materials section.

Aged↗

PubMed2026

The role of artificial intelligence in the diagnosis and prognosis of traumatic brain injury based on brain CT scans: a systematic review.

Traumatic brain injury (TBI) is a leading cause of emergency department visits and a major contributor to injury-related mortality and long-term neurological disability. Non-contrast computed tomography (CT) is the gold-standard imaging modality for the rapid diagnosis of TBI. Clinical outcomes depend strongly on early detection and prompt acute management. Artificial intelligence (AI)-based models may support faster automated identification of traumatic findings and early prediction of patient prognosis. A systematic literature search was conducted in PubMed/MEDLINE, Scopus, IEEE Xplore, ACM Digital Library, and the Cochrane Library in accordance with PRISMA 2020 guidelines to evaluate AI-based models for automated detection of TBI-related findings on CT and for prediction of clinical outcomes. Risk of bias and applicability were assessed using QUADAS-2 for diagnostic accuracy studies and PROBAST + AI for prediction model studies. Twenty-two studies were included. Sixteen studies evaluated diagnostic tasks and 10 evaluated prognostic outcomes, with four studies contributing to both categories. Diagnostic performance was generally high, with many studies reporting AUC values approaching or exceeding 0.90, particularly for larger lesion volumes.Prognostic performance was more variable, with moderate to high discrimination and substantial heterogeneity. Only 9 studies incorporated independent external validation, and performance was frequently lower in external cohorts. All prognostic model studies were judged to be at high overall risk of bias using PROBAST + AI, and most diagnostic accuracy studies also demonstrated high or unclear risk of bias in at least one QUADAS-2 domain, most frequently in patient selection. AI-based models applied to brain CT demonstrate strong technical performance for both diagnostic and prognostic tasks in TBI. However, most studies relied on retrospective designs and lacked independent external validation which limits models generalizability and raises concern for potential overfitting. Prospective, multicenter studies with standardized methodologies and rigorous external validation are required before widespread clinical implementation.

Humans↗

PubMed2026

Diagnostic Performance of Machine Learning for Systemic Lupus Erythematosus: Systematic Review and Meta-Analysis.

BACKGROUND: Early and accurate diagnosis of systemic lupus erythematosus (SLE) and its organ involvement is essential. Previous reviews of machine learning (ML) in SLE combined heterogeneous tasks and validation strategies and may have overinterpreted model performance. OBJECTIVE: This study evaluated the diagnostic performance of ML and deep learning (DL) models for 3 clinically distinct SLE-related tasks: SLE classification or diagnosis, lupus nephritis (LN) diagnosis, and neuropsychiatric systemic lupus erythematosus (NPSLE) discrimination. We also assessed methodological quality and certainty of evidence. METHODS: PubMed, Embase, Cochrane Library, Web of Science, and IEEE Xplore were searched from January 2014 to April 2026. Eligible peer-reviewed diagnostic accuracy studies developed or validated ML or DL models for 1 of the 3 prespecified tasks, used an accepted reference standard, and provided data for a 2×2 contingency table. Bivariate random-effects meta-analyses with the Hartung-Knapp-Sidik-Jonkman adjustment were used to pool sensitivity and specificity. We reported 95% prediction intervals (PIs), assessed risk of bias using the Quality Assessment of Diagnostic Accuracy Studies for Artificial Intelligence tool (QUADAS-AI; Viknesh Sounderajah [Imperial College London]), and evaluated certainty of evidence using the Grading of Recommendations Assessment, Development, and Evaluation framework for diagnostic test accuracy. RESULTS: Twenty-nine studies were included: 17 for SLE classification, 5 for LN diagnosis, and 7 for NPSLE discrimination. In the primary task-stratified analysis, pooled sensitivity was 0.91 (95% CI 0.86-0.94; 95% PI 0.56-0.99), and pooled specificity was 0.94 (95% CI 0.91-0.96; 95% PI 0.69-0.99), with low heterogeneity (I²=23.9% and 22.9%, respectively). DL models showed a sensitivity of 0.93 and specificity of 0.95, compared with 0.88 and 0.94 for traditional ML models. Certainty of evidence was high for most analyses but low for LN diagnosis because of inconsistency and imprecision. All studies were retrospective, and only 9 of 29 (31%) performed independent external validation. Overall risk of bias was high or unclear in 22 of 29 (75.9%) studies. No study reported model calibration, decision-curve analysis, or net clinical benefit. CONCLUSIONS: ML models showed promising diagnostic accuracy across 3 distinct SLE-related tasks, but wide PIs, limited external validation, and pervasive risk of bias restrict conclusions about real-world generalizability. Prospective multicenter studies with standardized tasks and reference standards, independent external validation, and formal assessment of calibration and clinical utility are required before clinical implementation.

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

Restrictive vs Liberal Transfusion Strategy in Traumatic Brain Injury: A Secondary Analysis of the TRAIN Trial.

IMPORTANCE: Anemia is a prevalent condition among patients with traumatic brain injury (TBI); however, the optimal hemoglobin (Hb) threshold to initiate red blood cell transfusion (RBCT) is not well defined. OBJECTIVE: To assess which of 2 different Hb thresholds for guiding RBCT in patients with anemia and TBI is associated with a more favorable neurological outcome. DESIGN, SETTING, AND PARTICIPANTS: This was a preplanned secondary analysis of the Transfusion Strategies in Acute Brain Injured Patients multicentric randomized clinical trial, conducted in 72 intensive care units across 22 countries between September 1, 2017, and December 31, 2022. Follow-up was completed June 30, 2023. Only patients with TBI were included in the present analysis, conducted from February to May 2025. INTERVENTIONS: Liberal (transfusion at Hb <9 g/dL [to convert to g/L, multiply by 10.0]) vs restrictive (transfusion at Hb <7 g/dL) RBCT strategy over a maximum of 28 days. MAIN OUTCOME AND MEASURES: The primary outcome was the occurrence of unfavorable neurological outcome, defined as a Glasgow Outcome Scale Extended score of 1 to 5 (overall range, 1-8, with higher scores indicating more favorable outcome) at 180 days. In addition, 14 prespecified serious adverse events, including infection and cerebral ischemia, were assessed. Data were analyzed using both the intention-to-treat and per-protocol principles. RESULTS: Of 486 patients who presented with TBI (mean [SD] age, 46.8 [17.6] years; 347 [71.4%] male), 475 were included in the primary outcome analysis: 236 were randomized to the liberal transfusion strategy group and 239 to the restrictive transfusion strategy group. Both groups had similar baseline characteristics. In total, 534 RBCTs were administered in the liberal transfusion strategy group, compared with 246 RBCTs in the restrictive group. At 180 days after randomization, 138 patients (58.5%) in the liberal group had unfavorable neurological outcome compared with 161 patients (67.4%) in the restrictive group (relative risk [RR], 0.86 [95% CI, 0.75-1.00]; P = .047; fragility index = 1). There were no significant differences in the occurrence of secondary outcomes (eg, 28-day mortality: 42 of 240 [17.5%] vs 51 of 244 [20.9%]; RR, 0.84 [95% CI, 0.58-1.21]; P = .34) or serious adverse events (eg, RR, 1.13 [95% CI, 0.88-1.43]; P = .34 for infection and RR, 0.87 [95% CI, 0.40-1.90]; P = .72 for cerebral ischemia). After adjustment for several confounders, being randomized to the liberal group was associated with a lower observed probability of unfavorable neurological outcome (odds ratio, 0.60 [95% CI, 0.38-0.94]; P = .03). CONCLUSIONS AND RELEVANCE: In this secondary analysis of a multicenter randomized clinical trial, a liberal RBCT strategy was associated with a lower risk than a restrictive RBCT strategy of unfavorable neurological outcome at 180 days among patients with TBI. These findings should be interpreted with caution in light of the inherent uncertainty of the estimate. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT02968654.

Humans↗

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↗

PubMed2026

Predicting training outcomes for developmental dyslexia from EEG data.

Developmental dyslexia (DD) is characterised by lower-than-average reading abilities and is diagnosed in approximately 10% of individuals. The societal barriers may limit professional fulfilment and psychological wellbeing of individuals with DD, calling for the development of effective interventions to counteract them. As DD is associated with challenges in both phonological and visuo-attentional domains, different longitudinal training approaches were developed to strengthen them. However, they require a considerable amount of personal, social and economic resources and the outcomes may vary depending on individual differences in behavioural and neurophysiological functionality. Hence, predicting training outcomes might help in developing personalised treatment protocols and optimising the use of resources. In the present work we applied machine learning to resting-state EEG to predict longitudinal training outcomes in adults with DD enrolled in a randomized clinical trial. In particular, one group received a visuo-attentional training combined with transcranial alternating current stimulation (tACS), another group received visuo-attentional training with sham/placebo stimulation, and the third group received a phonological training with sham/placebo stimulation. The improvement in text reading speed was associated with spectral power in low-beta and individual frequencies in the alpha (IAF) and beta (IBF) bands, while the improvement in pseudoword reading was associated with IBF. The findings highlight the potential of capturing neural markers of treatment responsiveness in DD. Future studies should focus on the generalisability of predictive models to real-world settings, while investigating whether specific EEG markers predict responsiveness to distinct remediation protocols, thus supporting the development of personalised interventions.

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

Active Site Assembly by SMG5 as a Mechanism for SMG6 Endonuclease Licencing in Nonsense-mediated mRNA Decay.

Nonsense-mediated mRNA decay (NMD) is a conserved eukaryotic surveillance pathway that eliminates transcripts containing premature termination codons (PTCs). Substantial progress has been made in defining the transcript features that mark aberrant translation termination for NMD activation, yet key mechanistic steps remain incompletely understood - including how recruitment of the central NMD factor UPF1 is coupled to the downstream effector phase in which targeted mRNAs are nucleolytically degraded. In metazoans, NMD employs an endonucleolytic route mediated by SMG6, a PIN-domain nuclease, alongside SMG5 and SMG7, which act downstream of PTC recognition. SMG5 has recently been proposed to licence SMG6 activity, yet the molecular basis of this licencing has remained elusive. Here, we combine AlphaFold structural predictions with biochemical assays to investigate interactions among human SMG5, SMG6, and SMG7. Structural models predict a high-confidence interface between SMG5 and SMG6 PIN domains that forms a composite active site: a conserved SMG5 aspartate (D893) complements the SMG6 acidic triad to reinstate the canonical tetrad required for PIN-domain catalysis. In vitro, SMG6 alone exhibits weak endonucleolytic activity, which is enhanced ∼10-fold by the SMG5 PIN domain. Mutational analyses confirm that conserved residues from both proteins are essential for this composite configuration. Our findings reveal that the SMG5 PIN domain, previously considered catalytically inert, plays a critical role in activating SMG6 by completing its active site. This work provides mechanistic insight into the SMG5-dependent licencing step and uncovers a composite PIN nuclease architecture at the heart of the metazoan NMD effector phase.

Nonsense Mediated mRNA Decay↗

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

Clinical applications of digital twin technology in In Vitro Fertilisation.

BACKGROUND: Digital twin technology, originating from aerospace and manufacturing industries, has emerged as a transformative tool in healthcare. In vitro fertilisation (IVF) faces persistent challenges including suboptimal embryo selection, unpredictable treatment outcomes, and limited personalisation of protocols. Despite advances in assisted reproductive technology, existing literature exhibits fragmentation: artificial intelligence applications in embryo selection, ovarian stimulation, and endometrial assessment have been developed independently without systematic integration into comprehensive treatment frameworks. Digital twin technology offers unprecedented opportunities to create virtual replicas of biological systems, enabling real-time monitoring, predictive modelling, and personalised treatment strategies. AIM: This narrative review aims to critically examine the current applications of digital twin technology in IVF, evaluate its potential benefits and limitations, synthesize existing evidence into an integrative conceptual model, and identify future directions for implementation in reproductive medicine. METHOD: A comprehensive narrative review was conducted using PubMed, Scopus, Web of Science, and IEEE Xplore databases. A narrative review approach was selected over systematic review to accommodate the heterogeneity of evidence types in this emerging field, including theoretical frameworks, simulation studies, and proof-of-concept implementations that would be excluded from systematic reviews. Search terms included "digital twin," "IVF," "in vitro fertilisation," "assisted reproductive technology," "embryo selection," and "predictive modelling." Studies published between 2015 and 2025 were included, focusing on original research articles, systematic reviews, and proof-of-concept studies describing digital twin applications in reproductive medicine. RESULTS: Digital twin technology in IVF demonstrates significant potential across multiple domains including embryo development simulation, ovarian response prediction, endometrial receptivity modelling, and personalised stimulation protocols. Current applications integrate artificial intelligence, machine learning algorithms, time-lapse imaging, and omics data to create comprehensive virtual models. Early evidence suggests improvements in embryo selection accuracy, ovarian response prediction, and treatment protocol optimization, though large-scale randomized controlled trials remain limited. Implementation challenges include data integration complexity, computational requirements, regulatory considerations, and validation requirements. CONCLUSION: Digital twin technology represents a paradigm shift in IVF practice, offering personalised, predictive, and precision medicine approaches. This review synthesizes existing evidence to propose an integrative conceptual model for digital twin implementation across the IVF treatment spectrum, identifies critical knowledge gaps, and establishes research priorities to advance clinical translation. Despite current limitations, continued advancement promises improved success rates and patient outcomes.

Humans↗

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↗

PubMed2026

Screening of Estrogenic and Antiestrogenic Effects of Estradiol, Bisphenol A, and Fulvestrant Using 2D and 3D Breast Cancer Cell Systems With a Luciferase Reporter Gene Assay.

Endocrine-disrupting chemicals (EDCs) like bisphenol A (BPA) pose health risks by interfering with hormones. This study develops and utilizes in vitro 2D and 3D cell models to evaluate the estrogenic and antiestrogenic properties of compounds. Human breast cancer cell lines T47D and MCF7, stably transfected with a luciferase reporter gene (ERE-LUC), were first compared in 2D. Due to the significantly higher sensitivity and responsiveness observed in the T47D line during preliminary 2D screenings, this cell line was exclusively selected for the development of the 3D spheroid model. Cells were treated with 17β-estradiol (E2), BPA, and Fulvestrant (FUL) to assess cell viability and luciferase activity. In 2D models, T47D ERE-LUC cells showed higher responsiveness than MCF7 ERE-LUC, which failed to show significant luciferase induction with E2. In the 3D T47D model, cells exhibited significant and robust changes in luciferase activity in response to E2 and BPA, highlighting the enhanced fidelity of 3D cultures in replicating tissue conditions compared to their 2D counterparts. The study highlights the effectiveness of 3D models over 2D in evaluating estrogenic activity. Specifically, the 3D T47D ERE-LUC system serves as a superior, sensitive, and reliable platform for screening EDCs, offering benefits in cost, data speed, and reduced in vivo reliance.

Humans↗

PubMed2026

Introgression shapes the genomic conflict landscape of Malus, providing evidence for a reticulate backbone in a woody crop lineage.

Phylogenomic discordance is widespread across plants, but its evolutionary significance is often obscured when conflict is treated primarily as analytical noise rather than as evidence of underlying processes. In woody lineages in particular, incomplete lineage sorting, introgression, and genome duplication can interact over long timescales to produce complex genomic histories that are not adequately summarized by a strictly bifurcating tree. Here, we use Malus as a model woody genus to investigate how these processes structure conflict across a genus-scale, accession-based phylogenomic framework. Using broad taxon sampling, hundreds of nuclear loci, plastid genomes, and genome-wide SNP summaries, we reconstruct a robust nuclear backbone for sampled Malus lineages and evaluate where discordance is concentrated and which processes best explain it. Nuclear analyses resolve eight major clades, whereas conflict is non-random and localized to recurrent hotspots rather than evenly distributed across the tree. Cytonuclear discordance is similarly concentrated, especially around Clade H, represented by sampled accessions of M. tschonoskii, where localized plastid-nuclear disagreement is consistent with candidate plastid capture or organellar introgression. Multiple complementary analyses further indicate that the strongest conflict is not explained by ILS alone, but instead reflects lineage-structured introgression, while polyploid complexes represent additional localized sources of evolutionary complexity. Together, these results provide evidence for a reticulate genomic backbone in Malus and show how integrating nuclear, plastid, and genome-wide conflict analyses can help distinguish background discordance from process-specific signals in woody plant radiations. Several lineage-level reticulation hypotheses identified here should now be tested with broader population-level sampling and curated reference accessions.

Malus↗

PubMed2026

Intramuscular patient-derived xenografts achieve high engraftment rates in gastric cancer: implications for pharmacodynamic testing and genomic biomarker discovery.

BACKGROUND: Gastric cancer (GC) exhibits marked inter-patient heterogeneity, limiting empirical chemotherapy efficacy. Patient-derived xenograft (PDX) models preserve the molecular features of parental tumors and can serve as pharmacodynamic surrogates, but conventional subcutaneous PDX suffers from low engraftment rates. This study evaluated an optimized intramuscular PDX platform for individualized drug testing in GC and applied whole exome sequencing (WES) for biomarker identification (Clinical trial registry: ChiCTR-OOC-17012731). MATERIALS AND METHODS: Ninety-eight treatment-naive GC patients were enrolled between April 2018 and December 2020. Fresh tumor tissues were engrafted into NCG mice by intramuscular transplantation. Drug efficacy was evaluated using tumor cell necrosis rate and Ki-67 expression. WES was performed on 32 engrafted tumorgrafts to characterize driver mutations in fast- and slow-growing subgroups. RESULTS: An engraftment rate of 71.7% (43/60) was achieved, substantially exceeding rates reported in prior studies. Clinical characteristics were independent of engraftment success and outgrowth time (all p > 0.05). Fast- and slow-growing tumorgrafts diverged in frequently altered genes: KMT2C, APOB, CDK12 and MSH2 predominated in fast-growing grafts, whereas TP53, CHD3 and TET2 were enriched in slow-growing grafts. Slow-growing tumorgrafts correlated with longer progression-free survival (p = 0.02). PDX-guided treatment was associated with improved prognosis. CONCLUSIONS: Intramuscular transplantation into NCG mice yields high engraftment rates for GC PDX. PDX-guided chemotherapy selection is associated with favorable outcomes. Driver mutation divergence between fast- and slow-growing tumorgrafts provides candidate prognostic biomarkers.

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