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Selective monitoring of trace-level catechin and myricetin in herbal and aqueous matrices using magnetic MIP-DSPME: Optimization via design of experiments.

A novel dispersive solid-phase microextraction approach utilizing a magnetic molecularly imprinted polymer (MMIP) integrated with HPLC-UV detection was developed for the concurrent quantification of catechin and myricetin in herbal extracts and aqueous samples. The sorbent was engineered as a core-shell nanocomposite, consisting of a selective polymer layer deposited onto Fe3O4@SiO2-APTMS magnetic nanoparticles. Dual-template imprinting using catechin and myricetin generated complementary binding cavities within the polymer framework. Experimental variables influencing extraction were systematically screened and subsequently optimized. A Plackett-Burman design was first applied to identify the most influential factors, with pH and sorption time identified as the dominant variables. These parameters were subsequently fine-tuned using a central composite design, and the optimization process was completed in only 30 experimental runs. The sorption characteristics of the imprinted sorbent (MMIP) were compared with those of its non-imprinted counterpart (MNIP). The MMIP demonstrated markedly higher maximum binding capacities (Qmax), reaching 119.3 mg g-1 for myricetin and 112.1 mg g-1 for catechin, whereas the corresponding values for the MNIP were 32.55 and 32.08 mg g-1, respectively. Moreover, the affinity constants (KL = 0.760-0.950 L mg-1) were approximately 2.3-fold higher for the MMIP, confirming its stronger and more selective interactions with the target analytes. The selectivity coefficients for the targeted flavonoids relative to structurally related compounds, including ferulic acid, p-coumaric acid, melatonin, and curcumin, exceeded 3.5 for the MMIP, whereas the corresponding values for the MNIP were close to 1.1, demonstrating the high molecular recognition capability of the imprinted sorbent. Method validation demonstrated limits of detection (LODs) of 0.33-0.59 ng mL-1 and limits of quantification (LOQs) of 1.10-1.96 ng mL-1, and excellent linearity over the concentration range of 5.0-5500 ng mL-1 (R2 > 0.998). The method achieved recoveries of 93.96% to 105.69% with RSDs below 5.5%, while the preconcentration factors ranged from 209 to 229. Furthermore, the sorbent retained more than 95% of its extraction efficiency after four consecutive reuse cycles and more than 80% after six cycles, demonstrating excellent stability and reusability. The proposed method was successfully applied to the analysis of six medicinal plant extracts and water samples, showing negligible matrix interference and superior sensitivity, selectivity, and operational simplicity compared with conventional solid-phase extraction methods.

Flavonoids

Maternal anemia and the risk of preterm birth: a meta-analysis.

BACKGROUND: Globally, preterm birth continues to be a primary contributor to neonatal complications and fatalities. Anemia among the most common nutritional disorders in pregnancy has been proposed as a potential contributor to early delivery. Although extensively studied, the available evidence does not yet provide a clear consensus. This study aimed to conduct a meta-analysis to quantitatively assess the relationship between maternal anemia and the risk of preterm birth. METHODS: This meta-analysis was conducted and reported in accordance with the PRISMA guidelines and the MOOSE checklist. A systematic and exhaustive search was performed across multiple electronic databases PubMed, Scopus, Web of Science, Embase, and the Cochrane Library to identify relevant studies published from inception to 1 January 2025. Effect sizes were combined using a random-effects meta-analysis. RESULTS: A total of 45 articles, reporting 60 independent study populations&#xa0;comprising 2,119,392 pregnant individuals were included. Considerable heterogeneity was found across the included studies (I2 = 95.54%, p&#x2009;<&#x2009;0.001), which justified the application of a random-effects model for pooling effect sizes. Maternal anemia was significantly associated with an increased risk of preterm birth (pooled odds ratio[OR]&#x2009;=&#x2009;1.28, 95% confidence interval [CI]: 1.20-1.36, p&#x2009;<&#x2009;0.001). Despite substantial heterogeneity, sensitivity analyses confirmed the robustness of this association. The relationship was strongest in studies conducted in Asia (OR = 1.30, 95% CI: 1.22-1.40; p&#x2009;<&#x2009;0.001) and the Europe (OR = 1.24, 95% CI: 1.08-1.41; p&#x2009;=&#x2009;0.001) and reached statistical significance when anemia was assessed during the first trimester (OR = 1.12, 95% CI: 1.03-1.51; p&#x2009;=&#x2009;0.007) and the third trimester (OR = 1.65, 95% CI: 1.42-1.91; p&#x2009;<&#x2009;0.001), while no significant associations were found in the second trimesters (OR = 1.10, 95% CI: 0.99-1.22; p&#x2009;=&#x2009;0.05). Funnel plot asymmetry and a significant Egger's test (p = 0.001) indicated potential publication bias, although Begg's test was not significant (p = 0.425). CONCLUSIONS: The current evidence suggests that maternal anemia, particularly in the third trimester, is significantly associated with an increased risk of preterm birth. These findings emphasize the clinical imperative for comprehensive and timely anemia screening during the third trimester. Integrating targeted interventions such as iron and micronutrient supplementation, is essential to mitigate the risk of preterm delivery and improve neonatal outcomes.

Humans

Data-centric, robust, and explainable multimodal deep learning for clinical decision support: A systematic review.

PURPOSE: Multimodal deep learning is increasingly proposed for clinical decision support (CDS) under a "data-centric" framing that prioritizes label quality, missing-modality robustness, distribution shift, calibration, and explainability. Prior reviews have examined multimodal medical AI, CDS, and data-centric methods separately, but none address their intersection. We mapped the modalities, fusion strategies, and data-centric and explainability techniques used in this recent literature, quantified how often each is implemented rather than merely mentioned, assessed deployment-relevant evidence (external validation, clinical-outcome measurement, equity), and formally appraised study-level risk of bias. METHODS: Following the PRISMA 2020 statement (PROSPERO CRD420261427815; registered retrospectively), we screened 150 records and included primary, clinical, multimodal studies that applied machine or deep learning to a decision-support task and reported at least one quantitative result. Two reviewers screened and extracted data with consensus adjudication. Each study was coded against pre-specified operational definitions, separating implemented or empirically evaluated techniques from those only mentioned. Study-level risk of bias was assessed with PROBAST + AI. Synthesis was narrative. RESULTS: Thirty-one studies met inclusion; 30 (97%) were published between 2024 and 2026, with a median of three modalities (range 2-6), most commonly structured EHR (71%) and imaging (39%). Data-centric techniques were frequently reported (74-84% across label-noise, distribution-shift, calibration, missing-modality and class-imbalance handling; equity 61%). However, external validation was reported in only 4/31 studies (13%), a clinical or provider outcome in 3/31 (10%), and no study reported routine deployment. Overall risk of bias was high in 27/31 studies (87%), driven by the analysis domain. CONCLUSION: Within this recent, self-selected slice of the field, technical robustness and explainability techniques are widely reported but rarely validated out-of-distribution or against clinical outcomes, and the underlying evidence is at high risk of bias. Progress requires external multi-site validation, clinical-outcome measurement, formal bias appraisal, and adherence to AI reporting standards (e.g., TRIPOD + AI) before deployment can be justified.

Deep Learning

Qualitative evidence of service user experiences and perspectives on long-acting injectable buprenorphine for opioid treatment - a scoping review.

BACKGROUND: There is substantial literature on opioid treatment program (OTP) formulations and how they relate to the pharmacotherapy service user experience. As a newer formulation, less is known about service user experiences of long-acting injectable buprenorphine (LAIB). The aim of this scoping review is to map the qualitative evidence and gaps in the literature on service user experiences and perspectives of LAIB. METHODS: Our search strategy included Medline, Embase, PsycINFO, CINAHL, Scopus and Web Science, and citation chaining, from January 2016 to June 2025. Studies were included if reporting qualitative descriptions of LAIB service user experiences of treatment for opioid dependence, inclusive of qualitative, mixed methods (description of qualitative data only), case reports and English language. Articles were screened by two reviewers. A living experience first author led the analysis using inductive coding and thematic analysis, to produce a descriptive summary of synthesised findings alongside key study characteristics and quality appraisal, adhering to the Systematic reviews and Meta-Analysis for Scoping Reviews (PRISMA-ScR) checklist. RESULTS: After screening 838 titles/abstracts and reviewing 150 full texts, 40 studies met the eligibility criteria. All were conducted in high income countries, principally the US (n=12); Australia (n=10); and England and Wales (n=9). We identified five themes: Navigating LAIB treatment; Embodied and relational effects of LAIB; Impact and role of the service provider; Narratives of harm reduction and recovery; Stigma and criminalisation. LAIB was commonly experienced as increasing convenience, stability and freedom from daily supervised dosing, enabling improved work, travel, privacy and social participation. Reduced clinic/dosing contact often lessened enacted stigma and treatment burden. However, experiences were heterogenous. Some participants described injection-site discomfort, uncertainty about dose adequacy, reduced flexibility once injected, and ambivalence about LAIB effects. There was inconsistency in LAIB service user reports on service connection, isolation and psychosocial support. Treatment experiences were strongly shaped by provider practices. CONCLUSIONS: Findings underscore the need for integrated, flexible, harm-reduction oriented and person-centred LAIB treatment models that prioritise choice, autonomy and therapeutic relationships to maximise benefit for service users. However, evidence of LAIB service user experiences is concentrated in high-income countries, and the absence of perspectives from low- and middle-income country settings represents a substantial gap in the evidence base.

LAIB

Effect of a digitally augmented general health promotion intervention on abstinence from health-risk behaviors among emergency department discharge patients: A randomized controlled trial.

BACKGROUND: Noncommunicable diseases (NCDs) are the leading global cause of death and are driven by modifiable behaviors, such as tobacco use, harmful alcohol consumption, unhealthy diet, and physical inactivity. Recognizing that emergency department (ED) visits represent a unique opportunity to promote behavior change, this trial evaluated a digitally augmented, theory based general health promotion approach, combining a brief telephone-based intervention with mobile instant messaging support, to help discharged ED patients abstain from health risk behaviors. METHODS AND FINDINGS: This assessor-blinded randomized controlled trial was conducted in a major public hospital ED in Hong Kong. Adults (18-65 years) triaged as semi-urgent or non-urgent and with &#x2265;1 health-risk behavior and smartphone access were randomized to receive a digitally augmented, theory&#x2011;based general health&#x2011;promotion intervention consisting of a brief telephone&#x2011;based AWARD&#x2011;model intervention (Ask, Warn, Advise, Refer, and Do-it-again) followed by weekly WhatsApp or WeChat messages for 6 months, or to a control group receiving brief telephone advice only. The primary outcome was self-report abstinence from &#x2265;1 health-risk behavior at 6 months; secondary outcomes included the proportion of participants who achieved self-reported abstinence from &#x2265;1 health-risk behavior at 12 months and reduction in the number of behaviors at 6 and 12 months. Of the 2,134 screened patients, 572 were enrolled (286 per group). At 6 months, 30.1% of the intervention participants versus 19.9% of the controls achieved self-reported abstinence (RR&#x2009;=&#x2009;1.51; 95% CI, 1.13-2.02; P&#x2009;=&#x2009;0.006). The intervention also significantly increased the likelihood of fewer risky behaviors at 6 (RR&#x2009;=&#x2009;1.54; P&#x2009;=&#x2009;0.01) and 12 (RR&#x2009;=&#x2009;1.48; P&#x2009;=&#x2009;0.02) months. Physical inactivity showed the greatest improvement at 6 months (31.7% versus 16.2%; P&#x2009;<&#x2009;0.001). The effects attenuated after cessation of booster messaging. Limitations include reliance on self-reported outcomes, the single-center study design, and loss to follow-up, which may have affected the generalizability of the results. CONCLUSIONS: A digitally augmented, theory-based general health promotion strategy delivered at ED discharge through brief telephone intervention and mobile instant messaging support demonstrated short-term benefits in promoting self-reported abstinence and reducing health-risk behaviors at 6 months. However, the absence of a sustained effect at 12 months suggests that extended support or maintenance strategies may be required to maintain these improvements over time. Multicenter trials with longer follow-up are warranted to evaluate long-term effectiveness. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov (Registration No: NCT06077565).

Humans

Machine learning-based prediction of unplanned readmission and construction of an online calculator for elderly patients with mild ischemic stroke.

OBJECTIVE: To screen for independent risk factors for unplanned readmission in elderly patients with mild ischemic stroke, and to construct and validate an online risk prediction calculator based on an interpretable machine learning model, thereby providing a promising practical tool for accurate clinical assessment of 30&#x2011;day all&#x2011;cause unplanned readmission risk in this population. METHODS: A prospective cohort study was conducted, including 1050 patients aged&#xa0;&#x2265;&#xa0;60&#xa0;years with mild ischemic stroke admitted between August 2023 and September 2024. Participants were randomly divided into a training set (840 cases) and a test set (210 cases) at a ratio of 8:2. Risk factors were screened by univariate analysis and multivariable Logistic regression. Four machine learning models, namely LightGBM, XGBoost, Random Forest, and K&#x2011;Nearest Neighbors (KNN), were developed and their performance was evaluated using AUC, accuracy, sensitivity, and specificity as metrics. The SHAP framework was used for interpretability analysis, and an online calculator was subsequently developed based on the optimal model. RESULTS: Univariate analysis showed significant differences (P&#xa0;<&#xa0;0.05) in 13 factors including age, smoking, AIP, TyG index, HALP score, etc. Multivariable Logistic regression identified age (OR&#xa0;=&#xa0;9.752), smoking (OR&#xa0;=&#xa0;5.171), AIP (OR&#xa0;=&#xa0;6.691), TyG index (OR&#xa0;=&#xa0;4.393), HALP score (OR&#xa0;=&#xa0;2.831), and&#xa0;&#x2265;&#xa0;2 comorbidities (OR&#xa0;=&#xa0;3.664) as independent risk factors. All four machine learning models demonstrated good predictive performance. Based on a comprehensive evaluation of multiple metrics and computational efficiency, the LightGBM model exhibited the best predictive performance (AUC&#xa0;=&#xa0;0.884, accuracy&#xa0;=&#xa0;0.829, sensitivity&#xa0;=&#xa0;0.812, specificity&#xa0;=&#xa0;0.875). SHAP analysis showed that age, AIP, TyG index, smoking, and HALP score were key predictors. An online calculator developed based on this model enables individualized risk predictions. CONCLUSION: Key risk factors associated with 30&#x2011;day unplanned readmission in elderly patients with mild ischemic stroke were identified. The LightGBM model demonstrated high predictive accuracy, and together with the interpretability analysis and online calculator, offers a practical tool to support clinical risk assessment. However, this tool requires future external validation.

Humans

Emerging Principles in Spatial Functional Genomics.

Spatial transcriptomic and proteomic atlases have enabled mapping of gene programs within intact tissues, but these measurements remain largely descriptive and do not define the mechanisms controlling tissue biology. Pooled CRISPR screening provides scalable causal interrogation of gene function but remains largely confined to dissociated systems that lack spatial context. In vivo spatial functional genomics (SFG) bridges these approaches by integrating genetic perturbations with in situ transcriptomic and proteomic readouts to measure gene function within intact tissue ecosystems. By preserving spatial organization, SFG enables interpretation of perturbations through effects on cell-cell interactions, diffusible signals, multicellular niches, and tissue architecture. Here, we outline key design axes of SFG: perturbation strategy, barcoding strategy, and phenotypic readout. We discuss computational challenges, including spatial autocorrelation, neighborhood dependence, and context-aware null modeling, and highlight how SFG reveals non-cell-autonomous, architecture-dependent mechanisms of gene function, advancing toward predictive models of tissue organization and gene function.

Genomics

Risk Factors for Long-Term Health-Related Quality-of-Life and Mental Health Outcomes in Traumatic Brain Injury: A Systematic Review and Meta-Analysis.

Traumatic brain injury (TBI) often leads to long-term disability, including persistent mental health issues and lower health-related quality of life (HRQoL). Early interventions can improve recovery, but because resources limit routine monitoring of all patients, trauma care remains largely symptom-driven. The combination of long-term disability and limited capacity for routine follow-up highlights the need for risk-stratified follow-up care and reliable evidence on early prognostic factors. However, the existing literature is sparse and methodologically heterogeneous, limiting the clinical applicability of findings. We therefore conducted a systematic review and meta-analysis to identify early risk factors for poorer long-term mental health and HRQoL outcomes. A systematic search of seven electronic databases identified studies of adult patients with TBI, with outcomes assessed at least 6 months postdischarge. Two authors independently screened the studies, assessed the risk of bias, and extracted the data. We pooled effect estimates using a random-effects meta-analysis and calculated 95% prediction intervals. A narrative synthesis was applied when meta-analysis was not feasible. The review was registered with PROSPERO (CRD42024576912) and reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Of the 8,104 articles screened, 64 studies met the inclusion criteria (n = 334,672). Most studies (58%) had a low risk of bias. Female sex, socioeconomic disadvantage, psychiatric history, assaultive-related injuries, and previous TBI were consistently associated with worse long-term outcomes. Across meta-analyses, assault-related injuries more than doubled the odds of post-traumatic stress disorder (odds ratio [OR] = 2.72; 95% confidence interval [CI]: 2.01-3.66, I2 = 0%). Higher odds were also observed among females (OR = 1.33; 95% CI: 1.11-1.59, I2 = 0%), individuals with prior TBI (OR = 1.56; 95% CI: 1.07-2.27, I2 = 0%), and those with psychiatric history (OR = 2.38; 95% CI: 1.83-3.10, I2 = 48%). We found that female sex (OR = 1.72; 95% CI: 1.38-2.16, I2 = 58%), prior TBI (OR = 1.52; 95% CI: 1.25-1.85, I2 = 0%), and psychiatric history (OR = 3.25; 95%CI: 1.86-5.69, I2 = 98%) were associated with higher odds of depression. Furthermore, higher pooled anxiety scores were observed in females and in individuals with a psychiatric history. The study identified several readily available factors present before or at discharge that are associated with poor long-term HRQoL and mental health outcomes. Leveraging these factors in follow-up protocols, prediction modeling, and clinical decision support systems may facilitate risk-stratified postdischarge care for TBI patients.

Humans

[Tafluprost/timolol fixed-dose combination versus tafluprost monotherapy for open-angle glaucoma and ocular hypertension: a multicenter, randomized, double-blind, parallel-group trial].

Objective: To evaluate the efficacy and safety of a preservative-free tafluprost/timolol maleate fixed-dose combination compared with preservative-free tafluprost monotherapy in Chinese patients with open-angle glaucoma (OAG) or ocular hypertension (OHT). Methods: This was a multicenter, randomized, double-blind, parallel-controlled clinical trial conducted across 25 centers, including the Eye & ENT Hospital of Fudan University, from January 2019 to November 2022. Patients diagnosed with OAG or OHT who required enhanced intraocular pressure (IOP) reduction after a 4-week washout period were enrolled. Participants were randomized 1&#x2236;1 to receive either tafluprost/timolol or tafluprost once daily for 3 months. The primary endpoint was the change from baseline in mean diurnal IOP (the average of measurements at 8:00, 10:00, and 16:00) at Month 3. Secondary endpoints included IOP changes at individual time points and the proportion of responders achieving predefined IOP reduction thresholds. Safety was assessed via the incidence of adverse events (AEs). Analysis of covariance (ANCOVA) using the Markov Chain Monte Carlo (MCMC) method was employed for the primary endpoint; superiority was established if the upper limit of the 95% confidence interval (CI) was<0 mmHg (1 mmHg=0.133 kPa). Continuous variables in secondary endpoints were compared using ANCOVA, and responder rates were analyzed using Fisher's exact test. Results: A total of 219 patients were enrolled (tafluprost/timolol group: n=110; tafluprost group: n=109). The primary efficacy analysis set included 215 patients (tafluprost/timolol: n=107; tafluprost: n=108). Baseline characteristics were well-balanced between the two groups. The majority of patients were male [127 (59.1%)] with a mean age of (44.80&#xb1;15.71) years at screening. At Month 3, the mean diurnal IOP reduction from baseline was (6.56&#xb1;3.44) mmHg in the tafluprost/timolol group and (5.36&#xb1;2.94) mmHg in the tafluprost group. After adjusting for baseline IOP, the between-group difference was -1.312 mmHg (95%CI: -2.010 to -0.696); as the upper limit was<0 mmHg, tafluprost/timolol demonstrated superior IOP-lowering efficacy to tafluprost. Responder rates for IOP reductions of&#x2265;15%,&#x2265;25%, and&#x2265;30% were significantly higher in the tafluprost/timolol group (P=0.016, 0.028, and 0.032, respectively). The incidence of ocular AEs was 20.0% (22/110) in the tafluprost/timolol group and 26.6% (29/109) in the tafluprost group. The most common AE was conjunctival hyperemia, occurring in 2.7% (3/110) and 8.3% (9/109) of the groups, respectively. Conclusion: Compared with preservative-free tafluprost monotherapy, the tafluprost/timolol combination provides significantly greater IOP reduction in patients with OAG and OHT, while maintaining a favorable safety profile.

Humans

Integrated transcriptomic and metabolomic analysis of fluoride tolerance-related pathways and differentially expressed genes in silkworm strain XSKD.

XueSong KD (XSKD) silkworm strain exhibits prominent fluoride tolerance, yet the underlying molecular mechanisms of fluoride tolerance remains unclear. In the present study, fourth-instar pre-molting XSKD silkworms were used as experimental materials for integrated transcriptomic and untargeted metabolomic analyses. In total, 572 differentially expressed genes and 90 differential metabolites were screened. GO enrichment and KEGG enrichment based on the hypergeometric distribution model revealed that 13-Hydroxy-9Z,11E-octadecadienoic acid (13-(S)-HODE) acts as the core differential metabolite, which is significantly enriched in the linoleic acid metabolism pathway. Within this pathway, LOC101737302 and CYP338A1 display opposite expression trends and show correlations with pathway metabolites. Based on multi-omics data, this study preliminarily characterizes the lipid metabolic response under fluoride stress, providing omics dataset support for further in-depth exploration of the molecular mechanism of fluoride tolerance in silkworms.

Animals

Evaluation of Physical and Mental Workload and Transfusion Time in Trauma Resuscitation.

BACKGROUND: Trauma resuscitation is time sensitive and complex. Whole blood (WB) and blood components are standard treatments for trauma related hemorrhage, yet their nursing workload and transfusion time have not been well evaluated. PURPOSE: To assess feasibility of a simulation-based crossover trial and obtain preliminary estimates comparing nursing workload and transfusion completion time between WB and blood component administration. METHODS: A randomized crossover pilot study using in situ simulation was conducted with experienced trauma nurses. Time-motion analysis measured transfusion completion time, and the National Aeronautical and Space Administration Task Load Index assessed workload domains. RESULTS: Strong feasibility was demonstrated across recruitment, retention, adherence, and completion. WB was associated with significantly shorter transfusion time, lower overall workload and mental demand, less effort, and better perceived performance. CONCLUSIONS: These findings support the feasibility and justify a fully powered trial. WB may improve resuscitation efficiency and reduce cognitive burden, with potential implications for patient outcomes and nursing workflow.

Humans

Proteomic and phosphoproteomic profiles of time-dependent dynamic changes in LPS-induced macrophage polarization.

The temporal proteomic and phosphoproteomic reprogramming during early M1 macrophage polarization (0-6&#xa0;h) remains poorly understood. We performed time-resolved proteomic and phosphoproteomic analyses of LPS-stimulated RAW264.7 macrophages at seven time points within 6&#xa0;h. Time-clustering of differentially expressed molecules revealed two patterns: initial change with partial recovery, and sustained dysregulation. Upregulated proteins and phosphorylation sites were enriched in the Rho GTPase signaling pathway, T-cell receptor signaling pathway, NF-&#x3ba;B cascade, osteoclast differentiation pathway, and antiviral immune pathway. Downregulated pathways were associated with cell cycle regulation, chromatin remodeling, RNA metabolism, and mRNA processing, indicating resource reallocation to prioritize acute inflammatory responses. Kinase-substrate network analysis confirmed the mitogen-activated protein kinase (MAPK), cyclin-dependent kinase (CDK), protein kinase B (AKT), and ribosomal S6 kinase (RSK) families as core upstream phosphorylation regulators. Integrated analysis revealed synergistic and antagonistic relationships between proteomic and phosphoproteomic changes. This study provides a temporal molecular atlas of M1 polarization, delineating inflammatory signaling dynamics and offering a basis for therapeutic target discovery in inflammatory diseases. SIGNIFICANCE: Macrophage M1 polarization is a central event in innate immune defense against pathogenic invasion, yet its dysregulation is a pivotal driver of the onset and progression of a broad spectrum of inflammation-associated disorders, spanning autoimmune diseases, infectious conditions and inflammatory bone diseases, making the dissection of its molecular regulatory mechanisms an urgent research priority in immunology and translational medicine. Dynamic molecular events within 0-6&#xa0;h after LPS stimulation are critical for initiating and shaping M1 inflammatory activation, yet systematic time-resolved proteomic and phosphoproteomic profiling remains insufficient.In this study, we comprehensively characterized temporal proteome and phosphoproteome changes at seven consecutive time points during macrophage polarization, clarified two distinct dynamic molecular patterns, identified core signaling pathways and key kinase regulators involved in inflammatory reprogramming, and uncovered the leading role of post-translational phosphorylation modifications in initiating polarization. This work delineates the time-series molecular atlas of early macrophage activation, provides novel insights into the temporal regulatory mechanism of inflammatory signaling networks, and lays a solid experimental foundation for exploring new intervention targets and regulatory nodes in clinical translational research.

Lipopolysaccharides

Impact of Commercial Artificial Intelligence on Radiologist Reading Time for Pulmonary Nodule Evaluation at Chest CT.

Background Chest CT is a primary method for identifying pulmonary nodules, yet interpreting scans remains time-intensive and demanding. Currently, artificial intelligence (AI) is expected to reduce reading times, but the effect of AI on reporting times in this setting is unknown. Purpose To evaluate the impact of a commercial AI software on radiologists' reading time for pulmonary nodule assessment on chest CT scans within a real-world clinical setting. Materials and Methods This retrospective study included patients who underwent chest CT examinations at a tertiary medical center between September 2021 and May 2024. The study period was divided into pre- and post-AI phases. The primary outcome was radiology reporting time. The association between AI implementation and reporting time was evaluated using a multivariable parametric Weibull shared frailty survival model adjusted for reader function, examination type, patient location, and requesting specialty, with clustering at the radiologist level. Interaction analyses assessed heterogeneity across prespecified subgroups. An exploratory extrapolation estimated projected workforce and financial impact. Results This study included 19&#x2009;433 patients (mean age, 62 years &#xb1; 14.2 [SD]; 21&#x2009;814 men; 39&#x2009;323 chest CT examinations, 19&#x2009;190 pre-AI, and 20&#x2009;133 post-AI). AI implementation was associated with faster report completion (adjusted hazard ratio, 1.17; 95% CI: 1.14, 1.21; P < .001). The adjusted median reporting time decreased from 21.3 minutes pre-AI to 18.2 minutes post-AI (14.6% reduction; P < .001). Heterogeneity was observed across reader function (P < .001), examination type (P = .048), and requesting specialty (P = .03). The largest relative reductions were observed for CT thorax electrocardiogram-gated examinations (-41.1%; P < .001) and thoracic radiologists (-25.0%; P < .001), whereas emergency department examinations showed increased median reporting time (7.1%; P < .001). At institutional scan volumes (approximately 20&#x2009;000-22&#x2009;000 chest CT examinations annually), exploratory modeling suggested an approximate reduction of 0.5 full-time equivalent radiologist workload. Conclusion Implementation of commercial AI-assisted pulmonary nodule assessment on chest CT scans reduced radiologist reporting time in a real-world clinical setting. &#xa9; The Author(s) 2026. Published by the Radiological Society of North America under a CC BY 4.0 license. Supplemental material is available for this article. See also the editorial by Iwasawa in this issue.

Humans

Origins and timing of somatic variants in the brain.

Somatic variants accumulate in human brain cells throughout the lifespan. Variant allele fraction has traditionally been used as a proxy for both the developmental timing of somatic variants and their functional effect, based on the assumption that earlier mutations are shared by larger cell populations and therefore have greater potential for severe phenotypes. However, recent discoveries challenge this simplified model. Variables such as developmental bottlenecks, lineage restriction, and cellular and molecular context play critical roles in shaping the distribution and functional impact of somatic variants in the brain. These insights support a shift toward a context-dependent framework for interpreting somatic mosaicism.

Humans

Timing of OMERACT core domain measurement in gout clinical trials: a systematic review of randomised trials.

AIMS: The Outcome Measures in Rheumatology (OMERACT) initiative has endorsed core domain sets for gout trials. The aims of this study were to evaluate the time points and frequencies at which the gout core domains are measured in existing gout urate-lowering therapy and gout flare trials, and whether all collected measurements were reported. METHODS: Urate-lowering therapy (n = 29) and gout flare randomised clinical trials (n = 14) from 2005 were identified from a prior systematic review of core domain reporting. Data were extracted for the time points and frequencies at which each core domain was measured, as well as whether all collected measurements were reported. RESULTS: In urate-lowering therapy trials, the core domains were measured at seven different frequencies. Serum urate and gout flares were most commonly measured monthly, and tophus burden was most commonly measured three monthly. Reporting of all collected measurements varied, from 24/29 (83%) trials for serum urate to 0/2 (0%) trials for activity limitation. In gout flare trials, core domains were measured at nine different frequencies. Pain, joint tenderness and joint swelling were most commonly measured monthly. Reporting of all collected measurements varied, from 13/14 (93%) trials for pain to 3/8 (37.5%) trials for joint tenderness. CONCLUSION: In both urate-lowering therapy and gout flare trials, there is substantial variability in when the core domains are measured, and reporting of collected measurements is inconsistent. This work provides the foundation for a consensus process to establish standardised time points and frequencies for measuring the OMERACT-endorsed gout core domains.

Gout

Assessing time to symptomatic progression, a patient-relevant efficacy endpoint, in the MARIPOSA study in non-small cell lung cancer.

INTRODUCTION: In the phase 3 randomized MARIPOSA study, amivantamab and lazertinib combination therapy demonstrated improved progression-free survival (PFS) and overall survival (OS) versus osimertinib in participants with previously untreated, epidermal growth factor receptor-mutated advanced non-small cell lung cancer. Time to symptomatic progression (TTSP) was introduced to assess clinical worsening and complement endpoints that investigate radiographic disease progression and patient-reported outcomes. TTSP provides an easily interpretable measure of disease-specific symptom worsening to further support patient experience. METHODS: In MARIPOSA, TTSP was quantitatively assessed as a secondary efficacy endpoint and defined as the time from randomization until participants experience disease-specific symptom worsening requiring a clinical intervention or treatment change, or death. To evaluate the impact of amivantamab and lazertinib on TTSP considering its established OS benefit against osimertinib, an exploratory analysis censoring death events was performed. RESULTS: At the final protocol-specified OS analysis (median follow up: 37.8 months), median TTSP was 43.6 months with amivantamab and lazertinib versus 29.3 months with osimertinib (hazard ratio [HR]: 0.69; 95% confidence interval [CI]: 0.57-0.83; p&#x202f;<&#x202f;0.0001). Amivantamab and lazertinib reduced deaths following a TTSP event compared to osimertinib. A strong correlation between TTSP and PFS or OS was observed. CONCLUSIONS: Amivantamab and lazertinib significantly delayed TTSP versus osimertinib. TTSP offers a clinician-validated measurement of disease-specific symptom worsening, capturing symptoms perceived by patients that prompt clinical action. TTSP is highly correlated with PFS and OS, providing complementary insights alongside traditional endpoints. TTSP enhances understanding of treatment benefit and supports informed clinical decision-making by integrating patient experience.

Humans

Algae-to-host horizontal gene transfer in Paramecium bursaria is associated with host adaptation during endosymbiosis.

Paramecium bursaria maintains a stable endosymbiosis with green algae, yet the evolutionary consequences of this association remain unclear. Here, we screened the host genome for algal-derived horizontally transferred genes (HTGs) using a lineage-aware workflow designed to detect horizontal gene transfer (HGT) between two defined lineages. We identified 16 candidate HTGs, including four putative newly transferred genes and 12 homologous transferred genes, most of which were functionally associated with redox homeostasis and metabolism. Five HTGs showed symbiosis-dependent expression. RNAi knockdown of GH32s and SATs reduced host proliferation, total cell area, and motility, while GH32s knockdown also reduced endosymbiont load. Duplication patterns suggest that most transfers may have occurred after the P. bursaria lineage diverged from the sampled Paramecium species but before its lineage-specific whole-genome duplication (WGD). The HTGs also showed host-associated shifts in GC content and gene length, while representative HTGs retained conserved domains and functional motifs. Together, our results support algae-to-host HGT in P. bursaria and suggest that some transferred genes may contribute to metabolic integration during endosymbiosis.

Gene Transfer, Horizontal