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Effects of transcutaneous electrical acupoint stimulation versus acupressure on the trajectories of multidimensional adverse reactions to chemotherapy in breast cancer patients: a secondary analysis of a randomized controlled trial.

BACKGROUND: Chemotherapy for breast cancer often induces multidimensional adverse reactions such as nausea and vomiting, anxiety, depression, and sleep disturbances. These symptoms are interrelated and may evolve dynamically, impacting patients' treatment outcomes and quality of life. As non-pharmacological interventions, transcutaneous electrical acupoint stimulation (TEAS) and self-acupressure (SA) have shown potential in alleviating symptoms. However, their long-term effects on the joint developmental trajectories of these multidimensional symptoms (nausea and vomiting, anxiety, depression, and sleep disturbances) remain unclear. OBJECTIVE: This study aimed to identify potential trajectory class of multidimensional adverse reactions in breast cancer patients undergoing chemotherapy and to explore the differential effects of TEAS and SA on different trajectory subgroups. METHODS: This was a secondary analysis of a randomized controlled trial. A total of 189 breast cancer patients receiving chemotherapy were included. The Group-Based Multi-Trajectory Model (GBMTM) was employed to identify joint developmental trajectories of acute/delayed chemotherapy-induced nausea and vomiting (CINV), anxiety, depression, and sleep quality during chemotherapy. Subsequently, causal forest was used to analyze the average treatment effects (ATE) of TEAS (vs. control group) and SA (vs. control group) on patients' symptom trajectory. RESULTS: Multidimensional adverse reactions were classified into two heterogeneous trajectories: a "High Symptom Burden-Persistent (HSBP)" type (n&#x2009;=&#x2009;101) and a "Low Symptom Burden-Relieving (LSBR)" type (n&#x2009;=&#x2009;88). The persistent high incidence of acute CINV contrasted sharply with the comprehensive relief of other symptoms in the latter group. Causal forest suggested that both TEAS and SA significantly increased the probability of patients being classified into the "LSBR" trajectory. The ATE was 0.147 (95% CI: 0.143, 0.151) for TEAS, slightly lower (P&#x2009;<&#x2009;0.05) than 0.176 (95% CI: 0.162, 0.190) for SA.&#xa0; CONCLUSION: Multidimensional adverse reactions in breast cancer patients undergoing chemotherapy exhibit heterogeneity in their trajectories. Both TEAS and SA were associated with a higher probability of patients being classified into a more favorable symptom trajectory-LSBR. The multidimensional trajectory identification with treatment effect estimation may serve as a useful analytical strategy for future longitudinal research in cancer chemotherapy-induced adverse reactions symptom management. CLINICAL TRIAL REGISTRATION: ChiCTR2300077667 (Chinese Clinical Trial Registry, https://www.chictr.org.cn/ ), Registered 15 November 2023.

Humans

Integrated multi-omics profiling of amniotic fluid identifies predictive biomarkers for fetal growth restriction trajectories.

BACKGROUND: Fetal growth restriction (FGR) is a complex condition with highly heterogeneous clinical outcomes, making prenatal distinction between transient and persistent growth failure challenging. This study aims to identify amniotic fluid (AF) biomarkers capable of differentiating distinct FGR trajectories and characterizing persistent growth failure mechanisms. METHODS: Integrated proteomic and metabolomic profiling was performed on AF samples from transient FGR (n&#x2009;=&#x2009;11), persistent FGR (n&#x2009;=&#x2009;9), and healthy controls (n&#x2009;=&#x2009;13). Diagnostic and prognostic models were developed using multivariate analysis. Selected protein candidates were validated via ELISA in an independent cohort (n&#x2009;=&#x2009;69). RESULTS: Multi-omics analysis revealed distinct molecular signatures for FGR stratification. A two-protein diagnostic panel (PDGFA and phospho-STAT5A) achieved an AUC of 1.000 in the discovery stage and 0.780 in the external validation cohort. For prognostic assessment, a molecular signature including IREB2, HLA-C, and PLXNB2 accurately predicted persistent growth failure from transient recovery (AUC = 0.966). Cross-platform integration highlighted the mass spectrometry-derived WASHC2C as a central hub protein with a significant progressive increase across the control, transient, and persistent groups (p&#x2009;<&#x2009;0.001). CONCLUSIONS: This study establishes a multi-omics framework for prenatal FGR stratification. Our findings identify distinct molecular&#xa0;signatures reflecting&#xa0;the intrauterine environment and provide high-performance molecular tools for predicting divergent fetal growth trajectories to guide personalized clinical decision-making.

Humans

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 (&#x3b2;&#xa0;=&#xa0;-0.45; 95%CI[-0.70, -0.19]; FDR-p&#xa0;=&#xa0;0.003) and verbal memory (&#x3b2;&#xa0;=&#xa0;-0.45; 95%CI[-0.72, -0.18]; FDR-p&#xa0;=&#xa0;0.003). Significant time &#xd7; 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

Tissue origins of the plasma proteomic response to glucose ingestion in humans.

AIMS/HYPOTHESIS: Circulating proteins act as important hormonal signals of nutrient intake. We aimed to systematically characterise the time-resolved proteomic response to glucose ingestion in humans, and to assess its robustness following prolonged complete caloric restriction. METHODS: We conducted oral glucose tolerance tests (OGTTs) in 11 healthy volunteers before and after 7 days of complete caloric restriction and measured the response of >2900 targets through high-resolution plasma protein profiling. RESULTS: We identified a signature of 44 proteins that changed significantly following glucose ingestion, which was reproducible after 7 days without food, and was strongly (20-fold) enriched for 'stomach-specific' proteins. We report that annexin A10 (ANXA10) shows the most significant post-glucose change observed, similar to the trajectories of secreted hormones. We present observational human evidence from multiple sources suggesting that ANXA10 is secreted upon sensing an increase in gastric pH, with the stomach as the major contributing tissue. Despite a profound metabolic shift after 7 days of complete caloric restriction, characterised by delayed insulin secretion and postprandial hyperglycaemia, only four proteins showed robust evidence for a differential trajectory during both OGTTs. This included plasma levels of tryptophanyl-tRNA synthetase&#xa0;1 (WARS), for which we found a genetic association with glucose homeostasis and coronary artery disease. CONCLUSIONS/INTERPRETATION: Our exploratory study identifies the proteomic response to glucose ingestion and demonstrates its reproducibility despite major shifts in glucose homeostasis. We characterise the gastrointestinal origin of these changes, and hypothesise a hitherto under-recognised role for sensing of changes in gastric pH on the plasma proteome.

Humans

A multi-scale fusion model based on multi-phase contrast-enhanced CT for predicting pancreatic cancer resectability.

Purpose.Develop a multi-scale fusion model (MSFM) based on multi-phase contrast-enhanced computed tomography (CECT) to predict pancreatic cancer (PC) resectability, thereby assisting expert decision-making.Methods.This retrospective study enrolled 280 patients with PC from four institutions, which were randomly divided into a training cohort (202 patients) and an independent test cohort (78 patients). Three-phase CECT images (arterial, venous, and delayed phases) were used for modeling. The MSFM comprises two sub-networks: (1) a multi-phase fusion network for extracting cross-phase shared fusion features, (2) a phase-specific branch network for capturing phase-specific features; and a post-fusion strategy to generate the final predictive score by integrating the shared fusion features and three groups of phase-specific features. Additionally, a human-machine fusion deep learning model (HMfDL) was constructed by fusing the predictive score of the MSFM with expert assessments.Results.In the independent test, the MSFM achieved an AUC (area under the receiver operating characteristic curve) of 0.8385 (95% CI: 0.7521-0.9249), accuracy of 84.62%, sensitivity of 72.00%, and specificity of 90.57%. This performance outperformed single-phase models (AUC range: 0.7638-0.7781), two-phase models (AUC range: 0.7826-0.7864), and ten states-of-the-art classifiers (AUC range: 0.7404-0.7796). The HMfDL further improved the performance, reaching an AUC of 0.8626 (95% CI: 0.7853-0.9400), accuracy of 91.03%, sensitivity of 80.00%, and specificity of 96.23%. Notably, the HMfDL corrected 58.82% of misdiagnosis made by experts.Conclusions. The MSFM effectively fuses multi-phase CECT to enable highly accurate predictions of PC resectability, and provides valuable support for expert decision-making through HMfDL.

Humans

Divergent trajectories of genome architecture and chromosome evolution in ferns and angiosperms.

Ferns and angiosperms represent the two largest vascular plant lineages but exhibit striking genomic and ecological contrasts. We investigated whether differences in genome size, chromosome architecture, GC content, and stomatal traits reveal divergent evolutionary trajectories between these lineages. We assembled the most comprehensive dataset to date, integrating genome size, chromosome number and size, GC content, and stomatal traits for over 1100 fern species and compared it with an extensive angiosperm dataset. Ferns exhibited markedly lower variability and c. 16-fold slower rates of chromosome size evolution than angiosperms. A persistent positive relationship between genome size and chromosome number in ferns suggests limited cytological post-polyploid diploidization. While ferns generally possess larger stomata, this difference disappears after accounting for genome size, indicating that nucleotypic constraints, rather than lineage-specific physiology, dictate stomatal dimensions. Both groups share a unimodal GC-genome size relationship peaking at c. 14 Gbp. Larger fern chromosomes imply lower genome-wide recombination rates, potentially limiting genetic reshuffling and adaptive potential. Our results highlight fundamentally divergent evolutionary trajectories, likely shaped by meiotic symmetry in ferns and meiotic asymmetry, possibly centromere drive, and post-polyploid diploidization in angiosperms, defining the functional and genomic landscapes of these lineages across deep evolutionary timescales.

Genome, Plant

Early-stage trajectories of social-occupational functioning and long-term functional outcome prediction in early psychosis: A 12-year follow-up of the randomized controlled trial on extended early intervention.

BACKGROUND: Functional impairment in psychosis often persists despite symptomatic remission. There is a paucity of research examining early-course psychosocial functioning trajectories, and none has been conducted to examine relationship between the trajectories and prospective long-term functional outcomes in early psychosis sample. METHODS: We conducted 12-year follow-up of a randomized controlled trial on extended early intervention for first-episode psychosis to identify early-course social-occupational functioning trajectories and their baseline predictors and associations with 12-year outcomes. Participants who completed Social and Occupational Functioning Scale (SOFAS) scores at three or more timepoints between baseline and 3-year follow-up were included in the study. Premorbid adjustment, illness characteristics, symptom severity, functioning, and treatment profiles were assessed. Latent growth mixture modeling was employed to derive early-course social-occupational functioning trajectories based on SOFAS scores over 3-year follow-up. RESULTS: A total of 148 participants were included in this study, with 106 patients having completed the 12-year follow-up. Our results identified four distinct trajectories, including persistently-good class, gradually-improved class, suboptimal-stable class, and persistently-poor class. Patients in persistently-poor class had more severe negative symptoms at baseline compared to patients in persistently-good class. Patients with persistently-poor trajectory had worse long-term outcomes than those with other classes in the majority of functional measures at 12-year follow-up. CONCLUSIONS: The majority of patients were classified in early-stage suboptimal or poor functional trajectories. Above one-fourth of the participants exhibited persistently-poor social-occupational functioning trajectory, which predicted worse functional outcomes at 12-year follow-up. These findings highlighted the importance of tracking functional changes during the initial years of illness.

Humans

Biomass burning contributions to Mexico City's atmospheric CO2 estimated using a multi-isotope approach.

Fossil fuel combustion dominates anthropogenic emissions worldwide; however, special attention should be addressed to biomass burning, since it is an increasingly important contributor under warmer, drier fire-weather conditions exacerbated by climate change. These emissions could impact the atmospheric composition of heavily urbanized environments. To assess the influence of biomass burning, along with fossil fuels combustion and soil and plant respiration on Mexico City's atmospheric composition, we conducted a year-long (December 2023-December 2024) isotopic monitoring of atmospheric CO2, combining radiocarbon (&#x394;14C), CO2 stable isotopes (&#x3b4;13C, &#x3b4;18O), and CO/CO2 ratios. Once defined the isotopic signatures and the characteristic CO/CO2 that describe the sources, we performed Monte Carlo simulations under two tracer modalities (&#x394;14C + CO/CO2 and &#x394;14C + CO2 stable isotopes) for source apportionment. Results show that during the dry season, particularly in March-April, atmospheric &#x394;14C values approached and overlapped background levels despite Mexico City's fossil-fuel dominance, indicating enhanced non-fossil inputs. Moreover, backward HYSPLIT trajectories supported that these elevated &#x394;14C values coincided with regional wildfire activity. Monte Carlo results attributed up to &#x223c;34 %-60 % of local CO2 to biomass burning in April, followed by March with contributions of &#x223c;31 %-49 %. Since these biomass burning figures contrast with the official emissions inventory of Mexico City metropolitan area, which assigns <1 % of total CO2 emissions to biomass burning, this study could exhibit the emissions inventory underestimation of this source, and thus, the need to reassess and incorporate top-down isotopic constraints in fire-affected urban regions.

Mexico

Examining early-phase symptom trajectories in interpersonal psychotherapy versus antidepressant medication for adults with depression: A dynamic time warp network analysis.

BACKGROUND: Depression is characterized by substantial symptom heterogeneity, which is often concealed when examining total severity scores. Analyzing symptom-level change can improve our understanding of treatment effects and recovery processes. This study, therefore, examined dynamic symptom networks during early-phase interpersonal psychotherapy (IPT) and selective serotonin reuptake inhibitor (SSRI) antidepressant treatment, assessing patterns of symptom change across as well as differences between treatments. METHODS: Using weekly item-level Hamilton Depression Rating Scale (HAM-D) data from a randomized clinical trial comparing IPT and SSRIs for adults with depression, this preregistered study examined symptom trajectories in the first six weeks of treatment with Dynamic Time Warping (DTW). RESULTS: Depressive symptom trajectories and DTW-based symptom networks were largely similar for IPT and SSRI. In both conditions, changes in somatic symptoms of anxiety and middle insomnia tended to precede improvements in depressed mood. CONCLUSIONS: Early symptom change may occur outside the core affective domain, underscoring the importance of monitoring symptoms broadly. Symptom-level patterns may reflect patients' stage of recovery and provide clinically relevant information beyond total severity scores. The absence of differences in improvement patterns between IPT and SSRI suggest few indications for treatment selection based on baseline symptom profiles. Future research should replicate and extend these findings to subsequent treatment phases using more frequent assessments and a broader range of interventions.

Humans

New Evidence in Heart Failure: 2026 Update.

Heart failure (HF) remains a major cause of morbidity, mortality, impaired quality of life and healthcare expenditure worldwide. The global burden of HF continues to increase due to population aging, improved survival, and the growing prevalence of cardiovascular, renal, and metabolic comorbidities. Simultaneously, the pace of scientific progress in HF has accelerated considerably. Recent advances have refined our understanding of HF epidemiology, prognosis, and disease trajectories, including emerging concepts of HF improvement, remission, and recovery. The Second Universal Definition of HF has also updated the classification framework, moving beyond the traditional ejection fraction-based categories. HF is now broadly classified into two major phenotypes: heart failure with reduced ejection fraction (HFrEF) and heart failure with preserved ejection fraction (HFpEF). Novel mechanistic insights highlight the role of inflammation, immune activation, metabolic dysfunction, mitochondrial biology, and multisystem interactions in HF progression. There has also been significant progress in the characterization and management of major comorbidities, including chronic kidney disease (CKD), diabetes, obesity, atrial fibrillation (AF), pulmonary hypertension, frailty, malnutrition, and cancer. Diagnostic innovations include novel biomarkers, multi-omics technologies, artificial intelligence-based approaches, advanced imaging techniques, congestion assessment tools, and emerging digital health solutions. Important advances have occurred in specific HF aetiologies, including cardiomyopathies, cardiac amyloidosis (CA), myocarditis, arrhythmia-induced cardiomyopathy (AiCM), and Chagas cardiomyopathy. Therapeutic developments continue to reshape HF management across the spectrum of left ventricular ejection fraction. Recent evidence has focused on optimization of guideline-directed medical therapy in HFrEF, expansion of evidence-based therapies in HFpEF, and growing roles for sodium-glucose cotransporter-2 inhibitors, finerenone, incretin-based therapies, and transcatheter valve interventions. Collectively, these advances support the transition from a predominantly phenotype-based approach towards a more personalized and biologically informed model of HF care, with the potential to further improve outcomes across the entire HF spectrum.

Journal Article

USleep: efficacy of app-based audio interventions to improve sleep disturbance in working adults, a multi-arm randomized controlled trial.

STUDY OBJECTIVES: To evaluate the efficacy of three categories of standalone, audio-based sleep interventions (Bedtime Stories, Sleep Sounds, Sleep Skills) delivered via mental health application (MHapp) in improving sleep among working adults with sleep disturbance. METHODS: A multi-arm, parallel randomized controlled trial was conducted. Adults with self-reported sleep disturbances were recruited online and randomly allocated to Bedtime Stories, Sleep Sounds, Sleep Skills, or digital control. Participants completed self-report questionnaires on sleep disturbance and other related outcomes at baseline (t0) and after the 4-week intervention (t1). The primary analysis followed an intention-to-treat approach using mixed-effects models. RESULTS: A total of 495 working adults (mean age&#x2009;=&#x2009;32.7&#xa0;years; 55.8% female) were randomized. For sleep disturbance (primary outcome), the between-group Hedges' g effect sizes were very small and not statistically significant (Bedtimes stories vs. control: g&#x2009;=&#x2009;0.12, 95% CI -0.13 to 0.37, Sleep Sounds vs. control: g&#x2009;=&#x2009;0.14, 95% CI -0.11 to 0.39, Sleep Skills 0.07, 95% CI -0.07 to 0.29), with slightly greater reductions in sleep disturbance for the intervention groups than control. The same pattern was observed for sleep-related impairment, mental health, well-being, and pre-sleep arousal. CONCLUSION: Audio-based sleep interventions delivered via a MHapp did not demonstrate superior efficacy over a digital control condition in reducing self-reported sleep disturbance among working adults. Although safe and well-tolerated, their use as standalone treatments for sleep disturbance is not supported by these findings. Future research should explore effectiveness in real-world settings, including user content choice across categories, and use objective sleep measures. CLINICAL TRIAL REGISTRATION: Registered at https://www.isrctn.com/ under "Evaluating the efficacy of audio-based digital tools to improve sleep on the Unmind workplace well-being platform"; https://www.isrctn.com/ISRCTN13426045; registration number: 13426045.

Humans

Delayed maturation of the milk microbiome in women with type 1 diabetes.

AIMS/HYPOTHESIS: The breastmilk microbiome plays a crucial role in gut microbial colonisation and immune development, but little is known about how it is influenced by type 1 diabetes. METHODS: We conducted a longitudinal 16S rRNA gene sequencing study of milk from women with type 1 diabetes (n=69 pregnancies; 174 samples) and women who did not have type 1 diabetes (n=49 pregnancies; 123 samples), collected at seven timepoints from birth to 15 months postpartum. Alpha diversity (richness, inverse Simpson evenness) was analysed by generalised linear mixed models, beta diversity was analysed by Bray-Curtis dissimilarities and PERMANOVA, and differential abundance was analysed by limma. Additionally, we examined associations with maternal genetic risk score (GRS), maternal HLA type, glycaemic management (HbA1c) and breastmilk secretory IgA (sIgA), and performed a parallel analysis for the infant stool microbiome. RESULTS: A significant interaction between type 1 diabetes status and timepoint was observed for alpha diversity, both richness (p=0.01) and inverse Simpson diversity (p=0.003), indicating distinct temporal trajectories between women with and without type 1 diabetes. In those without type 1 diabetes, richness increased significantly between birth and 1&#xa0;week postpartum, but this early increase was delayed in women with type 1 diabetes to between 1&#xa0;week and 3&#xa0;months postpartum (p=0.002). Beta diversity analysis revealed earlier and more extensive compositional shifts in women without type 1 diabetes compared to those with type 1 diabetes. These differences persisted after adjusting for Caesarean delivery, BMI, parity and infant sex, and were not attributable to a delay in initiating breastfeeding. Taxa with delayed enrichment in women with type 1 diabetes included Streptococcus spp. and Rothia mucilaginosa, which metabolise human milk oligosaccharides to short-chain fatty acids to promote development of the infant's gut barrier and immune system. Maternal GRS, HLA, HbA1c or sIgA were not associated with milk microbiota diversity trajectories. In infant stool samples, alpha diversity did not differ between exposure groups, and showed no evidence of delayed maturation. Beta diversity revealed an early compositional shift between birth and 1&#xa0;week postpartum only in infants born to women without type 1 diabetes. Similarly, significant taxonomic changes between birth and 1&#xa0;week postpartum were detected only in infants born to women without type 1 diabetes, but with some taxa differing between exposure groups at 1&#xa0;week. CONCLUSIONS/INTERPRETATION: Maternal type 1 diabetes is associated with delayed early maturation of the breastmilk microbiome. Early compositional differences in microbiota restructuring were also observed in the infant gut, partially mirroring the pattern in the milk microbiome; however, sustained differences in infant gut microbiota diversity were not detected. Further investigation could determine whether these changes affect development of the infant's gut and immune system.

Humans

Longitudinal functional trajectory and surgical outcomes after intracranial meningioma resection: implications for surgical decision-making in older patients.

OBJECTIVE: As the population ages, meningiomas are increasingly encountered in older patients, yet longitudinal functional outcomes following surgery across age groups remain incompletely characterized. This study evaluated age-related differences in clinical and tumor characteristics, functional trajectory, and surgical outcomes. METHODS: This was a retrospective cohort study of 396 consecutive patients who underwent surgery for intracranial meningiomas at a single academic center between January 2023 and September 2025. Patients were stratified into 5 age groups (< 65, 65-69, 70-74, 75-79, and &#x2265; 80 years). Neurological deficits and Karnofsky Performance Status (KPS) were assessed preoperatively, at discharge, and at last follow-up. Logistic regression analyses identified predictors of prolonged length of stay (LOS) (> 5 days) and poor functional outcome at discharge (KPS < 80). RESULTS: Older patients presented with greater comorbidity burden, larger tumors, and lower preoperative KPS (all p < 0.05), while gross-total resection was achieved at comparable rates across all age groups (p = 0.504). A clinically meaningful inflection point was observed around age 75 years, with KPS < 80 at discharge rising from 7.4% and 9.7% in the < 65-year and 70- to 74-year subgroups and to 36.2% and 57.1% in the 75- to 79-year and &#x2265; 80-year subgroups (p < 0.001), and median LOS increased from 4 days in the younger groups to 9 and 7 days in the 75- to 79-year and &#x2265; 80-year groups (p < 0.001). However, recovery rates among patients who experienced functional decline at discharge were comparable across age strata. On multivariable analysis, independent predictors of prolonged LOS were age &#x2265; 75 years (OR 2.31, p = 0.019), diabetes mellitus (OR 2.85, p = 0.004), posterior fossa location (OR 2.1, p = 0.008), tumor diameter (OR 1.33, p < 0.001), postoperative edema (OR 2.58, p = 0.015), and neurosurgical complications (OR 3.18, p = 0.002). Independent predictors of poor functional outcome at discharge were age &#x2265; 75 years (OR 5.84, p < 0.001), lower preoperative KPS (OR 2.8, p < 0.001), posterior fossa location (OR 3.72, p = 0.003), neurosurgical complications (OR 3.56, p = 0.008), and recurrent meningioma (OR 2.89, p = 0.025). Among 70 endoscopic endonasal approach patients, higher preoperative deficit burden and subtotal resection rates were observed compared to open craniotomy, though overall functional outcomes were comparable. CONCLUSIONS: Surgical risk in meningioma resection increases from age 75 years onwards, yet recovery capacity following initial functional decline remains similar across all age groups. Preoperative functional status, tumor location, comorbidity burden, and recurrence history should guide surgical decision-making rather than age alone.

Humans

A Multi-omics Regulated Cell Death Framework Defines Immune Phenotypes and Guides Precision Therapy in Colorectal Cancer.

Colorectal cancer (CRC) is molecularly and immunologically heterogeneous, contributing to variable treatment response. Because regulated cell death (RCD) intersects with tumor metabolism, immune regulation, and therapeutic susceptibility, we built an RCD-centered framework for CRC stratification. Multi-cohort transcriptomic data were used to infer RCD subtypes with non-negative matrix factorization (NMF) and non-negative least squares (NNLS). Genomic, bulk RNA-seq, single-cell RNA-seq, and spatial transcriptomic datasets were integrated to characterize subtype-associated biology. Machine-learning models were developed for immunotherapy response and survival-risk estimation. Candidate compounds were screened by GDSC2-based drug-sensitivity modeling and molecular docking, and FSTL3 was functionally assessed in vitro. The framework separated CRC samples into two RCD-related phenotypes resembling immune-hot and immune-cold states. RCD1 showed immune activation and higher mutational burden, whereas RCD2 showed immune-suppressed features, intratumoral heterogeneity, and aggressive biology. RCD-associated signatures showed potential for predicting immunotherapy response and survival risk. Dasatinib was prioritized for immune-cold, high-risk tumors, with preliminary evidence supporting its activity in CRC cells, while functional assays suggested a role for FSTL3 in growth, invasion, epithelial-mesenchymal transition, and apoptosis regulation. These findings suggest that RCD-based multi-omics analysis may refine CRC stratification and help generate therapeutic hypotheses.

Colorectal cancer

Long-Term Weight Trajectories in Infants Receiving Prolonged Breastfeeding: Impact of Formula Supplementation.

OBJECTIVE: This study compared weight trajectories in infants breastfed for at least 1 year, with or without formula supplementation. STUDY DESIGN: A retrospective cohort of 252 infants followed in well-baby clinics. All infants were breastfed &#x2265;12 months and received complementary foods at 4-6 months. Of these, 174 received no formula, and 78 received daily formula supplementation. Anthropometric data were collected from birth to 5 years of age. RESULTS: Among males, those breastfed without formula had significantly lower body weight between 13 and 18 months compared with those receiving formula (10.20 kg vs. 10.97 kg, p < 0.001). From 19 months onward, no significant weight differences were observed and trajectories converged through 5 years. CONCLUSION: Prolonged breastfeeding in male infants is associated with lower weight in early toddlerhood; however, differences resolve by age two. These findings suggest early variations may represent physiological patterns. Further controlled studies are needed.

Humans

"Abrazos, no Balazos": Intensity of Risk for Exposure to Violence and Armed Conflict Trajectories for Adolescents and Young Adults in M&#xe9;xico 2018-2024.

PURPOSE: "Abrazos, no balazos" (Hugs, not gunshots) is the approach to violence used by the Federal Mexican government from 2018 to 2024. This study identifies distinct conceptually useful latent class growth trajectories in the annual intensity of risk for exposure to events and fatalities from violence against civilians and battles for adolescents and young adults (AYAs) in M&#xe9;xico from 2018 to 2024. METHODS: Data are from the Armed Conflict Location and Event Data project. Latent class growth analyses were conducted with four longitudinal dependent variables assessed in seven sequential years (2018-2024). RESULTS: In most of the Mexican states, AYAs experienced low intensity-flat trajectories (p >.096) in the annual intensity of risk for exposure to events and fatalities from violence against civilians and battles. AYAs who lived in states with extremely, markedly, or moderately elevated 2018 intensities of risk for exposure to violence experienced decreasing trajectories (p =.000). One latent class with a mildly elevated-increasing trajectory (p =.000) in the annual intensity of risk for exposure to violence was identified for each of the four longitudinal dependent variables. DISCUSSION: During the time that the Federal Mexican government used the "Abrazos, no balazos" approach, AYAs in the majority of the states in M&#xe9;xico had intensity of risk for exposure to violence and armed conflict trajectories that were consistent with the goals of primary and secondary violence prevention. Violence prevention efforts should be augmented in states with unfavorable trajectories.

Humans

Recovering membrane interaction kinetics of single molecules from 3D tracking data.

Interactions between cytosolic biomolecules and the bacterial inner membrane are fundamental to many cellular processes, yet directly measuring their binding kinetics in living cells remains challenging. Conventional 2D single-molecule tracking analyses can be insufficient, particularly when membrane association does not markedly alter the diffusion rate. Here, we present a method to recover membrane interaction kinetics from 3D single-molecule trajectories in rod-shaped bacteria. Using simulated 3D tracking data, we identify membrane-associated motion by quantifying how well short trajectory segments follow the circular curvature of the cell membrane. The resulting measure is further analyzed using a hidden Markov modeling framework, enabling robust discrimination between cytosolic and membrane-bound states and capturing the dynamics of state transitions without requiring diffusion-rate changes or direct colocalization with membrane markers. This work establishes a general framework for extracting membrane interaction kinetics from 3D single-molecule tracking data in live bacteria and highlights the value of realistic microscopy simulations for quantitative interpretation and systematic bias assessment.

Kinetics

Mul-PheG2P: decoupled learning and prediction-space fusion enables robust and interpretable multi-phenotype genomic prediction.

Genomic prediction of multiple phenotypes is crucial in modern plant breeding; however, existing methods struggle with negative transfer and lack interpretability, particularly across high-dimensional small-sample data and diverse species. To address this, we propose Mul-PheG2P, a novel paradigm based on decoupled learning and predictive space fusion. It employs a two-stage design: first training phenotype-specific encoders using genetic data, then decoupling phenotype-specific learning from cross-phenotype aggregation via an interpretable prediction layer. Mul-PheG2P outperforms existing methods across diverse crop datasets, including maize (Zea mays), wheat (Triticum aestivum), and tomato (Solanum lycopersicum). It provides a multi-scale interpretability chain: at the macro level, it quantifies phenotypic contributions via attention-based weighting; at the micro level, Integrated Gradients reveal the genetic basis of predictions. Notably, the model successfully identified the CCT (CONSTANS, CO-like, and TOC) motif regulating photoperiodism and the SQUAMOSA (SQUAMOSA promoter binding protein) promoter for inflorescence development, confirming its ability to capture functional biological mechanisms. These results highlight the high performance and interpretability of Mul-PheG2P, showcasing its value for low-cost, large-scale screening to advance precision breeding.

Phenotype