Search Results (24,721)

Background: Age- and cancer-related sarcopenia and malnutrition are common in older patients with colorectal cancer (CRC) and may negatively influence treatment tolerance and prognosis. However, the comparative prognostic value of post-chemotherapy changes in CT-based body composition parameters at the third lumbar vertebra (L3) and the twelfth thoracic vertebra (T12) levels, and their associations with nutritional indices, remain unclear. This study aimed to examine and compare the prognostic relevance of post-chemotherapy body composition changes at L3 and T12 and to assess their relationship with nutritional indices in older patients with metastatic CRC (mCRC). Methods: This retrospective study included 87 older patients with mCRC. Baseline and ~3-month follow-up CT scans were analyzed at L3 and T12 using 3D Slicer to quantify skeletal muscle index (SMI), subcutaneous adipose tissue index (SATI), visceral adipose tissue index (VATI), visceral-to-subcutaneous fat ratio (VSR), and intramuscular adipose tissue index (IMATI). Changes (Δ) in CT-derived body composition after chemotherapy were calculated as percentage change using ((follow-up − baseline)/baseline) × 100. Prognostic Nutritional Index (PNI) and Geriatric Nutritional Index (GNRI), which are established nutritional assessment tools, were calculated from baseline laboratory/anthropometric data. Agreement between T12 and L3 was assessed, and associations with grade ≥3 toxicity, progression-free survival (PFS), and overall survival (OS) were evaluated using multivariable models and ROC analyses. Results: Mean age was 69.0 ± 4.5 years (59 male/28 female), and 26.4% developed grade ≥3 adverse events. Over 3 months, mean SMI declined significantly at both L3 (46.7 ± 8.8 → 42.8 ± 9.8 cm²/m²) and T12 (34.6 ± 8.2 → 31.6 ± 8.1 cm²/m²) (p < 0.001 for both), accompanied by decreases in VATI and VSR; T12-IMATI increased significantly. Baseline PNI showed a weak positive correlation with L3-SMI (r = 0.302, p = 0.033), whereas GNRI showed moderate correlations with SMI at L3 (r = 0.502, p < 0.001) and T12 (r = 0.317, p = 0.025) and was associated with longitudinal changes in muscle metrics. T12-SMI consistently yielded lower values than L3-SMI, and agreement varied by compartment (best for SATI; weakest for VSR). Lower GNRI and greater L3-SMI loss were independently associated with grade ≥3 toxicity; ΔL3-SMI showed the highest discrimination (AUC = 0.79, 95% CI = 0.69–0.87, p < 0.001; cut-off >5.1% loss). All patients progressed (median PFS 7.6 months); mortality was 82.8% (median follow-up: 25 months). In multivariable analysis, PFS, CRP, GNRI, and ΔL3-SMI remained independently associated with OS. ΔL3-SMI provided the strongest mortality discrimination (AUC = 0.85, 95% CI = 0.74–0.94, p < 0.001; cut-off >10.4% loss), while ΔIMATI was also informative (AUC = 0.71, 95% CI = 0.59–0.82, p = 0.023). Conclusions: In older patients with mCRC, early post-chemotherapy skeletal muscle loss—particularly at the L3 level—showed the strongest prognostic association with severe toxicity and mortality. GNRI provided complementary prognostic information as a marker of baseline immunonutritional reserve. Although T12-derived measurements were correlated with L3-derived values, systematic bias suggests that they should not be interpreted interchangeably for longitudinal risk stratification. Full article

Accurately characterizing the kinematics of slow-moving urban landslides remains a major scientific and operational challenge, because no single monitoring technique can simultaneously provide spatially continuous deformation patterns and reliable three-dimensional displacement measurements. This study investigates the spatial and temporal evolution of a slow-moving landslide affecting the University of Azuay campus in Cuenca (Ecuador), where ongoing ground deformation has caused structural damage to several buildings. An integrated monitoring strategy combining GNSS measurements, Sentinel-1 multi-temporal DInSAR analysis, and geophysical investigations (ERT and seismic profiling) was adopted to characterize landslide kinematics and constrain subsurface conditions. GNSS observations revealed that the north–south displacement component was dominant, with cumulative displacements exceeding 20 cm during the monitoring period (from July 2021 to June 2024), while east–west displacements were on the order of 10 cm. MT-DInSAR analysis delineated the spatial extent of the unstable area and identified mean deformation rates of up to approximately −1.5 cm/year in the central sector of the landslide. The combined interpretation of geodetic and geophysical data indicates that slope instability is controlled by saturated fine-grained layers and mechanical contrasts, with the basal sliding zone associated with weak levels of the Mangan Formation. Overall, the results demonstrate the value of a multi-sensor, component-wise monitoring strategy for improving the reliability of deformation estimates and for supporting landslide risk assessment and land-use planning in complex urban environments. Full article

Background: Micro- and nanoplastics (MNPs) are widespread environmental contaminants with growing evidence linking them to adverse health effects, including progression and worsening of allergic diseases. As allergies are rapidly increasing among youth (affecting almost 30% of children), this demographic represents a vulnerable population facing emerging environmental threats. Since no prior study has investigated MNP risks perceptions in an allergic population, this study aimed to assess public awareness and risk perception of MNP in Croatian youth, focusing on the influence of urbanicity, education, and allergy status. Methods: A total of 1155 participants (aged 6–18 years) were recruited from three Croatian regions as part of the EU Horizon 2020 IMPTOX and the Horizon Europe EDIAQI studies. Allergy status was determined via skin prick tests (SPT), and standardized questionnaires were used to collect data on MNP awareness and perception. Results: Awareness was significantly higher among allergic individuals (89.5% vs. non-allergic 79%, FDR p value= 0.036) and those with university-level education (88.3% vs. elementary 63.3%, FDR p value = 0.050). Allergic participants were also more concerned about food contamination by MNPs (87.7%) compared to non-allergic individuals (79.2%), FDR p value = 0.005). Media and social media were the primary sources of information regarding MNPs (FDR p value = 0.026). Conclusions: Education and allergy status are the strongest predictors of MNP awareness and related risk perceptions in the Croatian population. Targeted public health communication and educational strategies are needed to translate basic awareness into informed behavioral and policy engagement. Full article

Background/Objectives: Routine liver biopsies play an important role in monitoring liver allografts but carry non-negligible risks. This pilot study assesses the feasibility of dynamic long-axial field-of-view (LAFOV) [¹⁸F]FDG PET/CT as a non-invasive alternative to biopsy. Methods: Liver transplant (LTx) recipients meeting the inclusion criteria of ≥10 months post-transplantation and scheduled routine biopsy were prospectively enrolled, along with healthy controls. All participants underwent dynamic LAFOV [¹⁸F]FDG PET/CT, followed by biopsy in LTx recipients, who were stratified by inflammatory severity using the BANFF score. Hepatic kinetic parameters (K1, k2, k3, k4) and SUVmean/SUVmax were compared using Mann–Whitney U tests. Correlations were assessed using Spearman’s rank correlation. A p-value < 0.05 was considered significant. Analyses were performed in RStudio (version 2024.12.10563). Results: Sixteen LTx recipients (mean age 48.6 years; seven female, nine male) and eight healthy controls (mean age 35.4 years; six female, two male) were included. Healthy controls had mean k3 and k4 values of 0.0037 min⁻¹ ± 0.0003 min⁻¹ and 0.0019 min⁻¹ ± 0.0011 min⁻¹, respectively. LTx recipients showed significantly higher k3 and k4 values, both when including and excluding patients with biopsy-confirmed inflammation. Descriptive comparisons between LTx recipients with and without significant inflammation (n = 3) showed no clear differences. Spearman analysis showed no significant correlations between the BANFF score and kinetic parameters. The strongest degree of correlation was found between BANFF score and k3, indicating a moderate positive but non-significant association (k3: rs = 0.396, p = 0.128). Conclusions: Elevated k3 and k4 values in LTx recipients were not explained by allograft inflammation, suggesting altered FDG kinetics post-transplant. These differences may confound [¹⁸F]FDG PET interpretation. Larger studies are needed to assess the clinical applicability of dynamic LAFOV [¹⁸F]FDG PET/CT. Full article

Background: Manganese (Mn) is an essential trace element with antioxidant properties; however, excessive exposure may contribute to inflammation and vascular dysfunction. Hair analysis provides an indicator of long-term Mn exposure. This study evaluated the relationship between hair Mn levels, acute coronary syndrome (ACS), coronary artery disease (CAD) severity, and cardiovascular risk factors, with particular emphasis on metabolic status in a cardiometabolic population. Methods: Hair Mn concentration was measured using inductively coupled plasma optical emission spectrometry (ICP-OES) in 80 patients (mean age 67 ± 11 years; 28.8% women) undergoing coronary angiography for suspected ACS. Final diagnoses included stable CAD (N = 42) and ACS [ST-elevation myocardial infarction (STEMI) N = 17, non-ST-elevation myocardial infarction (NSTEMI) N = 12, and unstable angina (UA) N = 9]. CAD severity was quantified using the SYNTAX score and the Coronary Artery Surgery Study Score (CASSS). Associations with clinical variables were assessed using non-parametric tests and Spearman correlations. The median SYNTAX score was 13.8 (range 0.0–68.5), and the median hair Mn concentration was 0.22 ppm (range 0.01–1.65). Results: SYNTAX scores were higher in ACS than in stable CAD (p = 0.027), with the highest values observed in NSTEMI. Hair Mn levels did not differ among diagnostic groups and showed no association with CASSS or SYNTAX (R = −0.11; p = 0.348). No differences were detected with respect to sex, smoking, prior myocardial infarction, hypertension, hyperlipidemia, or type 2 diabetes. A modest inverse correlation was observed between hair Mn and body mass index (BMI) in unadjusted analysis (R = −0.25; p = 0.03), but this association was not robust after correction for multiple comparisons, suggesting a potential exploratory link between manganese homeostasis and cardiometabolic status. Conclusions: Although hair Mn concentration was not associated with angiographic indices of CAD severity or ACS subtypes, the observed relationship with BMI may indicate a role of Mn homeostasis in cardiometabolic regulation. Larger prospective studies are required to clarify these associations. Full article

Activated sludge treatment is plagued by high secondary pollution risks, and ship antifouling paint particles (APPs) as hazardous heavy metal-rich solid wastes generated from hull derusting wastewater, pose severe environmental threats and intractable disposal dilemmas. This study developed a novel pilot-scale activated sludge reduction process coupling APPs-derived carbon-based catalysts with ultrasound-Fe²⁺/peroxydisulfate (PDS) advanced oxidation. Columnar catalysts were fabricated via direct carbonization-molding using waste APPs from an 82,000 deadweight bulk carrier were used as the sole raw material to prepare columnar catalysts via direct carbonization-molding; single-factor and orthogonal experiments optimized process parameters, Scanning Electron Microscopy (SEM), Energy Dispersive Spectroscopy (EDS) and X-ray Photoelectron Spectroscopy (XPS) characterized catalyst and sludge properties, free radical quenching experiments elucidated reaction mechanisms and a 90-day continuous pilot run assessed catalytic stability. The process achieved a 43.5% sludge removal rate under optimal conditions, accompanied by 100% toluene and 92.3% phenolic compound degradation, as well as efficient total phosphorus (TP) and total nitrogen (TN) removal. Mechanistic studies via characterization and quenching experiments confirmed the catalyst enhanced PDS activation through free/non-free radical synergy and accelerated Fe²⁺/Fe³⁺ redox cycling. A 90-day continuous pilot operation demonstrated excellent long-term catalytic stability, with sludge removal rate remaining above 38%. This “waste treating waste” technology realizes high-value APPs resource utilization, provides a low-carbon sludge disposal pathway, and offers a scalable solution for collaborative pollution control in the wastewater treatment and shipping industries. Full article

Background and Aim: Lymphovascular invasion (LVI) is a negative prognostic factor for gastric cancer, but detection limitations hinder its clinical utility and subtype analysis. This study aimed to explore the predictive value of LVI and its subtypes in the prognosis and recurrence patterns of gastric cancer using our enhanced detection method. Methods: We reviewed 2057 patients who underwent gastrectomy in 2018, of whom 1073 met the inclusion criteria. Propensity score matching (PSM) was performed to balance baseline clinicopathological characteristics. Results: After PSM, 311 patients were assigned to the LVI+ group and 311 to the LVI- group. The LVI+ group demonstrated a poorer prognosis. Subtype analysis revealed that lymphatic invasion (LI), but not venous invasion (VI), was associated with poor prognosis in the matched cohort. Stratified by pathological tumor-node-metastasis (TNM) stage, LVI+ and LI+ patients had worse prognosis in Stages I and III, while VI+ patients had worse prognosis in Stage III. Stratified by lymph node status, LVI+ predicted poorer prognosis in both node-negative (N0) and node-positive (N+) patients, and LI+ was also associated with worse prognosis among N+ patients, whereas VI+ was not significantly associated with prognosis in either subgroup. Recurrence analysis indicated that LVI+ was associated with distant and peritoneal metastases, whereas LI+ was associated with local recurrence, distant and peritoneal metastases. Conclusions: Lymphovascular invasion was associated with adverse prognosis in resectable gastric cancer, with lymphatic invasion showing a stronger prognostic impact than venous invasion. These findings indicate that refined assessment of lymphovascular invasion may complement conventional TNM staging in postoperative risk stratification. Full article

To address the challenges of coordinated optimization in building integrated energy systems (IES) under the dual-carbon targets—characterized by strong multi-energy coupling, significant uncertainty in renewable generation, and stringent safety constraints—a novel safe deep reinforcement learning algorithm, Safe-DDPG, is proposed. Traditional deep reinforcement learning methods often suffer from high constraint-violation risk and limited policy reliability due to coupled objectives in building IES optimization. To overcome these limitations, a dual-channel critic architecture is designed to independently evaluate and decouple economic and safety objectives. In addition, a dynamic safety–penalty mechanism based on logarithmic barrier functions is introduced, together with an adaptive exploration strategy, enabling dynamic balancing between economic cost and constraint satisfaction according to system states during training. Experimental results demonstrate that, compared with mainstream algorithms, Safe-DDPG achieves substantial improvements across multiple key performance indicators: safety violations are reduced by up to 96.7%, average daily operating costs decrease by 18.5%, and cumulative rewards increase by more than 30%. Ablation studies further confirm the effectiveness and necessity of each core component. Two DRL methods from reference papers are reproduced, and their performance is compared with the proposed method in the existing experimental results, showing that the proposed method has significant advantages in reward value and economic cost. This work provides a safe, reliable, and efficient reinforcement-learning-based approach for optimization and scheduling of building energy systems under complex operational constraints. Full article

Mercury (Hg) bioaccumulation in freshwater fish represents a major pathway of human exposure, particularly in cascade reservoir systems where hydrological retention and legacy contamination can enhance methylmercury (MeHg) formation and trophic transfer. This study quantified total mercury (THg) concentrations in seven tissues of seven fish species from the Arda River cascade (Bulgaria). Multi-tissue measurements were integrated with morphometric predictors, multivariate statistical analyses, and combined deterministic and probabilistic human-health risk assessments. Muscle and liver contained the highest THg concentrations, whereas gills and gonads exhibited the lowest levels. Predatory species and larger individuals accumulated significantly more Hg, reflecting trophic magnification and size-dependent exposure. A longitudinal gradient across the cascade reservoirs suggests hydrological retention effects influencing mercury distribution. Species- and tissue-specific size–Hg relationships further indicate heterogeneous bioaccumulation dynamics among taxa. Risk assessment indicated acceptable exposure for adults and pregnant women at average consumption (140 g·week⁻¹), but elevated exposure for children consuming high-Hg predators. Monte Carlo simulations (N = 30,000) revealed upper-tail risks, while Safe Weekly Intake thresholds provided species-specific consumption limits. These findings highlight the value of integrating multi-tissue monitoring with probabilistic risk modelling to support evidence-based fish-consumption advisories in contaminated freshwater systems. Full article

Growth differentiation factor 15 (GDF15) is a stress-responsive cytokine strongly associated with aging, multimorbidity, and cardiovascular disease. Although prior studies have established its prognostic value in high-risk populations, its role in the general population remains less defined. The aim of this study was to determine if there is an association between plasma GDF15 levels, heart disease and mortality in a representative population-based cohort. We analyzed 1532 participants (mean age 55 years; 54.6% women) with available baseline plasma GDF15 concentrations. Participants were stratified according to an optimal cutoff of 1081 pg/mL, derived from ROC curve analysis for mortality. Associations with prevalent heart disease were assessed using multivariable logistic regression models adjusted for cardiovascular risk factors and NT-proBNP. Mortality was analyzed using Cox proportional hazards models, with model performance evaluated by C-index and time-dependent ROC curves. Individuals with GDF15 > 1081 pg/mL were older and exhibited a more adverse cardiometabolic profile with higher prevalence of comorbidities. Elevated GDF15 was independently associated with ischemic cardiomyopathy (OR 3.34, 95% CI: 1.38–8.11), particularly in men (OR 4.26, 95% CI: 1.40–12.96), but not in women. No independent associations were observed with arrhythmias, valvulopathy, or heart failure after adjustment for NT-proBNP. During a median follow-up of 6.2 years, 51 deaths occurred. Elevated GDF15 independently predicted all-cause mortality (HR 2.47, 95% CI: 1.19–5.13), though the effect was attenuated after adjustment for NT-proBNP. GDF15 improved model discrimination (ΔC-index = +0.01; LRT p = 0.011) and showed robust time-dependent predictive ability, with AUCs of 0.76, 0.82, and 0.85 at 2, 4, and 6 years, respectively. In this population-based cohort, elevated GDF15 identified individuals with an adverse health profile, was independently associated with ischemic cardiomyopathy in men, and predicted mortality. Although its incremental predictive value over NT-proBNP was modest, GDF15 could provide complementary biological information and may enhance multimarker strategies for cardiovascular risk stratification in the general population. Full article

Ecological restoration is increasingly applied as an effective strategy for mitigating environmental risks associated with tailings impoundments. However, plant establishment and ecological recovery in tailings substrates are often limited by unfavorable physicochemical properties and potential toxicity. This study investigated the changes in soil microbial community structure and diversity under the synergistic remediation of compound organic fertilizer and plants. Field plots subjected to combined organic fertilizer–plant remediation in a tailings impoundment in northern China were selected. The high-throughput sequencing of bacterial 16S rRNA genes and fungal ITS regions was performed alongside analyses of soil physicochemical properties. Compared to the untreated tailings soil, remediated soils showed pH values closer to neutrality, lower electrical conductivity, and significantly higher organic matter content, indicating an overall reduction in environmental stress and potential toxicity. The relative abundance of copiotrophic bacteria, such as Proteobacteria, increased, whereas that of stress-tolerant taxa adapted to extreme environments, such as Firmicutes , decreased. Although slight variations in dominant groups were observed among plots with different plant species, key microbial groups contributing to soil environmental improvement were largely consistent. These findings demonstrate that this combined remediation effectively improves the physicochemical properties and microbial community structure of tailings soil, providing a risk-oriented and ecologically sustainable strategy for the ecological restoration of similar sites. Full article

Uneven urbanization can lead to significant quantities of vacant and abandoned land while exacerbating urban heat island (UHI) effects and simultaneously adversely affecting socioeconomically disadvantaged communities. This study examines the correlation between land surface temperature (LST) and urban vacant and abandoned land in socially vulnerable neighborhoods in Houston, TX, USA, where extreme heat can present significant environmental and public health challenges. Six critical study locations exhibiting a social vulnerability index (SVI) over 0.7 and average land surface temperature (LST) values surpassing 82 °F (27.8 °C) are analyzed through spatial analytics and drone footage. Findings indicate that vegetated vacant spaces help mitigate urban heat by decreasing land surface temperature, but abandoned structures exacerbate temperatures due to heat retention from non-permeable surfaces. Findings suggest that elevated socioeconomic vulnerability correlates with increased land surface temperature, exacerbating heat-related hazards in at-risk communities. In this six-site sample, the abandonment rate exhibited a positive correlation with the site mean land surface temperature (exploratory linear fit: +2.42 °F [0.74, 4.11]/+1.35 °C [0.41, 2.28] per +1% increase in abandonment; to be interpreted as exploratory and potentially confounded). Results provide critical insights for climate resilience planning and urban heat reduction through high-resolution thermal and geographical analysis, highlighting the impact of vacant and abandoned land on LST. Such findings endorse certain urban cooling techniques, including land reutilization and green infrastructure, to enhance environmental equality and adaptation. Full article

Postoperative stroke is a serious and fatal condition that often affects elderly surgical patients. This rare but severe complication arises from complex interactions between comorbidities, physiologic instability and demographic disturbances that traditional risk tools often fail to capture.This study aims to develop and validate a machine learning model with an improved ability to predict the risk of postoperative stroke in elderly patients utilising the comprehensive clinical and demographic ICU data from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. External validation was performed on MIMIC-III and the eICU Collaborative Research Database, with eICU being the primary validation set. We identified postoperative surgical intensive care unit (SICU) patients aged 55 years or older from all databases. A strict temporal window of the first 24 h of ICU admission was applied across all three datasets while extracting features like laboratory measurements and vital sign summaries in order to ensure that all predictor values were derived from a fixed observation period at the beginning of ICU stay. After preprocessing, applying Multivariate Imputation by Chained Equations (MICE) imputation and initial screening of 88 candidate variables, 20 clinically meaningful predictors were selected through a multistage feature selection pipeline incorporating RFECV and permutation importance. SHAP analysis and LIME analysis were used for interpretability. We evaluated ten machine learning techniques, including Logistic Regression, Decision Tree, Random Forest, K-Nearest Neighbors (KNNs), Support Vector Machine (SVM–RBF Kernel), Gradient Boosting (GBDT), Neural Network, XGBoost, CatBoost, Naive Bayes. Among them, Random Forest demonstrated strong predictive performance by achieving an AUROC of 0.8072 (95% CI [0.7890, 0.8253]) on the internal validation set. The model also achieved AUROC of 0.7557 (95% CI [0.7267, 0.7794]) and 0.9144 (95% CI [0.8893, 0.9378]) on the external validation sets eICU and MIMIC-III, respectively. Mean systolic blood pressure, Elixhauser score, minimum calcium, and minimum INR (PT) were consistently identified as the most influential predictors through both SHAP analysis and LIME analysis, thus strengthening model interpretability. Our findings suggest that a Random Forest-based predictive model can provide an accurate and generalisable prediction of postoperative stroke in elderly ICU patients using routinely collected physiologic and laboratory data. This also supports early risk stratification and targeted postoperative monitoring. Full article

Objective: The integration of artificial intelligence (AI) into computer-aided detection (CAD) is a major innovation in lung cancer diagnosis. However, its reliability in detecting the earliest radiographic sign—faint ground-glass opacities (GGOs) indicating pre-invasive adenocarcinoma—remains a critical, unquantified gap. This study aimed to perform a rigorous failure analysis to define the specific conditions under which commercial AI/CAD systems fail in a low-dose CT (LDCT) screening setting. Methods: In this retrospective diagnostic accuracy study, a primary cohort of 100 patients and an external validation cohort of 50 patients with moderate/low-risk nodules on LDCT were included. An expert reference standard was established by a consensus panel of three thoracic radiologists. Two independent, commercially deployed AI/CAD systems from different vendors (Vendor A & Vendor B) processed all cases. Nodules confirmed by experts but missed by AI were analyzed. Their morphology was categorized, and their mean CT attenuation (HU) was measured via manual region-of-interest placement. Results: The AI systems demonstrated significant and comparable false negative rates in the combined cohort: 12.7% for Vendor A and 14.7% for Vendor B. The vast majority of missed nodules were GGOs (92.3% and 78.6%, respectively, in the primary cohort). Crucially, quantitative analysis revealed a consistent density threshold for AI failure: the mean CT value of missed GGOs was −737 ± 51.50 HU for Vendor A and −727 ± 70.07 HU for Vendor B. This algorithmic blind spot was fully corroborated by the external validation cohort (−741 ± 48.2 HU and −733 ± 62.5 HU, respectively). Anatomical complexity (juxta-pleural/endobronchial location) was a secondary failure factor. Conclusions: This study identifies a quantifiable “−730 HU blind spot” as a common limitation of current commercial AI/CAD systems in diagnosing early lung adenocarcinoma. This finding represents a pivotal advancement in understanding AI’s role in diagnostics: it is not infallible. To innovate and safeguard screening efficacy, radiologists must adopt a human–AI collaborative model with mandated manual verification targeting low-attenuation opacities, ensuring this diagnostic innovation fulfills its promise while mitigating the risks of overdiagnosis. Full article

Background/Objectives: Social rejection during the latency stage is a significant risk factor for children’s emotional and social development. Whereas earlier research focused primarily on individual characteristics of rejected children, contemporary perspectives emphasize peer-group processes, including norm formation, hierarchies, and social status structures. Although autonomy has been widely examined as an individual developmental construct, less attention has been given to its possible collective expression within the classroom peer group. This study aimed to explore how children understand and experience group autonomy and to clarify its role in social status and peer rejection. Methods: Twelve classroom-based focus groups were conducted with 140 fifth-grade children from five public elementary schools in Israel. Discussions were initiated using a projective narrative describing ambiguous peer exclusion. Data were audio-recorded, transcribed verbatim, and analyzed using thematic analysis. Coding was conducted independently by two researchers and refined through iterative comparison and reflexive procedures. Results: Three themes emerged: (1) a shared longing for classroom-based group autonomy and collective decision-making; (2) group autonomy as an implicit hierarchical criterion shaping social status, whereby reduced reliance on adults and alignment with peer norms were associated with higher status, while adult dependence was linked to marginalization; and (3) an ambivalent structure of autonomy, as children valued peer independence yet expressed fear of adult punishment and responsibility. Conclusions: Findings suggest that during the latency stage autonomy shifts toward a collectively organized peer-group process. Recognizing group autonomy as a developmental dimension may deepen understanding of social status and peer rejection within classroom contexts. Full article