Search Results (829)

Decoding mental states from non-invasive neural recordings is central to brain-computer interface research. Multimodal acquisition that combines electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) couples the high temporal resolution of EEG with the spatial specificity of fNIRS, compensating for the individual limitations of each modality. While such hybrid systems achieve strong intra-subject performance, cross-subject generalization remains constrained by inter-individual variability in neural responses. This study introduces the Eigenvalue-Guided Positional Encoding Classification Transformer (EPECT), an architecture that integrates eigenvalue-aware multi-head self-attention with sinusoidal positional encoding to capture both the spectral structure of the learned feature representations and the temporal ordering of multimodal sequences. Stacked one-dimensional convolutions extract local patterns prior to transformer encoding, and global average pooling aggregates the final representation for classification. EPECT was evaluated on two publicly available EEG-fNIRS datasets covering motor imagery (MI), n-back, discrimination/selection response (DSR), and word generation (WG) paradigms under a cross-subject protocol. The model achieved classification accuracies of 97.3%, 96.3%, 98.1%, and 97.9% on the MI, n-back, DSR, and WG tasks, respectively. Ablation studies quantified the contribution of each architectural component, and integrated gradients analysis revealed structured modality-specific attribution patterns aligned with task-relevant cortical regions. Additional experiments with synthetic cortical perturbations demonstrate the sensitivity of EPECT to subtle activity changes, indicating potential utility for tracking neurorehabilitation outcomes in future clinical applications. Full article

Shelter dogs may experience long-term environmental and social stressors that can affect their behaviour and welfare. Some individuals show reduced activity, low responsiveness to environmental stimuli, and limited interaction with their surroundings. This pilot study investigated behavioural patterns and allopregnanolone concentrations in shelter dogs exhibiting these behavioural characteristics. Ten shelter dogs were enrolled and divided into two groups: five dogs showing depression-like patterns and five matched control dogs. Each dog wore a three-axis accelerometer for 30 days to quantify activity levels. Behavioural observations were conducted using video recordings, and hair samples were collected at baseline and after 30 days to assess allopregnanolone concentrations as a potential stress marker. Dogs in the case group showed significantly longer resting time than controls (p ≤ 0.05), indicating reduced activity levels. Trends toward lower levels of exploratory and social behaviours were also observed, although the differences were not statistically significant. Allopregnanolone concentrations ranged from 0.6 to 4.6 pg/mg and showed considerable inter-individual variability, with no significant differences detected between groups. These findings provide preliminary evidence of behavioural and physiological alterations in shelter dogs displaying depression-like patterns. However, further studies with larger populations are needed to validate these findings and improve welfare assessment in shelter environments. Full article

Background: Hydrogen breath testing is commonly used to assess intestinal fermentation and diagnose small intestinal bacterial overgrowth (SIBO). However, it remains unclear whether hydrogen production reflects systemic inflammatory or metabolic status. This study evaluated the relationship between hydrogen production dynamics and systemic biomarkers using a data-driven analytical approach. Methods: This cross-sectional study included 162 adults undergoing lactulose hydrogen breath testing. Hydrogen production was characterized using continuous measures, including area under the curve (AUC), early and late hydrogen responses, and unsupervised clustering-derived hydrogen response groups. Associations with serum 25-hydroxyvitamin D, C-reactive protein (CRP), leukocyte count, and interleukin-6 (IL-6) were assessed using multivariable regression models adjusted for age and body mass index (BMI). Results: Hydrogen production showed substantial interindividual variability. Unsupervised analysis identified low-, intermediate-, and high-hydrogen response groups. Differences between groups were driven mainly by overall fermentation intensity rather than distinct temporal response profiles. No significant associations were observed between hydrogen production metrics and systemic biomarkers. Hydrogen-related variables were not independently associated with vitamin D, CRP, leukocyte count, or IL-6 concentrations. In contrast, BMI was consistently associated with inflammatory markers, particularly CRP and IL-6. Correlation analyses demonstrated strong relationships among hydrogen-derived variables but weak associations with systemic parameters. Conclusions: Data-driven analysis revealed marked heterogeneity in intestinal hydrogen production but no detectable association with systemic inflammatory or metabolic markers within the present cohort. These findings suggest that hydrogen breath test metrics primarily reflect local intestinal fermentation rather than systemic physiological status. Hydrogen breath testing remains useful for assessing gastrointestinal function, but no evidence supporting its value as a marker of systemic inflammation was identified in the present cohort. Full article

Background/Objectives: Large language models (LLMs) are increasingly used by the public to seek health information, yet their accuracy in addressing common vaccine myths remains unclear. Sycophantic LLM behavior, where models align with rather than correct user-stated beliefs, poses specific risks in health contexts. Methods: We conducted an exploratory multi-vendor evaluation of three LLMs (GPT-5, Gemini 2.5 Flash, Claude Sonnet 4) using officially curated vaccination myths from Germany’s public health institution and two realistic user framings (curious skeptic, convinced believer). All model responses were independently evaluated by two blinded medical experts for misconception addressal (binary criterion applied to the response text), scientific accuracy, and communication clarity (5-point Likert scales). Additionally, blinded marketing experts ranked models for lay communication clarity. Flesch Reading Ease scores were computed for all outputs. Results: Across all myths, framings, and models (66 response items), both medical raters judged that all responses refuted the targeted misconception; no response affirmed or ignored a myth, including under the adversarial convinced believer framing. Scientific accuracy and clarity ratings were high and tightly clustered (median 4.0–4.5), with no combined score below 3 and substantial inter-rater agreement. Marketing experts independently ranked Gemini 2.5 Flash and GPT-5 highest for lay clarity. Readability analysis revealed generally low accessibility, particularly for the convinced believer framing and for Claude Sonnet 4 outputs. Conclusions: Our findings suggest that general-purpose LLMs can produce scientifically accurate, on-topic rebuttals to widely documented vaccine myths under realistic default conditions, although linguistic complexity and framing-sensitive style may limit accessibility. Whether such outputs change beliefs or behavior in hesitant individuals was not tested. With readability optimization, these outputs could serve as building blocks for myth-debunking tools, given prospective evaluation with behavioral endpoints. Full article

Background: Given that true exercise response variation on cardiorespiratory fitness in adults with coronary heart disease (CHD) is not known, this study addressed this gap. Methods: Randomized controlled trials (RCTs) comparing continuous aerobic exercise (CAE) to controls in adults ≥18 years of age with CHD were included. The primary outcome was exercise-associated inter-individual response differences (IIRDs) in cardiorespiratory fitness (VO_2peak in ml^.kg^−1.min⁻¹). Using the inverse variance heterogeneity (IVhet) model, a standard deviation of individual response difference (SD_ir) meta-analysis was conducted. Ninety-five percent confidence intervals (CIs) and prediction intervals (PIs) were calculated. Results: Twenty-eight RCTs representing 1383 participants (725 CAE, 658 control) were included. Statistically significant and clinically important improvements (≥1.0 mL^.kg^−1.min⁻¹) were observed for VO_2peak as a result of CAE ($\overline{X}$, 3.6, 95% CI, 2.8 to 4.4 mL^.kg^−1.min⁻¹, p < 0.001), but no statistically significant or clinically important IIRD based on the SD_ir were found ($\overline{X}$, 0.9, 95% CI, −1.5 to 2.0 mL^.kg^−1.min⁻¹; 95% PI, −2.4 to 2.7). Based on GRADE, the strength of evidence was of low certainty. Conclusions: There is low certainty evidence that CAE results in statistically significant and clinically important improvements in VO_2peak in adults with CHD, but no exercise-associated IIRD was observed once properly accounted for. Full article

Chronic atrophic gastritis (CAG) is a pivotal precancerous condition in gastric carcinogenesis, with progression typically following the classic Correa cascade. Although Helicobacter pylori (H. pylori) infection is widely recognized as the principal etiological factor, the persistence of gastric cancer (GC) risk in a subset of patients after successful eradication suggests that gastric microbiota dysbiosis may also contribute to CAG progression. In recent years, high-throughput sequencing technologies have revealed distinct microbial restructuring in patients with CAG, characterized by decreased microbial diversity, depletion of commensal taxa, and enrichment of opportunistic pathogens. These compositional changes are accompanied by metabolic dysfunction, activation of inflammatory signaling pathways, and disruption of immune homeostasis, which may contribute to a microenvironment permissive for precancerous transformation of the gastric mucosa. Probiotics and related microbiome-based therapeutics, including prebiotics, synbiotics, and postbiotics, have emerged as promising adjunctive strategies for H. pylori eradication and disease management. Their beneficial effects are mediated through multiple mechanisms, including remodeling of the microbial community, inhibition of pathogen colonization, modulation of host immune responses, and restoration of mucosal barrier integrity. However, whether these interventions can reverse established atrophic or metaplastic lesions remains unclear. In addition, how strain specificity, dose dependency, and interindividual heterogeneity influence clinical efficacy has yet to be fully elucidated. In this review, we summarize the compositional and functional features of gastric microbiota dysbiosis in patients with CAG, as well as the mechanisms and clinical applications of microbiome-based interventions. We further highlight current limitations in the field and discuss future directions for precision microecological therapies integrating multi-omics approaches, engineered probiotics, and artificial intelligence. These advances may provide a theoretical framework and practical guidance for the diagnosis and management of CAG and the prevention of GC. Full article

Filament–wound carbon fiber composites are widely used in lightweight structural applications, where their mechanical performance is strongly affected by manufacturing-induced heterogeneities. In this study, the tensile behavior of carbon fiber composite specimens produced by filament winding was investigated using Digital Image Correlation (DIC) to obtain full-field strain measurements. Uniaxial tensile tests were performed while monitoring the spatial distribution of strain over the specimen surface. Beyond conventional global stress–strain characterization, DIC enabled the identification of significant strain heterogeneity both within individual specimens and among different specimens manufactured under the same nominal conditions. Localized strain concentrations were observed to develop in specific regions, revealing non-uniform deformation patterns that were not captured by global measurements alone. The results demonstrate that, despite similar global mechanical responses, substantial variability exists at the local scale. This intra and inter-specimen heterogeneity highlights the influence of filament winding architecture and local variability on tensile performance. The study underscores the limitations of relying solely on global measurements and emphasizes the capability of DIC to provide deeper insight into strain distribution and damage initiation mechanisms. These findings support the use of full-field optical techniques as a powerful tool for the mechanical characterization and quality assessment of filament–wound composite structures. Full article

Radiation-induced periodontitis represents an underrecognized and mechanistically complex toxicity of head and neck radiotherapy, arising from the interplay of oxidative stress, inflammatory dysregulation, impaired bone remodeling, and epithelial barrier disruption. Despite its clinical relevance, the molecular determinants underlying inter-individual susceptibility remain poorly defined. Heat shock protein 27 (HSP27), a stress-inducible molecular chaperone, has emerged as a candidate mediator potentially linking biological pathways relevant to radiation-induced tissue injury, including redox regulation, cytoskeletal stability, DNA repair, and apoptosis control. However, no clinical or experimental study has directly evaluated HSP27 in radiation-induced periodontitis. Therefore, the proposed involvement of HSP27 in this setting should be interpreted as a biologically plausible, hypothesis-generating framework rather than evidence of a proven causal mechanism. Convergent but indirect evidence from periodontal biology, radiation-response models, inflammatory disease, and cellular stress systems suggests that HSP27 may plausibly influence periodontal tissue resilience and injury responses after radiotherapy. Therapeutic modulation of HSP27 may represent a potential investigational strategy to mitigate radiation-induced periodontitis, but this concept requires direct validation in periodontal cell-based, animal, organoid, and prospective clinical studies. This review synthesizes current mechanistic and translational evidence to evaluate HSP27 as a candidate mediator, biomarker, and investigational therapeutic target in radiation-induced periodontitis. Full article

Sustaining rice productivity under the dual constraints of freshwater scarcity and low-temperature stress represents a pressing challenge for high-latitude japonica rice systems worldwide. There is an urgent need to develop coupled irrigation–agronomic management strategies that jointly safeguard yield stability and water use efficiency (WUE) in cold-region rice production. In this study, a two-year field experiment was conducted in 2024–2025 on albic soil (Albic Luvisols, WRB; θfc 38.2% v/v, pH 5.80, clayey texture with poor permeability and a propensity for subsurface waterlogging) in the Sanjiang Plain, Heilongjiang Province, China (47°15′ N, 133°28′ E), with nine coupled “irrigation regime × auxiliary practice” treatments, comprising conventional continuous flooding, four-level controlled irrigation (CI) at lower thresholds of 60%, 70%, 75%, and 80% θfc, and their combinations with film mulching (FM) or a humic-acid-based soil amendment (SA). An interpretable machine-learning diagnostic framework was developed, with elastic net (EN) as the primary analytical model and random forest (RF) as a nonlinear control, to simultaneously identify core yield predictors and outlier treatments. The principal findings were: (i) The soil-amendment-coupled 75% θfc CI treatment (SACI) increased grain yield by 12.3% and reduced water input by 17.0% relative to conventional continuous flooding, with WUE reaching 1.801 kg m⁻³, a 35.3% gain over the control (p < 0.05); these improvements were consistent across both individual years (year × treatment interaction: p = 0.601; inter-year rank correlation ρ = 0.967). Lowering the CI threshold below 75% θfc significantly reduced grain yield through diminished effective-panicle retention. (ii) Multi-method consensus analysis (Kendall’s W = 0.871, p < 0.01) identified root volume at the milk stage as the most strongly and consistently associated statistical predictor of yield formation, with convergent mechanistic support from independent rhizosphere evidence (Eh, TTC reductive activity). Definitive causal validation awaits isotope-tracing experiments. (iii) The film-mulching × continuous-flooding treatment (FMCG) was diagnosed as a yield-response outlier (permutation test p = 0.003), three in situ rhizosphere measurements (redox potential, root TTC-reducing activity, and rhizosphere temperature) supported the proposed mechanism of hot–anoxic rhizospheric inhibition. Methodologically, this study develops a four-level evidence convergence framework that integrates intra-model self-consistency, cross-model (EN vs. RF) consensus, independent rhizosphere evidence, and distribution-free permutation testing, with Jackknife+ conformal prediction and companion Monte Carlo simulations (1000 replicates) used to quantify the reliability boundaries under small-sample conditions (n = 27). These findings provide an evidence-based irrigation–soil co-management strategy for cold-region rice production in Northeast China, and the proposed diagnostic paradigm offers a generalizable, reliability-quantified methodological template for interpretable small-sample modeling in multifactorial coupled field experiments. Full article

The complement system is a central component of innate immunity that coordinates host defense, immune surveillance, and inflammatory responses through tightly regulated proteolytic cascades. Genetic variation within complement genes contributes substantially to interindividual differences in complement activity and disease susceptibility. While coding variants directly alter complement protein structure and function, the microRNA (miRNA)-mediated control and post-transcriptional regulation is not fully understood in shaping complement gene expression across immune and inflammatory mechanisms. Complement pathway genes exhibit extensive and heterogeneous 3′-untranslated regions (3′UTRs), which serve as primary platforms for miRNA binding and RNA-binding protein interactions. Both common and rare single-nucleotide polymorphisms within coding regions and 3′UTRs can influence miRNA targeting efficiency, disrupt regulatory motifs, or alter mRNA turnover, thereby fine-tuning complement activity rather than causing complete loss of function. Here, we systematically analyzed miRNA binding sites and single-nucleotide polymorphisms (SNPs) within the 3′UTRs of complement pathway genes spanning the classical, lectin, alternative, and terminal pathways. Our analysis uncovered heterogeneous patterns of miRNA-mediated regulation across the complement system. While core complement components showed relatively sparse conserved miRNA targeting, regulatory factors, receptors, and terminal pathway proteins emerged as densely regulated nodes, harboring multiple conserved binding sites. A broad repertoire of miRNAs was predicted to engage complement genes in a pathway-specific manner, implicating these interactions in inflammation, cancer progression, metabolic regulation, and immune signaling. SNPs within miRNA-binding regions are predicted to disrupt or create regulatory interactions, providing a mechanistic basis for how non-coding genetic variation can alter gene expression and modulate disease susceptibility. Our findings indicate miRNA-mediated post-transcriptional regulation as an important yet underappreciated layer of complement system control, providing a framework for understanding how regulatory genetic variation shapes complement-driven immune responses and disease risk. Full article

Background: Chronic stress contributes to mental and physical disorders, including burnout, anxiety, and depression. While self-report assessments remain valuable, they are inherently subjective and may be insensitive to short-term psychophysiological fluctuations. Remote photoplethysmography (rPPG) enables non-contact extraction of cardiovascular signals from facial videos and has increasingly been explored for stress-related monitoring through heart rate and heart rate variability features. Objective: This preliminary study aimed to assess the feasibility, usability, and preliminary construct validity of a mobile rPPG-based application for psychophysiological stress monitoring in daily life by examining usability, stress index distributions, and associations with self-reported psychological distress. Methods: A total of 252 participants from the general population and university students completed standardized facial video acquisition using a smartphone-based rPPG application and self-report questionnaires. The app extracted pulse wave signals, computed cardiovascular features related to heart rate and pulse rate variability, and integrated them into three indices: Stress Level, Stress Recovery, and Stress Response. Correlation and regression analyses examined associations with psychological distress. Results: The three indices showed substantial inter-individual variability. Stress Level was significantly associated with anxiety (r = 0.13, p = 0.036), depressive symptoms (r = 0.13, p = 0.047), and General Emotional Distress (r = 0.17, p = 0.006). In regression analysis, Stress Level emerged as the only significant independent correlate of General Emotional Distress (β = 0.21, p = 0.017). Younger participants and women showed higher Stress Level scores. Conclusions: The present findings should therefore be interpreted as preliminary and exploratory evidence of construct validity, suggesting that the app-derived indices may capture individual differences in stress-related physiological activation in everyday contexts. Currently, the observed associations were weak, the model explained limited variance, and the results do not demonstrate clinical validity, diagnostic utility, or predictive accuracy. Looking ahead, further longitudinal studies, repeated rPPG assessments, correction-aware analyses, and validation against reference physiological measures are needed before these indices can be considered suitable for clinical or preventive use. Full article

Marine pollution monitoring increasingly relies on Biological Early Warning Systems (BEWSs), which use living organisms as continuous, integrative sentinels of water quality. The moon jellyfish Aurelia aurita is a sensitive but under-exploited candidate for this role. We present a computer-vision BEWS pipeline that is unsupervised at inference time and operates without labelled pollution-response data, converting side-view aquarium video of single A. aurita medusae into a binary pollution alarm. Per-frame YOLO bounding-box detections are reduced to a continuous bell-area signal and a centroid trajectory, from which eleven pulsation, kinematic, and detection-quality features are extracted on 60 s sliding windows. A per-animal baseline is fitted on a clean-water baseline (recommended ≥15 min), and a two-layer detector—fast outlier detection on the mean absolute z-score with a k-of-N rule, plus one-sided CUSUM (cumulative sum) accumulation—flags any sustained deviation. Validation on six adult medusae exposed to diesel-WAF detected all six animals (95% CI 54–100%) and produced no false alarms in 203 clean-window opportunities (exact 95% upper bound 1.8%; rule-of-three estimate ≈1.5%). First-alarm latencies ranged from 1.0 to 23.7 min, and the observed responses were described as three descriptive patterns in this pilot dataset: sharp step-change, slow drift, and mixed. The deployed anomaly scoring step contains no neural-network weights, runs in under 300 lines of Python, and is designed for field-portable use in settings where a stationary side-view camera can be positioned alongside an aquarium, although field validation remains required. Per-animal anomaly detection accommodates the strong inter-individual variability of the diesel-WAF response that limits supervised clean-versus-polluted classification at this sample size. Full article

Introduction: Labor pain is among the most intense forms of acute pain, mediated in part by excitatory glutamatergic neurotransmission within central nociceptive pathways. Glutamate plays a key role in spinal dorsal horn signaling and central sensitization, yet its peripheral dynamics during labor and in response to different analgesic modalities remain unclear. This exploratory study aimed to evaluate whether maternal salivary glutamate levels differ between epidural labor analgesia and systemic morphine analgesia during normal vaginal delivery. Method: In this observational comparative study, 36 women were selected to either epidural analgesia (n = 16) or systemic morphine analgesia (n = 20). Salivary samples were collected during active labor and analyzed for glutamate concentration using a validated enzymatic colorimetric assay. Clinical and demographic data were recorded. Non-parametric tests were applied due to non-normal distribution of glutamate levels. Results: Baseline maternal and perinatal characteristics were comparable between groups. Median salivary glutamate levels were higher in the epidural group than in the morphine group (5.32 nmol/µL [IQR 2.83–8.00] vs. 3.99 nmol/µL [IQR 2.26–8.03]), but the difference was not statistically significant (p = 0.599). Glutamate concentrations showed marked inter-individual variability (0.14–29.89 nmol/µL) and a right-skewed distribution. No significant associations were observed between glutamate levels and maternal age, Body Mass Index, gestational age, birth weight, or obstetric comorbidities. Conclusion: In this exploratory cohort, maternal salivary glutamate concentrations did not differ significantly between epidural labor analgesia and systemic morphine analgesia during labor. The variability observed suggests complex and heterogeneous regulation of peripheral glutamatergic activity in parturition. Further larger-scale studies integrating central and peripheral measurements are warranted. Full article

Background: Appetite regulation is governed by a complex neuroendocrine network that integrates peripheral peptide signals with hypothalamic and brainstem circuits to coordinate energy intake and maintain energy homeostasis. Disruption of these pathways contributes to obesity and other disorders characterised by dysregulated feeding behaviour. Objective: To map and synthesise the current evidence on the role of appetite-regulating peptide hormones and central neural pathways in appetite control, obesity pathophysiology, and emerging therapeutic approaches. Methods: A scoping review of the literature was conducted to identify and synthesise evidence relating to the physiological and pathological mechanisms of appetite regulation. The review examined the actions of key peptide hormones, including ghrelin, glucagon-like peptide-1 (GLP-1), peptide YY (PYY), leptin, and insulin, their interactions within the gut–brain axis, and their effects on central appetite-regulating circuits. Results The evidence highlights the central role of the arcuate nucleus in integrating peripheral hormonal signals with neural pathways controlling feeding behaviour. Appetite regulation is mediated by the balance between orexigenic neuropeptide Y/agouti-related peptide (NPY/AgRP) neurons and anorexigenic pro-opiomelanocortin/cocaine- and amphetamine-regulated transcript (POMC/CART) neurons, with further modulation by the paraventricular, lateral, and ventromedial hypothalamic nuclei. The literature identifies hormone resistance, impaired satiety signalling, and altered neuroendocrine feedback as major contributors to obesity. Evidence on therapeutic interventions demonstrates the potential of GLP-1 receptor agonists, including liraglutide and semaglutide, and the dual incretin agonist tirzepatide, while also highlighting challenges related to treatment durability, adverse effects, and weight regain following discontinuation. Conclusions: Current evidence demonstrates that appetite regulation involves highly interconnected peripheral and central signalling pathways. The reviewed literature supports the development of multi-target and precision-based therapeutic strategies for obesity and identifies important areas for future research, including mechanisms of treatment resistance, long-term efficacy, and inter-individual variability in neuroendocrine responses. Full article

Background/Objectives: Postoperative remodeling and positional deviations of the mandibular coronoid process (CP) after orthognathic surgery remain insufficiently characterized, particularly in three-dimensional analyses. The aim of this study was to evaluate qualitative and quantitative CP changes following bimaxillary orthognathic surgery using a deep learning-assisted three-dimensional workflow. Methods: This retrospective study included 75 patients treated with combined orthodontic–surgical therapy, including 25 patients with skeletal Class II malocclusion and 50 patients with skeletal Class III malocclusion. Preoperative and 6-month postoperative computed tomography scans were analyzed. Automatic segmentation and three-dimensional reconstruction were performed using a convolutional neural network based on the nnU-Net architecture. Qualitative assessment included evaluation of CP displacement patterns and visualization of local surface differences using heat maps. Quantitative analysis included volumetric assessment of preoperative and postoperative CP models, calculation of apposition-compatible (Vapo) and resorption-compatible (Vres) volumetric changes, and mixed-effects modeling accounting for within-patient correlations. Results: Medial displacement of the CP predominated in both skeletal classes and was more frequent in Class III patients. Qualitative surface analysis demonstrated a consistent location-dependent remodeling pattern, characterized by predominant apposition-compatible changes on the lateral and medial surfaces and predominant resorption-compatible changes along the anterior border. Quantitative analyses revealed an overall positive remodeling balance, although substantial inter-individual variability was observed. Mixed-effects analyses demonstrated no significant overall effects of side or skeletal class on volumetric remodeling; however, a significant interaction between side and skeletal class was identified for net remodeling balance. A significant random patient effect indicated considerable variability in remodeling response among individuals. Conclusions: AI-assisted three-dimensional analysis enables a reproducible assessment of postoperative CP remodeling following orthognathic surgery. Coronoid process remodeling is characterized by heterogeneous, location-dependent surface changes and substantial inter-individual variability. The observed remodeling patterns are compatible with adaptive responses to altered postoperative biomechanical conditions, although the underlying biological mechanisms remain to be clarified. Full article