Search Results (11,022)

This study presents a closed-loop digital–physical workflow for manufacturing patient-specific anatomical models and surgical guides for maxillofacial reconstruction. The workflow combines medical-image segmentation, additive manufacturing of anatomical models, surgeon-led physical simulation, re-digitization of the modified models, landmark-based and surface-based alignment with the original CT-derived anatomy, with FFD used as a limited supporting approach for localized geometry updating, CAD design, and fabrication of sterilizable guides. Technical feasibility was examined in two detailed mandibular reconstruction cases involving temporomandibular joint prosthesis implantation. The workflow was subsequently used in adapted forms in eight clinically heterogeneous mandibular reconstruction cases related to oncological treatment. These cases are reported as supplementary clinical implementations and were neither treated as direct replications of the complete closed-loop methodology nor pooled for quantitative comparison. In the two detailed cases, the guides were verified on the anatomical models, used intraoperatively, and followed by postoperative imaging providing qualitative clinical confirmation of implant positioning. The study did not include a direct CT-based control workflow or standardized geometric deviation analysis. Therefore, operating-time and cost effects are reported as case-specific observations and an illustrative scenario rather than comparative evidence. The main contribution is the physical-to-digital feedback step, which allows surgeon-introduced modifications of a printed model to be transferred back to the digital geometry before final guide design. The results support the technical feasibility and adaptability of the workflow, while prospective quantitative validation remains necessary. Full article

Background/Objectives: Resistance training with aerobic active recovery (RT-AR) is a proposed session architecture in which controlled low-impact aerobic activity replaces part of passive inter-set recovery. This hypothesis-driven narrative review evaluates its rationale in adults with obesity and metabolic syndrome (MetS) and proposes a multi-omics research framework. Methods: Structured searches of PubMed/MEDLINE and Scopus were combined with a narrative synthesis of systematic reviews, meta-analyses, controlled intervention studies, and mechanistic studies. Dedicated high-sensitivity searches were performed for studies directly evaluating aerobic active recovery during resistance-training inter-set recovery. Results: No randomized chronic intervention studies directly evaluating RT-AR in adults with obesity or MetS were identified; therefore, the rationale presented here is based on indirect evidence from conventional exercise and mechanistic studies. Evidence from overweight, abdominal-obesity, insulin-resistance, or type 2 diabetes cohorts was treated as partially applicable or indirect when the target phenotype differed. Aerobic, resistance, and combined training support improvements in body composition, cardiometabolic outcomes, physical function, and selected adipokines, whereas microbiota and DNA-methylation findings remain heterogeneous and are not RT-AR-specific. Conclusions: RT-AR should be regarded as a testable training architecture rather than an established therapeutic modality. Future trials should determine whether its effects exceed those attributable to total exercise dose, whether the resistance-training stimulus is preserved, and how diet, medication use, sex, and other major modifiers influence clinical and multi-omics responses. Full article

Background: Trichotillomania (hair pulling disorder) and skin picking disorder often begin around puberty, suggesting the potential role of hormones in the etiology and maintenance of these conditions. However, little research has explored whether usage of hormonal medications, including birth control, affects symptoms in people with these disorders. Methods: Two hundred and ten women with self-reported trichotillomania and/or skin picking disorder were recruited from the community if they had previously taken a hormonal medication in their lifetime. Data were collected on the perceived relationship between hormonal medication use and severity of hair pulling or skin picking. Results: While some women reported positive and/or negative effects of hormonal medications on their hair pulling (18.0%) or skin picking (17.8%), most women (approximately 82.0%) reported no change in symptoms while taking these medications. Conclusions: Sex hormones may still influence the precipitation of trichotillomania and skin picking disorder; however, they appear to have continued effects on hair pulling and skin picking in adulthood for only a subset of those with these conditions. Full article

Oral targeted therapies now constitute a substantial and growing proportion of anticancer drug therapy, shifting administration from the controlled intravenous setting to patient-managed oral therapy in the outpatient setting, where systemic exposure depends on factors that parenteral therapy largely bypasses. Food effects, gastric pH, first-pass metabolism, transporter activity, organ function, concomitant medications and adherence contribute to variability in exposure, and many oral anticancer agents have narrow therapeutic indices in which modest exposure changes carry clinical consequence. This review synthesizes the pharmacokinetic determinants of oral anticancer drug exposure across twenty-seven exemplar agents spanning the main mechanistic classes and translates them into actionable pharmacy practice. Its contribution is a cross-class agent-level comparison in which within-class divergences are made explicit, the integration of determinants usually reviewed separately, and an explicit statement of the evidence level behind every entry. We examine food effects, the interaction between acid-suppressive therapy and pH-dependent agents, the dominant role of cytochrome P450 3A4 and of the efflux transporters P-glycoprotein and breast cancer resistance protein, and the exposure–response relationships that motivate therapeutic drug monitoring, for which the evidence remains uneven and does not yet support routine use. We propose a structured framework for operationalizing these principles in daily practice. Full article

To thoroughly investigate the effects of high-impact weather and compound weather types on the triggering of severe influenza outbreaks and to effectively support the implementation of related weather risk forecasting services, methodologies from synoptic meteorology, climatology, medical statistics, time-lag effect, seasonally stratified correlation analysis, and SPSS (IBM SPSS Statistics 25) software were integrated, and severe influenza episodes in Langfang, China, were explored. The research encompasses the collection and processing of meteorological, influenza, and air pollution data; the study and analysis of the characteristics of severe influenza occurrences and associated meteorological conditions; the categorization of high-impact weather types, compound patterns, and their associated influenza distribution characteristics that induce severe influenza episodes; the analysis of the synergistic effects of air pollution coupled with high-impact weather events such as haze on triggering severe influenza; and the assessment of the effects of social prevention and control measures in mitigating severe influenza outbreaks. This study establishes an influenza risk forecasting grade based on high-impact weather classification, providing a scientific reference for the public to defend against influenza. Full article

Background: Treatment of peri-implantitis remains challenging because biofilm removal from microstructured implant surfaces is often incomplete. The present study is an uncontrolled, prospective feasibility case series involving six patients (six implants), not a controlled clinical trial, in which short-term clinical outcomes following use of a multimodal protocol to decontaminate the titanium implant surface were obtained; consequently, the independent contribution of the Ximplant^® device to the observed outcomes cannot be determined. The protocol comprised surgical access, mechanical debridement, chemical conditioning, systemic administration of medication, and cleaning with an alternating-current device (Ximplant^®; LED, S.p.A., Aprilia, Italy). Methods: Six adults with peri-implantitis, each contributing one implant, were consecutively treated using the multimodal protocol. Probing depth (PD), bleeding on probing (BOP), plaque index (PI), and suppuration (SU) were determined at baseline, 3 weeks, 6 months, and 12 months. Longitudinal changes were analyzed using repeated-measures analysis of variance and non-parametric tests for categorical variables. Results: Mean total PD decreased from 4.56 ± 0.45 mm at baseline to 3.03 ± 0.44 mm at the 3-week follow-up and remained stable at the 6-month follow-up (3.08 ± 0.35 mm) and at 12-month follow-up (3.19 ± 0.41 mm; p < 0.0001). BOP and SU were absent in all implants at each follow-up visit. PI improved markedly, although the buccal aspect of one implant was PI-positive at the 3-week and the 12-month follow-up. Conclusions: The multimodal protocol used in this study was associated with rapid and sustained clinical improvement over the 12-month follow-up period. A study limitation is that because the individual parts of the protocol were applied concurrently, the independent contribution of any of them to the outcomes determined could not be isolated. Full article

Background/Objectives: Deep learning has achieved remarkable success in medical image analysis; however, limited model interpretability remains a major barrier to its clinical translation. MRI-negative temporal lobe epilepsy (TLE) is characterized by the absence of readily identifiable structural abnormalities on conventional MRI. Methods: We propose a hierarchical, multiscale 3D residual network (H-MSResNet) combined with layer-wise relevance propagation (LRP). The study included structural T1-weighted MRIs from 101 patients with MRI-negative TLE and 101 healthy controls. Model classification performance was evaluated using a fivefold cross-validation approach. Subsequently, group-level LRP analysis was integrated with a standard brain atlas to quantify the anatomical regions contributing to the model’s decisions. Results: H-MSResNet achieved an average classification accuracy of 76.27% and a best single-fold accuracy of 82.50%, with higher accuracy, specificity, and F1 score but lower sensitivity and AUC than the two comparison models. Group-level, LRP-based analysis combined with a standard brain atlas revealed that the model’s decision-making primarily focused on structures related to the temporal lobe and limbic system, including regions such as the hippocampus, parahippocampal gyrus, and amygdala. Population-level attribution also showed interhemispheric differences across several regions. Conclusions: Structural MRIs of MRI-negative TLE contain latent discriminative information that can be recognized by deep learning models. The H-MSResNet and LRP framework provides viable, explainable methodological support for the computer-aided diagnosis and brain region analysis of MRI-negative epilepsy. Full article

Background and Objectives: Real-world persistence with medication-supported weight management programs is often low. While digital weight loss services (DWLS) provide multi-modal digital supports to improve engagement and counter attrition, the existing literature frequently relies on unidimensional or binary classifications of user engagement. This study used unsupervised machine learning to identify distinct digital engagement phenotypes and evaluated their independent associations with 6-month weight loss outcomes in patients prescribed tirzepatide. Materials and Methods: This retrospective cohort study analyzed deidentified data from 9470 medication-adherent, complete-case adult patients (out of 39,220 tirzepatide initiators) within a British DWLS who initiated tirzepatide between 20 May 20 and 2 December 2025. K-means clustering was performed on four continuous, longitudinal usage metrics: weekly app logins, health coach messaging, automated assistant (JuneBot) messaging, and weight tracking. To evaluate the primary clinical endpoint—6-month percentage weight loss—unadjusted pairwise comparisons (Tukey HSD) and a fully adjusted ordinary least squares multivariate linear regression model were executed to control for baseline demographic, clinical, and interim behavioral covariates. Results: Four stable engagement phenotypes emerged: non-engaged (n = 1772), high health coach engagement (n = 1141), high JuneBot engagement (n = 1472), and passive self-trackers (n = 5085). In a baseline-adjusted multivariate regression model, all active phenotypes were independently associated with 6-month weight loss relative to the low engagement baseline. Compared with this reference group, adjusted mean differences in percentage weight loss were 4.60% (SE = 0.26, p < 0.001) in the high health coach cluster, 4.69% (SE = 0.24, p < 0.001) in the high JuneBot cluster, and 3.71% (SE = 0.19, p < 0.001) in the passive self-tracker cluster. Conclusions: In this selected per-protocol, complete-case cohort of patients who persisted with tirzepatide treatment and reported 6-month weight data, distinct patterns of digital engagement were associated with different weight-loss outcomes. Greater conversational and self-tracking engagement was associated with greater observed 6-month weight loss than low engagement after adjustment for measured baseline characteristics. However, the retrospective observational design, concurrent assessment of engagement and outcome, substantial cohort selection, and potential residual confounding preclude causal or comparative-effectiveness conclusions, including claims of equivalence between automated and human support. Prospective studies with temporally defined engagement exposures and randomized allocation to support modalities are required. Full article

Psychotic disorder remains a major global health burden despite the plethora of anti-psychotic medications currently available. Poor adherence owing to numerous adverse effects and cost burden is a major challenge to treating psychosis. In view of this, the use of ethnomedicinal plants has become more common. In Nigeria, West Africa, the seeds of Phaseolus lunatus (Lima bean) are used to treat psychosis-like illness. Despite its extensive use, there are not many scientific studies that validate its efficacy. Therefore, this study evaluated the antipsychotic, anxiolytic-like, and sleep-enhancing properties of the seed extract. Pulverized dried seeds were extracted in a mixture (1:1) of water and methanol and screened for phytoconstituents. Using murine models, oral doses of 400, 800, and 1600 mg/kg of the extract were evaluated for antipsychotic, anxiolytic, and sleep-enhancing properties. Brain malondialdehyde (MDA), superoxide dismutase (SOD), catalase, glutathione peroxidase, and glutathione reductase (GR) levels were estimated after administering the doses of extract to mice for 14 consecutive days. The seed extract significantly inhibited d-amphetamine-induced stereotypy and ketamine-induced hyperlocomotion in a dose-dependent manner. It also exhibited significant anxiolytic-like activity at 800 mg/kg, as indicated by increased time spent on the open arm of the elevated plus maze and an increased number of head dips on the hole board. Compared with untreated controls, sleep onset was significantly faster, and sleep duration was longer in mice that received 1600 mg/kg of the extract. There was a decrease in MDA levels at a dose of 1600 mg/kg and an increase in SOD and GR levels in the mice brains. Our findings suggest that Lima bean extract exhibited antipsychotic-like, anxiolytic-like, sedative–hypnotic, and antioxidant activities in mice likely due to its flavonoid and alkaloidal constituents. Our study provides preliminary evidence in mice that supports the ethnomedicinal use of Lima beans as a functional food for psychosis-like illness. Full article

Background/Objectives: Atrial fibrillation (AF) and heart failure with reduced ejection fraction (HFrEF) frequently coexist and are linked by shared risk factors and pathophysiological mechanisms. Their association is consistently related to worse clinical outcomes. This narrative review summarizes current evidence regarding the epidemiology, pathophysiology, management strategies, and prognosis of patients with AF and HFrEF. Methods: This is a narrative review based on published randomized trials, registries, and observational studies evaluating the interaction between AF and HFrEF, with a focus on therapeutic strategies including rate and rhythm control, catheter ablation, stroke prevention, and guideline-directed medical therapy. Results: AF and HFrEF have a bidirectional relationship, with each condition promoting the development and progression of the other. AF contributes to hemodynamic impairment and adverse remodeling, while HFrEF promotes atrial structural and electrical changes. Management remains complex. Rate control is commonly achieved with beta-blockers and digoxin, while rhythm control is limited by the safety profile of antiarrhythmic drugs. Catheter ablation has shown improvements in left ventricular function and, in selected patients, reductions in hospitalizations and mortality, although results are not consistent across all trials. Guideline-directed medical therapy improves outcomes in HFrEF, but its interaction with AF varies across drug classes. Stroke risk is significantly increased, requiring appropriate anticoagulation. Patients with AF and HFrEF have an increased risk of mortality, hospitalization, and adverse clinical events compared with those with either condition alone, although the extent to which these outcomes are attributable to AF itself, HF severity, or the associated comorbidity burden remains uncertain. Conclusions: The coexistence of AF and HFrEF identifies a high-risk population with complex management and unfavorable outcomes. While advances in rhythm control and heart failure therapies have improved selected outcomes, optimal treatment strategies and their impact on long-term prognosis remain incompletely defined. Full article

Choroidal neovascularization (CNV) subtype classification from optical coherence tomography (OCT) images is clinically important because treatment response and disease prognosis vary across subtypes. However, automated classification remains challenging owing to subtle inter-class differences and considerable imaging noise. We propose an erasing–refining discriminative feature network (ERDF-Net) that mitigates noisy dominant activations and reveals fine-grained structural cues. The model perturbs salient regions to facilitate subtle feature learning, restores clean salient information, and fuses both representations via channel–spatial attention to form a coherent and discriminative embedding of CNV morphology. Experiments on a clinical OCT dataset show that ERDF-Net consistently surpasses state-of-the-art fine-grained and erasing-based methods across multiple metrics. Ablation and visualization analyses further confirm the benefit and interpretability of controlled salient suppression and refined feature fusion. ERDF-Net provides an effective and reliable solution for fine-grained medical image classification. Full article

Background and Objectives: Endometriosis is a chronic inflammatory disease associated with impaired fertility, but the extent to which its systemic inflammatory profile differs from that observed in infertile women without endometriosis remains incompletely understood. This study aimed to characterize and compare the systemic inflammatory profiles of women with endometriosis, infertile women without endometriosis, and healthy controls by evaluating serum interleukin-6 (IL-6), tumor necrosis factor-alpha (TNF-α), and high-sensitivity C-reactive protein (hs-CRP). In addition, the study explored the IL-6/TNF-α ratio as an indicator of inflammatory balance and evaluated its relationship with ovarian reserve. Materials and Methods: This observational comparative study included 87 women divided into three groups: healthy controls (n = 29), women with endometriosis (n = 29), and infertile women without endometriosis (n = 29). Serum IL-6, TNF-α, and hs-CRP concentrations were determined specifically for the present study, whereas the corresponding clinical and embryological data were retrieved from medical records. Group comparisons were performed using the Kruskal–Wallis test followed by Dunn’s post hoc test with Holm correction. The IL-6/TNF-α ratio was calculated as an exploratory indicator of inflammatory balance. Associations between inflammatory biomarkers and anti-Müllerian hormone (AMH) concentrations were assessed using Spearman’s correlation analysis. Results: Significant differences in serum inflammatory biomarkers were observed among the three groups. IL-6 concentrations were significantly increased in both women with endometriosis and infertile women without endometriosis compared with healthy controls, whereas TNF-α concentrations were significantly elevated only in infertile women without endometriosis compared with both healthy controls and women with endometriosis (adjusted p < 0.001 for both comparisons). Differences in hs-CRP were more modest but remained significant overall. Women with endometriosis exhibited a significantly higher IL-6/TNF-α ratio than infertile women without endometriosis, suggesting distinct inflammatory patterns between these conditions. No significant correlations were identified between circulating inflammatory biomarkers and AMH concentrations. Conclusions: Women with endometriosis and infertile women without endometriosis exhibit distinct systemic inflammatory profiles rather than simply different levels of inflammation. The IL-6/TNF-α ratio may provide additional information regarding the balance of inflammatory pathways beyond the isolated evaluation of individual cytokines. Larger prospective studies integrating systemic and local inflammatory biomarkers with assisted reproductive outcomes are warranted to validate these findings and further explore their clinical relevance. Full article

Arabidopsis class A genes APETALA 1 (AP1) and AP2 determine sepal and petal identity; AP2 also acts as a repressor that directly negatively regulates AP1 expression to control flowering time, while TOE1 represses flowering by inhibiting CONSTANS (CO) activity. Petunia AP2-type ROB is required for perianth and pistil development, as well as the repression of B-function and TOE-type BEN. However, how AP1 and AP2 orthologs from Fagopyrum tataricum work together to regulateflowering and floral organ development remains unclear. F. tataricum is an edible and medical crop rich in bioactive phytochemicals that have health benefits. This plant has only one perianth whorl, making it an excellent model for exploring the development and evolution of apetaly. In this study, we found that AP1-like FataAP1, AP2-type FataAP2, and TOE-type FataTOE were expressed in the roots, stems, leaves, flowers, and fruits of tartary buckwheat and in all stages detected during floral bud differentiation and development. The Y1H assay and DLR suggested that FataAP2 directly activates FataAP1 transcription and that FataAP1 directly activates the transcription of FataTOE. The VIGS silencing of FataAP2, FataAP1, and FataTOE resulted in flowers with increased tepal numbers and partly abnormal outer-whorl stamens with reduced filament lengths and shriveled anthers without pollen grains. A hierarchical regulatory cascade, FataAP2-FataAP1-FataTOE, was uncovered, which modulated tepal numbers and outer-whorl stamen development during tartary buckwheat flower development. Our current research provides new insights into the molecular mechanism of floral organ development in tartary buckwheat and may provide new evidence for exploring the floral phenotypic differences between tartary buckwheat and common buckwheat. Full article

This response letter addresses criticisms from a recent commentary regarding a real-world survey on insulin pen needle preferences. The authors clarify that their study was purposefully designed as an observational survey to capture genuine patient perceptions under routine clinical conditions, rather than functioning as a randomized controlled trial. Consequently, methodological constraints such as blinding were fundamentally inapplicable. Furthermore, the authors emphasize the limited relevance of the Hawthorne effect in this context. While originally described in industrial settings, recent systematic reviews in the medical literature indicate that its magnitude and impact on modern clinical research are highly uncertain and generally modest. Ultimately, the study effectively highlights real-world patient experiences with the shortest and thinnest needles currently available, aligning with advances in injection technology. Full article

Technological advances enable continuous vital sign monitoring with wireless biosensors in general wards. However, traditional thresholds used in routine monitoring do not effectively identify serious adverse events (SAEs). This study aimed to assess the prognostic ability of combinations of threshold severity and duration in continuous vital sign monitoring for SAEs in acute medical and surgical patients. Data on heart rate (HR), respiratory rate (RR), and peripheral oxygen saturation (SpO₂) were collected from four prospective observational studies and two randomised controlled trials. The primary outcome was an SAE within 30 days. Traditional thresholds were based on the National Early Warning Score, and optimised thresholds were derived by identifying threshold values and durations with the highest area under the receiver operating characteristic curve (AUROC) for any SAE and specific SAE types. Of 1492 patients, 1077 were included in HR and RR analyses and 761 in SpO₂ analyses; 30% experienced an SAE. For any SAE, traditional thresholds had AUROC values of 0.47–0.50 (95% CI 0.43–0.54). Optimised thresholds also showed limited ability (AUROC 0.51, 95% CI 0.44–0.56). In contrast, 18 thresholds for specific SAE types had AUROC > 0.70; the highest AUROC was observed for HR > 104 beats/min for ≥36 min for upcoming respiratory SAEs (AUROC 0.82, 95% CI 0.74–0.90). Optimised thresholds showed low prognostic ability for any SAE but higher AUROC than traditional thresholds. Several thresholds demonstrated moderate prognostic ability for specific SAE groups and warrant validation. Full article