Search Results (29,874)

Background: The long-term success of total knee arthroplasty (TKA) is often compromised by stress shielding, which can lead to bone resorption and even implant loosening. This study employs finite element analysis (FEA) to compare the stress-shielding effects of a knee prosthesis made from polyether ether ketone (PEEK) with a traditional titanium Ti6Al4V implant on an osteoporotic tibial bone model. Methods: Stress distribution and the stress-shielding factor (SSF) were evaluated at seven critical points in the proximal tibia under physiological loading conditions. Results: Results indicate that the PEEK prosthesis yields a more uniform stress transmission, with von Mises stress levels within the optimal 2–3 MPa range for bone maintenance and consistently negative or near-zero SSF values, implying minimal stress shielding. Conversely, titanium implants exhibited significant stress shielding with high positive SSF values across all points. Additionally, stress concentrations on the polyethylene liner were lower and more evenly distributed in the PEEK model, suggesting reduced wear potential. Conclusions: These findings highlight the biomechanical advantages of PEEK in reducing stress shielding and preserving bone integrity, supporting its potential use to improve implant longevity in TKA. Further experimental and clinical validation are warranted. Full article

Background: Plantar fasciitis (PF) is a common enthesopathy in patients with ankylosing spondylitis (AS). Shear wave elastography (SWE) and the Belgrade ultrasound enthesitis score (BUSES) may detect PF, but their comparative diagnostic performance is unclear. Objective: To compare SWE with the BUSES for identifying PF in individuals with and without AS. Methods: In this cross-sectional study, 96 participants were stratified into AS and non-AS populations, each further divided based on the presence or absence of clinical PF. Demographic data, the American Orthopedic Foot and Ankle Society Score (AOFAS), and the BASDAI score were recorded. All subjects underwent grayscale ultrasonography, the BUSES scoring, and SWE assessment of the plantar fascia. Logistic regression models were constructed for each population, controlling for age, body mass index (BMI), and fascia–skin distance. ROC curve analyses were performed to evaluate diagnostic accuracy. Results: In both AS and non-AS groups, SWE and the BUSES were significant predictors of PF (p < 0.05). SWE demonstrated slightly higher diagnostic accuracy, with area under the curve (AUC) values of 0.845 (AS) and 0.837 (non-AS), compared to the BUSES with AUCs of 0.785 and 0.831, respectively. SWE also showed stronger adjusted odds ratios in regression models. The interobserver agreement was good to excellent for both modalities. Conclusions: Both SWE and the BUSES are effective for PF detection, with SWE offering marginally superior diagnostic performance, particularly in AS patients. SWE may enhance the early identification of biomechanical changes in the plantar fascia. Full article

Electroencephalogram (EEG) analysis is essential for diagnosing neurological disorders but typically requires expert interpretation and significant time. Purpose: This study aims to automate the classification of normal and abnormal EEG recordings to support clinical diagnosis and reduce manual workload. Automating the initial screening of EEGs can help clinicians quickly identify potential neurological abnormalities, enabling timely intervention and guiding further diagnostic and treatment strategies. Methodology: We utilized the Temple University Hospital EEG dataset to develop a DenseNet-based deep learning model. To enable a fair comparison of different EEG representations, we used three input types: signal images, spectrograms, and scalograms. To reduce dimensionality and simplify computation, we focused on two channels: T5 and O1. For interpretability, we applied Local Interpretable Model-agnostic Explanations (LIME) and Gradient-weighted Class Activation Mapping (Grad-CAM) to visualize the EEG regions influencing the model’s predictions. Key Findings: Among the input types, spectrogram-based representations achieved the highest classification accuracy, indicating that time-frequency features are especially effective for this task. The model demonstrated strong performance overall, and the integration of LIME and Grad-CAM provided transparent explanations of its decisions, enhancing interpretability. This approach offers a practical and interpretable solution for automated EEG screening, contributing to more efficient clinical workflows and better understanding of complex neurological conditions. Full article

Background: Fluid management is a critical aspect of care for neurocritically ill patients, yet the optimal approach remains unclear. The relationship between fluid balance and clinical outcomes in these patients requires further investigation, particularly regarding the timing and volume of fluid administration. Methods: This retrospective observational study analyzed 2186 adult patients admitted to the neurosurgical intensive care unit (ICU) from January 2013 to December 2022. We employed a generalized additive model (GAM) with cubic spline smoothing to examine non-linear relationships between fluid balance and mortality. The maximally selected rank statistics method was used to determine the optimal cutoff value for fluid balance. Associations between fluid balance patterns and 28-day mortality were analyzed using a multivariable logistic regression model. Results: Initial analysis identified fluid balance on day 1 as the most significant predictor of mortality; patients with positive fluid balance showed a higher 28-day mortality. Non-survivors showed significantly higher fluid input throughout the 7-day observation period, particularly during the first 24 h (4444 mL vs. 3978 mL, p = 0.007). Multivariable analysis confirmed that fluid balance on day 1 remained independently associated with 28-day mortality after adjusting for confounders (adjusted odd ratio 1.705, 95% confidence interval: 1.001–2.905, p = 0.049). Additionally, the relationship between fluid input day 1 and mortality demonstrated a progressively increasing probability of 28-day mortality with higher fluid volumes. Early fluid balance, particularly during the first 24 h of ICU admission, shows a significant association with mortality in neurocritically ill patients. Conclusions: These findings emphasize the crucial importance of careful fluid management in the early phase of neurocritical care and suggest that implementation of strict fluid monitoring protocols, especially during the initial period of care, may improve patient outcomes. Full article

Diabetes mellites (DM) is a chronic disease with increasing prevalence worldwide and multiple health implications. Among them, sarcopenia is a metabolic disorder characterized by loss of muscle mass and function. The two age-related diseases, DM and sarcopenia, share underlying pathophysiological pathways. This narrative literature review aims to provide an overview of the existing evidence on metabolomic studies evaluating DM associated with sarcopenia. Advancements in targeted and untargeted metabolomics techniques could provide better insight into the pathogenesis of sarcopenia in DM and describe their entangled and fluctuating interrelationship. Recent evidence showed that sarcopenia in DM induced significant changes in protein, lipid, carbohydrate, and in energy metabolisms in humans, animal models of DM, and cell cultures. Newer metabolites were reported, known metabolites were also found significantly modified, while few amino acids and lipids displayed a dual behavior. In addition, several therapeutic approaches proved to be promising interventions for slowing the progression of sarcopenia in DM, including physical activity, newer antihyperglycemic classes, D-pinitol, and genetic USP21 ablation, although none of them were yet validated for clinical use. Conversely, ceramides had a negative impact. Further research is needed to confirm the utility of these findings and to provide potential metabolomic biomarkers that might be relevant for the pathogenesis and treatment of sarcopenia in DM. Full article

Chimeric antigen receptor (CAR)-T immunotherapy has revolutionized the management of patients with relapsed/refractory B-cell hematological malignancies. There is emerging evidence that CAR-engineered cells—not only T cells, but also natural killers and macrophages—might have a crucial role in the treatment of autoimmune disorders and solid tumors. Moreover, given the burden of chronic infectious diseases, the mortality and morbidity of infections in immunocompromised individuals, and the development of multidrug-resistant pathogens, including bacteria, fungi, and mycobacteria, a need for novel and personalized therapeutics in this field is emerging. To this end, the development of CAR cells for the management of chronic infections has been reported. In this literature review, we summarize the ongoing clinical and pre-clinical data about CAR cell products in the field of infectious diseases. Currently, clinical studies on CAR immunotherapy for infections mainly concern human immunodeficiency virus infection treatment, and data regarding other infections largely originate from preclinical in vitro and in vivo models. In the era of personalized medicine, effective and safe therapies for the management of chronic infections and infectious complications in immunocompromised patients are crucial. Full article

Acromegaly is caused by an excessive secretion of growth hormone and the secondary elevation of IGF-1 levels, leading to progressive changes in multiple body systems, including the craniofacial region and oral cavity. Dental manifestations such as mandibular overgrowth, macroglossia, malocclusion, periodontal disease, and prosthetic difficulties represent not only a clinical component of the disease but also a significant therapeutic and diagnostic challenge. The aim of this review is to present the current state of knowledge on the relationship between acromegaly and oral health and to analyze the role of interdisciplinary collaboration between endocrinologists and dentists in patient care. For this narrative review, a literature search was conducted in the PubMed, Scopus, and Web of Science databases covering the period from 2000 to 2025. Sixty-two peer-reviewed publications meeting the methodological and thematic criteria were included in the analysis, including original studies, meta-analyses, systematic reviews, and case reports. The results indicate significant correlations between disease activity and the severity of periodontal and microbiological changes, while effective endocrine treatment only results in the partial regression of morphological changes. Particular attention was given to the role of the dentist in recognizing the early symptoms of the disease, planning prosthetic and surgical treatment, and monitoring therapy-related complications. Interdisciplinary collaboration models, including integrated clinics and co-managed care, were also described as optimal systemic solutions for improving treatment quality. The conclusion drawn from the analysis are as follows: there is a need for the permanent integration of dentistry into the standard of interdisciplinary care for patients with acromegaly, in both diagnostic and therapeutic dimensions. Increasing awareness among dentists and developing integrated collaboration models may reduce the time to diagnosis, improve patients’ quality of life, and enable the more effective management of craniofacial complications in the course of this rare disease. Full article

The Gross Motor Function Measure-66 (GMFM-66, range of values: 0 to 100 points) is one of the most widely used clinical tests to quantify motor function in children with cerebral palsy (CP). A disadvantage of the GMFM-66 is that it can take up to one hour to complete. The aim of the study was to evaluate whether the GMFM-66 can be predicted with sufficient accuracy by the results of an instrumental gait analysis (IGA) in ambulant children with CP. A retrospective analysis was conducted on n = 256 ambulant children with CP enrolled in a rehabilitation program between 2018 and 2023. The sample consisted of 97 females and 159 males, with a mean age of 9.0 years (SD 3.6 years). The IGA was performed with a Zebris FDM pressure plate. For the prediction of the GMFM-66, different statistical models were used (multiple linear regression and machine learning algorithms). Among the models considered, the XGBoost model had the best predictive performance (mean absolute error 6.32 (95%CI 5.35–7.28)). Agreement between results from gait analyses by the Zebris FDM pressure plate and GMFM-66 is not yet sufficient to predict the GMFM-66 score with acceptable accuracy for clinical purposes. Full article

Background/Objectives: Diabetic retinopathy is a leading cause of vision impairment worldwide, and the development of reliable automated classification systems is crucial for early diagnosis and clinical decision-making. This study presents a comprehensive comparative evaluation of two state-of-the-art deep learning families for the task of classifying diabetic retinopathy using retinal fundus images. Methods: The models were trained and tested in both binary and multi-class settings. The experimental design involved partitioning the data into training (70%), validation (20%), and testing (10%) sets. Model performance was assessed using standard metrics, including precision, sensitivity, specificity, F1-score, and the area under the receiver operating characteristic curve. Results: In binary classification, the ResNeXt101-64x4d model and RegNetY32GT model demonstrated outstanding performance, each achieving high sensitivity and precision. For multi-class classification, ResNeXt101-32x8d exhibited strong performance in early stages, while RegNetY16GT showed better balance across all stages, particularly in advanced diabetic retinopathy cases. To enhance transparency, SHapley Additive exPlanations were employed to visualize the pixel-level contributions for each model’s predictions. Conclusions: The findings suggest that while ResNeXt models are effective in detecting early signs, RegNet models offer more consistent performance in distinguishing between multiple stages of diabetic retinopathy severity. This dual approach combining quantitative evaluation and model interpretability supports the development of more robust and clinically trustworthy decision support systems for diabetic retinopathy screening. Full article

Background/Objectives: Metabolic syndrome (MetS) is a multifactorial condition characterized by abdominal obesity, dyslipidemia, insulin resistance, hypertension, and chronic inflammation. As its global prevalence rises, there is increasing interest in natural, multi-targeted approaches to manage MetS. Curcuma longa Linn. (turmeric), especially its active compound curcumin, has shown therapeutic promise in preclinical studies. This systematic review and meta-analysis evaluated the effects of Curcuma longa and its derivatives on MetS-related outcomes in rodent models. Methods: A comprehensive search was conducted across six databases (PubMed, Scopus, AMED, LILACS, MDPI, and Google Scholar), yielding 47 eligible in vivo studies. Data were extracted on key metabolic, inflammatory, and oxidative stress markers and analyzed using random-effects models. Results were presented as mean differences (MD) with 95% confidence intervals (CI). Results: Meta-analysis showed that curcumin significantly reduced body weight (rats: MD = −42.10; mice: MD = −2.91), blood glucose (rats: MD = −55.59; mice: MD = −28.69), triglycerides (rats: MD = −70.17; mice: MD = −24.57), total cholesterol (rats: MD = −35.77; mice: MD = −52.61), and LDL cholesterol (rats: MD = −69.34; mice: MD = −42.93). HDL cholesterol increased significantly in rats but not in mice. Inflammatory cytokines were markedly reduced, while oxidative stress improved via decreased malondialdehyde (MDA) and elevated superoxide dismutase (SOD) and catalase (CAT) levels. Heterogeneity was moderate to high, primarily due to variations in curcumin dosage (ranging from 10 to 500 mg/kg) and treatment duration (2 to 16 weeks) across studies. Conclusions: This preclinical evidence supports Curcuma longa as a promising functional food component for preventing and managing MetS. Its multi-faceted effects warrant further clinical studies to validate its translational potential. Full article

Background: Biological aging influences cancer outcomes, but its changes during chemotherapy and impact on chemotoxicity in colorectal cancer (CRC) remain underinvestigated. We examined (1) trajectories of biological aging (using Levine Phenotypic Age) during six months of chemotherapy, (2) sociodemographic and clinical risk factors for biological aging, and (3) links between biological aging and chemotoxicity. Methods: Using data from electronic health records (2013–2019) from 1129 adult CRC patients, we computed biological aging (raw Levine Phenotypic Age and its age acceleration [Levine Phenotypic Age–chronological age]) from routine blood tests (e.g., complete blood counts, hepatorenal/inflammatory markers). Chemotoxicity was identified primarily via International Classification of Diseases (ICD-9 and -10) codes. Results: Chemotherapy accelerated biological aging over time. Biological aging at baseline and changes over time predicted chemotoxicity. However, changes in biological aging over time showed stronger associations than baseline biological aging. Advanced cancer stages, higher comorbidity burden, and socioeconomic disadvantage (especially area-level deprivation) were associated with accelerated biological aging at baseline and over time. Biological aging occurred across both young and older adults. Conclusions: Levine Phenotypic Age, computed from routine blood tests in EHRs, offers a feasible clinical tool for aging-related chemotoxicity risk stratification. Validation in diverse cohorts and the development of predictive models are needed. Full article

Background/Objectives: Thrombotic thrombocytopenic purpura (TTP) is a microangiopathic hemolytic anemia exhibiting 90% mortality without prompt treatment. The aim of this study was to investigate the association of therapeutic plasma exchange (TPE)-treated TTP in end-stage renal disease (ESRD) patients with mortality, demographics, and clinical comorbidities. We queried the United States Renal Data System for ESRD patients starting dialysis between 1 January 2005 and 31 December 2018, using International Classification of Diseases (ICD)-9 and ICD-10 codes for thrombotic microangiopathy, with a TPE procedure code entered within 7 days. Methods: Cox proportional hazards models were used to assess mortality, adjusting for demographic and clinical factors. Results: Among 1,155,136 patients, increased age [adjusted odds ratio (OR) = 0.96, 95% confidence interval (CI): 0.94–0.96]; black race (OR = 0.67, CI: 0.51–0.89); and Hispanic ethnicity (OR = 0.43, CI: 0.28–0.66) were associated with a lower risk of TPE-treated TTP diagnosis, whereas female sex (OR = 1.59, CI: 1.25–2.02) and tobacco use (OR = 2.08, CI: 1.58–2.75) had a higher risk. A claim for TPE-treated TTP carried a lower risk of death (adjusted hazard ratio = 0.024, CI: 0.021–0.028). Female sex, black race, Hispanic ethnicity, and hypothyroidism were also associated with decreased all-cause mortality. Conclusions: These findings suggest that ESRD patients with TPE-treated TTP are significantly protected from mortality compared with ESRD patients without this diagnosis. Full article

Background/Objectives: Acute kidney injury (AKI) is a common and severe complication in patients with acute myocardial infarction (AMI). Very elderly patients are at a heightened risk of developing AKI. Fibrinogen and albumin are well-known biomarkers of inflammation and nutrition, which are highly related to AKI. We aim to explore the predictive value of the fibrinogen-to-albumin ratio (FAR) for AKI in very elderly patients with AMI. Methods: A retrospective cohort of AMI patients ≥ 75 years old hospitalized at the First Affiliated Hospital of Xi’an Jiaotong University between January 2018 and December 2022 was established. Clinical data and medication information were collected through the biospecimen information resource center at the hospital. Univariate and multivariable logistic regression models were used to analyze the association between FAR and the risk of AKI in patients with AMI. FAR was calculated as the ratio of fibrinogen (FIB) to serum albumin (ALB) level (FAR = FIB/ALB). The primary outcome is acute kidney injury, which was diagnosed based on KDIGO 2012 criteria. Results: Among 1236 patients enrolled, 66.8% of them were male, the median age was 80.00 years (77.00–83.00), and acute kidney injury occurred in 18.8% (n = 232) of the cohort. Comparative analysis revealed significant disparities in clinical characteristics between patients with or without AKI. Patients with AKI exhibited a markedly higher prevalence of arrhythmia (51.9% vs. 28.1%, p < 0.001) and lower average systolic blood pressure (115.77 ± 25.96 vs. 122.64 ± 22.65 mmHg, p = 0.013). In addition, after adjusting for age, sex, history of hypertension, left ventricular ejection fraction (LVEF), and other factors, FAR remained an independent risk factor for acute kidney injury (OR = 1.47, 95%CI: 1.36–1.58). ROC analysis shows that FAR predicted stage 2–3 AKI with superior accuracy (AUC 0.94, NPV 98.6%) versus any AKI (AUC 0.79, NPV 93.0%), enabling risk-stratified management. Conclusions: FAR serves as both a high-sensitivity screening tool for any AKI and a high-specificity sentinel for severe AKI, with NPV-driven thresholds guiding resource allocation in the fragile elderly. Full article

Although PD-1/PD-L1 inhibitors have transformed cancer immunotherapy, a substantial proportion of patients derive no clinical benefit due to resistance driven by the tumour microenvironment (TME). Transforming growth factor-β (TGF-β) is a key immunosuppressive cytokine implicated in this resistance. Several bifunctional antibodies that co-target PD-1 and TGF-β signalling have entered clinical trials and shown encouraging efficacy, but the mechanistic basis of their synergy is not fully understood. Here, we engineered 015s, a bifunctional fusion antibody that simultaneously targets murine PD-1 and TGF-β and evaluated its antitumour efficacy and mechanistic impact in pre-clinical models. Antibody 015s exhibited high affinity, dual target binding, and the effective inhibition of PD-1 and TGF-β signalling. In vivo, 015s significantly suppressed tumour growth compared with anti-mPD-1 or TGF-β receptor II (TGF-βRII) monotherapy. When combined with the CD24-targeted ADC, 015s produced even greater antitumour activity and achieved complete tumour regression. Mechanistic studies demonstrated that 015s significantly reduced tumour cell migration and invasion, reversed epithelial–mesenchymal transition (EMT), decreased microvascular density, and attenuated collagen deposition within the TME. Antibody 015s also decreased bioactive TGF-β1 and increased intratumoural IFN-γ, creating a more immunostimulatory milieu. These findings support further development of PD-1/TGF-β bifunctional antibodies for cancers with high TGF-β activity or limited response to immune checkpoint blockade. Full article

Thyroid cancer is the most common endocrine malignancy, and preoperative distinction between benign and malignant nodules remains challenging, especially in cytologically indeterminate cases. Circulating microRNAs (miRNAs) have gained interest as non-invasive biomarkers due to their stability and involvement in tumorigenesis. This study aimed to assess the preoperative diagnostic value of circulating miR-146a and miR-221 in patients undergoing thyroidectomy. A total of 56 patients were included, of whom 24 had malignant and 32 had benign thyroid lesions confirmed by histopathology. Preoperative plasma levels of miR-146a and miR-221 were quantified using qRT-PCR, and relative expression was calculated with the 2^−ΔΔCt method. miR-221 expression was significantly higher in malignant cases, with an area under the ROC curve of 1.00, achieving 100% sensitivity and specificity at the optimal threshold. miR-146a showed no significant discriminatory ability. Weak correlations were observed between miRNA expression and clinical parameters such as age, TIRADS score, or thyroid volume. Logistic regression including miR-221 led to perfect separation, indicating strong predictive capacity but precluding multivariate modeling. These findings suggest that circulating miR-221 may serve as a highly accurate biomarker for thyroid malignancy and warrant further validation in larger, prospective cohorts. Full article