Search Results (633)

Honey is a natural product of honeybees that has been consumed for centuries due to its nutritional value and potential health benefits. Recent scientific research has focused on its antioxidant capacity, which is linked to a variety of bioactive compounds such as phenolic acids, enzymes (e.g., glucose oxidase, catalase), flavonoids, ascorbic acid, carotenoids, amino acids, and proteins. Together, these components work synergistically to neutralize free radicals, regulate antioxidant enzyme activity, and reduce oxidative stress. This review decisively outlines the antioxidant effects of honey and presents compelling clinical and experimental evidence supporting its critical role in preventing diseases associated with oxidative stress. Honey stands out for its extensive health benefits, which include robust protection against cardiovascular issues, notable anticancer and anti-inflammatory effects, enhanced glycemic control in diabetes, immune modulation, neuroprotection, and effective wound healing. As a recognized functional food and dietary supplement, honey is essential for the prevention and adjunct treatment of chronic diseases. However, it faces challenges due to variations in composition linked to climatic conditions, geographical and floral sources, as well as hive management practices. The limited number of large-scale clinical trials further underscores the need for more research. Future studies must focus on elucidating honey’s antioxidant mechanisms, standardizing its bioactive compounds, and examining its synergistic effects with other natural antioxidants to fully harness its potential. Full article

Background/Objectives: Cerebrovascular reactivity (CVR) is a key marker of cerebrovascular function, facilitating the early detection of neurovascular dysfunction. Breath-hold functional MRI (bh-fMRI) is a non-invasive method for assessing CVR. This study evaluates the reproducibility of bh-fMRI using short breath-hold periods, which are practical for clinical use. Methods: In a prospective study, 50 healthy subjects underwent three self-paced, end-expiration bh-fMRI sessions with 9 s breath-hold periods at 3T. A 30 min break between the second and third sessions was included. The reproducibility of the percentage signal change (PSC) in predefined volumes of interest for a ±0 s, ±3 s and ±6 s interval around the cerebellar peak (IAP)) was evaluated. The intraclass correlation coefficient (ICC) and the intra-personal coefficient of variation (CV_intra) were calculated between the individual sessions. Results: This study demonstrated excellent reproducibility, with an ICC (2, k) for a ±0 s IAP across all sessions at 0.887 (95% CI: 0.882–0.892). The ICC values remained within an excellent range even when the participants left the scanner between sessions. The CV_intra for the ±0 s IAP (14.54% ± 8.54%) remained below the 33% fiducial limit. A larger IAP revealed higher ICC values but higher CV_intra values and lower PSC values. Conclusions: Bh-fMRI with 9 s breath-hold periods yields highly reproducible CVR assessments, supporting its feasibility for clinical implementation. Full article

Background/Objectives: Benign paroxysmal positional vertigo (BPPV) is the most prevalent vestibular disorder encountered in clinical settings and is highly responsive to evidence-based diagnostic and therapeutic interventions. However, variations in practice patterns among physician specialties can compromise timely diagnosis and effective treatment. Understanding these variations is essential for improving clinical outcomes and standardizing care. This study aimed to assess the diagnostic and treatment practices for BPPV among Ear, Nose, and Throat (ENT) specialists, neurologists, general practitioners, and family physicians in Saudi Arabia and to examine how these practices are influenced by clinical experience and patient case exposure. Methods: A cross-sectional, questionnaire-based study was conducted between April 2023 and March 2024 at King Khalid University, Abha, Saudi Arabia. A total of 413 physicians were recruited using purposive sampling. Data were analyzed using IBM SPSS version 24.0. Parametric tests, including one-way ANOVA and chi-square tests, were used to assess differences across groups. A p-value of <0.05 was considered statistically significant. Results: Overall, all physician groups exhibited limited adherence to guideline-recommended positional diagnostic and therapeutic maneuvers. However, ENT specialists and neurologists demonstrated relatively higher compliance, particularly in performing the Dix–Hallpike test, with 46.97% and 26.79% reporting “always” using the maneuver, respectively (p < 0.001, Cramér’s V = 0.22). Neurologists were the most consistent in conducting oculomotor examinations, with 73.68% reporting routine performance (p < 0.001, Cramér’s V = 0.35). Epley maneuver usage was highest among neurologists (86.36%) and ENT specialists (77.14%) compared to family physicians (50.60%) and GPs (67.50%) (p = 0.044). Physicians with 11–15 years of experience and >50 BPPV case exposures consistently showed a greater use of diagnostic maneuvers, repositioning techniques, and guideline-concordant medication use (betahistine 76.67%; p < 0.001). Continuing medical education (CME) participation and the avoidance of unnecessary imaging were also highest in this group (46.67% and 3.33%, respectively; p < 0.001). Conclusions: Significant inter-specialty differences exist in the management of BPPV in Saudi Arabia. Greater clinical experience and higher case exposure are associated with improved adherence to evidence-based practices. Targeted educational interventions are needed, particularly in primary care, to enhance guideline implementation. Full article

Background: Colorectal liver metastasis (CRLM) represents a major clinical challenge in oncology, affecting 25–50% of colorectal cancer patients and significantly impacting survival. While multimodal therapies—including surgical resection, systemic chemotherapy, and local ablative techniques—have improved outcomes, prognosis remains heterogeneous due to variations in tumor biology, patient factors, and institutional practices. Methods: This review synthesizes current evidence on prognostic factors influencing CRLM management, encompassing clinical (e.g., tumor burden, anatomic distribution, timing of metastases), biological (e.g., CEA levels, inflammatory markers), and molecular (e.g., RAS/BRAF mutations, MSI status, HER2 alterations) determinants. Results: Key findings highlight the critical role of molecular profiling in guiding therapeutic decisions, with RAS/BRAF mutations predicting resistance to anti-EGFR therapies and MSI-H status indicating potential responsiveness to immunotherapy. Emerging tools like circulating tumor DNA (ctDNA) and radiomics offer promise for dynamic risk stratification and early recurrence detection, while the gut microbiome is increasingly recognized as a modulator of treatment response. Conclusions: Despite advancements, challenges persist in standardizing resectability criteria and integrating multidisciplinary approaches. Current guidelines (NCCN, ESMO, ASCO) emphasize personalized strategies but lack granularity in terms of incorporating novel biomarkers. This exhaustive review underscores the imperative for the development of a unified, biomarker-integrated framework to refine CRLM management and improve long-term outcomes. Full article

Background: Mesenchymal stem cells (MSCs), multipotent and immune-regulatory cells derived from tissues such as bone marrow, dental pulp, and periodontal ligament, emerged as promising agents in regenerative dentistry. Their clinical applications include endodontic tissue regeneration, periodontal healing, and alveolar bone repair, addressing critical challenges in dental tissue restoration. Methods: A systematic review was conducted following PRISMA guidelines and registered in PROSPERO. We searched PubMed, Scopus, and Web of Science databases for open-access, English-language clinical trials and observational studies published from 2015 to 2025. Studies focusing on the application of MSCs in dental tissue regeneration were included based on predefined eligibility criteria. Results: Out of 2400 initial records, 13 studies met the inclusion criteria after screening and eligibility assessment. Most studies investigated MSCs derived from dental pulp and periodontal ligament for regenerating periodontal tissues and alveolar bone defects. The majority reported improved clinical outcomes; however, variations in MSC sources, delivery methods, sample sizes, and follow-up periods introduced methodological heterogeneity. Conclusions: MSCs show significant potential in enhancing bone and periodontal regeneration in dental practice. Nonetheless, the current evidence is limited by small sample sizes, short follow-up, and inconsistent methodologies. Future large-scale, standardized clinical trials are required to validate MSC-based regenerative therapies and optimize treatment protocols. Full article

Salivary α-amylase, primarily encoded by the AMY1 gene, initiates the enzymatic digestion of dietary starch in the oral cavity and has recently emerged as a potential biomarker in metabolic research. Variability in salivary amylase activity (SAA), driven largely by copy number variation of AMY1, has been associated with postprandial glycemic responses, insulin secretion dynamics, and susceptibility to obesity. This review critically examines current analytical approaches for quantifying SAA, including enzymatic assays, colorimetric techniques, immunoassays, and emerging biosensor technologies. The methodological limitations related to sample handling, intra-individual variability, assay standardization, and specificity are highlighted in the context of metabolic and clinical studies. Furthermore, the review explores the physiological relevance of SAA in energy homeostasis and its associations with visceral adiposity and insulin resistance. We discuss the potential integration of SAA measurements into obesity risk stratification and personalized dietary interventions, particularly in individuals with altered starch metabolism. Finally, the review identifies key research gaps and future directions necessary to validate SAA as a reliable metabolic biomarker in clinical practice. Understanding the diagnostic and prognostic value of salivary amylase may offer new insights into the prevention and management of obesity and related metabolic disorders. Full article

Background: Artificial intelligence (AI) is being increasingly promoted as a means to enhance diagnostic accuracy, to streamline workflows, and to improve overall care quality in primary care. However, empirical evidence on how primary care physicians (PCPs) perceive, engage with, and emotionally respond to AI technologies in everyday clinical settings remains limited. Concerns persist regarding AI’s usability, transparency, and potential impact on professional identity, workload, and the physician–patient relationship. Methods: This qualitative study investigated the lived experiences and perceptions of 28 PCPs practicing in diverse outpatient settings across Germany. Participants were purposively sampled to ensure variation in age, practice characteristics, and digital proficiency. Data were collected through in-depth, semi-structured interviews, which were audio-recorded, transcribed verbatim, and subjected to rigorous thematic analysis employing Mayring’s qualitative content analysis framework. Results: Participants demonstrated a fundamentally ambivalent stance toward AI integration in primary care. Perceived advantages included enhanced diagnostic support, relief from administrative burdens, and facilitation of preventive care. Conversely, physicians reported concerns about workflow disruption due to excessive system prompts, lack of algorithmic transparency, increased cognitive and emotional strain, and perceived threats to clinical autonomy and accountability. The implications for the physician–patient relationship were seen as double-edged: while some believed AI could foster trust through transparent use, others feared depersonalization of care. Crucial prerequisites for successful implementation included transparent and explainable systems, structured training opportunities, clinician involvement in design processes, and seamless integration into clinical routines. Conclusions: Primary care physicians’ engagement with AI is marked by cautious optimism, shaped by both perceived utility and significant concerns. Effective and ethically sound implementation requires co-design approaches that embed clinical expertise, ensure algorithmic transparency, and align AI applications with the realities of primary care workflows. Moreover, foundational AI literacy should be incorporated into undergraduate health professional curricula to equip future clinicians with the competencies necessary for responsible and confident use. These strategies are essential to safeguard professional integrity, support clinician well-being, and maintain the humanistic core of primary care. Full article

Background: Gestational diabetes mellitus (GDM) is a prevalent pregnancy complication globally. Maternal vitamin D deficiency has been linked to the risk of GDM. The aim of this study was to explore and synthesise current evidence on the association between vitamin D deficiency and the development of gestational diabetes in Western countries. Methods: A scoping review was conducted in accordance with the Joanna Briggs Institute (JBI) methodological framework. Relevant studies were identified through a comprehensive search across seven databases: ProQuest Public Health, Google Scholar, PubMed, ScienceDirect, The Lancet, BMC Public Health, the International Journal of Women’s Health, and Scopus. Studies were included based on predefined inclusion and exclusion criteria relevant to the research question. The review followed the JBI protocol, and the PRISMA flowchart was used to guide and visualise the study selection process. Results: Nineteen studies were included in the final analysis, comprising research predominantly from Australia (5), the United States (5), and Canada (4). The findings indicate a notable association between vitamin D deficiency and GDM risk, moderated by factors such as maternal age, ethnicity, seasonal variation, and body mass index (BMI). Older maternal age and higher BMI were linked with lower vitamin D levels and a higher incidence of GDM. Ethnic groups with darker skin tones showed higher rates of vitamin D deficiency, increasing vulnerability to GDM. Seasonal patterns revealed lower vitamin D levels during winter months, correlating with greater GDM risk. These patterns underscore the need for targeted preventive strategies, including the potential role of vitamin D supplementation. Conclusions: This review supports an observed association between maternal vitamin D deficiency and increased GDM risk, influenced by demographic and environmental factors. While the evidence points to a potential preventative role for vitamin D, further high-quality research, including systematic reviews and meta-analyses, is essential to establish causality and inform clinical guidelines. The review identifies knowledge gaps and suggests directions for future research and clinical practice. Full article

Autogenous tooth transplantation offers a biologically favorable approach to tooth replacement, preserving the periodontal ligament, promoting alveolar development, and maintaining proprioception. Background/Objectives: Its broader clinical applicability is limited by variability in techniques and outcome definitions. This systematic review and meta-analysis evaluated the clinical success of autogenous tooth transplantation across donor tooth types, developmental stages, surgical techniques, and fixation methods. Methods: Following PRISMA 2020 guidelines and a PROSPERO-registered protocol (CRD42024625550), five databases and the gray literature were searched through July 2025. Eligible studies reported clinical outcomes for autogenous tooth transplantation. Risk of bias was assessed using the Newcastle–Ottawa Scale. A random-effects meta-analysis of logit-transformed proportions was conducted, with subgroup and sensitivity analyses by tooth type, root development stage, surgical technique, and fixation method. Results: Twenty studies involving 1366 transplanted teeth were included. The pooled success rate was 94.0% (95% CI: 22.5–99.9%) across follow-up periods ranging from one month to twenty-nine years. However, interpretation is limited by distinct heterogeneity (I² = 99.8%) and the wide confidence interval. Subgroup analyses by tooth type, root maturity, surgical technique, and fixation method are, therefore, emphasized to support clinical interpretation. Conclusions: Autogenous tooth transplantation achieves consistently high success across clinical contexts when biologic handling is respected. These findings support its broader use in dental and orthodontic practice and underscore the need for standardized outcome reporting and prospective research. Interpretation is limited by heterogeneity and variation in reporting standards. Full article

Background/Objectives: Proton therapy delivers highly conformal doses to the target area without producing an exit dose, minimizing cumulative doses to healthy liver tissue. This study aims to evaluate current practices, challenges, and variations in the implementation of proton stereotactic body radiation therapy (SBRT) and hypofractionated therapy for liver malignancies, with the goal of providing a technical assessment to promote broader adoption and support future clinical trials. Methods and Materials: An extensive survey was conducted by NRG Oncology across North American proton treatment centers to assess the current practices of proton liver SBRT and hypofractionated therapy. The survey focused on key aspects, including patient selection, prescription and normal tissue constraints, simulation and motion management, treatment planning, quality assurance (QA), treatment delivery, and the use of image-guided radiation therapy (IGRT). Results: This survey captures the current practice patterns and status of proton SBRT and hypofractionated therapy in liver cancer treatment.  Proton therapy is increasingly preferred for treating inoperable liver malignancies due to its ability to minimize healthy tissue exposure. However, the precision required for proton therapy presents challenges, particularly in managing uncertainties and target motion during high-dose fractions and short treatment courses. Survey findings revealed significant variability in clinical practices across centers, highlighting differences in motion management, dose fractionation schedules, and QA protocols. Conclusion: Proton SBRT and hypofractionated therapy offer significant potential for treating liver malignancies. A comprehensive approach involving precise patient selection, treatment planning, and QA is essential for ensuring safety and effectiveness. This survey provides valuable insights into current practices and challenges, offering a foundation for technical recommendations to optimize the use of proton therapy and guide future clinical trials. Full article

This paper presents a methodology for extracting and simulating arterial pulse waveform signals from Fabry–Perot interferometric measurements, emphasizing a practical approach for noninvasive cardiovascular assessment. A key novelty of this work is the presentation of a complete Python-based processing pipeline, which is made publicly available as open-source code on GitHub (git version 2.39.5). To the authors’ knowledge, no such repository for demodulating these specific interferometric signals to obtain a raw arterial pulse waveform previously existed. The proposed system utilizes accessible Python-based preprocessing steps, including outlier removal, Butterworth high-pass filtering, and min–max normalization, designed for robust signal quality even in settings with common physiological artifacts. Key features such as the rate of change, the Hilbert transform of the rate of change (envelope), and detected extrema guide the signal reconstruction, offering a computationally efficient pathway to reveal its periodic and phase-dependent dynamics. Visual analyses highlight amplitude variations and residual noise sources, primarily attributed to sensor bandwidth limitations and interpolation methods, considerations critical for real-world deployment. Despite these practical challenges, the reconstructed arterial pulse waveform signals provide valuable insights into arterial motion, with the methodology’s performance validated on measurements from three subjects against synchronized ECG recordings. This demonstrates the viability of Fabry–Perot sensors as a potentially cost-effective and readily implementable tool for noninvasive cardiovascular diagnostics. The results underscore the importance of precise yet practical signal processing techniques and pave the way for further improvements in interferometric sensing, bio-signal analysis, and their translation into clinical practice. Full article

Background: Data accessibility remains a significant barrier in healthcare AI due to privacy constraints and logistical challenges. Synthetic data, which mimics real patient information while remaining both realistic and non-identifiable, offers a promising solution. Large Language Models (LLMs) create new opportunities to generate high-fidelity clinical conversations between patients and physicians. However, the value of this synthetic data depends on careful evaluation of its realism, accuracy, and practical relevance. Objective: To assess the performance of four leading LLMs: ChatGPT 4.5, ChatGPT 4o, Claude 3.7 Sonnet, and Gemini Pro 2.5 in generating synthetic transcripts of patient–physician interactions in plastic surgery scenarios. Methods: Each model generated transcripts for ten plastic surgery scenarios. Transcripts were independently evaluated by three clinically trained raters using a seven-criterion rubric: Medical Accuracy, Realism, Persona Consistency, Fidelity, Empathy, Relevancy, and Usability. Raters were blinded to the model identity to reduce bias. Each was rated on a 5-point Likert scale, yielding 840 total evaluations. Descriptive statistics were computed, and a two-way repeated measures ANOVA was used to test for differences across models and metrics. In addition, transcripts were analyzed using automated linguistic and content-based metrics. Results: All models achieved strong performance, with mean ratings exceeding 4.5 across all criteria. Gemini 2.5 Pro received mean scores (5.00 ± 0.00) in Medical Accuracy, Realism, Persona Consistency, Relevancy, and Usability. Claude 3.7 Sonnet matched the scores in Persona Consistency and Relevancy and led in Empathy (4.96 ± 0.18). ChatGPT 4.5 also achieved perfect scores in Relevancy, with high scores in Empathy (4.93 ± 0.25) and Usability (4.96 ± 0.18). ChatGPT 4o demonstrated consistently strong but slightly lower performance across most dimensions. ANOVA revealed no statistically significant differences across models (F(3, 6) = 0.85, p = 0.52). Automated analysis showed substantial variation in transcript length, style, and content richness: Gemini 2.5 Pro generated the longest and most emotionally expressive dialogues, while ChatGPT 4o produced the shortest and most concise outputs. Conclusions: Leading LLMs can generate medically accurate, emotionally appropriate synthetic dialogues suitable for educational and research use. Despite high performance, demographic homogeneity in generated patients highlights the need for improved diversity and bias mitigation in model outputs. These findings support the cautious, context-aware integration of LLM-generated dialogues into medical training, simulation, and research. Full article

Nitric oxide (NO) predominantly regulates endometrial receptivity, angiogenesis, immunological tolerance, and trophoblast invasion throughout the implantation period. Both insufficient and excessive nitric oxide production have been linked to suboptimal embryo implantation and infertility. The primary enzymatic source of uterine nitric oxide, along with hormonal, metabolic, and immunological variables and genetic variations in the endothelial nitric oxide synthase gene (NOS3), affects endothelial nitric oxide synthase (eNOS). Despite its considerable importance, there is limited knowledge regarding the practical implementation of nitric oxide-related diagnoses and therapies in reproductive medicine. A comprehensive assessment was performed in accordance with the PRISMA principles. Electronic searches were carried out in PubMed, Scopus, and Embase, and we analyzed the literature published from 2000 to 2024 regarding the association between NO, its metabolites (NO₂⁻ and NO₃⁻), eNOS expression, NOS3 gene variants, and reproductive outcomes. Relevant studies encompassed clinical trials, observational studies, and experimental research using either human or animal subjects. We collected data about therapeutic interventions, hormonal and immunological associations, nitric oxide measurement techniques, and in vitro fertilization success rates. A total of thirty-four studies were included. Dysregulated nitric oxide signaling, characterized by modified eNOS expression, oxidative stress, or NOS3 polymorphisms (e.g., Glu298Asp and intron 4 VNTR), was linked to diminished endometrial receptivity and an elevated risk of implantation failure and miscarriage. The dynamics of local uterine NO are essential as elevated and diminished systemic levels of NO₂⁻/NO₃⁻ corresponded with enhanced and decreased implantation rates, respectively. Among many therapeutic approaches, targeted hormone treatments, antioxidant therapy, and dietary nitrate supplements have demonstrated potential in restoring nitric oxide balance and enhancing reproductive outcomes. In animal models, the modification of nitric oxide significantly impacted decidualization, angiogenesis, and embryo viability. Nitric oxide is a multifaceted molecular mediator with considerable ramifications for successful implantation. Its therapeutic and diagnostic efficacy increases with its sensitivity to environmental, hormonal, and genetic alterations. Integrating targeted nitric oxide modulation, oxidative stress assessment, and NOS3 genotyping with personalized reproductive therapy will enhance endometrial receptivity and improve IVF outcomes. Future translational research should incorporate nitric oxide signaling into personalized treatment protocols for patients with unexplained infertility or recurrent implantation failure. Full article

Background/Objectives: Heart failure with preserved ejection fraction (HFpEF) has emerged as one of the most challenging syndromes in modern cardiology due to its complex pathophysiology, diagnostic ambiguity, and lack of effective targeted therapies. Unlike heart failure with reduced ejection fraction (HFrEF), HFpEF encompasses a highly heterogeneous patient population unified only by a preserved left ventricular ejection fraction (LVEF) ≥ 50%. This broad definition overlooks important biological and clinical differences, leading to inconclusive results in large-scale therapeutic trials and suboptimal patient outcomes. In recent years, advances in data-driven methodologies—such as unsupervised machine learning, cluster analysis, and latent class modeling—have enabled the identification of distinct HFpEF phenotypes. These phenotypes, often defined by demographic, clinical, hemodynamic, and biomarker profiles, exhibit differential prognoses and treatment responses. Methods: This systematic review synthesizes findings from 20 studies published between 2010 and 2025, examining phenotypic classification strategies and their clinical implications. Results: Despite methodological variation, several recurring phenotypes emerge, including metabolic–obese, frail–elderly, atrial-fibrillation-dominant, cardiorenal, and pulmonary hypertension/right-heart phenotypes. Each presents a distinct pathophysiological mechanism and risk profile, highlighting the inadequacy of current one-size-fits-all treatment approaches. The review also explores the prognostic value of phenotypes, the impact of phenotypic variation on treatment efficacy, and the methodological challenges that hinder translation into clinical practice—such as inconsistent input variables, lack of external validation, and limited integration with real-world data. Conclusions: Ultimately, the findings underscore the need for a paradigm shift from ejection fraction-based classification to phenotype-guided management in HFpEF. Embracing a precision medicine framework could enable personalized treatment strategies, improve clinical trial design, and enhance outcomes for this diverse patient population. The review concludes by outlining future directions, including the development of standardized phenotyping algorithms, integration of multi-omic and digital health data, and the implementation of pragmatic, phenotype-stratified clinical trials. Full article

As a synthetic analogue of vasopressin, desmopressin or DDAVP has well established hemostatic properties. We present a review of DDAVP and summarize the clinical and laboratory evidence for its use in hemophilia A, von Willebrand disease (VWD), platelet function disorders, uremia, liver cirrhosis, and pregnancy, followed by illustrative examples of its broad efficacy from our local practice. In brief, DDAVP acts to release von Willebrand factor (VWF) and factor VIII from endogenously stored reserves, thereby correcting plasma deficiencies present in mild to moderately affected patients with hemophilia A and VWD. Thus, DDAVP represents a non-transfusional therapy for these disorders. Typically, a trial of DDAVP is arranged to assess individual responsiveness before employing DDAVP clinically, since there is individual variation in responsiveness. Thereafter, DDAVP can be utilized in responsive patients for clinical use and provides a factor replacement sparing strategy in these patients for some clinical situations. Nevertheless, DDAVP is best applied as a factor replacement sparing strategy, especially for minor procedures or short-term use. Full article