Search Results (16,914)

Celiac disease (CeD) is an autoimmune disorder where adherence to a lifelong gluten-free diet (GFD) is the only available treatment. While this approach is rather effective, some patients experience ongoing symptoms, and this factor, along with the rigidity of the GFD, may predispose some to disordered eating behaviors, including Avoidant/Restrictive Food Intake Disorder (ARFID). ARFID is characterized by persistent food avoidance that is not driven by body image concerns, resulting in nutritional, psychological, and social impairment. This scoping literature review explores the emerging intersection between ARFID and CeD, examining prevalence, pathophysiology, clinical features, complications, and management strategies. Recent studies report that 14–57% of individuals with CeD may meet the criteria for ARFID, depending on the population and screening tools used. Factors contributing to ARFID in CeD may include ongoing gastrointestinal symptoms, anxiety over gluten exposure, negative conditioned responses to food, social challenges related to GFD adherence, and psychiatric co-morbidities. ARFID in CeD is associated with worsened nutritional deficiencies, anxiety, depression, and impaired social functioning, making the diagnosis of ARFID challenging due to symptom overlap with CeD and other psychiatric conditions. Management requires a multidisciplinary approach, including medical, nutritional, and psychological interventions. Routine screening, early intervention, and integrated care models may improve outcomes and quality of life. Full article

Background/Objectives: Antimicrobial resistance (AMR) is a major global health threat, with children at higher risk due to developmental differences in drug metabolism, limited treatment options and inappropriate antibiotic use. Pediatric antimicrobial stewardship programs (ASPs) face implementation challenges, often relying on adult-based guidelines and limited pediatric-specific evidence. This study aimed to identify and prioritize the most critical areas for pediatric ASP intervention development through a structured, multi-round Delphi consensus process with experts in antimicrobial stewardship and infectious diseases. Method: A four-round modified Delphi process was conducted to identify and prioritize key pediatric ASP interventions. Experts in antimicrobial stewardship and infectious diseases were recruited through an existing clinical trial. Using an iterative survey and in-person discussions, experts provided input on priority areas, which were thematically grouped and refined across rounds. Structured feedback supported real-time refinement and consensus-building. Results: Twenty experts participated in the process, generating 25 priority items in Round 1 through open-ended responses. These were narrowed to seven key priorities through structured voting and discussion. The final items were clustered into three intersecting themes: Care Settings, Prescriptions, and Strategies. Care Settings focused on high-impact areas such as outpatient clinics and intensive care units, where misuse is common and/or care is complex. The prescriptions theme prioritized shorter durations and narrow-spectrum agents. The strategy theme highlighted the need for outcome-based metrics, improved diagnostic stewardship, and routine tracking of patient outcomes to guide and assess stewardship efforts. Conclusions: This expert consensus identified key priorities for pediatric ASPs, providing a foundation for future interventions. Findings can be used to inform policy and practice, improving the appropriate use of antimicrobials in pediatrics and combating AMR. Full article

Major depressive disorder (MDD) is one of the most prevalent psychiatric conditions and is characterized by alterations in cortical excitability, network connectivity, and neuroplasticity. Despite significant progress in neuroimaging and neurophysiology, the identification of objective and reliable biomarkers remains a major challenge, limiting diagnostic accuracy and treatment optimization. Transcranial magnetic stimulation combined with electroencephalography (TMS-EEG) has emerged as a powerful methodology to probe causal brain dynamics with high temporal resolution. This review aims to summarize recent advances in the application of TMS-EEG to MDD, highlighting the transition from traditional TMS-evoked potential (TEP) analyses to more advanced, multidimensional approaches. We reviewed original research articles published between 2020 and 2025 that investigated neurophysiological markers and approaches to MDD using TMS-EEG. Traditional TEP measures provide markers of local cortical responses but are limited in capturing distributed network dysfunction. Emerging approaches expand the scope of TMS-EEG, allowing for the characterization of oscillatory activity, connectivity patterns, and large-scale network dynamics. Recent contributions also demonstrate the potential of computational and multivariate techniques to enhance biomarker sensitivity and predictive value. Taken together, recent evidence highlights TMS-EEG as a uniquely positioned methodology to investigate the neurophysiological substrates of MDD. By linking conventional TEP-based indices with innovative analytic strategies, TMS-EEG enables a multidimensional assessment of cortical function and dysfunction that transcends traditional descriptive markers. This integrative perspective not only refines mechanistic models of MDD but also opens new avenues for biomarker discovery, patient stratification, and treatment monitoring. Ultimately, the convergence of advanced TMS-EEG approaches with clinical applications holds promise for translating neurophysiological insights into precision psychiatry interventions aimed at improving outcomes in MDD. Full article

Congenital genetic heart defects are major contributors to pediatric morbidity and mortality, underscoring the importance of early detection and individualized therapeutic strategies. This review aimed to summarize current knowledge on a spectrum of inherited cardiovascular disorders, with a focus on their genetic etiology, molecular pathogenesis, and phenotypic presentation in children. Conditions discussed include Marfan syndrome, Noonan syndrome, various cardiomyopathies, Duchenne muscular dystrophy, DiGeorge syndrome, and the tetralogy of Fallot. These six conditions were selected to represent the spectrum of pediatric cardiovascular genetic diseases, encompassing connective tissue disorders, multisystem syndromes, primary myocardial diseases, neuromuscular cardiac involvement, and structural congenital defects, thereby illustrating how distinct genotypes lead to diverse phenotypes. For each disorder, the underlying genetic mutations, associated molecular pathways, cardiovascular involvement, clinical features, and approaches to diagnosis and management are examined. Emphasis is placed on the role of timely diagnosis, genetic counseling, and personalized treatment in improving patient outcomes. The review concludes by highlighting emerging research directions and novel therapeutic interventions aimed at enhancing care for these complex pediatric conditions. Full article

Background: Antimicrobial drugs are used to treat bacterial diseases in livestock production systems, including bovine respiratory disease (BRD) in feedlot cattle. It is recommended that therapeutic antimicrobial use (AMU) in food animals be informed by diagnostic tests to limit the emergence of antimicrobial resistance (AMR) and preserve the effectiveness of available drugs. Recent evidence demonstrates preliminary support for the pen as a prospective target for AMR testing-based interventions in higher-risk cattle. Methods: A previously reported agent-based model (ABM) was modified and then used in this study to investigate the potential for different pen-level sampling and laboratory testing-informed BRD treatment strategies to favorably impact selected antimicrobial stewardship and management outcomes in the western Canadian context. The incorporation of sample testing to guide treatment choice was hypothesized to reduce BRD relapses, subsequent AMU treatments and resultant AMR in sentinel pathogen Mannheimia haemolytica. The ABM was extended to include a discrete event simulation (DES) workflow that models the testing process, including the time at sample collection (0 or 13 days on feed) and the type of AMR diagnostic test (antimicrobial susceptibility testing or long-read metagenomic sequencing). Candidate testing scenarios were simulated for both a test-only control and testing-informed treatment (TI) setting (n = 52 total experiments). Key model outputs were generated for both the pen and feedlot levels and extracted to data repositories. Results: There was no effect of the TI strategy on the stewardship or economic outcomes of interest under baseline ecological and treatment conditions. Changes in the type and number of uses by antimicrobial class were observed when baseline AMR in M. haemolytica was assumed to be higher at feedlot arrival, but there was no corresponding impact on subsequent resistance or morbidity measures. The impacts of sample timing and diagnostic test accuracy on AMR test positivity and other outputs were subsequently explored with a theoretical “extreme” BRD treatment protocol that maximized selection pressure for AMR. Conclusions: The successful implementation of a pen-level sampling and diagnostic strategy would be critically dependent on many interrelated factors, including the BRD treatment protocol, the prevalences of resistance to the treatment classes, the accuracy of available AMR diagnostic tests, and the selected “treatment change” thresholds. This study demonstrates how the hybrid ABM-DES model can be used for future experimentation with interventions proposed to limit AMR risk in the context of BRD management. Full article

Introduction: Health literacy (HL) is a key determinant of health outcomes, particularly among vulnerable populations such as low-income older adults. Limited HL is associated with poor understanding of medication instructions and lower medication adherence, which can compromise therapeutic success. This study aims to assess the levels of HL and medication adherence among low-income older adults and to analyse the relationship between HL, medication adherence, and other determinants. Methods: A cross-sectional study was conducted among low-income older adults in Portugal’s Beira and Serra Estrela Region. HL was assessed using the European Health Literacy Survey Questionnaire (HLS-EU-PT), and medication adherence was measured with the Adherence to Treatment Measure (MAT) scale. Descriptive statistics, Spearman correlations, ordinal logistic regression, and linear regression were used to analyse associations between HL, adherence, and sociodemographic and health factors. Results: Of 196 participants, most had problematic or inadequate HL (87.8%). Medication adherence was relatively high (mean = 5.37, SD = 0.54). HL was positively associated with medication adherence (R = 0.260, p < 0.001), education (R = 0.277, p < 0.001), and ability to pay expenses (R = 0.235, p = 0.002) and negatively with age (R = −0.179, p = 0.019), poor health status (R = −0.237, p = 0.002), and difficulty affording medication (R = −0.389, p < 0.001). Completion of the third cycle of primary education predicted higher HL (OR = 1.939, 95% CI: 0.088–3.790, p = 0.040); the ability to pay expenses predicted better adherence (B = 0.101, 95% CI: 0.014–0.187, p = 0.022). Conclusions: Low HL remains a significant barrier among low-income older adults in Portugal, despite generally high medication adherence. Education and financial stability are key determinants to HL and adherence. Interventions should integrate HL promotion with efforts to reduce socioeconomic barriers and support medication management in the vulnerable populations. Full article

Objective: This study conducted a comprehensive analysis of molecular transmission networks and pretreatment drug resistance (PDR) in newly diagnosed HIV-1 infections in Taizhou, China. Methods: From 2021 to 2023, we collected 1126 plasma samples from newly diagnosed HIV patients in Taizhou. The HIV pol gene was amplified, and the obtained sequence was used to construct a maximum likelihood (ML) phylogenetic tree and molecular transmission network. PDR-related mutations were analyzed based on the Stanford University HIV Resistance Database. We conducted genotyping analysis and analysis of factors related to the larger clusters (≥10). Results: We successfully amplified and sequenced the pol region from 937 (83.2%, 937/1126) treatment-naïve HIV-1 patients, each with comprehensive epidemiological documentation. Phylogenetic characterization revealed significant subtype heterogeneity, with CRF07_BC (42.1%, 395/937), CRF01_AE (27.6%, 259/937) and CRF08_BC (22.1%, 209/937) being the most prevalent. Notably, 11.4% of the sequenced population (107/937) presented detectable PDR mutations. Univariate analysis revealed that larger clusters (≥10) are more inclined to be aged ≥60, divorced or widowed, have high or technical secondary school education, and have sexual contact with homosexuality. Multivariate analysis revealed that age ≥60 years and not having a PDR mutation (p < 0.05) were factors associated with larger clusters (≥10). Conclusions: Molecular transmission networks suggest that CRF08_BC is spreading rapidly among the older male population. Consequently, targeted interventions aimed at this population are crucial for halting the ongoing rapid dissemination of this subtype. Full article

Background/Objectives: Solitary plasmacytoma of bone (SPB) results from abnormal proliferation of plasma cells and accounts for 2–5% of all plasmacytic malignancies. Radiation therapy is the standard of care in treating SPB due to its efficacy in controlling disease progression and optimizing patient survival. However, prior studies have highlighted disparities in radiation therapy receipt among various cancer types. In this study, we aim to investigate whether similar sociodemographic and clinical disparities exist in the treatment of SPB through use of the Surveillance, Epidemiology, and End Results (SEER) database. Methods: The SEER database was queried for biopsy-confirmed cases of SPB between 2000 and 2021 using the ICD-O-3 histology code 9731/3 and primary site codes C40.0–41.9. Chi-square tests, Fisher’s exact tests, and multivariable logistic regression were completed using SPSS v29.0.2, with significance set to p < 0.05. Results: A total of 4139 patients were identified, of which 75.3% received treatment with radiation therapy. Multivariable analysis revealed that low-income patients making less than $74,999 annually (aOR 0.80, 95% CI 0.67–0.97), as well as those from non-Hispanic Asian/Pacific Islander (aOR 0.49, 95% CI 0.33–0.73) and Hispanic (aOR 0.77, 95% CI 0.60–0.98) racial and ethnic groups, were significantly less likely to receive radiation therapy. Conclusions: These findings reveal notable disparities in radiation therapy utilization for SPB patients based on income and race and ethnicity, emphasizing the need for interventions to address systemic inequities, improve access to care, and ensure that all patients receive high-quality cancer care to optimize long-term outcomes. Full article

The term heart disease refers to a wide range of conditions that impact the heart and blood vessels. It continues to be a major global cause of morbidity and mortality. The narrowing or blockage of blood vessels, which can result in major medical events like heart attacks, angina (chest pain) or strokes, is a common issue linked to heart disease. In order to lower the risk of serious complications and facilitate prompt medical intervention, early diagnosis and prediction are essential. This study developed predictive models that can precisely identify people at risk by applying a variety of machine learning algorithms to a structured dataset on heart disease. Blood pressure, cholesterol, age, gender, and other health-related indicators are among the 13 essential characteristics that make up the dataset. Numerous machine learning models such as Naïve Bayes, K-Nearest Neighbors (KNN), Support Vector Machine (SVM), Decision Tree, Random Forest, and others were trained using these features. Using the RapidMiner platform, which offered a visual environment for data preprocessing, model training, and performance analysis, all models were created and assessed. The best-performing model was the Naïve Bayes classifier which achieved an impressive accuracy rate of 90% after extensive testing and comparison of performance metrics like accuracy precision and recall. This outcome shows how well the model can predict heart disease in actual clinical settings. By supporting individualized health recommendations, enabling early diagnosis, and facilitating timely treatment, the effective application of such models can significantly benefit patients and healthcare professionals. Furthermore, heart disease incidence can be considerably decreased by identifying and addressing modifiable risk factors such as high blood pressure, elevated cholesterol, smoking, diabetes, and physical inactivity. In summary, machine learning has the potential to improve the identification and treatment of heart-related disorders. This study highlights the value of data-driven methods in healthcare and indicates that incorporating predictive models into standard medical procedures may enhance patient outcomes, lower healthcare expenses, and improve public health administration. Full article

Chronic hepatitis B (CHB) remains a major global health challenge, largely due to the persistence of covalently closed circular DNA (cccDNA) and impaired host immunity. Interferon-α (IFN-α), a key antiviral cytokine, not only directly restricts HBV replication but also orchestrates innate and adaptive immune responses. This review summarizes current advances in IFN-α-mediated immune regulation, highlighting its effects across diverse immune cell populations. Evidence indicates that IFN-α can reprogram immune responses to promote viral clearance, although clinical efficacy is limited by modest response rates and adverse effects. Recent progress in cytokine engineering, subtype research, and rational combination strategies—including nucleo(s/t)ide analogs, RNA interference therapeutics, antisense oligonucleotides, therapeutic vaccines, and beyond—has expanded opportunities to improve treatment outcomes. While challenges remain, these advances lay the foundation for optimizing IFN-α–based interventions and highlight IFN-α as a key driver for innovative therapies aimed at achieving a functional cure of chronic hepatitis B. Full article

Hormone replacement therapy (HRT) has been utilized in clinical practice for decades as a main therapeutic approach for mitigating menopausal symptoms. The symptoms mostly encompass vasomotor and genitourinary issues resulting from the deficiency of estrogen and progesterone. Initially identified as a universally advantageous and indispensable intervention, hormone replacement therapy subsequently became the subject of considerable scientific and clinical debate, especially after the publication of extensive epidemiological studies indicating potential adverse effects associated with cardiovascular and cancer risk. This study aims to reassess the role of HRT in clinical practice by analyzing its historical evolution, expanded clinical uses, and changes in guidelines necessitated by resent scientific studies. Current evidence from clinical studies and meta-analyses unequivocally demonstrates that hormone replacement therapy is the most efficacious treatment for vasomotor and urogenital symptoms, and also acknowledging its potential role in osteoporosis prevention. The administration of HRT requires careful individual assessment, considering the patient’s age, timing of initiation, existence of comorbidities. In this setting, therapy decisions have to be based on a combination of the most up-to-date clinical guidelines, risk stratification, and the patient’s preferences. In conclusion, the assessment of HRT confirms its primary role in reducing menopausal symptoms while also highlighting the imperative for a individual strategy that balances benefits and risks to improve outcomes for women. Full article

Objectives: This study aimed to assess the impact of traditional Korean medicine services (TKMS) on subsequent knee surgery and opioid use in patients diagnosed with knee osteoarthritis (KOA). Methods: This retrospective cohort study used National Health Insurance Review and Assessment Service claims data from 2015 to 2017 to identify patients treated for KOA (M17) in 2016. Patients with at least two Korean medicine (KM) clinic visits within 6 weeks of the initial diagnosis formed the TKMS group, while those without visits to KM clinics formed the n group. Propensity score matching (PSM) (1:1) was applied and the incidence of knee surgery and opioid use was followed up for one year. Kaplan–Meier survival curves and Cox proportional hazards models estimated time-to-event outcomes and hazard ratios (HRs). Sensitivity analyses were performed to verify the results across varied treatment windows of 4, 8, and 10 weeks. Results: After PSM, 247,168 patients were included in the analysis for each group. The TKMS group exhibited significantly lower HRs for knee surgery (HR = 0.69, 95% CI: 0.66–0.72), opioid use (HR = 0.66, 95% CI: 0.65–0.66), and their compound events (HR = 0.66, 95% CI: 0.65–0.67) compared with the Non-TKMS group. The results remained consistent across sensitivity analyses. Conclusions: Among patients with KOA, the utilization of TKMS may significantly reduce the incidence of knee surgery and opioid use. Thus, the utilization of TKMS may be associated with a reduced need for unnecessary surgical interventions and with lower reliance on high-risk medications. Full article

Epilepsy is one of the most prevalent and disabling neurological disorders, affecting approximately one percent of the population. Due to the complex pathophysiology underlying drug-resistant epilepsy, nearly one-third of patients with epilepsy do not benefit from current treatments. Neuroinflammation is one of the most well-studied pathways in epileptogenesis, and inflammatory mediators play a crucial role in this process. The IL-1β/IL-1R1/IL-1Ra and HMGB1/TLR4 pathways play significant roles in epileptogenesis in both animal and human studies. Interventional investigations on the IL-1β/IL-1R1/IL-1Ra and HMGB1/TLR4 pathways showed antiseizure effects, suggesting that these pathways could be therapeutic targets for epilepsy. However, related targeted treatments are limited in clinical practice. In this work, we evaluated the advances of the IL-1β/IL-1R1/IL-1Ra and HMGB1/TLR4 pathways in epileptogenesis, as well as clinical trials or interventional investigations of current medications or substances targeting these pathways. To facilitate clinical translation, we highlighted the gap between research advancements and clinical practice and presented several strategies for closing the gap to fulfill the urgent requirements of patients with epilepsy. Full article

Cancer remains a major global health burden, representing one of the leading causes of mortality among noncommunicable diseases worldwide. Although conventional treatment modalities, including surgical resection, chemotherapy, radiotherapy, targeted therapy, and immunotherapeutic interventions, have demonstrated clinical benefits, their therapeutic efficacy is often constrained by inherent limitations such as low specificity, systemic toxicity, or tumor heterogeneity. These challenges underscore the imperative for developing innovative treatment strategies. Emerging evidence has implicated ion channels as critical players in oncogenesis and cancer progression. These proteins modulate diverse oncogenic phenotypes, including uncontrolled proliferation, metastatic dissemination, and apoptotic resistance. Their frequent dysregulation in malignancies correlates with disease aggressiveness and clinical outcomes, positioning them as promising targets for precision oncology. Notably, pharmacological modulation of ion channels exerts multifaceted antitumor effects, with several channel-targeting agents advancing through clinical trials. This review explores recent advances in ion channel-targeted therapies, emphasizing their mechanisms, clinical applications, and challenges. Furthermore, we examine the pathophysiological contributions of ion channels to tumor biology and evaluate their emerging utility as predictive biomarkers, providing perspectives on addressing critical gaps in current oncologic management. Full article

Atrial fibrillation (AF) is the supraventricular tachy-arrhythmia most commonly detected in the general population, with significant sex-related differences in epidemiology, pathophysiology, and treatment outcomes. Emerging evidence highlights the role of sex hormones—particularly estrogen and testosterone—in modulating left atrial electrophysiologic substrate, structural remodeling, inflammation, and thromboembolic risk. Hormonal fluctuations across different lifespan influence AF onset, progression, and therapeutic response, yet current management approaches largely overlook such determinants. This narrative review integrates data from basic, translational, and clinical research to examine hormonal effects on atrial substrate, disease progression, and differential results of treatments, including stroke prevention, pharmacological options, and transcatheter ablation. It also explores the potential of hormone-targeted interventions, antifibrotic therapies, and precision strategies tailored to hormonal status. Addressing these mechanisms could optimize patient-specific management, improve outcomes and guide future clinical practice recommendations. Advancing toward sex-specific, hormone-informed AF care requires further mechanistic studies, hormonal profiling, and sex-stratified clinical trials. Full article