Search Results (1,894)

Background: Stress is a critical determinant of mental health, yet conventional monitoring approaches often rely on subjective self-reports or physiological signals that lack real-time responsiveness. Recent advances in large language models (LLMs) offer opportunities for speech-driven, adaptive stress detection, but existing systems are limited to retrospective text analysis, monolingual settings, or detection-only outputs. Methods: We developed a real-time, speech-driven stress detection framework that integrates audio recording, speech-to-text conversion, and linguistic analysis using transformer-based LLMs. The system provides multimodal outputs, delivering recommendations in both text and synthesized speech. Nine LLM variants were evaluated on five benchmark datasets under zero-shot and few-shot learning conditions. Performance was assessed using accuracy, precision, recall, F1-score, and misclassification trends (false-negatives and false-positives). Real-time feasibility was analyzed through latency modeling, and user-centered validation was conducted across cross-domains. Results: Few-shot fine-tuning improved model performance across all datasets, with Large Language Model Meta AI (LLaMA) and Robustly Optimized BERT Pretraining Approach (RoBERTa) achieving the highest F1-scores and reduced false-negatives, particularly for suicide risk detection. Latency analysis revealed a trade-off between responsiveness and accuracy, with delays ranging from ~2 s for smaller models to ~7.6 s for LLaMA-7B on 30 s audio inputs. Multilingual input support and multimodal output enhanced inclusivity. User feedback confirmed strong usability, accessibility, and adoption potential in real-world settings. Conclusions: This study demonstrates that real-time, LLM-powered stress detection is both technically robust and practically feasible. By combining speech-based input, multimodal feedback, and user-centered validation, the framework advances beyond traditional detection only models toward scalable, inclusive, and deployment-ready digital mental health solutions. Full article

Background: Mandibular canal (MC) variants are common and clinically relevant for anesthesia, implant placement, third-molar surgery, and osteotomies. Reported prevalences vary widely because they depend on imaging modality, acquisition parameters, and operational definitions. Methods: This was a focused narrative review with structured methods (PubMed/MEDLINE and Scopus, 2000–6 October 2025; last search 6 October 2025), predefined eligibility criteria and dual independent screening; no meta-analysis was conducted. Study-selection counts are reported in the text. Prevalence statements are contextualized by modality, imaging parameters (e.g., cone-beam computed tomography (CBCT) voxel size magnetic resonance imaging (MRI) field strength/sequences), and diagnostic thresholds (e.g., anterior loop (AL) criteria). Results: Compared with panoramic radiography (PR), CBCT consistently reveals more variant pathways. Typical CBCT estimates for bifid MC fall in the single-digit to low double-digit range, contingent on voxel size and definitions, whereas PR detects far fewer. Trifid canals are uncommon (≈1–2% in CBCT series). Reported retromolar canal frequencies vary broadly across populations and protocols, and AL length and prevalence are threshold-dependent. Selective MRI may complement CBCT by depicting soft-tissue branches not accompanied by a bony canal. We synthesize a variant-aware, imaging-led workflow: PR for screening; CBCT when predefined criteria are met and results are reasonably expected to change management; MRI reserved for targeted soft-tissue questions, in line with As Low as Reasonably Achievable (ALARA)/and As Low As Diagnostically Acceptable (ALADA) principles. We apply the Landfald Clinical Framework (LCF) as a hypothesis-generating, clinical synthesis tool linking variant patterns to procedural modifications and risk mitigation. Conclusions: A narrowed, clinically oriented approach—contextualizing prevalence by modality and definitions and applying an imaging-led, variant-aware workflow—can improve planning and safety in the posterior mandible. The LCF is used pragmatically within this workflow and does not constitute a new anatomical taxonomy; formal reliability and validity testing remain necessary. Full article

Background/Objectives: Precise breast ultrasound (BUS) segmentation supports reliable measurement, quantitative analysis, and downstream classification yet remains difficult for small or low-contrast lesions with fuzzy margins and speckle noise. Text prompts can add clinical context, but directly applying weakly localized text–image cues (e.g., CAM/CLIP-derived signals) tends to produce coarse, blob-like responses that smear boundaries unless additional mechanisms recover fine edges. Methods: We propose XBusNet, a novel dual-prompt, dual-branch multimodal model that combines image features with clinically grounded text. A global pathway based on a CLIP Vision Transformer encodes whole-image semantics conditioned on lesion size and location, while a local U-Net pathway emphasizes precise boundaries and is modulated by prompts that describe shape, margin, and Breast Imaging Reporting and Data System (BI-RADS) terms. Prompts are assembled automatically from structured metadata, requiring no manual clicks. We evaluate the model on the Breast Lesions USG (BLU) dataset using five-fold cross-validation. The primary metrics are Dice and Intersection over Union (IoU); we also conduct size-stratified analyses and ablations to assess the roles of the global and local paths and the text-driven modulation. Results: XBusNet achieves state-of-the-art performance on BLU, with a mean Dice of 0.8766 and IoU of 0.8150, outperforming six strong baselines. Small lesions show the largest gains, with fewer missed regions and fewer spurious activations. Ablation studies show complementary contributions of global context, local boundary modeling, and prompt-based modulation. Conclusions: A dual-prompt, dual-branch multimodal design that merges global semantics with local precision yields accurate BUS segmentation masks and improves robustness for small, low-contrast lesions. Full article

Background/Objectives: Digital interventions are essential for dementia care, particularly for older and isolated populations, and provide valuable support for caregivers. This umbrella review aimed to evaluate the acceptability and barriers to implementing the use of digital tools for health monitoring and management in older people with dementia and/or their caregivers. Methods: The review included studies assessing acceptability factors and barriers related to technology use in these groups. A total of 612 studies were identified across three databases. After removing duplicates, 400 articles remained. Following title and abstract screening, thirty articles were selected for full-text evaluation and five met the eligibility criteria for inclusion in this review. These systematic reviews collectively covered 93 primary studies, encompassing 12 to 279 participants with dementia and 11 to 2761 caregivers. Results: Frequently reported factors included self-management support, information access, and enhanced communication, although these were not consistently addressed across all reviews. The most significant barrier was a lack of technical knowledge, which hindered effective use. This gap in knowledge could compromise self-management and potentially increase burden on caregivers. Conclusions: In conclusion, digital interventions offer significant benefits in addressing accessibility challenges and are generally well-received by people with dementia, their caregivers, and healthcare providers. However, addressing the lack of technological proficiency is crucial to ensuring these interventions are effective and do not inadvertently create additional challenges. Practical strategies should include tailored digital literacy training for older adults and caregivers, simplified user interfaces, and ongoing technical support to enhance engagement and long-term adherence. Full article

Transcranial direct current stimulation (tDCS) is being explored as an adjunct for diabetes-related symptoms grounded in diabetes-associated alterations in brain networks. We reviewed clinical trials of tDCS conducted in people with diabetes and summarized mechanistic findings relevant to metabolic control. Two reviewers searched PubMed/MEDLINE, Cochrane Library, Google Scholar, Scopus, and ResearchGate for studies published from 1 January 2008 to 31 August 2025. Forty-one records were identified; after screening and full-text assessment, 11 studies met the inclusion criteria. Across predominantly middle-aged adults with long-standing type 2 diabetes, protocols were low-intensity and well-tolerated. The most consistent clinical benefit was analgesia with primary motor cortex stimulation, with randomized comparisons favoring active tDCS over sham. Dorsolateral prefrontal stimulation paired with working-memory training improved cognition and reduced anxiety, while combined motor–prefrontal courses yielded gains in sleep quality and health-related quality of life; a small, randomized study in proliferative diabetic retinopathy reported short-term visual improvements after occipital stimulation. Safety was favorable, and no serious adverse events were reported. Objective metabolic endpoints in diabetic cohorts were scarce; early evidence for insulin-independent improvements in glucose handling and neurometabolic shifts derives mainly from non-diabetic or mixed samples and remains hypothesis-generating. Overall, tDCS appears to be a promising, well-tolerated adjunct for diabetes-related complications. Larger, rigorously sham-controlled trials that align targets with clinical phenotypes and include standardized metabolic outcomes are needed. Full article

Background and Aims: In recent decades, lifestyle patterns have undergone significant transformations, particularly in low- and middle-income countries (LMICs). These changes have contributed to a dual nutritional crisis characterized by the coexistence of undernutrition and overweight/obesity, commonly referred to as the Double Burden of Malnutrition (DBM). Compounding this issue is the persistent prevalence of parasitic infections, due to poor personal hygiene and sanitation practices which further exacerbate nutritional imbalances, creating what is now recognized as the Triple Burden of Malnutrition (TBM). This review aims to explore the evolving lifestyle factors that have contributed to the emergence of the DBM and to examine its intersection with parasitic infections. The focus is particularly on South Asian low- and middle-income countries, where these overlapping burdens present a significant public health challenge. By highlighting the interconnectedness of malnutrition, obesity, and parasitic diseases, this study seeks to provide a comprehensive understanding of the current nutritional landscape in South Asian LMICs and to inform future health interventions and policies. Methods: This study was conducted using published and unpublished secondary data that are available on websites and other printed materials. One of the main requirements is date, with 2013 being regarded as the initiative’s landmark. Another crucial factor is the availability of the entire article. For this study, only research publications published in English were taken into consideration. Zotero was used for compilation. The majority of the analysis was performed using percentages and ratios. A thorough evaluation of all the studies’ methodology, design, execution, and reporting was performed in order to spot any systematic flaws in this study. Results: Only 45 of the 105 full-text papers that were screened met the requirements for inclusion. Of these studies, 15 satisfied the inclusion and exclusion requirements. The results show that China, with a comparatively higher income level status, has more prevalence of overweight and obesity among children (11.5%) and women (34.6%) than India (2.1% of OWOB among children and 20.6% among women). Nepal stands behind China and India with 1.2% of OWOB among children and between them with 22.2% OWOB among women. Interestingly, among the three South Asian nations, India has the highest stunting, wasting, and underweight among children (38.4%, 21%, and 35.7%, respectively) followed by Nepal (35.8%, 9.7%, and 27%) and China (8.1%, 2%, and 2.5%). This study finds no significant difference in the prevalence of intestinal parasitic infections among OWOB and underweight populations. This review finds that the DBM along with parasitic infections has resulted in a Triple Burden of Malnutrition, which is currently a major public health issue in low- and middle-income countries in South Asia. Discussion: The various types of malnutrition were once thought of and treated as distinct public health problems, but the new understanding is that undernutrition and overnutrition are linked, and that in order for policy solutions to be successful, double-duty measures that simultaneously address multiple dimensions must be put in place. When the DBM is combined with parasite illnesses, it becomes the Triple Burden of Malnutrition, which is the primary cause of the financial burden in LMICs. China has the worst obesity problem, yet it also has more obesity-related laws and intervention programs than India and Nepal combined. All three nations, however, have failed to stop or deal with the dramatic increase in OWOB over the last 20 years. For effective implementation and results, genetic and psychological factors must also be taken into account when developing policies and programs to tackle the obesity epidemic, undernutrition, and parasite diseases. Conclusions: The prevalence of the DBM has been rising globally, with South Asia seeing a faster rate of increase. A growing DBM is favorably correlated with national economic development. In South Asian LMICs, the DBM combined with parasite diseases has resulted in a Triple Burden of Malnutrition, a debilitating illness. Full article

Background: FDA-approved artificial sweeteners (ASs) are widely used in food products due to their low-calorie content and high sweetness. However, growing evidence links them to adverse metabolic effects, including stroke and coronary heart disease. The musculoskeletal system, as a key metabolic target organ, has gradually gained attention, but the potential impact of ASs on its health remains unclear. Objective: This systematic review aims to assess the effects of ASs on bone and muscle, explore the underlying biological mechanisms and provide guidance for future research. Methods: A comprehensive literature search was conducted in PubMed, Embase, and Web of Science using relevant keywords from inception to 25 June 2025. Studies written in English, available in full text, and investigating FDA-approved ASs in relation to the musculoskeletal system were included. Two independent reviewers screened and selected the eligible studies. The findings were summarized using a narrative synthesis approach. Results: A total of 15 studies (12 preclinical, 3 clinical), covering aspartame, acesulfame potassium, sucralose, and saccharin were included from an initial pool of 662 articles identified across PubMed (168), Embase (368), and Web of Science (126). Among them, twelve studies focused on skeletal effects, four on muscles, and two on joints; three studies reported multiple outcomes. No studies investigated ligaments or tendons. Conclusions: Based on our search, this review provides a narrative synthesis of the available evidence on ASs influencing skeletal structure, development, biomechanical strength, and skeletal muscle metabolism. Potential mechanisms involve gut microbiota, oxidative stress, and signaling pathways such as SIRT1/FOXO3a and PGC-1α/UCP3. Further research is warranted to clarify these mechanisms and to assess the chronic health effects of long-term AS exposure on the musculoskeletal system in human populations. Full article

In mathematics, and in learning mathematics, representations (texts, formulae, and figures) play a vital role. Eye-tracking is a promising approach for studying how representations are attended to in the context of mathematics learning. The focus of the research reported here is on the methodological and conceptual challenges that arise when analysing students’ engagement with different kinds of representations using such data. The study critically examines some of these issues through a case study of three engineering students engaging with an instructional document introducing double integrals. This study reports that not only the characteristics of different types of representations affect students’ engagement with areas of interests (AOIs), but also methodological decisions, such as how AOIs are defined, will be consequential for interpretations of that engagement. This shows that both technical parameters and the inherent nature of the representations themselves must be considered when defining AOIs and analysing students’ engagement with representations. The findings offer practical considerations for designing and analysing eye-tracking studies when students’ engagement with different representations is in focus. Full article

Background/Objectives: Giant atrial chambers are rare but clinically important conditions, most often linked to rheumatic mitral valve disease, though they may also occur in congenital or other acquired disorders. Despite their low prevalence, they entail major hemodynamic, arrhythmogenic, and extracardiac risks. This study aimed to review recent evidence on giant atrial pathology—including giant left atrium (GLA), giant right atrium (GRA), and atrial appendage aneurysms—and to illustrate its relevance through cases of symptomatic extracardiac compression. Methods: A PubMed search on 15 September 2025 using “giant atrium” and limited to human, free full-text studies from the last 10 years yielded 93 results. After screening, 21 reports describing 24 cases were analyzed and compared with institutional experience. Results: GLA is most often defined by an anteroposterior diameter ≥6.5 cm or ≥8 cm, while criteria for GRA and appendage aneurysms remain inconsistent. Reported complications include atrial fibrillation, thromboembolism, and compression of mediastinal structures, with presentations such as dysphagia or airway obstruction. While valve surgery alone may suffice, many authors recommend concomitant atrial reduction or aneurysm resection in symptomatic patients. Conclusions: Giant atrial pathology, though uncommon, carries significant cardiac and extracardiac implications. Management should be individualized, and awareness of atypical manifestations is critical for timely diagnosis and treatment. Full article

Background: Diabetes and mental health conditions frequently co-occur, with depression and anxiety affecting up to 20–30% of people with diabetes. These comorbidities worsen glycemic control, adherence, and quality of life, yet mental health is often neglected in diabetes care. Integrating mental health services into diabetes management is recommended by international organizations to improve patient outcomes. Objectives: To systematically review the evidence on integrated mental health interventions in diabetes care, compared to usual diabetes care, in improving patient outcomes (glycemic control, mental health, adherence, quality of life). Methods: We searched PubMed/MEDLINE, Embase, PsycINFO, and Scopus (2000 through July 2024) for studies of diabetes care integrating mental health support (e.g., collaborative care, co-location, stepped care, or digital interventions). Inclusion criteria were controlled trials or cohort studies involving individuals with type 1 or type 2 diabetes receiving an integrated mental health intervention, with outcomes on glycemic control and/or mental health. Two reviewers independently screened titles/abstracts and full texts, with disagreements resolved by consensus. Data on study design, population, intervention components, and outcomes were extracted. Risk of bias was assessed using Cochrane or appropriate tools. Results: Out of records identified, 64 studies met inclusion criteria (primarily randomized controlled trials). Integrated care models consistently improved depression and anxiety outcomes and diabetes-specific distress, and yielded modest but significant reductions in glycated hemoglobin (HbA1c) compared to usual care. Many interventions also enhanced treatment adherence and self-management behaviors. For example, collaborative care trials showed greater depression remission rates and small HbA1c improvements (~0.3–0.5% absolute reduction) relative to standard care. Co-located care in diabetes clinics was associated with reduced diabetes distress, depression scores, and HbA1c over 12 months. Digital health integrations (telepsychiatry, online cognitive-behavioral therapy) improved psychological outcomes and adherence, with some reporting slight improvements in glycemic control. Integrated approaches often increased uptake of mental health services (e.g., higher referral completion rates) and showed high patient satisfaction. A subset of studies reported fewer emergency visits and hospitalizations with integrated care, and one economic analysis found collaborative care cost-effective in primary care settings. Conclusions: Integrating mental health into diabetes care leads to better mental health outcomes and modest improvements in glycemic control, without adverse effects. Heterogeneity across studies is noted, but the overall evidence supports multidisciplinary, patient-centered care models to address the psychosocial needs of people with diabetes. Healthcare systems should prioritize implementing and scaling integrated care, accompanied by provider training and policy support, to improve outcomes and bridge the persistent treatment gap. Future research should focus on long-term effectiveness, cost-effectiveness, and strategies to reach diverse populations. Full article

Prepubescent children and young adolescents (ages 7–14) are in a critical developmental stage for establishing the foundations of healthy sexual behavior. Increasing rates of precocious puberty, combined with limited access to accurate and age-appropriate sexual health education, heighten the vulnerability of this age group to sexual health risks. These risks include early and often coerced sexual initiation, exposure to sexual abuse, and consequent outcomes such as sexually transmitted infections and early pregnancies. However, comprehensive cross-regional analyses and evidence-based interventions addressing the sexual health needs of this age group remain limited. Addressing this gap promotes mutual learning, context-specific adaptation, and global alignment of sexual health support efforts, crucial for achieving the Sustainable Development Goal target of universal access to sexual and reproductive health care. This scoping review aims to map the available evidence on the scope and characteristics of sexual health interventions for prepubescents and young adolescents in the United States and Sub-Saharan Africa. The proposed scoping review will be conducted in accordance with the Arksey and O’Malley framework and Joanna Briggs Institute (JBI) methodology for scoping review. A systematic search of English-language articles published from 2010–2025 will be conducted across PubMed, CINAHL, PsycINFO, Scopus, Web of Science, ERIC, and African Index Medicus. Five reviewers will screen the articles in Covidence and independently assess full-text articles using a standardized data extraction form. Discrepancies will be resolved through discussion and with a sixth reviewer. The review will follow the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guidelines. Data will be summarized and synthesized to identify patterns in interventions, delivery methods, outcomes, and implications for practice, research, and policy. Comparative and gap analyses will highlight similarities, differences, and priorities for future research and interventions. An adolescent sexual health expert will help validate and contextualize findings. Results can guide strategies to address shared challenges and advance universal access to sexual health support for prepubescents and young adolescents. Full article

Objective: To explore medical students’ perceptions towards the integration of basic science into virtual patient (VP) cases and to evaluate the impact on self-perceived clinical reasoning (CR) ability. Methods: We conducted a qualitative and explorative study involving 14 medical students during their clinical placement within rheumatology. Basic science elements were integrated into five VP scenarios using the virtual interactive case simulator. Students’ perceptions were explored through the analysis of semi-structured interviews with seven students, followed by Malterud’s systematic text condensation. Results: The analysis yielded five themes: (i) appreciation of basic science knowledge, (ii) ambiguity towards basic science as an obstacle for integration, (iii) the effect of integration on self-perceived clinical reasoning, (iv) engaging design of the basic science integration, and (v) low knowledge of clinical reasoning concepts. Despite positive perceptions, students demonstrated low motivation for independent engagement in practice. The students who completed the intervention reported enhanced self-perceived CR abilities, as evidenced by more comprehensive thinking processes. Conclusions: Basic science integration into VP cases was positively perceived and appeared to enhance self-perceived CR abilities. However, students’ reluctance to independently engage posed implementation challenges. Early introduction of CR learning objectives and CR as a conceptual framework may improve motivation and provide coherence for the integration of basic science in the clinical components of medical education. Full article

Background: Meat adulteration poses serious public health, economic, and religious concerns, particularly in the Middle East and North Africa (MENA) and Gulf Cooperation Council (GCC) regions where halal authenticity is essential. While isolated studies have reported undeclared species in meat products, a comprehensive regional synthesis of prevalence, detection technologies, and regulatory responses has been lacking. Methods: This scoping review followed PRISMA-ScR guidelines. A systematic search of PubMed, Scopus, and Web of Science from database inception to 15 September 2025 was conducted using controlled vocabulary (MeSH) and free-text terms. Eligible studies included laboratory-based investigations of meat adulteration in MENA and GCC countries. Data were charted on study characteristics, adulteration types, detection methods, and regulatory context. Results: Out of 50 records screened, 35 studies were included, covering 27 MENA/GCC countries. Prevalence of adulteration varied widely, from 5% in UAE surveillance studies to 66.7% in Egyptian native sausages. Undeclared species most frequently detected were poultry, donkey, equine, pig, and dog. Molecular methods, particularly PCR and qPCR, were most widely applied, followed by ELISA and spectroscopy. Recent studies introduced biosensors, AI-assisted spectroscopy, and blockchain traceability, but adoption in regulatory practice remains limited. Conclusions: Meat adulteration in the MENA and GCC regions is localized and product-specific rather than uniformly widespread. Detection technologies are advancing, yet regulatory enforcement and halal-sensitive verification remain fragmented. Strengthening laboratory capacity, harmonizing regional standards, and investing in portable biosensors, AI-enhanced spectral tools, and blockchain-based traceability are critical for consumer trust, halal integrity, and food safety. Full article

Background and Objectives: Public health needs collaborative, privacy-preserving analytics, but centralized AI is constrained by data sharing and governance. Federated learning (FL) enables training without moving sensitive data. This review assessed how FL is used for disease prevention in population and public health, and mapped benefits, challenges, and policy implications. Methods: Following PRISMA 2020, we searched PubMed, Scopus, Web of Science, IEEE Xplore, and Google Scholar for peer reviewed English-language studies from January 2020–30 June 2025, applying FL to surveillance, outbreak detection, risk prediction, or policy support. Two reviewers screened and extracted data with third-reviewer arbitration. Quality was appraised with a tool adapted from MMAT and AI reporting frameworks. No meta-analysis was performed. Results: Of 5230 records identified (4720 after deduplication), 200 full texts were assessed and 19 were included. Most used horizontal FL across multiple institutions for communicable diseases, COVID-19, tuberculosis and some chronic conditions. Reported gains included privacy preservation across sites, better generalizability from diverse data, near real-time intelligence, localized risk stratification, and support for resource planning. Common barriers were non-IID data, interoperability gaps, compute and network limits in low-resource settings, unclear legal pathways, and concerns about fairness and transparency. Few studies linked directly to formal public-health policy or low-resource deployments. Conclusions: FL is promising for equitable, secure, and scalable disease-prevention analytics that respect data sovereignty. Priorities include robust methods for heterogeneity, interoperable standards, secure aggregation, routine fairness auditing, clearer legal and regulatory guidance, and capacity building in underrepresented regions. Full article

Variable renewable energy sources and cross-zonal trades stress transmission grids, pushing them toward thermal limits. This systematic review, reported in accordance with PRISMA 2020, examines how demand-side response (DSR) can provide relief at the transmission scale. We screened peer-reviewed literature and operator documentation, from 2010 to 2025, indexed in Web of Science, Scopus, and IEEE Xplore; organized remedial actions across supply, network, and demand/storage levers; and categorized operational attributes (time to effect, spatial targeting, activation lead times, telemetry, and measurement and verification). Few reviewed sources explicitly link DSR to transmission congestion relief, highlighting the gap between its mature use in frequency and adequacy services and its still-limited, location-specific application on the grid. We identify feasibility conditions, including assets downstream of the binding interface, minute-scale activation, and feeder-grade baselines with rebound accounting. This implies the following design requirements: TSO–DSO eligibility registries and conflict resolution, portfolio mapping to power-flow sensitivities, and co-optimization with redispatch, HVDC, topology control, and storage within a security-constrained optimal-power-flow framework. No full-text risk-of-bias assessment or meta-analysis was undertaken; the review used English-only title/abstract screening. Registration: none. Funding: none. Full article