Emerging evidence suggests that human flourishing is not guaranteed, even in economically developed nations, with substantial disparities reported across populations and contexts. This highlights an urgent need for scalable, context-sensitive approaches that support flourishing and holistic wellbeing. Physical activity represents one such pathway, with growing evidence linking participation to psychological, social, and physical dimensions of flourishing. However, many strategies aimed at increasing physical activity overlook the complexity of behaviour change and the socio-cultural factors shaping movement experiences. As a result, physical activity is often framed as a prescriptive health behaviour rather than a meaningful, intrinsically rewarding experience. This paper presents a conceptual framework that integrates meaningful physical activity, physical literacy, and human flourishing to inform policy, practice, and research aimed at fostering lifelong engagement in movement and wellbeing. A Delphi study was conducted with an international panel of experts working across the fields of meaningful physical activity, physical literacy, and human flourishing (N = 8; 75% female). Through iterative rounds of consultation, including focus group workshops and structured evaluation processes, participants provided feedback to refine a preliminary conceptual framework and establish consensus regarding its clarity, relevance, and practical utility. The Delphi process resulted in a refined framework characterised by enhanced conceptual coherence, stronger alignment with contemporary theory and policy, and greater clarity regarding the interrelationships among meaningful physical activity, physical literacy, and human flourishing. Expert feedback contributed to a more explicit articulation of the mechanisms through which meaningful movement experiences and physical literacy development may support flourishing across the lifespan. The resulting framework provides a theoretically grounded and practice-oriented model for understanding how movement experiences may contribute to human flourishing. By emphasising the quality, meaning, and embodied nature of physical activity, the framework offers guidance for policymakers, public health practitioners, educators, and community organisations seeking to promote sustainable, lifelong engagement in movement and support holistic wellbeing.
Youth with attention-deficit/hyperactivity disorder (ADHD) may experience persistent barriers to engagement in individual psychotherapy despite adequate pharmacologic treatment and evidence-based therapeutic content. Existing gamified approaches often rely on fixed protocols, specialized materials, or group-based formats to address interfering symptoms such as distractibility, low frustration tolerance, and difficulty sustaining mental effort, with mixed feasibility and clinical outcomes. This case describes a novel, individualized gamified intervention designed to address limitations of existing approaches and support ADHD treatment engagement. An otherwise healthy 11-year-old male with ADHD, combined type, was referred for outpatient psychotherapy to address difficulties with organization and emotional self-regulation while receiving methylphenidate extended-release 18 mg daily. Early sessions used established approaches, including gamified interventions, but were marked by distractibility, fidgeting, and disengagement. Treatment was reorganized into a structured, therapist-led, quest-based gamified framework delivered across 21 completed 60-minute sessions over approximately 24 weeks. ChatGPT-4o was used to assist with narrative creation and maintenance and to support integration of therapist-selected psycho-education, behavioral skills training, cognitive-behavioral strategies, mindfulness, and parent management principles into a tabletop role-playing structure. Over time, the patient demonstrated progressively improved engagement, emotional awareness, organization, and coping skills, corroborated by parent-informed improvements on the "Hyperactive/Impulsive" and "Conduct" items of the National Institute for Children's Health Quality (NICHQ) Vanderbilt Assessment Scale, third edition. This case illustrates how therapist-led gamification may function as a pragmatic delivery framework for evidence-based individual psychotherapy in youth with ADHD when engagement is a primary treatment barrier. The intervention emphasized therapist-guided skills coaching, flexibility, narrative reinforcement, and repeated practice. A large language model was used to make the intervention feasible, primarily as a preparatory narrative support tool under full therapist oversight. Further study is needed to evaluate the feasibility, acceptability, and generalizability of individualized gamified psychotherapy frameworks in outpatient ADHD treatment.
As cancer incidence rises in Asian countries, chemotherapy remains central to treatment amid rapid population aging and declining fertility in most of them. These trends underscore concern over long-term reproductive health, as chemotherapy-induced ovarian toxicity and premature ovarian insufficiency (POI) emerge as major late effects with unclear population-specific susceptibility. This review examines chemotherapy-induced ovarian damage via the PI3K-AKT-FOXO3 signaling axis, a key regulator of follicular quiescence, stress responses, and ovarian longevity. Evidence was synthesized from human studies, experimental models, and mechanistic investigations to develop this population-specific conceptual framework. Chemotherapy initiates DNA damage and oxidative stress, which subsequently activate interconnected pathways involving mitochondrial dysfunction, dysregulated autophagy, apoptosis, ferroptosis, inflammatory signaling, and dysregulation of the PI3K-AKT-FOXO3 axis, ultimately accelerating follicular activation and depletion. A distinctive contribution of this review is the integration of longevity-associated genetic susceptibility with ovarian vulnerability, highlighting evidence suggesting that certain FOXO3 and PI3K-AKT pathway variants, reported to be more prevalent in several Asian populations, may influence susceptibility to chemotherapy-induced ovarian injury. This review proposes a two-hit hypothesis as a conceptual framework integrating currently available molecular, experimental, and population-based evidence while acknowledging that direct clinical validation remains limited. Within this framework, longevity-associated genetic predisposition affecting the PI3K-AKT-FOXO3 axis constitutes the first hit, whereas chemotherapy-induced cellular stress represents the second hit, together accelerating follicular burnout and increasing the risk of POI. This framework supports future evaluation of genotype-informed risk stratification, individualized fertility preservation strategies, and prospective validation in Asian cancer cohorts, with the ultimate goal of informing ethnicity-specific fertility preservation strategies and optimized chemotherapy protocols.
Electron tomography (ET) is crucial for determining the three-dimensional (3D) structure of materials in real space but challenging due to the inherent missing wedge, high dose, and limited depth-of-field. Although deep learning can address these challenges in principle, the scarcity of ET data severely limits its application. In this study, we propose a general data-driven ET reconstruction framework that uses extensive and readily available random high-entropy projections to construct large-scale datasets. By integrating both real structural priors and depth-dependent imaging physics, the framework enables high-quality 3D reconstruction independent of specific materials or resolutions. Using this strategy, we successfully determine the 3D atomic structure of a 13-nm Pt nanoparticle containing 52 138 atoms, achieving a root-mean-square displacement of 22.6 pm; the projection consistency error is significantly reduced, effectively expanding the depth-of-field limit of atomic-scale ET.
Maize is one of the most important food crops in the world, and foliar diseases can lead to significant yield losses if identification is not performed on time. Experts conducting manual inspections find it less effective and more subjective. Deep learning-based approaches utilizing Convolutional Neural Networks (CNNs) and Vision Transformers (ViTs) have been demonstrated as a viable approach to automate disease diagnosis. Thus, while CNNs fail to capture wider context due to their local feature focus and ViTs need larger datasets and tend to miss finer-grained details. To overcome these limitations, we present EDISP a hybrid framework that connects Convolutional Neural Networks (CNNs) and Vision Transformers (ViTs) for local feature extraction, as well as global contextual learning. The EDISP framework brings together the strengths of CNNs and ViTs to overcome their individual weaknesses. It is trained on a dataset that includes both controlled-environment and real-field maize leaf images, which helps it handle different environmental conditions. The data undergoes thorough preprocessing, including normalization, augmentation, and stratified splitting into training, validation, and test sets to support generalization. The CNN focuses on detailed local disease features, while the ViT captures broader contextual information across the maize leaf surfaces. The proposed EDISP model significantly outperforms standalone CNN and ViT Models in multiple performance metrics, achieving an overall classification accuracy of 99.40%, precision of 99.43%, recall of 99.38%, and an F1-score of 99.40%. Experimental results demonstrate that EDISP excels in identifying maize leaf diseases, including Common Rust, Gray Leaf Spot, Northern Leaf Blight, and Healthy leaves, with minimal false positives and negatives. External validation with an independent dataset further highlights the model's robustness and ability to generalize to real-world conditions. The EDISP hybrid architecture, integrating CNNs and ViTs, provides a stronger method for accurate, automated maize leaf disease detection. Its robust performance, consistent results on controlled and field datasets shows robustness in diverse environments. However, EDISP's effectiveness may be limited by image quality, lighting, or disease types not seen in training. These results highlight the promise of hybrid deep learning in precision agriculture and offer a scalable solution for disease detection, supporting farmers without expert diagnostic resources.
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Men experience poorer health outcomes than women and are less likely to engage with traditional healthcare services, highlighting the need for gender-responsive, community-based approaches. The Football Cooperative (FC) initiative in Ireland uses recreational football as a socially engaging setting to support men's health and wellbeing. Although football-based initiatives demonstrate strong acceptability and health benefits, translating locally successful models into sustainable systems capable of large-scale delivery remains challenging. This study aimed to identify multilevel determinants influencing implementation of the FC initiative and to develop a prioritised implementation strategy to support national scale-up. A two-part qualitative design was employed, comprising (1) multilevel data collection through semi-structured interviews, focus groups, and reflective logs with stakeholders across participant, provider, organisational, and community/system levels, and (2) strategy development and prioritisation through an adapted Delphi consensus process. Data were analysed using a framework-informed approach guided by the Consolidated Framework for Implementation Research (CFIR), and scalability was further examined using the Intervention Scalability Assessment Tool (ISAT). Findings indicate that implementation of the FC initiative is underpinned by relational facilitators supporting sustained engagement, including psychological safety, inclusive gameplay, and accessibility and operational practicality at participant level. However, while these support local delivery, they do not readily translate to scale. Critical determinants constraining scale-up were identified across ecological levels, including reliance on volunteer coordination and limited role clarity at provider level, informal administrative and digital systems and limited workforce capacity at organisational level, and the absence of formalised governance, cross-sector collaboration, and sustainable funding at system level. In response, seven implementation strategies were prioritised: maintaining psychological safety and accessibility (participant level); strengthening coordination systems and volunteer capacity and role support (provider level); developing monitoring and digital infrastructure and supporting governance transition and distributed leadership (organisational level); and establishing cross-sector collaboration and funding mechanisms to support scale (community/system level). This study provides a theory-informed, stakeholder-endorsed implementation strategy to support the transition of a community-based men's health initiative from local delivery to scalable systems. The findings contribute to implementation science by demonstrating how multilevel determinant analysis can be translated into prioritised strategies supporting scale-up of gender-responsive interventions.
Palliative care is an essential health service for patients with chronic and life-threatening conditions. Although palliative care has been formally recognized in Georgia's legislation and state programs since the mid-2000s, evidence regarding the development, accessibility, and integration of services remains limited. The WHO framework, Assessing the Development of Palliative Care Worldwide: A Set of Actionable Indicators, and its application in the EAPC Atlas of Palliative Care in the European Region 2025 provide an opportunity for a comprehensive assessment of the national palliative care system. This study evaluated the development of palliative care in Georgia using WHO actionable indicators and compared the findings with the EAPC 2025 Atlas to identify system-level gaps and priorities for improvement. This study employed a descriptive health systems assessment and policy analysis of palliative care development in Georgia. The evaluation was guided by the World Health Organization's 2021 framework, Assessing the Development of Palliative Care Worldwide: A Set of Actionable Indicators. Fourteen indicators across six domains were operationalized using national administrative data, policy documents, institutional reports, and published literature from 2021 to 2024. Quantitative and qualitative findings were triangulated and benchmarked against the European Association for Palliative Care (EAPC) Atlas of Palliative Care in the European Region 2025 to assess service availability, accessibility, geographical distribution, coverage, and system capacity. While palliative care is legally recognized and partially embedded in national health policy, implementation remains limited and uneven. Service provision is highly centralized in Tbilisi, with restricted outpatient and home-based services in regions. In 2024, only 16.7% of the estimated national palliative care need was met. Opioid consumption remains in the very low range, reflecting restrictive regulations, limited medicine availability, and insufficient prescriber training. Similarly, the EAPC 2025 Atlas shows low performance across key WHO indicators, particularly in governance, monitoring mechanisms, service integration, research, and education. Despite early legislative advances, Georgia's palliative care system remains fragmented and inadequately integrated into primary health care. Strengthening governance, financing, education, and monitoring in line with WHO and EAPC benchmarks is essential to achieve equitable, sustainable, and comprehensive palliative care coverage.
Febrile seizures (FS) affect 2-5% of children globally, causing significant caregiver anxiety and healthcare utilization. Emerging evidence implicates neuroinflammation and T-cell-mediated immunity in FS pathogenesis, suggesting potential targets for future investigation. This Review synthesizes current evidence on FS prevention, emphasizing a paradigm shift from universal pharmacological approaches toward risk-stratified, personalized strategies. The COVID-19 pandemic provided unique insights: non-pharmaceutical interventions reduced FS incidence by 54-70%, while the Omicron variant emerged as a novel trigger associated with complex FS features. Prevention is conceptualized within a three-level framework: primary prevention targets all children through vaccination (MMR, PCV13, COVID-19 vaccines) and infection control; secondary prevention focuses on high-risk children with prior FS, where risk stratification integrates clinical predictors (complex features, young age, low fever), biomarkers (hyponatremia, zinc/vitamin D deficiency, inflammatory indices), and pathogen-specific risks (influenza A, Omicron); tertiary prevention addresses complications and epileptogenesis in children with complex FS or genetic predisposition (SCN1A, PCDH19). Key immunological mechanisms include HMGB1-NLRP3 inflammasome activation, TRPV1-mediated Th17 differentiation, and IL-1β/IL-10 dysregulation. Antipyretics do not prevent FS recurrence during distant febrile episodes, while intermittent benzodiazepines (diazepam, intranasal midazolam) effectively reduce early recurrence in high-risk children (NNT = 6.8), albeit with adverse effects in up to 36%. Emerging frontiers include novel therapeutic targets (HMGB1 inhibitors, TRP channel modulators, TSP-1 pathway inhibitors) and non-pharmacological innovations (wearable sensors, chronotherapy). Crucially, caregiver education underpins all prevention levels, addressing high rates of parental anxiety (58.2%). This integrated framework guides clinical practice toward more individualized, risk-based management.
Breast cancer (BC) management has transitioned from histological classification to molecular subtyping, yet therapeutic resistance and intratumor heterogeneity remain critical clinical challenges. This review examines the emerging paradigm shift toward integrating mitochondrial metabolism into the precision medicine framework. We detail the complex mitonuclear crosstalk where nuclear genetic alterations, such as Breast Cancer 1 (BRCA1) deficiency and TP53 mutations, fundamentally reprogram mitochondrial bioenergetics. Specifically, the loss of BRCA1 function triggers a systemic NAD+ depletion trap through PARP1 hyperactivation, while oncogenic drivers like MYC coordinate with PGC1α to enhance mitochondrial biogenesis for metastatic survival. We evaluate the diagnostic potential of mitochondrial DNA heteroplasmy and machine learning derived metabolic gene signatures as high performance biomarkers for patient stratification and the detection of minimal residual disease via liquid biopsy. Furthermore, we analyze current clinical efforts to target mitochondrial vulnerabilities, including respiratory chain inhibitors like metformin and BH3 mimetics, while highlighting the significant challenges posed by metabolic plasticity and nutrient competition in the tumor microenvironment. The analysis of clinical trial data, such as the MA.32 study, suggests that metabolic interventions require precise patient selection based on specific metabolic phenotypes rather than broad application. Looking forward, the integration of genome scale metabolic models and artificial intelligence (AI) offers a transformative pathway to simulate patient specific metabolic fluxes and identify novel synthetic lethal targets. By bridging the gap between nuclear genomic drivers and dynamic mitochondrial adaptations, this review aims to provide a preliminary framework for the exploration of metabolic-genomic precision oncology in BC.
Background: Bladder cancer (BLCA) exhibits marked heterogeneity, and current classifiers provide limited guidance for prognosis or treatment. Because epigenetic reprogramming and metabolic rewiring jointly shape BLCA biology, we sought to identify epigenomically informed biomarkers with functional relevance. Methods: Epigenome (genome-wide promoter DNA methylation) and matched transcriptome (RNA sequencing) profiles from tumor and adjacent normal samples were integrated to identify genes with concordant differential methylation and expression patterns. A survival-oriented machine learning framework distilled these candidates into a 25-gene signature. The prognostic performance was evaluated in 4 independent BLCA cohorts. Multilayer characterization included the computational inference of tumor-infiltrating immune cells and in silico drug sensitivity prediction. The functional relevance of key lipid metabolic hub genes was confirmed by pharmacological inhibition in BLCA cell line models, followed by colony formation and migration assays. Results: The signature, enriched for cell cycle regulation and lipid metabolism, stratified patients into high- and low-risk groups across the discovery and 4 validation datasets. The prognostic value remained independent of age, pathological stage, and common genomic alterations. Low-risk tumors exhibited computationally inferred immune-inflamed phenotypes, whereas high-risk tumors exhibited lower immune engagement and lower half-maximal inhibitory concentration values for several drugs. Network analysis identified fatty acid synthase and stearoyl-coenzyme A desaturase as central nodes; their inhibition reduced BLCA cell proliferation and migration, supporting pathway-level functional relevance. Conclusion: By integrating epigenomic and transcriptomic layers with machine learning, we delineated a lipid-centric 25-gene signature that delivers stage-independent prognostication, illuminates tumor-immune interactions, and nominates actionable therapeutic targets. This experimentally vetted multi-omics framework advances precision oncology for BLCA.
Male victims of rape face significant barriers when reporting to the South African Police Service (SAPS), where hegemonic masculinity and heteronormative institutional cultures render male victimhood socially unintelligible. This study examines how police perceptions and institutional practices produce epistemic and secondary victimization for male rape victims. A qualitative design using in-depth semi-structured interviews was employed. Fourteen SAPS officers in Johannesburg were recruited via purposive and snowball sampling. Data were analyzed using thematic content analysis following Braun and Clarke's six-phase framework, within an interpretive-constructivist epistemology, an intersectional theoretical framework, and Connell's hegemonic masculinity theory. Key themes emerged: (1) internalized rape myths and stigma as barriers to reporting male rape; (2) heteronormativity, homophobia and policing of male victimhood homophobia and the role of heteronormativity and homophobia in policing male victimhood. The section also addresses secondary and epistemic victimization through dismissive and intrusive questioning, and emergent pockets of resistance among officers advocating for more inclusive, victim-centred practices. The findings demonstrate that hegemonic masculinity functions not only as a social ideology but as an institutional logic governing recognition, credibility, and access to justice for male rape victims. Gay and gender-nonconforming individuals face compounded stigma. Structural interventions, including gender-sensitive training and institutional reform, are needed to address the systemic marginalization of male rape victims within South African policing.
It is univocally anticipated that in a theory of quantum gravity, there exist quantum superpositions of semiclassical states of spacetime geometry. Such states could arise, for example, from a source mass in a superposition of spatial configurations. In this paper, we introduce a framework for describing such "quantum superpositions of spacetime states." We introduce the notion of the relativity of spacetime superpositions, demonstrating that for states in which the superposed amplitudes differ by a coordinate transformation, it is always possible to re-express the scenario in terms of dynamics on a single, fixed background. Our result unveils an inherent ambiguity in labelling such superpositions as genuinely quantum-gravitational, which has been done extensively in the literature, most notably with reference to recent proposals to test gravitationally-induced entanglement. We apply our framework to the above-mentioned scenarios, looking at gravitationally-induced entanglement, the problem of decoherence of gravitational sources, and clarifying commonly overlooked assumptions. In the context of decoherence of gravitational sources, our result implies that the resulting decoherence is not fundamental, but depends on the existence of external systems that define a relative set of coordinates through which the notion of spatial superposition obtains physical meaning.
Sirtuin-1 (Sirt1) is a key NAD+-dependent deacylase regulating metabolism, stress responses, genome stability, and aging. Although well-characterized biochemically and structurally, its substrate selectivity remains unclear: in vitro, Sirt1 appears promiscuous, while in vivo it activates particular processes in response to different stimuli. Emerging evidence indicates that selectivity arises from multiple regulatory layers beyond the catalytic site. Here we review how post-translational modifications (PTMs) ‒ including phosphorylation, acetylation, and glycosylation ‒ modulate activity, localization, and substrate affinity. For instance, phosphorylation at S27/T530 (by JNK1) or S682 (by HIPK2) affects nuclear translocation, substrate targeting, or complex formation with cofactors such as AROS and DBC1. Protein-protein interactions, for example with DBC1, PACS2, and transcription factors, further direct Sirt1 to specific substrates or compartments, functioning as allosteric regulators. Spatial compartmentalization, including nucleocytoplasmic shuttling and localization to promyelocytic leukemia nuclear bodies (PML-NBs), integrates Sirt1 into defined signaling contexts. Moreover, liquid-liquid phase separation (LLPS) may concentrate Sirt1 and substrates within condensates, enhancing its selectivity. Overall, Sirt1 specificity emerges from PTMs, interactions, localization, and phase behavior ‒ offering a framework for developing selective modulators in metabolic and age-related diseases.
Ongoing improvement and evaluation of clinical care are essential to maintaining high standards. The Accreditation Council for Graduate Medical Education (ACGME) requires all accredited family medicine programs to provide quality improvement (QI) education. Given competing educational demands, residency programs must adopt innovative approaches to teaching QI. This article describes an individualized approach to QI education that we implemented in our family medicine residency program and the outcome of its evaluation. Guided by a logic model and evaluated using the RE-AIM (Reach, Effectiveness, Adoption, Implementation, and Maintenance) framework, this quasi-experimental 1-group pre-test-post-test study (July 2022-June 2023) involved all second-year family medicine residents during a protected QI month. Residents participated in a 1-on-1 session with a QI expert, completed a 10-item baseline knowledge survey, received 4 weekly mentoring meetings to develop a QI charter to address resident-selected quality gap, and completed an online QI module. Knowledge was reassessed at the month's end, and an end-of-year survey evaluated perceptions and sustainability. The program achieved 100% reach with the participation of all 12 residents. Knowledge scores improved from 6.25 (±2.2) to 9.0 (±0.95) out of 10 (P < .001). Adoption was high, with all residents completing the module and a QI charter; implementation fidelity was 100%. Ten residents (83%) completed the end-of-year survey, unanimously reporting improved understanding of QI and confidence to lead future projects. An individualized mentoring approach to QI education was feasible and effective, enhancing resident knowledge and readiness to design targeted improvement initiatives.
Smart wearable biosensors represent a significant paradigm shift from one-time sample analysis to real-time biochemical monitoring at the body interface. Besides the flexible design of the device or wireless readout, their clinical utility will also require the reliability of the entire sensing pathway under real physiological conditions. This pathway involves biofluid access to clinical interpretation. Despite rapid progress, many wearable biosensor platforms remain limited by weak biofluid-blood correlation, receptor degradation, biofouling, motion artefacts, sensor drift and insufficient patient-level validation. Thus, a chemistry-to-clinics approach is crucial to assess the analytical reliability and translational readiness of recognition elements, sensing materials, and engineered biointerfaces. Enzymes, antibodies, aptamers, nucleic-acid systems, molecularly imprinted polymers, and nanozymes are discussed within the context of selectivity, stability, antifouling behaviour and suitability for continuous monitoring of sweat, interstitial fluid, tears, wound exudate and breath condensate. The functionality of carbon nanostructures, metal-based nanomaterials, hydrogels, MXenes, metal-organic frameworks and self-powered interfaces are evaluated in terms of their applications in amplification, mechanical conformity, biofluid handling and signal stability. Artificial intelligence is positioned as a support layer for signal correction, calibration, classification, multimodal fusion and predictive interpretation, rather than as a substitute for robust sensing chemistry. This review provides a critical chemistry-to-clinical perspective on smart wearable biosensors and outlines the validation, manufacturing, cybersecurity, post-market surveillance and benchmarking requirements needed for their translation into reliable diagnostic and therapeutic-monitoring technologies.
Point-of-care ultrasound (POCUS) has become an increasingly important component of perioperative medicine, supporting real-time assessment of cardiovascular function, pulmonary pathology, gastric content, airway anatomy, vascular access, regional anesthesia, and perioperative complications. Perioperative POCUS is relevant to anesthesiologists and to the broader perioperative team, including critical care clinicians, pain physicians, emergency clinicians, surgeons, and ultrasound educators who participate in perioperative diagnosis, procedures, resuscitation, and postoperative care. Despite its growing clinical relevance, POCUS education in anesthesiology and perioperative medicine remains heterogeneous, with variable curricular scope, inconsistent assessment strategies, and persistent barriers related to faculty expertise, protected training time, equipment access, and competency verification. This narrative review used a transparent, targeted search strategy across biomedical and education databases, with adapted PRISMA reporting elements used to describe sources, search concepts, and selection boundaries while preserving the interpretive purpose of a narrative synthesis. Simulation-based education offers a practical and ethically sound approach for teaching POCUS before learners perform examinations in high-stakes perioperative environments. This review synthesizes educational theory, perioperative POCUS competency frameworks, empirical ultrasound simulation evidence, cross-disciplinary procedural simulation literature, and assessment scholarship to propose an integrated training model for perioperative POCUS. We organize simulation-based POCUS education into six complementary models: low-fidelity task training, standardized-patient and peer scanning, high-fidelity physiologic simulation, hybrid operating-room crisis simulation, virtual and augmented reality platforms, and longitudinal simulation-based mastery learning. Effective perioperative POCUS education should progress from cognitive preparation and deliberate image acquisition practice to interpretation, clinical integration, documentation, and team-based decision-making. Assessment should combine image-quality rubrics, interpretation tests, entrustable professional activities, objective structured clinical examinations, image portfolios, and longitudinal workplace-based feedback. Because the evidence base differs across simulation modalities and assessment tools, programs should distinguish empirically tested instruments from locally adapted or theoretical tools and should validate competency thresholds before using them for high-stakes credentialing. Key research priorities include multicenter validation of competency thresholds, comparative effectiveness studies of simulation modalities, cost-effectiveness analyses, faculty development models, responsible integration of artificial intelligence, and studies linking simulation-based training to clinical performance and patient outcomes. Simulation is not a substitute for supervised clinical scanning; rather, it is a bridge between theoretical knowledge and safe, competent bedside practice.
Acupuncture needles are widely used to treat various medical conditions, but can occasionally lead to serious adverse events. The therapeutic index (TI), originally developed in pharmacology to quantify the safety margin between effective and toxic doses, provides a valuable potential framework for evaluating anatomical safety in acupuncture. We applied the TI concept to two commonly used acupoints-GB21 and ST36-by quantifying the TI value, defined as the ratio of the median hazardous depth (HD₅₀) to the median effective depth (ED₅₀), based on ultrasound-guided measurement and de-qi responses. Using ultrasound-guided measurements in 39 participants, we calculated the TI for each point and constructed cumulative distribution functions to visualize the therapeutic window. GB21 demonstrated a TI of 1.54, indicating a relatively wide safety margin, whereas ST36 had a TI of 1.09, reflecting a narrow and potentially risk-prone margin. These findings emphasize the impact of anatomical variability and highlight the need for personalized depth control in acupuncture practice. Our study provides preliminary evidence that integrating the TI concept into acupuncture safety assessment may support more individualized, data-driven needling strategies. These findings should be interpreted as exploratory and require confirmation in larger, demographically diverse populations and at additional acupoints before being generalized to routine clinical practice.
HER2-positive breast cancer accounts for 15-20% of all breast cancer cases. Although the development of monoclonal antibodies (e.g., trastuzumab, pertuzumab), tyrosine kinase inhibitors (e.g., lapatinib, pyrotinib), and antibody-drug conjugates (e.g., T-DM1, trastuzumab deruxtecan) has greatly improved patient prognosis, primary or acquired resistance to anti-HER2 therapy remains a major clinical challenge, leading to treatment failure and disease progression. Recent research has elucidated diverse resistance mechanisms, including HER2 signaling pathway aberrations (such as receptor mutations, alternative splicing, and bypass activation), tumor microenvironment remodeling (involving immunosuppressive cells, metabolic reprogramming, and immune checkpoint molecules), and ADC-specific resistance (impaired internalization, lysosomal dysfunction, payload efflux, and ferroptosis blockade). However, existing reviews primarily focus on trastuzumab and classical signaling pathways, with insufficient integration of ADC-specific mechanisms or microenvironmental immune evasion. Furthermore, the translation of mechanistic discoveries into clinical strategies remains weak, and a systematic summary of validated biomarkers (e.g., PIK3CA mutations, PTEN loss, p95HER2, ADAR1, HLA-G) and related clinical trials is lacking. The purpose of this review is threefold: (1) to systematically integrate recent advances in anti-HER2 resistance mechanisms from three perspectives-HER2 signaling abnormalities, tumor microenvironment remodeling, and ADC-specific barriers; (2) to provide an evidence-based framework for target prioritization by categorizing mechanisms according to their validation stage (clinically validated, substantial in vivo evidence, or in vitro studies only); and (3) to summarize current biomarker-driven clinical trials and emerging therapeutic strategies, including combination immunotherapy, CDK4/6 inhibitors, PI3K PROTACs, and cold atmospheric plasma. Ultimately, this review aims to bridge the gap between basic research and clinical practice, offering practical guidance for overcoming anti-HER2 resistance through precision combination strategies in HER2-positive breast cancer.