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PubMed2026

Patient and Public Involvement and Engagement in Pediatric Health Research: A Systematic Review.

BACKGROUND: Patient and public involvement and engagement (PPIE) can increase the relevance and efficiency of research projects. An overview of PPIE approaches and implementation in pediatric research studies is needed to facilitate learning from others' experiences. OBJECTIVE: We aimed to systematically review practices in PPIE across all pediatric health research disciplines regarding characteristics and recruitment of PPIE participants, timepoints and methods used for PPIE, levels of involvement, benefits and barriers of PPIE. SEARCH STRATEGY: We searched Pubmed, EMBASE, Cochrane and PsycInfo using a comprehensive set of terms based on the concepts 'Patient and Public Involvement,' 'Health Research' and 'Pediatrics.' INCLUSION CRITERIA: We included original research articles describing PPIE implementation in pediatric health research published in English or German between 01/2003-10/2024. DATA EXTRACTION AND SYNTHESIS: Data was extracted using predefined categories and synthesized by narrative summary and thematic synthesis. PPIE reporting quality was assessed using the GRIPP2 short form checklist. MAIN RESULTS: Out of 1910 references, we included 37 original research articles, representing 35 studies. PPIE participants were mostly children, adolescents or caregivers involved in all research stages, especially in study design (89%) and recruitment (51%). Key positive impacts of PPIE on research included enhanced recruitment and retention rates and personal benefits for PPIE participants. Barriers to PPIE were financial and time resources required and challenges in recruiting representative PPIE participants. The level of involvement and PPIE reporting quality varied highly between studies. DISCUSSION: Common benefits and barriers of PPIE exist across pediatric research disciplines. Reporting quality varied highly between studies. CONCLUSIONS: PPIE is valuable in pediatric health research. Adherence to guidelines for conducting and reporting PPIE is important to enhance mutual learning. PATIENT OR PUBLIC CONTRIBUTION: PPIE input contributed to the understandability of the lay summary. The findings of this review, together with parent and public input, will inform guidelines for future PPIE activities at the authors' institutions.

Humans↗
PubMed2026

Data-centric, robust, and explainable multimodal deep learning for clinical decision support: A systematic review.

PURPOSE: Multimodal deep learning is increasingly proposed for clinical decision support (CDS) under a "data-centric" framing that prioritizes label quality, missing-modality robustness, distribution shift, calibration, and explainability. Prior reviews have examined multimodal medical AI, CDS, and data-centric methods separately, but none address their intersection. We mapped the modalities, fusion strategies, and data-centric and explainability techniques used in this recent literature, quantified how often each is implemented rather than merely mentioned, assessed deployment-relevant evidence (external validation, clinical-outcome measurement, equity), and formally appraised study-level risk of bias. METHODS: Following the PRISMA 2020 statement (PROSPERO CRD420261427815; registered retrospectively), we screened 150 records and included primary, clinical, multimodal studies that applied machine or deep learning to a decision-support task and reported at least one quantitative result. Two reviewers screened and extracted data with consensus adjudication. Each study was coded against pre-specified operational definitions, separating implemented or empirically evaluated techniques from those only mentioned. Study-level risk of bias was assessed with PROBAST + AI. Synthesis was narrative. RESULTS: Thirty-one studies met inclusion; 30 (97%) were published between 2024 and 2026, with a median of three modalities (range 2-6), most commonly structured EHR (71%) and imaging (39%). Data-centric techniques were frequently reported (74-84% across label-noise, distribution-shift, calibration, missing-modality and class-imbalance handling; equity 61%). However, external validation was reported in only 4/31 studies (13%), a clinical or provider outcome in 3/31 (10%), and no study reported routine deployment. Overall risk of bias was high in 27/31 studies (87%), driven by the analysis domain. CONCLUSION: Within this recent, self-selected slice of the field, technical robustness and explainability techniques are widely reported but rarely validated out-of-distribution or against clinical outcomes, and the underlying evidence is at high risk of bias. Progress requires external multi-site validation, clinical-outcome measurement, formal bias appraisal, and adherence to AI reporting standards (e.g., TRIPOD + AI) before deployment can be justified.

Deep Learning↗
PubMed2026

Molecular Landscape and Advanced Diagnostic Technologies for BRAF Mutations in Cancer: From Quantitative PCR and ddPCR to CRISPR-Based Platforms.

BRAF mutations are key oncogenic alterations across multiple malignancies, including melanoma, thyroid carcinoma, colorectal cancer, non-small cell lung cancer, glioma, and hairy cell leukemia. The most prevalent variant, BRAF-V600E, induces constitutive activation of the MAPK signaling pathway, promoting tumor progression and influencing therapeutic responsiveness. Accurate detection of BRAF alterations is therefore essential for molecular classification, prognostic assessment, treatment selection, and resistance surveillance. This review summarizes the molecular heterogeneity of BRAF mutations and critically evaluates current diagnostic methodologies. Conventional approaches such as allele-specific PCR and Sanger sequencing are compared with advanced quantitative platforms, including high-resolution melting analysis, droplet digital PCR, and next-generation sequencing, with emphasis on analytical sensitivity, mutation coverage, and clinical applicability. Emerging technologies such as CRISPR-based assays, rolling circle amplification systems, and nanoparticle-based biosensors and point-of-care diagnostic platforms are also discussed for their potential to enhance ultra-sensitive detection, particularly in liquid biopsy settings. These emerging tools are highlighted for their potential to enable ultra-sensitive, rapid, and decentralized mutation detection, particularly in liquid biopsy settings. Key challenges, including intratumoral heterogeneity, low allele-frequency variants, FFPE-associated artifacts, and clonal evolution under therapeutic pressure, are examined within a translational framework. In addition, we examine critical barriers to clinical implementation, including standardization, cost, and global accessibility of molecular diagnostics, and outline potential solutions through scalable technologies and decentralized testing strategies. We propose that optimal BRAF testing requires a mutation subclass-informed and clinically integrated strategy combining comprehensive baseline profiling with longitudinal molecular monitoring. Future diagnostic paradigms will likely integrate multi-omics data and artificial intelligence (AI)-assisted interpretation to refine precision oncology implementation. Looking forward, we propose that optimal BRAF testing will require integration of multi-omics profiling with AI-assisted interpretation, enabling automated variant classification, real-time clinical decision support, and improved prediction of therapeutic response and resistance.

Humans↗
PubMed2026

Process evaluation of a nurse-led transitional care model (Cardiolotse) within a randomized controlled trial aiming to improve care coordination for patients with cardiovascular diseases in Germany.

BACKGROUND: Patients with higher age suffering from cardiovascular disease discharged from hospital are at greater risk of readmission within 30 days. We evaluated an innovative care program providing post-discharge support and helping patients to navigate through the healthcare system. This paper reports the findings of the process evaluation of the randomized controlled trial Cardiolotse, a nurse-led transitional care model improving care coordination for patients with cardiovascular diseases in Germany. METHODS: A process evaluation, following the guidelines of the Medical Research Council (MRC) Framework, was performed. Semi-structured interviews with all relevant target groups were conducted to gain more insight about implementation processes. Questionnaires and medical records were used to explore mechanisms of impact and understand how change was produced in the intervention. Qualitative data were analysed using content analysis with deductive and inductive categories. Descriptive statistics and subgroup analyses were utilized to explore quantitative data. RESULTS: Overall, the designed training programme was perceived positively by the study nurses, so called Cardiolotsen (CLs). Patients receiving support by the CLs reported positive satisfaction ratings. Interactions between CLs and patients were reported as trustworthy and reliable. A total of approximately 12,500 contacts were made over the course of the intervention. However, changes in satisfaction scores between intervention and control groups in terms of medical treatment or the interaction between medical health providers involved in the treatment could not be determined. Furthermore, data suggested reach issues with respect to office-based physicians, as regular CL contact could not be achieved with 90% of the participating general practitioners and cardiologists. CONCLUSIONS: The CLs served as an important source of support for the participating patients throughout the intervention. At regular intervals, they checked a patient's health status and their adherence to therapies after discharge. However, the process evaluation identified cross-sectoral communication and information exchange between CLs and office-based physicians as an implementation challenge. TRIAL REGISTRATION: The study was retrospectively registered at German Clinical Trial Register, http://www.drks.de/DRKS00020424 (Trial Registration Number DRKS00020424) on 18 June 2020.

Humans↗
PubMed2026

Artificial intelligence-supported double reading in European population breast cancer screening: A systematic review and meta-analysis of prospective programs.

BACKGROUND: Most European population mammography screening programs rely on double reading with arbitration, a model that delivers mortality benefit but is increasingly challenged by radiologist workload, variable specificity, and interval cancers. Artificial intelligence (AI) is being evaluated to support or optimize these established European screening pathways. PURPOSE: To synthesize prospective or program-embedded evaluations of AI conducted within European-style population screening programs and to estimate exploratory program-level absolute risk differences (RDs) per 1000 examinations for cancer detection rate (CDR) and recall. MATERIALS AND METHODS: We performed a prespecified, focused evidence synthesis of three large studies embedded within routine population screening programs operating under European-relevant workflows: MASAI (randomized AI-supported risk triage within a national program), ScreenTrustCAD (prospective paired-reader evaluation with AI as an independent reader in a double-reading framework), and PRAIM (nationwide decision-referral implementation). Outcomes were harmonized as AI-control RDs per 1000 examinations. Random-effects pooling used Hartung-Knapp-Sidik-Jonkman models. For the paired-reader design, sensitivity analyses applied a Kish effective sample-size approach across plausible within-examination correlations (ρ = 0.3-0.8). Positive predictive value (PPV) and workflow/time outcomes were summarized descriptively. RESULTS: Across 597,419 examinations, the pooled CDR RD was +0.9 per 1000 (95% CI -0.0 to +1.8; I2 ≈ 12%), consistent with a modest directional increase with borderline statistical uncertainty. The pooled recall RD was -0.6 per 1000 (95% CI -3.1 to +2.1; I2 ≈ 41-43%), indicating no consistent recall increase across screening programs. Where reported, PPV was higher with AI-supported screening. Efficiency signals included 44.3% fewer total readings in MASAI and shorter reading times for AI-normal examinations in PRAIM; in PRAIM, a program-level safety-net mechanism recovered 204 cancers that would otherwise have been missed. CONCLUSION: In European population screening programs characterized by double reading and arbitration, prospective program-embedded evidence suggests that AI integration may yield a small absolute increase in cancer detection (≈1/1000) without a consistent increase in recall, alongside improved PPV and efficiency signals. These findings suggestAI primarily as a complementary reader within European screening workflows, with implementation requiring explicit quality assurance and monitoring of interval cancers and stage distribution.

Humans↗
PubMed2026

Changes in heroin-related ambulance attendances following the introduction of a medically supervised injecting room in Victoria, Australia.

BACKGROUND: Injecting drug use contributes significantly to morbidity, mortality and broader social harms globally. Supervised Injecting Facilities (SIFs) are harm reduction interventions that reduce overdose risk and facilitate access to health services for marginalised individuals. While international evidence supports the effectiveness of SIFs, Australian population-level surveillance data quantifying their impact on emergency medical service utilisation remain limited. METHODS: Using data from the National Ambulance Surveillance System, we conducted a retrospective, interrupted time series analysis of heroin-related ambulance attendances within the local catchment of the Medically Supervised Injecting Room (MSIR) between January 2015 and December 2023. Supplementary analysis included comparisons with central Melbourne suburbs and the broader state of Victoria. Key intervention timepoints, including the opening of the MSIR on 30 June 2018, expansion of its operating hours in July 2019, and the COVID-19 pandemic from April 2020 to October 2021, were examined to assess changes in heroin-related attendances over time. Segmented regression models were used to assess changes in heroin-related ambulance attendance trends over time. RESULTS: At the time the MSIR opened, the model-predicted heroin-related ambulance attendance rate within the MSIR catchment was 123 per 100,000 population per month, equivalent to approximately 48 heroin-related ambulance attendances per month. Prior to implementation, the attendance rate was increasing by an estimated 0.74 per 100,000 population per month. Following the opening of the MSIR, the previously increasing trajectory reversed, with ambulance attendance rates declining by approximately 2.3 per 100,000 population per month relative to the pre-intervention trend. By the end of the study period (December 2023), the predicted monthly heroin-related ambulance attendance rate had declined to 36 per 100,000 population (approximately 14 attendances per month), representing an overall reduction of 70.7% from the time of MSIR implementation. These reductions persisted throughout the COVID-19 lockdown period and were sustained after restrictions lifted. Supplementary analysis showed no comparable reductions in the central Melbourne region or the remainder of Victoria. CONCLUSIONS: The introduction of the MSIR in Richmond was associated with a sustained reduction in heroin-related ambulance attendances within its catchment area. These findings provide strong population-level evidence that SIFs reduce acute heroin-related harms requiring emergency ambulance response, reinforcing their role as an effective harm reduction strategy within the Australian context.

Humans↗
PubMed2026

Leveraging traveller genomics for LMIC diarrhoeal disease management.

Diarrhoeal pathogens impose a substantial global health burden, disproportionately affecting low- and middle-income countries (LMICs). However, in these settings, health-seeking behaviours, suboptimal microbiological capacity, and challenges in establishing genomics capacity constrain effective surveillance, including surveillance of antimicrobial resistance (AMR). In contrast, high-income countries routinely generate and share large volumes of diarrhoeal pathogen genomes through established systems, with a significant proportion originating from travellers returning from LMICs. These data reveal strong geographical structuring of lineages and clinically relevant AMR patterns, demonstrating untapped potential to support improvements in geographically granulated surveillance to support antimicrobial treatment recommendations. In this opinion article, we outline the potential to integrate traveller-derived microbial genomic data into LMIC public health decision-making and highlight the scientific, ethical, practical, and governance considerations for implementation.

antimicrobial resistance↗
PubMed2026

External ventricular drain safety campaign and opportunities for global neuroanesthesiology quality and safety.

PURPOSE OF REVIEW: This review describes the conceptualization and implementation of the External Ventricular Drain (EVD) Safety Campaign, a global patient safety initiative by the Society for Neuroscience in Anesthesiology and Critical Care. It summarizes recent literature on EVD insertion and maintenance, highlights opportunities to advance quality and safety in neuroanesthesiology, and outlines priorities and a framework for future work. RECENT FINDINGS: The Society for Neuroscience in Anesthesiology and Critical Care launched a global initiative to improve EVD management. EVD insertion and maintenance remain key areas of ongoing research and quality improvement, particularly in reducing complications. SUMMARY: The EVD Safety Campaign provides a structured framework to improve care delivery and patient outcomes worldwide. Continued focus on standardization, education, and complication reduction, especially infection prevention, will be essential to advancing the field.

Humans↗
PubMed2026

Perioperative Depression and Anxiety Care in Older Patients: A Randomized Clinical Trial.

IMPORTANCE: Depression and anxiety are common among older adults undergoing surgery and are associated with adverse postoperative outcomes. However, effective tailored perioperative mental health interventions are lacking. OBJECTIVE: To evaluate a perioperative intervention to optimize mental health. DESIGN, SETTING, AND PARTICIPANTS: A single-blind, hybrid, type 1, effectiveness-implementation randomized clinical trial was conducted (November 1, 2022, to March 31, 2025), with 3-month postoperative follow-up, at a US academic and community practice hospital network. Participants were 60 years or older; scheduled for cardiac, oncologic, or orthopedic surgery; and had clinically meaningful symptoms of depression and/or anxiety based on the Patient Health Questionnaire-Anxiety and Depressive Symptom (PHQ-ADS) scale. A total of 3159 patients were screened for eligibility, with 1518 ineligible, 1079 declining participation, and 236 excluded for other reasons. A total of 326 patients were enrolled and randomized (1:1), with 20 excluded after surgery cancelation. INTERVENTION: Participants were assigned to receive a perioperative intervention combining psychological management and pharmacologic optimization or enhanced usual care (materials for self-managing symptoms). MAIN OUTCOMES AND MEASURES: The primary outcome was change in PHQ-ADS score from baseline to 3 months after surgery. Other outcomes included persistent postsurgical pain, delirium, falls, quality of life, patient satisfaction, length of stay, and rehospitalizations. Implementability was evaluated through semistructured interviews and reach, acceptability, feasibility, appropriateness, and fidelity measures. RESULTS: A total of 306 older adults were included in analysis (mean [SD] age, 68.5 [6.1] years; 209 [68.3%] female; 153 randomized to intervention and 153 randomized to enhanced usual care): 102 cardiac, 100 oncologic, and 104 orthopedic patients. Participants' mean (SD) baseline PHQ-ADS score was 18.5 (7.4). At 3 months, there was a significant decrease in PHQ-ADS scores in the intervention group compared with the enhanced usual care group (mean difference, 2.20; 95% CI, 0.16-4.24; P = .03). Effects varied by surgical subgroups (oncologic patients: mean difference, 4.93; 95% CI, 1.51-8.36; P = .005; cardiac patients: mean difference, 2.68; 95% CI, -0.98 to 6.35; P = .15; and orthopedic patients: mean difference, -1.11; 95% CI, -4.62 to 2.40; P = .54). Patients and interventionists perceived the intervention as appropriate, with high-fidelity delivery and broad reach across the target population. CONCLUSIONS AND RELEVANCE: In this randomized clinical trial, psychological management and pharmacologic optimization reduced anxiety and depression in older adults undergoing surgery. Future studies should assess reproducibility and determine which patients benefit most. TRIAL REGISTRATION: ClinicalTrials.gov Identifiers: NCT05575128, NCT05685511, and NCT05697835.

Humans↗
PubMed2026

Cost-Effectiveness of Electronic Patient-Reported Outcome Measure Interventions in Cancer: Systematic Review and Parameter Extraction for Economic Modeling.

BACKGROUND: Complex digital interventions that integrate electronic patient-reported outcome measures (ePROM) into clinical practice in cancer have the potential to improve quality of life, increase survival, and reduce health resource use and costs. Such systems can help patients with cancer self-manage chemotherapy symptoms, reduce clinicians' workloads through automated decision support, and resolve problems earlier. However, more research on the cost-effectiveness of ePROM monitoring is needed. OBJECTIVE: This paper comprises two complementary components: (1) a systematic literature review summarizing and evaluating the quantitative and qualitative evidence related to the cost-effectiveness of ePROM monitoring and (2) a health economic model parameter extraction. We also conducted supplementary targeted searches and scoping to provide context to our findings. METHODS: We searched Ovid (including MEDLINE and Embase), Scopus, and the International Health Technology Assessment Database for original English-language papers published on or before March 2025 using search strings that combined terms related to ePROMs, health economics, and cancer/oncology. We included papers reporting health economic-related outcomes for ePROM interventions designed for adult cancer populations and excluded screening tools and conference abstracts. RESULTS: We included 34 publications from 27 unique studies and identified and analyzed 26 ePROM-integrated interventions within these. Most (23/26) of the included interventions explicitly described some form of alert handling and automated decision support based on remote ePROM monitoring. Of the 34 publications, 5 presented full cost-effectiveness analysis results, of which 3 were highly uncertain and lacked clear differences in costs and health outcomes between ePROMs and standard care; conversely, 2 presented strong evidence of cost-effectiveness due to quality-of-life improvements, reduced hospitalizations, and potentially more autonomy in health-related travel (eg, ePROM-monitored patients can drive or walk to the hospital instead of using taxis or ambulances). A further 5 publications reported partial health economic results (eg, cost-consequence and budget impact), of which 1 detected no difference in strategies; in contrast, 4 reported lower health resource use and costs of ePROMs, mainly due to hospitalization reductions. Overall, 12 of the 27 studies included a qualitative component but mostly focused on user experience and design-related themes; only 2 of these addressed economic-specific themes (eg, changes in workflow and resource use due to ePROM implementation and integration), indicating some potential for time saving due to ePROM monitoring. CONCLUSIONS: Some ePROM-integrated interventions demonstrated cost-effectiveness in cancer care, but the evidence base remains limited. Where evidence does exist, cost-effectiveness appears driven by reduced hospitalization and improved quality of life. Qualitative research within the included studies rarely addressed economic questions. We provide a detailed parameter extraction for use in future economic modeling and recommend research priorities, including quantitative mapping of ePROM symptom data onto health resource use patterns, and qualitative work exploring how ePROM implementation affects clinical workloads and patient-perspective costs.

Humans↗
PubMed2026

Standardized visual overlays enhance laparoscopic instruction: A mixed-methods evaluation.

Effective communication during laparoscopic procedures is frequently undermined by spatial disorientation and inconsistent terminology between instructors and trainees. This study examined whether standardized visual overlays on endoscopic monitors could enhance communication and learning. We conducted a three-phase mixed-methods study: qualitative observation of 20 laparoscopic teaching cases; a randomized trial of 63 second-year medical students assigned to control, clock, or alphanumeric grid (AG) overlays during three trials of a standardized transfer task; and intraoperative implementation in 44 cases (30 AG, 14 clock) with post-case surveys and qualitative feedback. In simulation, the clock overlay produced the fastest completion times, whereas the AG yielded the lowest error scores, and both overlays outperformed the control. Intraoperatively, the AG was rated higher than the clock for communication clarity, spatial orientation, perceived operative efficiency, and trainee confidence. Standardized visual overlays, particularly the AG, appear to support intraoperative teaching by providing a shared spatial frame of reference.

Laparoscopy↗
PubMed2026

Multi‑omics approaches to decipher the molecular mechanisms of exercise‑mediated bone protection: From mechanistic insights to personalized exercise prescription (Review).

The global burden of bone metabolic disorders necessitates a shift from generic exercise recommendations toward personalized prescription strategies. Exercise confers skeletal protection through mechanotransduction, yet the underlying molecular networks remain incompletely understood. Multi‑omics technologies, including transcriptomics, proteomics, metabolomics and single‑cell spatial approaches, have revolutionized the capacity to decode exercise‑mediated bone adaptation at the systems level. The present review synthesizes current single‑omics landscapes and integrative multi‑omics analyses that elucidate the core regulatory networks, mechanobiological coupling mechanisms and multiorgan crosstalk that are implicated in the bone response to mechanical loading. Translational applications across clinical scenarios such as osteoporosis, osteoarthritis and disuse bone loss are evaluated, and the technical, analytical and translational challenges limiting clinical implementation are addressed. Finally, the present review provides a framework for translating multi‑omics molecular signatures into personalized exercise prescriptions for optimized skeletal health.

Humans↗
PubMed2026

Using the OPTIMAL Theory to Optimize Aerodynamics in Respiratory Training for Healthy Adults and Individuals With Parkinson's Disease.

BACKGROUND: The OPTIMAL (Optimizing Performance Through Intrinsic Motivation and Attention for Learning) theory is a motor learning framework proposing that optimizing intrinsic motivation enhances motor performance and learning. The theory identifies three key components-Enhanced Expectancies (EE), Autonomy Support (AS) and External Focus of Attention (EF)-which facilitate more efficient, goal-directed movement. These components have been shown to improve motor outcomes in limb-based tasks; however, their application to respiratory training, particularly in clinical contexts such as voice and swallowing therapy in patients with Parkinson's disease (pwPD), has not yet been systematically explored. AIMS: This study aimed to investigate whether implementing OPTIMAL theory strategies during a respiratory muscle strength training (RMST) task improves immediate respiratory motor performance in healthy adults and pwPD. Additionally, we aimed to examine the effects of these strategies on motivation and cognitive engagement. METHODS: This quasi-randomized, single-session trial included 47 participants: Healthy CONTROL (n = 17), Healthy OPTIMAL (n = 16) and PD OPTIMAL (n = 14). Healthy participants were quasi-randomly assigned to either intervention or control conditions, whereas pwPD completed the intervention only. All participants completed a single respiratory session that included baseline, practice and retention phases. Outcome measures included peak expiratory flow, cough peak expiratory flow, cognitive engagement (EEG-based Cognitive Engagement Index) and self-administered motivation questionnaire. OUTCOMES AND RESULTS: Exhalation force improved from baseline to retention in the Healthy OPTIMAL group (baseline: M = 296 L/min; retention: M = 338 L/min; p < 0.001) and the PD OPTIMAL group (baseline: M = 315 L/min; retention: M = 370 L/min; p < 0.0001), but not in the Healthy CONTROL group (p > 0.05). No significant changes in cough strength were observed in any group. No correlations were found between cognitive engagement and exhalation force or motivation scores. However, motivation increased more in the Healthy OPTIMAL group (Questionnaire 1: M = 57.2; Questionnaire 2: M = 60.7) and the PD OPTIMAL group (Questionnaire 1: M = 60.1; Questionnaire 2: M = 62.8) than in the Healthy CONTROL group (Questionnaire 1: M = 61.1; Questionnaire 2: M = 62.5). CONCLUSIONS AND IMPLICATIONS: Implementing the OPTIMAL theory enhances immediate respiratory motor performance in both healthy participants and pwPD. OPTIMAL theory has clinical value in voice and swallowing therapy, although further research is needed to establish long-term efficacy and clinical impact. WHAT THIS PAPER ADDS: What is already known on the subject Motivation is a critical factor in rehabilitation. The OPTIMAL theory has been shown to improve both motivation and motor performance in limb-based tasks. Its impact on respiratory training, however, has not been previously examined. What this paper adds to the existing knowledge This study shows that applying OPTIMAL strategies during a respiratory muscle strength training task significantly improved peak expiratory flow in both healthy adults and people with Parkinson's disease. What are the potential or clinical implications of this work? Integrating the OPTIMAL theory principles into respiratory therapy may enhance motor outcomes, supporting voice, swallowing and cough rehabilitation.

Humans↗
PubMed2026

Mechanisms of Hematopoietic Stem Cell Aging and Emerging Rejuvenation Strategies.

Hematopoietic stem cell (HSCs) aging is a complex biological process driven by both cell-intrinsic alterations and extrinsic cues from the bone marrow niche. Understanding these mechanisms is critical for developing therapies against aging-related hematopoietic disorders. This review synthesizes recent advances in the molecular mechanisms underlying HSCs aging, including microenvironmental aging, genomic instability, epigenetic dysregulation, mitochondrial dysfunction, and aberrant nuclear mechanotransduction. We summarize that the functional decline of HSCs during aging drives a compensatory expansion of the phenotypically defined stem cell pool, leading to an aberrant increase in cell number. We also highlight aging-associated HSCs heterogeneity, including CD150high and P-selectin-positive subsets that enrich for myeloid-biased or functionally compromised HSCs states while emphasizing that surface phenotype alone may not fully indicate functional rejuvenation. Finally, we discuss emerging rejuvenation strategies-including targeting myeloid-biased HSCs, modulating inflammatory pathways, and implementing epigenetic or metabolic interventions-supported by cutting-edge technologies such as single-cell multi-omics, gene editing, and computational modeling. These approaches hold promise for counteracting age-related hematopoietic decline and restoring immune competence.

Humans↗
PubMed2026

A point-of-use SERS assay for rapid detecting difenoconazole and flusilazole residues in fruit juices using Au/COF substrate.

We developed a ready-to-use surface-enhanced Raman scattering (SERS) sensor for rapid, pretreatment-free detection of difenoconazole (DIF) and flusilazole (FLU) in peach and lychee juices. The substrate combines Au nanoparticles (AuNPs) with covalent organic frameworks (COF) and is implemented on a portable 25-well plate, enabling in situ testing. Juices can be directly applied to the SERS-active Au/COF composite, allowing simultaneous adsorption and signal generation. The correlation between SERS intensity and logarithmic concentration yielded R-values between 0.925 and 0.986, meeting the monitoring needs of non-laboratory scenarios. The entire workflow completes within 12&#xa0;min, offering a faster alternative to conventional methods while maintaining high sensitivity and reproducibility. Detection limits reach 0.96-1.22&#xa0;ppb for DIF and FLU, both of which are below the regulatory maximum residue limits. Distinct SERS fingerprints enable reliable discrimination of mixed residues across juice matrices, supporting rapid on-site monitoring and cost-effective pesticide surveillance.

Triazoles↗
PubMed2026

From population to individual: advocating personalised digital tools for heat-health early warning in a changing climate.

Escalating heat extremes under climate change are imposing substantial health burdens, with 2023 and 2024 consecutively breaking global temperature records. Mounting evidence suggests that heatwaves elevate the risks of hospitalisation and mortality across multiple disease categories, including ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and acute kidney injury. Nonetheless, most existing heat-health warning systems remain primarily reliant on population-level predictions, and considering individual differences and disease-specific considerations when defining warning levels would benefit the effectiveness of early prevention for high-risk groups. In this Viewpoint, which is based on the framework of precision public health-delivering the right intervention to the right population at the right time-we propose a framework for personalised digital heat-health early warning tools comprising three dimensions: individualised, risk-stratified prediction models that generate tiered early warnings; personalised health prompts coupled with theory-informed behavioural interventions; and adaptive, equity-oriented alert delivery mechanisms tailored to diverse populations. Such tools have the potential to bridge precision disease prevention and climate adaptation, thereby helping to mitigate heat exposure risks and disease burdens, particularly among high-risk populations. Future implementation research will be essential to address substantial challenges related to feasibility, validation, and equity.

Journal Article↗
PubMed2026

Human-Centered Workspace Optimization: A 2 &#xd7; 2 Factorial Study of Adjustable Furniture and Indoor Environmental Quality.

Small workspaces function as integrated systems, yet ergonomic furniture and indoor environmental conditions are usually evaluated separately. A six-site, assessor-blinded, randomized 2 &#xd7; 2 factorial controlled study was conducted of two multicomponent packages-adjustable furniture and optimized indoor environmental quality (IEQ)-among 240 office workers for four weeks. Each group included 60 participants. Overall comfort in week 4 was highest for both packages (5.62 &#xb1; 0.53 versus 3.99 &#xb1; 0.60 with fixed furniture and basic IEQ). In a site-adjusted factorial model with HC3 robust standard errors, the adjustable-furniture effect was 0.86 points (95% confidence interval [CI], 0.62-1.09), the optimized-IEQ effect was 0.34 points (95% CI, 0.12-0.55), and their interaction was 0.44 points (95% CI, 0.14-0.74). Adjustable furniture improved postural comfort and reduced neck and lower back discomfort; optimized IEQ improved environmental comfort; both packages improved perceived productivity, satisfaction, and fatigue. The task-accuracy interaction did not remain significant after false-discovery-rate adjustment, and exploratory mediation and spline analyses did not support indirect or nonlinear effects. These results support coordinated ergonomic and environmental implementation while preserving distinct outcome pathways.

Interior Design and Furnishings↗
PubMed2026

Effects of intradialytic nutrition on dialysis adequacy and fatigue in hemodialysis patients: a randomized crossover study.

OBJECTIVE: To assess intradialytic nutrition's effects on dialysis adequacy and fatigue in maintenance hemodialysis patients. METHODS: A randomized, two-period, two-sequence, self-controlled crossover trial was conducted in two outpatient hemodialysis centers in T&#xfc;rkiye. Thirty-six patients were randomized; 32 completed both periods. The participants received standardized intradialytic nutrition in one period and no food intake during the control period. Dialysis adequacy was evaluated using the urea reduction ratio and single-pool Kt/V. Intradialytic blood pressure was recorded during dialysis sessions, and fatigue severity was measured using the Piper Fatigue Scale at the end of each period. RESULTS: No significant differences were observed in dialysis adequacy or fatigue scores between the two periods. Intradialytic nutrition was associated with greater reductions in systolic and diastolic blood pressure, particularly during the second hour of dialysis. No clinically relevant adverse events occurred. CONCLUSION: Intradialytic nutrition did not compromise dialysis adequacy or worsen fatigue severity but was associated with increased intradialytic blood pressure reductions. Individualized clinical decisions and careful hemodynamic monitoring are warranted when implementing intradialytic nutritional interventions. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT07687498.

Humans↗