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PubMed2026

An automated geometric modeling framework in GATE for the design and optimization of high-sensitivity converging-beam SPECT collimators.

Objective.The trade-off between detection sensitivity and spatial resolution is a fundamental challenge in designing organ-dedicated Single-photon emission computed tomography (SPECT) collimators. While converging-hole geometries offer a solution, their optimization is often hindered by the lack of flexible computational tools capable of modeling large-scale, non-parallel hole arrays. This study aims to develop an automated geometric modeling framework to facilitate the design and evaluation of complex converging- and diverging-hole collimators within standard Monte Carlo environments.Approach.We developed a specialized modeling framework by implementing custom C++ classes and a vector-based alignment algorithm within GATE. This platform enables automated, orientation-consistent construction of large-scale converging arrays not natively supported by standard implementations. A high-sensitivity pure cone-beam collimator (CBC) was designed using this framework. The evaluation used hot-rod, disc, and Jaszczak phantoms for physical characterization, while XCAT and dedicated brain models were employed for clinical tasks, including cardiac, brain perfusion, and DaTscan SPECT simulations.Main results.The CBC achieved a nearly fourfold sensitivity increase compared to a conventional low-energy high-resolution parallel-hole collimator at a 20 cm radius of rotation, while maintaining comparable spatial resolution. Despite a 52.3% field of view reduction, the CBC yielded a 2.2-fold noise reduction (CV: 11.7% vs 25.9%) and mitigated partial volume effects via geometric magnification. XCAT and brain phantom simulations confirmed enhanced anatomical definition and contrast recovery in cardiac, perfusion, and DaTscan tasks.Significance.This work provides an efficient computational tool for rapid design space exploration of advanced collimator geometries. The results demonstrate that the proposed CBC design offers a significant sensitivity advantage, making it highly suitable for high-performance, small-volume clinical applications such as brain and cardiac molecular imaging.

Tomography, Emission-Computed, Single-Photon↗

PubMed2026

Rational design of high-productivity perfusion processes for CHO Cells: From growth inhibitory strategies to model-driven optimization.

While perfusion culture for Chinese hamster ovary (CHO) cells offers advantages such as continuous operation and flexibility, it suffers from product loss through cell bleeding and difficulties in reaching high productivity due to sustained rapid cell growth. Growth inhibitory strategies are widely used to enhance productivity in fed‑batch processes; however, their practical implementation and comparative effectiveness in perfusion processes remain insufficiently explored. Meanwhile, process development often relies on costly trial‑and‑error approaches. Here, we systematically compared three growth inhibitory strategies in perfusion culture-low cell‑specific perfusion rate (CSPR), sodium butyrate, and mild hypothermia-with respect to cell growth, metabolism, productivity, and product quality. Genome‑scale metabolic flux sampling analysis revealed that low‑CSPR and sodium butyrate induce a convergent up‑regulation of energy metabolism, correlating with greater gains in specific productivity (qp). Building on this insight, we developed a growth‑kinetic model for the combined low‑CSPR + butyrate strategy, incorporating parameter uncertainty. This model‑guided framework enabled the rational design of two distinct high‑productivity perfusion processes: a sustained mode that achieved robust long‑term stability alongside substantial productivity gains, and a high‑intensity mode that pushed qp and daily volumetric titer to their maxima, with increases of up to 108.94% and 190.36%, respectively, in a model CHO cell line with a moderate baseline productivity. Our study provides a proof‑of‑concept framework for perfusion intensification, from strategy selection to rational process design.

Animals↗

PubMed2026

Human-Centered Workspace Optimization: A 2 × 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 × 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 ± 0.53 versus 3.99 ± 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

Selective monitoring of trace-level catechin and myricetin in herbal and aqueous matrices using magnetic MIP-DSPME: Optimization via design of experiments.

A novel dispersive solid-phase microextraction approach utilizing a magnetic molecularly imprinted polymer (MMIP) integrated with HPLC-UV detection was developed for the concurrent quantification of catechin and myricetin in herbal extracts and aqueous samples. The sorbent was engineered as a core-shell nanocomposite, consisting of a selective polymer layer deposited onto Fe3O4@SiO2-APTMS magnetic nanoparticles. Dual-template imprinting using catechin and myricetin generated complementary binding cavities within the polymer framework. Experimental variables influencing extraction were systematically screened and subsequently optimized. A Plackett-Burman design was first applied to identify the most influential factors, with pH and sorption time identified as the dominant variables. These parameters were subsequently fine-tuned using a central composite design, and the optimization process was completed in only 30 experimental runs. The sorption characteristics of the imprinted sorbent (MMIP) were compared with those of its non-imprinted counterpart (MNIP). The MMIP demonstrated markedly higher maximum binding capacities (Qmax), reaching 119.3 mg g-1 for myricetin and 112.1 mg g-1 for catechin, whereas the corresponding values for the MNIP were 32.55 and 32.08 mg g-1, respectively. Moreover, the affinity constants (KL = 0.760-0.950 L mg-1) were approximately 2.3-fold higher for the MMIP, confirming its stronger and more selective interactions with the target analytes. The selectivity coefficients for the targeted flavonoids relative to structurally related compounds, including ferulic acid, p-coumaric acid, melatonin, and curcumin, exceeded 3.5 for the MMIP, whereas the corresponding values for the MNIP were close to 1.1, demonstrating the high molecular recognition capability of the imprinted sorbent. Method validation demonstrated limits of detection (LODs) of 0.33-0.59 ng mL-1 and limits of quantification (LOQs) of 1.10-1.96 ng mL-1, and excellent linearity over the concentration range of 5.0-5500 ng mL-1 (R2 > 0.998). The method achieved recoveries of 93.96% to 105.69% with RSDs below 5.5%, while the preconcentration factors ranged from 209 to 229. Furthermore, the sorbent retained more than 95% of its extraction efficiency after four consecutive reuse cycles and more than 80% after six cycles, demonstrating excellent stability and reusability. The proposed method was successfully applied to the analysis of six medicinal plant extracts and water samples, showing negligible matrix interference and superior sensitivity, selectivity, and operational simplicity compared with conventional solid-phase extraction methods.

Flavonoids↗

PubMed2026

Optimized AAV5-RPGR ORF15 Gene Therapy Rescues Photoreceptor Structure and Function in X-Linked Retinitis Pigmentosa Mouse Model.

PURPOSE: To develop and evaluate an rAAV5-based gene therapy vector expressing an optimized human RPGR ORF15 transgene (rAAV5-RPGR) for the treatment of X-linked retinitis pigmentosa caused by RPGR mutations, addressing the challenges of cloning the unstable wild-type ORF15 sequence. DESIGN: This was a prospective experimental study. SUBJECTS: This was an animal study. METHODS: An optimized RPGR ORF15 sequence was designed to eliminate problematic secondary structures and cryptic splice sites. In vitro expression was validated in HEK 293T and photoreceptor-like 661 W cells. A complete Rpgr knockout mouse model (Rpgr-knockout [KO]) was generated and characterized phenotypically. Therapeutic efficacy was assessed in Rpgr-KO mice via subretinal injection of rAAV5-RPGR at low (1 × 10⁹ vg/eye), medium (3 × 10⁹ vg/eye), or high (1 × 10¹⁰ vg/eye) doses. Structural and functional outcomes were evaluated at 12- and 14-month postinjection. Short-term safety was assessed in rabbits 1 month after subretinal injection. MAIN OUTCOME MEASURES: Level of RPGR protein expression and Protein isoform profile (elimination of truncated isoforms), Cellular localization of transgene expression and Dose-dependence of expression, outer nuclear layer thickness, and electroretinography parameters. RESULTS: (1) The optimized vector increased RPGR protein expression 3.3-fold in vitro compared to wild-type and eliminated truncated isoforms. (2) Subretinal delivery of rAAV5-RPGR in mice demonstrated dose-dependent transgene expression localized correctly to photoreceptor inner segments. (3) In Rpgr-KO mice, high-dose treatment significantly preserved outer nuclear layer thickness at the injection site (42% greater than controls at 14 months, P < .01) and central retina (P < .05), reduced aberrant rhodopsin mislocalization (P < .01), and partially restored retinal function. ERG showed significantly improved scotopic a-wave (≥100 vs <90 µV in controls at 10 cd·s/m²) and photopic b-wave amplitudes (49-66 vs 31-46 µV at 30 cd·s/m²) in treated mice. (4) No vector-related toxicity was observed in rabbits. CONCLUSIONS: rAAV5-RPGR mediated efficiently, targeted expression of optimized RPGR-ORF15, significantly preserved photoreceptor structure and function in a severe X-linked retinitis pigmentosa mouse model, and demonstrated a favorable safety profile. This study provides preclinical proof-of-concept for RPGR-targeted gene replacement therapy.

Animals↗

PubMed2026

Challenges and future directions in AI-driven biomaterials for microbiome-associated oral infectious diseases: A systematic review.

Oral biofilm-induced antimicrobial resistance is the core pathogenic mechanism of microbiome-associated oral infectious diseases (dental caries, periodontitis, peri-implantitis, and endodontic infection). Traditional therapies and biomaterials are limited by poor biofilm penetration, drug resistance induction, single functionality, and inadequate adaptation to dynamic oral microenvironmental changes (e.g., pH fluctuations, salivary rinsing, masticatory stimulation). Artificial intelligence (AI) has transformed the field by integrating materials science, microbiology, and stomatology data. Via machine learning, deep learning, and multi-physics simulation, AI optimizes biomaterial physicochemical properties, decodes microenvironmental signals, constructs precise sensing-response loops, and supports the full chain of material design, performance prediction, and action simulation, advancing treatment from empirical intervention to precision regulation. This systematic review retrieved literature from PubMed, Embase, and Web of Science (January 2016-January 2026) using keywords across three dimensions: AI, biomaterials, and oral microbiome. Following inclusion/exclusion criteria, 99 articles were included. It elaborates on five core mechanisms of AI-driven oral biomaterials (precise oral microbiome analysis, targeted material design/optimization, performance prediction/simulation, targeted delivery/intervention, effect evaluation/dynamic regulation), analyzes their applications in microbiome-targeted biomaterial research and development (R&D) and clinical practice for the four major oral infectious diseases, addresses technical bottlenecks (insufficient targeting specificity and precision of biomaterials, poor stability and durability in complex oral microenvironments, inadequate biofilm disruption capacity, and clinical translation obstacles), and proposes future directions (multimodal design to enhance targeting specificity, structural and component optimization to improve stability/durability, development of multi-mechanism synergistic biofilm disruption strategies, strengthening translational research for clinical application, and deep integration of AI in the full chain of biomaterial R&D). This work provides comprehensive theoretical and practical support for the R&D, optimization, and clinical translation of AI-driven microbiome-targeted oral biomaterials.

Humans↗

PubMed2026

Targeting SIRT6: the design and therapeutic implications of activators and inhibitors.

Sirtuin 6 (SIRT6) is an NAD+-dependent deacylase that maintains genomic stability, regulates metabolism, and influences aging, making it an attractive but challenging therapeutic target. Pharmacological modulation of SIRT6 holds promise for cancer and metabolic disorders, yet its context-dependent functions demand precise intervention strategies. Potent, selective, and drug-like chemical probes are therefore essential to dissect SIRT6 biology and to validate its therapeutic potential. This review critically evaluates recent medicinal chemistry advances in SIRT6 modulation. We focus on structure-guided design strategies and structure-activity relationships (SAR) that have transformed initial hits into optimized leads for both activators and inhibitors, highlighting the remaining challenges in achieving isoform selectivity and drug-like properties.

Sirtuins↗

PubMed2026

Axial Length Adjustment and AL/R Ratio Optimization of IOL Power Calculation in Extremely Long Eyes.

PURPOSE: To evaluate the accuracy of modern intraocular lens (IOL) power calculation formulas and axial length (AL) adjustment methods in eyes with AL ≥ 30.0 mm. DESIGN: Retrospective consecutive cross-sectional study. PARTICIPANTS AND CONTROLS: A total of 308 eyes (308 patients) with AL ≥ 30.00 mm were included. METHODS: Accuracy of modern online formulas, alone or with established AL adjustments methods, was analyzed. Subgroup analyses were performed based on AL, keratometry (K), anterior chamber depth (ACD), lens thickness (LT), and AL-to-corneal radius (AL/R) ratio. MAIN OUTCOME MEASURES: Predictive accuracy was evaluated using the formula performance index (FPI), root mean square absolute prediction error (RMSAE), standard deviation (SD) of prediction error (PE), and percentage of eyes within ±0.25 and ±0.50 diopters (D). RESULTS: Overall, Holladay 1 combined with the nonlinear polynomial Wang-Koch axial length adjustment (H1-PWK) demonstrated the best overall performance, achieving the lowest SD (0.40), RMSAE (0.40), and highest FPI (0.494). A tendency toward hyperopic error was observed in eyes with AL ≥ 32.0 mm, K ≥ 46.0 D. The AL/R ratio showed a significant positive correlation with PE in the Ladas Super formula, Barrett Universal II, EVO, PEARL-DGS, and Hoffer QST formulas. Spline-based regression analysis indicated that the transition point of AL/R from myopic to hyperopic PE varied across different formulas. CONCLUSIONS: H1-PWK provides robust refractive accuracy in extremely long eyes. The AL/R ratio may provide a useful composite biometric stratification parameter compared to AL alone.

Humans↗

PubMed2026

A streamlined workflow for high throughput metaproteomic analysis of the rumen microbiome.

Metaproteomics can provide direct functional insights into complex microbial communities, yet its application in rumen research remains limited due to labor-intensive and low-throughput sample preparation workflows before the MS analysis. This work aimed to develop and characterize a streamlined, high throughput metaproteomic workflow optimized for rumen samples. Key steps, including microbial cell extraction, cell lysis, protein digestion, and LC-MS/MS acquisition, were systematically assessed and optimized to reduce hands-on time while maintaining deep proteome coverage. The optimized workflow integrates a minimized cell extraction protocol using 0.5 g starting material and in-solution tryptic digestion. Application of the final workflow to 72 samples from in vitro fermentation revealed that biological variability between inocula dominated technical variability, which remained moderate (median CV of 21-24% across batches). Overall, the optimized workflow supports robust taxonomic and functional characterization of the rumen microbiome with improved scalability. These advances provide a foundation for applying metaproteomics to larger experimental designs, including nutritional trials and cohort studies, thereby enabling broader functional interrogation of rumen microbial ecosystems. SIGNIFICANCE: This study addresses current limitations in the application of metaproteomics to rumen microbiome research by developing a streamlined and scalable sample preparation workflow. By optimizing key steps and reducing sample input while maintaining reproducibility and proteome coverage, this work enables more efficient processing of larger sample sets. These advances support the broader use of metaproteomics in rumen studies and facilitate functional investigations relevant to animal nutrition and sustainable livestock production.

Animals↗

PubMed2026

Determinants of Nonspecific Response to Treatment in Randomized Controlled Trials of Major Depressive Disorder: A Narrative Review.

The design, conduct, and interpretation of double-blind randomized placebo-controlled clinical trials in major depressive disorder (MDD) are complicated by determinants of nonspecific response to treatment (NSRT). This narrative review provides a comprehensive overview of the determinants of NSRT in randomized controlled trials (RCTs) for MDD, including the placebo effect, factors related to measurement of the primary endpoint, the inclusion of misdiagnosed patients, the relapsing-remitting course of MDD, and factors related to functional unblinding. Potential strategies to reduce the impact of the determinants of NSRT and to improve the interpretation of RCT outcomes in MDD are also summarized. These strategies include use of centralized rating and standardized rater training, independent diagnostic confirmation, optimized site selection, minimizing financial incentives, exclusion of subjects participating in multiple clinical trials, exclusion of patients with unstable major depressive episode trajectories, and use of active placebo and alternative trial designs. Uniformity among experts in the definitions of determinants of NSRT and related concepts, as well as in strategies to address them, may facilitate progress in the development of novel treatments for MDD.

Humans↗

PubMed2026

Analyzing the impact of subcutaneous injection needle, device, and administration characteristics on patient pain, anxiety, and safety: a systematic literature review.

The subcutaneous (SC) injection route is a commonly used and important method for therapeutic delivery of a wide range of compounds, and needle characteristics have a significant influence on patient pain, anxiety, safety, and other outcomes. This systematic review evaluates the evidence on how needle-specific characteristics (e.g. gauge, length, tip design, wall thickness, concealment) and administration- or device-related factors can affect patient-reported outcomes and clinical safety indicators during and following SC injections. A comprehensive search was conducted in MEDLINE, PubMed, Embase, and ClinicalTrials.gov in June 2024. Studies were included if they assessed the relationship between needle characteristics and pain, anxiety, safety, or related outcomes in individuals receiving SC injections. A dual-reviewer process was used for study selection, data extraction, and quality assessment. Sixty-two studies met inclusion criteria. Evidence consistently indicated that thinner and shorter needles reduced patient-reported pain and adverse events such as bruising and bleeding. Tapered and lubricated needles, hidden or retractable needle designs, and use of autoinjectors or prefilled syringes also contributed to reduced anxiety and improved user satisfaction. However, results were heterogeneous, and many studies lacked sufficient power or single-variable evaluation of individual needle parameters, limiting definitive conclusions. Needle characteristics significantly influence patient experience and safety with SC delivery. While both clinical evidence and practical experience clearly favor thinner, shorter, and concealed needles, further standardized, high-quality research is needed to isolate and quantify the specific contributions of individual needle characteristics to optimize injection practices and support patient-centered device design.

Humans↗

PubMed2026

Impact of PerioperAtive LidocAine Infusions on Enhanced Recovery After Noncardiac Surgery (IMPALA-ERAS) in an inpatient setting: rationale, design and protocol for a sequential, repeated crossover trial.

INTRODUCTION: Multimodal analgesic strategies designed to minimise perioperative opioid exposure are fundamental components of enhanced recovery after surgery (ERAS) pathways. Despite widespread implementation of ERAS protocols, the optimal analgesic regimen remains undefined, as the individual contributions of specific agents to overall analgesic efficacy and opioid-sparing effects are not fully elucidated. Intravenous lidocaine, a widely utilised local anaesthetic, possesses both analgesic and anti-inflammatory properties and has been associated with improved gastrointestinal recovery. This study seeks to pragmatically evaluate the impact of incorporating perioperative intravenous lidocaine infusion into established ERAS pathways on postoperative functional recovery. METHODS AND ANALYSIS: The Impact of PerioperAtive LidocAine Infusions (IMPALA) on ERAS trial is a single-centre, pragmatic, cluster-randomised, double-blinded, placebo-controlled study. A total of 2290 patients undergoing elective colorectal surgery, emergency general surgery, urology, ventral hernia repair, surgical oncology or spine surgery will be randomly assigned to receive either intraoperative and postoperative intravenous lidocaine infusions (administered for up to 48 hours) or placebo as part of a standardised multimodal analgesic regimen integrated into established ERAS pathways. The primary outcome is case mix index-adjusted resource length of stay, defined as the time interval from surgical initiation to hospital discharge adjusted for case mix index. The primary outcome is total inpatient opioid consumption within the first 72 hours, reported in oral morphine milligram equivalents. Secondary outcomes include various in-hospital clinical endpoints derived from the electronic health record. ETHICS AND DISSEMINATION: This protocol and accompanying statistical analysis plan outline the study design, primary and secondary endpoints and analytic methodology. The IMPALA-ERAS trial has received ethical approval from the Vanderbilt University Institutional Review Board (IRB: 250617). The findings will be disseminated via peer-reviewed publications and presentations at national conferences. Results from this trial are expected to inform evidence-based practices regarding perioperative lidocaine infusion and its potential contributions to enhanced postoperative recovery in surgical patients. TRIAL REGISTRATION NUMBER: NCT07224711.

Humans↗

PubMed2026

Targeted Nanoparticle Delivery CRISPR/Cas9: overcoming biological barriers, enhancing stability, and improving therapeutic precision.

Clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9) has emerged as a promising gene-editing platform for genetic disorders; however, its in vivo application remains limited by low delivery efficiency and biological barriers. Many CRISPR payloads fail to reach target sites due to extracellular degradation, immune clearance, and intracellular trafficking limitations. This review examines the interplay between biological barriers and nanoparticle engineering strategies for CRISPR/Cas9 delivery. A barrier-oriented engineering approach is proposed as a central framework, encompassing ligand-based surface modification for enhanced targeting and uptake, improved circulation stability via PEGylation and biomimetic coatings, and optimized payload release through endosomal escape strategies. Stimulus-responsive nanoparticle systems further enable spatiotemporal control over payload release. Nuclear targeting strategies, including optimization of nuclear localization signals (NLS) and exploitation of endogenous trafficking pathways, are highlighted as key factors for improving genome-level editing efficiency. Despite these advances, major challenges-including limited intracellular delivery efficiency, insufficient targeting precision, and safety concerns-continue to hinder clinical translation. Future directions highlight artificial intelligence-driven nanoparticle design, personalized delivery systems, and next-generation CRISPR platforms. Overall, an integrated, barrier-oriented engineering strategy is essential for advancing CRISPR/Cas9 delivery toward clinical applications, ultimately advancing global good health and well-being.

CRISPR/Cas9↗

PubMed2026

Rationale, design, and experiences from the vanguard phase of the bariatric surgery for the reduction of cardiovascular events (BRAVE) trial.

BACKGROUND: Observational studies suggest that metabolic/bariatric surgery (MBS) reduces mortality and major adverse cardiovascular events in patients with obesity, but adequately powered randomized trials (RCTs) are lacking. The Bariatric Surgery for the Reduction of Cardiovascular Events (BRAVE) trial was designed to address this evidence gap. METHODS: BRAVE is an investigator-initiated, multi-center, open-label RCT with blinded endpoint adjudication comparing MBS vs guideline-based medical weight management (MWM) in adults with obesity and high-risk cardiovascular disease (CVD). Eligible participants have a body-mass index ≥35 kg/m² or ≥30 kg/m² with type 2 diabetes or age >55 years, and prior myocardial infarction (MI), coronary intervention, heart failure (HF), atrial fibrillation (AF) with elevated CHA₂DS₂-VASc score, cerebrovascular disease, or peripheral arterial disease. Participants are randomized 1:1 to MBS (sleeve gastrectomy, Roux-en-Y gastric bypass, or duodenal switch) or MWM, which includes dietary, behavioral, and pharmacologic therapies. The primary outcome is the composite of all-cause death, MI, stroke, HF events, coronary revascularization, AF hospitalization, and renal events. A vanguard phase of 200 participants was implemented to optimize recruitment and logistics. RESULTS: As of October 2025, 2,514 individuals have been screened from 17 centers in Canada, Brazil, Italy and Spain, with 444 entered MBS work-up, and 200 have been randomized. The randomized cohort (mean age 59.8 years; 37% female; mean BMI 44.0 kg m⁻²) has high burden of hypertension (82%), diabetes (45%), coronary artery disease (44%), HF (39%), and AF (48%). Recruitment barriers were identified and addressed through targeted education and enhanced patient engagement. CONCLUSIONS: BRAVE is the first large RCT evaluating whether MBS safely reduces major cardiovascular events compared with medical therapy in high-risk patients with obesity. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT05531474.

Humans↗

PubMed2026

Dispositional optimism and open-label placebo responses in hair cortisol concentrations and psychological distress-A randomized controlled trial.

Open-label placebo (OLP) treatments show beneficial effects on various health-related outcomes, but studies investigating OLP effects on physiological measures remain scarce. This randomized controlled trial examined the effect of a 4-week OLP intervention on psychological distress and hair cortisol concentrations (HCC) in 202 healthy university students preparing for mandatory oral exams and whether dispositional optimism moderates the OLP effects. Participants were randomly assigned to an OLP or control group. Psychological distress was repeatedly assessed via negative affect, test anxiety, and subjective stress. HCC was measured before and within the intervention. Treatment expectations were additionally examined in interaction with optimism. Results show that OLPs significantly reduced psychological distress and HCC compared to the controls. Optimism moderated the OLP effect on HCC, with less optimistic individuals demonstrating the strongest reduction, independent of expectation. Optimism did not moderate OLP effects in psychological distress. However, the OLP effect on psychological distress depended on the three-way interaction of group, optimism, and expectation. The results suggest that OLPs alleviate the psychophysiological impact of a real-life stressor and indicate that optimism and expectation differently shape psychological and physiological OLP responses. These findings are discussed within the framework of the interactionist perspective.

Humans↗

PubMed2026

Improving insurance deduction identification: a hybrid artificial intelligence model using machine learning and expert systems.

PURPOSE: Financial challenges in healthcare systems worldwide, especially in low- and middle-income countries like Iran, have increased hospitals' reliance on insurance reimbursements. Unrecognized insurance deductions often cause severe financial shortages, making efficient deduction management crucial. This study aimed to design a hybrid intelligent system for identifying and predicting insurance deductions by combining machine learning and expert system frameworks. DESIGN/METHODOLOGY/APPROACH: A mixed-methods design was applied in four stages. First, a scoping review identified the causes and patterns of insurance deductions. Second, interviews with 15 insurance experts produced a validated checklist and a dataset from inpatient billing records. Third, using the CRISP-DM methodology, machine learning algorithms were developed and tested in SPSS Modeler alongside a fuzzy expert system developed in MATLAB. Finally, the model was validated using the holdout method. FINDINGS: Four categories of deduction drivers were identified: service provision, registration errors, document submission issues, and revenue conversion processes. The CHAID decision tree outperformed other algorithms with a 99% precision rate and the lowest Mean Absolute Error (9.43). A brief assessment of potential overfitting was conducted to ensure that the CHAID model's high accuracy was interpreted cautiously and supported by the validation results. The fuzzy expert system with validated rules was adaptable for deduction classification, especially for cases unsuitable for quantitative modeling. ORIGINALITY/VALUE: The hybrid model improves detection and prevention of deductions, offering actionable insights for hospital administrators, insurers, and policymakers. Its implementation can enhance hospital information systems, streamline claims processing, and optimize revenue management amid financial constraints.

Machine Learning↗

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

Yoga MAT: A factorial randomized study using the Multiphase Optimization Strategy to develop a multicomponent yoga intervention for people with chronic pain taking medications for opioid use disorder.

BACKGROUND: People taking medications for opioid use disorder (MOUD) commonly experience chronic pain. Yoga interventions show promise for decreasing pain-related disability in other populations. More time spent in yoga practice may improve pain-related outcomes. METHODS: The Multiphase Optimization Strategy (MOST) provided the framework for developing an optimized yoga intervention package. In a 2x2x2x2 factorial experiment, we evaluated four candidate intervention components which, when added to a weekly yoga class, might increase yoga engagement. The primary outcome was minutes per week of yoga practice (classes and other yoga practice) over the 12-week intervention period. We sought to determine which combination of intervention components was associated with the most yoga practice for people with chronic pain taking buprenorphine or methadone as MOUD. RESULTS: We enrolled 192 adults. There was a significant main effect for Component "B" (having two private sessions with a yoga teachers; IRR = 1.10, 90%CI 1.02; 1.18), and a synergistic interaction between Components "B" and "D" (D was financial incentives for attending class; IRR = 1.11, 90%CI 1.02; 1.19). This combination of these two components (without other potential components) was associated with the second highest model-predicted mean minutes of yoga per week (157.1min; 90% CI = 120.1-194.0) which was only 4min less than the combination including all four components. CONCLUSIONS: We identified a combination of intervention components as the optimized intervention. A next step will be to test the effect of this optimized intervention on pain and substance use outcomes in a randomized controlled clinical trial.

Humans↗