Search Results (24,255)

Oxygen (O₂) leakage in macrophyte rhizospheres is an adaptive strategy for hypoxic environments, which is important in lake ecological restoration. In this investigation, the fluorescent planar optode (PO) technique is used for two-dimensional (2D) distribution of dissolved O₂ at a submillimeter scale in the rhizosphere of Vallisneria spiralis under various environmental conditions. The spatial heterogeneity in the distribution of oxic microniches is frequently verified in the rhizosphere. The radial oxygen loss (ROL) rate for root systems is characterized by the following sequence: basal root (20.6 ± 5.1–49.6 ± 9.5 nmol m⁻² s⁻¹, n = 7) > lateral root (14.1 ± 4.1–36.6 ± 8.3 nmol m⁻² s⁻¹, n = 7) > root tip (13.1 ± 4.6–28.8 ± 6.4 nmol m⁻² s⁻¹, n = 7). The O₂ maximum value on lines transecting each kind of root also obeys the sequence mentioned above. For one typical root, (1) O₂ decreases from 131.2 ± 2.4–147.4 ± 3.7 μmol L⁻¹ at the root center to 47.2 ± 1.4–75.9 ± 2.2 μmol L⁻¹ in the rhizosphere fringe due to O₂ supply from the root surface and O₂ consumption in rhizosphere sediment, and (2) the furthest distance from the aboveground part to the root tip leads to the lowest O₂ concentration at the root apex of that root. The light/dark transition and O₂ level in overlying water modulate the photosynthetic activity of leaves and the transfer of oxygen in the water column through aerenchyma tissue to the roots. The sequence of the oxygenated area (%), ROL rate, and O₂ concentration in rhizosphere sediment under various conditions is demonstrated as: high illumination/high O₂ > darkness/high O₂ > high illumination/low O₂ > darkness/low O₂. The effect of O₂ in water on the ROL of Vallisneria spiralis is more distinct than illumination. Oxygen storage in roots, and especially O₂ diffusion from overlying water, can supplement O₂ deficiency in the rhizosphere during the cessation of photosynthesis under darkness. This research advances the understanding of complex interrelationships among O₂ dynamics in different root parts, photosynthesis, O₂ in overlying water and O₂ transfer through plant aerenchyma to the rhizosphere. Full article

Background/Objectives: The accuracy and reliability of automated clinical analyzers are fundamental to patient safety and effective medical decision-making. Traditional quality control (QC) methods, which rely on periodic manual calibration and reactive maintenance, are inherently limited by high latency and labor costs; furthermore, they fail to provide continuous, real-time monitoring. This paper introduces a novel hybrid ensemble learning framework for the automated quality inspection of medical devices through the analysis of time-series reaction curves. Methods: Our system integrates three heterogeneous anomaly detection paradigms: an Enhanced Dynamic Time Warping (DTW) detector for robust non-linear pattern matching, a Shape Template Matching (STM) detector that mimics expert clinical logic by analyzing morphological features in a normalized shape space, and a specialized Time-series Variational Autoencoder (TimeVAE) for deep representation learning. The outputs of these detectors are fused using a weighted ensemble strategy, which is specifically designed to prioritize the minimization of false negatives—a critical requirement in medical diagnostics. Results: We evaluate our framework on a comprehensive, multi-center real-world dataset comprising seven distinct biochemical assays. Experimental results demonstrate that our proposed method achieves superior performance, attaining a $0\%$ false negative rate on CRE and DBIL assays and outperforming all baseline methods on the other five datasets. An ablation study confirms the model’s robustness even with limited training data, and a comparative analysis against eight state-of-the-art baseline methods further validates the effectiveness of our domain-optimized ensemble approach. Conclusions: The system provides a robust, interpretable, and highly automated solution for transitioning from reactive maintenance to proactive, real-time quality assurance in clinical laboratories. Full article

Theranostics is a novel approach that integrates diagnostic and therapeutic efficacy on a single platform, holding great promise for precision medicine by enabling real-time monitoring of disease progression and therapeutic response. Despite significant advances, the successful development and delivery of theranostic systems are critically limited by multiple biological barriers present at systemic, tissue, cellular, anatomical, and immunological levels. These barriers restrict bioavailability, target accessibility, and therapeutic efficacy, while often increasing off-target accumulation and adverse effects. This review provides a comprehensive overview of the major biological barriers encountered in theranostic development, including physiological barriers such as plasma protein binding, renal clearance, and hepatic metabolism; anatomical barriers like endothelial linings, the blood–brain barrier (BBB), and the tumor microenvironment; cellular barriers involving membrane permeability, intracellular trafficking, and endo-lysosomal entrapment; and immunological barriers such as immune recognition, inflammatory responses, and complement activation. Special emphasis is placed on the BBB, highlighting its structural complexity, transport mechanisms, and strategies such as molecular Trojan-horse technology, receptor-mediated and adsorptive-mediated transcytosis, and nanocarrier-based approaches to enhance central nervous system delivery. The review further discusses targeted delivery challenges, including receptor heterogeneity and multidrug resistance, and critically evaluates current strategies to overcome these barriers through surface functionalization, stimuli-responsive systems, biomimetic carriers, and controlled-release mechanisms. Finally, recent advances, clinical challenges, and future perspectives—including personalized theranostics, artificial intelligence—assisted design, and next-generation barrier-penetrating systems—are explored. Overall, this review aims to provide a structured understanding of biological barriers in theranostics and highlight innovative approaches to improve their translational potential. Full article

Against the backdrop of the deep advancement of the carbon peak and carbon neutrality goals and the superposition of the transportation power strategy, leveraging the spatial restructuring of highway networks to optimize the low-carbon layout of county-level industries has become a crucial lever for balancing economic quality improvement with carbon intensity control. This study selects panel data from 129 counties in Yunnan Province spanning 2015–2024, constructing a comprehensive highway network development index from four dimensions: highway density, road network connectivity, weighted hierarchical structure, and county accessibility. Using a two-way fixed effects benchmark model, a stepwise mediation effect testing framework, and a regional heterogeneity identification strategy, the paper systematically examines the marginal effects, transmission pathways, and spatially differentiated characteristics of highway network development on county-level industrial carbon emission intensity. Key findings are as follows: Enhanced highway network development significantly suppresses the increase in county-level industrial carbon emission intensity, and a well-developed road network can provide long-term empowerment for the low-carbon transformation of county-level industries. Mechanism analysis confirms that highway network development reduces emissions through two core pathways: first, a direct emission reduction effect achieved by optimizing the county-wide freight organization system, reducing inefficient transport energy consumption, and improving overall transport efficiency; second, an indirect low-carbon enabling effect realized by breaking down administrative barriers in county markets, lowering cross-regional business transaction costs, deepening industrial division of labor and collaboration, and forcing resource allocation improvements. Heterogeneity analysis reveals that the low-carbon dividends of highway network development exhibit significant gradient differentiation: the emission reduction enabling effect is strongest in counties within the Central Yunnan urban agglomeration, followed by cultural tourism counties in western Yunnan and border counties in southern Yunnan, with the weakest marginal enabling effect observed in traditional agricultural counties in northeastern Yunnan. Full article

This study examines the impact of ESG disclosure, leverage, and profitability on firm value, measured by Tobin’s Q, among 67 non-financial Tadawul-listed companies in Saudi Arabia over the period 2015–2024. ESG disclosure is captured through a manual content-analysis index that scores the proportion of expected environmental, social, and governance items reported by each firm. The study further investigates whether board independence moderates these relationships while controlling for liquidity, firm size, current ratio, capital expenditure, and board size. Methodologically, the study employs the two-step system generalized method of moments (system GMM) estimator, which addresses dynamic persistence, endogeneity, and unobserved heterogeneity. The findings reveal that ESG disclosure has a positive and significant effect on firm value, indicating that the Saudi market increasingly rewards firms that provide broader sustainability-related information. Profitability also exerts a positive influence on Tobin’s Q, while leverage has a negative and significant effect, suggesting that higher debt weakens market valuation. Among the moderating effects, board independence significantly reduces the negative impact of leverage on firm value, although it does not significantly strengthen the positive ESG disclosure–firm value relationship. The results also show that liquidity, firm size, capital expenditure, and board size positively influence firm value. The study’s novelty lies in being the first, to our knowledge, to integrate ESG disclosure, financial structure, profitability, and board independence within a single dynamic firm-value framework over a decade-long panel that brackets the Saudi Exchange’s 2021 ESG disclosure guideline. In doing so, it advances emerging-market ESG research by showing that, under Saudi Arabia’s largely voluntary disclosure regime and concentrated-ownership structure, board independence operates primarily as a risk-monitoring mechanism rather than as an amplifier of disclosure value. The findings imply that regulators should strengthen and progressively mandate ESG reporting frameworks, that investors should treat ESG transparency as value-relevant information, and that firms should view ESG transparency and prudent governance as strategic tools for enhancing market value in line with Vision 2030. Full article

This study investigates the mechanical performance of a pulsed laser butt-welded IN792 DS joint and its relationship to its microstructure by means of grid nanoindentation. A new ISE-free (rate-derived) hardness parameter (H_R) has been introduced to account for the local bulk elastoplastic behavior of the material in combination with the stable contribution of residual stress, thus overcoming the limitations of the current standard codes. It allows performance comparability between different welding experiments, materials, and joint configurations. It offers an alternate means to mechanically determine the HAZ width when microscopic and metallurgical methods fail to detect it. Moreover, the spectra of two independent indentation parameters have been utilized as an input within an iterative statistical deconvolution scheme to estimate the composition of the relevant phases present within the fused zone. While one parameter spectrum acted as a predictor in the first stage, the second one served as a corrector for the final estimation of the four detected phases, thereby self-validating the iteration procedure with 5% tolerance. The validity of phase estimation was first determined over the entire FZ and then at three levels of the weald seam (top, neck and bottom) for further validation. The results indicate that the γ-matrix and ultrafine fine/hard second phases in the fused zone amounted to 54% and 43% volume fractions, respectively. The associated deconvoluted mechanical performance, expressed in terms of E_IT, H_IT, and H_R, corresponded to approximately 209 ± 4.5, 6.3 ± 0.2, 4.4 ± 0.1 and 224 ± 7.0, 6.7 ± 0.1, and 4.6 ± 0.1 GPa, respectively. A correlation between the estimated phases and the local mechanical performance via the conventional indentation parameter (H_IT and E_IT) and the new H_R parameter in the three relevant regions of the fused zone was discussed while discerning the effect of cooling rate on precipitate size, heterogeneity, porosity, residual stresses, and grain orientation. Further validation studies on different sample geometries, materials and joint configurations are needed to confirm the generality of the proposed methodology. Full article

Tight oil reservoir quality and development effectiveness are highly dependent on microscopic pore structure characteristics and spatial heterogeneity. In this study, tight sandstones from the Chang 3, Chang 6, Chang 7, and Chang 8 members of the Triassic Yanchang Formation in the Xunyi exploration area, southern Ordos Basin, were selected as research objects. By integrating X-ray diffraction (XRD), cast thin sections, scanning electron microscopy (SEM), high-pressure mercury injection (HPMI) experiments, and multifractal theory, the multi-scale heterogeneity characteristics of pore structures in different layers were quantitatively characterized. The response relationships between multifractal parameters, macroscopic physical properties, and pore size distributions were discussed, and the geological control mechanisms of sedimentation and diagenesis on heterogeneity were revealed. The results indicate that the sedimentary environment plays a fundamental role in controlling reservoir physical properties. The Chang 3 and Chang 8 members, deposited in underwater distributary channels, are dominated by primary and dissolution pores, with physical properties significantly superior to the gravity flow-deposited Chang 6 and Chang 7 members. Multifractal analysis shows that the Chang 3 member has the largest singularity spectrum width (Δα =1.943 ± 0.56) and heterogeneity index (R_d = 1.782 ± 0.99), reflecting its broadest pore size distribution, strongest heterogeneity, and significant intra-layer differences; while the pore structures from Chang 6 to Chang 8 are relatively stable, with the Chang 8 member exhibiting high spatial connectivity. This study demonstrates that the quantitative evaluation method based on multifractal theory can effectively identify microscopic structural differences in tight sandstones, providing a critical supporting basis for reservoir classification characterization and favorable layer selection in the Yanchang Formation of the Ordos Basin. Full article

Background: Insomnia and stress-related sleep disorders are increasingly recognized as systemic conditions linked to the microbiota–gut–brain axis (MGBA). With growing clinical interest in natural products that modulate the gut environment, this systematic review evaluates the efficacy and mechanisms of non-pharmacological interventions, specifically probiotics, prebiotics, dietary indices, and botanicals, in alleviating insomnia, restoring circadian rhythms, and modulating neurochemical markers. Methods: In strict accordance with PRISMA 2020 guidelines, we searched PubMed, ScienceDirect, Scopus, and The Cochrane Library for English language studies published from inception to March 31, 2026. Eligibility was restricted to studies with rigorously controlled designs, specifically randomized controlled trials (RCTs) and controlled in vivo animal studies. Interventions had to target the gut microbiota, with primary outcomes measuring sleep quality (subjective or objective) or sleep-related neurochemical markers. We excluded uncontrolled, single-arm, or observational designs; in vitro studies; non-original research; and studies involving subjects with severe medical or psychiatric comorbidities (e.g., cancer, ADHD, severe psychiatric disorders) to prevent confounding variables, though mild-to-moderate anxiety and depression were permitted. Risk of bias was assessed using the Cochrane RoB 2.0 and SYRCLE tools. Due to significant methodological heterogeneity, a narrative synthesis stratified by intervention and population was conducted. This review was not registered in PROSPERO. Results: A total of 56 studies (33 humans, 23 animals) met the inclusion criteria. Taxonomic nomenclature was updated to reflect 2020 reclassifications (e.g., Lactiplantibacillus plantarum). In human trials, interventions significantly improved subjective sleep metrics (PSQI, ISI). Recent additions demonstrated the efficacy of the Dietary Index for Gut Microbiota (DI-GM) and the improvement in N3 sleep latency by yeast mannan. Furthermore, whole-food patterns (e.g., the MIND diet) and Traditional Chinese Medicine (TCM) decoctions successfully enriched beneficial taxa, such as Bacteroides coprophilus, and increased short-chain fatty acid (SCFA) production. Animal models demonstrated that “psychobiotic” strains (Bifidobacterium breve, Lacticaseibacillus paracasei), prebiotics (GOS/PDX), and TCM formulas effectively restored GABA/5-HT profiles, lowered morning cortisol, and facilitated REM rebound in PCPA-induced models, while also consolidating non-rapid eye movement (NREM) sleep and downregulating clock genes (Per1/Per2). Conclusions: Psychobiotics, prebiotics, and botanicals represent a highly viable non-pharmacological strategy for treating insomnia. However, current evidence is constrained by a heavy reliance on subjective human questionnaires, short follow-up durations limiting insight into long-term stability, and a substantial translational gap between mechanistic rodent models and human clinical outcomes. Full article

Multi-criteria group decision making (MCGDM) under linguistic uncertainty remains a fundamental challenge in applied mathematics, where decision makers seldom assign crisp numerical evaluations and frequently exhibit heterogeneous risk attitudes shaped by behavioural factors. An integrated mathematical framework, hereafter PLR-3WBC (Probabilistic Linguistic Regret-driven Three-Way Bayesian Consensus), is developed to systematically integrate four methodological components that have each been individually validated in the MCGDM literature: representation of decision information with explicit probability mass on linguistic terms; quantification of decision-maker regret and rejoice psychology under linguistic uncertainty; classification of alternatives into three actionable decision regions rather than a single-valued ranking; and group consensus reaching with credal weight aggregation. Each component has demonstrated its effectiveness in its respective domain; the present framework capitalises on their complementary strengths by embedding them within a single pipeline equipped with formal guarantees, an integration that has not been previously reported. The framework integrates five methodological components: probabilistic linguistic term sets (PLTS) for information representation; the Bayesian best–worst method (BBWM) for credal criterion weighting; a regret–rejoice value function adapted to the linguistic domain for behavioural evaluation; three-way decision (3WD) thresholds derived from a loss-function model for actionable classification; and a distance-based consensus reaching process with feedback mechanism for group convergence. A case study on age-friendliness evaluation of twelve aging urban residential communities under an indicator system of five dimensions and eighteen criteria, with four expert decision makers, demonstrates that PLR-3WBC delivers an actionable three-way classification, recovers a transparent group consensus, and produces rankings broadly consistent with classical TOPSIS, VIKOR, PROMETHEE-II, and BWM-TOPSIS (Spearman rank correlation exceeding 0.97), thereby confirming that the integrated framework preserves the ordinal reliability of these established methods, while additionally delivering three outputs that arise from the methodological integration: an actionable three-way classification enabling discrete budget-aligned decisions, credal weight intervals quantifying the depth of expert agreement on criterion importance, and a behavioural reordering of borderline non-dominated alternatives that reflects the loss-averse psychology of the decision panel and would remain hidden under single-method deployment. Sensitivity analyses with respect to the regret aversion coefficient, the loss function parameters, and the consensus threshold confirm that the qualitative classification is stable across a wide parameter envelope, supporting the practical deployment of PLR-3WBC in age-friendly community renewal programmes. Full article

With the global rise in sustainable investment concepts, environmental, social, and governance (ESG) factors have increasingly become important criteria influencing investment decisions. Although institutional investors are paying greater attention to corporate ESG performance, limited evidence exists regarding its impact within the Chinese A-share market. Using panel data from Chinese listed firms during the period 2010–2023, this study employs fixed-effects models with clustered standard errors as the baseline estimation method. To improve the robustness of the findings, Tobit regression, Logit regression, lagged-variable models, heterogeneity analysis, and Hausman tests are further conducted. The empirical findings indicate that the overall ESG score and the individual environmental (E), social (S), and governance (G) dimensions do not exhibit statistically significant effects on institutional ownership in the baseline fixed-effects regressions. The results suggest that ESG performance has not yet become a dominant determinant of institutional investment decisions in China’s capital market. However, the robustness tests based on Tobit and Logit models provide limited evidence that ESG performance may still influence institutional investor behavior under alternative empirical specifications. Furthermore, the heterogeneity analysis reveals that the relationship between ESG dimensions and institutional ownership differs across environmentally related and non-environmentally related firms, although the effects are generally weak and statistically limited. The study contributes to the ESG and institutional investment literature in three important ways. First, it provides updated evidence from the Chinese A-share market over the 2010–2023 period, reflecting the evolving stage of ESG development in emerging economies. Second, it comparatively examines the differentiated roles of environmental, social, and governance dimensions rather than relying solely on aggregated ESG indicators. Third, it highlights the limited and transitional nature of ESG integration among institutional investors in China, where traditional financial indicators continue to play a more important role in investment decisions. The findings provide important implications for policymakers, listed firms, and institutional investors seeking to promote sustainable finance development and improve the effectiveness of ESG disclosure practices in emerging markets. Full article

Background: Anti-amyloid monoclonal antibodies represent the first disease-modifying therapeutic strategy targeting amyloid-β pathology in early Alzheimer’s disease (AD). Although several agents have demonstrated the ability to reduce cerebral amyloid burden, their clinical efficacy and safety remain subjects of substantial scientific and regulatory debate. This study aimed to synthesize randomized evidence evaluating the benefit–risk profile of anti-amyloid monoclonal antibodies in biomarker-confirmed early AD. Methods: A systematic review and classical pairwise meta-analysis of randomized controlled trials (RCTs) was conducted following the PRISMA 2020 guidelines. PubMed/MEDLINE, Embase, and the Cochrane Central Register of Controlled Trials were searched for phase III placebo-controlled trials evaluating lecanemab, donanemab, aducanumab, and gantenerumab in patients with mild cognitive impairment due to AD or mild AD dementia with biomarker confirmation of amyloid pathology. The primary outcome was change from baseline in the Clinical Dementia Rating–Sum of Boxes (CDR-SB) at the longest available follow-up. Safety outcomes included amyloid-related imaging abnormalities with edema or effusion (ARIA-E), amyloid-related imaging abnormalities with hemorrhage (ARIA-H), serious adverse events, and treatment discontinuation. Random-effects meta-analyses were performed. Results: Six randomized comparisons derived from four phase III trials involving 7695 participants met the eligibility criteria. Anti-amyloid monoclonal antibodies were associated with a statistically significant slowing of clinical progression compared with placebo (pooled mean difference in CDR-SB: −0.42 points; 95% CI −0.59 to −0.25; I² = 78%). The observed effect was primarily driven by trials of lecanemab and donanemab, whereas aducanumab demonstrated discordant results across trials and gantenerumab showed no clinically meaningful benefit. Despite statistical significance, the magnitude of the pooled effect approached the lower boundary of the minimal clinically important difference reported for CDR-SB in early AD. Treatment was associated with a markedly increased risk of ARIA-E (pooled risk ratio 10.1; 95% CI 7.8–13.0), with moderate heterogeneity across studies. Most ARIA-E events were asymptomatic and detected through protocol-mandated MRI monitoring. Conclusions: In biomarker-confirmed early Alzheimer’s disease, anti-amyloid monoclonal antibodies produce a statistically significant but modest slowing of clinical decline accompanied by a substantially increased risk of ARIA. The benefit–risk profile appears heterogeneous across individual antibodies and may reflect pharmacological differences in amyloid targeting and clearance mechanisms. These findings support cautious, individualized use of anti-amyloid therapies and highlight the need for longer-term studies to determine whether short-term slowing of decline translates into clinically meaningful disease modification. Full article

Northeast China is one of China’s major commodity grain bases and plays a strategic role in national food security. Against the background of rural population outflow and agricultural modernization, new agricultural business entities (NABEs), including family farms, farmers’ cooperatives, and agribusinesses, have become important actors in reshaping agricultural production organization. Based on registration data for 2014, 2018, and 2023, this study uses kernel density estimation (KDE), standard deviational ellipse (SDE) analysis, spatial autocorrelation analysis, ordinary least squares (OLS) regression, and multiscale geographically weighted regression (MGWR) to examine the spatiotemporal patterns and driving factors of NABEs in Northeast China. The results show that: (1) NABEs expanded rapidly from 2014 to 2023 and became increasingly concentrated in agriculturally advantageous plain areas. (2) Family farms showed the fastest expansion, farmers’ cooperatives had the widest spatial coverage, and agribusinesses were mainly concentrated around transport corridors and market nodes. (3) In terms of industrial structure, crop-production entities remained dominant, followed by animal husbandry entities, while forestry, fishery, and agricultural support service entities accounted for relatively small shares; however, their numbers continued to increase. (4) The OLS results showed that the reclamation rate and road network density had relatively stable associations with the spatial distribution of multiple entity types, whereas economic development, science and technology investment, and fiscal support showed differentiated relationships across entity types and regions. (5) The MGWR results further reveal spatial heterogeneity in the effects of driving factors. These findings provide empirical evidence for type-specific cultivation and differentiated policy support for NABEs in major grain-producing areas. Full article

Background: The management of diabetic foot disease and knee osteoarthritis (OA) with smart orthotics holds significant importance during the early stages of these conditions, given their potential consequences, including functional impairment, chronic pain, and economic burden. Real-time monitoring of plantar foot pressure enables early detection of abnormal force distribution and gait biomechanics, allowing for the redirection of forces away from affected ulcers or arthritic joints. This is the first systematic review to synthesise clinical evidence for smart orthotics technology with real-time plantar pressure sensor biofeedback across both diabetic foot ulcer prevention and knee osteoarthritis management simultaneously. A search of the PROSPERO register confirmed no existing registration covers this specific combination. Objectives: To examine the clinical evidence for the use of standard and smart orthotics in the prevention and management of diabetic foot ulcers (DFUs) and knee OA, and to evaluate their impact on plantar pressure redistribution, ulcer recurrence, pain, biomechanics, and economic burden. Eligibility criteria: Studies published in English involving human adult participants (≥18 years) with a clinical diagnosis of diabetes mellitus (at risk of DFU or with peripheral neuropathy) or knee OA, where the intervention involved any orthotic device or smart/intelligent insole with clinical outcomes reported, were included. Studies on healthy individuals only, those not reporting participant age, and non-weight-bearing protocols not differentiated from weight-bearing were excluded. Information sources: Five databases were searched: CINAHL (EBSCO Information Services, Ipswich, MA, USA), PubMed Advanced (National Library of Medicine, Bethesda, MD, USA), Wiley Online Library (John Wiley & Sons, Hoboken, NJ, USA), Cochrane Library (Cochrane Collaboration, London, UK), and Google Scholar (Google LLC, Mountain View, CA, USA). Searches were completed in May 2026. Methods: We conducted a comprehensive literature review. This review was structured and reported with reference to the PRISMA 2020 statement (Preferred Reporting Items for Systematic Reviews and Meta-Analysis; University of Ottawa, Ottawa, ON, Canada) to guide transparency of reporting. It does not constitute a full Cochrane-style systematic review; risk of bias assessment was applied to key included studies and GRADE (Grading of Recommendations Assessment, Development and Evaluation; McMaster University, Hamilton, ON, Canada) certainty ratings were applied informally and narratively rather than as formal per-outcome evidence profiles. Five databases were searched yielding 92,637 records. After removal of 398 duplicates by Rayyan, 92,239 records remained. A subsequent automated keyword-based relevance filter applied within Rayyan (Rayyan AI, Doha, Qatar), prior to human screening, excluded 84,572 records that did not contain any terms related to orthotics, diabetic foot, or knee osteoarthritis, yielding 7667 records for human title/abstract screening. A narrative synthesis approach was adopted owing to the heterogeneity of study designs and outcome measures across included studies, which precluded meta-analysis. This review was not prospectively registered. A complete list of all 78 included studies, including those not individually discussed in the results and discussion. Results: The available clinical studies report promising findings for orthotics and smart orthotics in pain reduction, ulcer prevention, and potential reduction in economic burden, though conclusions are limited by small sample sizes, heterogeneity, and predominantly open-label designs. Recent research found that orthotics can be used to alter the gait pattern that influences knee OA by reducing excessive force on the affected joint. A randomised controlled trial demonstrated an 80% relative risk reduction in DFU recurrence (RR = 0.20; 95% CI: 0.06–0.79; p = 0.022), with absolute event rates of 6.3% in the intervention group versus 30.8% in controls (ARR = 24.5%); a second trial reported a 71% reduction in ulcer incidence over 18 months; and a third randomised controlled trial demonstrated statistically significant plantar pressure reduction (p < 0.01) in patients with diabetic neuropathy. Conclusions: The available evidence suggests that orthotics may be associated with improved pressure redistribution, reduced ulcer incidence, and benefit in the management of knee OA. Although the number of studies directly comparing smart orthotics with standard orthotics remains limited, the limited comparative studies suggested that smart orthotics showed promising results in reducing ulcer incidence, providing the patient with real-time feedback to offload via their electronic devices. These findings, while preliminary, highlight the potential of smart orthotic technology as an adjunct to standard orthotic care in reducing the overall burden of diabetic foot disease and knee osteoarthritis. Limitations: The primary methodological limitation of this review is the open-label design of all included smart orthotic trials, which precludes participant blinding and introduces performance bias. However, this limitation is structural and inherent to the wearable technology field—analogous to surgical trials—and is substantially mitigated by the use of objective primary outcome measures (plantar pressure and ulcer recurrence) across the three included RCTs, the consistency of effect direction across independent RCTs conducted in different countries, and a narrative sensitivity analysis confirming robustness of findings (Risk of Bias Across Studies Section). Formal per-outcome GRADE evidence profiles were not produced; overall certainty of evidence was assessed narratively with reference to GRADE domains and is judged to be low to moderate for smart orthotics in DFU prevention and low for knee OA management, consistent with the Level 2–3 evidence base and open-label study designs. Future adequately powered, multi-site RCTs with standardised outcome reporting, minimum 24-month follow-up, and integrated health economic modelling are the highest priority to extend these preliminary findings. Registration: This review was not prospectively registered. Full article

Background/Objectives: Treatment for laryngeal cancer often impacts voice, swallowing, communication, and quality of life. Patient-reported outcome measures (PROMs) are increasingly used to evaluate survivorship, but their application and connection with objective functional measures vary widely. The objective was to explore how PROMs are used in laryngeal cancer research, identify the functional areas they assess, analyze their link with objective clinical outcomes, and identify methodological gaps in current studies. Methods: This scoping review followed PRISMA-ScR guidelines. Searches were conducted in PubMed/MEDLINE, Scopus, and Web of Science from their start until April 2026. Included studies involved adults with laryngeal cancer reporting PROMs and/or objective functional outcomes. Data on study features, PROM tools, evaluated domains, and how PROMs relate to objective outcomes were extracted and summarized descriptively. Results: Ninety-five studies with 10,807 participants were included. Most were observational (84.2%) and conducted at a single center (72.6%). Voice-related outcomes were the most common (86.3%), followed by psychological (72.6%) and swallowing outcomes (65.3%). Less frequently assessed were nutritional (22.1%) and supportive care domains (41.1%). The Voice Handicap Index family was the most used PROM group (30.5%). Over half the studies reported PROMs and objective measures separately without statistical integration (51.6%), while only 13.7% performed analytical integration, and none used predictive multivariable models. Significant variation existed in PROM choices, assessed domains, and integration approaches. Conclusions: PROM use in laryngeal cancer survivorship research is heterogeneous and predominantly focused on voice-related outcomes. Limited analytical integration with objective measures hampers a comprehensive understanding of recovery. There is a need for standardized, multidimensional assessment frameworks that include functional, nutritional, psychosocial, and objective outcomes to effectively support patient-centered survivorship care and rehabilitation planning. Full article

Rapid identification of fish disease lesions is essential for disease monitoring and early intervention in aquaculture, yet existing detection methods rely heavily on extensive lesion annotations and fixed category definitions. To address the challenges of limited annotated data and heterogeneous supervision, this study proposes PaliGemma2-FishGrounding, a generative vision-language grounding framework for few-shot fish disease lesion localization. The framework reformulates lesion detection as an open-vocabulary grounding task and unifies lesion localization, disease recognition, health-status classification, and symptom understanding within a single instruction-learning paradigm. By integrating heterogeneous supervision from multiple fish disease datasets, the proposed method enables lesion localization through structured vision-language generation rather than conventional closed-set detection. Experimental results on an Epizootic Ulcerative Syndrome (EUS) lesion dataset demonstrate that the proposed framework outperforms YOLOv8-based baselines, achieving an AP50 of 0.3659 and an AR@10 of 0.5378 while maintaining a zero invalid-box rate. Ablation studies further confirm the effectiveness of the instruction-learning strategy and grounding-based design. The results indicate that generative vision-language models can effectively leverage limited lesion annotations and auxiliary disease knowledge for fish disease analysis. This framework provides a practical solution for low-annotation disease monitoring and offers a promising direction for intelligent aquaculture applications under data-scarce conditions. Full article