Search Results (54,843)

The resource utilization of swine manure represents a critical pathway for advancing sustainable agricultural development. This study, based on survey data from 509 swine farmers in Sichuan Province, employs the Ordered Probit (Oprobit) model and the Conditional Mixed Process (CMP) model to analyze the mechanisms and pathways through which cognition about manure treatment, environmental regulation, and their interaction influence farmers’ behaviors towards manure resource utilization. It further delves into the heterogeneous characteristics of influencing factors. The findings reveal the following: (1) Farmers possess a high level of cognition regarding manure treatment, while environmental regulation is moderately implemented. The principal methods of manure resource utilization focus on recycling to fields and organic fertilizer production, with over 95% of farmers adopting at least one method of resource utilization. (2) Both cognition of manure treatment and environmental regulation significantly promote the behavior of manure resource utilization. There are substitutive or complementary effects between moral cognition and constraint regulation, as well as capability cognition and guidance regulation. (3) Among the farming community, the behavior of large-scale farmers is mainly influenced by moral cognition, whereas non-large-scale farmers are more affected by capability cognition and guidance regulation; middle-aged and young farmers are predominantly influenced by capability cognition, incentives, and guidance regulation, whereas the older generation of farmers is driven more by moral cognition and guidance regulation. Based on these insights, this study proposes targeted strategies for enhancing cognition and regulatory alignment across different groups, aiming to elevate the level of manure resource utilization and promote the green transformation of livestock farming. Full article

Background: Large-cell carcinoma (LCC) and large-cell neuroendocrine carcinoma (LCNEC) are kinds of rare lung tumors classified as distinct forms of non-small-cell lung cancer (NSCLC). They both differ in cellular morphology, neuroendocrine marker expression, and clinical outcomes. Thus, LCC and LCNEC exhibit different clinicopathological characteristics and survival outcomes. This study seeks to assess how clinicopathological and immunohistochemical features influence the need for adjuvant chemotherapy in individuals with early-stage, surgically resected LCC or LCNEC. Methods: This multicenter retrospective analysis included 79 patients who underwent surgical resection for large-cell carcinoma (LCC) or large-cell neuroendocrine carcinoma (LCNEC) between January 2008 and March 2025. We evaluated prognostic factors that influence survival in patients with LCC and LCNEC and assessed the effect of adjuvant chemotherapy on survival outcomes. Results: This study included 79 patients—39 diagnosed with LCC and 40 diagnosed with LCNEC. All patients were in stages I–III and received curative surgery. The median age was 61 years for LCC patients and 58.5 years for LCNEC patients. The median overall survival (mOS) was 80.1 months for patients with LCC and 34.2 months for those with LCNEC. Multivariate Cox regression analysis revealed that age (HR: 0.279), stage (HR: 0.198), and chromogranin A expression (HR: 0.088) were independent prognostic factors for overall survival in LCC patients. In LCNEC patients, stage (HR: 0.20), synaptophysin expression (HR: 0.30), type of surgery (HR: 0.31), and adjuvant chemotherapy (HR: 0.264) were identified as factors influencing overall survival. Adjuvant chemotherapy improved overall survival in LCNEC patients (67.0 vs. 17.8 months). Conclusions: Patients with LCNEC generally have poorer prognoses than those with LCC, exhibiting reduced overall survival periods. Disease stage is the most significant factor influencing overall survival for both groups. Notably, in LCNEC patients, adjuvant chemotherapy was found to independently improve survival outcomes regardless of stage. Full article

Although previous studies have examined various factors that influence biceps brachii activation, such as grip position, load, and exercise variation, to our knowledge, no prior studies have compared muscle activation during a traditional biceps curl and a Bayesian cable curl. Therefore, this study aimed to examine the differences in biceps brachii muscle activation between these two training modalities. Data from eleven volunteers (age: 25 ± 6 y; weight: 86 ± 13 kg; height: 177 ± 8 cm) were included in the analysis. Muscle activity was assessed using the normalized root mean square (RMS) values obtained from surface electromyography (sEMG). A within-subjects, counterbalanced design was utilized where all participants completed both testing conditions in a randomized order to control for potential order effects. Participants visited the laboratory and fitness center on two occasions. On the first day, anthropometric measurements were obtained, along with one repetition maximum (1-RM) for both the dumbbell biceps curl and the Bayesian curl. On the second day, participants performed an isometric maximal voluntary contraction (MVC), followed by electromyographic assessment of muscle activity during the dumbbell biceps curl and the Bayesian curl, each performed at 80% of their respective 1-RM. When the normal distribution was confirmed via the Shapiro–Wilk test (p > 0.05), a paired t-test was used for statistical analysis. On the other hand, when normality was not confirmed, the Wilcoxon test was utilized. Statistically significant differences (p = 0.003) were observed in the EMG amplitude (%) between the biceps curl (111.46 ± 26.80) and the Bayesian curl (93.39 ± 15.65) with a large effect size (d = 0.82). Based on the EMG analysis, the dumbbell biceps curl elicited significantly greater muscle activation compared to the Bayesian curl, suggesting that the conventional movement places a higher mechanical and neuromuscular demand on the biceps brachii. Full article

The antibacterial properties of Ag(I) coordination compounds are well documented; however, their effectiveness is highly dependent on the choice of appropriate ligands, and it is frequently hindered by their low water solubility and limited bioavailability. Herein, six new Ag(I) complexes incorporating the quinazolinone thioamide mqztH (=2-mercapto-4(3H)-quinazolinone) and phosphine co-ligands were synthesized and investigated for their antibacterial activity. In vitro activity assays against Escherichia coli (E. coli) and Staphylococcus aureus (S. aureus) bacterial strains revealed that all complexes selectively inhibited S. aureus bacterial growth. Structure–activity relationship analysis showed that monodentate PPh₃ co-ligands play a key role in enhancing the antibacterial efficacy of their complexes. Notably, complex [AgCl(mqztH)(PPh₃)₂] (1) exhibited broad-spectrum activity, with IC₅₀ values of 4.2 ± 1.4 μg mL^–1 (4.9 μΜ) for S. aureus and 63 ± 1.9 μg mL^–1 (75 μΜ) for E. coli bacteria. To improve solubility and antibacterial activity, complex 1 was encapsulated in barium alginate (BaAlg) matrices to form hydrogel-based drug delivery formulations [¹]@BaAlg. The synthesized formulations retained the bactericidal effect of the complex, achieving comparable activity at concentrations lower by an order of magnitude compared to complex 1 in free form. Combined with the demonstrated high biocompatibility of complex 1 toward L929 normal eukaryotic cells, as well as the biocompatible nature of the alginate matrix, these findings underscore the strong potential of the complex 1-loaded hydrogel formulations for further investigation and development as effective antibacterial drug platforms. Mechanistic studies confirmed the redox-active nature of complex 1 and its potential to inhibit the function of glutathione reductase (GR) and thioredoxin reductase (TrxR) at low concentrations, suggesting the interference with bacterial redox homeostasis as a relevant mechanism of bioactivity. Full article

Purpose: Luggage X-rays suffer from low contrast, material overlap, and noise; dual-energy imaging reduces ambiguity but creates colour biases that impair segmentation. This study aimed to (1) employ connotative fusion by embedding realistic detonator patches into real X-rays to simulate threats and enhance unattended detection without requiring ground-truth labels; (2) thoroughly evaluate fusion techniques in terms of balancing image quality, information content, contrast, and the preservation of meaningful features. Methods: A total of 1000 X-ray luggage images and 150 detonator images were used for fusion experiments based on deep learning, transform-based, and feature-driven methods. The proposed approach does not need ground truth supervision. Deep learning fusion techniques, including VGG, FusionNet, and AttentionFuse, enable the dynamic selection and combination of features from multiple input images. The transform-based fusion methods convert input images into different domains using mathematical transforms to enhance fine structures. The Nonsubsampled Contourlet Transform (NSCT), Curvelet Transform, and Laplacian Pyramid (LP) are employed. Feature-driven image fusion methods combine meaningful representations for easier interpretation. Singular Value Decomposition (SVD), Principal Component Analysis (PCA), Random Forest (RF), and Local Binary Pattern (LBP) are used to capture and compare texture details across source images. Entropy (EN), Standard Deviation (SD), and Average Gradient (AG) assess factors such as spatial resolution, contrast preservation, and information retention and are used to evaluate the performance of the analysed methods. Results: The results highlight the strengths and limitations of the evaluated techniques, demonstrating their effectiveness in producing sharpened fused X-ray images with clearly emphasized targets and enhanced structural details. Conclusions: The Laplacian Pyramid fusion method emerges as the most versatile choice for applications demanding a balanced trade-off. This is evidenced by its overall multi-criteria balance, supported by a composite (geometric mean) score on normalised metrics. It consistently achieves high performance across all evaluated metrics, making it reliable for detecting concealed threats under diverse imaging conditions. Full article

Students with autism spectrum disorder (ASD) often face difficulties in solving arithmetic word problems, particularly in transitioning from informal counting strategies to more efficient methods based on number facts and formal operations. This study examined the development of problem-solving strategies in a single student with ASD and intellectual disability across two sequential single-case experiments using multiple baseline designs. Study 1 (age 13 years 9 months; 17 sessions) employed Modified Schema-Based Instruction (MSBI) to teach addition and subtraction change problems, while Study 2 (age 14 years 10 months; 18 sessions) utilized the Conceptual Model-based Problem Solving (COMPS) approach for multiplication and division equal-group problems. Success was defined as both correctness of the response and correctly identifying the required operation. Results indicated that the student’s performance improved in all problem types in both studies, with maintenance observed 8 weeks after Study 1 and 5 weeks after Study 2. Instruction effects generalized to two-step addition and subtraction problems in Study 1, and to two-step addition and multiplication problems in Study 2. The findings indicate that both MSBI and COMPS facilitated the student’s shift from informal strategies to efficient operation-based problem solving. Implications for practice include the need for individualized reinforcements, careful adaptation of instruction, and providing teachers with a variety of problems and knowledge of these teaching methods to support students with ASD in developing advanced problem-solving skills. Full article

Background and Aims: Severe acute respiratory distress syndrome (ARDS) in patients with long COVID remains associated with extremely high mortality and significant long-term sequelae. Non-invasive ventilatory strategies such as continuous positive airway pressure (CPAP) and high-flow nasal cannula (HFNC) are widely used before endotracheal intubation (ETI). Still, their comparative effectiveness in this population is not well established. Understanding survival outcomes and sequelae can help refine treatment strategies for this high-risk group. This study aimed to evaluate outcomes, sequelae, and treatment strategies in long COVID patients with severe ARDS, focusing on non-invasive ventilatory support before ETI. Materials and Methods: A retrospective cohort analysis was performed using a study comparing severe ARDS patients with and without COVID-19. The inclusion criterion was a Horovitz quotient (PaO₂/FiO₂) < 50 mmHg. Results: The study included a total of 59 patients diagnosed with long COVID-19 ARDS, with a mortality rate of 85%. A significant proportion of the patient population was male, accounting for 75%. The highest survival rate was observed among patients who initially received CPAP support, with a survival rate of 23.08%, in contrast to those treated solely with HFNC or those who alternated between HFNC and CPAP. Among patients who required endotracheal intubation and subsequent mechanical ventilation, survival rates were 40% for those who had previously received CPAP, 10% for those treated with alternating HFNC and CPAP, and 0% for those managed exclusively with HFNC before ETI. Survivors often exhibited sequelae, such as impaired pulmonary function, persistent dyspnea, and diminished physical performance. Conclusions: Patients with long COVID who develop severe ARDS (PaO₂/FiO₂ < 50 mmHg) face exceptionally high ICU mortality, with outcomes determined mainly by age, comorbidities, and profound hypoxemia. Although CPAP showed a trend toward improved survival, the data do not establish superiority and should be regarded as hypothesis-generating. Rather, they highlight the complexity of managing this underrepresented subgroup and underscore the need for larger, multicenter studies with broader inclusion criteria to confirm or refute these preliminary observations. Full article

A reassessment of the risk-benefit balance of the two lipid nanoparticle (LNP)-based vaccines, Pfizer’s Comirnaty and Moderna’s Spikevax, is currently underway. While the FDA has approved updated products, their administration is recommended only for individuals aged 65 years or older and for those aged 6 months or older who have at least one underlying medical condition associated with an increased risk of severe COVID-19. Among other factors, this change in guidelines reflect an expanded spectrum and increased incidence of adverse events (AEs) and complications relative to other vaccines. Although severe AEs are relatively rare (occurring in < 0.5%) in vaccinated individuals, the sheer scale of global vaccination has resulted in millions of vaccine injuries, rendering post-vaccination syndrome (PVS) both clinically significant and scientifically intriguing. Nevertheless, the cellular and molecular mechanisms of these AEs are poorly understood. To better understand the phenomenon and to identify research needs, this review aims to highlight some theoretically plausible connections between the manifestations of PVS and some unique structural properties of mRNA-LNPs. The latter include (i) ribosomal synthesis of the antigenic spike protein (SP) without natural control over mRNA translation, diversifying antigen processing and presentation; (ii) stabilization of the mRNA by multiple chemical modification, abnormally increasing translation efficiency and frameshift mutation risk; (iii) encoding for SP, a protein with multiple toxic effects; (iv) promotion of innate immune activation and mRNA transfection in off-target tissues by the LNP, leading to systemic inflammation with autoimmune phenomena; (v) short post-reconstitution stability of vaccine nanoparticles contributing to whole-body distribution and mRNA transfection; (vi) immune reactivity and immunogenicity of PEG on the LNP surface increasing the risk of complement activation with LNP disintegration and anaphylaxis; (vii) GC enrichment and double proline modifications stabilize SP mRNA and prefusion SP, respectively; and (viii) contaminations with plasmid DNA and other organic and inorganic elements entailing toxicity with cancer risk. The collateral immune anomalies considered are innate immune activation, T-cell- and antibody-mediated cytotoxicities, dissemination of pseudo virus-like hybrid exosomes, somatic hypermutation, insertion mutagenesis, frameshift mutation, and reverse transcription. Lessons from mRNA-LNP vaccine-associated AEs may guide strategies for the prediction, prevention, and treatment of AEs, while informing the design of safer next-generation mRNA vaccines and therapeutics. Full article

The neuropeptide calcitonin gene-related peptide (CGRP), especially a-CGRP, is central in migraine pathophysiology. Although CGRP is a therapeutic target and potential biomarker, inconsistencies in measurement procedures need to be further studied for reliable results. This study aims to analyze factors influencing plasma CGRP measurement. Chronic migraine (CM) patients were recruited in our Headache Unit. Blood samples were collected before and during treatment with CGRP monoclonal antibodies, processed and stored. Levels of CGRP were measured with isoform-specific enzyme-linked immunosorbent assay (ELISA) tests. Statistical tests were used to assess concentration changes and group differences. The addition of protease inhibitors (PIs) to plasma samples significantly increased a-CGRP level detection, with a smaller effect on β-CGRP. No correlation was found between the a- and β-CGRP levels in plasma. The plasma-PI samples showed higher CGRP concentrations than in serum. The a-CGRP levels decreased during treatment while the β-CGRP levels remained stable. a-CGRP and age correlated negatively, but no sex-related differences were observed either for a- or β-CGRP. PI improved CGRP detection in plasma. The a-CGRP levels, which were influenced by age, decreased with specific treatment, suggesting its potential role as a biomarker. In contrast, β-CGRP remained stable, suggesting independent regulation of both isoforms. Full article

This study evaluated age-related changes in nutrient digestibility in dogs and examined the effects of physiological development and dietary composition on digestive efficiency. Twenty Beagle dogs were assigned to three groups: puppies (<1 year; n = 8), adults (3–4 years; n = 8), and seniors (10–11 years; n = 4). All animals were fed diets formulated to contain identical nutrient levels that met or exceeded the minimum recommended nutrient requirements established by the Association of American Feed Control Officials. The digestibility of dry matter (DM), crude protein (CP), ether extract (EE), nitrogen-free extract (NFE), calcium (Ca), phosphorus (P), and amino acids were compared among the groups. The results showed that NFE digestibility was significantly higher in puppies, whereas CP digestibility was lower than that in adults and seniors, likely due to immature digestive function. In addition, EE digestibility was significantly lower in puppies, whereas P digestibility decreased with age. No significant difference was observed in Ca digestibility. Amino acid digestibility is lower in puppies, particularly for essential amino acids such as lysine, isoleucine, histidine, and arginine. These results indicate that age-related differences in digestive physiology and protein source affect nutrient utilization, providing a basis for developing life stage-specific nutritional strategies for companion animals. Full article

Background: Artificial Intelligence (AI) is increasingly applied in endurance sports to optimize performance, enhance recovery, and personalize nutrition and supplementation. This review synthesizes current knowledge on AI applications in endurance sports, emphasizing implications for metabolic health, nutritional strategies, and recovery optimization, while also addressing ethical considerations and future directions. Methods: A narrative review was conducted using targeted searches of PubMed, Scopus, and Web of Science with cross-referencing. Extracted items included sport/context, data sources, AI methods including machine learning (ML), validation type (internal vs. external/field), performance metrics, comparators, and key limitations to support a structured synthesis; no formal risk-of-bias assessment or meta-analysis was undertaken due to heterogeneity. Results: AI systems effectively integrate multimodal physiological, environmental, and behavioral data to enhance metabolic health monitoring, predict recovery states, and personalize nutrition. Continuous glucose monitoring combined with AI algorithms allows precise carbohydrate management during prolonged events, improving performance outcomes. AI-driven supplementation strategies, informed by genetic polymorphisms and individual metabolic responses, have demonstrated enhanced ergogenic effectiveness. However, significant challenges persist, including measurement validity and reliability of sensor-derived signals and overall dataset quality (e.g., noise, missingness, labeling error), model performance and generalizability, algorithmic transparency, and equitable access. Furthermore, limited generalizability due to homogenous training datasets restricts widespread applicability across diverse athletic populations. Conclusions: The integration of AI in endurance sports offers substantial promise for improving performance, recovery, and nutritional strategies through personalized approaches. Realizing this potential requires addressing existing limitations in model performance and generalizability, ethical transparency, and equitable accessibility. Future research should prioritize diverse, representative, multi-site data collection across sex/gender, age, and race/ethnicity. Coverage should include performance level (elite to recreational), sport discipline, environmental conditions (e.g., heat, altitude), and device platforms (multi-vendor/multi-sensor). Equally important are rigorous external and field validation, transparent and explainable deployment with appropriate governance, and equitable access to ensure scientifically robust, ethically sound, and practically relevant AI solutions. Full article

Recent advances in molecular biology have led to the development of RNA-based therapeutics, offering significant promise for treating various eye diseases. Current RNA therapeutics include RNA aptamers, antisense oligonucleotides (ASOs), small interfering RNA (siRNA), and messenger RNA (mRNA) that can target specific genetic and molecular pathways involved in eye disorders. In addition to their potential in therapy, RNA technologies have also provided tools for mechanistic studies to improve the understanding of eye diseases, expanding the possibilities of RNA-based treatments. Despite the utility of RNA in studying eye disease mechanisms and its potential in disease treatment, only a few RNA-based therapies have been approved for posterior eye diseases. This paper reviews RNA interference and related ocular delivery and posterior eye diseases, focusing on the use of RNA aptamers, siRNA, short hairpin RNA (shRNA), and microRNA (miRNA). Approaches using RNA to advance our understanding of eye diseases and disease treatments, particularly in the posterior segment of the eye, are discussed. It is concluded that RNA therapeutics offer a novel approach to treating a variety of eye diseases by targeting their molecular causes. siRNA, shRNA, miRNA, and ASO can directly silence disease-driving genes, while RNA aptamers bind to specific targets. Although many RNA-based therapies are still in experimental stages, they hold promise for conditions such as age-related macular degeneration (AMD), diabetic macular edema (DME), glaucoma, and inherited retinal disorders. Effective delivery methods and long-term safety are key challenges that need to be addressed for these treatments to become widely available. Full article

Background: Dental anxiety is a common challenge in paediatric dentistry, often leading to avoidance of treatment and compromised oral health. Non-pharmacological interventions such as music therapy have gained increasing attention as safe and cost-effective alternatives to pharmacological approaches. Although several clinical studies have examined the impact of music on children’s dental anxiety, the evidence has not yet been systematically summarised with quantitative synthesis. Objective: This systematic review and meta-analysis aimed to evaluate the effectiveness of music therapy in reducing dental anxiety and fear among paediatric patients. Methods: A comprehensive literature search was conducted in PubMed, Scopus, Web of Science, and Cochrane Library from inception to August 2025. Randomised controlled trials (RCTs) evaluating music therapy for dental anxiety in children were included. Primary outcomes were self-reported dental anxiety/fear scales and physiological measures (heart rate, blood pressure, oxygen saturation). Risk of bias was assessed using the revised Cochrane risk of bias tool (RoB 2, version 2019; Cochrane Collaboration, London, UK) Meta-analyses were performed using a random-effects model with Review Manager (RevMan, version 5.4; Cochrane Collaboration, London, UK). Results: Seven randomized controlled trials (RCTs) involving 476 children aged 4–14 years were included. Music therapy significantly reduced self-re-ported dental anxiety compared with control groups (SMD = −0.48, 95% CI: −0.72 to −0.25, p < 0.001). Heart rate was also significantly reduced (SMD = −0.42, 95% CI: −0.68 to −0.16, p = 0.002), whereas changes in blood pressure and oxygen saturation were not statistically significant. The overall risk of bias was moderate, with most concerns related to blinding. Conclusions: Music therapy is an effective non-pharmacological intervention to reduce dental anxiety in children, particularly improving subjective anxiety and physiological arousal as measured by heart rate. Its integration into paediatric dental practice may enhance cooperation and treatment outcomes, offering a safe, inexpensive, and child-friendly approach. Full article

Background/Objectives: Sarcopenia is common in patients with diabetes mellitus. The use of branched-chain amino acids may influence muscle mass. The aim of this study is to evaluate the effect of a diabetes-specific formula enriched with calcium hydroxy-methyl-butyrate (CaHMB) on muscle mass in patients with diabetes and high risk of malnutrition. Methods: A prospective observational study in 95 patients divided into two cohorts of patients with diabetes, treated with a tailored diet, dietary counseling, and diabetes-specific oral nutritional supplements (ONSs) administered between meals: one enriched with CaHMB (CaHMB Diabetes ONS) 44 (46.32%) patients; and another without CaHMB (Diabetes-Specific ONS) 51 (53.68%) patients. Anthropometric parameters, bioimpedance, artificial intelligence (AI)-assisted ultrasound of the rectus femoris muscle (PIIXMED^TM), and handgrip strength were assessed. Evaluations were conducted at baseline and after 3 months. Results: The mean age was 71.05 (10.67) years; 56.8% were male. After three months, both groups increased their nutritional intake with no differences in dietary protein content between groups. The CaHMB group showed a greater increase in muscle mass as measured by ultrasound, both in muscle area (CaHMB ONS: +5.84 (−3.3 ± 21.58)% vs. Diabetes-Specific ONS: −9.34% (−25.78 ± 12.02)%; p < 0.01) and muscle thickness (CaHMB ONS: +9.17 (−4.40 ± 21.05)% vs. Diabetes-Specific ONS −6.30 (−18.57 ± 12.56)%; p < 0.01). The CaHMB ONS group showed a higher likelihood of increased muscle mass compared to the Diabetes-Specific ONS, with an odds ratio (OR) of 9.31 (95%CI: 2.16–40.13) for thickness and 3.96 (95%CI: 1.11–14.13) for area, adjusted for gender, age, serum albumin, and baseline glycated hemoglobin. Conclusions: Supplementation with Ca-HMB in patients with diabetes and high risk of malnutrition showed significant improvements in muscle mass as assessed by AI-assisted ultrasound. Both groups increased nutritional intake, but only the CaHMB group showed specific benefits in muscle parameters. Full article

Background: Individuals with generalized joint hypermobility (GJH) often exhibit altered sensorimotor control, which may contribute to balance and proprioception deficits. This study investigated the effects of sensory training applied to the plantar surface on sensorimotor organization components, including light touch, vibration, two-point discrimination, proprioception, muscle strength, and balance, in individuals with GJH. Methods: This randomized controlled trial included 65 asymptomatic individuals aged 18–25 years with a Beighton score of 5 or higher. The participants were randomly assigned to either the treatment (n = 32) or control (n = 33) group. The treatment group was given a 2-week home program that included plantar sensory training and an informative brochure on healthy foot care; the control group was given only the brochure. Light touch, two-point discrimination, vibration sense, proprioception, muscle strength, and balance parameters were assessed before and after the intervention. Results: Compared to the control group, the treatment group demonstrated significant improvements in light touch (p < 0.01), two-point discrimination (p < 0.01), vibration sense (p < 0.01), and proprioceptive accuracy (p < 0.01). Balance performance improved markedly in the posterolateral direction (+8.3 cm, p < 0.01), while anterior and posteromedial directions showed moderate but nonsignificant gains. Muscle strength showed no statistically significant changes across groups (p > 0.05). The control group exhibited no meaningful pre-post changes. Conclusions: Sensory training directed at the plantar surface results in positive changes in various components of sensorimotor organization in individuals with GJH. Full article