OBJECTIVE: To explore the genetic etiology of 46 Chinese pedigrees affected with Hereditary multiple exostoses (HME) and provide genetic counseling and reproductive intervention. METHODS: Whole-exome sequencing and Sanger sequencing were carried out on 87 patients from the 46 pedigrees to analyze the variants of EXT1 and EXT2 genes. Pathogenicity of the variants was assessed based on the guidelines from the American College of Medical Genetics and Genomics and Association for Molecular Pathology (ACMG/AMP). Prenatal diagnosis and preimplantation genetic testing (PGT) were provided for couples with identified pathogenic mutations. This study was approved by the Medical Ethics Committee of the hospital (Ethics No.: LL-SC-SG-2014-010). RESULTS: In total 17 and 22 pathogenic variants were respectively identified in the EXT1 and EXT2 genes, among which 5 EXT1 and 12 EXT2 variants were unreported previously. Three patients with no family history were found to harbor de novo variants of the EXT1 gene. Twenty nine couples had opted for PGT or underwent prenatal diagnosis following natural conception, and 17 healthy babies were born. CONCLUSION This study has clarified the genetic etiology of 45 HME pedigrees and identified 17 novel variants, which has enriched the mutational spectrum of the EXT1 and EXT2 genes. Reproductive intervention through PGT and prenatal diagnosis have prevented the recurrence of HME in these families.
Humans ; Female ; Male ; Pedigree ; Exostoses, Multiple Hereditary/diagnosis* ; N-Acetylglucosaminyltransferases/genetics* ; Adult ; Exostosin 1 ; Asian People/genetics* ; Genetic Testing ; Exostosin 2 ; Mutation ; China ; Prenatal Diagnosis ; Pregnancy ; Genetic Counseling ; Preimplantation Diagnosis ; Exome Sequencing ; East Asian People

Aberrant activation of glycolysis represents a key metabolic mechanism underlying the initiation and progression of nasal inflammation. Allergic rhinitis, chronic rhinosinusitis, and vasomotor rhinitis exhibit distinct etiologies, yet all are characterized by inflammatory responses, impaired epithelial barrier function, and neurovascular dysregulation, in which glycolytic metabolic reprogramming acts as a central hub connecting immunometabolism and inflammatory regulation.Recent evidence indicates that glycolysis-dependent activation of immune cells provides the essential energy basis for inflammatory onset. In dendritic cells, eosinophils, mast cells, and Th2 cells, the expression of key glycolytic enzymes including HK2, PKM2, and LDHA is upregulated, thereby promoting cellular activation and proinflammatory cytokine release via the mTOR-HIF-1α signaling axis. Notably, the metabolic reprogramming of eosinophils prolongs their survival and enhances the release of cytotoxic granules, while in mast cells, enhanced glycolysis facilitates IgE-mediated degranulation and histamine release. Furthermore, glycolysis also influences the Th17/Treg balance, with enhanced glycolytic flux promoting Th17 differentiation and contributing to the heterogeneous inflammatory profiles observed across different rhinitis subtypes.As a central metabolite, lactate contributes to the formation of a metabolism-inflammation vicious cycle through multiple mechanisms. Lactate acidifies the local microenvironment to activate TRPV1 channels and facilitate neuropeptide release, mediates immune cell chemotaxis through GPR81, and regulates gene expression via histone lactylation, thereby sustaining proinflammatory gene transcription. These lactate-mediated processes collectively amplify local inflammation and contribute to the persistence of nasal symptoms.Glycolytic reprogramming in epithelial cells is modulated by the EGF/EGFR pathway, and its dysregulation may result in disrupted tight junctions, abnormal goblet cell hyperplasia, and subsequent tissue remodeling. Substance P and calcitonin gene-related peptide released from sensory neurons, in conjunction with metabolic products, synergistically maintain persistent inflammatory stimulation by activating mast cells, forming a neuro-immune-metabolic regulatory network that drives disease chronicity.From a therapeutic perspective, glycolytic inhibitors such as 2-deoxyglucose, FX11, and 3-bromopyruvate exert anti-inflammatory effects by targeting key enzymes including HK2 and LDHA, each with distinct mechanisms: 2-DG competitively inhibits hexokinase, FX11 selectively targets LDHA to reduce lactate production, and 3-BrPA modulates multiple glycolytic enzymes. Moreover, traditional Chinese medicine formulas, monomeric active components, and small-molecule compounds have shown promising potential in alleviating nasal inflammation by regulating the mTOR-HIF-1α axis, exerting antioxidant effects, and modulating endoplasmic reticulum stress pathways. The multi-target characteristics of these natural products offer advantages in addressing the complex pathophysiology of nasal inflammatory diseases.Despite these advances, several challenges remain. The non-selective inhibition of glycolysis may interfere with epithelial repair and mucosal regeneration, leading to delayed wound healing. Technical limitations in dynamic metabolic monitoring and sampling precision hinder the accurate assessment of local nasal metabolism. Furthermore, current animal models, which predominantly rely on acute stimulation protocols, inadequately recapitulate the chronic tissue remodeling processes characteristic of human rhinitis.This review systematically summarizes glycolysis as a common metabolic node shared by different rhinitis subtypes, offering a novel theoretical basis for the development of precision therapeutic strategies targeting metabolic reprogramming.

Aberrant activation of glycolysis represents a key metabolic mechanism underlying the initiation and progression of nasal inflammation. Allergic rhinitis, chronic rhinosinusitis, and vasomotor rhinitis exhibit distinct etiologies, yet all are characterized by inflammatory responses, impaired epithelial barrier function, and neurovascular dysregulation, in which glycolytic metabolic reprogramming acts as a central hub connecting immunometabolism and inflammatory regulation.Recent evidence indicates that glycolysis-dependent activation of immune cells provides the essential energy basis for inflammatory onset. In dendritic cells, eosinophils, mast cells, and Th2 cells, the expression of key glycolytic enzymes including HK2, PKM2, and LDHA is upregulated, thereby promoting cellular activation and proinflammatory cytokine release via the mTOR-HIF-1α signaling axis. Notably, the metabolic reprogramming of eosinophils prolongs their survival and enhances the release of cytotoxic granules, while in mast cells, enhanced glycolysis facilitates IgE-mediated degranulation and histamine release. Furthermore, glycolysis also influences the Th17/Treg balance, with enhanced glycolytic flux promoting Th17 differentiation and contributing to the heterogeneous inflammatory profiles observed across different rhinitis subtypes.As a central metabolite, lactate contributes to the formation of a metabolism-inflammation vicious cycle through multiple mechanisms. Lactate acidifies the local microenvironment to activate TRPV1 channels and facilitate neuropeptide release, mediates immune cell chemotaxis through GPR81, and regulates gene expression via histone lactylation, thereby sustaining proinflammatory gene transcription. These lactate-mediated processes collectively amplify local inflammation and contribute to the persistence of nasal symptoms.Glycolytic reprogramming in epithelial cells is modulated by the EGF/EGFR pathway, and its dysregulation may result in disrupted tight junctions, abnormal goblet cell hyperplasia, and subsequent tissue remodeling. Substance P and calcitonin gene-related peptide released from sensory neurons, in conjunction with metabolic products, synergistically maintain persistent inflammatory stimulation by activating mast cells, forming a neuro-immune-metabolic regulatory network that drives disease chronicity.From a therapeutic perspective, glycolytic inhibitors such as 2-deoxyglucose, FX11, and 3-bromopyruvate exert anti-inflammatory effects by targeting key enzymes including HK2 and LDHA, each with distinct mechanisms: 2-DG competitively inhibits hexokinase, FX11 selectively targets LDHA to reduce lactate production, and 3-BrPA modulates multiple glycolytic enzymes. Moreover, traditional Chinese medicine formulas, monomeric active components, and small-molecule compounds have shown promising potential in alleviating nasal inflammation by regulating the mTOR-HIF-1α axis, exerting antioxidant effects, and modulating endoplasmic reticulum stress pathways. The multi-target characteristics of these natural products offer advantages in addressing the complex pathophysiology of nasal inflammatory diseases.Despite these advances, several challenges remain. The non-selective inhibition of glycolysis may interfere with epithelial repair and mucosal regeneration, leading to delayed wound healing. Technical limitations in dynamic metabolic monitoring and sampling precision hinder the accurate assessment of local nasal metabolism. Furthermore, current animal models, which predominantly rely on acute stimulation protocols, inadequately recapitulate the chronic tissue remodeling processes characteristic of human rhinitis.This review systematically summarizes glycolysis as a common metabolic node shared by different rhinitis subtypes, offering a novel theoretical basis for the development of precision therapeutic strategies targeting metabolic reprogramming.

Background/Aims: Chronic constipation is prevalent yet under-diagnosed across Asia, compromising quality of life and burdening healthcare systems. Cultural stigma, varied diets, and limited access to standardized diagnostic tools delay timely care. Methods: The Bali Chronic Constipation Roundtable in November 2024, brought together experts from 11 Asian countries. The group reviewed epidemiological data, analyzed multinational questionnaire on clinical practice pattern, and conducted structured discussions to identify key barriers and propose region-specific recommendations. Results: Chronic constipation prevalence varies across Asia, ranging from 1.8% in India to 16.6% in Japan, with women and the elderly disproportionately affected. Under-reporting persists owing to cultural taboos and widespread self treatment with laxatives and traditional medications. Although the Rome IV criteria remains the global standard, they may not fully reflect Asian symptom profiles, and diagnosis is limited by scarce motility laboratories. First line therapies such as dietary-fiber optimization and osmotic laxatives are widely available, but newer pharmacotherapies (prucalopride, linaclotide, lubiprostone, and elobixibat) remain costly and unevenly accessible. Biofeedback for dyssynergic defecation is underutilized due to limited availability. Experts recommend expanded regional research on to refine diagnostic criteria, coupled with enhanced physician education and public awareness. They advocate accessibility to second-line and novel therapies that incorporate culturally attuned regional guidelines, and improved access to gastrointestinal motility testing. Conclusions The Bali Chronic Constipation Roundtable highlighted Asia’s need for region specific diagnostics and management. Addressing diagnostic and treatment gaps will improve outcomes, while ongoing researcher clinician policy collaboration must standardize guidelines, advance research, and ensure equitable care across Asia.

Objectives: . Idiopathic sudden sensorineural hearing loss (ISSNHL) is a significant cause of hearing loss. Intratympanic steroid injection (ITSI) is commonly used as an initial or salvage treatment; however, the lack of a standardized treatment protocol has resulted in variability in clinical practice. In addition, no efficient prediction model currently exists to support personalized management. Therefore, this study aimed to develop tailored management strategies for ISSNHL using a machine-learning model. Methods: . This retrospective multicenter cohort study was conducted between January 2015 and December 2020, with data analysis performed between January 2021 and March 2024. Patients were selected based on the International Classification of Diseases, 10th Revision criteria for ISSNHL, along with relevant medication and procedure codes. Patients with pure-tone audiogram results not meeting ISSNHL criteria, better initial hearing in the affected ear, an identifiable etiology, no post-treatment audiogram, or delayed treatment (>6 weeks) were excluded. We included 770 patients diagnosed with ISSNHL who received ITSI. The primary outcome was the area under the receiver operating characteristic curve for prediction performance. Recovery status was determined using the last pure-tone audiogram. Modeling was conducted on the Quanta for Medical Care AI platform using five machine-learning algorithms and a nested cross-validation framework, in which feature selection and hyperparameter tuning were performed in the inner folds and model performance was evaluated in the outer folds. Results: . A random forest classifier outperformed the other models in predicting hearing outcomes, achieving an area under the receiver operating characteristic curve of 0.788. Time to ITSI was the most influential treatment-related factor, with ITSI administered within 10 days of hearing loss being associated with better outcomes. This model can be used to provide personalized prognostic estimates under different treatment protocols. Conclusion . The machine-learning-based prediction model facilitates personalized treatment strategies and timely treatment adjustments for ISSNHL, thereby optimizing the likelihood of complete recovery.

With the continuous deepening of the concept of precision diagnosis and treatment for lung cancer, how to achieve higher efficiency and accuracy in the screening, diagnosis, and treatment pathways in clinical practice has become an important issue that urgently needs to be overcome. The current clinical difficulty lies in the fact that despite continuous advancements in imaging and molecular diagnostic technologies, there are still limitations in manual efficiency and subjective experience when it comes to massive data analysis and multi-scale feature extraction. Artificial intelligence (AI), especially algorithm systems based on deep learning, is an innovative technology capable of deeply empowering medical big data. This method utilizes algorithms such as convolutional neural networks, combined with radiomics, pathomics, and multi-modal data fusion analysis, demonstrating immense potential in early precise detection and benign-malignant differentiation of pulmonary nodules, digital pathological subtype recognition and non-invasive prediction of driver genes, precise 3D surgical planning and automatic delineation of radiotherapy target volumes, as well as dynamic risk warning during follow-up. This innovative technology provides a brand-new solution for realizing intelligent and individualized lung cancer diagnosis and treatment models. This consensus, based on the latest evidence from evidence-based medicine and combined with the development trends in the AI field and real-world clinical needs, was ultimately formed by gathering the consensus opinions of multidisciplinary experts in radiology, pathology, thoracic surgery, and other fields. The main content covers the application specifications of AI in the three core scenarios of lung cancer screening, diagnosis, and treatment, the technical standards for data collection and algorithm validation, as well as the ethical and regulatory challenges faced at the current stage. It aims to clarify the applicable boundaries of AI as a clinical auxiliary decision support tool, providing scientific guidance and standardized exploration directions for peers currently engaged in or planning to carry out AI-assisted clinical diagnosis, treatment, and translation of lung cancer.

Introduction: Adequate knowledge of diabetes is essential for effective self-management and glycemic control. Emerging trends in digital platforms, video-based education offer a scalable and accessible approach to patient learning. However, evidence on the effectiveness of validated YouTube-based diabetes education in the Malaysian population remains limited. We aimed to evaluate the impact of a newly developed, tri-language YouTube diabetes education programme on clinical and knowledge outcomes. Methodology: In this multicentre study, patients with diabetes mellitus were randomly assigned to intervention (YouTube-based education) and control groups (standard care). The intervention consisted of newly developed and validated short educational videos on YouTube regarding diabetes, complications and lifestyle changes, delivered weekly via WhatsApp over 9 weeks. Videos were available in English, Malay and Chinese. The control group received standard care and counseling. Demographic data, hemoglobin A1c (HbA1c), and knowledge scores were collected at baseline and 3 months post-intervention. Results: A total of 109 patients (62.4% female; mean age 53.2 years; mean diabetes duration 16.3 years) were enrolled in the study, with similar baseline characteristics between groups. The intervention group demonstrated significantly greater improvement in glycemic control compared to the control group (HbA1c: −1.22 ± 1.36% vs. −0.24 ± 1.05%; p <0.001). While knowledge scores improved in both groups, the increase was significantly greater in the intervention group (2.66 vs. 0.80; p = 0.001). Notably, improvement in knowledge score predicted HbA1c reduction (b = 0.091; 95% CI 0.01, 0.172; p = 0.028). Conclusion The tri-language YouTube-based diabetes education programme significantly improved both glycemic control and patients’ knowledge. This accessible, scalable video-based education represents an effective strategy to enhance diabetes selfmanagement, offering flexible, on-demand learning for diverse populations.
Social Media ; Diabetes Mellitus

Introduction: The 2021 IDF-DAR risk calculator had been previously evaluated in multiple studies and subsequently widely accepted and applied in clinical practice as a practical standardized tool for patient risk stratification. Recently updated, the 2026 IDF-DAR Risk calculator enables a more individualized, evidence-related evaluation of patientrelated and disease-related risk factors, incorporating modern diabetes technologies, including continuous glucose monitoring (CGM), automated insulin delivery (AID) systems, and advanced insulin formulations to enhance risk stratification. This tool allows medical professionals to tailor Ramadan practices based on overall factors toward promoting safe fasting. Methodology: This prospective multicentre observational study recruited adults with Type 1 and Type 2 diabetes attending public hospitals nationwide. People with diabetes (PwD) intending to perform Ramadan fasting were invited to participate and assessed using the 2026 IDF-DAR Risk Calculator in the 6-week pre-Ramadan period between 30th January and 19th March 2026. Results: A total of 458 PwD were evaluated and stratified into low (15.7%), moderate (41%), and high risk (43.3%) categories. Most participants had Type 2 diabetes (83.6%), with 60.3% having a disease duration exceeding 10 years and 43% exhibiting poor glycemic control (hemoglobin A1c >9%). Insulin therapy was used by 76.4% of participants, including two individuals with Type 1 diabetes using AID systems. Most participants reported no recent hypoglycemia (76.4%), 81.0% performed glucose monitoring, and 3.3% used CGM. Severe comorbidities were uncommon, with 1.1% having unstable macrovascular disease and 4.4% advanced chronic kidney disease (estimated glomerular filtration rate <30). Notably, 72.2% received structured Ramadan education. Conclusion Majority of PwD attending tertiary diabetes clinics were in the moderate- to high-risk category and intended to fast despite medical advice against fasting in some cases. Although most participants were on insulin therapy, hypoglycemia was low in the pre-Ramadan period. Integration of modern technologies, advanced insulin therapies, and structured education may support safer fasting practices.
Risk Assessment ; Diabetes Mellitus ; Hospitals ; Fasting

Objective This study aimed to investigate the genetic diversity, differentiation, and population structure of Aedes albopictus across different geographical regions in Shandong Province, and to explore the relationship between genetic diversity and geographical distribution. Methods Between July and August 2024, ten Ae. albopictus populations were sampled from seven cities in Shandong Province. Genomic DNA was extracted from individual mosquitoes, and the mitochondrial cytochrome c oxidase subunit I(COⅠ)gene was amplified using PCR and sequenced. The obtained sequences were verified using BLAST and analyzed with MAFFT, MEGA 11, DnaSP v6.12, Arlequin 3.5, PopART 1.7, STRUCTURE 2.3.4 and the R packages adegenet and vegan to assess genetic diversity and population structure. Results A total of 229 COⅠ sequences(662 bp) was obtained, revealing ten variable sites with no insertions or deletions. The overall base composition showed an AT bias of 67.7%. Haplotype analysis identified 11 haplotypes, with Hap2 being the dominant and most widely distributed haplotype across all populations. Neutrality tests showed significant population expansion only in the Rizhao population. Mantel testing result revealed that geographical distance does not significantly impede gene flow. Overall, genetic differentiation among populations was low, indicating frequent gene flow. When combined with additional samples from Shanghai, Fujian, Guangdong, Yunnan, Hainan and Guangxi, STRUCTURE, UPGMA and DAPC analyses revealed two primary genetic clusters of Ae. albopictus. Conclusions Ae. albopictus populations in Shandong Province exhibit frequent gene flow, low genetic differentiation, and relatively low overall genetic diversity. However, the Rizhao population showed signs of recent expansion, highlighting the need for enhanced surveillance and targeted control measures in this area.

OBJECTIVE To comprehensively evaluate the different drying methods of Metapanax delavayi based on multi-index dimensions， including sun drying （SD）， shade drying （ND）， hot air drying （HAD）， vacuum drying （VD）， and vacuum freeze drying （VFD）. METHODS An electronic eye was used to evaluate the appearance of samples with five drying methods. An electronic tongue was used to evaluate taste. The microstructure was evaluated by scanning electron microscope. The contents of moisture， total ash， acid-insoluble ash and water-soluble extract were detected by the methods in Chinese Pharmacopoeia . The contents of neochlorogenic acid， chlorogenic acid， cryptochlorogenic acid， 3，5- O -dicaffeoylquinic acid and 4，5- O -dicaffeoylquinic acid were determined by high-performance liquid chromatography. The comprehensive quality evaluation of five samples based on chemometrics， entropy weight-technique for order preference by similarity to ideal solution （TOPSIS） and grey relational analysis （GRA） with the above indicators as variables， the key indicators affecting the qualit y were screened by variable importance in projection （VIP） ＞1.0. RESULTS The color results of five samples showed that average L * ， a * ， b * ranged from 47.532 to 56.986， －4.957 to －0.718， 19.313 to 28.194， respectively. The taste results of the five samples showed that the presented high response values were for sourness and bitterness. Microstructural observation demonstrated that the ND samples showed smooth surfaces with compact texture； SD samples exhibited rough surfaces with obvious cracks； VD samples showed relatively rough surfaces with layered stacked morphology； HAD samples showed loose and coarse structures； VFD samples showed relatively smooth surfaces. The average moisture content ranged from 7.064% to 8.513%， the average total ash content ranged from 5.214% to 5.706%， the average acid-insoluble ash content ranged from 0.576% to 0.720%， and the average water-soluble extract content ranged from 26.081% to 28.395%. The contents of the five constituents were 2.559-8.940， 8.731-21.037， 1.710-4.479， 1.967-6.130， 1.199-2.001 mg/g， respectively. The results of cluster analysis and orthogonal partial least squares-discriminant analysis showed that the five samples were divided into three categories， both the VFD sample and HAD sample were clustered into one category， and the other samples were clustered into one category. The VIP values of chlorogenic acid， L * ， b * ， 3，5- O -dicaffeoylquinic acid， neochlorogenic acid and a * were higher than 1.0. The results of the entropy weight-TOPSIS method combined with GRA showed that the comprehensive closeness coefficients of the five samples were 0.414， 0.488， 0.412， 0.452 and 0.563， respectively. CONCLUSIONS Among the five drying samples， the quality of VFD sample was the best. Chlorogenic acid， L * ， b * ， 3，5- O -dicaffeoylquinic acid， neochlorogenic acid and a * were the key indicators to distinguish the quality of the different drying methods of M. delavayi .