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:To explore the relationships among psychological resilience,spiritual health,and illness uncertainty in cancer patients,and to analyze the mediating role of disease uncertainty.Methods:The cancer patients were selected by convenience sampling method from Feb 2024 to May 2024 in the Department of Oncology of a Grade Ⅲ-A general hospital in Wuhu City.Data were collected using a general information questionnaire,the Mishel Uncertainty in Illness Scale(MUIS),the Functional Assessment of Chronic Illness Therapy-Spiritual Well-being Scale(FACIT-SP-12,Chinese version),and the Connor-Davidson Resilience Scale(CD-RISC-10).Pearson correlation analysis was conducted to assess the relationships among psychological resilience,illness uncertainty,and spiritual health.The mediating effect of illness uncertainty was tested using Hayes'PROCESS Model 4 and the Bootstrap method.Results:The total scores of spiritual health,psychological resilience and illness uncertainty of cancer patients was(25.11±7.19),(24.36±6.75)and(67.75±13.06),respectively.The spiritual health was positively correlated with psychological resilience(r=0.415,P＜0.01)and negatively correlated with illness uncertainty(r=-0.398,P＜0.01).The psychological resilience was negatively correlated with illness uncertainty(r=-0.668,P＜0.01).Illness uncertainty partially mediated the relationship between psychological resilience and spiritual health,accounting for 35.29%of the total effect.Conclusions:The spiritual health of cancer patients is at a moderate level.Enhancing psychological resilience and reducing illness uncertainty can alleviate psychological burden and improve spiritual health,thereby promoting overall quality of life.

Objective:To explore the relationships among psychological resilience,spiritual health,and illness uncertainty in cancer patients,and to analyze the mediating role of disease uncertainty.Methods:The cancer patients were selected by convenience sampling method from Feb 2024 to May 2024 in the Department of Oncology of a Grade Ⅲ-A general hospital in Wuhu City.Data were collected using a general information questionnaire,the Mishel Uncertainty in Illness Scale(MUIS),the Functional Assessment of Chronic Illness Therapy-Spiritual Well-being Scale(FACIT-SP-12,Chinese version),and the Connor-Davidson Resilience Scale(CD-RISC-10).Pearson correlation analysis was conducted to assess the relationships among psychological resilience,illness uncertainty,and spiritual health.The mediating effect of illness uncertainty was tested using Hayes'PROCESS Model 4 and the Bootstrap method.Results:The total scores of spiritual health,psychological resilience and illness uncertainty of cancer patients was(25.11±7.19),(24.36±6.75)and(67.75±13.06),respectively.The spiritual health was positively correlated with psychological resilience(r=0.415,P＜0.01)and negatively correlated with illness uncertainty(r=-0.398,P＜0.01).The psychological resilience was negatively correlated with illness uncertainty(r=-0.668,P＜0.01).Illness uncertainty partially mediated the relationship between psychological resilience and spiritual health,accounting for 35.29%of the total effect.Conclusions:The spiritual health of cancer patients is at a moderate level.Enhancing psychological resilience and reducing illness uncertainty can alleviate psychological burden and improve spiritual health,thereby promoting overall quality of life.

Objective To investigate the influencing factors of grade 3-4 multiple myeloma bone disease(MBD)in newly diagnosed multiple myeloma(NDMM)patients,and establish a risk prediction model based on a nomogram.Methods A total of 261 patients with NDMM who were treated in Ningbo Medical Center Lihuili Hospital from January 2015 to December 2021 were retrospectively selected.The patients were divided into group A(MBD grade 0-2,110 cases)and group B(MBD grade 3-4,151 cases)according to MBD grade at the time of initial diagnosis.Logistic regression analysis was used to screen the risk factors for grade 3-4 MBD in NDMM patients,and the risk prediction model was constructed.The receiver operating characteristic(ROC)curve was used for comprehensive evaluation.Results Multivariate regression analysis showed that age,serum phosphorus,C-reactive protein(CRP),globulin(GLB)and bone marrow plasma cell percentage(BMPCp)were independent risk factors for grade 3-4 MBD in NDMM patients(P<0.05).Based on this,risk prediction model was constructed as follows:logit(P)=-15.092+0.107(age)+1.150(serum phosphorus)+0.057(CRP)+0.040(GLB)+0.212(BMPCp).There was no significant difference between the predicted probability and the actual incidence by the Hosmer-Lemeshow goodness of fit test(P=0.770).The accuracy of the model in predicting grade 3-4 MBD in NDMM patients was 90.40%,and the area under the curve was 0.957(95%CI:0.932-0.981),indicating a reliable prediction ability.Conclusion Age,serum phosphorus,CRP,GLB and BMPCp were all independent risk factors for grade 3-4 MBD in NDMM patients,and the constructed risk prediction model has a relatively good predictive effect on the occurrence of grade 3-4 MBD in NDMM patients.

AIM To investigate the protective effect of Sanfeng Tongqiao Dropping Pills against house dust mite(HDM)-induced allergic asthma in mice.METHODS Compared to the intact BALB/c mice in the blank control group,the BALB/c mice randomly assigned into the model group,the dexamethasone group(0.67 mg/kg),and the low-dose,medium-dose,and high-dose Sanfeng Tongqiao Dropping Pills groups(15,30 and 60 mg/kg),were induced into acute allergic asthma models via weekly intraperitoneal sensitization with 0.1 mL HDM solution(0.5 mg/mL)for three weeks followed by three consecutive daily intranasal challenges with 10 μL HDM solution(2.5 mg/mL)starting in the third week.The drug administered continuously 7 days after the last excitation.The mice had their airway reactive Penh value detected,their pulmonary pathological changes observed by HE staining,their blood eosinophils(EOS)counted,their Th2 cytokines in lung tissue and serum IgE levels detected by ELISA,and their number of peripheral blood mononuclear cells(PBMC)and pulmonary Th2 cells detected by flow cytometry.Chronic allergic asthma was induced in grouped BALB/c mice through repeated intranasal challenges with 10 μL HDM solution(2.5 mg/mL)administered five times weekly for five consecutive weeks.Drug treatment continued for 14 days following the final challenge.After the final treatment,the mice had their pulmonary pathological changes observed by HE staining,and their levels of Th2 cytokines in B ALF and lung tissue and serum IgE detected by ELISA.RESULTS Compared to the blank control group,the acute allergic asthma model group exhibited increases in Penh value,EOS count and IgE level in serum,IL-4 and IL-5 levels in lung tissue(P＜0.01);obvious pulmonary inflammatory cells infiltration,and thickened airway wall;and increase in pulmonary number of Th2 cells(P＜0.01).Compared to the model group,the groups intervened with Sanfeng Tongqiao Dropping Pills demonstrated decreased Penh value,serum EOS count,IgE level and IL-5 level in lung tissue(P＜0.05,P＜0.01);reduced pulmonary inflammatory infiltration and alleviated airway wall thickening;and decreased number of pulmonary Th2 cells.Compared to the blank group,the chronic allergic asthma model group showed obvious pulmonary inflammatory infiltration and airway wall thickening;and increased EOS count and IgE level in serum,IL-4 and IL-13 in lung tissue and IL-14 in BALF(P＜0.05,P＜0.01).Compared to the model group,the groups intervened with either medium-dose or high-dose Sanfeng Tongqiao Dropping Pills demonstrated reduced pulmonary inflammatory infiltration;and decreased serum EOS count,IgE level,IL-13 in lung tissue and IL-14 in BALF(P＜0.05,P＜0.01).CONCLUSION Sanfeng Tongqiao Dropping Pills reduce Th2 cells in peripheral blood and lung tissue,suppress type 2 inflammation,and thereby alleviate allergic asthma.

This study was aimed at exploring novel auxiliary diagnostic biomarkers for brucellosis and their potential miR-NA-mRNA regulatory networks.High-throughput sequencing was used to compare miRNA expression differences in serum ex-osomes between patients with brucellosis and healthy controls.Subsequently,RT-qPCR was used to validate the expression of significantly upregulated exosomal miRNAs.The diagnostic value of these miRNAs was assessed with ROC curves,and bioin-formatics analyses were performed to investigate the potential roles of the miRNAs in brucellosis infection.The ROC curve a-nalysis indicated that the area under the curve for exosomal hsa-miR-11400(P＜0.05),hsa-miR-199a-5p(P＜0.05),and hsa-miR-148a-5p(P＜0.05)was 0.79,0.81,and 0.74,respectively.A total of 465 differentially expressed miRNAs and their tar-get genes were predicted,including 25 immune-related target genes,most of which were closely associated with cancer-related proteoglycans,NF-kappa B signaling pathways,and IL-17 signaling pathways.The constructed differentially expressed gene network indicated that the immune genes PLXNA2,IL17RA,PRKCA,CD22,ACVR1B,and CBL might be regulated by hsa-miR-199a-5p and hsa-miR-148a-5p.These findings suggest that exosomal miRNAs might serve as auxiliary diagnostic indicators for brucellosis.Our exosomal miRNA-mRNA regulatory network provides new insights into the pathogenesis and treatment of brucellosis.

Objective To investigate the effect of dorsal repulsive axon guidance protein(Draxin)on the migration of trunk neural crest cells during the early development of embryonic mouse spinal cord.Methods Immunohistochemistry and in situ hybridization were used to detect the expression characteristics of Draxin in early embryonic spinal cord(8 mice each group);In situ hybridization was used to detect the change of migration characteristics of trunk neural crest cells in early embryonic spinal cord of different types of mouse(5 mice each group);in vitro culture method was used to check the effect of Draxin on the migration characteristics of embryonic mouse trunk neural crest cells(16 mice each group).Resultsβ-galactosidase gene Z(LacZ)gene was introduced when Draxin gene was knocked out to produce Draxin gene knockout mice.β-galactosidase staining was used to detect LacZ gene expression in Draxin knockout embryonic mice,and the result showed that Draxin expression was observed in the spinal cord of early embryonic mice since 9.5 days(E9.5).Draxin expression was obvious in the embryonic mice spinal cord in E10.5 period.In situ hybridization was used to detect the expression of Draxin gene in the spinal cord of wild type embryonic mice,and the result further verified the obvious expression of Draxin in the early embryonic mice spinal cord in El0.5 period.Sox10 in situ hybridization was used to detect neural crest cell migration in the spinal cord of embryonic mice in E10.5 period.The result showed that segmental migration of neural crest cells in the early embryonic spinal cord of some Draxin knockout mice was delayed compared with the wild type mice.The effect of Draxin on the migration of wild type early embryonic mice trunk neural crest cells in vitro was tested.The result showed that Draxin reduced the migration distance of neural crest cells in vitro.Conclusion In the early developmental stage of embryonic spinal cord(E9.5-E10.5),neural crest cells migrated exuberant.At the same time,Draxin plays an important inhibitory function in the formation of the specific migration pathways of trunk neural crest cells by promoting neural crest cells migrating away from Draxin expressing regions.

Drug repurposing offers a promising alternative to traditional drug development and significantly re-duces costs and timelines by identifying new therapeutic uses for existing drugs.However,the current approaches often rely on limited data sources and simplistic hypotheses,which restrict their ability to capture the multi-faceted nature of biological systems.This study introduces adaptive multi-view learning(AMVL),a novel methodology that integrates chemical-induced transcriptional profiles(CTPs),knowledge graph(KG)embeddings,and large language model(LLM)representations,to enhance drug repurposing predictions.AMVL incorporates an innovative similarity matrix expansion strategy and leverages multi-view learning(MVL),matrix factorization,and ensemble optimization techniques to integrate heterogeneous multi-source data.Comprehensive evaluations on benchmark datasets(Fdata-set,Cdataset,and Ydataset)and the large-scale iDrug dataset demonstrate that AMVL outperforms state-of-the-art(SOTA)methods,achieving superior accuracy in predicting drug-disease associations across multiple metrics.Literature-based validation further confirmed the model's predictive capabilities,with seven out of the top ten predictions corroborated by post-2011 evidence.To promote transparency and reproducibility,all data and codes used in this study were open-sourced,providing resources for pro-cessing CTPs,KG,and LLM-based similarity calculations,along with the complete AMVL algorithm and benchmarking procedures.By unifying diverse data modalities,AMVL offers a robust and scalable so-lution for accelerating drug discovery,fostering advancements in translational medicine and integrating multi-omics data.We aim to inspire further innovations in multi-source data integration and support the development of more precise and efficient strategies for advancing drug discovery and translational medicine.

Drug repurposing offers a promising alternative to traditional drug development and significantly reduces costs and timelines by identifying new therapeutic uses for existing drugs. However, the current approaches often rely on limited data sources and simplistic hypotheses, which restrict their ability to capture the multi-faceted nature of biological systems. This study introduces adaptive multi-view learning (AMVL), a novel methodology that integrates chemical-induced transcriptional profiles (CTPs), knowledge graph (KG) embeddings, and large language model (LLM) representations, to enhance drug repurposing predictions. AMVL incorporates an innovative similarity matrix expansion strategy and leverages multi-view learning (MVL), matrix factorization, and ensemble optimization techniques to integrate heterogeneous multi-source data. Comprehensive evaluations on benchmark datasets (Fdataset, Cdataset, and Ydataset) and the large-scale iDrug dataset demonstrate that AMVL outperforms state-of-the-art (SOTA) methods, achieving superior accuracy in predicting drug-disease associations across multiple metrics. Literature-based validation further confirmed the model's predictive capabilities, with seven out of the top ten predictions corroborated by post-2011 evidence. To promote transparency and reproducibility, all data and codes used in this study were open-sourced, providing resources for processing CTPs, KG, and LLM-based similarity calculations, along with the complete AMVL algorithm and benchmarking procedures. By unifying diverse data modalities, AMVL offers a robust and scalable solution for accelerating drug discovery, fostering advancements in translational medicine and integrating multi-omics data. We aim to inspire further innovations in multi-source data integration and support the development of more precise and efficient strategies for advancing drug discovery and translational medicine.

Functional dyspepsia (FD), characterized by persistent or recurrent dyspeptic symptoms without identifiable organic, systemic or metabolic causes, is an increasingly recognized global health issue. The objective of this guideline is to equip clinicians and nursing professionals with evidence-based strategies for the management and treatment of adult patients with FD using traditional Chinese medicine (TCM). The Guideline Development Group consulted existing TCM consensus documents on FD and convened a panel of 35 clinicians to generate initial clinical queries. To address these queries, a systematic literature search was conducted across PubMed, EMBASE, the Cochrane Library, China National Knowledge Infrastructure (CNKI), VIP Database, China Biology Medicine (SinoMed) Database, Wanfang Database, Traditional Medicine Research Data Expanded (TMRDE), and the Traditional Chinese Medical Literature Analysis and Retrieval System (TCMLARS). The evidence from the literature was critically appraised using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach. The strength of the recommendations was ascertained through a consensus-building process involving TCM and allopathic medicine experts, methodologists, pharmacologists, nursing specialists, and health economists, leveraging their collective expertise and empirical knowledge. The guideline comprises a total of 43 evidence-informed recommendations that span a range of clinical aspects, including the pathogenesis according to TCM, diagnostic approaches, therapeutic interventions, efficacy assessments, and prognostic considerations. Please cite this article as: Zhang SS, Zhao LQ, Hou XH, Bian ZX, Zheng JH, Tian HH, Yang GH, Hong WS, He YY, Liu L, Shen H, Li YP, Xie S, Shu J, Zeng BF, Li JX, Liu Z, Xiao ZH, Xiao JD, Zheng PY, Huang SG, Chen SL, Fei GJ. International clinical practice guideline on the use of traditional Chinese medicine for functional dyspepsia (2025). J Integr Med. 2025; 23(5):502-518.
Dyspepsia/drug therapy* ; Humans ; Medicine, Chinese Traditional/methods* ; Practice Guidelines as Topic ; Drugs, Chinese Herbal/therapeutic use*