A unified consensus statement on medication-related osteonecrosis of the jaw (MRONJ) has not yet been established among the Asian member countries or regions of the Asian Federation of Osteoporosis Societies (AFOS). This study aimed to develop a consensus on MRONJ in patients with osteoporosis across these countries and regions. In this study, the term “Asia-Pacific” refers specifically to the Asian member countries and regions of AFOS. A structured survey consisting of nine MRONJ-related questions was distributed across 10 countries and regions to assess the level of agreement and summarize regional perspectives. In addition, a manual literature review and voting were conducted to evaluate the current evidence on MRONJ. The key aspects of MRONJ, including definition, staging, diagnosis, pathogenesis, risk factors, management, and prevention, were generally consistent among the AFOS countries and regions. The annual incidence and incidence rate of MRONJ associated with low-dose antiresorptive therapy in patients with osteoporosis ranged from 0.025% to 0.136% and 21 to 283 cases per 100,000 person-years, respectively. However, evidence regarding the benefits of drug discontinuation before dental surgery, such as tooth extraction, remains insufficient. Large-scale, multinational studies across AFOS countries and regions are warranted to determine the incidence of MRONJ better and evaluate the impact of antiresorptive drug discontinuation before dental procedures. These findings may contribute to the devel opment of effective evidence-based strategies for preventing MRONJ in patients with osteoporosis.

Objective To investigate the association between the weight-adjusted waist index (WWI) and prostate cancer (PCa) in order to provide reference for the screening and diagnosis of PCa.Methods Data of 18732 men aged ≥20 years were obtained from the US National Health and Nutrition Examination Survey (NHANES) conducted between 1999 and 2018. The relationship between WWI and PCa was assessed using a multivariate logistic regression model.A stratified analysis was performed across four time periods:1999—2006, 2007—2010, 2011—2014, and 2015—2018.Restricted cubic splines (RCS) and subgroup analyses were employed to evaluate the potential nonlinear associations and interactions between WWI and PCa risk. The receiver operating characteristic (ROC) curve was utilized to compare the predictive performance of WWI with other obesity-related indicators, including waist-to-height ratio (WtHR), body mass index (BMI), waist circumference, and body weight.Results In the fully adjusted model, each 1-unit increase in WWI was associated with a 74% higher risk of PCa (OR=1.74, 95%CI:1.44-2.11, P＜0.001).Individuals in the highest quartile of WWI had nearly five times greater odds of PCa compared to those in the lowest quartile (OR=4.96, 95%CI:2.69-9.15, P＜0.001).The observed association remained consistent across all four survey cycles.RCS analysis revealed a nonlinear positive association between WWI and PCa risk. Threshold analysis indicated that when WWI ≥9.97, there was a significant positive correlation with PCa risk (OR=1.39, 95% CI:1.18-1.64, P＜0.001).Subgroup analyses confirmed the robustness of this association across different demographic and clinical subpopulations.Furthermore, WWI demonstrated superior discriminatory ability for predicting PCa compared to WtHR, BMI, waist circumference, and body weight (AUC=0.706, 0.608, 0.509, 0.594, 0.488, P＜0.001).Conclusion For the general male population in the US, WWI serves as an independent risk factor for PCa.This association has remained stable over 1999—2018, and WWI outperforms conventional obesity indicators in terms of predictive accuracy.Therefore, individuals with WWI ≥9.97 should be prioritized for prostate-specific antigen (PSA) screening, which may enhance current screening and diagnostic strategies.

ObjectiveTo establish consensus on Chinese Herbal Medicine (CHM) for rheumatoid arthritis (RA) among 21 Singaporean experts, this study addressed the lack of CHM clinical practice guidelines (CPGs) in Singapore. Despite advancements in RA therapies, the disease's progressive nature and high costs of novel treatments worsen disparities in management and outcomes. The initiative aimed to bridge this gap by developing expert-backed recommendations for CHM use in RA care.MethodsThe group of experts conducted two rounds of Delphi surveys containing 29 items identified from a literature review. Consensus was defined as ≥75% of votes in dichotomized ratings on a five-point ordinal scale for recognition. Items that did not reach consensus were discussed in a focus group with four selected experts.ResultsNineteen experts completed both rounds of Delphi surveys. A consensus was reached for 27 items, which encompassed Chinese medicine rationale, pattern differentiation, management, CHM prescription, and co-effectiveness with pharmacological therapy. Collective expert opinions were formed for the two remaining items. All items received a recognition score 3.5.ConclusionsThe consensus derived from this study provides a foundation for CHM CPGs for RA in Singapore. However, the findings are limited by the demographic composition of the experts and the representativeness of the patient pool.

Acute respiratory distress syndrome(ARDS)is a common respiratory emergency,but current clinical treatment remains at the level of symptomatic support and there is a lack of effective targeted treatment measures.Our previous study confirmed that inhalation of hydrogen gas can reduce the acute lung injury of ARDS,but the application of hydrogen has flammable and explosive safety concerns.Drinking hydrogen-rich liquid or inhaling hydrogen gas has been shown to play an important role in scavenging reactive oxygen species and maintaining mitochondrial quality control balance,thus improving ARDS in patients and animal models.Coral calcium hydrogenation(CCH)is a new solid molecular hydrogen carrier prepared from coral calcium(CC).Whether and how CCH affects acute lung injury in ARDS re-mains unstudied.In this study,we observed the therapeutic effect of CCH on lipopolysaccharide(LPS)induced acute lung injury in ARDS mice.The survival rate of mice treated with CCH and hydrogen inhalation was found to be comparable,demonstrating a significant improvement compared to the untreated ARDS model group.CCH treatment significantly reduced pulmonary hemorrhage and edema,and improved pulmonary function and local microcirculation in ARDS mice.CCH promoted mitochon-drial peripheral division in the early course of ARDS by activating mitochondrial thioredoxin 2(Trx2),improved lung mitochondrial dysfunction induced by LPS,and reduced oxidative stress damage.The results indicate that CCH is a highly efficient hydrogen-rich agent that can attenuate acute lung injury of ARDS by improving the mitochondrial function through Trx2 activation.

OBJECTIVE To analyze the differences in chemical composition of mussels from Shengsi,Zhoushan in different har-vest months,and to compare the differences in the composition of mussels from different origins,so as to provide ideas for the compre-hensive utilization of its resources.METHODS Ultra-high performance liquid chromatography-triple quadrupole mass spectrometry(UHPLC-QqQ-MS)and spectrophotometry were used to analyze and evaluate the contents of nucleosides,amino acids,water-soluble proteins,total sugars and polysaccharides in mussels from Shengsi,Zhoushan in 12 months of the year and from 5 different origins;principal component analysis(PCA),partial least squares discriminant method(PLS-DA)and TOPSIS method were used to compre-hensively evaluate mussels.RESULTS A total of 16 amino acids and 11 nucleosides were detected in mussels.The average content of total amino acids in Shengsi mussels throughout the year was 4 851.74 μg·g-1,the average content of total nucleosides was 921.40 μg·g-1,and the average contents of water-soluble protein,polysaccharides,and total sugars were 51.32 mg·g-1,74.39 μg·g-1,and 417.22 mg·g-1,respectively.The nucleosides of Shengsi mussels were the highest in March and April,the ami-no acids and water-soluble proteins were the highest in April and May,and the polysaccharides and total sugars were the highest in Oc-tober and November.The PCA and PLS-DA results of the chemical components of different resources showed that there were great differences in Shengsi mussel samples harvested in different seasons.The entropy weight TOPSIS analysis showed that the comprehen-sive scores of Shengsi mussels in March and April(S7 and S8)were better than those in other areas,and the comprehensive score of Shengsi mussels in April(S8)was the highest,which was determined to be the best harvesting month.CONCLUSION The comparison results of multi-type resource chemistry show that there are great differences in the chemical compo-sition of Shengsi mussels in different harvesting seasons;the quality of Shengsi mussels is better than that of other areas;April is the best harvesting season,providing a reference for the quality evaluation and comprehensive development and utilization of mussels.

Objective To explore a deep learning-based automatic bone age estimation model for elbow joint X-ray images of Chinese Han adolescents and children and evaluate its performance.Methods A total of 943(517 males and 426 females)elbow joint frontal view X-ray images of Chinese Han ado-lescents and children aged 6.00 to<16.00 years were collected from East,South,Central and North-west China.Three experimental schemes were adopted for bone age estimation.Scheme 1:Directly in-put preprocessed images into the regression model;Scheme 2:Train a segmentation network using"key elbow joint bone annotations"as labels,then input segmented images into the regression model;Scheme 3:Train a segmentation network using"full elbow joint bone annotations"as labels,then in-put segmented images into the regression model.For segmentation,the optimal model was selected from U-Net,UNet++and TransUNet.For regression,VGG16,VGG19,InceptionV2,InceptionV3,ResNet34,ResNet50,ResNet101 and DenseNet121 models were selected for bone age estimation.The dataset was randomly split into 80%(754 samples)for training and validation for model fitting and hyperparameter tuning,and 20%(189 samples)as an internal test set to test the performance of the trained model.An additional 104 elbow joint X-ray images from the same demographic and age group were col-lected and used as an external test set.Model performance was evaluated by comparing the mean ab-solute error(MAE),root mean square error(RMSE),accuracies within±0.7 years(P±0.7 years)and±1.0 years(P±1.0 years)between the estimated age and the actual age,and by drawing radar charts,scat-ter plots,and heatmaps.Results When segmented with Scheme 3,the UNet++model achieved good segmentation performance with a segmentation loss of 0.000 4 and an accuracy of 93.8%at a learning rate of 0.000 1.In the internal test set,the DenseNet121 model with Scheme 3 yielded the best results with MAE,P±0.7 years and P±1.0 years being 0.83 years,70.03%,and 84.30%,respectively.In the external test set,the DenseNet121 model with Scheme 3 also performed best,with an average MAE of 0.89 years and an average RMSE of 1.00 years.Conclusion When performing automatic bone age estima-tion using elbow joint X-ray images in Chinese Han adolescents and children,it is recommended to use the UNet++model for segmentation.The DenseNet121 model with Scheme 3 achieves optimal per-formance.Using segmentation networks,especially that trained with annotation areas encompassing the full elbow joint including the distal humerus,proximal radius,and proximal ulna,can improve the ac-curacy of bone age estimation based on elbow joint X-ray images.

Objective To explore a deep learning network model suitable for bone age estimation using shoulder joint X-ray images in Chinese Han adolescents.Methods A retrospective collection of 1 286 shoulder joint X-ray images of Chinese Han adolescents aged 12.0 to<18.0 years(708 males and 578 females)was conducted.Using random sampling,approximately 80%of the samples(1 032 cases)were selected as the training and validation sets for model learning,selection and optimization,and the other 20%samples(254 cases)were used as the test set to evaluate the model's generalization ability.The original single-channel shoulder joint X-ray images and dual-channel inputs combining original images with segmentation labels(manually annotated shoulder joint regions multiplied pixel-by-pixel with original images,followed by segmentation via the U-Net++network to retain only key shoulder joint region information)were respectively input into four network models,namely VGG16,ResNet18,ResNet50 and DenseNet121 for bone age estimation.Additionally,manual bone age estimation was con-ducted on the test set data,and the results were compared with the four network models.The mean absolute error(MAE),root mean square error(RMSE),coefficient of determination(R2),and Pear-son correlation coefficient(PCC)were used as main evaluation indicators.Results In the test set,the bone age estimation results of the four models with dual-channel input of shoulder joint X-ray images outperformed those with single-channel input in all four evaluation indicators.Among them,DenseNet121 with dual-channel input achieved best results with MAE of 0.54 years,RMSE of 0.82 years,R2 of 0.76,and PCC(r)of 0.88.Manual estimation yielded an MAE of 0.82 years,ranking second only to dual-channel DenseNet121.Conclusion The DenseNet121 model with dual-channel input combined with original images and segmentation labels is superior to manual evaluation results,and can effectively estimate the bone age of Chinese Han adolescents.

Objective:To investigate the association between vitamin D deficiency, overweight and mild obstructive sleep apnea (OSA).Methods:The study was a cross-sectional study. A total of 82 mild OSA patients diagnosed in Pujin Community Health Service Center of Shanghai Minhang District and the medical consortium of Shanghai Fifth People′s Hospital from January to December 2022 were enrolled, and 82 non-OSA patients visiting outpatient clinics at the same period were selected as controls. All participants underwent polysomnography monitoring and AHI and LpO 2 were recorded. Venous blood was collected and serum vitamin D concentration was detected by ELISA method. The associated factors of mild OSA were determined with logistic regression analysis. Results:The prevalence of tonsillar hypertrophy (32.90%(27/82) vs. 18.29%(15/82)), smoking (52.4%(43/82) vs. 35.37%(29/82)) and allergic rhinitis (24.39% (20/82) vs. 12.20% (10/82) ) in mild OSA group was significantly higher than that in the control group ( χ2=4.609, 4.853 and 4.080, all P<0.05). The mild OSA group had a higher BMI ( (26.23±4.21) kg/m 2vs. (21.85±1.36) kg/m 2, t=2.517, P<0.05 ) and lower serum vitamin D level ( (12.36±7.98) pg/ml vs. (23.56±9.32) pg/ml, t=-11.818, P<0.05) compared with the non-OSA group. There were no significant differences in rates of alcohol consumption (39.02%(32/82) vs. 34.15%(28/82)) and family history of OSA (9.76%(8/82) vs. 6.10%(5/82), χ2=0.752) between the two groups. Multivariate logistic regression analysis showed that overweight ( OR=1.227, 95% CI: 1.045-1.441, P<0.05) was an independent risk factor for mild OSA, while vitamin D level ( OR=0.904, 95% CI: 0.832-0.981, P<0.05) was a protective factor for mild OSA. Interaction analysis revealed that the risk of combination of two factors for developing mild OSA was 5.638, which exceeded that of high BMI (1.375) or vitamin D deficiency alone (2.216) (all P<0.05). Conclusion:Vitamin D deficiency and overweight are risk factors for the development of mild OSA, and there is a positive interaction between these two factors.

Periodontitis is a globally prevalent inflammatory oral disease, affecting approximately 50% of the population worldwide and imposing a substantial burden on patients′ health and quality of life. Early and accurate diagnosis is critical for preventing disease progression; however, conventional diagnostic approaches often rely on subjective clinical assessments, which only primarily evaluate the cumulative state of the disease, thus limiting their ability to achieve precise early detection. In recent years, the rapid advancement of artificial intelligence (AI) in medical diagnostics has demonstrated significant promise, particularly through the integration of multimodal data to enable more comprehensive information capture and analysis. Multimodal data fusion, which combines diverse inputs such as imaging, clinical parameters, and biomarkers, offers transformative potential for AI-powered periodontitis diagnostics. This innovative approach aims to overcome the limitations of traditional methods, significantly enhancing diagnostic accuracy and predictive capabilities. This manuscript reviews the primary diagnostic techniques for periodontitis, explores recent advances in AI applications within this domain, and emphasizes the potential of multimodal data in facilitating precision diagnosis. Furthermore, it provides new insights and supports for personalized treatment strategies.

The development of polysaccharide conjugate vaccines, which convert polysaccharide antigens into T-cell-dependent immunogens through covalent conjugation with protein carriers, represents a critical strategy for enhancing immune protection in infants and young children. Globally licensed conjugate vaccines currently employ carrier proteins including Tetanus Toxoid, Diphtheria Toxoid, and Cross-Reacting Material 197. Recent advances have focused on three key areas: novel carrier protein discovery, optimized conjugation strategies, and evaluation of immune interference during co-administration of multivalent formulations. These efforts aim to achieve broader serotype coverage, prolonged protective efficacy, and simplified immunization schedules. This review synthesizes recent progress in carrier protein development, encompassing vaccine design principles, manufacturing processes, safety profiles, and epidemiological effectiveness. Furthermore, it critically examines current selection criteria for carrier proteins, their clinical applications, and persistent challenges, providing strategic insights to inform future conjugate vaccine development and immunization policy optimization in China.