ObjectiveTo observe the clinical efficacy and radiographic outcomes of manipulative reduction combined with small splint fixation in the treatment of distal radius fractures. MethodsThe clinical data of 1051 patients with distal radius fractures were retrospectively collected from five hospitals included in the Jiangsu Diagnosis and Treatment Data Platform for Traditional Chinese Medicine（TCM） Dominant Diseases. Propensity score matching at a 1∶4 ratio was applied， resulting in 580 cases selected for final analysis， which comprised 448 patients in the TCM group（manipulative reduction plus small splint fixation） and 132 in the surgical treatment group（open reduction and internal fixation）. Each group was further stratified into type A， B， and C subgroups based on AO fracture classification. Radiographic indicators including palmar tilt， radial inclination， and radial height were compared between groups before treatment and 1 day， 1 week， and 4-6 weeks after treatment， and pain visual analog scale（VAS） scores before treatment and 1 week and 4-6 weeks after treatment were also compared. Wrist joint function was assessed 12 weeks after treatment， using the Dienst wrist function score and the Gartland and Werley（G-W） wrist function score. Additionally， the radiographic indicators at different timepoints and the 12-week wrist function levels were compared between groups across different fracture types. ResultsNo statistically significant difference was observed in radiographic indicators and VAS scores at all timepoints before and after treatment， as well as wrist joint function grades assessed by the Dienst score and the G-W score at 12 weeks after treatment （P＞0.05）. Compared to those before treatment， both groups showed increased palmar tilt， radial inclination， and radial height 1 week and 4-6 weeks after treatment， and decreased VAS scores （P＜0.05）. Compared to those 1 week after treatment， both groups showed a decrease in palmar tilt， an increase in radial inclination and radial height， and a reduction in VAS score 4-6 weeks after treatment（P＜0.05）. In type A and B subgroups， the surgical treatment group had a higher radial inclination than the TCM group 4-6 weeks after treatment， while in the type C subgroup， a higher radial height was shown in the surgical treatment group than in the TCM group 4-6 weeks after treatment（P＜0.05）. In type C subgroup， there was significant difference between groups in the wrist joint function by G-W scores 12 weeks after treatment（P＜0.05）. ConclusionManipulative reduction combined with small splint fixation can maintain fracture alignment and alleviate pain in treating distal radius fractures， which achieves therapeutic outcomes comparable to surgical treatment. It is particularly suitable for type A and B fractures and can be considered an effective treatment option for distal radius fractures.

ObjectiveTo construct an automatic measurement model for palmar tilt and radial inclination suitable for traditional Chinese medicine （TCM） clinical scenarios， and to validate its accuracy and efficiency in TCM manipulative reduction settings. MethodsData on anteroposterior （AP） and lateral X-rays of distal radius fractures were collected from patients admitted to 18 TCM/ integrated TCM and western medicine hospitals in Jiangsu province between September 1st， 2023， and September 1st， 2024， via the Jiangsu Diagnosis and Treatment Big Data Platform for TCM Dominant Diseases. A medical image segmentation framework based on multi-scale feature fusion and edge-awareness was employed， combined with anatomical knowledge specific to TCM orthopedics， to optimize the feature extraction strategy of an artificial intelligence （AI） model. This framework enabled automatic segmentation of fracture regions and measurement of distal radius palmar tilt and radial inclination. The accuracy of the AI model in measuring radial inclination and volar tilt was validated， and the measurement time and average time gain rate of the AI model were compared to those of manual measurement. ResultsA total of 15,444 AP and lateral X-ray images of distal radius fractures were collected， and were divided into a training set （11,144 images， 5066 AP and 6078 lateral）， a validation set （3700 images， 1840 AP and 1860 lateral）， and an independent test set （600 images， 300 AP and 300 lateral） after preprocessing. In the measurement of 300 AP X-rays in the independent test set for radial inclination， when the degree error between AI measurement and manual measurement was ＜3° and ＜5°， AI measurement accuracy was 83% and 93%， respectively. In 300 lateral X-rays in the test set for palmar tilt， when AI measurements had an error of ＜3° and ＜5° compared to manual measurements， corresponding accuracy rate was 78% and 90%， respectively. For 50 X-ray images， AI measurement time was （1.37±0.05） min for radial inclination while manual measurement time was （22.57±2.52） min （P＜0.001）； in terms of palmar tilt， the AI measurement time was （1.33±0.14） min， shorter than （23.70±2.80） min for manual measurement time （P＜0.001）. Average time gain rates for manual and AI measurements were 93.93% and 94.39% respectively. ConclusionAn automatic measurement model for palmar tilt and radial inclination in distal radius fractures has been established， enabling more accurate and efficient assessment as well as providing a tool to support the quantitative evaluation of the efficacy of TCM manipulative reduction and large-sample clinical research.

Objective To investigate the correlations of expression levels of serum transforming growth factor-β1(TGF-β1)and insulin-like growth factor-1(IGF-1)with clinicopathological features of patients with adenomyosis,and the clinical value of their prediction of postoperative recurrence.Methods Eighty-two patients with adenomyosis were selected as study subjects(study group).Patients were followed up for two years after surgery and divided into recurrence group(n=15)and non-recur-rence group(n=67)based on their postoperative status.An additional 85 healthy individuals who un-derwent physical examinations during the same period were selected as control group.Serum TGF-β1 and IGF-1 levels were compared between the study group and the control group.The correlations of se-rum TGF-β1 and IGF-1 levels with the clinicopathological characteristics of adenomyosis patients was analyzed.Serum TGF-β1 and IGF-1 levels were compared between the recurrence and non-recurrence groups.Receiver operating characteristic(ROC)curve analysis was used to evaluate the diagnostic efficacy of serum TGF-β1 and IGF-1 levels in predicting postoperative recurrence in adenomyosis pa-tients.Results Serum TGF-β1 and IGF-1 levels in the study group were significantly higher than those in the control group(P＜0.05).Serum TGF-β1 levels were correlated with menstrual vol-ume,history of curettage,uterine volume,pathological type,lesion volume,endometrial status and ectopic gland cycle(P＜0.05).Serum IGF-1 levels were correlated with menstrual volume,history of curettage,uterine volume,pathological type,endometrial status and ectopic gland cycle(P＜0.05).Postoperative serum TGF-β1 and IGF-1 levels in the recurrence group were significantly higher than those in the non-recurrence group(P＜0.05).ROC curve analysis showed that the area under the curve(AUC)for predicting postoperative recurrence using serum TGF-β1,IGF-1 and their combination were 0.823,0.803 and 0.940,respectively.The clinical efficacy of TGF-β1 and IGF-1 in combination in predicting postoperative recurrence was superior to that of TGF-β1 alone(ZcombinedwithTGF-β1=2.001,ZcombinedwithIGF-1=2.318,P=0.045,0.021).Conclusion The serum levels of TGF-β1 and IGF-1 in patients with adenomyosis are significantly increased,which are closely related to the clinicopathological features of the patients.The combination of serum TGF-β1 and IGF-1 levels has high clinical efficacy in predicting postoperative recurrence.

Objective:To compare the benefits and prognostic risks of unilateral lobectomy (with or without isthmusectomy) or total (or near-total) thyroidectomy for primary foci of unilateral papillary thyroid cancer (PTC) patients with ipsilateral lateral cervical lymph node metastasis (LLNM) , so as to find out the optimal surgery for these patients.Methods:A total of 505 unilateral PTC patients with ipsilateral LLNM who underwent initial surgical treatment at the Thyroid Surgery Department of Zhejiang Cancer Hospital from Feb. 2012 to Jan. 2020 were retrospectively reviewed. The patients were divided into unilateral lobectomy group ( n=314) and total thyroidectomy group ( n=191) according to the extent of resection of primary foci. Then 177 pairs of cases were screened out after eliminating the potential confounding bias between the two groups by using propensity score matching (PSM) , analyzing the differences in clinical outcomes such as recurrence-free survival (RFS) , overall survival (OS) , hospitalization costs, and postoperative complications between the two groups. Results:After PSM, the postoperative complication rate was 37.3% ( n=66) in the total thyroidectomy group and 3.4% ( n=6) in the unilateral lobectomy group. The complication was mainly characterized by temporary hypoparathyroidism (HP) . Although the difference in length of hospitalization between the two groups was not statistically significant ( P=0.792) , patients in the unilateral lobectomy group used less surgical time ( P<0.001) , had lower hospitalization and surgical costs ( P<0.0001) , and took a relatively smaller dose of levothyroxine (L-T4) one month after the operation ( P<0.0001) , as compared with the total thyroidectomy group. Univariate analysis showed that the number of LLNM total lymph node metastasis (LNM) rate, LLNM rate, and T stage were significant risk factors for relapse. Multi-factor regression analysis indicated that T-staging was a risk factor for recurrence. After a median follow-up of 60 (3-138) months, 19 patients (10.7%) in the unilateral lobectomy group and 11 patients (6.2%) in the total thyroidectomy group recurred, with no statistical difference between the two groups ( P=0.133) . The OS curve displayed no significant difference between the unilateral lobectomy and total thyroidectomy groups ( P=0.740) . Conclusion:For unilateral PTC patients with ipsilateral LLNM without other high-risk features, unilateral lobectomy could be a better option.

Objective:To investigate the current status and influencing factors of barriers to going out among elderly patients with chronic obstructive pulmonary disease (COPD), and to provide a reference for implementing targeted preventive measures.Methods:Elderly COPD patients from the People's Hospital of Xinjiang Uygur Autonomous Region were selected between January and May 2024 by convenience sampling. A cross-sectional survey was conducted using a general information questionnaire, Scale on Barriers to Going Out for the Elderly, Perceived Isolation Scale and COPD Assessment Test (CAT).Results:A total of 270 questionnaires were distributed, with 250 valid responses, the effective response rate was 92.6%. Among the 250 elderly COPD patients, there were 124 males and 126 females, with age distributions: 116 patients aged 60-69 years, 94 aged 70-79 years, and 40 aged ≥80 years. The total score for Scale on Barriers to Going Out for the Elderly was (20.01 ± 4.09). The score on barriers to going out in elderly COPD patients were positively correlated with the Perceived Isolation Scale and CAT scores ( r = 0.456 and 0.625, both P <0.05). Multiple linear regression analysis revealed that age, oxygen therapy, exercise habits,Perceived Isolation Scale, and CAT score classification were the main influencing factors for barriers to going out ( t values were -2.85 to 8.93, all P<0.05), explaining 63.0% of the total variance. Conclusions:The level of barriers to going out in elderly COPD patients is moderate-to-high level. Healthcare professionals should emphasize the assessment of barriers to going out, closely monitor high-risk groups, and develop and implement interventions to prevent such barriers.

Aim To investigate the effect of N6-methy-ladenosine(m6A)demethylase ALKBH5 on the prolif-eration and migration of cardiac fibroblasts(CFs)in-duced by high glucose.Methods Primary CFs were isolated from neonatal mouse hearts and identified u-sing optical and confocal microscopy.Cell activation was induced using a high-glucose medium(33 mmol·L-1 glucose).An ALKBH5 overexpression model was established by transfecting CFs with an ALKBH5 ex-pression vector in a high-glucose medium.The expres-sion of ALKBH5 in CFs was assessed through immuno-fluorescence staining,Western blot and RT-qPCR.Changes in m6A levels were evaluated using Dot blot a-nalysis.Additionally,Alterations in the expression of proliferating cell nuclear antigen(PCNA)and collagenⅠ,a pivotal fibrosis indicator,were measured using Western blot.The proliferation and migration ability of CFs were assessed through EdU staining and Transwell migration assay,respectively.Results Following treatment with high glucose,the expression of ALKBH5 in CFs notably decreased,while m6A level increased.This was accompanied by a significant increase in the expression of the proliferation marker PCNA and the fi-brosis marker collagen Ⅰ.Additionally,there was a sig-nificant improvement in the ability of proliferation and migration.Overexpression of ALKBH5 resulted in a significant decrease in the expressions of PCNA and collagen Ⅰ,leading to the inhibition of both proliferation and migration in CFs.Conclusion Overexpression of ALKBH5 suppresses the expression of PCNA and colla-gen Ⅰ,consequently reducing the proliferation and mi-gration of CFs,potentially through m6A methylation modification.

Objective To explore the application effect of multimodal somatosensory exercise based on artificial intelligence technology in home rehabilitation exercise for elderly patients with chronic obstructive pulmonary dis-ease(COPD),so as to promote COPD patients to participate in home rehabilitation exercise.Methods Using the convenient sampling method,80 elderly patients with COPD admitted to the Department of Respiratory Medicine of a tertiary A hospital in Urumqi from November 2023 to February 2024 were selected as the research subjects.Ac-cording to the random number table method,they were divided into a control group and an experimental group,with 40 cases in each group.The control group adopted the traditional exercise training method,and the experimental group adopted the multi-modal somatosensory movement based on artificial intelligence technology for exercise in-tervention,with 5 times a week,and the intervention was implemented for 12 weeks.The pulmonary function index,modified Medical Research Council scale score,physical fitness level,Chronic Obstructive Pulmonary Disease As-sessment Test scale score and exercise compliance of the 2 groups were compared before intervention and 12 weeks after intervention.Results 77 patients completed the study,with 39 in the experimental group and 38 in the control group.The forced vital capacity,forced expiratory volume in one second,forced expiratory volume in one second to forced vital capacity ratio,physical fitness level and exercise compliance of the experimental group were higher than those of the control group,while the modified British Medical Research Council scale score and Chron-ic Obstructive Pulmonary Disease Assessment Test score were lower than those of the control group.The differences were statistically significant(P＜0.05).Conclusion Somatosensory exercise based on artificial intelligence technology can improve the lung function of the patients with COPD,improve the exercise compliance and physical fitness in-dicators of elderly patients and improve the quality of life of the patients.

In the study,calcium carbonate nanocubes(CCNC)were controllably prepared,and a simple and universal modified enzyme-linked immunosorbent assay(ELISA)method was developed for colorimetric and electrochemical dual-mode detection of lung cancer potential biomarker ferritin.The classic sandwich immunoassay mode was adopted.Monoclonal antibodies were modified on microwell of microplate and CCNC firstly.In the presence of ferritin,the CCNC were well captured on the surface of the microplate through the sandwich immunoreaction mode.Calcium ions released by acid hydrolysis formed a colored complex with the following added chromogenic agent,and the color of the sample solution changed from weak yellow to red.Spectrophotometry could be used for the quantitative detection of ferritin.Under the optimal conditions,the absorbance at 512 nm showed a good linear relationship with the logarithm of concentration of ferritin in the range of 1-250 ng/mL,with detection limit of 0.6 ng/mL,which was comparable that of the traditional ELISA method.In addition,gold nanoparticles(AuNPs)modified electrode-based electrochemical technique was also been introduced into the modified ELISA method.Under the optimized conditions,the linear range for ferritin test was 0.05-100 ng/mL,with an extreme low detection limit of 32 pg/mL(S/N>3).The CCNC probe used here exhibited obvious advantages over the enzyme probes in traditional ELISA technique in terms of stability,simplicity and cost,providing a new type of nanoprobe for ELISA technology.

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.