Purpose: The aim of this study was to investigate the feasibility of an intelligent handheld ultrasound (US) device for assisting non-expert general practitioners (GPs) in detecting carotid plaques (CPs) in community populations. Methods: This prospective parallel controlled trial recruited 111 consecutive community residents. All of them underwent examinations by non-expert GPs and specialist doctors using handheld US devices (setting A, setting B, and setting C). The results of setting C with specialist doctors were considered the gold standard. Carotid intima-media thickness (CIMT) and the features of CPs were measured and recorded. The diagnostic performance of GPs in distinguishing CPs was evaluated using a receiver operating characteristic curve. Inter-observer agreement was compared using the intragroup correlation coefficient (ICC). Questionnaires were completed to evaluate clinical benefits. Results: Among the 111 community residents, 80, 96, and 112 CPs were detected in settings A, B, and C, respectively. Setting B exhibited better diagnostic performance than setting A for detecting CPs (area under the curve, 0.856 vs. 0.749; P<0.01). Setting B had better consistency with setting C than setting A in CIMT measurement and the assessment of CPs (ICC, 0.731 to 0.923). Moreover, measurements in setting B required less time than the other two settings (44.59 seconds vs. 108.87 seconds vs. 126.13 seconds, both P<0.01). Conclusion Using an intelligent handheld US device, GPs can perform CP screening and achieve a diagnostic capability comparable to that of specialist doctors.

Objective:To investigate the regulatory effects of transcutaneous auricular vagus nerve stimulation (taVNS) on functional connectivity (FC) of thalamic subregions in patients with premenstrual syndrome (PMS).Methods:This study was a cross-sectional investigation. Clinical, laboratory, and imaging data were retrospectively collected from 56 PMS patients (PMS group) and 66 healthy controls (control group) recruited from various universities and hospitals in Nanning between November 2021 and June 2024. Resting-state functional MRI (fMRI) data and fMRI data during taVNS immediate stimulation (2 Hz, 25 Hz) were acquired from subjects during their late luteal phase. Using thalamic subregions (anterior thalamic nucleus, lateral nucleus, ventral nucleus, medial nucleus, central nucleus, posterior nucleus) as seeds, two-sample t-tests or paired t-tests were employed to analyze alterations in thalamic subregion FC in PMS patients and the regulatory effects of taVNS on these changes. Independent samples t-test were used to compare the differences in clinical and laboratory indicators between the PMS group and the control group. The relationship between taVNS regulation of thalamic subregion FC in PMS patients and thalamic internal functional connectivity were analyzed using mediation effect analysis. Results:Compared to the control group, patients in the PMS group showed increased scores on the Daily Record of Severity of Problems, Pittsburgh Sleep Quality Index, Self-Rating Anxiety Scale, Self-Rating Depression Scale, Hamilton Anxiety Rating Scale 17, and Hamilton Depression Rating Scale 14 during the late luteal phase ( P<0.05). At baseline, PMS patients exhibited higher FC between the left thalamic lateral nucleus and the left insula, and lower FC between the left medial nucleus, posterior nucleus, and ventral nucleus of the thalamus and the right middle frontal gyrus (MFG) compared to the control group (GRF corrected, voxel-level P<0.001, cluster-level P<0.05). During 2 Hz taVNS immediate stimulation in PMS group, FC between the left thalamic medial nucleus, posterior nucleus, ventral nucleus and the right MFG, as well as the FC between the left thalamic ventral nucleu and the left MFG increased compared to baseline levels; meanwhile, FC between the left thalamic posterior nucleus, ventral nucleus and the left insula decreased compared to baseline levels (GRF corrected, voxel-level P<0.001, cluster-level P<0.05). During 25 Hz taVNS immediate stimulation, the FC between the left thalamic ventral nucleus and the right MFG decreased compared to the baseline level (GRF corrected, voxel-level P<0.001, cluster-level P<0.05). Mediation effect analysis showed that the FC between the left thalamic posterior nucleus and the left lateral nucleus mediated part of the association between the FC of the left lateral thalamic nucleus-left insula and the FC of the left ventral thalamic nucleus-left putamen/insula; there were significant direct effects between the FC of the left lateral thalamic nucleus-the left posterior nucleus and FC of the left lateral thalamic nucleus-the left insula, as well as between the FC of the left ventral thalamic nucleus-the left MFG and FC of the left ventral thalamic nucleus-the right MFG. Conclusions:taVNS can modulate abnormal FC of the left thalamic subregions in PMS patients, restoring it toward normalization. The regulatory effects of 2 Hz stimulation are more pronounced than those of 25 Hz stimulation. This modulation primarily operates through two pathways: the left thalamic lateral nucleus-left insula-left thalamic ventral nucleus pathway and the left MFG-left thalamic ventral nucleus-right MFG.

Objective To explore the causal relationship between breast cancer and free fatty acid receptor 4(FFAR4)by using two-sample Mendelian randomization.Methods By using Genome-wide Association Studies and expression quantitative trait locus(eQTL)data,single nucleotide polymorphism sites closely related to breast cancer and FFAR4 were extracted.Causal effect values were calculated by using five methods:inverse variance weighting(IVW),MR-Egger,weighted median,simple mode and weighted mode.Cochran Q tests were used to detect heterogeneity,MR-Egger intercept tests and MR-PRESSO tests were used to assess level multiplicity,and the hold-out method was employed for sensitivity analysis to ensure robustness of the results.Additionally,Bayesian co-location analysis was used to evaluate whether FFAR4 expression shares the same causal genetic variant with breast cancer in given genomic region.Results A total of 12 eQTLs closely related to FFAR4 expression levels were included in this study.The results of IVW analysis showed that increased FFAR4 expression levels increased the risk of overall breast cancer,Luminal A,Luminal B/HER2-negative,and HER2-enhanced subtypes of breast cancer.The co-location analysis showed that the posterior probability of FFAR4 expression level and total breast cancer shared causal variation was 0.889.Conclusion There may be a causal relationship between FFAR4 expression and breast cancer.

Objective To analyze the application of in-use laparoscopes in clincal departments to enhance the laparoscope's effectiveness.Methods The effective utilization data of 29 laparoscopes from January 2024 to June 2024 were acquired with an hospital intelligent medical device management platform.Comparisons were carried out in terms of average daily workload,average daily hours of use and average daily efficiency between the laparoscopes from different departments and brands with non-parametric Kruskal-Wallis test and between the conventional and 3D laparoscopes with non-parametric Mann-Whitney U test.Pearson's correlation coefficient was used to analyze the correlation between the number of years of laparoscope use and the average daily workload,the average daily hours of use,and the average daily efficiency and the chi-square test was applied to investigating the relationship between the surgery grade and the type of equipment selected.Results Thoracic sugery department had the highest average daily workload(3.82 person-time),while the general medical department had the highest average daily hours of use(443.76 min)and the highest daily efficiency(92.45％).There were significant differences between the laparoscopes from different departments in average daily workload,average daily hours of use and average daily efficiency(P＜0.05).Brand D laparoscope behaved the best among brands of laparoscopes with the highest average daily workload(3.72 person-time),average daily hours of use(394.41 min)and average daily efficiency(82.17％).There were sig-nificant differences between the brands of laparoscopesin average daily workload,average daily hours of use and average daily efficiency(P＜0.05).3D laparoscopes obviously gained advantages over the conventional ones in average daily workload,average daily hours of use and average daily efficiency(P＜0.05).The number of years of use correlated negatively with average daily workload,average daily hours of use and average daily efficiency,with Pearson correlation coefficients being-0.095,-0.039 and-0.039 respectively.Grade Three and Four surgeries had significant differences in types of selected equipment(P＜0.001),and 3D laparoscopes were preferred for Grade Four surgery.Conclusion Utilization analysis of laparoscopes provides data support for optimized application and setup of laparoscopes.[Chinese Medical Equipment Journal,2025,46(2):87-91]

Objective To explore the relationship between community health follow-up management and the mental health of the long-term care insurance residents,and to provide a basis for the construction of an integrated community home care service mode for disabled elders.Methods The residents were selected through cluster sampling who participated in LTCI home care from Jan 1 to Dec 31,2021.After a year of participation,the subjects'mental health was assessed face-to-face by trained community doctors using the Self-Rating Anxiety Scale and the Self-Rating Depression Scale.By referring to residents'electronic health records combined with on-site questionnaire survey,community doctors collected the demographic information and health follow-up management provided by primary medical and health institutions.The multivariate logistic regression were conducted to evaluate the association between follow-up care and mental health outcomes.Results The study consisted of 399 LTCI-enrolled individuals,57.64%(n=230)received follow-up care by family physicians.The prevalence of anxiety and depression among participants was 19.80%(n=79)and 67.67%(n=270),respectively.Univariate analysis found that community health follow-up management could underscore the potential impact of follow-up care in mitigating anxiety(χ2=38.926,P<0.001)and depression(χ2=14.598,P<0.001)among LTCI enrollees.Multivariate analysis revealed that follow-up care was an independent protective factor against anxiety(adjusted OR=0.351,95%CI:0.176-0.701,P=0.003).However,follow-up care did not significantly impact depression prevalence.Additionally,LTCI grade and education level were also identified factors influencing the mental health of participants(P<0.05).Conclusion Community health service centers provide health follow-up management that plays a positive role in alleviating the anxiety symptoms of disabled residents under long-term care insurance home care.It is an effective way to improve the quality of LTCI home care services.

Objective To investigate the stability and reproducibility of the treatment fractions during the intensity-modulated radiotherapy(IMRT)for breast cancer and the effect of respiratory motion on the dose irradiation of breast cancer radiotherapy by comparing the results of breast cancer dosimetric verification based on fractionated images by an electronic portal imaging device(EPID).Methods A total of 28 IMRT patients admitted to some hospital from January to June 2023 were grouped according to the pathological results and effects of respiratory motion on the accuracy of radiotherapy during clinical treatment,including 14 cases in a breast group and 14 cases in a non-breast group with 8 ones of head and neck tumors,5 ones of esophageal cancer and 1 case of cervical cancer.All the patients underwent a scan with cone beam computed tomography(CBCT)before the first radiotherapy,and image registration was carried out with a positioning CT.An EPID was used to acquire transmission dose images of 10 fractions of radiotherapy,and γ analysis was performed using the RIT 113 QA software to compare the images of the subsequent 9 fractions with those of the first fraction,with the images of the first fraction of radiotherapy as the baseline values.Absolute maximum dose normalization was implemented under the condition of 10％dose assessment threshold,and the γ-pass rates under the 3 criteria of 2％/2 mm,3％/2 mm and 3％/3 mm were counted separately.The fraction dose verification results of the 28 patients were divided into 3 treatment phases of 2-4 times(T1),5-7 times(T2)and 8-10 times(T3)to analyze the stability of dose irradiation during the radiotherapy.SPSS 22.0 software was used for statistical analysis.Results Under the condition of 10％dose assessment threshold,the breast and non-breast groups had the γ-pass rates being(95.80±2.65)％and(94.60±6.59)％under the 2％/2 mm criterion and(98.46±1.31)％and(97.50±3.30)％under the 3％/2 mm criterion respectively,and the differences were statistically significant(all P<0.05).Under the assessment criteria of 2％/2 mm,3％/2 mm and 3％/3 mm,the breast group had the γ-pass rates of fractions of treatment significantly lower than those of the non-breast group(all P<0.05),while the γ-pass rates showed no significant differences at T1,T2 and T3 treatment phases(all P>0.05).Conclusion EPID fraction images contribute to evaluating IMRT accuracy effectively.IMRT has high stability and reproducibility during the treatment cycle,while respiration may result in dose deviation during the fraction radiotherapy for breast cancer,and optical surface tracking technology or active breathing control technology is suggested to be involved in to relieve dose deviation.[Chinese Medical Equipment Journal,2025,46(6):54-58]

Compared to traditional machine learning algorithms,which often suffer from low feature extraction efficiency,insufficient nonlinear pattern recognition capabilities and slow training speeds,the broad learning system(BLS)enhances the learning ability and efficiency by horizontally expanding the network structure.BLS offers advantages such as a simple structure,fast training speed,and strong generalization capabilities.While BLS has demonstrated potential in various fields,but its application in identification of complex samples has not been fully explored.This research investigated the feasibility of using BLS algorithm for identification of complex samples based on physicochemical indicators.Using the iris,wine,and breast cancer datasets,the length and width of petals and sepals of iris flowers,the physicochemical properties of wine,and the nuclear characteristics of breast cancer cells were used as input variables to establish BLS models for identifying iris species,wine varieties,and benign versus malignant nucleus.The model performance was evaluated by confusion matrices,accuracy,and runtime.Compared with partial least squares-discriminant analysis(PLS-DA),soft independent modeling of class analogies(SIMCA),and artificial neural networks(ANN),the results indicated that BLS demonstrated significant advantages in computational efficiency and recognition accuracy.Thus,BLS was an efficient and reliable method for identification of complex samples.

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.

Cancer is the main cause of death,and drug therapy has greatly improved the effectiveness of anti-tumor treatment.However,there are problems such as high adverse reactions and the risk of developing drug resistance after long-term use.There is an urgent need to seek new drug targets.Human antigen R(HuR),as an RNA binding protein,promotes the whole process of tumor occurrence,development and metastasis through post transcriptional regulation of mRNA stability,and HuR is general-ly highly expressed in tumor tissue,making it a new target for an-ti-tumor therapy and a standard for prognosis evaluation.Tradi-tional Chinese medicine formulas and their various chemical components can inhibit tumor proliferation,induce tumor cell ap-optosis,inhibit angiogenesis,suppress immune escape,and re-verse tumor drug resistance by regulating HuR activity.This re-view summarizes the importance of HuR in regulation of tumor progression,as well as analyzes the mechanisms of the antitumor effects through active ingredients of Chinese medicine with the regulation of HuR.It is expected to provide new ideas for tumor therapy and guidance for the development of HuR-targeted anti-tumor drugs.