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.

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.

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.

A portable molecularly imprinted(MIP)surface-enhanced Raman scattering(SERS)chip was fabricated via a green electrochemical approach for highly selective detection of bisphenol A(BPA).This MIP-AuNP/UIO-66/SPE sensor was fabricated through a single-step co-deposition process.The process involved electropolymerization onto a UIO-66 modified screen-printed electrode(SPE),by usingo-phenylenediamine(OPD)as functional monomer and BPA as template,and simultaneously electro-reduction generated gold nanoparticles(AuNPs),which served as the SERS-active substrate.Ultimately,this one-step method formed a three-dimensional porous architecture on the electrode surface.Under 785 nm laser excitation,the sensing chip exhibited a highly sensitive SERS response towards BPA.The intensity of its characteristic peak at 850 cm-1 showed a good linear relationship with logarithm of BPA concentration in the range of 1.0×10-10 to 1.0×10-6 mol/L,with a detection limit of 1.0×10-12 mol/L.More importantly,the fabricated chips maintained highly selective binding affinity for BPA in water samples even in the presence of structural analogs bisphenol F(BPF)and bisphenol S(BPS).When the chip was applied to detection of BPA in water samples from plastic bottle and paper cup,the recovery rates ranged from 94.0%to 103.0%with relative standard deviations(RSD)less than 4.7%.The developed chip offered a highly sensitive and selective solution for detection of trace BPA in complex water 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.

Objective To investigate the correlation between sleep duration and chest pain in the Chinese population.Methods A cross-sectional analysis was conducted using data on chest pain and sleep duration from 7942 participants in the 2018 China Health and Retirement Longitudinal Study(CHARLS).Among them,1239 had chest pain and 6703 did not;2645 were aged>65 years and 5297 were aged≤65 years.All participants were categorized into three groups based on sleep duration:≤6 h(n=3123),6-8 h(n=2959),and>8 h(n=1860).Differences in characteristics such as gender,age,marital status,education level,diabetes,and hypertension were compared across these groups.Multivariate logistic regression analysis,curve fitting,and threshold effect analysis were further employed to explore the correlation between sleep duration and chest pain.Results A total of 7942 participants were finally included in the study.Among the three groups with sleep duration>8 h,6-8 h and≤6 h,the incidences of chest pain were 12.6%,13.0%,and 19.8%,respectively.Multivariate logistic regression analysis demonstrated that with the increase in sleep duration,the incidence of chest pain showed a decreasing trend[odds ratio(OR)=0.88,95%confidence interval(CI)0.86-0.91,P<0.001].Curve fitting and threshold effect analysis indicated a U-shaped relationship between sleep duration and the risk of chest pain.In the population aged≤65 years,the inflection point for sleep duration was 8.5 h,beyond which the risk of chest pain did not decrease;in the population aged>65 years,the inflection point was 7.7 h,beyond which the risk of chest pain significantly increased(P<0.05).Conclusions There is a U-shape relationship between sleep duration and the risk of chest pain.In the age group≤65 years old,8.5 h is the turning point;in the population>65 years old,7.7 h is the turning point.When the sleep duration is below the turning point,prolonging the sleep time can help reduce the risk of chest pain.It is recommended to maintain an appropriate sleep duration of 6-8 h to reduce the risk of chest pain.

Objective To investigate the effects of Chaihuang Qingyi Huoxue Granules on multiple organ damage induced by caerulein combined with lipopolysaccharide in mice with severe acute pancreatitis(SAP).Methods Twenty-four C57BL/6J mice were randomly divided into three groups:control(n=8),SAP(n=8)and Chaihuang Qingyi Huoxue Granules(CHQY group,n=8).Mice in SAP and CHQY groups were intraperitoneally injected with caerulein(50 μg/kg)at hourly intervals for 7 consecutive times,followed by an immediate intraperitoneal injection of lipopolysaccharide(10 mg/kg).Mice in control group received an equal volume of normal saline.After the successful establishment of the model,CHQY group mice were administered Chaihuang Qingyi Huoxue Granules[3.185 g/(kg·d)]via gavage,while control and SAP group mice received an equal volume of normal saline.Twenty-four hours post-modeling,mice were anesthetized,and serum was collected and separated for analysis of the activities of amylase(AMY),lipase(LPS),aspartate transaminase(AST),alanine transaminase(ALT)and the contents of creatinine(CREA)and urea(UREA)using an automatic biochemical analyzer.Serum levels of interleukin(IL)-1β,IL-6,IL-8,IL-18,and tumor necrosis factor-α(TNF-α)were measured by ELISA.Tissue samples from pancreas,lung,liver,kidney,and small intestine were collected for histopathological examination using hematoxylin-eosin(HE)staining and scored.The expression of nuclear factor-κB p65(NF-κB p65)was detected in all tissues by immunohistochemistry.Results Compared with control group,the activities of AMY,LPS,AST and ALT,and the contents of CREA,UREA,IL-1β,IL-6,IL-8,IL-18,and TNF-α were increased(P<0.05).Pathological injuries in the pancreas,lung,liver,kidney,and small intestine was significant,with increased pathological scores and a higher proportion of NF-κB p65 positive cells(P<0.05).Compared with SAP group,the activities of AMY,LPS,AST,ALT,and the contents of CREA,UREA,IL-1β,IL-6,IL-8,IL-18,and TNF-α in the serum of CHQY group were decreased(P<0.05).Pathological injuries in the pancreas,lung,liver,kidney and small intestine were reduced,with lower pathological scores and a decreased proportion of NF-κB p65 positive cells(P<0.05).Conclusion Chaihuang Qingyi Huoxue Granules have a certain therapeutic effect on SAP model mice,which may be related to reducing inflammation response and improving multiple organ damage such as the pancreas,lung,liver,kidney and small intestine.

Alzheimer's disease(AD)is a common neurodegenerative disease in the elderly.Increasing evidence shows that peripheral immune cells are involved in the occurrence and development of AD.Both gut microbiota dysbiosis and abnormalities of peripheral immune cells occur in the early stage of AD.The gut microbiota can influence the central nervous system through mechanisms such as the gut-brain axis and the regulatory effects on peripheral immune cells.AD treatment methods targeting the gut microbiota and immune cells have been receiving increasing attention.This review summarizes the regulatory effects and mechanisms of the gut microbiota on peripheral immune cells,as well as the research progress on the gut microbiota's roles in the occurrence and development of AD,aiming to provide new ideas for relevant research on the prevention,diagnosis,and treatment of AD.

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.