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.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

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 observe the effects of Yixintai on lipid metabolism and the protein expressions of CPT-1 and CD36 in rats with heart failure;To explore the mechanism of its treatment of heart failure.Methods 106 out of 120 SD rats were selected to establish the heart failure model induced by myocardial infarction by ligating the left anterior descending coronary artery,and 14 rats were selected as the sham-operation group.The successful model rats were randomly divided into model group,trimetazidine group and Yixintai low-,medium-and high-dosage groups,with 14 rats in each group.The administration group was given corresponding drugs by gavage once a day for 4 weeks.LVEF,LVFS,LVIDd and LVIDs were measured by color doppler ultrasonography,the contents of ANP,BNP,LA and FFA in serum were detected by ELISA,the contents of TG,TC,LDL and HDL were detected by automatic biochemical analyzer,HE and Masson staining were used to observe the morphology of myocardial tissue,the expressions of CPT-1 and CD36 protein in myocardial tissue were detected by Western blot.Results Compared with the sham-operation group,LVEF and LVFS in the model group decreased(P<0.05),the LVIDs and LVIDd increased(P<0.05);the contents of serum ANP,BNP,LA,FFA,TG,TC and LDL increased(P<0.05),while the content of HDL decreased(P<0.05),with myocardial edema,irregular arrangement of myocardial fibers,increased inflammatory cell infiltration and collagen fiber deposition;the protein expressions of CPT-1 and CD36 in myocardial tissue decreased(P<0.05).Compared with the model group,the LVEF and LVFS in Yixintai each dosage groups and trimetazidine group increased(P<0.05),LVIDs and LVIDd decreased(P<0.05);the contents of ANP,BNP,LA,FFA,TG,TC and LDL in serum of Yixintai medium-and high-dosage groups and trimetazidine group decreased(P<0.05),the content of HDL increased(P<0.05);myocardial edema was improved,inflammatory cell infiltration was reduced,collagen fiber deposition was reduced,and the protein expressions of CPT-1 and CD36 in myocardial tissue increased(P<0.05).Conclusion Yixintai may improve myocardial energy metabolism and treat heart failure by increasing the expression of CPT-1 and CD36 protein in myocardial tissue and promoting fatty acid β oxidation.

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.

This study was aimed at tracing the molecular typing and drug resistance characteristics of a suspected food poi-soning event caused by Clostridium perfringens in a district of Wuhan City.The FilmArray detection system and multiple fluo-rescence quantitative PCR methods were used to rapidly screen for pathogens in samples from the poisoning event.According to the initial screening results,bacteria were isolated,cultured,and identified by mass spectrometry.Fluorescence PCR was used to detect six virulence genes of the isolated Clostridium perfringens strains.On the basis of whole genome sequencing results,we conducted virulence genes,resistance genes,and whole genome single nucleotide polymorphism genetic evolution(wgSNPs)analyses.Antibiotic sensitivity testing was conducted with the agar dilution method.A total of ten strains of Clos-tridium perfringens were isolated,including eight strains from seven anal swab samples,one strain from fecal samples,and one strain from food samples.Food with suspected contamination had a Clostridium perfringens count of 7.8×106 CFU/g.The PLC(a)toxin gene was detected in all ten gas producing capsule isolation strains,but no other 5 tox-in genes such as CPE were detected,thus confirming that all were type A bacteria producing capsule Clostridium.All strains were 100％resistant to clindamycin and almost completely sensitive to antibiotics such as vancomycin,cefoxitin,and meropenem.Ten strains of Clos-tridium perfringens carried resistance genes such as tetB(P),tetA(P),and mprF,followed by ermQ(70％),ant(6)-Ⅰb(10％),and LnuP(10％).Genetic evolution analysis of wgSNPs indicated that the four outbreak strains clustered together and belonged to an independent subbranch with the suspected food sourcestrains,thus indicating close genetic relationships.In con-clusion,this food poisoning incident might have been be caused by hand torn chickens contaminated with Clostridium perfrin-gens,and the molecular types of the strains revealed high genetic diversity.No multiple drug resistance was observed,but all strains were resistant to clindamycin,an aspect requiring further clinical attention.

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.