Objective To develop an automatic segmentation network for thyroid nodules by integrating wavelet transform and CNN-Transformer in order to improve the efficiency and accuracy of ultrasound image segmentation.Methods A total of 1 371 sets of ultrasound images of thyroid nodules were collected from Department of Ultrasonography of Second Affiliated Hospital of Army Medical University between May 2023 and February 2024.After preprocessing and normalization,the data were divided into training,validation,and testing sets in a ratio of 8∶1∶1.Based on UNet,CNN and Swin-Transformer were used in parallel as the encoder,with a wavelet transform module inserted between the encoder and decoder to construct a thyroid nodule segmentation network.The performance of the segmentation model was evaluated on the collected internal dataset using accuracy,IoU,and Dice coefficient metrics.Results The finally verified 1 371 sets of ultrasonic thyroid nodules had an average Dice coefficient of 79.63%and an IoU of 67.30%.Compared with UNet,the segmentation accuracy was improved by 1.02%.The segmentation model obtained accurate location and smooth edges of thyroid nodules,and the segmentation was more consistent in thyroid nodule edge and morphology with those marked by doctors manually when compared with other segmentations.Compared with UNet,this segmentation method can learn the texture of nodules more fully and avoid the situation that nodules had been incorrectly divided into surrounding tissues.Conclusion Our developed segmentation model based on wavelet transform and CNN-Transformer demonstrates better segmentation accuracy in comparison to conventional UNet variants,such as UNet,Attention-UNet,and UNetv2,and medical segment anything models like SAM Med2D.This segmentation method enables accurate segmentation of ultrasound thyroid nodules,thereby enhancing clinical workflow efficiency through automated precise delineation.

Food safety problems caused by foodborne pathogenic bacteria pose a serious threat to public health,creating an urgent need to develop testing methods and techniques with excellent performance and are simple to use and of affordable cost.Traditional testing methods,such as isolation and culture,morphological observation,biochemical identification,and serological tests,have many limitations,including complex procedures,reliance on specialized technical equipment and personnel,and long turnaround time,rendering them inadequate for meeting current and future testing demands.Therefore,it is particularly important to develop simple,rapid,and highly sensitive methods for analyzing pathogenic bacteria.The fusion of nucleic acid aptamers and nanozymes brings new ideas for the rapid testing of pathogenic bacteria.On one hand,aptamers offer specific recognition capability for target bacteria and can be combined with various nucleic acid signal amplification techniques.On the other hand,the enzyme-like catalytic activity and signal amplification effect of many nanomaterials provide a basis for highly sensitive testing.This review highlights the application potential of nanozyme?aptamer coupling systems in the field of microbial analysis by briefly summarizing the latest research progress in the use of nanozymes combined with aptamers for the detection of foodborne pathogenic bacteria.First of all,two main approaches to conjugating nanozymes with aptamers are introduced.Then,the testing mechanisms and typical applications of nanozyme?aptamer coupling systems for foodborne pathogenic bacteria are discussed.Finally,future development trends and existing challenges are disucssed from four perspectives,including specificity,high sensitivity,high throughput,and intelligent detection.This review aims to provide a useful reference for the fusion of nanozymes and aptamers and for the development of on-site rapid testing techniques for foodborne pathogens,and to encourage broader academic interest to further advance this promising research field.

Objective:To examine the structural network changes in participants with amnestic mild cognitive impairment(aMCI)and investigate the correlation between these changes and the onset of Alzheimer's disease(AD).Methods:In this prospective study, a total of 100 individuals with amnestic mild cognitive impairment(aMCI)were enrolled as the research group.Additionally, 25 healthy individuals who were matched in terms of age and sex were enrolled as healthy controls.Upon enrollment, all participants underwent MRI scans, neuropsychological assessments, and clinical evaluations.The participants were then followed every 6 months for a period of 36 months or until they withdrew from the study.Based on the outcome of the follow-up(whether Alzheimer's disease occurred), the aMCI participants were divided into two groups: stable aMCI group and progressive aMCI group.The Chinese version of the Brief Mental State Examination(MMSE), the Montreal Cognitive Assessment(MoCA), the Clinical Dementia Rating Scale(CDR), and the Auditory Word Learning Test(AVLT)were utilized to evaluate the overall mental and cognitive status of the subjects.Pearson correlation analysis was employed to investigate the relationship between structural network changes and cognitive decline.Logistic regression was performed to analyze the predictive ability of structural network changes in determining the onset of AD.Results:Compared to the stable aMCI group, the progressive aMCI group exhibited lower levels of global efficiency( P=0.002), local efficiency( P=0.007), feeder connections( P=0.003), local connections( P=0.008), and right precuneus nodal efficiency( P=0.010).Correlation analysis revealed that global efficiency( r=0.604, P=0.002), feeder connections( r=0.513, P=0.012), and right precuneus nodal efficiency( r=0.504, P=0.014)were correlated with AVLT-delay scores(baseline)in the progressive aMCI group.A logistic regression model demonstrated that global efficiency, feeder connections, and right precuneus nodal efficiency could significantly predict the onset of AD(all P<0.05, AUCunited=0.797, 95% CI: 0.684-0.884, sensitivity=73.91, 95% CI: 51.6-89.8, specificity=76.60, 95% CI: 62.0-87.7). Conclusions:Among participants with aMCI, individuals who exhibit lower global efficiency, feeder connections, or right precuneus nodal efficiency are at a higher risk of developing AD.These indicators are anticipated to serve as new targets for clinical intervention.

Objective:To explore the association between changes in brain structural network during the early stage of stroke recovery and the onset of post-stroke depression (PSD).Methods:A total of 87 acute ischemic stroke patients scheduled for discharge, who were admitted to the Yixing Hospital Affiliated to Jiangsu University from March 2020 to May 2021, were prospectively collected. During the same period, 34 healthy control subjects matched with the stroke patients were also collected. All participants underwent systematic magnetic resonance imaging scans and scale assessments, and were followed up longitudinally for 2 years. Based on the occurrence of depression during follow-up, the stroke patients were divided into PSD group and post-stroke non-depression (PSND) group. Graph theoretical analysis was used to analyze the topological characteristics of brain structural network. Analysis of variance was used to explore the differences in brain structural network attributes among groups. Logistic regression model was used to analyze the predictive power of differential brain network attributes for PSD. Linear regression analysis was conducted to investigate the relationship between the synergism of non-rich-club regions and changes in rich-club connectivity.Results:The rich-club connectivity and synergism of the non-rich-club regions were significantly lower in the PSD group than in the PSND group (rich-club connectivity, P<0.01; synergism of feeder/local, P<0.001). The regression model demonstrated that the synergism of non-rich-club regions had a good predictive power for the occurrence of PSD ( OR=1.195, 95%CI 1.073-1.471, P<0.001). Furthermore, linear regression analysis revealed a significant correlation between the synergism of non-rich-club regions and Δrich-club connectivity ( r=-0.691, P<0.001). Conclusion:The good synergism of non-rich-club regions during the early stage of stroke recovery promotes the repair of rich-club connectivity and inhibits the onset of PSD.

Objective:To investigate the features of the brain structural network in patients with postpartum depression (PPD).Methods:This cross-sectional study included PPD patients who visited the mental health counseling clinic after delivery at the Jiangsu University Affiliated Yixing Hospital from June 2013 to September 2022 (PPD group). Matched non-PPD postpartum women based on age, years of education, and body mass index who came for postpartum follow-up (non-PPD postpartum group), and non-pregnant women who visited the hospital or underwent physical examinations during the same period (non-pregnant group) were also included. Demographic data and diffusion tensor imaging (DTI) data were collected for all three groups. The brain was partitioned into 90 regions using an anatomical template to construct the brain structural network. Network-based statistics (NBS) were applied to further screen and construct subnetworks. The efficacy of the subnetworks in identifying PPD was evaluated through multivariable logistics regression models and receiver operating characteristic curves. A comparison of the connectivity strength of white matter tracts and topological attributes of brain structural network parameters was conducted using independent samples t-tests, and the results were corrected using the false discovery rate (FDR) method. Results:(1) A total of 116 subjects were included, with 40 in the non-pregnant group, 40 in the non-PPD postpartum group, and 36 in the PPD group. PPD group had higher Edinburgh Postnatal Depression Scale (EPDS) scores than the non-pregnant and non-PPD postpartum groups [(18.0±4.1) scores vs. (2.5±1.2) and (6.1±2.1) scores, F=340.40; t=24.65,10.60 and 16.16 in pairwise comparison; all P<0.001]. (2) Compared to the non-pregnant group, there was a decrease in the connectivity strength of nine white matter tracts within the brain structural network of the postpartum group (including left dorsolateral superior frontal gyrus-left anterior cingulate and paracingulate gyrus, left dorsolateral superior frontal gyrus-right amygdala, left dorsolateral superior frontal gyrus-left insula, left insula-left lentiform nucleus, left insula-left hippocampus, left hippocampus-right amygdala, left hippocampus-left precuneus, left anterior cingulate and paracingulate gyrus-right amygdala, and right amygdala-right hippocampus) (all P<0.05, FDR corrected). No increased connection strengths were observed. There were no significant differences in the connection strengths of these nine tracts between the non-PPD and PPD groups. (3) A characteristic subnetwork for the maternal group was successfully constructed based on the nine tracts, which exhibited typical small-world properties (σ>1). Compared to the non-PPD maternal group, the characteristic path length in the PPD group was increased [(3.904±0.328) vs. (4.130±0.433), t=－2.58], and global efficiency was decreased [(0.361±0.036) vs. (0.331±0.053), t=2.91] (both P<0.05). Local property comparisons showed that the node efficiency values for the left dorsolateral superior frontal gyrus, left insula, left anterior cingulate and paracingulate gyrus, left hippocampus, right hippocampus, right amygdala, left precuneus and left putamen in the PPD group were significantly reduced [(0.273±0.023) vs. (0.267±0.030), t=0.98; (0.299±0.035) vs. (0.276±0.041), t=2.64; (0.265±0.019) vs. (0.258±0.025), t=1.38; (0.318±0.028) vs. (0.305±0.031), t=1.92; (0.312±0.027) vs. (0.302±0.031), t=1.50; (0.322±0.030) vs. (0.298±0.026), t=3.71; (0.356±0.040) vs. (0.338±0.056), t=1.62; (0.346±0.028) vs. (0.331±0.036), t=1.74; all P<0.05]. However, only the differences in node efficiency values for the left insula and right amygdala remained significant after FDR correction (corrected P=0.041 and 0.003). (4) Global efficiency, as well as node efficiency for the left insula and right amygdala, demonstrated good value for identifying PPD [areas under the curve (AUC) and their 95% CI were 0.827 (0.732-0.922), 0.741 (0.628-0.854), and 0.761 (0.653-0.867), respectively], with even better performance when combined [0.897 (0.828-0.969)]. (5) In the PPD group, global efficiency ( r=－0.43, P=0.008), node efficiency for the left insula ( r=－0.39, P=0.019), and node efficiency for the right amygdala ( r=－0.42, P=0.011) were all negatively correlated with EPDS scores. Conclusion:Aberrations in global efficiency, node efficiency for the left insula, and node efficiency for the right amygdala may serve as characteristic neuroimaging biomarkers for PPD.

Objective:To investigate the effects of multidisciplinary small-class teaching on expertise and skill acquisition and learning experience in standardized residency training in general surgery.Methods:Sixty residents of grade 2021 rotating in general surgery from January to August 2023 were divided into multidisciplinary teaching group ( n=30) and traditional teaching group ( n=30, to receive tradition one-on-one teaching). All the residents underwent a theoretical examination and Mini-Clinical Evaluation Exercise (Mini-CEX) skill assessment before admission, and the scores were compared between the two groups. At the end of training, the two groups were compared in terms of theoretical and Mini-CEX skill assessment scores and the degree of satisfaction with teaching. Statistical analysis was conducted using SPSS 26.0. Results:There were no significant differences in the theoretical assessment and Mini-CEX skill assessment scores before admission between the two groups ( P>0.05). At the end of training, the multidisciplinary teaching group had a significantly higher theoretical examination score [(88.15±3.45) vs. (72.25±4.36), P<0.05] and a significantly higher Mini-CEX score [(86.35±2.24) vs. (76.28±3.92), P<0.05] compared with the traditional teaching group. According to the survey, the residents in the multidisciplinary teaching group were more satisfied with teaching and more likely to recognize the teaching effects. Conclusions:Multidisciplinary small-class teaching can help improve the quality of standardized general surgery residency training on gastrointestinal tumor treatment, which is a highly accepted and effective attempt at standardized residency training.

OBJECTIVE：To provide reference for improving the operation efficiency of drug quality sampling and inspection in China . METHODS ：Starting from the application and management situation of inspection standards/methods in provincial inspection institutions ，the problems existing in the application and management of inspection standards/methods in provincial inspection institutions were analyzed ；the inspection standards/methods database of provincial inspection institutions is attempted to build，combining with the relevant experience and practices of FDA. RESULTS & CONCLUSIONS ：The inspection methods involved in drug sampling and inspection could be divided into official standards and non-standard methods. Official standards were the main standards for drug sampling and inspection ，and were mainly used for routine inspection. Such kind of standards could be classified according to the characteristics of compiled ，single-page and later-issued supplementary ；an electronic catalogue should be established for unified management. Non-standard methods were only used for sample preliminary screening ，verification of official inspection results ，quality evaluation and inspection of unknown or suspicious samples in emergency inspection. Its tracking，collection and management mechanisms were not yet complete. It is recommended to draw on the experience of drug sampling and inspection in the United States so as to establish method database hierarchically. For the mature method established in drug supervision system ，an electronic catalog and document content database should be established and the method should be confirmed before use ；for national standards and the recommended methods published by authoritative institutions in other industries，and mature methods published in scientific and technological literature ，the retrieval channels should be listed ，the methods should be verified ，reviewed and approved before use ，and an electronic catalogue should be established and recorded in time after use. The electronic catalogue format of non-standard methods generally include controlled number ，applicable variety name，method name ，inspection items ，etc.

Objective:To detect the levels of serum IgM and IgG antibodies against 2019-nCoV in 79 patients with COVID-19 for understanding their variation patterns in vivo. Methods:Chemiluminescence immunoassay was used to detect the levels of 2019-nCoV-specific IgM and IgG antibodies in 167 serum samples collected at different periods (≤10 d, 10<~20 d, 20<~30 d、>30 d) after disease onset from 79 clinically confirmed COVID-19 patients in Hangzhou Xixi Hospital. The results were statistically analyzed together with clinical data.Results:The average levels of IgM and IgG antibodies in severe and common cases were higher than those in mild cases [IgM: 21.77 (10.18-128.65) and 13.13 (6.08-35.14) vs 3.01(1.69-8.69), χ 2=27.442, P<0.01; IgG: (124.22±36.79) and (120.04±63.25) vs (52.31±53.68), F/χ 2=27.295, P<0.01]. The positive rates of IgM and IgG antibodies in severe and common cases were also higher than those in mild cases after recovery ( P<0.01). The levels of IgM and IgG antibodies were affected by the time of detection. The level of IgM antibody detected during 10<~20 d of the disease onset was significantly higher than that within 10 d of the disease onset ( P<0.05). The level of IgG antibody detected after 10 d of the disease onset was significantly higher than that within 10 d of the disease onset ( P<0.01). Conclusions:Higher levels of IgM and IgG antibodies were detected in patients with severe COVID-19. A significant correlation was found between the levels of IgM and IgG antibodies and the time of detection.

Objective To investigate implementing approach and clinical effect of 4-dimensional innovative model basing on JCI standards on health education to elderly patients with CHD.Methods Following JCI standards, a 4-dimensional model was innovated, regarding 4 aspects of health education for elderly patients with CHD:concept, platform, transmission system and technological application. Totals of 120 elderly patients with CHD were divided randomly into observation group and control group. For the patients in the observation group, health education was conducted according to the 4-dimentional innovative model, while in the control group, routine health education approach for CHD was used, which was to hand out health pamphlets explaining knowledge concerning diet, drug, exercise, follow-up visit, etc. After 5 days of intervention, CHD organism functional status and quality of life of the CHD patients in the two groups were evaluated and compared. Indexes, such as self-management skills, were compared 6 months after discharge. Results In SAQ scoring, there were significant differences between observation group and control group regarding limitation degree of motion, attacking condition of angina or stable condition of angina, scores of satisfaction on treatment and awareness of the disease ( P<0. 05 ) . Conclusions Conducting health education to elderly patients with CHD with the 4-dimensional innovative model basing on JCI standards plays a significant role in promoting guarantee of medical safety, prevention of harmful cardiac incidents, and enhancement of treatment compliance, patients′ self-management abilities and patients′satisfaction.