ObjectiveTo investigate the association between noninvasive liver fibrosis markers and carotid plaque （CP） in patients with lean metabolic dysfunction-associated fatty liver disease （MAFLD）， and to provide a basis for screening high-risk populations. MethodsA total of 957 patients with lean MAFLD who underwent physical examination in Subei People’s Hospital from January 2021 to June 2023 was enrolled as the observation cohort， with the presence or absence of CP as the outcome， and fibrosis-4 （FIB-4） index and nonalcoholic fatty liver disease fibrosis score （NFS） were used to assess liver fibrosis degree. The independent-samples t test was used for comparison of normally distributed continuous data between two groups， and the Mann-Whitney U test was used for comparison of non-normally distributed continuous data between two groups； the chi-square test was used for comparison of categorical data between two groups. The multivariate logistic regression analysis， the restricted cubic spline analysis， the receiver operating characteristic curve， and the mediation effect analysis were used to investigate the association between liver fibrosis degree and CP. ResultsThe prevalence rate of CP was 36.6% in the lean MAFLD population. Compared with the non-CP group（n=607）， the CP group （n=350） had a significantly higher proportion of male patients， a significantly higher proportion of patients with smoking/diabetes/hypertension， and significantly higher levels of age， creatinine， blood urea nitrogen， triglycerides， fasting blood glucose， aspartate aminotransferase， aspartate aminotransferase/alanine aminotransferase ratio， NFS， and FIB-4 index， as well as significantly lower levels of platelet count and albumin （all P<0.05）. The multivariate logistic regression analysis showed that after adjustment for confounding factors， FIB-4 index （odds ratio［OR］=2.979， 95% confidence interval［CI］：2.141 — 4.219， P<0.001） and NFS （OR=1.747， 95%CI： 1.499 — 2.046， P<0.001） were positively correlated with CP. Both FIB-4 index and NFS had a good value in predicting CP. Hypertension had a significant indirect effect on the prevalence rate of CP through its impact on liver fibrosis markers， and its mediating effect accounted for 39.5% — 40.8% of the total effect （P<0.001）. ConclusionIn patients with lean MAFLD， NFS and FIB-4 index are significantly positively correlated with the prevalence rate of CP， and they can be used as potential epidemiological predictive indicators. Liver fibrosis markers may play a mediating role in the association between hypertension and CP. Interventions targeting hypertension and liver fibrosis markers may help to prevent and delay the progression of CP.

ObjectiveTo investigate the association of liver fibrosis scores and inflammation markers with gallstones in patients with metabolic dysfunction-associated fatty liver disease （MAFLD）， as well as the mediating role of liver fibrosis scores in the relationship between inflammation markers and gallstones. MethodsA total of 14 567 patients who received physical examination and were diagnosed with MAFLD in Subei People’s Hospital from January 2014 to June 2023 were enrolled in this study， and according to the results of abdominal color Doppler ultrasound， they were divided into gallstone group with 1 724 patients and non-gallstone group with 12 843 patients. Related clinical data were collected from all patients， including demographic data， medical history， family history， physical examination， Color Doppler ultrasound， and biochemical parameters. The biomarkers associated with metabolic disorders and insulin resistance included triglyceride-glucose index （TyG）， TyG-body mass index （BMI） index， atherogenic index of plasma （AIP）， and non-high-density lipoprotein cholesterol-to-high-density lipoprotein cholesterol ratio （NHHR）； the biomarkers associated with inflammation and nutritional status included neutrophil-to-lymphocyte ratio （NLR）， neutrophil percentage-to-albumin ratio （NPAR）， and monocyte-to-lymphocyte ratio （MLR）； the biomarkers for assessing liver fibrosis degree and liver function included albumin-bilirubin （ALBI） score， NAFLD fibrosis score （NFS）， fibrosis-4 （FIB-4） index， and aspartate aminotransferase-to-platelet ratio index （APRI）. The independent-samples t test was used for comparison of normally distributed continuous data between two groups， while the Mann-Whitney U test was used for comparison of non-normally distributed continuous data between two groups； the chi-square test was used for comparison of categorical data between two groups. Multivariate Logistic regression analysis， restricted cubic spline analysis， and mediating effect analysis were used to assess the association of liver fibrosis markers and inflammation markers with the risk of gallstones. ResultsThe prevalence rate of gallstones was 11.8% among the MAFLD patients. There were significant differences between the gallstone group and the non-gallstone group in sex， age， smoking history， diabetes， hypertension， lymphocytes， platelets， glucose， albumin， serum uric acid， alanine aminotransferase， aspartate aminotransferase， red blood cell， NLR， NPAR， MLR， NFS， FIB-4 index， and ALBI score （all P<0.05）. The multivariate Logistic regression analysis showed that NLR （odds ratio ［OR］=1.091， 95% confidence interval ［CI］： 1.028　—　1.160， P<0.05）， NPAR （OR=1.073， 95%CI： 1.042　—　1.105， P<0.05）， MLR （OR=1.142， 95%CI： 1.057　—　1.232， P<0.05）， NFS （OR=1.239， 95%CI： 1.190　—　1.291， P<0.05）， and FIB-4 index （OR=1.326， 95%CI： 1.241　—　1.417， P<0.05） were influencing factors for the prevalence rate of gallstones. The restricted cubic spline analysis showed a significant non-linear association between NFS/FIB-4 index and the risk of gallstone （non-linear P<0.05）. The mediating effect analysis further showed that the association of NLR， MLR， and NPAR with gallstones was partially mediated by NFS or FIB-4 index， with a mediating effect accounting for 36.79%、28.09%、29.67% and 18.31%、17.70、11.57%， respectively. ConclusionNFS and FIB-4 index have a non-linear association with the prevalence rate of gallstones in MAFLD patients， and they also mediate the association of NLR， NPAR， and MLR with the risk of gallstone.

Objective:To develop PixelSIFT-UNet, a novel semantic segmentation model that integrates deep learning with scale-invariant feature transform (SIFT) algorithm to improve the segmentation accuracy of oral mucosal lesions.Methods:This investigation utilized 838 standard clinical white light images of oral mucosal diseases acquired from January 2020 to December 2022 at the Stomatology Hospital Zhejiang University School of Medicine. Randomization was achieved through Python′s random.seed function implementation. The random sample function was subsequently applied for sampling distribution. The dataset was stratified into three subsets with a 6∶2∶2 ratio: training ( n=506), validation ( n=166), and testing ( n=166). Lesion boundaries were annotated using Labelme software, and a PixelSIFT-UNet-based deep learning model was developed with VGG-16 and ResNet-50 backbone networks. Model parameters were optimized using the validation set, and performance metrics [including Dice coefficient, mean intersection over union (mIoU), mean pixel accuracy (mPA), and Precision] were assessed on the test set. The model′s performance was benchmarked against conventional semantic segmentation frameworks (U-Net and PSPNet). Results:The developed PixelSIFT-UNet model could achieve precise segmentation of three common oral mucosal lesions: oral lichen planus, oral leukoplakia, and oral submucous fibrosis. Utilizing VGG-16 as the backbone network, the model achieved Dice coefficient, mIoU, mPA, and Precision values of 0.642, 0.699, 0.836, and 0.792, respectively. Implementation with ResNet-50 backbone network yielded metrics of 0.668, 0.733, 0.872 and 0.817, demonstrating significant improvements across all performance indicators compared to conventional U-Net model (relevant metrics: 0.662, 0.717, 0.861 and 0.809) and PSPNet model (relevant metrics: 0.671, 0.721, 0.858 and 0.813).Conclusions:The proposed PixelSIFT-UNet architecture demonstrates superior performance in oral mucosal lesion segmentation tasks, surpassing conventional semantic segmentation models and providing robust quantitative improvements in segmentation accuracy.

Objective:To develop PixelSIFT-UNet, a novel semantic segmentation model that integrates deep learning with scale-invariant feature transform (SIFT) algorithm to improve the segmentation accuracy of oral mucosal lesions.Methods:This investigation utilized 838 standard clinical white light images of oral mucosal diseases acquired from January 2020 to December 2022 at the Stomatology Hospital Zhejiang University School of Medicine. Randomization was achieved through Python′s random.seed function implementation. The random sample function was subsequently applied for sampling distribution. The dataset was stratified into three subsets with a 6∶2∶2 ratio: training ( n=506), validation ( n=166), and testing ( n=166). Lesion boundaries were annotated using Labelme software, and a PixelSIFT-UNet-based deep learning model was developed with VGG-16 and ResNet-50 backbone networks. Model parameters were optimized using the validation set, and performance metrics [including Dice coefficient, mean intersection over union (mIoU), mean pixel accuracy (mPA), and Precision] were assessed on the test set. The model′s performance was benchmarked against conventional semantic segmentation frameworks (U-Net and PSPNet). Results:The developed PixelSIFT-UNet model could achieve precise segmentation of three common oral mucosal lesions: oral lichen planus, oral leukoplakia, and oral submucous fibrosis. Utilizing VGG-16 as the backbone network, the model achieved Dice coefficient, mIoU, mPA, and Precision values of 0.642, 0.699, 0.836, and 0.792, respectively. Implementation with ResNet-50 backbone network yielded metrics of 0.668, 0.733, 0.872 and 0.817, demonstrating significant improvements across all performance indicators compared to conventional U-Net model (relevant metrics: 0.662, 0.717, 0.861 and 0.809) and PSPNet model (relevant metrics: 0.671, 0.721, 0.858 and 0.813).Conclusions:The proposed PixelSIFT-UNet architecture demonstrates superior performance in oral mucosal lesion segmentation tasks, surpassing conventional semantic segmentation models and providing robust quantitative improvements in segmentation accuracy.

Objective To explore the targets and mechanisms of Tongguanteng Injection in inhibiting the proliferation and migration of cervical cancer.Methods The biological activity of Tongguanteng Injection in inhibiting human cervical cancer SiHa cells was determined by MTT method.Detecting the effect of Tongguanteng Injection on SiHa cell migration through wound healing assay.Using network pharmacology to collect the key targets for treating cervical cancer,and perform molecular docking and enrichment analysis on the targets.Immunohistochemistry and Western blot were used to detect the key proteins to validate the network pharmacology predictions.Result Tongguanteng Injection significantly inhibited the proliferation and migration in a dose-dependent manner in human cervical cancer SiHa cells.Based on the main active ingredients of Marsdenia tenacissima,81 therapeutic targets for cervical cancer were obtained,which may treat cervical cancer by affecting key proteins such as FGF2,MAPK1,and MAPK3.Immunohistochemical results indicated that FGF2,MAPK1 and MAPK3 were expressed in cervical cancer tissues.The western bolt assays showed that Tongguanteng Injection could significantly reduce the FGF2 protein expression.Meanwhile,the MAPK1 and MAPK3 protein expressions were significantly increased.Conclusion Tongguanteng Injection may regulate the FGF2,MAPK1 and MAPK3,effectively impede the proliferation and migration of cervical cancer.

Objective:To construct a nursing quality evaluation indicator system for pulse indicator continuous cardiac output (PiCCO) monitoring and provide a basis for evaluating the nursing quality of PiCCO monitoring.Methods:Using Donabedian′s "structure-process-result" three-dimensional quality evaluation model as the theoretical framework, the nursing quality evaluation indicator system for PiCCO was established through literature search, Delphi expert correspondence, and hierarchical analysis during the period May to August 2023.Results:Of the 22 experts, 6 were male and 16 were female, aged (46.59 ± 4.34) years. The return rates of the questionnaires of the 2 rounds of expert correspondence were both 100%, the coefficients of expert authority were both 0.945, and the Kendall coordination coefficients were 0.045-0.186 ( χ2 values were 2.00-221.46, all P<0.05) and 0.045-0.132 ( χ2 values were 2.00-82.16, all P<0.05), respectively. The finalized nursing quality evaluation indicator system for PiCCO included 3 primary indicators, 7 secondary indicators, and 36 tertiary indicators. Conclusions:The nursing quality evaluation indicator system for PiCCO is practical and scientific, which can provide reference for PiCCO monitoring nursing quality evaluation.

Creutzfeldt-Jakob disease(CJD)is a rapidly progressive and fatal neurodegenerative disorder caused by prions,with certain infectivity and iatrogenic transmission risks.With the rapid progress and application of new dia-gnostic biomarkers and detection methods,as well as the construction and improvement of surveillance and reporting systems,the detection of CJD in patients domestically and internationally has shown an increasing trend year by year.Due to its long incubation period and heterogeneity of early symptoms,early identification and diagnosis of the disease is difficult,increasing the risk of transmission within medical institutions.Currently,there is a lack of con-sensus on the infection prevention and control of CJD.In order to timely identify and diagnose CJD as well as effec-tively block its transmission in medical institutions,this consensus summarizes 15 clinical concerns and formulates 24 specific recommendations based on the latest domestic and international research findings and clinical evidence,as well as combines with clinical practice,aiming to standardize healthcare-associated infection prevention and control measures for CJD and reduce its transmission risk in medical institutions.

Objective To explore the targets and mechanisms of Tongguanteng Injection in inhibiting the proliferation and migration of cervical cancer.Methods The biological activity of Tongguanteng Injection in inhibiting human cervical cancer SiHa cells was determined by MTT method.Detecting the effect of Tongguanteng Injection on SiHa cell migration through wound healing assay.Using network pharmacology to collect the key targets for treating cervical cancer,and perform molecular docking and enrichment analysis on the targets.Immunohistochemistry and Western blot were used to detect the key proteins to validate the network pharmacology predictions.Result Tongguanteng Injection significantly inhibited the proliferation and migration in a dose-dependent manner in human cervical cancer SiHa cells.Based on the main active ingredients of Marsdenia tenacissima,81 therapeutic targets for cervical cancer were obtained,which may treat cervical cancer by affecting key proteins such as FGF2,MAPK1,and MAPK3.Immunohistochemical results indicated that FGF2,MAPK1 and MAPK3 were expressed in cervical cancer tissues.The western bolt assays showed that Tongguanteng Injection could significantly reduce the FGF2 protein expression.Meanwhile,the MAPK1 and MAPK3 protein expressions were significantly increased.Conclusion Tongguanteng Injection may regulate the FGF2,MAPK1 and MAPK3,effectively impede the proliferation and migration of cervical cancer.

Objective:To explore the clinicopathological features of rectal neuroendocrine tumor (R-NET) G2, identify prognostic factors, and summarize treatment experience.Methods:The clinical data of patients diagnosed with R-NET G2 by pathological diagnosis admitted to Cancer Hospital of the Chinese Academy of Medical Sciences from January 2003 to September 2023 were retrospectively analyzed. The Fisher's exact test and Kaplan-Meier curves were performed to analyze the association between pathological features and prognosis.Results:A total of 22 patients were enrolled in this study and 21 patients were followed up for a period of 6-98 months with a median follow-up time of 42 months. 5 patients died due to tumor progression during the follow-up period. The 1-, 3-, and 5-year cancer-specific survival (CSS) of the whole group were 100.0%, 92.9%, and 69.6%, respectively. Of the 22 patients, 20 underwent surgical treatment, of which 15 underwent postoperative adjuvant therapy; 2 underwent medical treatment for liver and bone multiple metastases. The 5-year survival rates of patients with tumours ≥2 cm in length, T2-3 stage, lymph node metastasis, and distant metastasis (57.1%, 68.8%, 66.7%, and 63.6%, respectively) were shorter than those of patients with tumours <2 cm in length, T1 stage, no lymph node metastasis, and no distant metastasis (all 100.0%, P＜0.001). In addition, patients with liver metastases had larger primary tumor diameters and higher T-stages compared with those without distant metastasis ( P＜0.05). Conclusions:R-NET G2 has a high degree of malignancy compared with G1 and a high propensity for metastasis. Clinicians should formulate appropriate diagnostic and treatment strategies based on factors such as tumor size, depth of invasion, lymph node status, presence of distant metastasis, and the location and extent of distant metastasis.

Loop-mediated isothermal amplification(LAMP)is a newin vitronucleic acid amplification technique,which has been widely used in rapid detection of pathogenic bacteria,with advantages of high efficiency,simple operation and low cost.Microfluidic chip technique is a kind of miniaturized and integrated analytical technology,which integrates automation and high throughput,and can effectively avoid sample cross-contamination and has the advantages of high sample utilization rate and high cost-effectivenes.LAMP combined with microfluidic chip can detect multiple samples of the same pathogen at the same time or single samples of different pathogens at the same time,providing a new method for the rapid,field detection of pathogens.In this paper,the research progresses of LAMP microfluidic chip and its application in rapid detection of pathogenic bacteria in recent years were reviewed,and the future prospect was discussed.