With the widespread adoption of low-dose CT screening and the extensive application of high-resolution CT, the detection rate of sub-centimeter lung nodules has significantly increased. How to scientifically manage these nodules while avoiding overtreatment and diagnostic delays has become an important clinical issue. Among them, lung nodules with a consolidation tumor ratio less than 0.25, dominated by ground-glass shadows, are particularly worthy of attention. The therapeutic challenge for this group is how to achieve precise and complete resection of nodules during surgery while maximizing the preservation of the patient's lung function. The "watershed topography map" is a new technology based on big data and artificial intelligence algorithms. This method uses Dicom data from conventional dose CT scans, combined with microscopic (22-24 levels) capillary network anatomical watershed features, to generate high-precision simulated natural segmentation planes of lung sub-segments through specific textures and forms. This technology forms fluorescent watershed boundaries on the lung surface, which highly fit the actual lung anatomical structure. By analyzing the adjacent relationship between the nodule and the watershed boundary, real-time, visually accurate positioning of the nodule can be achieved. This innovative technology provides a new solution for the intraoperative positioning and resection of lung nodules. This consensus was led by four major domestic societies, jointly with expert teams in related fields, oriented to clinical practical needs, referring to domestic and foreign guidelines and consensus, and finally formed after multiple rounds of consultation, discussion, and voting. The main content covers the theoretical basis of the "watershed topography map" technology, indications, operation procedures, surgical planning details, and postoperative evaluation standards, aiming to provide scientific guidance and exploration directions for clinical peers who are currently or plan to carry out lung nodule resection using the fluorescent microscope watershed analysis method.

BACKGROUND:Quercetin plays an important role in the proliferation and differentiation of bone marrow mesenchymal stem cells,but less research has been done on its mechanism of promoting the migration of bone marrow mesenchymal stem cells. OBJECTIVE:To study the effect of quercetin on the migration of human bone marrow mesenchymal stem cells through in vitro experiments,and to explore the regulatory role of CCR1 and CXCR4. METHODS:Human bone marrow mesenchymal stem cells were selected as experimental subjects.CCK8 assay was used to detect the effect of quercetin on the proliferative activity of human bone marrow mesenchymal stem cells.Cell scratch assay and Transwell assay were used to detect the in vitro invasive and migratory abilities of human bone marrow mesenchymal stem cells after quercetin treatment,respectively.The role of quercetin in relation to CCR1 and CXCR4 was demonstrated with the help of molecular docking technology.Western blot assay and real-time fluorescence quantitative PCR were used to detect the migration-related chemokine expression after quercetin treatment. RESULTS AND CONCLUSION:(1)5 and 10 μmol/L quercetin could significantly promote the proliferation of human bone marrow mesenchymal stem cells,and the drug concentration of 10 μmol/L resulted in the highest cell proliferation efficiency.(2)To better explore the dose-effect relationship of quercetin affecting the migration of human bone marrow mesenchymal stem cells,5 and 10 μmol/L quercetin were selected for the subsequent experiments,and ligustrazine was used as the positive control drug,and the experiments were divided into blank control group,5 μmol/L quercetin group,10 μmol/L quercetin group,and 100 μmol/L ligustrazine group.(3)In vitro migration and invasion ability of human bone marrow mesenchymal stem cells were elevated in a concentration-dependent manner after quercetin treatment,and the migration effect of 10 μmol/L quercetin group was better than that of ligustrazine group.(4)The molecular docking results suggested that there was a strong interaction between quercetin and CCR1 and CXCR4.(5)Quercetin could up-regulate the expression of CCR1 and CXCR4 proteins and mRNA.(6)This study confirmed at the cellular level that quercetin could promote the migration of human bone marrow mesenchymal stem cells by targeting CCR1 and CXCR4.

Objective This study aimed to comprehensively analyze and compare the clinicopathological features and prognosis of Chinese patients with human epidermal growth factor receptor 2(HER2)-low early breast cancer(BC)and HER2-IHC0 BC. Methods Patients diagnosed with HER2-negative BC(N=999)at our institution between January 2011 and December 2015 formed our study population.Clinicopathological characteristics,association between estrogen receptor(ER)expression and HER2-low,and evolution of HER2 immunohistochemical(IHC)score were assessed.Kaplan-Meier method and log-rank test were used to compare the long-term survival outcomes(5-year follow-up)between the HER2-IHC0 and HER2-low groups. Results HER2-low BC group tended to demonstrate high expression of ER and more progesterone receptor(PgR)positivity than HER2-IHC0 BC group(P<0.001).The rate of HER2-low status increased with increasing ER expression levels(Mantel-Haenszel χ2 test,P<0.001,Pearson's R=0.159,P<0.001).Survival analysis revealed a significantly longer overall survival(OS)in HER2-low BC group than in HER2-IHC0 group(P=0.007)in the whole cohort and the hormone receptor(HR)-negative group.There were no significant differences between the two groups in terms of disease-free survival(DFS).The discordance rate of HER2 IHC scores between primary and metastatic sites was 36.84%. Conclusion HER2-low BC may not be regarded as a unique BC group in this population-based study due to similar clinicopathological features and prognostic roles.

The contents recorded in the rotation registration manual is not only the quantitative indicators for evaluating the quality of residency training, but also the important basis for training assessment and issuance of training certificates. In order to solve the problems of data authenticity, information delay, and repeated entry in the rotation registration manual for residency training, Shanghai East Hospital, Tongji University, launched a project to dock the electronic rotation registration manual with the hospital information system. Through the establishment of the project team, the development of working mechanisms, and the implementation of the project, data analysis was used for process reformation and system optimization, so as to continuously improve management efficiency and medical safety while solving problems and form a set of implementation system with reference significance in practice.

This article describes the experience of implementing the informatization construction of teaching supervision for standardized residency training in Shanghai East Hospital, Tongji University, and discusses the means to improve teaching activity supervision, such as management informatization and internet technology. This study aims to ensure the efficiency and work quality of supervision, optimize the process and resource allocation of supervision, and lay a solid foundation for improving the quality of residency training and teaching in the hospital (especially the key indicators for residency training and teaching quality, including the supervision rate of teaching activities and the completion rate of teaching activities) and establishing a sound system and the assets of teaching data in residency training.

Objective To study the effect and mechanism of paeonol(PAE)on renal interstitial fibrosis in rats.Methods The rats were randomly divided into sham operation(Sham)group,unilateral ureteral obstruction(UUO)group,PAE low dose(PAE-L)group,PAE medium dose(PAE-M)group,PAE high dose(PAE-H)group and irbesartan(IRB)group.Except for the Sham group,the UUO model was established in other groups.Each group was given a corresponding intervention for two weeks.Serum creatinine(Scr),blood urea nitrogen(BUN),serum 8-hydroxydeoxyguanosine(8-OHdG)levels,renal tissue superoxide dismutase(SOD),glutathione peroxidase(GPX)activities,α-smooth muscle actin(α-SMA),type Ⅰ collagen(Col-Ⅰ),fibronectin(FN),silent information regulator 1(SIRT1),nuclear factor E2-related factor 2(Nrf2)protein expression were detected;observe pathological changes of kidney tissue and calculate collagen volume fraction(CVF).Results Compared with the UUO group,the serum levels of Scr,BUN,and 8-OHdG in each dose group of PAE were decreased,the activities of SOD and GPX in kidney tissue were increased,the positive expressions of α-SMA,Col-Ⅰ and FN in kidney tissue were decreased,and the protein expressions of SIRT1 and Nrf2 were increased.Masson staining showed a decrease of CVF in renal tissue(all P<0.05),and HE staining showed a different degree of improvement in pathological changes such as inflammatory cell infiltration and tubular dilatation in renal tissue;PAE improves renal interstitial fibrosis in rats in a dose-dependent manner(P<0.05),and the effect of large dose PAE on renal interstitial fibrosis in rats was similar to that of IRB.Conclusion PAE can alleviate UUO-induced rat renal interstitial fibrosis and oxidative stress,and improve rat renal function.And this mechanism may be related to the activation of the SIRT1/Nrf2 signaling pathway.

Background::Acute pulmonary embolism (APE) is a fatal cardiovascular disease, yet missed diagnosis and misdiagnosis often occur due to non-specific symptoms and signs. A simple, objective technique will help clinicians make a quick and precise diagnosis. In population studies, machine learning (ML) plays a critical role in characterizing cardiovascular risks, predicting outcomes, and identifying biomarkers. This work sought to develop an ML model for helping APE diagnosis and compare it against current clinical probability assessment models.Methods::This is a single-center retrospective study. Patients with suspected APE were continuously enrolled and randomly divided into two groups including training and testing sets. A total of 8 ML models, including random forest (RF), Na?ve Bayes, decision tree, K-nearest neighbors, logistic regression, multi-layer perceptron, support vector machine, and gradient boosting decision tree were developed based on the training set to diagnose APE. Thereafter, the model with the best diagnostic performance was selected and evaluated against the current clinical assessment strategies, including the Wells score, revised Geneva score, and Years algorithm. Eventually, the ML model was internally validated to assess the diagnostic performance using receiver operating characteristic (ROC) analysis.Results::The ML models were constructed using eight clinical features, including D-dimer, cardiac troponin T (cTNT), arterial oxygen saturation, heart rate, chest pain, lower limb pain, hemoptysis, and chronic heart failure. Among eight ML models, the RF model achieved the best performance with the highest area under the curve (AUC) (AUC = 0.774). Compared to the current clinical assessment strategies, the RF model outperformed the Wells score ( P = 0.030) and was not inferior to any other clinical probability assessment strategy. The AUC of the RF model for diagnosing APE onset in internal validation set was 0.726. Conclusions::Based on RF algorithm, a novel prediction model was finally constructed for APE diagnosis. When compared to the current clinical assessment strategies, the RF model achieved better diagnostic efficacy and accuracy. Therefore, the ML algorithm can be a useful tool in assisting with the diagnosis of APE.

Objective To explore the molecular epidemiological characteristics of carbapenem-resistant Klebsiella pneumoniae(CRKP),and reveal its mechanism of resistance to ceftazidime/avibactam(CZA).Methods CZA-re-sistant CRKP strains initially isolated from the Affiliated Hospital of Xuzhou Medical University from January 2021 to September 2023 were collected.The carriage of 5 carbapenemase genes(blaKPC,blaNDM,blaOXA,blaVIM,blaIMp)were detected with gene amplification method and colloidal gold method.The relative copy number and expression level of Klebsiella pneumoniae(KP)carbapenemase-producing KP(KPC-KP)was detected with real-time quantita-tive polymerase chain reaction(RT-qPCR),mutation sites of KPC mutation strains were analyzed with whole-ge-nome sequencing,and epidemic characteristics of CRKP and resistance mechanism to CZA were analyzed.Results A total of 73 CZA-resistant CRKP strains were isolated,with 37(50.68％)being KPC and NDM co-producing strains,33(45.21％)NDM-producing alone(23 strains producing NDM-5 and 10 strains producing NDM-1),and 3 KPC-producing alone.KP-2842 strain was identified as ST11-type KPC-33 variant,KP-2127 and KP-2189 strains produced KPC-2.Compared with KP ATCC BAA-1705,the copy number of blaKPC in these strains up-regulated by 1.04-3.86 fold,and the expression increased by 6.66-12.93 fold,respectively.Colloidal gold and PCR methods demonstrated good consistency and the ability to detect the enzyme co-producing and KPC-33 variant.Conclusion In this hospital,the resistance of CRKP to CZA is primarily mediated by the metalloenzyme NDM,with co-produc-tion of NDM and KPC being a characteristic of CRKP.High copy number and expression level of blaKPC-2 also con-tribute to CZA resistance.This study identified the KPC-33 variant for the first time in ST11-type CRKP in Jiangsu Province.

A growing number of neuroimaging studies have revealed abnormal brain structural and functional alterations in subjects with internet addiction (IA), however, with conflicting conclusions. We plan to conduct a systematic review and meta-analysis on the studies of voxelbased morphometry (VBM) and resting-state functional connectivity (rsFC), to reach a consolidated conclusion and point out the future direction in this field. A comprehensive search of rsFC and VBM studies of IA will be conducted in the PubMed, Cochrane Library, and Web of Science databases to retrieve studies published from the inception dates to August 2021. If the extracted data are feasible, activation likelihood estimation and seed-based d mapping methods will be used to meta-analyze the brain structural and functional changes in IA patients. This study will hopefully reach a consolidated conclusion on the impact of IA on human brain or point out the future direction in this field.

Alzheimer's disease (AD) is associated with the impairment of white matter (WM) tracts. The current study aimed to verify the utility of WM as the neuroimaging marker of AD with multisite diffusion tensor imaging datasets [321 patients with AD, 265 patients with mild cognitive impairment (MCI), 279 normal controls (NC)], a unified pipeline, and independent site cross-validation. Automated fiber quantification was used to extract diffusion profiles along tracts. Random-effects meta-analyses showed a reproducible degeneration pattern in which fractional anisotropy significantly decreased in the AD and MCI groups compared with NC. Machine learning models using tract-based features showed good generalizability among independent site cross-validation. The diffusion metrics of the altered regions and the AD probability predicted by the models were highly correlated with cognitive ability in the AD and MCI groups. We highlighted the reproducibility and generalizability of the degeneration pattern of WM tracts in AD.
Humans ; White Matter/diagnostic imaging* ; Diffusion Tensor Imaging/methods* ; Alzheimer Disease/complications* ; Reproducibility of Results ; Cognition ; Cognitive Dysfunction/complications* ; Brain/diagnostic imaging*