Objective To develop a deep learning model based on fundus retinal images to improve the detection rate of mild cognitive impairment(MCI)in patients with coronary heart disease,achieve early intervention and improve prognosis.Methods The study was a single-center cross-sectional study that retrospectively included patients diagnosed with coronary heart disease(CHD)by coronary angiography(≥50％ stenosis of at least one coronary vessel)from Beijing Anzhen Hospital between November 2021 and December 2022.The whole data set was randomly divided into the training set and the testing set according to the ratio of 8∶2 for model development.After that,the patient data of the same center from January 2023 to April 2023 were included in the time verification method to verify the model.The diagnostic criteria for MCI were MMSE＜27 or MoCA＜26.Four kinds of convolutional neural network(CNN)architectures were used to train fundus images,and a comprehensive vision model of MCI detection was established through model integration.The area under the curve(AUC),sensitivity and specificity of the receiver operating curve(ROC)were used to evaluate the performance of the AI model.Results We collected 5 880 eligible fundus images from 3 368 CHD patients.Based on the results of the MMSE scale,the algorithm was labeled,including 2 898 males and 527 MCI patients.The AUC of the deep learning model in the test group is 0.733(95％CI 0.688-0.778),and the sensitivity of the algorithm in the test group is 0.577(95％CI 0.528-0.625)by using the operating point with the maximum sum of sensitivity and specificity.With a specificity of 0.758(95％CI 0.714-0.802),corresponding to a validated AUC of 0.710(95％CI 0.601-0.818).Based on the results of the MoCA scale,the algorithm labels 2 437 males and 1 626 MCI patients.The AUC of the deep learning model in the test group was 0.702(95％CI 0.671-0.733).The operating point with the maximum sum of sensitivity and specificity was selected,and the sensitivity of the algorithm was 0.749(95％CI 0.719-0.778)and the specificity was 0.561(95％CI 0.527-0.595),corresponding to the AUC value of the verification group was 0.674(95％CI 0.622-0.726).Conclusions The deep learning algorithm model based on fundus images has good diagnostic performance,and may be used as a new non-invasive,convenient and rapid screening method for MCI in CHD population.

Objective To develop a deep learning model based on fundus retinal images to improve the detection rate of mild cognitive impairment(MCI)in patients with coronary heart disease,achieve early intervention and improve prognosis.Methods The study was a single-center cross-sectional study that retrospectively included patients diagnosed with coronary heart disease(CHD)by coronary angiography(≥50％ stenosis of at least one coronary vessel)from Beijing Anzhen Hospital between November 2021 and December 2022.The whole data set was randomly divided into the training set and the testing set according to the ratio of 8∶2 for model development.After that,the patient data of the same center from January 2023 to April 2023 were included in the time verification method to verify the model.The diagnostic criteria for MCI were MMSE＜27 or MoCA＜26.Four kinds of convolutional neural network(CNN)architectures were used to train fundus images,and a comprehensive vision model of MCI detection was established through model integration.The area under the curve(AUC),sensitivity and specificity of the receiver operating curve(ROC)were used to evaluate the performance of the AI model.Results We collected 5 880 eligible fundus images from 3 368 CHD patients.Based on the results of the MMSE scale,the algorithm was labeled,including 2 898 males and 527 MCI patients.The AUC of the deep learning model in the test group is 0.733(95％CI 0.688-0.778),and the sensitivity of the algorithm in the test group is 0.577(95％CI 0.528-0.625)by using the operating point with the maximum sum of sensitivity and specificity.With a specificity of 0.758(95％CI 0.714-0.802),corresponding to a validated AUC of 0.710(95％CI 0.601-0.818).Based on the results of the MoCA scale,the algorithm labels 2 437 males and 1 626 MCI patients.The AUC of the deep learning model in the test group was 0.702(95％CI 0.671-0.733).The operating point with the maximum sum of sensitivity and specificity was selected,and the sensitivity of the algorithm was 0.749(95％CI 0.719-0.778)and the specificity was 0.561(95％CI 0.527-0.595),corresponding to the AUC value of the verification group was 0.674(95％CI 0.622-0.726).Conclusions The deep learning algorithm model based on fundus images has good diagnostic performance,and may be used as a new non-invasive,convenient and rapid screening method for MCI in CHD population.

This study explores the role and underlying molecular mechanisms of fucoidan sulfate(FPS) in regulating heme oxygenase-1(Hmox1)-mediated ferroptosis to ameliorate myocardial injury in diabetic cardiomyopathy(DCM) through in vivo and in vitro experiments and network pharmacology analysis. In vivo, a DCM rat model was established using a combination of "high-fat diet feeding + two low-dose streptozotocin(STZ) intraperitoneal injections". The rats were randomly divided into four groups: normal, model, FPS, and dapagliflozin(Dapa) groups. In vitro, a cellular model was created by inducing rat cardiomyocytes(H9c2 cells) with high glucose(HG), using zinc protoporphyrin(ZnPP), an Hmox1 inhibitor, as the positive control. An automatic biochemical analyzer was used to measure blood glucose(BG), serum aspartate aminotransferase(AST), serum lactate dehydrogenase(LDH), and serum creatine kinase-MB(CK-MB) levels. Echocardiography was used to assess rat cardiac function, including ejection fraction(EF) and fractional shortening(FS). Pathological staining was performed to observe myocardial morphology and fibrotic characteristics. DCFH-DA fluorescence probe was used to detect reactive oxygen species(ROS) levels in myocardial tissue. Specific assay kits were used to measure serum brain natriuretic peptide(BNP), myocardial Fe~(2+), and malondialdehyde(MDA) levels. Western blot(WB) was used to detect the expression levels of myosin heavy chain 7B(MYH7B), natriuretic peptide A(NPPA), collagens type Ⅰ(Col-Ⅰ), α-smooth muscle actin(α-SMA), ferritin heavy chain 1(FTH1), solute carrier family 7 member 11(SLC7A11), glutathione peroxidase 4(GPX4), 4-hydroxy-2-nonenal(4-HNE), and Hmox1. Immunohistochemistry(IHC) was used to examine Hmox1 protein expression patterns. FerroOrange and Highly Sensitive DCFH-DA fluorescence probes were used to detect intracellular Fe~(2+) and ROS levels. Transmission electron microscopy was used to observe changes in mitochondrial morphology. In network pharmacology, FPS targets were identified through the PubChem database and PharmMapper platform. DCM-related targets were integrated from OMIM, GeneCards, and DisGeNET databases, while ferroptosis-related targets were obtained from the FerrDb database. A protein-protein interaction(PPI) network was constructed for the intersection of these targets using STRING 11.0, and core targets were screened with Cytoscape 3.9.0. Molecular docking analysis was conducted using AutoDock and PyMOL 2.5. In vivo results showed that FPS significantly reduced AST, LDH, CK-MB, and BNP levels in DCM model rats, improved cardiac function, decreased the expression of myocardial injury proteins(MYH7B, NPPA, Col-Ⅰ, and α-SMA), alleviated myocardial hypertrophy and fibrosis, and reduced Fe~(2+), ROS, and MDA levels in myocardial tissue. Furthermore, FPS regulated the expression of ferroptosis-related markers(Hmox1, FTH1, SLC7A11, GPX4, and 4-HNE) to varying degrees. Network pharmacology results revealed 313 potential targets for FPS, 1 125 targets for DCM, and 14 common targets among FPS, DCM, and FerrDb. Hmox1 was identified as a key target, with FPS showing high docking activity with Hmox1. In vitro results demonstrated that FPS restored the expression levels of ferroptosis-related proteins, reduced intracellular Fe~(2+) and ROS levels, and alleviated mitochondrial structural damage in cardiomyocytes. In conclusion, FPS improves myocardial injury in DCM, with its underlying mechanism potentially involving the regulation of Hmox1 to inhibit ferroptosis. This study provides pharmacological evidence supporting the therapeutic potential of FPS for DCM-induced myocardial injury.
Animals ; Ferroptosis/drug effects* ; Rats ; Diabetic Cardiomyopathies/physiopathology* ; Male ; Rats, Sprague-Dawley ; Polysaccharides/pharmacology* ; Heme Oxygenase-1/genetics* ; Myocytes, Cardiac/metabolism* ; Myocardium/pathology* ; Humans ; Cell Line ; Heme Oxygenase (Decyclizing)

Objective:To explore the effects of smoking on peripheral regulatory T cells (Tregs), transforming growth factor beta1 (TGF-β 1) and interleukin-10 (IL-10) in elderly patients with non-small cell lung cancer (NSCLC). Methods:This was a cross-sectional study. A total of 43 elderly patients (≥60 years old) who were hospitalized in the Department of Geriatrics Medicine, Guangzhou First People′s Hospital from January 2018 to December 2024 and were newly diagnosed with NSCLC were recruited. According to smoking history, patients were divided into non-smoking group (15 cases), low smoking group (13 cases, smoking index<400) and high smoking group (15 cases, smoking index≥400). Venous blood samples were collected from participants, plasma and cells were separated. Flow cytometry was used to measure the proportions of Tregs and the expression of forkhead box P3 (Foxp3) in peripheral blood. Plasma levels of TGF-β 1 and IL-10 were measured by enzyme-linked immunosorbent assay. The effects of smoking on peripheral Tregs, TGF-β 1, and IL-10 in elderly patients with NSCLC were analyzed. Data were analyzed by one-way ANOVA, rank-sum test, and Fisher′s exact test. Results:The proportions of Tregs in non-smoking group, low smoking group and high smoking group were 2.50% (2.32%, 2.81%), 2.83% (2.48%, 3.72%), and 3.01% (2.37%, 3.73%), respectively, and there were no statistically significant differences among the three groups ( H=3.845, P>0.05). The proportions of Foxp3 +Tregs were (3.72±0.84)%, (4.64±1.10)%, and (4.68±1.27%), respectively. The mean fluorescence intensities (MFI) of Foxp3 were 123.0 (108.0, 128.0), 131.0 (123.5, 350.0), and 222.0 (141.0, 311.0), respectively. Both the proportions of Foxp3 +Tregs and the MFI of Foxp3 were higher in low smoking group and high smoking group than those in non-smoking group (all P<0.05). However, there were no significant differences between low smoking group and high smoking group (all P>0.05). The concentrations of IL-10 were 2.27 (1.42, 3.95), 3.42 (2.30, 5.08), and 3.26 (2.35, 6.28) ng/L, respectively. There were no statistically significant differences among the three groups ( H=2.930, P>0.05). The concentrations of TGF-β 1 were (10.72±9.37), (13.46±10.39), and (25.28±16.67) ng/ml, respectively. The concentration of TGF-β 1 in high smoking group was higher than that in non-smoking group and low smoking group (all P<0.05). However, there was no statistically significant difference between low smoking group and non-smoking group ( P>0.05). Conclusions:Smoking intensity may be correlated with the immunosuppressive function of Tregs in elderly patients with NSCLC. Higher smoking levels are associated with increased Foxp3 expression in Tregs and elevated plasma levels of TGF-β 1, potentially enhancing the immunosuppressive function of Tregs.

Turning to critical illness is a common stage of various diseases and injuries before death. Patients usually have complex health conditions, while the treatment process involves a wide range of content, along with high requirements for doctor′s professionalism and multi-specialty teamwork, as well as a great demand for time-sensitive treatments. However, this is not matched with critical care professionals and the current state of medical care in China. Telemedicine, which shortens the distance of medical professionals and the gap of disease diagnosis and treatments in various regions through electronic information, can effectively solve the current problem. Therefore, there is an urgent need to develop a standardized, high-quality visualization telemedicine round system .Therefore, experts have been organized to search domestic and foreign literature on telemedicine round for critically ill patients and to form this consensus based on clinical experiences so as to further improve the level of critical care treatments in regions.

Objective:To explore the effects of smoking on peripheral regulatory T cells (Tregs), transforming growth factor beta1 (TGF-β 1) and interleukin-10 (IL-10) in elderly patients with non-small cell lung cancer (NSCLC). Methods:This was a cross-sectional study. A total of 43 elderly patients (≥60 years old) who were hospitalized in the Department of Geriatrics Medicine, Guangzhou First People′s Hospital from January 2018 to December 2024 and were newly diagnosed with NSCLC were recruited. According to smoking history, patients were divided into non-smoking group (15 cases), low smoking group (13 cases, smoking index<400) and high smoking group (15 cases, smoking index≥400). Venous blood samples were collected from participants, plasma and cells were separated. Flow cytometry was used to measure the proportions of Tregs and the expression of forkhead box P3 (Foxp3) in peripheral blood. Plasma levels of TGF-β 1 and IL-10 were measured by enzyme-linked immunosorbent assay. The effects of smoking on peripheral Tregs, TGF-β 1, and IL-10 in elderly patients with NSCLC were analyzed. Data were analyzed by one-way ANOVA, rank-sum test, and Fisher′s exact test. Results:The proportions of Tregs in non-smoking group, low smoking group and high smoking group were 2.50% (2.32%, 2.81%), 2.83% (2.48%, 3.72%), and 3.01% (2.37%, 3.73%), respectively, and there were no statistically significant differences among the three groups ( H=3.845, P>0.05). The proportions of Foxp3 +Tregs were (3.72±0.84)%, (4.64±1.10)%, and (4.68±1.27%), respectively. The mean fluorescence intensities (MFI) of Foxp3 were 123.0 (108.0, 128.0), 131.0 (123.5, 350.0), and 222.0 (141.0, 311.0), respectively. Both the proportions of Foxp3 +Tregs and the MFI of Foxp3 were higher in low smoking group and high smoking group than those in non-smoking group (all P<0.05). However, there were no significant differences between low smoking group and high smoking group (all P>0.05). The concentrations of IL-10 were 2.27 (1.42, 3.95), 3.42 (2.30, 5.08), and 3.26 (2.35, 6.28) ng/L, respectively. There were no statistically significant differences among the three groups ( H=2.930, P>0.05). The concentrations of TGF-β 1 were (10.72±9.37), (13.46±10.39), and (25.28±16.67) ng/ml, respectively. The concentration of TGF-β 1 in high smoking group was higher than that in non-smoking group and low smoking group (all P<0.05). However, there was no statistically significant difference between low smoking group and non-smoking group ( P>0.05). Conclusions:Smoking intensity may be correlated with the immunosuppressive function of Tregs in elderly patients with NSCLC. Higher smoking levels are associated with increased Foxp3 expression in Tregs and elevated plasma levels of TGF-β 1, potentially enhancing the immunosuppressive function of Tregs.

Turning to critical illness is a common stage of various diseases and injuries before death. Patients usually have complex health conditions, while the treatment process involves a wide range of content, along with high requirements for doctor′s professionalism and multi-specialty teamwork, as well as a great demand for time-sensitive treatments. However, this is not matched with critical care professionals and the current state of medical care in China. Telemedicine, which shortens the distance of medical professionals and the gap of disease diagnosis and treatments in various regions through electronic information, can effectively solve the current problem. Therefore, there is an urgent need to develop a standardized, high-quality visualization telemedicine round system .Therefore, experts have been organized to search domestic and foreign literature on telemedicine round for critically ill patients and to form this consensus based on clinical experiences so as to further improve the level of critical care treatments in regions.

Objective: To investigate the causes and management of long-term persistent pelvic presacral space infection. Methods: Clinical data of 10 patients with persistent presacral infection admitted to the Cancer Hospital of Zhengzhou University from October 2015 to October 2020 were collected. Different surgical approaches were used to treat the presacral infection according to the patients' initial surgical procedures. Results: Among the 10 patients, there were 2 cases of presacral recurrent infection due to rectal leak after radiotherapy for cervical cancer, 3 cases of presacral recurrent infection due to rectal leak after radiotherapy for rectal cancer Dixons, and 5 cases of presacral recurrent infection of sinus tract after adjuvant radiotherapy for rectal cancer Miles. Of the 5 patients with leaky bowel, 4 had complete resection of the ruptured nonfunctional bowel and complete debridement of the presacral infection using an anterior transverse sacral incision with a large tipped omentum filling the presacral space; 1 had continuous drainage of the anal canal and complete debridement of the presacral infection using an anterior transverse sacral incision. 5 post-Miles patients all had debridement of the presacral infection using an anterior transverse sacral incision combined with an abdominal incision. The nine patients with healed presacral infection recovered from surgery in 26 to 210 days, with a median time of 55 days. Conclusions: Anterior sacral infections in patients with leaky gut are caused by residual bowel secretion of intestinal fluid into the anterior sacral space, and in post-Miles patients by residual anterior sacral foreign bodies. An anterior sacral caudal transverse arc incision combined with an abdominal incision is an effective surgical approach for complete debridement of anterior sacral recalcitrant infections.
Humans ; Reinfection ; Rectum/surgery* ; Rectal Neoplasms/surgery* ; Drainage ; Anal Canal/surgery* ; Pelvic Infection

This study aims to characterize the cell atlas of the epididymis derived from a 46,XY disorders of sex development (DSD) patient with a novel heterozygous mutation of the nuclear receptor subfamily 5 group A member 1 (NR5A1) gene. Next-generation sequencing found a heterozygous c.124C>G mutation in NR5A1 that resulted in a p.Q42E missense mutation in the conserved DNA-binding domain of NR5A1. The patient demonstrated feminization of external genitalia and Tanner stage 1 breast development. The surgical procedure revealed a morphologically normal epididymis and vas deferens but a dysplastic testis. Microfluidic-based single-cell RNA sequencing (scRNA-seq) analysis found that the fibroblast cells were significantly increased (approximately 46.5%), whereas the number of main epididymal epithelial cells (approximately 9.2%), such as principal cells and basal cells, was dramatically decreased. Bioinformatics analysis of cell-cell communications and gene regulatory networks at the single-cell level inferred that epididymal epithelial cell loss and fibroblast occupation are associated with the epithelial-to-mesenchymal transition (EMT) process. The present study provides a cell atlas of the epididymis of a patient with 46,XY DSD and serves as an important resource for understanding the pathophysiology of DSD.
Male ; Humans ; Epididymis ; Disorder of Sex Development, 46,XY/genetics* ; Disorders of Sex Development ; Mutation ; Mutation, Missense ; Steroidogenic Factor 1/genetics*

Accurate classification of the acetabular injuries and appropriate treatment plan are great challenges for orthopedic surgeons because of the irregular anatomical structure of the acetabulum and aggregation of important vessels and nerves around it. Letournel-Judet classification system has been widely applied to classify acetabular fractures. However, there are several limitations, including incomplete inclusion of fracture types, difficulty in understanding and insufficient guidance for surgical treatment, etc. Serious complications such as traumatic arthritis are common due to wrong classification and diagnosis and improper selection of surgical strategy, which brings a heavy burden to the society and families. Three-column classification, based on anatomic characteristics, has advantages of containing more fracture types and being easy to understand, etc. To solve the problems existing in the diagnosis and treatment process based on Letournel-Judet classification, achieve accurate diagnosis and treatment of patients with acetabular fractures, and obtain satisfactory prognosis, the Orthopedic Trauma Emergency Center of Third Hospital of Hebei Medical University and the Trauma Orthopedic Branch of the Chinese Orthopedic Association organized experts from relevant fields to formulate the Expert consensus on the accurate diagnosis and treatment of acetabular fractures based on three-column classification ( version 2023) in terms of principles of evidence-based medicine. Based on the three-column classification, 15 recommendations were proposed, covering the diagnosis, treatment, complication prevention and management, etc, so as to provide reference for accurate diagnosis and treatment of acetabular fractures.