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.

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.

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 analyze and compare therapy responses, outcomes, and incidence of severe hematologic adverse events of flumatinib and imatinib in patients newly diagnosed with chronic phase chronic myeloid leukemia (CML) . Methods: Data of patients with chronic phase CML diagnosed between January 2006 and November 2022 from 76 centers, aged ≥18 years, and received initial flumatinib or imatinib therapy within 6 months after diagnosis in China were retrospectively interrogated. Propensity score matching (PSM) analysis was performed to reduce the bias of the initial TKI selection, and the therapy responses and outcomes of patients receiving initial flumatinib or imatinib therapy were compared. Results: A total of 4 833 adult patients with CML receiving initial imatinib (n=4 380) or flumatinib (n=453) therapy were included in the study. In the imatinib cohort, the median follow-up time was 54 [interquartile range (IQR), 31-85] months, and the 7-year cumulative incidences of CCyR, MMR, MR(4), and MR(4.5) were 95.2%, 88.4%, 78.3%, and 63.0%, respectively. The 7-year FFS, PFS, and OS rates were 71.8%, 93.0%, and 96.9%, respectively. With the median follow-up of 18 (IQR, 13-25) months in the flumatinib cohort, the 2-year cumulative incidences of CCyR, MMR, MR(4), and MR(4.5) were 95.4%, 86.5%, 58.4%, and 46.6%, respectively. The 2-year FFS, PFS, and OS rates were 80.1%, 95.0%, and 99.5%, respectively. The PSM analysis indicated that patients receiving initial flumatinib therapy had significantly higher cumulative incidences of CCyR, MMR, MR(4), and MR(4.5) and higher probabilities of FFS than those receiving the initial imatinib therapy (all P<0.001), whereas the PFS (P=0.230) and OS (P=0.268) were comparable between the two cohorts. The incidence of severe hematologic adverse events (grade≥Ⅲ) was comparable in the two cohorts. Conclusion: Patients receiving initial flumatinib therapy had higher cumulative incidences of therapy responses and higher probability of FFS than those receiving initial imatinib therapy, whereas the incidence of severe hematologic adverse events was comparable between the two cohorts.
Adult ; Humans ; Adolescent ; Imatinib Mesylate/adverse effects* ; Incidence ; Antineoplastic Agents/adverse effects* ; Retrospective Studies ; Pyrimidines/adverse effects* ; Leukemia, Myelogenous, Chronic, BCR-ABL Positive/drug therapy* ; Treatment Outcome ; Benzamides/adverse effects* ; Leukemia, Myeloid, Chronic-Phase/drug therapy* ; Aminopyridines/therapeutic use* ; Protein Kinase Inhibitors/therapeutic use*

Objective: This cross-sectional investigation aimed to determine the incidence, clinical characteristics, prognosis, and related risk factors of olfactory and gustatory dysfunctions related to infection with the SARS-CoV-2 Omicron strain in mainland China. Methods: Data of patients with SARS-CoV-2 from December 28, 2022, to February 21, 2023, were collected through online and offline questionnaires from 45 tertiary hospitals and one center for disease control and prevention in mainland China. The questionnaire included demographic information, previous health history, smoking and alcohol drinking, SARS-CoV-2 vaccination, olfactory and gustatory function before and after infection, other symptoms after infection, as well as the duration and improvement of olfactory and gustatory dysfunction. The self-reported olfactory and gustatory functions of patients were evaluated using the Olfactory VAS scale and Gustatory VAS scale. Results: A total of 35 566 valid questionnaires were obtained, revealing a high incidence of olfactory and taste dysfunctions related to infection with the SARS-CoV-2 Omicron strain (67.75%). Females(χ2=367.013, P<0.001) and young people(χ2=120.210, P<0.001) were more likely to develop these dysfunctions. Gender(OR=1.564, 95%CI: 1.487-1.645), SARS-CoV-2 vaccination status (OR=1.334, 95%CI: 1.164-1.530), oral health status (OR=0.881, 95%CI: 0.839-0.926), smoking history (OR=1.152, 95%CI=1.080-1.229), and drinking history (OR=0.854, 95%CI: 0.785-0.928) were correlated with the occurrence of olfactory and taste dysfunctions related to SARS-CoV-2(above P<0.001). 44.62% (4 391/9 840) of the patients who had not recovered their sense of smell and taste also suffered from nasal congestion, runny nose, and 32.62% (3 210/9 840) suffered from dry mouth and sore throat. The improvement of olfactory and taste functions was correlated with the persistence of accompanying symptoms(χ2=10.873, P=0.001). The average score of olfactory and taste VAS scale was 8.41 and 8.51 respectively before SARS-CoV-2 infection, but decreased to3.69 and 4.29 respectively after SARS-CoV-2 infection, and recovered to 5.83and 6.55 respectively at the time of the survey. The median duration of olfactory and gustatory dysfunctions was 15 days and 12 days, respectively, with 0.5% (121/24 096) of patients experiencing these dysfunctions for more than 28 days. The overall self-reported improvement rate of smell and taste dysfunctions was 59.16% (14 256/24 096). Gender(OR=0.893, 95%CI: 0.839-0.951), SARS-CoV-2 vaccination status (OR=1.334, 95%CI: 1.164-1.530), history of head and facial trauma(OR=1.180, 95%CI: 1.036-1.344, P=0.013), nose (OR=1.104, 95%CI: 1.042-1.171, P=0.001) and oral (OR=1.162, 95%CI: 1.096-1.233) health status, smoking history(OR=0.765, 95%CI: 0.709-0.825), and the persistence of accompanying symptoms (OR=0.359, 95%CI: 0.332-0.388) were correlated with the recovery of olfactory and taste dysfunctions related to SARS-CoV-2 (above P<0.001 except for the indicated values). Conclusion: The incidence of olfactory and taste dysfunctions related to infection with the SARS-CoV-2 Omicron strain is high in mainland China, with females and young people more likely to develop these dysfunctions. Active and effective intervention measures may be required for cases that persist for a long time. The recovery of olfactory and taste functions is influenced by several factors, including gender, SARS-CoV-2 vaccination status, history of head and facial trauma, nasal and oral health status, smoking history, and persistence of accompanying symptoms.
Female ; Humans ; Adolescent ; SARS-CoV-2 ; Smell ; COVID-19/complications* ; Cross-Sectional Studies ; COVID-19 Vaccines ; Incidence ; Olfaction Disorders/etiology* ; Taste Disorders/etiology* ; Prognosis

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.