The neonatal mammalian heart has a remarkable regenerative capacity, while the adult heart has difficulty to regenerate. A metabolic reprogramming from glycolysis to fatty acid oxidation occurs along with the loss of cardiomyocyte proliferative capacity shortly after birth. In this study, we sought to determine if and how metabolic reprogramming regulates cardiomyocyte proliferation. Reversing metabolic reprogramming by carnitine palmitoyltransferase 1 (CPT1) inhibition, using cardiac-specific Cpt1a and Cpt1b knockout mice promoted cardiomyocyte proliferation and improved cardiac function post-myocardial infarction. The inhibition of CPT1 is of pharmacological significance because those protective effects were replicated by etomoxir, a CPT1 inhibitor. CPT1 inhibition, by decreasing poly(ADP-ribose) polymerase 1 expression, reduced ADP-ribosylation of dual-specificity phosphatase 1 in cardiomyocytes, leading to decreased p38 MAPK phosphorylation, and stimulation of cardiomyocyte proliferation. Our present study indicates that reversing metabolic reprogramming is an effective strategy to stimulate adult cardiomyocyte proliferation. CPT1 is a potential therapeutic target for promoting heart regeneration and myocardial infarction treatment.

OBJECTIVE: To investigate the association between long-term glycemic control and cerebral infarction risk in patients with diabetes through a large-scale cohort study. METHODS: This prospective, community-based cohort study included 12,054 patients with diabetes. From 2006 to 2012, 38,272 fasting blood glucose (FBG) measurements were obtained from these participants. FBG trajectory patterns were generated using latent mixture modelling. Cox proportional hazards models were applied to assess the subsequent risk of cerebral infarction associated with different FBG trajectory patterns. RESULTS: At baseline, the mean age of the participants was 55.2 years. Four distinct FBG trajectories were identified based on FBG concentrations and their changes over the 6-year follow-up period. After a median follow-up of 6.9 years, 786 cerebral infarction events were recorded. Different trajectory patterns were associated with significantly varied outcome risks (Log-Rank P < 0.001). Compared with the low-stability group, Hazard Ratio ( HR) adjusted for potential confounders were 1.37 for the moderate-increasing group, 1.23 for the elevated-decreasing group, and 2.08 for the elevated-stable group. CONCLUSION Sustained high FBG levels were found to play a critical role in the development of ischemic stroke among patients with diabetes. Controlling FBG levels may reduce the risk of cerebral infarction.
Humans ; Cerebral Infarction/blood* ; Middle Aged ; Male ; Female ; Blood Glucose/analysis* ; Fasting/blood* ; Aged ; Prospective Studies ; Risk Factors ; Diabetes Mellitus/blood* ; Adult ; Proportional Hazards Models

Objective:To preliminarily establish a sample clot warning model for coagulation screening tests using 5 machine learning methods.Methods:This cross-sectional study collected 7 401 routine screening test samples from Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, from January 1st, 2015, to August 18th, 2024, including 4 786 clotted (positive) and 2 615 qualified (negative) samples for model development. The dataset was divided into Dataset 1 and Dataset 2 based on a reagent change for APTT in December 2018, with separate models developed for each. An additional 2 493 samples (October 31st to November 8th, 2024) were used to evaluate consistency between the model and manual assessment, while 23 200 samples (October 17th to December 31st, 2024) were used for assessing real-world predictive performance. Five machine learning algorithms were employed to develop the clot prediction model: logistic regression (LR), random forest (RF), extreme gradient boosting (XGBoost), naive bayes (NB), and artificial neural network (ANN), with the ANN model constructed using two different hidden layer and neuron parameter settings. Model selection was based on AUC, accuracy, sensitivity, specificity, F1-score, PPV, and NPV, with the optimal model integrated into the LIS for validation.Results:Among the six models using 5 machine learning algorithms, XGBoost demonstrated the highest performance (AUC=0.961, sensitivity=0.945, F1-score=0.934) and robustness to reagent changes ( Z=-1.333, P=0.113). When deployed, the differences between the model's predictions and manual pre-judgment were statistically significant ( Z=-5.289 to 8.933, all P<0.01). The predictive efficacy indices AUC (95% CI), sensitivity, specificity, and accuracy of the XGBoost model deployed in real-world operation of the LIS were 0.939 (0.918—0.960), 0.958, 0.921, and 0.921 respectively. Conclusion:In this study, a clot warning model for coagulation screening samples was established based on the XGBoost algorithm, and its prediction efficacy is good, providing a foundation for intelligent pre-analytical quality control for coagulation screening tests.

AIM To study the chemical constituents from the bark of Toona sinensis(A.Juss.)Roem and their anti-inflammatory activity.METHODS Silica gel,RP-18 reverse phase silica gel and HPLC were used for isolation and purification,then the structures of obtained compounds were identified by physicochemical properties and spectral data.Their anti-inflammatory activity were evaluated by RAW264.7 model.RESULTS Sixteen compounds were isolated and identified as(9Z)-18-hydroxyo-ctadec-9-en-4,6-diyn-3-one(1),toonapolyyne C(2),(9S,10E,16R)-octadec-10-ene-12,14-diyne-1,9,16-triol(3),(9S,10E,16R)-9,16-dihydroxyoctadec-10-ene-12,14-diy-n-1-yl acetate(4),toonapolyyne A(5),toonasindiyne B(6),scopoletin(7),sco-parone(8),3-O-acetyl(-)-epicatechin(9),p-ethoxyacetanilide(10),kulonic acid(11),β-sitosterol-3-O-β-D-glucopyranoside(12),vanillic acid(13),cleomiscosin A(14),(-)-isolariciresinol(15),resveratrol(16).The IC50 values of compounds 3-4,6,11-13 for NO were 6.90,10.49,20.03,9.49,18.34,24.36 μmol/L,respectively.CONCLUSION Compound 1 is a new polyacetylene,8-16 are isolated from T.sinensis for the first time.Compounds 3-4,6,11-13 have good anti-inflammatory activity.

AIM To study the chemical constituents from the bark of Toona sinensis(A.Juss.)Roem and their anti-inflammatory activity.METHODS Silica gel,RP-18 reverse phase silica gel and HPLC were used for isolation and purification,then the structures of obtained compounds were identified by physicochemical properties and spectral data.Their anti-inflammatory activity were evaluated by RAW264.7 model.RESULTS Sixteen compounds were isolated and identified as(9Z)-18-hydroxyo-ctadec-9-en-4,6-diyn-3-one(1),toonapolyyne C(2),(9S,10E,16R)-octadec-10-ene-12,14-diyne-1,9,16-triol(3),(9S,10E,16R)-9,16-dihydroxyoctadec-10-ene-12,14-diy-n-1-yl acetate(4),toonapolyyne A(5),toonasindiyne B(6),scopoletin(7),sco-parone(8),3-O-acetyl(-)-epicatechin(9),p-ethoxyacetanilide(10),kulonic acid(11),β-sitosterol-3-O-β-D-glucopyranoside(12),vanillic acid(13),cleomiscosin A(14),(-)-isolariciresinol(15),resveratrol(16).The IC50 values of compounds 3-4,6,11-13 for NO were 6.90,10.49,20.03,9.49,18.34,24.36 μmol/L,respectively.CONCLUSION Compound 1 is a new polyacetylene,8-16 are isolated from T.sinensis for the first time.Compounds 3-4,6,11-13 have good anti-inflammatory activity.

Objective:To preliminarily establish a sample clot warning model for coagulation screening tests using 5 machine learning methods.Methods:This cross-sectional study collected 7 401 routine screening test samples from Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, from January 1st, 2015, to August 18th, 2024, including 4 786 clotted (positive) and 2 615 qualified (negative) samples for model development. The dataset was divided into Dataset 1 and Dataset 2 based on a reagent change for APTT in December 2018, with separate models developed for each. An additional 2 493 samples (October 31st to November 8th, 2024) were used to evaluate consistency between the model and manual assessment, while 23 200 samples (October 17th to December 31st, 2024) were used for assessing real-world predictive performance. Five machine learning algorithms were employed to develop the clot prediction model: logistic regression (LR), random forest (RF), extreme gradient boosting (XGBoost), naive bayes (NB), and artificial neural network (ANN), with the ANN model constructed using two different hidden layer and neuron parameter settings. Model selection was based on AUC, accuracy, sensitivity, specificity, F1-score, PPV, and NPV, with the optimal model integrated into the LIS for validation.Results:Among the six models using 5 machine learning algorithms, XGBoost demonstrated the highest performance (AUC=0.961, sensitivity=0.945, F1-score=0.934) and robustness to reagent changes ( Z=-1.333, P=0.113). When deployed, the differences between the model's predictions and manual pre-judgment were statistically significant ( Z=-5.289 to 8.933, all P<0.01). The predictive efficacy indices AUC (95% CI), sensitivity, specificity, and accuracy of the XGBoost model deployed in real-world operation of the LIS were 0.939 (0.918—0.960), 0.958, 0.921, and 0.921 respectively. Conclusion:In this study, a clot warning model for coagulation screening samples was established based on the XGBoost algorithm, and its prediction efficacy is good, providing a foundation for intelligent pre-analytical quality control for coagulation screening tests.

Although indigenous malaria has been eliminated in Wuhan since 2013,imported malaria remains a potential threat as an infectious source of local malaria transmission.The epidemiological and clinical characteristics of imported malaria are particularly important in areas where local malaria has been eliminated.This study was aimed at analyzing the epidemiological and clinical characteristics of imported malaria in Wuhan from 2012 to 2019,to provide a basis for further improving the preven-tion and control of imported malaria.Patients in Wuhan diagnosed with imported malaria from January 1,2012,to December 31,2019,were included in this study.A case-control study was con-ducted to analyze the features of patients with severe malaria.Uni-variate and multivariate logistic regression was used to identify risk factors for prolonged hospital length of stay(LOS).Among 229 imported malaria cases,212(92.6％)were in Chinese citizens,and most cases were in men(96.5％).The gender ratio is 28:1,and the age of cases is mainly concertrated between 18 and 50 years old(89.1％).More than 80％of patients were mi-grant workers,and most cases were infections from African countries(92.6％).Plasmodium falciparum(80.8％)was the dominant species.Fifty-three severe malaria cases were identified during the study period.Compared with uncomplicated cases,severe cases tended to occur in patients with no history of malaria(P=0.008),patients infected with Plasmodium falciparum(P=0.009),and patients who were initially misdiagnosed(P＜0.001).The median LOS was 6 days,and the species of infec-tion(Plasmodium falciparum),the use of antimalarial drugs(group B),antipyretic time(longer than 3 days),and the turn-around time of blood smear microscopy(longer than 3 days)were significantly associated with longer LOS(all P＜0.05).Al-though malaria has been eradicated in Wuhan for many years,imported cases continue to pose a threat.Efforts should be made to strengthen malaria knowledge education for outbound personnel.Additionally,medical institutions must enhance diagnosis and treatment capabilities for malaria,and adhere to standardized treatment processes,and the development of drug resistance and occurrence of severe malaria must be prevented.

Objective Cognitive impairment(CI)in older individuals has a high morbidity rate worldwide,with poor diagnostic methods and susceptible population identification.This study aimed to investigate the relationship between different retinal metrics and CI in a particular population,emphasizing polyvascular status. Methods We collected information from the Asymptomatic Polyvascular Abnormalities Community Study on retinal vessel calibers,retinal nerve fiber layer(RNFL)thickness,and cognitive function of 3,785 participants,aged 40 years or older.Logistic regression was used to analyze the relationship between retinal metrics and cognitive function.Subgroups stratified by different vascular statuses were also analyzed. Results RNFL thickness was significantly thinner in the CI group(odds ratio:0.973,95%confidence interval:0.953-0.994).In the subgroup analysis,the difference still existed in the non-intracranial arterial stenosis,non-extracranial carotid arterial stenosis,and peripheral arterial disease subgroups(P<0.05). Conclusion A thin RNFL is associated with CI,especially in people with non-large vessel stenosis.The underlying small vessel change in RNFL and CI should be investigated in the future.

Objective To observe the efficacy and safety of Morinda officinalis oligosaccharides in the continuation treatment of mild and moderate depression.Methods An open,single-arm,multi-center design was adopted in our study.Adult patients with mild and moderate depression who had received acute treatment of Morinda officinalis oligosaccharides were enrolled and continue to receive Morinda officinalis oligosaccharides capsules for 24 weeks,the dose remained unchanged during continuation treatment.The remission rate,recurrence rate,recurrence time,and the change from baseline to endpoint of Hamilton Depression Scale(HAMD),Hamilton Anxiety Scale(HAMA),Clinical Global Impression-Severity(CGI-S)and Arizona Sexual Experience Scale(ASEX)were evaluated.The incidence of treatment-related adverse events was reported.Results The scores of HAMD-17 at baseline and after treatment were 6.60±1.87 and 5.85±4.18,scores of HAMA were 6.36±3.02 and 4.93±3.09,scores of CGI-S were 1.49±0.56 and 1.29±0.81,scores of ASEX were 15.92±4.72 and 15.57±5.26,with significant difference(P＜0.05).After continuation treatment,the remission rate was 54.59％(202 cases/370 cases),and the recurrence rate was 6.49％(24 cases/370 cases),the recurrence time was(64.67±42.47)days.The incidence of treatment-related adverse events was 15.35％(64 cases/417 cases).Conclusion Morinda officinalis oligosaccharides capsules can be effectively used for the continuation treatment of mild and moderate depression,and are well tolerated and safe.

ObjectiveTo investigate the effect of mucin 1 (MUC1) on the proliferation and apoptosis of nasopharyngeal carcinoma (NPC) and its regulatory mechanism. MethodsThe 60 NPC and paired para-cancer normal tissues were collected from October 2020 to July 2021 in Quanzhou First Hospital. The expression of MUC1 was measured by real-time quantitative PCR (qPCR) in the patients with PNC. The 5-8F and HNE1 cells were transfected with siRNA control (si-control) or siRNA targeting MUC1 (si-MUC1). Cell proliferation was analyzed by cell counting kit-8 and colony formation assay, and apoptosis was analyzed by flow cytometry analysis in the 5-8F and HNE1 cells. The qPCR and ELISA were executed to analyze the levels of TNF-α and IL-6. Western blot was performed to measure the expression of MUC1, NF-кB and apoptosis-related proteins (Bax and Bcl-2). ResultsThe expression of MUC1 was up-regulated in the NPC tissues, and NPC patients with the high MUC1 expression were inclined to EBV infection, growth and metastasis of NPC. Loss of MUC1 restrained malignant features, including the proliferation and apoptosis, downregulated the expression of p-IкB、p-P65 and Bcl-2 and upregulated the expression of Bax in the NPC cells. ConclusionDownregulation of MUC1 restrained biological characteristics of malignancy, including cell proliferation and apoptosis, by inactivating NF-κB signaling pathway in NPC.