The relationship between exercise and cardiac health has always been a hotspot in the fields of medicine and exercise science. Recently, with the in-depth study of the biological clock, people have gradually realized the close relationship between cardiac metabolic activity and circadian rhythms. The mammalian circadian system includes the central circadian clock and peripheral circadian clocks, the central circadian clock is the main clock system responsible for regulating the circadian rhythms in organisms, located in the suprachiasmatic nucleus (SCN) of the hypothalamus in mammals, which receives light signals from the retina and translates them into neural signals to regulate peripheral circadian clocks distributed throughout the body. Peripheral circadian clocks exist in various tissues and organs of organisms, coordinating with the central circadian clock to maintain the circadian rhythms of the organism. A series of clock genes regulate downstream clock-controlled genes through the transcriptional-translational feedback loop (TTFL), profoundly affecting the physiological activities of the heart, including cardiac contraction, relaxation, and metabolic processes. Factors such as sleep disorders, shift work, light pollution, and excessive use of electronic devices in modern lifestyles have led to widespread disruption of circadian rhythms, which are significantly correlated with increased cardiovascular disease incidence and mortality. Studies have found that dysregulation of the cardiac circadian clock can not only lead to myocardial lipid degeneration and weakened metabolic rhythms but also decrease myocardial glucose utilization, thereby increasing the risk of adverse cardiac events. Exercise, as a key zeitgeber, has been widely demonstrated to regulate the circadian clocks of peripheral organs such as skeletal muscle, kidneys, and liver. Additionally, exercise, as an important means to improve cardiovascular function, can effectively enhance cardiac metabolic function and resistance to stress stimuli, playing a significant role in promoting heart health. However, the specific mechanisms by which exercise affects the cardiac circadian clock and its related genes are currently unclear. Therefore, this review will focus on the relationship between the cardiac circadian clock and cardiac metabolic activity, summarize previous research to review the possible mechanisms of exercise-mediated regulation of cardiac metabolic activity on the cardiac circadian clock. The cardiac circadian clock plays an important role in maintaining cardiac metabolic activity and physiological functions. The loss of cardiac circadian clock genes Bmal1 and Clock can significantly reduce cardiac fatty acid and glucose utilization rates, increase myocardial lipotoxicity, weaken the circadian rhythm of myocardial triglyceride metabolism, and lead to abnormalities in the circadian clocks of other peripheral organs. Exercise, as a zeitgeber, can independently regulate the cardiac circadian clock apart from the central circadian clock. Additionally, exercise, as an important means to improve cardiovascular function, may regulate cardiac metabolic activity and the transcription of clock genes by activating the hypothalamic-pituitary-adrenal axis (HPA) and sympathetic-adrenal-medullary axis (SAM) and regulating energy metabolism, thereby maintaining the stability of the cardiac circadian clock and promoting heart health. Future research on the molecular mechanisms of exercise regulation of the cardiac circadian clock will help clarify the role and impact of clock genes in cardiac metabolism and physiological activities, providing new preventive and treatment strategies for shift workers, night owls, and patients with cardiovascular diseases. Therefore, future research should focus on (1) the mechanisms by which exercise regulates cardiac metabolic activity and the circadian clock, (2) the effects and mechanisms of exercise on the disruption of cardiac circadian clock induced by light-dark cycle disturbances, and (3) the effects of exercise on the metabolic activity and circadian rhythms of other peripheral organs regulated by the cardiac circadian clock.

An adsorption and concentration sampling device for volatile organic compounds(VOCs)was designed in this work,which improved the long-term monitoring stability of the online monitoring system for VOC adsorption and concentration,and solved the issue of rapid attenuation of responses toward higher carbon compounds.The designed VOC desorption device achieved an average heating rate of 40 ℃/s,with a relative standard deviation(RSD)of 0.4％.Quantitative analysis of mixture of 116 kinds of different VOC standard gases was performed,and the test results showed that the qualification rate of standard curves increased significantly from 90％to 99％,the proportion of detection limits below 0.1 nmol/mol improved from 85％to 90％,and the proportion of residual levels in the system below 0.1 nmol/mol also increased from 85％to 90％.The stable monitoring period was extended from 20 d to over 30 d,making it more conducive to long-term unattended monitoring by the developed instrument.

Aim To investigate the effects of Ginkgo biloba extract(GBE)on vascular endothelial dysfunc-tion induced by chronic intermittent hypoxia(CIH)in rats and its related mechanisms.Methods The CIH rat model was established,and 50 and 100 mg·kg-1 GBE was administered by intragastric administration.The systolic blood pressure(SBP)of the tail artery was detected in each group.HE staining was used to detect the morphology of aorta tissue.DAF-FM DA staining and nitric reductase assay were used to detect NO levels.ELISA was used to detect serum ET-1,TNF-α and IL-6 levels.DHE staining was used to de-tect reactive oxygen species(ROS)levels of aortic tis-sue.Kits were used to detect the serum levels of MDA,SOD and GSH-Px.Western blot was used to detect the levels of VCAM-1,ICAM-1,nucleus Nrf2,HO-1 and NQO1 of aortic tissue.Results GBE sig-nificantly decreased the levels of SBP,ET-1,ROS,MDA,VCAM-1,ICAM-1,TNF-α and IL-6,and sig-nificantly increased the levels of NO,SOD,GSH-Px,nuclear Nrf2,HO-1 and NQO1 in CIH rats.GBE sig-nificantly improved the histomorphology of aorta in CIH rats.Conclusions GBE can improve vascular endo-thelial dysfunction and reduce blood pressure in CIH model rats.The mechanism may be related to the acti-vation of Nrf2/ARE pathway and the inhibition of oxi-dative stress and inflammation by GBE.

Diabetes mellitus is a heterogeneous disease that encompasses a wide range of conditions, from mild cases to severe conditions where survival depends on insulin therapy. The Korean Diabetes Association Task Force Team for Diabetes with β-Cell Failure has established the term to classify severe refractory disease with β-cell failure. Individuals with β-cell failure are at high risk of diabetes-related complications. We propose that diabetes with β-cell failure can be diagnosed when individuals treated with multiple daily insulin injections or insulin pumps meet at least one of the following criteria: fasting C-peptide ≤ 0.6 ng/mL, non-fasting C-peptide ≤ 1.8 ng/mL, 24-hour urine C-peptide < 30 μg/day, or spot urine C-peptide/creatinine ratio ≤ 0.6 nmol/mmol. Among cases of diabetes with β-cell failure, β-cell failure with absolute insulin deficiency can be diagnosed when at least one of the following criteria is met: fasting C-peptide < 0.24 ng/mL, non-fasting C-peptide < 0.6 ng/mL, or spot urine C-peptide/ creatinine ratio < 0.2 nmol/mmol. Multiple daily insulin injections with long-acting insulin analogs and rapid-acting insulin analogs or insulin pumps are required for treatment of diabetes with β-cell failure. Continuous glucose monitoring and an automated insulin delivery system, sensor-augmented pump, or smart insulin pen, along with structured education, are necessary. We call for improvements in the relevant systems to ensure that such treatments can be provided.

Diabetes mellitus is a heterogeneous disease that encompasses a wide range of conditions, from mild cases to severe conditions where survival depends on insulin therapy. The Korean Diabetes Association Task Force Team for Diabetes with β-Cell Failure has established the term to classify severe refractory disease with β-cell failure. Individuals with β-cell failure are at high risk of diabetes-related complications. We propose that diabetes with β-cell failure can be diagnosed when individuals treated with multiple daily insulin injections or insulin pumps meet at least one of the following criteria: fasting C-peptide ≤ 0.6 ng/mL, non-fasting C-peptide ≤ 1.8 ng/mL, 24-hour urine C-peptide < 30 μg/day, or spot urine C-peptide/creatinine ratio ≤ 0.6 nmol/mmol. Among cases of diabetes with β-cell failure, β-cell failure with absolute insulin deficiency can be diagnosed when at least one of the following criteria is met: fasting C-peptide < 0.24 ng/mL, non-fasting C-peptide < 0.6 ng/mL, or spot urine C-peptide/ creatinine ratio < 0.2 nmol/mmol. Multiple daily insulin injections with long-acting insulin analogs and rapid-acting insulin analogs or insulin pumps are required for treatment of diabetes with β-cell failure. Continuous glucose monitoring and an automated insulin delivery system, sensor-augmented pump, or smart insulin pen, along with structured education, are necessary. We call for improvements in the relevant systems to ensure that such treatments can be provided.

Diabetes mellitus is a heterogeneous disease that encompasses a wide range of conditions, from mild cases to severe conditions where survival depends on insulin therapy. The Korean Diabetes Association Task Force Team for Diabetes with β-Cell Failure has established the term to classify severe refractory disease with β-cell failure. Individuals with β-cell failure are at high risk of diabetes-related complications. We propose that diabetes with β-cell failure can be diagnosed when individuals treated with multiple daily insulin injections or insulin pumps meet at least one of the following criteria: fasting C-peptide ≤ 0.6 ng/mL, non-fasting C-peptide ≤ 1.8 ng/mL, 24-hour urine C-peptide < 30 μg/day, or spot urine C-peptide/creatinine ratio ≤ 0.6 nmol/mmol. Among cases of diabetes with β-cell failure, β-cell failure with absolute insulin deficiency can be diagnosed when at least one of the following criteria is met: fasting C-peptide < 0.24 ng/mL, non-fasting C-peptide < 0.6 ng/mL, or spot urine C-peptide/ creatinine ratio < 0.2 nmol/mmol. Multiple daily insulin injections with long-acting insulin analogs and rapid-acting insulin analogs or insulin pumps are required for treatment of diabetes with β-cell failure. Continuous glucose monitoring and an automated insulin delivery system, sensor-augmented pump, or smart insulin pen, along with structured education, are necessary. We call for improvements in the relevant systems to ensure that such treatments can be provided.

Diabetes mellitus is a heterogeneous disease that encompasses a wide range of conditions, from mild cases to severe conditions where survival depends on insulin therapy. The Korean Diabetes Association Task Force Team for Diabetes with β-Cell Failure has established the term to classify severe refractory disease with β-cell failure. Individuals with β-cell failure are at high risk of diabetes-related complications. We propose that diabetes with β-cell failure can be diagnosed when individuals treated with multiple daily insulin injections or insulin pumps meet at least one of the following criteria: fasting C-peptide ≤ 0.6 ng/mL, non-fasting C-peptide ≤ 1.8 ng/mL, 24-hour urine C-peptide < 30 μg/day, or spot urine C-peptide/creatinine ratio ≤ 0.6 nmol/mmol. Among cases of diabetes with β-cell failure, β-cell failure with absolute insulin deficiency can be diagnosed when at least one of the following criteria is met: fasting C-peptide < 0.24 ng/mL, non-fasting C-peptide < 0.6 ng/mL, or spot urine C-peptide/ creatinine ratio < 0.2 nmol/mmol. Multiple daily insulin injections with long-acting insulin analogs and rapid-acting insulin analogs or insulin pumps are required for treatment of diabetes with β-cell failure. Continuous glucose monitoring and an automated insulin delivery system, sensor-augmented pump, or smart insulin pen, along with structured education, are necessary. We call for improvements in the relevant systems to ensure that such treatments can be provided.

Diabetes mellitus is a heterogeneous disease that encompasses a wide range of conditions, from mild cases to severe conditions where survival depends on insulin therapy. The Korean Diabetes Association Task Force Team for Diabetes with β-Cell Failure has established the term to classify severe refractory disease with β-cell failure. Individuals with β-cell failure are at high risk of diabetes-related complications. We propose that diabetes with β-cell failure can be diagnosed when individuals treated with multiple daily insulin injections or insulin pumps meet at least one of the following criteria: fasting C-peptide ≤ 0.6 ng/mL, non-fasting C-peptide ≤ 1.8 ng/mL, 24-hour urine C-peptide < 30 μg/day, or spot urine C-peptide/creatinine ratio ≤ 0.6 nmol/mmol. Among cases of diabetes with β-cell failure, β-cell failure with absolute insulin deficiency can be diagnosed when at least one of the following criteria is met: fasting C-peptide < 0.24 ng/mL, non-fasting C-peptide < 0.6 ng/mL, or spot urine C-peptide/ creatinine ratio < 0.2 nmol/mmol. Multiple daily insulin injections with long-acting insulin analogs and rapid-acting insulin analogs or insulin pumps are required for treatment of diabetes with β-cell failure. Continuous glucose monitoring and an automated insulin delivery system, sensor-augmented pump, or smart insulin pen, along with structured education, are necessary. We call for improvements in the relevant systems to ensure that such treatments can be provided.

Background: Worldwide, sepsis is the leading cause of death in hospitals. If mortality rates in patients with sepsis can be predicted early, medical resources can be allocated efficiently. We constructed machine learning (ML) models to predict the mortality of patients with sepsis in a hospital emergency department. Methods: This study prospectively collected nationwide data from an ongoing multicenter cohort of patients with sepsis identified in the emergency department. Patients were enrolled from 19 hospitals between September 2019 and December 2020. For acquired data from 3,657 survivors and 1,455 deaths, six ML models (logistic regression, support vector machine, random forest, extreme gradient boosting [XGBoost], light gradient boosting machine, and categorical boosting [CatBoost]) were constructed using fivefold cross-validation to predict mortality. Through these models, 44 clinical variables measured on the day of admission were compared with six sequential organ failure assessment (SOFA) components (PaO 2 /FIO 2 [PF], platelets (PLT), bilirubin, cardiovascular, Glasgow Coma Scale score, and creatinine).The confidence interval (CI) was obtained by performing 10,000 repeated measurements via random sampling of the test dataset. All results were explained and interpreted using Shapley’s additive explanations (SHAP). Results: Of the 5,112 participants, CatBoost exhibited the highest area under the curve (AUC) of 0.800 (95% CI, 0.756–0.840) using clinical variables. Using the SOFA components for the same patient, XGBoost exhibited the highest AUC of 0.678 (95% CI, 0.626–0.730). As interpreted by SHAP, albumin, lactate, blood urea nitrogen, and international normalization ratio were determined to significantly affect the results. Additionally, PF and PLTs in the SOFA component significantly influenced the prediction results. Conclusion Newly established ML-based models achieved good prediction of mortality in patients with sepsis. Using several clinical variables acquired at the baseline can provide more accurate results for early predictions than using SOFA components. Additionally, the impact of each variable was identified.

Objective: Compare and analyze the results of the domestic Lanyi AH600 glycated hemoglobin analyzer and other different detection systems to understand the comparability of the detection results of different detectors, and establish the best cut point of Lanyi AH600 determination of haemoglobin A1c (HbA1c) in the diagnosis of diabetes. Methods: Multi center cohort study was adopted. The clinical laboratory departments of 18 medical institutions independently collected test samples from their respective hospitals from March to April 2022, and independently completed comparative analysis of the evaluated instrument (Lanyi AH600) and the reference instrument HbA1c. The reference instruments include four different brands of glycosylated hemoglobin meters, including Arkray, Bio-Rad, DOSOH, and Huizhong. Scatter plot was used to calculate the correlation between the results of different detection systems, and the regression equation was calculated. The consistency analysis between the results of different detection systems was evaluated by Bland Altman method. Consistency judgment principles: (1) When the 95% limits of agreement (95% LoA) of the measurement difference was within 0.4% HbA1c and the measurement score was≥80 points, the comparison consistency was good; (2) When the measurement difference of 95% LoA exceeded 0.4% HbA1c, and the measurement score was≥80 points, the comparison consistency was relatively good; (3) The measurement score was less than 80 points, the comparison consistency was poor. The difference between the results of different detection systems was tested by paired sample T test or Wilcoxon paired sign rank sum test; The best cut-off point of diabetes was analyzed by receiver operating characteristic curve (ROC). Results: The correlation coefficient R² of results between Lanyi AH600 and the reference instrument in 16 hospitals is≥0.99; The Bland Altman consistency analysis showed that the difference of 95% LoA in Nanjing Maternity and Child Health Care Hospital in Jiangsu Province (reference instrument: Arkray HA8180) was -0.486%-0.325%, and the measurement score was 94.6 points (473/500); The difference of 95% LoA in the Tibetan Traditional Medical Hospital of TAR (reference instrument: Bio-Rad Variant II) was -0.727%-0.612%, and the measurement score was 89.8 points; The difference of 95% LoA in the People's Hospital of Chongqing Liang Jiang New Area (reference instrument: Huizhong MQ-2000PT) was -0.231%-0.461%, and the measurement score was 96.6 points; The difference of 95% LoA in the Taihe Hospital of traditional Chinese Medicine in Anhui Province (reference instrument: Huizhong MQ-2000PT) was -0.469%-0.479%, and the measurement score was 91.9 points. The other 14 hospitals, Lanyi AH600, were compared with 4 reference instrument brands, the difference of 95% LoA was less than 0.4% HbA1c, and the scores were all greater than 95 points. The results of paired sample T test or Wilcoxon paired sign rank sum test showed that there was no statistically significant difference between Lanyi AH600 and the reference instrument Arkray HA8180 (Z=1.665,P=0.096), with no statistical difference. The mean difference between the measured values of the two instruments was 0.004%. The comparison data of Lanyi AH600 and the reference instrument of all other institutions had significant differences (all P<0.001), however, it was necessary to consider whether it was within the clinical acceptable range in combination with the results of the Bland-Altman consistency analysis. The ROC curve of HbA1c detected by Lanyi AH600 in 985 patients with diabetes and 3 423 patients with non-diabetes was analyzed, the area under curve (AUC) was 0.877, the standard error was 0.007, and the 95% confidence interval 95%CI was (0.864, 0.891), which was statistically significant (P<0.001). The maximum value of Youden index was 0.634, and the corresponding HbA1c cut point was 6.235%. The sensitivity and specificity of diabetes diagnosis were 76.2% and 87.2%, respectively. Conclusion: Among the hospitals and instruments currently included in this study, among these four hospitals included Nanjing Maternity and Child Health Care Hospital in Jiangsu Province (reference instrument: Arkray HA8180), Tibetan Traditional Medical Hospital of TAR (reference instrument: Bio-Rad Variant Ⅱ), the People's Hospital of Chongqing Liang Jiang New Area (reference instrument: Huizhong MQ-2000PT), and the Taihe Hospital of traditional Chinese Medicine in Anhui Province (reference instrument: Huizhong MQ-2000PT), the comparison between Lanyi AH600 and the reference instruments showed relatively good consistency, while the other 14 hospitals involved four different brands of reference instruments: Arkray, Bio-Rad, DOSOH, and Huizhong, Lanyi AH600 had good consistency with its comparison. The best cut point of the domestic Lanyi AH600 for detecting HbA1c in the diagnosis of diabetes is 6.235%.
Pregnancy ; Child ; Humans ; Female ; Glycated Hemoglobin ; Cohort Studies ; Diabetes Mellitus/diagnosis* ; Sensitivity and Specificity ; ROC Curve