BACKGROUND: There are few multi-city studies on the association between temperature and mortality in basin climates. This study was based on the Sichuan Basin in southwest China to assess the association of basin temperature with non-accidental mortality in the population and with the temperature-related mortality burden. METHODS: Daily mortality data, meteorological and air pollution data were collected for four cities in the Sichuan Basin of southwest China. We used a two-stage time-series analysis to quantify the association between temperature and non-accidental mortality in each city, and a multivariate meta-analysis was performed to obtain the overall cumulative risk. The attributable fractions (AFs) were calculated to access the mortality burden attributable to non-optimal temperature. Additionally, we performed a stratified analyses by gender, age group, education level, and marital status. RESULTS: A total of 751,930 non-accidental deaths were collected in our study. Overall, 10.16% of non-accidental deaths could be attributed to non-optimal temperatures. A majority of temperature-related non-accidental deaths were caused by low temperature, accounting for 9.10% (95% eCI: 5.50%, 12.19%), and heat effects accounted for only 1.06% (95% eCI: 0.76%, 1.33%). The mortality burden attributable to non-optimal temperatures was higher among those under 65 years old, females, those with a low education level, and those with an alternative marriage status. CONCLUSIONS Our study suggested that a significant association between non-optimal temperature and non-accidental mortality. Those under 65 years old, females, and those with a low educational level or alternative marriage status had the highest attributable burden.
Female ; Humans ; China/epidemiology* ; Cities ; Cold Temperature ; Hot Temperature ; Mortality ; Temperature ; Time Factors ; Middle Aged ; Male

BACKGROUND: The HELIOS stent is a sirolimus-eluting stent with a biodegradable polymer and titanium oxide film as the tie-layer. The study aimed to evaluate the safety and efficacy of HELIOS stent in a real-world setting. METHODS: The HELIOS registry is a prospective, multicenter, cohort study conducted at 38 centers across China between November 2018 and December 2019. A total of 3060 consecutive patients were enrolled after application of minimal inclusion and exclusion criteria. The primary endpoint was target lesion failure (TLF), defined as a composite of cardiac death, non-fatal target vessel myocardial infarction (MI), and clinically indicated target lesion revascularization (TLR) at 1-year follow-up. Kaplan-Meier methods were used to estimate the cumulative incidence of clinical events and construct survival curves. RESULTS: A total of 2998 (98.0%) patients completed the 1-year follow-up. The 1-year incidence of TLF was 3.10% (94/2998, 95% closed interval: 2.54-3.78%). The rates of cardiac death, non-fatal target vessel MI and clinically indicated TLR were 2.33% (70/2998), 0.20% (6/2998), and 0.70% (21/2998), respectively. The rate of stent thrombosis was 0.33% (10/2998). Age ≥60 years, diabetes mellitus, family history of coronary artery disease, acute myocardial infarction at admission, and device success were independent predictors of TLF at 1 year. CONCLUSION: The 1-year incidence rates of TLF and stent thrombosis were 3.10% and 0.33%, respectively, in patients treated with HELIOS stents. Our results provide clinical evidence for interventional cardiologists and policymakers to evaluate HELIOS stent. CLINICAL TRIAL REGISTRATION ClinicalTrials.gov, NCT03916432.
Humans ; Middle Aged ; Sirolimus/therapeutic use* ; Drug-Eluting Stents/adverse effects* ; Prospective Studies ; Cohort Studies ; Treatment Outcome ; Risk Factors ; Time Factors ; Percutaneous Coronary Intervention/adverse effects* ; Cardiovascular Agents/therapeutic use* ; Coronary Artery Disease/therapy* ; Myocardial Infarction/etiology* ; Thrombosis/complications* ; Polymers ; Registries

OBJECTIVE: To analyze the results of activated partial thromboplastin time (APTT) mixing test in coagulation factor Ⅷ inhibitor-positive hemophilia patients, so as to increase the value of APTT mixing test in the screen of factor Ⅷ inhibitor. METHODS: Eighty plasmas samples with different titers of coagulation factor Ⅷ inhibitors had been collected and diluted for routine immediate APTT mixing test and at 37 ℃ 2 hours incubation APTT mixing test. Fifteen samples were selected for immediate and normal temperature incubation for 15 min, 30min, 1 hour, 2 hours and 37 ℃ for 30 min, 1 hour, 2 hours APTT mixing test. RESULTS: The results of APTT mixing test were significantly correlated with the titers of coagulation factor Ⅷ inhibitors. The ROC curve result showed that the best diagnostic cut-off value for 2 hours incubation APTT mixing test at 37 ℃ to determine the presence or absence of coagulation factor Ⅷ inhibitors was 43.8 s (sensitivity and specificity was 85.90% and 100%, respectively), while the best diagnostic cut-off value for distinguishing high-titer and low-titer Ⅷ inhibitors was 52.4 s (sensitivity and specificity was 98.18% and 95.65%, respectively). The critical coagulation factor Ⅷ inhibitor titer that could not be corrected by immediate APTT was 5.14 BU/ml, while that could not be corrected by 37 ℃ 2 hours incubation APTT was 1.31 BU/ml. Paired samples t -test was performed on the APTT mixing test results at different times and temperatures, and the differences were statistically significant (P < 0.05). CONCLUSIONS The APTT mixing test can be used as a screening index for coagulation factor Ⅷ inhibitors. APTT mixing test result shows a significant time-temperature dependence with lower titers of coagulation factor Ⅷ inhibitor. Patients with hemophilia who cannot be corrected by immediate APTT mixing test should be alert to the possibility of high titer of coagulation factor Ⅷ.
Humans ; Factor VIII ; Hemophilia A/diagnosis* ; Blood Coagulation Tests/methods* ; Partial Thromboplastin Time ; Blood Coagulation Factors

OBJECTIVE: To explore the high-risk clinical factors of early death in patients with secondary hemophagocytic lymphohistiocytosis (sHLH), and further identify the clinical factors related to the rapid progression of sHLH in the short term. METHODS: The clinical manifestations, laboratory examination and prognosis of sHLH patients were retrospectively analyzed. Continuous variables were grouped by median, univariate and multivariate Cox regression analysis and Kaplan-Meier survival curve were used to explore the risk factors affecting early death of sHLH. Then, a nomogram model was established with independent risk factors, Bootstrap resampling method was used for verification, and consistency index (C-index) and calibration curve were used to detect the prediction accuracy. RESULTS: A total of 126 sHLH patients were enrolled, with a median age of 48.5(16-88) years, including 74 males and 52 females. Fifty-five patients (43.6%) died within 30 days, including 39 males and 16 females. Univariate regression analysis showed that lymphocyte count <0.45×10⁹/L, platelet count (PLT) <39.5×10⁹/L, prothrombin time (PT)≥13.3 s, activated partial thromboplastin time (APTT)≥39.7 s, albumin (ALB) <25.9 g/L, lactate dehydrogenase (LDH)≥811 U/L, creatinine (Cr) ≥67 μmol/L and procalcitonin (PCT)≥0.61 ng/ml were risk factors for death within 30 days in sHLH patients. Multivariate regression analysis showed that lymphocyte count <0.45×10⁹/L, APTT≥39.7 s and ALB <25.9 g/L were independent risk factors for death within 30 days in sHLH patients. A nomogram model was established based on the above three risk factors, its C-index was 0.683, and the calibration chart showed good agreement between the observed and predicted values of sHLH. CONCLUSIONS Lymphopenia, prolonged APTT, and hypoalbuminemia are risk factors for early death of sHLH patients. Early identification and positive intervention are expected to reduce early mortality in sHLH patients. The nomogram model based on the above risk factors provides a method for clinicians to evaluate sHLH.
Male ; Female ; Humans ; Middle Aged ; Aged ; Aged, 80 and over ; Lymphohistiocytosis, Hemophagocytic/complications* ; Retrospective Studies ; Prognosis ; Risk Factors ; Partial Thromboplastin Time ; Albumins

The extraction of neuroimaging features of migraine patients and the design of identification models are of great significance for the auxiliary diagnosis of related diseases. Compared with the commonly used image features, this study directly uses time-series signals to characterize the functional state of the brain in migraine patients and healthy controls, which can effectively utilize the temporal information and reduce the computational effort of classification model training. Firstly, Group Independent Component Analysis and Dictionary Learning were used to segment different brain areas for small-sample groups and then the regional average time-series signals were extracted. Next, the extracted time series were divided equally into multiple subseries to expand the model input sample. Finally, the time series were modeled using a bi-directional long-short term memory network to learn the pre-and-post temporal information within each time series to characterize the periodic brain state changes to improve the diagnostic accuracy of migraine. The results showed that the classification accuracy of migraine patients and healthy controls was 96.94%, the area under the curve was 0.98, and the computation time was relatively shorter. The experiments indicate that the method in this paper has strong applicability, and the combination of time-series feature extraction and bi-directional long-short term memory network model can be better used for the classification and diagnosis of migraine. This work provides a new idea for the lightweight diagnostic model based on small-sample neuroimaging data, and contributes to the exploration of the neural discrimination mechanism of related diseases.
Humans ; Time Factors ; Migraine Disorders/diagnostic imaging* ; Magnetic Resonance Imaging ; Brain/diagnostic imaging* ; Neuroimaging

Most information used to evaluate diabetic statuses is collected at a special time-point, such as taking fasting plasma glucose test and providing a limited view of individual's health and disease risk. As a new parameter for continuously evaluating personal clinical statuses, the newly developed technique "continuous glucose monitoring" (CGM) can characterize glucose dynamics. By calculating the complexity of glucose time series index (CGI) with refined composite multi-scale entropy analysis of the CGM data, the study showed for the first time that the complexity of glucose time series in subjects decreased gradually from normal glucose tolerance to impaired glucose regulation and then to type 2 diabetes (P for trend < 0.01). Furthermore, CGI was significantly associated with various parameters such as insulin sensitivity/secretion (all P < 0.01), and multiple linear stepwise regression showed that the disposition index, which reflects β-cell function after adjusting for insulin sensitivity, was the only independent factor correlated with CGI (P < 0.01). Our findings indicate that the CGI derived from the CGM data may serve as a novel marker to evaluate glucose homeostasis.
Humans ; Glucose ; Blood Glucose ; Insulin Resistance/physiology* ; Diabetes Mellitus, Type 2/diagnosis* ; Blood Glucose Self-Monitoring ; Time Factors ; Insulin

The brain-computer interface (BCI) based on motor imagery electroencephalography (MI-EEG) enables direct information interaction between the human brain and external devices. In this paper, a multi-scale EEG feature extraction convolutional neural network model based on time series data enhancement is proposed for decoding MI-EEG signals. First, an EEG signals augmentation method was proposed that could increase the information content of training samples without changing the length of the time series, while retaining its original features completely. Then, multiple holistic and detailed features of the EEG data were adaptively extracted by multi-scale convolution module, and the features were fused and filtered by parallel residual module and channel attention. Finally, classification results were output by a fully connected network. The application experimental results on the BCI Competition IV 2a and 2b datasets showed that the proposed model achieved an average classification accuracy of 91.87% and 87.85% for the motor imagery task, respectively, which had high accuracy and strong robustness compared with existing baseline models. The proposed model does not require complex signals pre-processing operations and has the advantage of multi-scale feature extraction, which has high practical application value.
Humans ; Time Factors ; Brain ; Electroencephalography ; Imagery, Psychotherapy ; Neural Networks, Computer

Interval timing is involved in a variety of cognitive behaviors such as associative learning and decision-making. While it has been shown that time estimation is adaptive to the temporal context, it remains unclear how interval timing behavior is influenced by recent trial history. Here we found that, in mice trained to perform a licking-based interval timing task, a decrease of inter-reinforcement interval in the previous trial rapidly shifted the time of anticipatory licking earlier. Optogenetic inactivation of the anterior lateral motor cortex (ALM), but not the medial prefrontal cortex, for a short time before reward delivery caused a decrease in the peak time of anticipatory licking in the next trial. Electrophysiological recordings from the ALM showed that the response profiles preceded by short and long inter-reinforcement intervals exhibited task-engagement-dependent temporal scaling. Thus, interval timing is adaptive to recent experience of the temporal interval, and ALM activity during time estimation reflects recent experience of interval.
Animals ; Mice ; Reward ; Time Factors ; Cognition ; Learning ; Decision Making ; Reinforcement, Psychology

Estimation of postmortem interval (PMI) is one of the important research contents in forensic pathology, and it has always been the focus and hot spot of research work. In recent years, scholars at home and abroad have made some research progress in estimating PMI by using ocular tissue. After death, the changes of cornea, aqueous humor, iris, lens, vitreous humor and retina all show time sequence change rule highly related to PMI. This paper reviews the research progress of PMI estimation based on the morphological, biochemical, molecular and genetic material changes of different ocular tissue structures after death, and discusses the existing problems and development trends.
Humans ; Postmortem Changes ; Time Factors ; Autopsy ; Vitreous Body ; Forensic Pathology

BACKGROUND: There is still uncertainty regarding whether diabetes mellitus (DM) can adversely affect patients undergoing carotid endarterectomy (CEA) for carotid stenosis. The aim of the study was to assess the adverse impact of DM on patients with carotid stenosis treated by CEA. METHODS: Eligible studies published between 1 January 2000 and 30 March 2023 were selected from the PubMed, EMBASE, Web of Science, CENTRAL, and ClinicalTrials databases. The short-term and long-term outcomes of major adverse events (MAEs), death, stroke, the composite outcomes of death/stroke, and myocardial infarction (MI) were collected to calculate the pooled effect sizes (ESs), 95% confidence intervals (CIs), and prevalence of adverse outcomes. Subgroup analysis by asymptomatic/symptomatic carotid stenosis and insulin/noninsulin-dependent DM was performed. RESULTS: A total of 19 studies (n = 122,003) were included. Regarding the short-term outcomes, DM was associated with increased risks of MAEs (ES = 1.52, 95% CI: [1.15-2.01], prevalence = 5.1%), death/stroke (ES = 1.61, 95% CI: [1.13-2.28], prevalence = 2.3%), stroke (ES = 1.55, 95% CI: [1.16-1.55], prevalence = 3.5%), death (ES = 1.70, 95% CI: [1.25-2.31], prevalence =1.2%), and MI (ES = 1.52, 95% CI: [1.15-2.01], prevalence = 1.4%). DM was associated with increased risks of long-term MAEs (ES = 1.24, 95% CI: [1.04-1.49], prevalence = 12.2%). In the subgroup analysis, DM was associated with an increased risk of short-term MAEs, death/stroke, stroke, and MI in asymptomatic patients undergoing CEA and with only short-term MAEs in the symptomatic patients. Both insulin- and noninsulin-dependent DM patients had an increased risk of short-term and long-term MAEs, and insulin-dependent DM was also associated with the short-term risk of death/stroke, death, and MI. CONCLUSIONS In patients with carotid stenosis treated by CEA, DM is associated with short-term and long-term MAEs. DM may have a greater impact on adverse outcomes in asymptomatic patients after CEA. Insulin-dependent DM may have a more significant impact on post-CEA adverse outcomes than noninsulin-dependent DM. Whether DM management could reduce the risk of adverse outcomes after CEA requires further investigation.
Humans ; Endarterectomy, Carotid/adverse effects* ; Carotid Stenosis/surgery* ; Risk Factors ; Treatment Outcome ; Time Factors ; Stents/adverse effects* ; Diabetes Mellitus, Type 2/complications* ; Diabetes Mellitus, Type 1 ; Stroke/complications* ; Insulin/therapeutic use* ; Myocardial Infarction/complications* ; Risk Assessment