Impact of stress hyperglycemia ratio on mortality in patients with critical acute myocardial infarction: insight from American MIMIC-IV and the Chinese CIN-II study

Background: Among patients with acute coronary syndrome and percutaneous coronary intervention, stress hyperglycemia ratio (SHR) is primarily associated with short-term unfavorable outcomes. However, the relationship between SHR and long-term worsen prognosis in acute myocardial infarction (AMI) patients admitted in intensive care unit (ICU) are not fully investigated, especially in those with different ethnicity. This study aimed to clarify the association of SHR with all-cause mortality in critical AMI patients from American and Chinese cohorts. Methods: Overall 4,337 AMI patients with their first ICU admission from the American Medical Information Mart for Intensive Care (MIMIC)-IV database (n = 2,166) and Chinese multicenter registry cohort Cardiorenal ImprovemeNt II (CIN-II, n = 2,171) were included in this study. The patients were divided into 4 groups based on quantiles of SHR in both two cohorts. Results: The total mortality was 23.8% (maximum follow-up time: 12.1 years) in American MIMIC-IV and 29.1% (maximum follow-up time: 14.1 years) in Chinese CIN-II. In MIMIC-IV cohort, patients with SHR of quartile 4 had higher risk of 1-year (adjusted hazard radio [aHR] = 1.87; 95% CI: 1.40–2.50) and long-term (aHR = 1.63; 95% CI: 1.27–2.09) all-cause mortality than quartile 2 (as reference). Similar results were observed in CIN-II cohort (1-year mortality: aHR = 1.44; 95%CI: 1.03–2.02; long-term mortality: aHR = 1.32; 95%CI: 1.05–1.66). In both two group, restricted cubic splines indicated a J-shaped correlation between SHR and all-cause mortality. In subgroup analysis, SHR was significantly associated with higher 1-year and long-term all-cause mortality among patients without diabetes in both MIMIC-IV and CIN-II cohort. Conclusion: Among critical AMI patients, elevated SHR is significantly associated with and 1-year and long-term all-cause mortality, especially in those without diabetes, and the results are consistently in both American and Chinese cohorts

Advances in the role of STAT3 in macrophage polarization

The physiological processes of cell growth, proliferation, differentiation, and apoptosis are closely related to STAT3, and it has been demonstrated that aberrant STAT3 expression has an impact on the onset and progression of a number of inflammatory immunological disorders, fibrotic diseases, and malignancies. In order to produce the necessary biological effects, macrophages (M0) can be polarized into pro-inflammatory (M1) and anti-inflammatory (M2) types in response to various microenvironmental stimuli. STAT3 signaling is involved in macrophage polarization, and the research of the effect of STAT3 on macrophage polarization has gained attention in recent years. In order to provide references for the treatment and investigation of disorders related to macrophage polarization, this review compiles the pertinent signaling pathways associated with STAT3 and macrophage polarization from many fundamental studies

Comparative investigations into environment-friendly production methods for railway prestressed concrete sleepers and bearers

Prestressed concrete sleeper is a safety-critical track component widely used in ballasted railway tracks. The performance, endurance and quality of prestressed concrete sleepers can detrimentally affect the serviceability and durability of a railway track. An optimal production method is an important criterion underpinning quality and durability over the entire service life of prestressed concrete sleepers. At present, the research work of the sleeper mainly focuses on the dynamic load, bearing capacity and structural design method, etc. However, there exists a lack of research on the specific advantages and disadvantages of the sleeper production process and the improvement of the sleeper process research. This study is the world’s first to collect and analyse the technical data and characteristics of modern production methods of prestressed concrete sleepers, including the long-line system method, pre-tensioned long-mould flow method, pre-tensioned short-mould flow method, post-tensioned short-mould flow method and instant-demoulded short-mould flow method. The precautions for these prestressed concrete sleepers are highlighted in the paper as well. The research results show that the long-line system method, pre-tensioned short-mould flow method, post-tensioned short-mould flow method and instant-demoulded short-mould flow method have a higher automation level and lower efficiency than the pre-tensioned long-mould flow method. The production method of the pre-tensioned long-mould flow method has high efficiency and low cost of equipment, but more workers are needed. Through a comparative analysis, this paper also determines the environmental impacts and provide new references and suggestions for the development and progress of sleeper production technologies

Winter remote sensing images are more suitable for forest mapping in Jiangxi Province

ABSTRACTJiangxi Province boasts the second-highest forest coverage in China. Its forests play a crucial role in providing essential ecosystem services and maintaining the ecological health of the region. High-resolution and high-precision forest mapping are significant in the timely and accurate monitoring of dynamic forest changes to support sustainable forest management. This study used Sentinel-2 images from four seasons in the Google Earth Engine (GEE) platform to map forest distribution. Moreover, the classification results were compared and analyzed using different classification algorithms and feature-variable combinations. Based on the overall accuracy, the optimal image seasonality, feature combinations and classification algorithms were selected, and the forest maps of Jiangxi Province were mapped from 2019 to 2021. The accuracy evaluation showed that the winter image classification results had the highest accuracy (above 0.88). The red edge bands carried by Sentinel-2 could effectively improve the classification accuracy. The Random Forest classifier is the optimal classification algorithm for forest mapping in Jiangxi Province. The forest mapping obtained can be used for ecological health assessment and ecosystem function. The study provides a scientific basis for accurate and timely extraction of forest cover and can serve as a valuable resource for forest management planning and future research

The Typical Damage Form and Mechanism of a Railway Prestressed Concrete Sleeper

Prestressed concrete sleepers are an important track component that is widely used in railway ballast track. Prestressed concrete sleepers have high strength, strong stability, and good durability; thus, their operation and use in railways are beneficial. However, in different countries and regions, certain damage to sleepers typically appears. Existing research on concrete sleepers focuses primarily on the structural design method, the application of new materials, theoretical analysis, and bearing strength test research, while ignoring sleeper damage. There are a few sleeper damage studies, but they look at only one type of damage; thus, there is no comprehensive study of prestressed concrete sleeper damage. The damage forms of prestressed concrete sleeper damage are thus summarized in this study, and the theory of the causes of prestressed concrete sleepers is analyzed based on the limit state method for the first time. The findings indicate that sleeper structure design is the primary cause of its operation and use status, and that special measures should be considered based on sleeper use conditions. In addition to meeting design requirements, materials, curing systems, product inspection, and other factors must be considered during manufacturing to improve the sleepers’ long-term performance. Keeping the track in good condition, including but not limited to the state of fasteners, ballast bed, and track geometry is also an important aspect of preventing sleeper damage. The outcomes of this study provide better insights into the influences of damage to railway prestressed concrete sleepers and can be used to improve track maintenance and inspection criteria

Effect of cumulative radiation exposure from Coronary catheterization on lung cancer mortality

Abstract Background Coronary catheterization (CC) procedure inevitably exposes patients with cardiovascular disease (CVD) to radiation, while cumulative radiation exposure may lead to higher risk of cancer. Methods This multi-center, retrospective study was based on the CC procedure in Cardiorenal ImprovemeNt II cohort (CIN-II, NCT05050877) among five regional central tertiary teaching hospitals in China between 2007 and 2020. Patients without known cancer were stratified according to the times they received CC procedure. Baseline information from their last CC procedure was analyzed. Cox regression and Fine-Gray competing risk models were used to assess the relationship between cumulative radiation exposure from CC procedures and cancer-specific, all-cause and cardiovascular mortality. Results Of 136,495 hospitalized survivors without cancer at baseline (mean age: 62.3 ± 11.1 years, 30.9% female), 116,992 patients (85.7%) underwent CC procedure once, 15,184 patients (11.1%) on twice, and 4,319 patients (3.2%) underwent CC procedure more than three times. During the median follow-up of 4.7 years (IQR: 2.5 to 7.4), totally 18,656 patients (13.7%) died after discharge, of which 617 (0.5%) died of lung cancer. Compared with the patients who underwent CC procedure once, the risk of lung cancer mortality increased significantly with the increase of the number of CC procedure (CC 2 times vs. 1 time: HR 1.42, 95% CI 1.13 to 1.78, P < 0.001; CC ≥ 3 times vs. 1 time: HR 1.64, 95%CI 1.13 to 2.39, P < 0.05). Similar results were observed in all-cause mortality and cardiovascular mortality, but not in other cancer-specific mortality. Conclusions Our data suggest that substantial proportion of CVD patients are exposed to multiple high levels of low-dose ionizing radiation from CC procedure, which is associated with an increased risk of cancer mortality in this population. Trial registration ClinicalTrials.gov: NCT05050877; URL: http://www.clinicaltrials.gov ; 21/09/2021

Non-Fatal Drowning Risk Prediction Based on Stacking Ensemble Algorithm

Drowning is a major public health problem and a leading cause of death in children living in developing countries. We seek better machine learning (ML) algorithms to provide a novel risk-assessment insight on non-fatal drowning prediction. The data on non-fatal drowning were collected in Qingyuan city, Guangdong Province, China. We developed four ML models to predict the non-fatal drowning risk, including a logistic regression model (LR), random forest model (RF), support vector machine model (SVM), and stacking-based model, on three primary learners (LR, RF, SVM). The area under the curve (AUC), F1 value, accuracy, sensitivity, and specificity were calculated to evaluate the predictive ability of the different learning algorithms. This study included a total of 8390 children. Of those, 12.07% (1013) had experienced non-fatal drowning. We found the following risk factors are closely associated with the risk of non-fatal drowning: the frequency of swimming in open water, distance between the school and the surrounding open waters, swimming skills, personality (introvert) and relationality with family members. Compared to the other three base models, the stacking generalization model achieved a superior performance in the non-fatal drowning dataset (AUC = 0.741, sensitivity = 0.625, F1 value = 0.359, accuracy = 0.739 and specificity = 0.754). This study indicates that applying stacking ensemble algorithms in the non-fatal drowning dataset may outperform other ML models