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Prolonged ventricular repolarization has been associated with cardiovascular disease. We sought to investigate the association of prolonged ventricular repolarization with mild cognitive impairment (MCI) and the potential underlying neuropathological mechanisms in older adults. This cross-sectional study included 4328 dementia-free participants (age ≥ 65 years; 56.8% female) in the baseline examination of the Multidomain INterventions to delay dementia and Disability in rural China; of these, 989 undertook structural brain magnetic resonance imaging (MRI) scans. QT, QTc, JT, JTc, and QRS intervals were derived from 12-lead electrocardiograph. MCI, amnestic MCI (aMCI), and non-amnestic MCI (naMCI) were defined following the Petersen's criteria. Volumes of gray matter (GM), white matter, cerebrospinal fluid, total white matter hyperintensities (WMH), periventricular WMH (PWMH), and deep WMH (DWMH) were automatically estimated. Data were analyzed using logistic and general linear regression models. Prolonged QT, QTc, JT, and JTc intervals were significantly associated with an increased likelihood of MCI and aMCI, but not naMCI (p < 0.05). In the MRI subsample, QT, QTc, JT, and JTc intervals were significantly associated with larger total WMH and PWMH volumes (p < 0.05), but not with DWMH volume. Statistical interactions were detected, such that prolonged QT and JT intervals were significantly associated with reduced GM volume only among participants with coronary heart disease or without APOE ε4 allele (p < 0.05). Prolonged ventricular repolarization is associated with MCI and cerebral microvascular lesions in a general population of older adults. This underlies the importance of cognitive assessments and brain MRI examination among older adults with prolonged QT interval. [ABSTRACT FROM AUTHOR]

High-quality development plays a crucial role in China’s economic progress in the new era. It represents a new concept of advancement and mirrors the increasing aspirations of the populace for an improved standard of living. In this context, the role of artificial intelligence (AI) in promoting sustainable development cannot be overemphasized. This paper explores how AI technologies can drive the transition to a green, low-carbon and circular economy. We have established an index system to measure the development level of the artificial intelligence industry and the high-quality development of the economy, which is relevant to the current state of the artificial intelligence industry and the advancement of the economy. Panel data from 2008 to 2017 has been utilized for this purpose. Global principal component analysis method and entropy value method are employed in the evaluation. Through in-depth analysis of the application of artificial intelligence and environmental protection in various provinces and cities, we clarify that artificial intelligence promotes innovation, saves resources, and is conducive to the development of green economy in the new era. [ABSTRACT FROM AUTHOR]

Guangxi, China, is one of the world's largest karst regions where potential toxic elements tend to accumulate, resulting in high soil background values. This study explores the ecological risk, elemental baseline values, and sources of potential toxic elements in karst regions, expanding the research to include 21 common elements. The significance of this research lies in its implications for the management of potential toxic element pollution, the formulation of environmental quality standards, and soil remediation in karst areas. In this study, 12,547 topsoil samples (0–20 cm) were collected in the study area. Pollution assessment and ecological risk evaluation of eight potential toxic elements (Zn, Ni, Cu, Pb, Cd, Hg, Cr, and As) were conducted using the geo-accumulation index method and potential ecological risk index method. Multivariate statistical analysis was applied to analyze the total content of 21 common elements (Zn, Ni, Cu, Pb, P, Cd, Hg, Co, Mn, Cr, V, I, S, As, pH, Se, N, CaO, Corg, Mo, and F). Additionally, the potential sources of 21 soil elements were preliminarily quantitatively analyzed using the principal component analysis-absolute principal component scores-multiple linear regression receptor model. The results showed that (1) Zn, Ni, Cu, Pb, Cd, Cr, V, and As were enriched in the research area and Ca, Cd, Mn, Mo, Hg, As, and Cu might have been influenced by human activities; (2) Cr, Pb, As, and Zn were generally lightly polluted, with Hg having a moderate potential ecological risk level; and (3) Ni and Zn have contributions of 37.99% and 35.07% from geological sources, agricultural fertilization, and pesticides. Mo, V, Cr, Se, Hg, and As exhibit contributions ranging from 39.44 to 59.22% originating from geological backgrounds and human activities. Corg, S, N, and P show contributions of 45.39% to 80.33% from surface vegetation. F, Co, Mn, and Pb have contributions ranging from 31.63 to 47.93% from acidic rocks in the soil parent material, mining activities, and transportation. Cd and CaO derive 31.67% and 40.23%, respectively, from soil parent material and industrial sources. I has 31.94% from geological background and human activities, and 31.95% from soil parent material and atmospheric sources. Cu has 30.56% from geological sources. The study results can serve as a scientific basis for element research in karst areas domestically and internationally. [ABSTRACT FROM AUTHOR]

Cardiomyocytes derived from human induced pluripotent stem cells (hiPSC-CMs) possess tremendous potential for basic research and translational application. However, these cells structurally and functionally resemble fetal cardiomyocytes, which is a major limitation of these cells. Microgravity can significantly alter cell behavior and function. Here we investigated the effect of simulated microgravity on hiPSC-CM maturation. Following culture under simulated microgravity in a random positioning machine for 7 days, 3D hiPSC-CMs had increased mitochondrial content as detected by a mitochondrial protein and mitochondrial DNA to nuclear DNA ratio. The cells also had increased mitochondrial membrane potential. Consistently, simulated microgravity increased mitochondrial respiration in 3D hiPSC-CMs, as indicated by higher levels of maximal respiration and ATP content, suggesting improved metabolic maturation in simulated microgravity cultures compared with cultures under normal gravity. Cells from simulated microgravity cultures also had improved Ca2+ transient parameters, a functional characteristic of more mature cardiomyocytes. In addition, these cells had improved structural properties associated with more mature cardiomyocytes, including increased sarcomere length, z-disc length, nuclear diameter, and nuclear eccentricity. These findings indicate that microgravity enhances the maturation of hiPSC-CMs at the structural, metabolic, and functional levels. [ABSTRACT FROM AUTHOR]

This document is a correction notice for an article titled "The influence of AI on the economic growth of different regions in China" published in Scientific Reports. The correction addresses an incomplete funding section in the original article and provides the correct information. The research is funded by the China Scholarship Council, the local innovation sub-project of the Western Project of the Sichuan Provincial, and supported by the Sichuan Provincial Science Foundation Project. The original article has been corrected. The authors of the article are Shuang Lin, Minke Wang, Chongyi Jing, Shengda Zhang, Jiuhao Chen, and Rui Liu. [Extracted from the article]

Coagulation alterations manifest early after severe burns and are closely linked to mortality outcomes. Nevertheless, the precise characterization of coagulation changes associated with early mortality remains elusive. We examined alterations in indicators linked to mortality outcomes at both the transcriptomic and clinical characteristic levels. At the transcriptomic level, we pinpointed 28 differentially expressed coagulation-related genes (DECRGs) following burn injuries and endeavored to validate their causal relationships through Mendelian randomization. DECRGs tied to survival exhibit a significant association with neutrophil function, wherein the expression of CYP4F2 and P2RX1 serves as robust predictors of fatal outcomes. In terms of clinical indicators, early levels of D-dimer and alterations in serum calcium show a strong correlation with mortality outcomes. Coagulation depletion and fibrinolytic activation, stemming from the hyperactivation of coagulation pathways post-severe burns, are strongly linked to patient mortality. Monitoring these early coagulation markers with predictive value can effectively identify individuals necessitating priority critical care., (© 2024. The Author(s).)

Colorectal cancer (CRC) is one of the most prevalent and deadliest illnesses all around the world. Growing proofs demonstrate that tumor-associated macrophages (TAMs) are of critical importance in CRC pathogenesis, but their mechanisms remain yet unknown. The current research was designed to recognize underlying biomarkers associated with TAMs in CRC. We screened macrophage-related gene modules through WGCNA, selected hub genes utilizing the LASSO algorithm and COX regression, and established a model. External validation was performed by expression analysis using datasets GSE14333, GSE74602, and GSE87211. After validating the bioinformatics results using real-time quantitative reverse transcription PCR, we identified SPP1, C5AR1, MMP3, TIMP1, ADAM8 as potential biomarkers associated with macrophages in CRC., (© 2024. The Author(s).)

Pneumonia is a highly lethal disease, and research on its treatment and early screening tools has received extensive attention from researchers. Due to the maturity and cost reduction of chest X-ray technology, and with the development of artificial intelligence technology, pneumonia identification based on deep learning and chest X-ray has attracted attention from all over the world. Although the feature extraction capability of deep learning is strong, existing deep learning object detection frameworks are based on pre-defined anchors, which require a lot of tuning and experience to guarantee their excellent results in the face of new applications or data. To avoid the influence of anchor settings in pneumonia detection, this paper proposes an anchor-free object detection framework and RSNA dataset based on pneumonia detection. First, a data enhancement scheme is used to preprocess the chest X-ray images; second, an anchor-free object detection framework is used for pneumonia detection, which contains a feature pyramid, two-branch detection head, and focal loss. The average precision of 51.5 obtained by Intersection over Union (IoU) calculation shows that the pneumonia detection results obtained in this paper can surpass the existing classical object detection framework, providing an idea for future research and exploration., (© 2024. The Author(s).)