Genetic and immunological insights into COVID-19 with acute myocardial infarction: Integrated analysis of mendelian randomization, transcriptomics, and clinical samples

Background: Globally, most deaths result from cardiovascular diseases, particularly ischemic heart disease. COVID-19 affects the heart, worsening existing heart conditions and causing myocardial injury. The mechanistic link between COVID-19 and acute myocardial infarction (AMI) is still being investigated to elucidate the underlying molecular perspectives. Methods: Genetic risk assessment was conducted using two-sample Mendelian randomization (TSMR) to determine the causality between COVID-19 and AMI. Weighted gene co-expression network analysis (WGCNA) and machine learning were used to discover and validate shared hub genes for the two diseases using bulk RNA sequencing (RNA-seq) datasets. Additionally, gene set enrichment analysis (GSEA) and single-cell RNA-seq (scRNA-seq) analyses were performed to characterize immune cell infiltration, communication, and immune correlation of the hub genes. To validate the findings, the expression patterns of hub genes were confirmed in clinical blood samples collected from COVID-19 patients with AMI. Results: TSMR did not find evidence supporting a causal association between COVID-19 or severe COVID-19 and AMI. In the bulk RNA-seq discovery cohorts for both COVID-19 and AMI, WGCNA’s intersection analysis and machine learning identified TLR4 and ABCA1 as significant hub genes, demonstrating high diagnostic and predictive value in the RNA-seq validation cohort. Single-gene GSEA and single-sample GSEA (ssGSEA) revealed immune and inflammatory roles for TLR4 and ABCA1, linked to various immune cell infiltrations. Furthermore, scRNA-seq analysis unveiled significant immune dysregulation in COVID-19 patients, characterized by altered immune cell proportions, phenotypic shifts, enhanced cell-cell communication, and elevated TLR4 and ABCA1 in CD16 monocytes. Lastly, the increased expression of TLR4, but not ABCA1, was validated in clinical blood samples from COVID-19 patients with AMI. Conclusion: No genetic causal link between COVID-19 and AMI and dysregulated TLR4 and ABCA1 may be responsible for the development of immune and inflammatory responses in COVID-19 patients with AMI

Seismic imaging of a mid-crustal low-velocity layer beneath the northern coast of the South China Sea and its tectonic implications

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Genetic and immunological insights into COVID-19 with acute myocardial infarction: integrated analysis of mendelian randomization, transcriptomics, and clinical samples

BackgroundGlobally, most deaths result from cardiovascular diseases, particularly ischemic heart disease. COVID-19 affects the heart, worsening existing heart conditions and causing myocardial injury. The mechanistic link between COVID-19 and acute myocardial infarction (AMI) is still being investigated to elucidate the underlying molecular perspectives.MethodsGenetic risk assessment was conducted using two-sample Mendelian randomization (TSMR) to determine the causality between COVID-19 and AMI. Weighted gene co-expression network analysis (WGCNA) and machine learning were used to discover and validate shared hub genes for the two diseases using bulk RNA sequencing (RNA-seq) datasets. Additionally, gene set enrichment analysis (GSEA) and single-cell RNA-seq (scRNA-seq) analyses were performed to characterize immune cell infiltration, communication, and immune correlation of the hub genes. To validate the findings, the expression patterns of hub genes were confirmed in clinical blood samples collected from COVID-19 patients with AMI.ResultsTSMR did not find evidence supporting a causal association between COVID-19 or severe COVID-19 and AMI. In the bulk RNA-seq discovery cohorts for both COVID-19 and AMI, WGCNA’s intersection analysis and machine learning identified TLR4 and ABCA1 as significant hub genes, demonstrating high diagnostic and predictive value in the RNA-seq validation cohort. Single-gene GSEA and single-sample GSEA (ssGSEA) revealed immune and inflammatory roles for TLR4 and ABCA1, linked to various immune cell infiltrations. Furthermore, scRNA-seq analysis unveiled significant immune dysregulation in COVID-19 patients, characterized by altered immune cell proportions, phenotypic shifts, enhanced cell-cell communication, and elevated TLR4 and ABCA1 in CD16 monocytes. Lastly, the increased expression of TLR4, but not ABCA1, was validated in clinical blood samples from COVID-19 patients with AMI.ConclusionNo genetic causal link between COVID-19 and AMI and dysregulated TLR4 and ABCA1 may be responsible for the development of immune and inflammatory responses in COVID-19 patients with AMI

Showcase of Active Learning and Teaching Practices in Spatial Data Infrastructure (SDI) Education

The new concept of Open Spatial Data Infrastructures (Open SDIs) has emerged from an increased interest in open data initiatives together with national and international directives, such as the EU Open Data Directive (Directive (EU) 2019/1024), and the large investment of European public authorities in developing SDIs for sharing spatial data within public authorities. Open SDIs have the potential to boost reaching SDIs’ general aims and goals of facilitating the exchange and sharing of spatial data to support planning and decision-making by including public participation and increased openness in all aspects of SDIs, including Open SDI Education. The open SPatial data Infrastructure eDucation nEtwoRk (SPIDER) project aims to address Open SDI Education by particular emphasis on studying Active Learning and Teaching (ALT) methods for SDI education. This article provides a theoretical basis of ALT for SDI methodologies. We show in which way ALT practices were already implemented in SDI education at the Partner universities before the COVID-19 pandemic. We also describe how the pandemic functioned as a catalyst for implementing ALT practices to an online environment, and how students evaluated these practices. The outcomes of our research can serve as an inspiration for SDI education in other countries

Effects of Poultry, Rabbit Meat and Fish Addition on Quality Attributes of Sichuan Sausages

To balance the nutrition and improve quality of sausages. This research investigated quality improvements of Sichuan sausages by 41.5% poultry, rabbit meat and fish addition. The moisture, crude fat, crude protein contents, pH, Aw, colour, texture, TBARS, protein carbonyl, free thiol groups, fatty acids composition and sensory attributes of pork, poultry, rabbit meat and fish mixture group sausages were evaluated. The results showed that the hardness of pork and rabbit meat mixture group sausages (76.37, 68.01 kg) was significant (P<0.05) higher than that of other 2 groups. The TBARS values in poultry meat and fish mixture group sausages (0.60, 0.63 mg MDA/kg) were significant (P<0.05) higher than that of rabbit meat mixture group. Only EPA and DHA were detected in fish mixture sausages. The ∑poly unsaturated fatty acids (19.96%) and ∑n-6:∑n-3 (22) in poultry meat mixture group sausages were significant (P<0.05) higher than that of other 3 groups. The overall quality scores of poultry and rabbit meat mixture group sausages (7.33, 7.05 points) were significant (P<0.05) higher than those of fish mixture groups. The results of this study indicated that the rabbit meat mixture group sausages had improved quality attributes, the yield rate management and application of liquid fat (vegetable and fish oil) addition could improve nutrition value of Sichuan sausages in the future work. The fish mixture group sausages had better fatty acids composition, and a slightly higher fat oxidation level, thus the application of antioxidates and de-fishy substances could be added in fish-based sausages to control fat oxidation and improve whole sausage quality and sensory attributes

Short sleep time may be the main reason for irregular breakfast to cause overweight—a cross-sectional study

IntroductionIn recent years, the relationship between circadian rhythm and overweight and obesity has attracted the attention of many scholars.MethodsTo evaluate association between the duration of sleep and the regularity of breakfast and overweight. A total of 1,178 students from Qingdao University were selected by stratified cluster sampling. There were 601 males (24.69 ± 0.80 years old) and 569 females (24.54 ± 0.70 years old). We used body mass index (BMI), waist circumference (WC), and waist-to-hip ratio (WHR) to define overweight levels. Chi-square test, Pearson correlation test, and logistic regression were applied to test association among overweight, sleep duration, sleep onset time, and breakfast regularity. Pittsburgh sleep quality index was used to assess the overall sleep quality of the study subjects. Mediation effect and Sobel test were used to analyze the effect of sleep duration on breakfast regularity and overweight.ResultsOnly 34.1% of the population ate breakfast every day, and eating breakfast 1–3 times per week was associated with a higher risk of overweight (BMI: OR = 2.183, 95%CI: 1.369,3,481; WC: OR = 2.101, 95%CI: 1.232,3,583; WHR: OR = 2.108, 95%CI: 1.331,3,337). The effects of all types of Usual Breakfast Consumption Frequency on overweight were fully mediated by sleep duration (p &lt; 0.05). In particular, the subjects exercised outdoors more than five times per week slept longer (p &lt; 0.05).ConclusionShort sleep duration may be the main reason for irregular breakfast leading to overweight. Adequate outdoor exercise is essential for weight maintenance

PARP9 affects myocardial function through TGF-β/Smad axis and pirfenidone

Cardiac arrhythmias are often linked to the overactivity of cardiac fibroblasts (CFs). Investigating the impact of poly (ADP-ribose) polymerase 9 (PARP9) on Angiotensin II (Ang II)-induced fibroblast activation and the therapeutic effects of pirfenidone (PFD) offers valuable insights into cardiac arrhythmias. This study utilized weighted gene co-expression network analysis (WGCNA), differential gene expression (DEG) analysis, protein-protein interaction (PPI), and receiver operating characteristic (ROC) analysis on the GSE42955 dataset to identify the hub gene with significant diagnostic value. The ImmuCellAI tool revealed an association between PARP9 and immune cell infiltration. Our in vitro assessments focused on the influence of PFD on myofibroblast differentiation, TGF-β expression, and Ang II-induced proliferation and migration in CFs. Additionally, we explored the impact on fibrosis markers and the TGF-β/Smad signaling pathway in the context of PARP9 overexpression. Analysis of the GSE42955 dataset revealed PARP9 as a central gene with high clinical diagnostic value, linked to seven types of immune cells. The in vitro studies demonstrated that PFD significantly mitigates Ang II-induced CF proliferation, migration, and fibrosis. It also reduces Ang II-induced PARP9 expression and decreases fibrosis markers, including TGF-β, collagen I, collagen III, and α-SMA. Notably, PARP9 overexpression can partially counteract PFD's inhibitory effects on CFs and modify the expression of fibronectin, CTGF, α-SMA, collagen I, collagen III, MMP2, MMP9, TGF-β, and p-Smad2/3 in the TGF-β/Smad signaling pathway. In summary, our findings suggestes that PFD effectively counteracts the adverse effects of Ang II-induced CF proliferation and fibrosis, and modulates the TGF-β/Smad signaling pathway and PARP9 expression. This identifies a potential therapeutic approach for managing myocardial fibrosis

Detecting One-Hundred-Year Environmental Changes in Western China Using Seven-Year Repeat Photography

Due to its diverse, wondrous plants and unique topography, Western China has drawn great attention from explorers and naturalists from the Western World. Among them, Ernest Henry Wilson (1876 –1930), known as ‘Chinese’ Wilson, travelled to Western China five times from 1899 to 1918. He took more than 1,000 photos during his travels. These valuable photos illustrated the natural and social environment of Western China a century ago. Since 1997, we had collected E.H. Wilson's old pictures, and then since 2004, along the expedition route of E.H. Wilson, we took 7 years to repeat photographing 250 of these old pictures. Comparing Wilson's photos with ours, we found an obvious warming trend over the 100 years, not only in specific areas but throughout the entire Western China. Such warming trend manifested in phenology changes, community shifts and melting snow in alpine mountains. In this study, we also noted remarkable vegetation changes. Out of 62 picture pairs were related to vegetation change, 39 indicated vegetation has changed to the better condition, 17 for degraded vegetation and six for no obvious change. Also in these photos at a century interval, we found not only rapid urbanization in Western China, but also the disappearance of traditional cultures. Through such comparisons, we should not only be amazed about the significant environmental changes through time in Western China, but also consider its implications for protecting environment while meeting the economic development beyond such changes

Simulating Water and Pollution Exports from Soil to Stream during the Thawing Period at the Small River Basin Scale

A physical model was developed to describe the soil-to-stream export processes of water and pollutants in a small river basin during the soil thawing period. The hydrological and pollution transport and transformation behaviors in paddy- and corn-dominated catchments were numerically simulated; the impacts of the pollution concentrations, interactions between the migrated water and pollutants in the soil, and pollutant transformations during the pollution export were coupled. Experimental field data from the Heidingzi river basin during the soil thawing period were used to calibrate the model parameters and evaluate the performance. The mass of the dissolved pollutants from soil particles in the migrated soil pore water was the key factor affecting the pollution export into the streams; the water content directly affected the pollution export. The concentration of the pollutants peaked when the initial exported water was high. The pollutant transport processes influenced the pollution export more significantly after the soil water was significantly reduced. The N-S efficiency coefficients between the simulated and monitored flow rates and the pollution concentrations at the outlets of the paddy- and corn-dominated catchments were >0.60 and >0.54, respectively. The system deviations between the simulated and monitored flow rates and the pollution concentrations were <10% and <15%, respectively. The proposed model effectively described the water flow, pollution transport and transformation processes