Vegetation EVI changes and response to natural factors and human activities based on geographically and temporally weighted regression

The research on vegetation changes plays a crucial role in the assessment of ecosystem health, monitoring environmental changes, providing early warnings for natural disasters, and supporting decision-making for sustainable development. However, understanding the nonstationary characteristics of drivers affecting vegetation change remains challenging. This study used Enhanced Vegetation Index (EVI) data obtained through Google Earth Engine (GEE), Theil-Sen, and Mann-Kendall methods to analyze the spatial-temporal patterns and trends of vegetation changes in Sichuan, western China from 2000 to 2020. The Geographical and Temporal Weighted Regression (GTWR) method was applied to deal with spatial and temporal nonstationarity simultaneously. Results showed that vegetation cover in Sichuan was good overall, with medium and high vegetation covering more than 78% of the area. About 72.75% of the area showed an increasing trend in vegetation cover, and areas with extremely significant and significant EVI growth (p < 0.01 and 0.01 ≤ p < 0.05) accounted for 23.94% of the total area. The areas with significant increases in vegetation EVI were mainly distributed in northeast, east, southeast, central, and southwest in Sichuan, while the areas with significant decreases were mainly distributed in the central Sichuan plain urban agglomeration and western Sichuan plateau. GTWR addressed the nonstationary effect of the temporal dimension on the drivers of natural and human activities, with a fitted R2 of 0.846. The study identified climate, terrain, and human activities as the primary driving factors behind vegetation EVI fluctuations. Annual average temperature and precipitation, human activities, and slope had a positive impact on vegetation EVI changes, while solar radiation and aspect had a negative inhibitory effect. The effects of climate, terrain, and human activities on EVI changes exhibited significant spatial heterogeneity and clustering, resulting in either positive promotion or negative inhibition. This study provides an additional methodology to solve the nonstationary problem of vegetation change trends and their response mechanisms. The revealed changes in vegetation EVI and the spatiotemporal heterogeneity characteristics of their driving factors are important for fragile ecosystems to adapt to and mitigate the effects of natural changes and human activities. Revealing the variations in vegetation EVI and their underlying drivers can showcase diverse characteristics across regions and time periods, the presence of spatiotemporal heterogeneity holds great significance in comprehending the adaptive strategies employed by fragile ecosystems to mitigate the effects of natural fluctuations and human-induced activities

Association between Polymorphisms in the Renin-Angiotensin-Aldosterone System Genes and Essential Hypertension in the Han Chinese Population

<div><p>Background</p><p>Renin-angiotensin-aldosterone system (RAAS) is the most important endocrine blood pressure control mechanism in our body, genes encoding components of this system have been strong candidates for the investigation of the genetic basis of hypertension. However, previous studies mainly focused on limited polymorphisms, thus we carried out a case-control study in the Han Chinese population to systemically investigate the association between polymorphisms in the RAAS genes and essential hypertension.</p><p>Methods</p><p>905 essential hypertensive cases and 905 normotensive controls were recruited based on stringent inclusion and exclusion criteria. All 41 tagSNPs within RAAS genes were retrieved from HapMap, and the genotyping was performed using the GenomeLab SNPstream Genotyping System. Logistic regression analysis, Multifactor dimensionality reduction (MDR), stratified analysis and crossover analysis were used to identify and characterize interactions among the SNPs and the non-genetic factors.</p><p>Results</p><p>Serum levels of total cholesterol (TC) and triglyceride (TG), and body mass index (BMI) were significantly higher in the hypertensive group than in the control group. Of 41 SNPs genotyped, rs3789678 and rs2493132 within <i>AGT</i>, rs4305 within <i>ACE</i>, rs275645 within <i>AGTR1</i>, rs3802230 and rs10086846 within <i>CYP11B2</i> were shown to associate with hypertension. The MDR analysis demonstrated that the interaction between BMI and rs4305 increased the susceptibility to hypertension. Crossover analysis and stratified analysis further indicated that BMI has a major effect, and rs4305 has a minor effect.</p><p>Conclusion</p><p>These novel findings indicated that together with non-genetic factors, these genetic variants in the RAAS may play an important role in determining an individual’s susceptibility to hypertension in the Han Chinese.</p></div

Genotype distributions of those SNPs significantly associated with hypertension.

<p>The <i>P</i> values were obtained from the comparison of two allele frequencies. OR, odds ratio; CI, confidence interval.</p

MDR analysis of gene-environment interaction.

<p>MDR analysis of gene-environment interaction.</p

Logistic regression for genetic and non-genetic factors.

<p>The <i>P</i> values of 6 SNPs were obtained from the comparison of two allele frequencies. BMI, body mass index; TC, total cholesterol; TG, triglyceride.</p>*<p><i>P</i> value was less than 0.05.</p

The risk of clopidogrel resistance is associated with ABCB1 polymorphisms but not promoter methylation in a Chinese Han population.

The goal of our study was to investigate the contribution of ABCB1 expression to the risk of clopidogrel resistance (CR). Platelets functions were measured using the Verify-Now P2Y12 assay. Applying Polymerase Chain Reaction-Restriction Fragment Length Polymorphism (PCR-RFLP), the single-nucleotide polymorphisms (SNPs) was tested. Using bisulphite pyrosequencing assay, we investigated the association of the ABCB1 DNA methylation levels and CR. It was shown that female, hypertension, and lower albumin levels increased the risk of CR (P<0.05). If patients did not have hypoproteinaemia or had hypertension, the SNP in rs1045642 was associated with CR (CC vs. TT: albumin ≥35, P = 0.042; hypertension, P = 0.045; C vs. T: albumin ≥35, P = 0.033; hypertension, P = 0.040). Additionally, the platelet inhibition of the CT+TT genotype in rs1128503 was larger than that of the CC genotype (P = 0.021). Multivariate logistic regression analysis showed that male, higher albumin and hsCRP decreased the risk of CR, and the stent size maybe positively correlated with CR. The SNP in rs1045642 was related to all-cause mortality (P = 0.024). We did not find any relationship between the methylation levels of the ABCB1 promoter and CR. In conclusions, our study indicated that ABCB1 polymorphisms might be useful in further evaluating the pathogenesis of CR