Image 3_The global burden of lead exposure-related ischemic stroke: based on Bayesian age-period-cohort analysis.png by Xiaofang Chen (256976)

“…</p>Results<p>In 2019, lead exposure-related ischemic stroke caused a significant disease burden, with males and middle-aged/older adults disproportionately affected. …”

Image 1_The global burden of lead exposure-related ischemic stroke: based on Bayesian age-period-cohort analysis.png by Xiaofang Chen (256976)

“…</p>Results<p>In 2019, lead exposure-related ischemic stroke caused a significant disease burden, with males and middle-aged/older adults disproportionately affected. …”

Table 1_Oxidative balance score is independently associated with reduced prevalence of sarcopenia among US adults with metabolic syndrome.docx by Miaohong Wang (8975903)

“…Restricted cubic spline analysis confirmed that these relationships were linear. The impact of age was significant, with OBS benefits only observed in those aged 40 and older.…”

Table 1_Microbial diversity and community assembly in heavy metal-contaminated soils: insights from selenium-impacted mining areas.xlsx by Zhiyong Wang (313131)

“…Our results showed that Se and other heavy metal contamination significantly altered microbial community composition, favoring metal-tolerant phyla such as Proteobacteria, Actinobacteriota and Firmicutes, while reducing the abundance of sensitive groups like Acidobacteriota and Chloroflexi. …”

Table 2_Microbial diversity and community assembly in heavy metal-contaminated soils: insights from selenium-impacted mining areas.docx by Zhiyong Wang (313131)

“…Our results showed that Se and other heavy metal contamination significantly altered microbial community composition, favoring metal-tolerant phyla such as Proteobacteria, Actinobacteriota and Firmicutes, while reducing the abundance of sensitive groups like Acidobacteriota and Chloroflexi. …”

Data Sheet 1_Soil microbiome dysbiosis and rhizosphere metabolic dysfunction drive continuous cropping obstacles of Codonopsis tangshen.docx by Dabing Xu (18961138)

“…However, their abundance decreased significantly under continuous cropping, ultimately disrupting soil carbon cycling. …”

Data Sheet 2_Effect of thyme-ivy syrup on antiviral immune response in patients with mild COVID-19: a prospective, open-label, randomized pilot study.docx by Stephanie Dauth (13274397)

“…Significant between-group differences were observed for changes in some parameters at day 4 (e.g., IL-10) and day 14. …”

Data Sheet 1_Effect of thyme-ivy syrup on antiviral immune response in patients with mild COVID-19: a prospective, open-label, randomized pilot study.docx by Stephanie Dauth (13274397)

“…Significant between-group differences were observed for changes in some parameters at day 4 (e.g., IL-10) and day 14. …”

Data Sheet 1_Inverse associations of the lifestyle critical 9 with cardiorenal syndrome: the mediating role of the dietary inflammatory index.xlsx by Hongman Li (19546419)

“…The dose–response curve illustrates a linear relationship between LC9 and CRS; as LC9 increases, the occurrence of CRS decreases. …”

Table 1_Inverse associations of the lifestyle critical 9 with cardiorenal syndrome: the mediating role of the dietary inflammatory index.docx by Hongman Li (19546419)

“…The dose–response curve illustrates a linear relationship between LC9 and CRS; as LC9 increases, the occurrence of CRS decreases. …”

Land use intensity classes standard. by Chao Ma (207385)

“…The habitat quality shows a spatial distribution pattern of “high in the surrounding areas and low in the central areas”, and autocorrelation analysis shows that county-level units have significant spatial agglomeration effects. (iii) The overall type shows an enhancement of dual factor or non-linear, in which land use intensity and population density are the main driving factors for the spatio-temporal evolution of habitat quality. …”

Land use transfer matrix 1990-2020 (km²). by Chao Ma (207385)

“…The habitat quality shows a spatial distribution pattern of “high in the surrounding areas and low in the central areas”, and autocorrelation analysis shows that county-level units have significant spatial agglomeration effects. (iii) The overall type shows an enhancement of dual factor or non-linear, in which land use intensity and population density are the main driving factors for the spatio-temporal evolution of habitat quality. …”

Study area habitat quality LISA clustering map. by Chao Ma (207385)

“…The habitat quality shows a spatial distribution pattern of “high in the surrounding areas and low in the central areas”, and autocorrelation analysis shows that county-level units have significant spatial agglomeration effects. (iii) The overall type shows an enhancement of dual factor or non-linear, in which land use intensity and population density are the main driving factors for the spatio-temporal evolution of habitat quality. …”

Spato-temporal changes in land use types. by Chao Ma (207385)

“…The habitat quality shows a spatial distribution pattern of “high in the surrounding areas and low in the central areas”, and autocorrelation analysis shows that county-level units have significant spatial agglomeration effects. (iii) The overall type shows an enhancement of dual factor or non-linear, in which land use intensity and population density are the main driving factors for the spatio-temporal evolution of habitat quality. …”

Pattern indices of landscape levels. by Chao Ma (207385)

“…The habitat quality shows a spatial distribution pattern of “high in the surrounding areas and low in the central areas”, and autocorrelation analysis shows that county-level units have significant spatial agglomeration effects. (iii) The overall type shows an enhancement of dual factor or non-linear, in which land use intensity and population density are the main driving factors for the spatio-temporal evolution of habitat quality. …”

Type level landscape index changes in 1990-2020. by Chao Ma (207385)

“…The habitat quality shows a spatial distribution pattern of “high in the surrounding areas and low in the central areas”, and autocorrelation analysis shows that county-level units have significant spatial agglomeration effects. (iii) The overall type shows an enhancement of dual factor or non-linear, in which land use intensity and population density are the main driving factors for the spatio-temporal evolution of habitat quality. …”

The role of IRF-1 in mediating T-cell immune imbalance in systemic lupus erythematosus and the construction of a diagnostic model by Zichen Huang (6587885)

“…Immune analysis revealed decreased numbers of resting CD4⁺ memory T cells and Tregs (<i>P</i> < 0.01), alongside expanded proinflammatory cells (M1/M2 macrophages, neutrophils; <i>P</i> < 0.01). …”

Location map of the study area. by Chao Ma (207385)

“…The habitat quality shows a spatial distribution pattern of “high in the surrounding areas and low in the central areas”, and autocorrelation analysis shows that county-level units have significant spatial agglomeration effects. (iii) The overall type shows an enhancement of dual factor or non-linear, in which land use intensity and population density are the main driving factors for the spatio-temporal evolution of habitat quality. …”

Data source. by Chao Ma (207385)

“…The habitat quality shows a spatial distribution pattern of “high in the surrounding areas and low in the central areas”, and autocorrelation analysis shows that county-level units have significant spatial agglomeration effects. (iii) The overall type shows an enhancement of dual factor or non-linear, in which land use intensity and population density are the main driving factors for the spatio-temporal evolution of habitat quality. …”

Research Technology Flow Chart. by Chao Ma (207385)

“…The habitat quality shows a spatial distribution pattern of “high in the surrounding areas and low in the central areas”, and autocorrelation analysis shows that county-level units have significant spatial agglomeration effects. (iii) The overall type shows an enhancement of dual factor or non-linear, in which land use intensity and population density are the main driving factors for the spatio-temporal evolution of habitat quality. …”