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. …”

Table 1_Probabilistic human health risk assessment of commercially supplied jar water in Gopalganj municipal area, Bangladesh.docx by Partha Pratim Brahma (19696279)

“…<p>Every day, the amount of quality fresh water decreases notably due to contamination of drinking water. …”

Impairing lipolysis in <i>An</i>. <i>gambiae</i> females induces severe embryonic lethality. by Maurice A. Itoe (9930475)

“…(F, G) Injection of dsAg<i>LSD</i>1 (F) significantly reduces the number of eggs laid and (G) severely decreases survival rates (Mann–Whitney test). …”

Species removal dampens the scale dependency of ecological determinism and stochasticity in rocky intertidal communities [dataset and codes] by Nelson Valdivia (600515)

“…The normalised stochasticity ratio (NST), which distinguishes between stochastic (>50%) and deterministic (<50%) community dynamics, decreased with spatial extent for sessile and mobile species, with consistently lower values under foundation species removal for sessile communities. …”

Modulation of renal inflammation and tubular injury by calcitriol in patients with early diabetic kidney disease: a randomized controlled trial by Pringgodigdo Nugroho (15460802)

“…Although UACR decreased more in the calcitriol group, the difference was not statistically significant (<i>p</i> = 0.099). …”

Additional file 2 of Evobrutinib mitigates neuroinflammation after ischemic stroke by targeting M1 microglial polarization via the TLR4/Myd88/NF-κB pathway by Yixiang Jiang (2580220)

“…Mean±SEM, n=5, one-way ANOVA, vs sham: * P < 0.05; MCAO vs Evobrutinib, ### P< 0.001,ns: no significance.…”

Results for the EPIC bowel subscale and the EORTC QLQ PR25 bowel symptoms scale. by John N. Staffurth (20636565)

“…This is also reflected in the mean and median QoL scores (w.r.t. the right-hand axis), which decreased in magnitude with time also.…”

Table 2_Drug-induced urinary retention: a real-world pharmacovigilance study using FDA and Canada vigilance databases.xlsx by Xianyu Dai (18939514)

“…The top 50 drugs were analyzed for annual reporting trends using linear regression. Disproportionality analysis using the reporting odds ratio (ROR) method, with P-values adjusted via Bonferroni correction, identified significant signals, which were then validated against drug labels and re-evaluated using the CVAR database. …”

Table 1_Immune checkpoint proteins are associated with persistently high liver stiffness after successful HCV treatment in people with HIV: a retrospective study.docx by Rubén Martín-Escolano (17411991)

“…Although LSM values showed a decreasing trend over the years following successful HCV treatment, this trend was not statistically significant due to substantial variability among PWH. …”

Table 1_Drug-induced urinary retention: a real-world pharmacovigilance study using FDA and Canada vigilance databases.docx by Xianyu Dai (18939514)

“…The top 50 drugs were analyzed for annual reporting trends using linear regression. Disproportionality analysis using the reporting odds ratio (ROR) method, with P-values adjusted via Bonferroni correction, identified significant signals, which were then validated against drug labels and re-evaluated using the CVAR database. …”