Table 1_Association between body composition in early pregnancy and the risk of gestational diabetes mellitus.docx by Yan Li (23143)

“…RCS analysis indicated that the risk of GDM continuously increased with higher levels of PBF and FM, whereas it decreased with FFM and LM (p-overall < 0.001, p-non-linear range: 0.073–0.924). …”

Supplementary file 1_The effect of development on cortical auditory evoked potentials in normal hearing listeners and cochlear implant users.docx by Eun Kyung Jeon (2032222)

“…</p>Results<p>Both onset and ACC responses were present across groups, with P1 latency decreasing significantly with age in NH and CI listeners. …”

Table 1_Association between DASH diet and metabolic syndrome in US adults: a cross-sectional study.xlsx by Jianing Liu (140090)

“…Subsequently, we discovered that DASH levels are significantly negatively correlated with waist circumference (WC), fasting plasma glucose (FPG), triglycerides (TG), and systolic blood pressure (SBP), while exhibiting a positive correlation with high-density lipoprotein cholesterol (HDL-C) through RCS curves and linear regression.…”

Table 1_Interaction between dietary selenium intake and age on severe headache or migraine in the United States: a population-based study.docx by Xinping Yu (555177)

“…</p>Conclusion<p>A higher dietary selenium intake is significantly associated with a decreased prevalence of migraine, and age can modify the association between them. …”

Table 2_Association between DASH diet and metabolic syndrome in US adults: a cross-sectional study.xlsx by Jianing Liu (140090)

“…Subsequently, we discovered that DASH levels are significantly negatively correlated with waist circumference (WC), fasting plasma glucose (FPG), triglycerides (TG), and systolic blood pressure (SBP), while exhibiting a positive correlation with high-density lipoprotein cholesterol (HDL-C) through RCS curves and linear regression.…”

Table 1_Metabolites mediate the effects of healthy lifestyles on the risks of common age-related diseases.xlsx by Yan Li (23143)

“…Furthermore, intermediate or healthy lifestyles significantly decreased the age-related risk of stroke, chronic liver disease, chronic kidney disease (CKD), osteoporosis, osteoarthritis, and hypertension. …”

Supplementary file 1_Metabolites mediate the effects of healthy lifestyles on the risks of common age-related diseases.docx by Yan Li (23143)

“…Furthermore, intermediate or healthy lifestyles significantly decreased the age-related risk of stroke, chronic liver disease, chronic kidney disease (CKD), osteoporosis, osteoarthritis, and hypertension. …”

Image 1_Interaction between dietary selenium intake and age on severe headache or migraine in the United States: a population-based study.pdf by Xinping Yu (555177)

“…</p>Conclusion<p>A higher dietary selenium intake is significantly associated with a decreased prevalence of migraine, and age can modify the association between them. …”

Table 1_Ultrasonographic assessment of optic nerve sheath diameter on the affected and unaffected sides as a predictor of clinical deterioration at discharge in patients with large... by Changlan Li (704841)

“…A positive linear correlation was identified between ONSD values and discharge outcomes. …”

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. …”

Table 1_Association between composite dietary antioxidant index and increased urinary albumin excretion: a population-based study.docx by Shaopeng Li (820947)

“…Higher CDAI scores were inversely related to ACR (OR: 0.99, 95% CI: 0.97–1.00), with a significant interaction effect by BMI (p = 0.0048). …”

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)

“…Six machine learning models were trained and validated in four independent cohorts. scRNA-seq revealed significant downregulation of IRF-1 in T-cell subsets (central memory CD8⁺, Th17) during active SLE, with compensatory overexpression in remission—validated clinically. …”

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. …”