Image 2_Dietary risk factors and cancer mortality burden from 1990 to 2021: a comparative study of China and global regions with varying sociodemographic development levels based o... by Chunxiu Zhao (21650204)

“…Red meat’s impact was greater in females, while inadequate plant consumption affected males more significantly. Dietary factors most influenced colorectal cancer in China (39.2%). …”

Image 1_Dietary risk factors and cancer mortality burden from 1990 to 2021: a comparative study of China and global regions with varying sociodemographic development levels based o... by Chunxiu Zhao (21650204)

“…Red meat’s impact was greater in females, while inadequate plant consumption affected males more significantly. Dietary factors most influenced colorectal cancer in China (39.2%). …”

Image 3_Dietary risk factors and cancer mortality burden from 1990 to 2021: a comparative study of China and global regions with varying sociodemographic development levels based o... by Chunxiu Zhao (21650204)

“…Red meat’s impact was greater in females, while inadequate plant consumption affected males more significantly. Dietary factors most influenced colorectal cancer in China (39.2%). …”

Repetitive stress induces a reduction in sound-evoked activity that develops as the stressor becomes chronic. by Ghattas Bisharat (20706928)

Data Sheet 1_Global, regional, and national trends in ischaemic stroke burden and risk factors among adults aged 20 + years (1990–2021): a systematic analysis of data from the Glob... by Sibo Liu (9975065)

“…High systolic blood pressure and high low-density lipoprotein cholesterol (LDL-C) levels consistently represented the most significant risk factors contributing to DALYs from 1990 to 2021.…”

Participant characteristics by village. by Tyler M. Barrett (20846174)

“…While many studies have forecast changes to food production at regional scales, fewer studies have directly assessed the effects of climate change on agricultural communities and the factors that influence climate adaptation at local scales. …”

Figure 2 from Loss of Sorting Nexin 10 Accelerates KRAS-Induced Pancreatic Tumorigenesis by Kohinoor Khan (22206206)

Data Sheet 1_Dietary risk factors and cancer mortality burden from 1990 to 2021: a comparative study of China and global regions with varying sociodemographic development levels ba... by Chunxiu Zhao (21650204)

“…Red meat’s impact was greater in females, while inadequate plant consumption affected males more significantly. Dietary factors most influenced colorectal cancer in China (39.2%). …”

Information on miR-335-3p mimic and inhibitor. by Dong-Hee Han (140305)

“…The progression of fibrosis involves transforming growth factor-beta 1 (TGF-β1), which accelerates ECM production via epithelial–mesenchymal transition and cell invasion. …”

Scatterplot 8. by Chao Yang (174810)

“…When the HAR was lower than 0.13, mortality within 28 days after ICU admission decreased significantly as the HAR increased. When the HAR was higher than 0.13, the HAR was not a protective factor for mortality within 28 days after ICU admission. …”

Scatterplot 5. by Chao Yang (174810)

“…When the HAR was lower than 0.13, mortality within 28 days after ICU admission decreased significantly as the HAR increased. When the HAR was higher than 0.13, the HAR was not a protective factor for mortality within 28 days after ICU admission. …”

Scatterplot 9. by Chao Yang (174810)

“…When the HAR was lower than 0.13, mortality within 28 days after ICU admission decreased significantly as the HAR increased. When the HAR was higher than 0.13, the HAR was not a protective factor for mortality within 28 days after ICU admission. …”

Scatterplot 1. by Chao Yang (174810)

“…When the HAR was lower than 0.13, mortality within 28 days after ICU admission decreased significantly as the HAR increased. When the HAR was higher than 0.13, the HAR was not a protective factor for mortality within 28 days after ICU admission. …”

Scatterplot 6. by Chao Yang (174810)

“…When the HAR was lower than 0.13, mortality within 28 days after ICU admission decreased significantly as the HAR increased. When the HAR was higher than 0.13, the HAR was not a protective factor for mortality within 28 days after ICU admission. …”

Scatterplot 2. by Chao Yang (174810)

“…When the HAR was lower than 0.13, mortality within 28 days after ICU admission decreased significantly as the HAR increased. When the HAR was higher than 0.13, the HAR was not a protective factor for mortality within 28 days after ICU admission. …”

Raw data of this study. by Chao Yang (174810)

“…When the HAR was lower than 0.13, mortality within 28 days after ICU admission decreased significantly as the HAR increased. When the HAR was higher than 0.13, the HAR was not a protective factor for mortality within 28 days after ICU admission. …”

Scatterplot 4. by Chao Yang (174810)

“…When the HAR was lower than 0.13, mortality within 28 days after ICU admission decreased significantly as the HAR increased. When the HAR was higher than 0.13, the HAR was not a protective factor for mortality within 28 days after ICU admission. …”

Scatterplot 3. by Chao Yang (174810)

“…When the HAR was lower than 0.13, mortality within 28 days after ICU admission decreased significantly as the HAR increased. When the HAR was higher than 0.13, the HAR was not a protective factor for mortality within 28 days after ICU admission. …”

Correlation matrix. by Chao Yang (174810)

“…When the HAR was lower than 0.13, mortality within 28 days after ICU admission decreased significantly as the HAR increased. When the HAR was higher than 0.13, the HAR was not a protective factor for mortality within 28 days after ICU admission. …”

Scatterplot 7. by Chao Yang (174810)

“…When the HAR was lower than 0.13, mortality within 28 days after ICU admission decreased significantly as the HAR increased. When the HAR was higher than 0.13, the HAR was not a protective factor for mortality within 28 days after ICU admission. …”