Data Sheet 1_Reconstructing Holocene centennial cooling events: synthesized temperature changes, chronology, and forcing in the Northern Hemisphere.docx by Sergey A. Gorbarenko (13696381)

“…The Holocene Thermal Maximum (HTM) happened between HCCEs 5 and 4a and was interrupted by HCCE 4c and 4b, coeval, with a significant southward shift of the ITCZ, likely related to cooling in the tropical zone. …”

3D Nanoscale Structures of Hydrated Polyamide Desalination Membranes Revealed by Cryogenic Transmission Electron Microscopy Tomography by Chenhao Yao (1569328)

“…Our findings reveal significant morphological differences between hydrated and dry membranes, resulting in variations in key structural parameters that impact performance. …”

Image 1_Association between controlling nutritional status score and mortality in older patients with dysphagia in Japan: a retrospective cohort study.tif by Yan Wang (15435)

“…Median survival durations decreased progressively: 716 days (mild), 362 days (moderate), and 106 days (severe). …”

3D Nanoscale Structures of Hydrated Polyamide Desalination Membranes Revealed by Cryogenic Transmission Electron Microscopy Tomography by Chenhao Yao (1569328)

“…Our findings reveal significant morphological differences between hydrated and dry membranes, resulting in variations in key structural parameters that impact performance. …”

Correlation analyses between studied genes. by Marwa A. Ali (11973086)

“…There was also an increase in <i>IL6</i> levels. There is a negative correlation between <i>NEAT-1</i> and <i>IL6</i> in COVID-19 patients.…”

Primers used in q-PCR. by Marwa A. Ali (11973086)

“…There was also an increase in <i>IL6</i> levels. There is a negative correlation between <i>NEAT-1</i> and <i>IL6</i> in COVID-19 patients.…”

Appendices. by Tingting Cui (564531)

“…The factors within the Park attributes (G1) and the park’s social media level (G4) showed a two-way interaction strength increase. (4)The coefficients of influence of impact factors on the space heterogeneity of vacation park vitality exhibit significant variation. …”

Temporal change in average visitor vitality. by Tingting Cui (564531)

“…The factors within the Park attributes (G1) and the park’s social media level (G4) showed a two-way interaction strength increase. (4)The coefficients of influence of impact factors on the space heterogeneity of vacation park vitality exhibit significant variation. …”

Data source. by Tingting Cui (564531)

“…The factors within the Park attributes (G1) and the park’s social media level (G4) showed a two-way interaction strength increase. (4)The coefficients of influence of impact factors on the space heterogeneity of vacation park vitality exhibit significant variation. …”

Data Sheet 1_Association of oxidative balance score with all-cause and cardiovascular mortality among patients with cardio-renal-metabolic disease.docx by Yucui Lin (21598376)

“…Moreover, Higher OBS quartiles were linked to a decreased risk of cardiovascular mortality, while no significant reduction was observed in the lower quartiles [model 3: Q2, Q3, Q4: aHR (95CI%) = 0.96(0.77–1.19), 0.78 (0.63–0.97), 0.70 (0.53–0.93), respectively; P for trend = 0.003]. …”

Baidu heat map average. by Tingting Cui (564531)

“…The factors within the Park attributes (G1) and the park’s social media level (G4) showed a two-way interaction strength increase. (4)The coefficients of influence of impact factors on the space heterogeneity of vacation park vitality exhibit significant variation. …”

Causal associations between gut <i>Bifidobacteriaceae</i> and transplant failure: a Mendelian randomization study by Han Yan (126662)

“…</p> <p>Mendelian randomization studies have shown that a lower abundance of Bifidobacteriaceae in the gut could increase the risk of transplant failure.</p>…”

Overview of the study area. by Tingting Cui (564531)

“…The factors within the Park attributes (G1) and the park’s social media level (G4) showed a two-way interaction strength increase. (4)The coefficients of influence of impact factors on the space heterogeneity of vacation park vitality exhibit significant variation. …”

Single factor detection results. by Tingting Cui (564531)

“…The factors within the Park attributes (G1) and the park’s social media level (G4) showed a two-way interaction strength increase. (4)The coefficients of influence of impact factors on the space heterogeneity of vacation park vitality exhibit significant variation. …”

Impact of mobility in a three-region system with heterogeneous epidemic conditions. by Mousumi Roy (8869412)

“…From left to right, we consider the scenarios with decreasing outgoing mobility and increasing non-commuting population. …”

Research frameworks. by Tingting Cui (564531)

“…The factors within the Park attributes (G1) and the park’s social media level (G4) showed a two-way interaction strength increase. (4)The coefficients of influence of impact factors on the space heterogeneity of vacation park vitality exhibit significant variation. …”

Model index comparison. by Tingting Cui (564531)

“…The factors within the Park attributes (G1) and the park’s social media level (G4) showed a two-way interaction strength increase. (4)The coefficients of influence of impact factors on the space heterogeneity of vacation park vitality exhibit significant variation. …”

Sound evoked cortical activity across vigilance states before and after NOE. by Linus Milinski (10532121)

“…Asterisks for panels <b>E-F</b> represent statistical significance p values *<0.05, **<0.01, ***<0.001 (GLMM). …”

Table2_Unveiling the molecular landscape of PCOS: identifying hub genes and causal relationships through bioinformatics and Mendelian randomization.xlsx by Yifang He (18126257)

“…</p>Conclusions<p>Our bioinformatics combined with MR analysis revealed that CD93, CYBB, DOCK8, IRF1, MBOAT1, MYO1F, NLRP1, NOD2, PIK3R1 increase the risk of PCOS, while PTER decreases the risk of PCOS. …”

Table13_Unveiling the molecular landscape of PCOS: identifying hub genes and causal relationships through bioinformatics and Mendelian randomization.xlsx by Yifang He (18126257)

“…</p>Conclusions<p>Our bioinformatics combined with MR analysis revealed that CD93, CYBB, DOCK8, IRF1, MBOAT1, MYO1F, NLRP1, NOD2, PIK3R1 increase the risk of PCOS, while PTER decreases the risk of PCOS. …”