Data Sheet 1_Analysis of endogenous hormones and transcriptomes involved in in vitro shoot apical dormancy during adventitious root formation in tree peony.xlsx by Yujie Yang (2327590)

“…In contrast to previous studies, high levels of abscisic acid (ABA) were not the dominant factor inducing dormancy in in vitro tree peony plantlets. …”

Data Sheet 1_Combined treatment with anti-PSMA antibody and human peripheral blood-derived NK cells for castration-resistant prostate cancer.xlsx by Fangming Wang (2810719)

“…CD16 is abundantly expressed in PB-NK cells. The anti-PSMA Ab significantly enhanced the cytotoxicity of NK cells against CRPC cells in vitro, evidenced by increased killing rate, upregulation of the degranulation marker CD107a, increased secretion of interferon-γ, and decreased PSA levels. …”

Supplementary file 1_The effect of probiotics on the diarrhea and constipation outcomes in children: an umbrella review of systematic reviews and meta-analyses.docx by Qizheng Wang (6440891)

“…Also, it is successful in reducing diarrhea duration [weighted mean difference (WMD) = −1.85; 95% CI: −2.83, −0.86] and [standardized mean difference (SMD) = −0.94; 95% CI: −1.32, −0.56] significantly. …”

Data Sheet 1_Potential geographical distribution of Cordyceps cicadae and its two hosts in China under climate change.docx by Junyi Chen (776323)

“…</p>Results<p>The primary environmental variables were soil pH, mean diurnal range, annual precipitation, precipitation seasonality, annual mean temperature and precipitation of the driest month. …”

Table2_Short-term organic fertilizer substitution increases sorghum yield by improving soil physicochemical characteristics and regulating microbial community structure.xlsx by Mengen Nie (20143902)

“…The effect of organic fertilizer substitution on bacterial diversity was greater than that on fungal diversity. Among the dominant bacterial phyla, the medium ratio of organic substitution treatment significantly increased the relative abundances of Proteobacteria (by 3.57%) and Actinomycetes (by 14.94%), and decreased the relative abundances of Acidobacteria (by 5.18%) and Planctomycetes (by 7.76%) compared with no fertilization, while the dominant fungal phyla did not respond significantly to the addition of organic fertilizer. …”

Table1_Short-term organic fertilizer substitution increases sorghum yield by improving soil physicochemical characteristics and regulating microbial community structure.docx by Mengen Nie (20143902)

“…The effect of organic fertilizer substitution on bacterial diversity was greater than that on fungal diversity. Among the dominant bacterial phyla, the medium ratio of organic substitution treatment significantly increased the relative abundances of Proteobacteria (by 3.57%) and Actinomycetes (by 14.94%), and decreased the relative abundances of Acidobacteria (by 5.18%) and Planctomycetes (by 7.76%) compared with no fertilization, while the dominant fungal phyla did not respond significantly to the addition of organic fertilizer. …”

Table 1_Effects of icariin as a feed additive on the reproductive function in bucks (Capra hircus).docx by Fang-e Zhao (20140809)

“…However, the serum concentration of GnRH in the ICA group initially increased, followed by a subsequent decrease (p < 0.05). The hypothalamic concentrations of dopamine (DA) and 5-hydroxytryptamine (5-HT) were significantly higher in the ICA group compared to the control group (p < 0.01). …”

Image_1_The causal effects of dietary component intake and blood metabolites on risk of delirium: a Mendelian randomization study.pdf by Qian Zhu (191342)

“…Moreover, increased blood 1-stearoylglycerol levels (OR 0.187, 95%CI 0.080–0.435, p = 9.97E-05) significantly contributed to reducing the risks of delirium. 3-methoxytyrosine (OR 0.359, 95%CI 0.154–0.841, p = 0.018) also has the potential to decrease the risk of delirium.…”

Table_1_The causal effects of dietary component intake and blood metabolites on risk of delirium: a Mendelian randomization study.xlsx by Qian Zhu (191342)

“…Moreover, increased blood 1-stearoylglycerol levels (OR 0.187, 95%CI 0.080–0.435, p = 9.97E-05) significantly contributed to reducing the risks of delirium. 3-methoxytyrosine (OR 0.359, 95%CI 0.154–0.841, p = 0.018) also has the potential to decrease the risk of delirium.…”

Data Sheet 1_Effects of icariin as a feed additive on the reproductive function in bucks (Capra hircus).docx by Fang-e Zhao (20140809)

“…However, the serum concentration of GnRH in the ICA group initially increased, followed by a subsequent decrease (p < 0.05). The hypothalamic concentrations of dopamine (DA) and 5-hydroxytryptamine (5-HT) were significantly higher in the ICA group compared to the control group (p < 0.01). …”

NHR-49/80 mediated FEDUS via the peroxisomal activation. by Meiyu Ruan (19929335)

“…Lower population density significantly decreased palmitic acid-induced AWC maturation. …”

<i>Tg</i>ATM1-depleted <i>Toxoplasma</i> are functionally complemented through expression of the <i>Plasmodium</i> or yeast homolog. by Deepti Shrivastava (17715780)

“…The number of significantly increased and decreased proteins is given and the NEET proteins CDGSH1 and CDGSH2 as well as <i>Tg</i>ATM1 are indicated.…”

Table 1_Inverse association between atherogenic index of plasma and testosterone in US adult males: A large cross-sectional study from the NAHNES 2011–2016.xlsx by Tanjian Li (20431610)

“…Serum lipids have been proven to influence serum testosterone levels, and AIP is a significant marker of lipid levels. …”

Image 2_The association between fluid balance trajectories and prognosis in ICU patients with cardiac arrest, a group-based trajectory model analysis.tiff by Qitian Zhang (19791372)

“…Four distinct FB trajectory patterns were identified, Trajectory 1 (rapid transition to negative balance), Trajectory 2 (stable balance), Trajectory 3 (positive balance gradually decreasing), and Trajectory 4 (decreasing at a high level). …”

Table 1_The association between fluid balance trajectories and prognosis in ICU patients with cardiac arrest, a group-based trajectory model analysis.xlsx by Qitian Zhang (19791372)

“…Four distinct FB trajectory patterns were identified, Trajectory 1 (rapid transition to negative balance), Trajectory 2 (stable balance), Trajectory 3 (positive balance gradually decreasing), and Trajectory 4 (decreasing at a high level). …”

Image 1_The association between fluid balance trajectories and prognosis in ICU patients with cardiac arrest, a group-based trajectory model analysis.tiff by Qitian Zhang (19791372)

“…Four distinct FB trajectory patterns were identified, Trajectory 1 (rapid transition to negative balance), Trajectory 2 (stable balance), Trajectory 3 (positive balance gradually decreasing), and Trajectory 4 (decreasing at a high level). …”

Image 4_The association between fluid balance trajectories and prognosis in ICU patients with cardiac arrest, a group-based trajectory model analysis.tiff by Qitian Zhang (19791372)

“…Four distinct FB trajectory patterns were identified, Trajectory 1 (rapid transition to negative balance), Trajectory 2 (stable balance), Trajectory 3 (positive balance gradually decreasing), and Trajectory 4 (decreasing at a high level). …”

Image 5_The association between fluid balance trajectories and prognosis in ICU patients with cardiac arrest, a group-based trajectory model analysis.tif by Qitian Zhang (19791372)

“…Four distinct FB trajectory patterns were identified, Trajectory 1 (rapid transition to negative balance), Trajectory 2 (stable balance), Trajectory 3 (positive balance gradually decreasing), and Trajectory 4 (decreasing at a high level). …”

Image 3_The association between fluid balance trajectories and prognosis in ICU patients with cardiac arrest, a group-based trajectory model analysis.tiff by Qitian Zhang (19791372)

“…Four distinct FB trajectory patterns were identified, Trajectory 1 (rapid transition to negative balance), Trajectory 2 (stable balance), Trajectory 3 (positive balance gradually decreasing), and Trajectory 4 (decreasing at a high level). …”

Supplementary file 2_Quantile regression application to identify key determinants of malnutrition in five West African countries of Gabon, Gambia, Liberia, Mauritania, and Nigeria.... by Reshav Beni (21422981)

“…</p>Method<p>This study employed a quantile regression model to examine the determinants of malnutrition at various quantiles of interest across the Western African countries under consideration to facilitate focused policy measures and intervention strategies aimed at decreasing the prevalence.</p>Results<p>For the lower quantiles (0.1 and 0.25), which indicate severe malnutrition, significant variables included the child’s weight [quantile = 0.1, 95% CI(0.0063, 0.0103), quantile = 0.25, 95% CI(0.0054, 0.0107)], mother’s education level [No education: quantile = 0.1, 95% CI(−49.7471, −32.1376), quantile = 0.25, 95% CI(−38.1513, −22.4438) Primary: quantile = 0.1, 95% CI(−24.8095, −5.7693), quantile = 0.25, 95% CI(−19.5273, −6.3424) Higher: quantile = 0.1, 95% CI(5.6499, 40.3274), quantile = 0.25, 95% CI(21.8158, 40.278)], drinking water source [Natural Sources: quantile = 0.1, 95% CI(0.6877, 24.384),Piped: quantile = 0.1, 95% CI(25.578, 45.2368), quantile = 0.25, 95% CI(22.2782, 34.8212), Bottle/Sachet: quantile = 0.25, 95% CI(3.438, 98.1675)], toilet type [Flush: quantile = 0.25, 95% CI(2.2598, 18.3457),Other: quantile = 0.1, 95% CI(8.7863, 24.504), quantile = 0.25, 95% CI(7.0995, 20.1119)], household wealth index [Poorest: quantile = 0.1, 95% CI(−52.5112, −16.9197), quantile = 0.25, 95% CI(−48.3804, −23.0633),Poorer: quantile = 0.1, 95% CI(−38.8744, −4.7586), quantile = 0.25, 95% CI(−34.6993, −9.1766), Middle: quantile = 0.25, 95% CI(−28.9491, −6.5834)], health care visits [No: quantile = 0.1, 95% CI(−19.293, −3.6393), quantile = 0.25, 95% CI(−17.2342, −5.6411)], consumption of fortified foods and tubers [No: quantile = 0.1, 95% CI(−36.3898, −12.0378), quantile = 0.25, 95% CI(−17.8127, −1.2374)], anemia status [Anemic: quantile = 0.1, 95% CI(−15.9326, −1.1929), quantile = 0.25, 95% CI(−12.3361, −1.5516)], mosquito net usage [No: quantile = 0.1, 95% CI(−22.0323, −0.8033), quantile = 0.25, 95% CI(−13.8107, 1.1366)], child’s age [0 to 12 months: quantile = 0.1, 95% CI(81.6424, 105.7155), quantile = 0.25, 95% CI(61.4817, 78.5194),12 to 24 months: quantile = 0.1, 95% CI(0.5592, 24.933), 24 to 36 months: quantile = 0.1, 95% CI(7.9128, 40.2828)] and gender [Female: quantile = 0.1, 95% CI(4.5351, 17.9783), quantile = 0.25, 95% CI(5.0076, 15.4735)], and recent fever [No: quantile = 0.1, 95% CI(11.5663, 29.5984), quantile = 0.25, 95% CI(7.0313, 20.8918)]. …”