Highly Sensitive and Selective Electrochemical Sensor via Cu-BTC/Au@Cu-BTC Modified Screen-Printed Electrode for the Detection of Chemical Agents by Xiaosen Li (6263651)

“…The peak current showed a good linear relationship with the concentrations of the three target substances, with <i>R</i>² values all greater than 0.99. …”

Data Sheet 1_The CD38+HLA-DR+ T cells with activation and exhaustion characteristics as predictors of severity and mortality in COVID-19 patients.docx by Qiuyue Long (11381148)

“…</p>Results<p>We revealed a significant increase in CD38⁺HLA-DR⁺ T cells in non-survivor COVID-19 patients, establishing them as an independent risk factor for 28-day mortality. …”

<b><i>Original data for "High risk of soil available silicon deficiency in bamboo forest: Insights from bamboo afforestation chronosequences in the karst region of southwest China"... by Kangning Yan (22751487)

“…Furthermore, aboveground Si content decreased significantly from leaves (10.54–21.45 g kg–1) to branches (3.81–5.61 g kg–1) and culms (1.07–1.98 g kg–1). …”

FLEXI interactions with RNA-binding proteins. by Jun Yao (9646)

“…RNA-binding sites: I, within introns corresponding to FLEXIs; SS-I and SS-E, bimodally enriched across the 5’- and 3’ splice sites in unspliced pre-mRNAs with the midpoints in the intron or flanking exon (SS-I and SS-E, respectively; Figs <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1011416#pgen.1011416.g004" target="_blank">4A</a> and <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1011416#pgen.1011416.s011" target="_blank">S11</a>). mRNA levels, RBPs whose knockdown resulted in significant difference in mRNA levels (increased or decreased, DESeq2 |LFC|≥1, adjusted p≤0.05) from host gene of FLEXIs with a binding site for that RBP compared to those genes whose transcripts lacked a binding site for the same RBPs based on ENCODE RBP-knockdown datasets (p≤0.05 calculated by Fisher’s exact test; <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1011416#pgen.1011416.s013" target="_blank">S13 Fig</a>). …”

Data Sheet 1_Rapid reshaping of the soil microbiome and metabolome during short-term flooding and draining in rice.docx by Yanyao Lu (22163632)

“…The TG subclass was consistently present in the lipid correlation networks across all comparison groups, with TG (15:0/18:1/18:1) exhibiting significant differences between the R4 and R1 groups. …”

Table 3_Rapid reshaping of the soil microbiome and metabolome during short-term flooding and draining in rice.xlsx by Yanyao Lu (22163632)

“…The TG subclass was consistently present in the lipid correlation networks across all comparison groups, with TG (15:0/18:1/18:1) exhibiting significant differences between the R4 and R1 groups. …”

Table 2_Rapid reshaping of the soil microbiome and metabolome during short-term flooding and draining in rice.xlsx by Yanyao Lu (22163632)

“…The TG subclass was consistently present in the lipid correlation networks across all comparison groups, with TG (15:0/18:1/18:1) exhibiting significant differences between the R4 and R1 groups. …”

Data Sheet 2_Rapid reshaping of the soil microbiome and metabolome during short-term flooding and draining in rice.docx by Yanyao Lu (22163632)

“…The TG subclass was consistently present in the lipid correlation networks across all comparison groups, with TG (15:0/18:1/18:1) exhibiting significant differences between the R4 and R1 groups. …”

Table 4_Rapid reshaping of the soil microbiome and metabolome during short-term flooding and draining in rice.xlsx by Yanyao Lu (22163632)

“…The TG subclass was consistently present in the lipid correlation networks across all comparison groups, with TG (15:0/18:1/18:1) exhibiting significant differences between the R4 and R1 groups. …”

Table 1_Altered brain functional network connectivity and topology in type 2 diabetes mellitus.doc by Weiwei Ni (9269921)

“…</p>Methods<p>Eighty-five T2DM patients and 67 healthy controls (HCs) were included. All participants underwent clinical, neuropsychological, and laboratory tests, followed by MRI examinations, including resting-state functional magnetic resonance imaging (rs-fMRI) and three-dimensional high-resolution T1-weighted imaging (3D-T1WI) on a 3.0 T MRI scanner. …”

Data Sheet 4_Rapid reshaping of the soil microbiome and metabolome during short-term flooding and draining in rice.docx by Yanyao Lu (22163632)

“…The TG subclass was consistently present in the lipid correlation networks across all comparison groups, with TG (15:0/18:1/18:1) exhibiting significant differences between the R4 and R1 groups. …”

Table 14_Rapid reshaping of the soil microbiome and metabolome during short-term flooding and draining in rice.xlsx by Yanyao Lu (22163632)

“…The TG subclass was consistently present in the lipid correlation networks across all comparison groups, with TG (15:0/18:1/18:1) exhibiting significant differences between the R4 and R1 groups. …”

Table 9_Rapid reshaping of the soil microbiome and metabolome during short-term flooding and draining in rice.docx by Yanyao Lu (22163632)

“…The TG subclass was consistently present in the lipid correlation networks across all comparison groups, with TG (15:0/18:1/18:1) exhibiting significant differences between the R4 and R1 groups. …”

Table 7_Rapid reshaping of the soil microbiome and metabolome during short-term flooding and draining in rice.xlsx by Yanyao Lu (22163632)

“…The TG subclass was consistently present in the lipid correlation networks across all comparison groups, with TG (15:0/18:1/18:1) exhibiting significant differences between the R4 and R1 groups. …”

Table 1_Rapid reshaping of the soil microbiome and metabolome during short-term flooding and draining in rice.xlsx by Yanyao Lu (22163632)

“…The TG subclass was consistently present in the lipid correlation networks across all comparison groups, with TG (15:0/18:1/18:1) exhibiting significant differences between the R4 and R1 groups. …”

Table 8_Rapid reshaping of the soil microbiome and metabolome during short-term flooding and draining in rice.xlsx by Yanyao Lu (22163632)

“…The TG subclass was consistently present in the lipid correlation networks across all comparison groups, with TG (15:0/18:1/18:1) exhibiting significant differences between the R4 and R1 groups. …”

Table 5_Rapid reshaping of the soil microbiome and metabolome during short-term flooding and draining in rice.xlsx by Yanyao Lu (22163632)

“…The TG subclass was consistently present in the lipid correlation networks across all comparison groups, with TG (15:0/18:1/18:1) exhibiting significant differences between the R4 and R1 groups. …”

Data Sheet 5_Rapid reshaping of the soil microbiome and metabolome during short-term flooding and draining in rice.docx by Yanyao Lu (22163632)

“…The TG subclass was consistently present in the lipid correlation networks across all comparison groups, with TG (15:0/18:1/18:1) exhibiting significant differences between the R4 and R1 groups. …”

Table 6_Rapid reshaping of the soil microbiome and metabolome during short-term flooding and draining in rice.xlsx by Yanyao Lu (22163632)

“…The TG subclass was consistently present in the lipid correlation networks across all comparison groups, with TG (15:0/18:1/18:1) exhibiting significant differences between the R4 and R1 groups. …”

Data Sheet 3_Rapid reshaping of the soil microbiome and metabolome during short-term flooding and draining in rice.docx by Yanyao Lu (22163632)

“…The TG subclass was consistently present in the lipid correlation networks across all comparison groups, with TG (15:0/18:1/18:1) exhibiting significant differences between the R4 and R1 groups. …”