Number of shared and specific OTUs of endophytic bacterial communities according to the type of plant tissue (A), the three phenotypic groups (B: leaves, C: roots) and the two habi... by Rabiath F. R. Adigoun (14189090)

Distribution of final population size (A) and mean change in mean MSI over time (B) over 100 simulations for each parameter set shown in Table 3 in the absence of weevils (left) an... by Alexandra M. Campbell (3284094)

Comparison of W_max (A), the changes in V_E (B), and W_VT (C) among the three oxygen conditions. by Kazufumi Hisamoto (21416905)

S3 File - by Zi-Yun Yi (19859589)

“…The GV oocytes displayed increased mitochondrial DNA (mtDNA) copy number and a significant transient increase in inner mitochondrial membrane potential (Δψm) from the TSD mice probably due to compensatory effect. …”

S2 File - by Zi-Yun Yi (19859589)

“…The GV oocytes displayed increased mitochondrial DNA (mtDNA) copy number and a significant transient increase in inner mitochondrial membrane potential (Δψm) from the TSD mice probably due to compensatory effect. …”

Scheme of the SiTFarm tool–farm to sector level. by Jure Brečko (20314959)

“…At the sector level, the gross margin decreased by 12% in 2020 but increased by 99% in 2022 compared to the reference year 2018, highlighting the incredible price volatility over a short period. …”

S1 File - by Jure Brečko (20314959)

“…At the sector level, the gross margin decreased by 12% in 2020 but increased by 99% in 2022 compared to the reference year 2018, highlighting the incredible price volatility over a short period. …”

GHG emissions in TAHs. by Jure Brečko (20314959)

“…At the sector level, the gross margin decreased by 12% in 2020 but increased by 99% in 2022 compared to the reference year 2018, highlighting the incredible price volatility over a short period. …”

A set of 5 criteria for the needs of multi-criteria evaluation–combination A. by Roman Vavrek (13200141)

Multi-organ differential gene expression changes statistically significant at hypertension onset. by Eden Hornung (20148295)

“…<i>Tgfb1</i> is significantly decreased in male SHR kidney compared to female at 16 weeks of age (p = 0.004). …”

Model vs. WKY group KEGG pathways (Top 15). by Xiao Zhang (152326)

“…</p><p>Results</p><p>From Day 1–5, compared with the WKY group, both the Model and SHR groups exhibited shortened incubation periods and slower average swimming speeds (<i><i>P</i></i> < 0.01); On day 6, compared with the WKY group, the Model group showed a significant decrease in the number of platform crossings (<i><i>P</i></i> < 0.05), time spent in the target quadrant (<i><i>P</i></i> < 0.05), and total distance traveled in the target quadrant (<i><i>P</i></i> < 0.05). …”

Behavioral data. by Xiao Zhang (152326)

“…</p><p>Results</p><p>From Day 1–5, compared with the WKY group, both the Model and SHR groups exhibited shortened incubation periods and slower average swimming speeds (<i><i>P</i></i> < 0.01); On day 6, compared with the WKY group, the Model group showed a significant decrease in the number of platform crossings (<i><i>P</i></i> < 0.05), time spent in the target quadrant (<i><i>P</i></i> < 0.05), and total distance traveled in the target quadrant (<i><i>P</i></i> < 0.05). …”

OPLS-DA model parameter. by Xiao Zhang (152326)

“…</p><p>Results</p><p>From Day 1–5, compared with the WKY group, both the Model and SHR groups exhibited shortened incubation periods and slower average swimming speeds (<i><i>P</i></i> < 0.01); On day 6, compared with the WKY group, the Model group showed a significant decrease in the number of platform crossings (<i><i>P</i></i> < 0.05), time spent in the target quadrant (<i><i>P</i></i> < 0.05), and total distance traveled in the target quadrant (<i><i>P</i></i> < 0.05). …”

Model vs. SHR group KEGG pathways (Top 15). by Xiao Zhang (152326)

“…</p><p>Results</p><p>From Day 1–5, compared with the WKY group, both the Model and SHR groups exhibited shortened incubation periods and slower average swimming speeds (<i><i>P</i></i> < 0.01); On day 6, compared with the WKY group, the Model group showed a significant decrease in the number of platform crossings (<i><i>P</i></i> < 0.05), time spent in the target quadrant (<i><i>P</i></i> < 0.05), and total distance traveled in the target quadrant (<i><i>P</i></i> < 0.05). …”

Receiver operating characteristic curve analyses for the prediction of hepatitis C. by Lu Han (151620)

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Exploring the correlation between systemic inflammation biomarkers and HCV infection (logarithm base 2). by Lu Han (151620)

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Threshold effect analysis of systemic inflammatory biomarkers on hepatitis C using two-piece wise linear regression. by Lu Han (151620)

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Demographic information and baseline population characteristics. by Lu Han (151620)

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Stratified associations between systemic inflammation biomarkers and hepatitis C (OR 95%, <i>P</i> value, LOG base 2). by Lu Han (151620)

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General addictive models demonstrate the relationship between systemic inflammatory biomarkers and anti-HCV. by Lu Han (151620)

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