Silencing <i>NbUCHs</i> triggers SGT1-dependent immunity in <i>N. benthamiana.</i> by Wenjia Yu (9422059)

Flow chart of experimental protocol. by Eun-Seon Yang (19751340)

“…SBP showed an increasing trend, but this was not statistically significant (<i>p</i> = 0.108). Interestingly, we observed significant decreases in arterial stiffness and PWV in POST_VM when comparing with PRE_VM (<i>p</i><0.001 and <i>p</i><0.001, respectively). …”

A representative ultrasound axis image. by Eun-Seon Yang (19751340)

“…SBP showed an increasing trend, but this was not statistically significant (<i>p</i> = 0.108). Interestingly, we observed significant decreases in arterial stiffness and PWV in POST_VM when comparing with PRE_VM (<i>p</i><0.001 and <i>p</i><0.001, respectively). …”

RipE1 undergoes phosphorylation in <i>N. benthamiana</i>, which contributes to protein stability. by Wenjia Yu (9422059)

Example of sample data. by Xiying Wang (4859998)

“…In contrast, the EGA-BPNN model achieves a significantly lower mean absolute relative error of 0.41% for single-flow prediction, demonstrating superior prediction performance. …”

Structure of BPNN. by Xiying Wang (4859998)

“…In contrast, the EGA-BPNN model achieves a significantly lower mean absolute relative error of 0.41% for single-flow prediction, demonstrating superior prediction performance. …”

The workflow of EGA-BPNN. by Xiying Wang (4859998)

“…In contrast, the EGA-BPNN model achieves a significantly lower mean absolute relative error of 0.41% for single-flow prediction, demonstrating superior prediction performance. …”

S1 Data - by Xiying Wang (4859998)

“…In contrast, the EGA-BPNN model achieves a significantly lower mean absolute relative error of 0.41% for single-flow prediction, demonstrating superior prediction performance. …”

Algorithm flow of the GA-BPNN model. by Xiying Wang (4859998)

“…In contrast, the EGA-BPNN model achieves a significantly lower mean absolute relative error of 0.41% for single-flow prediction, demonstrating superior prediction performance. …”

Detailed table of two-tailed Pearson correlation analysis results between different phenotypic data tested above and lectin microarray results. by Yiying Zhang (198443)

Detailed table of two-tailed Spearman correlation analysis results between different phenotypic data and lectin microarray results. by Yiying Zhang (198443)

Two-tailed Spearman correlation analysis results between different phenotypic data tested above and lectin microarray results. by Yiying Zhang (198443)

Frequency of underweight among different age groups of women (15–49 years) in the 2019 SLDHS. by Nelson Onira Alema (12394528)

Correlation analysis of lectin microarray data. by Yiying Zhang (198443)

NbUCH positive regulates RipE1 accumulation in <i>N. benthamiana.</i> by Wenjia Yu (9422059)

RipE1 phosphorylation and NbUCH-mediated deubiquitination are independent mechanisms leading to RipE1 stability. by Wenjia Yu (9422059)

NbUCH15 promotes RipE1 stability by deubiquitination. by Wenjia Yu (9422059)

Illustrative images of the quantitative processing of polar maps from a myocardial perfusion study in one of the investigated patients. by Káryta Suely Macêdo Martins (22404155)

Russet Burbank (RB) potato leaves, with functional and mutated metacaspase Stmc7, inoculated with Phytophthora infestans. by Bikram Poudel (15989201)

Flowchart of the study population. by Gábor Szaló (22615130)

“…</p><p>Results</p><p>The mean age of study participants was 57 years and women reported significantly higher stress levels on PSS-10 than men [Women: 13.6 ± 5.6; Men: 12.4 ± 5.3; p < 0.01]. …”