Effect of the cannabis extracts on the accumulation of scavenger receptors. by Bruno Musetti (9527085)

Flow cytometry measurement of CD11b, F-actin expression and content, and MHC Class II antigen expression of neutrophils from patients with CGD. by Daniel R. Ambruso (12042605)

<b>Climate warming, rather than nitrogen deposition, reduces plant diversity and increases community homogenization in a desert steppe</b> by Yi Zhu (22625741)

“…<p dir="ltr">It is still unclear how increasing nitrogen (N) deposition, climate warming, and their interaction affect biotic impoverishment (decreases in α-diversity) and homogenization (decreases in β-diversity) of plant communities at taxonomic, functional, and phylogenetic levels. …”

Figure 4 from Impact of Glucocorticoids on Immune Checkpoint Inhibitor Efficacy and Circulating Biomarkers in Non–Small Cell Lung Cancer Patients by Lauren Polyakov (21672045)

Juvenile demyelination induces a loss of functional autapses. by Sara Hijazi (21656615)

“…Cuprizone-treated mice show a significant decrease in the percentage of cells showing an autaptic response (<i>Fisher’s exact test; *p = 0.0173</i>). …”

Comparison between juvenile and adult demyelination. by Sara Hijazi (21656615)

“…Juvenile demyelination leads to impairment in PV interneuron maturation whereas adult demyelination induces a decrease in the excitability of PV interneurons. Summary data showing the averaged (± s.e.m) of the following intrinsic properties: (A) Resting membrane potential (RMP) (<i>ANOVA: n = 36,30,19,24 cells from 9/8/8/6 mice per group, ****p < 0.0001, post-hoc LSD test: *p < 0.05, **p < 0.01, ****p < 0.0001</i>), (B) Input resistance (IR) (<i>ANOVA: n = 36,30,19,24 cells from 9/8/8/6 mice per group, **p = 0.0024, post-hoc LSD test: *p < 0.05, **p < 0.01, ***p < 0.001</i>), (C) Sag (<i>ANOVA: n = 36,30,19,24 cells from 9/8/8/6 mice per group, **p = 0.0083, post-hoc LSD test: *p < 0.05, **p < 0.01</i>), (D) Rheobase (<i>ANOVA: n = 36,30,19,24 cells from 9/8/8/6 mice per group, p = 0.1230, post-hoc LSD test: *p < 0.05</i>) and (E) Action potential (AP) threshold (<i>ANOVA: n = 36,30,19,24 cells from 9/8/8/6 mice per group, *p = 0.0452, post-hoc LSD test: *p < 0.05</i>), (F) AP half-width (<i>ANOVA: n = 36,30,19,24 cells from 9/8/8/6 mice per group, **p = 0.0058, post-hoc LSD test: **p < 0.01</i>), (G) Average action potential (AP) frequency in response to 0–650 pA current steps illustrating no significant change in S1 PV interneuron firing frequency following juvenile demyelination (<i>group x current two-way repeated measures: n = 36,30,19,24 cells from 9/8/8/6 mice per group: F(39,1,291) = 2.487, ****p < 0.0001</i>) and (H) Maximum firing frequency per group (<i>ANOVA: n = 36,30,19,24 cells from 9/8/8/6 mice per group, ****p < 0.0001, post-hoc LSD test: ***p < 0.001, ****p < 0.0001</i>). …”

Multiscale QM/MM Simulations Identify the Roles of Asp239 and 1‑OH···Nucleophile in Transition State Stabilization in Arabidopsis thaliana Cell-Wall Invertase 1 by Wijitra Jitonnom (22410515)

“…The glycosylation and deglycosylation steps were considered in both wild type and mutants. …”

Neutrophil Superoxide anion production, Heat map for gene expression from neutrophils of CGD patients, and PCA plot for genome-wide gene expression. by Daniel R. Ambruso (12042605)

“…Genes that responded to IFN-γ with increased expression are at the bottom and those with decreased expression are at the top. …”

Generated spline library. by Zhe Hu (787283)

“…However, prediction accuracy diminishes for longer time steps as the step length increases. Following model updates with measured data, the accumulated prediction error rapidly decreases. …”

Correlation coefficient matrix. by Zhe Hu (787283)

“…However, prediction accuracy diminishes for longer time steps as the step length increases. Following model updates with measured data, the accumulated prediction error rapidly decreases. …”

Actual measurement of shape errors. by Zhe Hu (787283)

“…However, prediction accuracy diminishes for longer time steps as the step length increases. Following model updates with measured data, the accumulated prediction error rapidly decreases. …”

RMSE versus learning rate. by Zhe Hu (787283)

“…However, prediction accuracy diminishes for longer time steps as the step length increases. Following model updates with measured data, the accumulated prediction error rapidly decreases. …”

RMSE versus training parameters. by Zhe Hu (787283)

“…However, prediction accuracy diminishes for longer time steps as the step length increases. Following model updates with measured data, the accumulated prediction error rapidly decreases. …”

Assembly process of machine recognition form. by Zhe Hu (787283)

“…However, prediction accuracy diminishes for longer time steps as the step length increases. Following model updates with measured data, the accumulated prediction error rapidly decreases. …”

Process of steel truss incremental launching. by Zhe Hu (787283)

“…However, prediction accuracy diminishes for longer time steps as the step length increases. Following model updates with measured data, the accumulated prediction error rapidly decreases. …”

CGAN and AutoML stacking device. by Zhe Hu (787283)

“…However, prediction accuracy diminishes for longer time steps as the step length increases. Following model updates with measured data, the accumulated prediction error rapidly decreases. …”

Comprehensive prediction process of shape errors. by Zhe Hu (787283)

“…However, prediction accuracy diminishes for longer time steps as the step length increases. Following model updates with measured data, the accumulated prediction error rapidly decreases. …”

Shape error manual calculation process. by Zhe Hu (787283)

“…However, prediction accuracy diminishes for longer time steps as the step length increases. Following model updates with measured data, the accumulated prediction error rapidly decreases. …”

U-wave estimates versus R-matrix noise variance. by Zhe Hu (787283)

“…However, prediction accuracy diminishes for longer time steps as the step length increases. Following model updates with measured data, the accumulated prediction error rapidly decreases. …”

Sliding window process. by Zhe Hu (787283)

“…However, prediction accuracy diminishes for longer time steps as the step length increases. Following model updates with measured data, the accumulated prediction error rapidly decreases. …”