(a) Mycelial diameter (mm) determination on PDA plates, (b) Inhibition diameters, and (c) inhibition percentages of <i>Aspergillus flavus</i> treated with <i>U. epigea</i> extract... by Martha Cebile Jobe (21175426)

E₅₀ values. by Junxia Zhou (14381598)

The PRAME-AS knockout cells showed a decrease in migration, proliferation, stemness, and viability. by Zahra Hosseininia (22265113)

Localized schematic of ball valves with different openings (a) 25%; (b) 50%; (c) 75%; (d) 100%. by Weiqing Xu (1279959)

Distribution of hydrogen volume fraction at different openings (a) 25%; (b) 50%; (c) 75%; (d) 100%. by Weiqing Xu (1279959)

Repeated LSPC treatment prolongs survival of and decreases PrP^Res accumulation in a subset of prion-infected mice. by Heather Bender (363996)

Phosphorylation as an Effective Tool to Improve Stability and Reduce Toxicity of Antimicrobial Peptides by Zufang Ba (11036420)

“…Phosphorylation can reduce toxicity and improve the stability of AMPs. Based on these, we designed a series of peptides and their corresponding phosphorylated forms. …”

Population dynamics modeling of split^50cM <i>ClvR</i> V1 introduced at a 50% release, with fitness cost per allele varying from 0–15%. by Georg Oberhofer (3401438)

The fraction of predicted heterozygotes that are set to “No Call” by RHA decreases as the size of the heterozygote cluster increases. by Orna Mizrahi-Man (42539)

The introduction of mutualisms into assembled communities increases their connectance and complexity while decreasing their richness. by Gui Araujo (22170819)

“…(D) As a result, the introduction of mutualistic interactions promotes a growth in complexity in communities where it was once established as low, while stopping the introduction of further mutualistic interactions causes a slight decrease in complexity. …”

Crosslinking decreases the alignment of fibers associated with individual cells migrating out of spheroids. by Michael Pamonag (12295175)

KDM6A mRNA expression is decreased in PTFE mice. by Simon Lebek (9756148)

Predictions of random forests (RF), gradient boosting machines (GBM), and neural networks (NN) trained on 12 covariates chosen using subjective feature selection. by Dennis Ochola (11626912)

Predictions of random forests (RF), gradient boosting machines (GBM), and neural networks (NN) trained on 17 covariates selected after recursive feature selection. by Dennis Ochola (11626912)

The numerical values underlying Fig 4. by Wataru Matsunaga (3452621)

Subjects:

E₅₀ values of angle. by Junxia Zhou (14381598)

Curve fitting of E₅₀. by Junxia Zhou (14381598)

Fitting curves of E₅₀. by Junxia Zhou (14381598)

E₅₀ values of size. by Junxia Zhou (14381598)

E₅₀ fluctuation coefficient. by Junxia Zhou (14381598)