Expression of transcription factor, fast-twitch fiber, and slow-twitch fiber genes following acute or chronic stimulation. by Michael A. Petrie (677819)

“…MYH6 (6.76±2.50, p = 0.030), MYH7 (11.69±4.93, p = 0.025), MYL2 (2.78±0.80, p = 0.063), and MYL3 (9.07±3.75, p = 0.046) were increased after >1 year of muscle training, while they were decreased 3 hours after single session of muscle stimulation (0.81±0.04, p = 0.0073, 0.77±0.073, p = 0.030, 0.92±0.036, p = 0.066, 0.76±0.078, p = 0.037; respectively) (I, J, K, and L). † indicates a p-value <0.05 for a within group paired t-test. ‡ indicates a p-value <0.10 for a within group paired t-test.…”

A proposed model illustrates the dynamic and profound interaction of host polyamine biosynthesis and eIF5A hypusination with KSHV infection. by Guillaume N. Fiches (9300348)

“…At the early stage of lytic switch, KSHV ORF50/RTA gene starts to be actively transcribed upon certain stimuli, and the constant high level of hypusine-eIF5A ensures the efficient translation of RTA protein and overall promotes KSHV lytic reactivation. …”

Data_Sheet_1_A five domains assessment of sow welfare in a novel free farrowing system.zip by Kate Plush (19369684)

“…MR 0.5 ± 0.29 events, p = 0.038, and back leg forward: FC 227 ± 50.7 vs. MR 127 ± 26.4 events, p = 0.019), and a decreased proportion of MR sows had facial injuries after farrowing (10% CI [5, 20] vs. 67% CI [47, 95], p < 0.001). …”

Data_Sheet_1_A five domains assessment of sow welfare in a novel free farrowing system.zip by Kate Plush (19369684)

“…MR 0.5 ± 0.29 events, p = 0.038, and back leg forward: FC 227 ± 50.7 vs. MR 127 ± 26.4 events, p = 0.019), and a decreased proportion of MR sows had facial injuries after farrowing (10% CI [5, 20] vs. 67% CI [47, 95], p < 0.001). …”

Knowledge and acceptance of COVID-19 vaccine. by Adaobi Uchenna Mosanya (20384248)

“…The modal age range was 18–24 years accounting for 814 (71.2%) of the participants. A total of 577 (50.5%) participants demonstrated a good level of knowledge while 685 (59.9%) showed a positive perception of the COVID-19 vaccine. …”

Logistics regression COVID-19 vaccine predictors. by Adaobi Uchenna Mosanya (20384248)

“…The modal age range was 18–24 years accounting for 814 (71.2%) of the participants. A total of 577 (50.5%) participants demonstrated a good level of knowledge while 685 (59.9%) showed a positive perception of the COVID-19 vaccine. …”

Perception towards COVID-19 vaccine. by Adaobi Uchenna Mosanya (20384248)

“…The modal age range was 18–24 years accounting for 814 (71.2%) of the participants. A total of 577 (50.5%) participants demonstrated a good level of knowledge while 685 (59.9%) showed a positive perception of the COVID-19 vaccine. …”

The level of knowledge of the COVID-19 vaccine. by Adaobi Uchenna Mosanya (20384248)

“…The modal age range was 18–24 years accounting for 814 (71.2%) of the participants. A total of 577 (50.5%) participants demonstrated a good level of knowledge while 685 (59.9%) showed a positive perception of the COVID-19 vaccine. …”

S1 Data - by Ghada R. Sallam (18319994)

“…However, the increase in density led to a significant decrease in the accumulation of heavy metals in both water and fish organs. …”

Developmental potential of mouse SCC transferred oocytes in vitro. by Xiaoyu Liao (8161995)

Minidysferlin do not improve muscle histology. A by William Lostal (162211)

“…<b>D</b>/Quantification of CNF in muscles of <i>Dysf ^prmd</i> mice that expressed an equivalent level of minidysferlin than dysferlin in normal muscle and 6 times this dose. No decrease in the number of CNF was seen with the dose giving a level of minidysferlin equivalent to the dysferlin expression (x=1) whereas an important increase in seen with the dose leading to a 6-fold increase of expression (x=6). …”

PmrAB-dependent lipid A modification. by Michael Knopp (3814009)

“…The top 50 proteins with the most significant change in abundance (lowest p-value) in the <i>pmrA</i> mutant are shown. …”

Exploring the Interaction Chemistry of Ammonia with <i>n</i>‑Hexadecane over Wide Pressure Ranges: An Experimental and Kinetic Modeling Study by Yongxiang Zhang (31421)

“…In this investigation, the ignition delay times (IDTs) of NH₃/<i>n</i>C₁₆H₃₄ mixtures were measured in a rapid compression machine at different NH₃ energy ratios (50%, 70%, and 90%), temperatures of 693–1047 K, pressures of 20–60 bar, and equivalence ratios of 0.5–1.0. …”

Exploring the Interaction Chemistry of Ammonia with <i>n</i>‑Hexadecane over Wide Pressure Ranges: An Experimental and Kinetic Modeling Study by Yongxiang Zhang (31421)

“…In this investigation, the ignition delay times (IDTs) of NH₃/<i>n</i>C₁₆H₃₄ mixtures were measured in a rapid compression machine at different NH₃ energy ratios (50%, 70%, and 90%), temperatures of 693–1047 K, pressures of 20–60 bar, and equivalence ratios of 0.5–1.0. …”

Exploring the Interaction Chemistry of Ammonia with <i>n</i>‑Hexadecane over Wide Pressure Ranges: An Experimental and Kinetic Modeling Study by Yongxiang Zhang (31421)

“…In this investigation, the ignition delay times (IDTs) of NH₃/<i>n</i>C₁₆H₃₄ mixtures were measured in a rapid compression machine at different NH₃ energy ratios (50%, 70%, and 90%), temperatures of 693–1047 K, pressures of 20–60 bar, and equivalence ratios of 0.5–1.0. …”

MtDNA carryover removal and SCC integraty by MRR manipulation in mouse oocytes. by Xiaoyu Liao (8161995)

Exploring the Interaction Chemistry of Ammonia with <i>n</i>‑Hexadecane over Wide Pressure Ranges: An Experimental and Kinetic Modeling Study by Yongxiang Zhang (31421)

“…In this investigation, the ignition delay times (IDTs) of NH₃/<i>n</i>C₁₆H₃₄ mixtures were measured in a rapid compression machine at different NH₃ energy ratios (50%, 70%, and 90%), temperatures of 693–1047 K, pressures of 20–60 bar, and equivalence ratios of 0.5–1.0. …”

Paeameter ranges and optimal values. by Zhen Zhao (159931)

“…To address these issues, a population spatialization model that integrates feature selection with an improved random forest is proposed herein. …”

Improved random forest algorithm. by Zhen Zhao (159931)

“…To address these issues, a population spatialization model that integrates feature selection with an improved random forest is proposed herein. …”

Datasets used in the study area. by Zhen Zhao (159931)

“…To address these issues, a population spatialization model that integrates feature selection with an improved random forest is proposed herein. …”