SDG decreases iron-induced oxidative stress in H9c2 cells. by Stephanie Puukila (568109)

EC50 and percentage decrease in intracellular <i>Listeria</i> viability for effective compounds. by Marie-Eve Charbonneau (5658799)

Fitting curve of rock E₅₀. by Junxia Zhou (14381598)

Classification trees distinguishing whether de-escalation decreases (blue) or increases (green) the probability of death. by Josie Hughes (3738055)

“…<p>The first number at each node is the probability that de-escalation decreases the probability of death, followed by the percentage of simulations included at that node. 10-fold cross validation classification error was 25% and 11% in the (a) non-pseudomonal and (b) ciprofloxacin scenarios, respectively. …”

Variable importance plot (mean decrease accuracy and mean decrease Gini). by Fernando Martinez-Taboada (8655132)

Distribution Coefficients of the REEs, Sr, Y, Ba, Th, and U between α‑HIBA and AG50W-X8 Resin by Haoyu Li (1672648)

“…For all 19 elements, the distribution coefficients decrease with increasing acid concentration. For the REEs, a linear relationship is observed in log–log space between <i>K</i>_d values and α-HIBA molarity. …”

Decreased echinocandin susceptibility in <i>Candida parapsilosis</i> causing candidemia and emergence of a pan-echinocandin resistant case in China by Yating Ning (11264310)

<i>P. brasiliensis</i>-infected mice treated with CFA present remarkable decrease of fungal burden and increase of cytokines production. by Leandro Licursi de Oliveira (374413)

S1 File - by Chantelle M. de Vet (16535257)

“…The student’s RV-GLS consistency was poor during the first 25 measurements, moderate-to good during the second 25 measurements and again poor-to-moderate during the final 50 measurements. Repeated measurements analysis showed a significant decrease in variability of the LV- and RV-GLS score differences between the expert and trainees over time (<i>p</i>_adj<0.001), which was not significantly different between trainees. …”

Analysis of correlation of RV-GLS over consecutive quartiles of 25 measurements. by Chantelle M. de Vet (16535257)

Analysis of correlation of LV-GLS over consecutive quartiles of 25 measurements. by Chantelle M. de Vet (16535257)

LV-GLS agreement analysis between expert and trainees over consecutive quartiles of 25 measurements. by Chantelle M. de Vet (16535257)

GLS analysis with 2D-STE software. by Chantelle M. de Vet (16535257)

“…The student’s RV-GLS consistency was poor during the first 25 measurements, moderate-to good during the second 25 measurements and again poor-to-moderate during the final 50 measurements. Repeated measurements analysis showed a significant decrease in variability of the LV- and RV-GLS score differences between the expert and trainees over time (<i>p</i>_adj<0.001), which was not significantly different between trainees. …”

Standard deviation of the difference between the LV-GLS value of the expert and trainees in four consecutive groups of 25 fetal heart clips. by Chantelle M. de Vet (16535257)

RV-GLS agreement analysis between expert and novice trainees over consecutive quartiles of 25 measurements. by Chantelle M. de Vet (16535257)

Standard deviation of the difference between the RV-GLS value of the expert and trainees in four consecutive groups of 25 fetal heart clips. by Chantelle M. de Vet (16535257)

ICC of each trainee RV-GLS value compared with the expert in four consecutive groups of 25 fetal heart clips. by Chantelle M. de Vet (16535257)

ICC of each trainee LV-GLS value compared with the expert in four consecutive groups of 25 fetal heart clips. by Chantelle M. de Vet (16535257)

Mean of the difference between the RV-GLS value of the expert and trainees in four consecutive groups of 25 fetal heart clips. by Chantelle M. de Vet (16535257)

Mean of the difference between the LV-GLS value of the expert and trainees in four consecutive groups of 25 fetal heart clips. by Chantelle M. de Vet (16535257)