Sentence examples for significant negative interactions from inspiring English sources

Exact(4)

Significant negative interactions between depression and back pain were also observed for hospital and drug costs.

Knockdown of GCLC resulted in significant negative interactions with HgCl2 in SK-N-SH and MeHgCl in HepG2 cells.

For HL and NHL, significant negative interactions with maternal and paternal exposures precluded adjusted analyses (p-values of interaction term, 0.03 for NHL and 0.02 for HL).

Although it is suggestive that downstream knockdowns should suppress upstream knockdowns (Avery and Wasserman 1992; Carter et al. 2012), the majority of pair-wise knockdowns of known Ras genes exhibited significant negative interactions in both directions.

Similar(56)

Analysis of significant negative interaction patterns revealed Helicobacter to be a core node with multiple negative interactions with various genera.

Some hybrids with significant negative interaction heterosis were detected for either of EAC or GLS.

As predicted, the top models (based on AIC, AICc and the marginal R 2) included a large significant negative interaction term between mean wild boar nest density and the smallest saplings size class (Fig. 4a; Supplementary Table 4).

Interestingly, results revealed a significant negative interaction between light and NaCl concentration indicating that high NaCl concentration (40 gL−1) and low light intensity (10 μmol photons m−2s−1) enhanced the EPS production.

This model additionally revealed that the positive effect of item difficulty was smaller among strong test-takers as indicated by the significant negative interaction between item difficulty and cognitive skill.

Hornig et al. (1998) found a significant negative interaction between lithium and CRP within BD patients, while Dickerson et al. (2007) found that no medication affected the CRP association with BD, as we found in the current study.

There was a significant negative interaction between sugary soda consumption and being overweight (p = 0.005) or obese (p = 0.02) and with male gender (p = 0.008), indicating the need for subgroup analyses.

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