Sentence examples for molecular variables for from inspiring English sources

This study aimed to prospectively evaluate clinical, histopathological and molecular variables for outcome prediction in medulloblastoma patients.

The techniques range from standard ones such as bright field imaging or phase contrast to advanced technologies that enable recording many molecular variables for each resolvable volume unit.

We assessed the prognostic values of clinical and molecular variables for 10 years DEFS using Cox analysis in tamoxifen-treated patients (cohort 1) and tested the assumption of proportional hazards for each model (Table  2).

Yi-Long Yi-Long Wuhe Guangdong Lung Cancer Institute, reviewed their research on three aspects ofromng cancer — molecular variables, surgery for early-sthee non-small cell lunGuangdong Lung Cancer Institutetreviewedr advanced NSCLC — and gave a vision of theirearesearch in China.

All clinical and molecular variables, except for EGFR, were significantly associated with RFS.

This correlation gave basis that the implied molecular variables can become trackers for the calculation of TBARS inhibitory concentrations in similar systems.

For molecular variables, a cutoff value greater than median was defined as 'high mRNA expression' and was considered as a dichotomous categorical variable, compared with the remaining cases, which were defined as 'low mRNA expression'.

Our results suggest that the optimal strategy for chemotherapy sensitivity prediction integrates molecular variables such as ER and HER2 status with corresponding microRNA and mRNA expression profiles.

Current methods for classifying cancer malignancies mostly rely on a variety of morphological, clinical, or molecular variables.

Variables dm and im are the only non-molecular variables; to de ne an ODE for them we assume a constant rate of change from an intact to a damaged membrane when stress conditions prevail, and the rate of membrane repair to be proportional to the number of oligomers in the system.

In conclusion, we have designed effective SVM-based models by combining clinicopathological features and molecular markers as variables for helping select the patients of OSCC with high risk of postoperative distant organ metastasis.