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Background Colorectal cancer (CRC) patients with different molecular phenotypes, including microsatellite instability (MSI), CpG island methylator phenotype (CIMP), and somatic mutations in BRAF and KRAS gene, vary in treatment response and prognosis. However, molecular phenotyping under adequate quality control in a community-based setting may be difficult. We aimed to build the nomograms based on easily accessible clinicopathological characteristics to predict molecular phenotypes. Methods Three hundred and six patients with pathologically confirmed stage I-IV CRC were included in the cohort. The assays for MSI, CIMP, and mutations in BRAF and KRAS gene were performed using resected tumor samples. The candidate predictors were identified from clinicopathological variables using multivariate Logistic regression analyses to construct the nomograms that could predict each molecular phenotype. Results The incidences of MSI, CIMP, BRAF mutation and KRAS mutation were 25.3% (72/285), 2.5% (7/270), 3.4% (10/293), and 34.8% (96/276) respectively. In the multivariate Logistic analysis, poor differentiation and high neutrophil/lymphocyte ratio (NLR) were independently associated with MSI; poor differentiation, high NLR and high carcinoembryonic antigen/tumor size ratio (CSR) were independently associated with CIMP; poor differentiation, lymphovascular invasion and high CSR were independently associated with BRAF mutation; poor differentiation, proximal tumor, mucinous tumor and high NLR were independently associated with KRAS mutation. Four nomograms for MSI, CIMP, BRAF mutation and KRAS mutation were developed based on these independent predictors, the C-indexes of which were 61.22% (95% CI: 60.28-62.16%), 95.57% (95% CI: 95.20-95.94%), 83.56% (95% CI: 81.54-85.58%), and 69.12% (95% CI: 68.30-69.94%) respectively. Conclusion We established four nomograms using easily accessible variables that could well predict the presence of MSI, CIMP, BRAF mutation and KRAS mutation in CRC patients. more...

We investigate a simple model for motor pattern generation that combines central pattern generator (CPG) dynamics with a sensory feedback (FB) mechanism. Our CPG comprises a half-center oscillator with conductance-based Morris-Lecar model neurons. Output from the CPG drives a push-pull motor system with biomechanics based on experimental data. A sensory feedback conductance from the muscles allows modulation of the CPG activity. We consider parameters under which the isolated CPG system has either "escape" or "release" dynamics, and we study both inhibitory and excitatory feedback conductances. We find that increasing the FB conductance relative to the CPG conductance makes the system more robust against external perturbations, but more susceptible to internal noise. Conversely, increasing the CPG conductance relative to the FB conductance has the opposite effects. We find that the "closed-loop" system, with sensory feedback in place, exhibits a richer repertoire of behaviors than the "open-loop" system, with motion determined entirely by the CPG dynamics. Moreover, we find that purely feedback-driven motor patterns, analogous to a chain reflex, occur only in the inhibition-mediated system. Finally, for pattern generation systems with inhibition-mediated sensory feedback, we find that the distinction between escape- and release-mediated CPG mechanisms is diminished in the presence of internal noise. Our observations support an anti-reductionist view of neuromotor physiology: Understanding mechanisms of robust motor control requires studying not only the central pattern generator circuit in isolation, but the intact closed-loop system as a whole. more...