MicroRNA-613 (miR-613) plays important roles in tumorigenesis and cancer progression. We aimed to evaluate its expression level and potential for diagnosis and prognosis in esophageal squamous cell cancer (ESCC). We examined miR-613 expression in 60 pairs of ESCC cancerous and matched paracancerous tissues, serum samples from 75 ESCC patients and 75 healthy volunteers, and 105 formalin-fixed paraffin-embedded (FFPE) tissue samples using quantitative reverse transcription polymerase chain reaction. Receiver-operating characteristic (ROC) curve analysis, Kaplan-Meier method, and Cox regression were applied to analyze its diagnostic and prognostic value. MiR-613 was significantly decreased in ESCC tissue compared with paracancerous tissue (P < 0.001). Moreover, the expression level of miR-613 was significantly reduced with increased T stage of ESCC. Statistically significant difference between ESCC patients and healthy controls in expression level of miR-613 (0.89 ± 0.73 vs. 1.71 ± 1.03, P < 0.001) was found. The area under the ROC curve (AUC) based on serum miR-613 was 0.767 ± 0.040. We also performed analysis on early-stage patients and revealed that the AUC value was 0.728 ± 0.052 (P < 0.001). The Kaplan-Meier curve revealed that the downregulation of miR-613 was related to worse overall survival (OS) and progression-free survival (PFS) of ESCC patients (P = 0.018 and P = 0.035, respectively). Furthermore, the multivariate analysis identified miR-613 to be an independent prognostic factor for OS and PFS (P = 0.031 and P = 0.006, respectively) In conclusion, miR-613 is significantly reduced in cancerous tissue and serum samples of ESCC patients. It can serve as an ideal indicator for the diagnosis and prognosis of ESCC.

No abstract

No abstract

Soft robotic manipulators have been created and investigated for a number of applications due to their advantages over rigid robots. In minimally invasive surgery, for instance, soft robots have successfully demonstrated a number of benefits due to the compliant and flexible nature of the material they are made of. However, these type of robots struggle with performing tasks that require on-demand stiffness i.e. exerting higher forces to the surrounding environment. A number of semi-active and active mechanisms have been investigated to change and control the stiffness of soft robotic manipulators. Embedding these mechanisms in soft manipulators for spacerestricted applications can be challenging though.To better understand the inherent passive stiffness properties of soft manipulators, we propose a screw theory-based stiffness analysis for fluidic-driven continuum soft robotic manipulators. First, we derive the forward kinematics based on a parameterbased piece-wise constant curvature model. It is worth noting, our stiffness analysis can be conducted based on any freespace forward kinematic model. Then our stiffness analysis and mapping methodology is conducted based on screw theory. Initial results of our approach demonstrate the feasibility comparing computational and experimental data.

No abstract