A New Self-Loading Locomotion Mechanism for Wall Climbing Robots Employing Biomimetic Adhesives

A versatile locomotion mechanism is introduced and experimentally verified. This mechanism comprises four rectangular wheels (legs) with rotational phase difference which enables the application of pressure to each contacting surface for securing it to the surface using bio-inspired or pressure-sensitive adhesives. In this mechanism, the adhesives are applied to two rigid plates attached to each wheel via hinges incorporating torsional springs. The springs force the plates back to their original position after the contact with the surface is lost in the course of locomotion. The wheels are made of low-modulus elastomers, and the pressure applied during contact is controlled by the elastic modulus, geometry and phase difference of wheels. This reliable adhesion system does not rely upon gravity for adhering to surfaces, and provides the locomotion mechanism with the ability to climb walls and transition from horizontal to vertical surfaces.     

Comparing performances of logistic regression and neural networks for predicting melatonin excretion patterns in the rat exposed to ELF magnetic fields

Various studies have been reported on the bioeffects of magnetic field exposure; however, no consensus or guideline is available for experimental designs relating to exposure conditions as yet. In this study, logistic regression (LR) and artificial neural networks (ANNs) were used in order to analyze and predict the melatonin excretion patterns in the rat exposed to extremely low frequency magnetic fields (ELF‐MF). Subsequently, on a database containing 33 experiments, performances of LR and ANNs were compared through resubstitution and jackknife tests. Predictor variables were more effective parameters and included frequency, polarization, exposure duration, and strength of magnetic fields. Also, five performance measures including accuracy, sensitivity, specificity, Matthew's Correlation Coefficient (MCC) and normalized percentage, better than random (S) were used to evaluate the performance of models. The LR as a conventional model obtained poor prediction performance. Nonetheless, LR distinguished the duration of magnetic fields as a statistically significant parameter. Also, horizontal polarization of magnetic fields with the highest logit coefficient (or parameter estimate) with negative sign was found to be the strongest indicator for experimental designs relating to exposure conditions. This means that each experiment with horizontal polarization of magnetic fields has a higher probability to result in “not changed melatonin level” pattern. On the other hand, ANNs, a more powerful model which has not been introduced in predicting melatonin excretion patterns in the rat exposed to ELF‐MF, showed high performance measure values and higher reliability, especially obtaining 0.55 value of MCC through jackknife tests. Obtained results showed that such predictor models are promising and may play a useful role in defining guidelines for experimental designs relating to exposure conditions. In conclusion, analysis of the bioelectromagnetic data could result in finding a relationship between electromagnetic fields and different biological processes. Bioelectromagnetics 31:164–171, 2010. © 2009 Wiley‐Liss, Inc.     

Inhibition of endogenous miR-23a/miR-377 in CHO cells enhances difficult-to-express recombinant lysosomal sulfatase activity

Difficult-to-express (DTE) recombinant proteins such as multi-specific proteins, DTE monoclonal antibodies, and lysosomal enzymes have seen difficulties in manufacturability using Chinese hamster ovary (CHO) cells or other mammalian cells as production platforms. CHO cells are preferably used for recombinant protein production for their ability to secrete human-like recombinant proteins with posttranslational modification, resistance to viral infection, and familiarity with drug regulators. However, despite huge progress made in engineering CHO cells for high volumetric productivity, DTE proteins like recombinant lysosomal sulfatase represent one of the poorly understood proteins. Furthermore, there is growing interest in the use of microRNA (miRNA) to engineer CHO cells expressing DTE proteins to improve cell performance of relevant bioprocess phenotypes. To our knowledge, no research has been done to improve CHO cell production of DTE recombinant lysosomal sulfatase using miRNA. We identified miR-23a and miR-377 as miRNAs predicted to target SUMF1, an activator of sulfatases, using in silico prediction tools. Transient inhibition of CHO endogenous miR-23a/miR-377 significantly enhanced recombinant sulfatase enzyme-specific activity by ~15–21% compared to scramble without affecting cell growth. Though inhibition of miR-23a/miR-377 had no significant effect on the mRNA and protein levels of SUMF1, overexpression of miR-23a/377 caused ~30% and ~27–29% significant reduction in endogenous SUMF1 protein and mRNA expression levels, respectively. In summary, our data demonstrate the importance of using miRNA to optimize the CHO cell line secreting DTE recombinant lysosomal sulfatase.