Functional expression of KCNQ (Kv7) channels in guinea-pig bladder smooth muscle and their contribution to spontaneous activity

Background and Purpose: The aim of the study was to determine whether KCNQ channels are functionally expressed in bladder smooth muscle cells (SMC) and to investigate their physiological significance in bladder contractility. 

Experimental Approach: KCNQ channels were examined at the genetic, protein, cellular and tissue level in guinea pig bladder smooth muscle using RT-PCR, immunofluorescence, patch-clamp electrophysiology, calcium imaging, detrusor strip myography, and a panel of KCNQ activators and inhibitors. 

Key Results: KCNQ subtypes 1-5 are expressed in bladder detrusor smooth muscle. Detrusor strips typically displayed TTX-insensitive myogenic spontaneous contractions that were increased in amplitude by the KCNQ channel inhibitors XE991, linopirdine or chromanol 293B. Contractility was inhibited by the KCNQ channel activators flupirtine or meclofenamic acid (MFA). The frequency of Ca2+-oscillations in SMC contained within bladder tissue sheets was increased by XE991. Outward currents in dispersed bladder SMC, recorded under conditions where BK and KATP currents were minimal, were significantly reduced by XE991, linopirdine, or chromanol, and enhanced by flupirtine or MFA. XE991 depolarized the cell membrane and could evoke transient depolarizations in quiescent cells. Flupirtine (20M) hyperpolarized the cell membrane with a simultaneous cessation of any spontaneous electrical activity. 

Conclusions and Implications: These novel findings reveal the role of KCNQ currents in the regulation of the resting membrane potential of detrusor SMC and their important physiological function in the control of spontaneous contractility in the guinea pig bladder.

Molecular dynamics simulation of nanoindentation of Fe3C and tetrahedral Fe4C

Study of nanomechanical response of iron carbides is important because presence of iron carbides greatly influences the performance and longevity of steel components. This work contributes to the literature by exploring nanoindentation of nanocrystalline Fe3C and tetrahedral-Fe4C using molecular dynamics simulation. The chemical interactions of iron and carbon were described through an analytical bond order inter-atomic potential (ABOP) energy function. The indentations were performed at an indentation speed of 50 m/sec and a repeat trial was performed at 5 m/sec. Load-displacement (P-h) curve for both these carbides showed residual indentation depth and maximum indentation depth (hf/hmax) ratio to be higher than 0.7 i.e. a circumstance where Oliver and Pharr method was not appropriate to be applied to evaluate the material properties. Alternate evaluation revealed Fe3C to be much harder than Fe4C. Gibbs free energy of formation and radial distribution function, coupled with state of the average local temperature and von Mises stresses indicate the formation of a new phase of iron-carbide. Formation of this newer phase was found to be due to deviatoric strain rather than the high temperature induced in the substrate during nanoindentation

Parametric design optimization of hard turning of AISI 4340 steel (69 HRC)

Continuous research endeavors on hard turning (HT), both on machine tools and cutting tools, have made the previously reported daunting limits easily attainable in the modern scenario. This presents an opportunity for a systematic investigation on finding the current attainable limits of hard turning using a CNC turret lathe. Accordingly, this study aims to contribute to the existing literature by providing the latest experimental results of hard turning of AISI 4340 steel (69 HRC) using a CBN cutting tool. An orthogonal array was developed using a set of judiciously chosen cutting parameters. Subsequently, the longitudinal turning trials were carried out in accordance with a well-designed full factorial-based Taguchi matrix. The speculation indeed proved correct as a mirror finished optical quality machined surface (an average surface roughness value of 45 nm) was achieved by the conventional cutting method. Furthermore, Signal-to-noise (S/N) ratio analysis, Analysis of variance (ANOVA), and Multiple regression analysis were carried out on the experimental datasets to assert the dominance of each machining variable in dictating the machined surface roughness and to optimize the machining parameters. One of the key findings was that when feed rate during hard turning approaches very low (about 0.02mm/rev), it could alone be most significant (99.16%) parameter in influencing the machined surface roughness (Ra). This has, however also been shown that low feed rate results in high tool wear, so the selection of machining parameters for carrying out hard turning must be governed by a trade-off between the cost and quality considerations.

Detecting localized homogeneous anomalies over spatio-temporal data

The last decade has witnessed an unprecedented growth in availability of data having spatio-temporal characteristics. Given the scale and richness of such data, finding spatio-temporal patterns that demonstrate significantly different behavior from their neighbors could be of interest for various application scenarios such as – weather modeling, analyzing spread of disease outbreaks, monitoring traffic congestions, and so on. In this paper, we propose an automated approach of exploring and discovering such anomalous patterns irrespective of the underlying domain from which the data is recovered. Our approach differs significantly from traditional methods of spatial outlier detection, and employs two phases – i) discovering homogeneous regions, and ii) evaluating these regions as anomalies based on their statistical difference from a generalized neighborhood. We evaluate the quality of our approach and distinguish it from existing techniques via an extensive experimental evaluation.