Foliar spray of Auxin/IAA modulates photosynthesis,elemental composition,ROS localization and antioxidant machinery to promote growth of Brassica juncea

Auxins (Aux) are primary growth regulators that regulate almost every aspect of growth and development in plants. It plays a vital role in various plant processes besides controlling the key aspects of cell division, cell expansion, and cell differentiation. Considering the significance of Aux, and its potential applications, a study was conducted to observe the impact of indole acetic acid (IAA), a most active and abundant form of Aux on Brassica juncea plants growing under natural environmental conditions. Different concentrations (0, 10⁻¹⁰, 10⁻⁸, 10⁻⁶ M) of IAA were applied once in a day at 25-day stage of growth for 5 days, consecutively. Various parameters (growth, photosynthetic, biochemical, oxidative biomarkers and nutrient composition) were assessed at different days after sowing (DAS). Scanning electron microscopy (SEM) of leaf stomata, reactive oxygen species (ROS) localization in leaf and roots, and confocal microscopy were also conducted. The results revealed that all the IAA concentrations were effective in growth promotion and ROS reduction, however, the 10⁻⁸ M of IAA exhibited the maximum improvement in all the above mentioned parameters as compared to the control.     

Conformation and vasoreactivity of VIP in phospholipids: effects of calmodulin

The purpose of this study was to determine the conformation and vasorelaxant effects of vasoactive intestinal peptide (VIP) self-associated with sterically stabilized phospholipid micelles (SSM) and whether calmodulin modulates both of these processes. Circular dichroism spectroscopy revealed that VIP is unordered in aqueous solution at room temperature but assumes appreciable α helix conformation in SSM. This conformational transition was amplified at 37°C and by a low concentration of calmodulin (0.1 nM). Suffusion of VIP in SSM elicited significant time- and concentration-dependent potentiation of vasodilation relative to that elicited by aqueous VIP in the in situ hamster cheek pouch (P < 0.05). This response was significantly potentiated by calmodulin (0.1 nM). Collectively, these data indicate that exogenous calmodulin interacts with VIP in SSM to elicit conformational transition of VIP molecule from a predominantly random coil in aqueous environment to α helix in SSM. This process is associated with potentiation and prolongation of VIP-induced vasodilation in the in situ peripheral microcirculation.     

Predicting membrane protein types by fusing composite protein sequence features into pseudo amino acid composition

Membrane proteins are vital type of proteins that serve as channels, receptors, and energy transducers in a cell. Prediction of membrane protein types is an important research area in bioinformatics. Knowledge of membrane protein types provides some valuable information for predicting novel example of the membrane protein types. However, classification of membrane protein types can be both time consuming and susceptible to errors due to the inherent similarity of membrane protein types. In this paper, neural networks based membrane protein type prediction system is proposed. Composite protein sequence representation (CPSR) is used to extract the features of a protein sequence, which includes seven feature sets; amino acid composition, sequence length, 2 gram exchange group frequency, hydrophobic group, electronic group, sum of hydrophobicity, and R-group. Principal component analysis is then employed to reduce the dimensionality of the feature vector. The probabilistic neural network (PNN), generalized regression neural network, and support vector machine (SVM) are used as classifiers. A high success rate of 86.01% is obtained using SVM for the jackknife test. In case of independent dataset test, PNN yields the highest accuracy of 95.73%. These classifiers exhibit improved performance using other performance measures such as sensitivity, specificity, Mathew's correlation coefficient, and F-measure. The experimental results show that the prediction performance of the proposed scheme for classifying membrane protein types is the best reported, so far. This performance improvement may largely be credited to the learning capabilities of neural networks and the composite feature extraction strategy, which exploits seven different properties of protein sequences. The proposed Mem-Predictor can be accessed at http://111.68.99.218/Mem-Predictor.     

Crowdsourcing as a Novel Technique for Retinal Fundus Photography Classification: Analysis of Images in the EPIC Norfolk Cohort on Behalf of the UKBiobank Eye and Vision Consortium

Aim

Crowdsourcing is the process of outsourcing numerous tasks to many untrained individuals. Our aim was to assess the performance and repeatability of crowdsourcing for the classification of retinal fundus photography.

Methods

One hundred retinal fundus photograph images with pre-determined disease criteria were selected by experts from a large cohort study. After reading brief instructions and an example classification, we requested that knowledge workers (KWs) from a crowdsourcing platform classified each image as normal or abnormal with grades of severity. Each image was classified 20 times by different KWs. Four study designs were examined to assess the effect of varying incentive and KW experience in classification accuracy. All study designs were conducted twice to examine repeatability. Performance was assessed by comparing the sensitivity, specificity and area under the receiver operating characteristic curve (AUC).

Results

Without restriction on eligible participants, two thousand classifications of 100 images were received in under 24 hours at minimal cost. In trial 1 all study designs had an AUC (95%CI) of 0.701(0.680–0.721) or greater for classification of normal/abnormal. In trial 1, the highest AUC (95%CI) for normal/abnormal classification was 0.757 (0.738–0.776) for KWs with moderate experience. Comparable results were observed in trial 2. In trial 1, between 64–86% of any abnormal image was correctly classified by over half of all KWs. In trial 2, this ranged between 74–97%. Sensitivity was ≥96% for normal versus severely abnormal detections across all trials. Sensitivity for normal versus mildly abnormal varied between 61–79% across trials.

Conclusions

With minimal training, crowdsourcing represents an accurate, rapid and cost-effective method of retinal image analysis which demonstrates good repeatability. Larger studies with more comprehensive participant training are needed to explore the utility of this compelling technique in large scale medical image analysis.     

Delay-decomposing approach to robust stability for switched interval networks with state-dependent switching

This paper is concerned with a class of nonlinear uncertain switched networks with discrete time-varying delays . Based on the strictly complete property of the matrices system and the delay-decomposing approach, exploiting a new Lyapunov–Krasovskii functional decomposing the delays in integral terms, the switching rule depending on the state of the network is designed. Moreover, by piecewise delay method, discussing the Lyapunov functional in every different subintervals, some new delay-dependent robust stability criteria are derived in terms of linear matrix inequalities, which lead to much less conservative results than those in the existing references and improve previous results. Finally, an illustrative example is given to demonstrate the validity of the theoretical results.     

Effects of Convective Heat and Mass Transfer in Flow of Powell-Eyring Fluid Past an Exponentially Stretching Sheet

The aim here is to investigate the effects of convective heat and mass transfer in the flow of Eyring-Powell fluid past an inclined exponential stretching surface. Mathematical formulation and analysis have been performed in the presence of Soret, Dufour and thermal radiation effects. The governing partial differential equations corresponding to the momentum, energy and concentration are reduced to a set of non-linear ordinary differential equations. Resulting nonlinear system is computed for the series solutions. Interval of convergence is determined. Physical interpretation is seen for the embedded parameters of interest. Skin friction coefficient, local Nusselt number and local Sherwood number are numerically computed and examined.     

Radiation Effects on the Flow of Powell-Eyring Fluid Past an Unsteady Inclined Stretching Sheet with Non-Uniform Heat Source/Sink

This study investigates the unsteady flow of Powell-Eyring fluid past an inclined stretching sheet. Unsteadiness in the flow is due to the time-dependence of the stretching velocity and wall temperature. Mathematical analysis is performed in the presence of thermal radiation and non-uniform heat source/sink. The relevant boundary layer equations are reduced into self-similar forms by suitable transformations. The analytic solutions are constructed in a series form by homotopy analysis method (HAM). The convergence interval of the auxiliary parameter is obtained. Graphical results displaying the influence of interesting parameters are given. Numerical values of skin friction coefficient and local Nusselt number are computed and analyzed.     

Lipid contribution to the affinity of antigen association with specific antibodies conjugated to liposomes

Immunoliposomes, directed to clinically relevant cell-surface molecules with antibodies, antibody fragments or peptides, are used for site-specific diagnostic evaluation or delivery of therapeutic agents. We have developed intrinsically echogenic liposomes (ELIP) covalently linked to fibrin(ogen)-specific antibodies and Fab fragments for ultrasonic imaging of atherosclerotic plaques. In order to determine the effect of liposomal conjugation on the molecular dynamics of fibrinogen binding, we studied the thermodynamic characteristics of unconjugated and ELIP-conjugated antibody molecules. Utilizing radioimmunoassay and enzyme-linked immunosorbent assay protocols, binding affinities were derived from data obtained at three temperatures. The thermodynamic functions DeltaH(o) , DeltaG(o) and DeltaS(o) were determined from van't Hoff plots and equations of state. The resultant functions indicated that both specific and nonspecific associations of antibody molecules with fibrinogen occurred through a variety of molecular interactions, including hydrophophic, ionic and hydrogen bonding mechanisms. ELIP conjugation of antibodies and Fab fragments introduced a characteristic change in both DeltaH(o) and DeltaS(o) of association, which corresponded to a variable contribution to binding by phospholipid gel-liquid crystal phase transitions. These observations suggest that a reciprocal energy transduction, affecting the strength of antibody-antigen binding, may be a singular characteristic of immunoliposomes, having utility for optimization and further development of the technology.     

Electrochemical-based biosensors for detection of Mycobacterium tuberculosis and tuberculosis biomarkers

Abstract

Early detection of tuberculosis (TB) reduces the interval between infection and the beginning of treatment. However, commercially available tests cannot discriminate between BCG-vaccinated healthy persons and patients. Also, they are not suitable to be used for immunocompromised persons. In recent years, biosensors have attracted great attention due to their simple utility, accessibility, and real-time outputs. These sensors are increasingly being considered as pioneering tools for point-of-care diagnostics in communities with a high burden of TB and limited accessibility to reference laboratories. Among other types of biosensors, the electrochemical sensors have the advantages of low-cost operation, fast processing, simultaneous multi-analyte analyzing, operating with turbid samples, comparable sensitivity and readily available miniaturization. Electrochemical biosensors are sub-divided into several categories including: amperometric, impedimetric, potentiometric, and conductometric biosensors. The biorecognition element in electrochemical biosensors is usually based on antibodies (immunosensors), DNAs or PNAs (genosensors), and aptamers (aptasensors). In either case, whether an interaction of the antigen–antibody/aptamer or the hybridization of probe with target mycobacterial DNA is detected, a change in the electrical current occurs that is recorded and displayed as a plot. Therefore, impedimetric-based methods evaluate resistance to electron transfer toward an electrode by a Nyquist plot and amperometric/voltammetric-based methods weigh the electrical current by means of cyclic voltammetry, square wave voltammetry, and differential pulse voltammetry. Electrochemical biosensors provide a promising scope for the new era of diagnostics. As a consequence, they can improve detection of Mycobacterium tuberculosis traces even in attomolar scales.