A comparative effect of IAA and 4-Cl-IAA on growth,nodulation and nitrogen fixation in <Emphasis Type="Italic">Vigna radiata</Emphasis> (L.) Wilczek

The plants of mung bean (Vigna radiata L. Wilczek) were raised from the seeds soaked in water (control), IAA or 4-C-IAA (10⁻⁶, 10⁻⁸ or 10⁻¹⁰ M) for 8 or 12 h. The plants were allowed to grow in a net house and were sampled at 30 and 45 days after sowing (DAS). Both IAA and 4-Cl-IAA significantly affected the growth (length, fresh and dry mass of roots and shoots), the number of nodules, their fresh and dry mass and the activity of nitrogenase. However, the contents of nitrogen and carbohydrate exhibited a decrease in response to both the auxins. 4-Cl-IAA, at a concentration of 10⁻⁸ M, generated the best response. Moreover, 4-Cl-IAA at other two concentrations (10⁻⁶ and 10⁻¹⁰ M) was much more active than any of the IAA concentration used.     

Mitochondrial DNA diversity in Siberian Tatars of the Tobol-Irtysh basin

Data on the variation of the nucleotide sequence of hypervariable segment I (HVSI) and restriction fragment length polymorphism (RFLP) of the coding region of mitochondrial DNA (mtDNA) have been used to characterize the mitochondrial gene pool of Siberian Tatars of the Tobol-Irtysh basin (N = 218), one of three geographic/linguistic groups of Siberian Tatars. The gene pool of Siberian Tatars has been shown to contain both Asian and European mtDNA lineages at a ratio of 1.0 : 1.5. The mtDNA diversity of Siberian Tatars is substantially higher than that of other Turkic-speaking populations of North and Central Asia. The position of the mitochondrial gene pool of Tatars of the Tobol-Irtysh basin in the genetic space of northern Eurasia populations has been determined.     

Intracellular delivery of VIP-grafted sterically stabilized phospholipid mixed nanomicelles in human breast cancer cells

The purpose of this study was to determine whether biocompatible and biodegradable vasoactive intestinal peptide-grafted sterically stabilized phospholipid mixed nanomicelles (VIP-SSMM; size, approximately 15 nm), a novel nanosized actively targeted drug delivery platform for breast cancer, accumulate in human MCF-7 breast cancer cells. Using hydrophobic CdSe/ZnS quantum dots (QD), we found that QD-loaded VIP-SSMM accumulated significantly faster and in greater quantity in MCF-7 cells than did QD-loaded SSMM alone (p<0.05). This process was mediated, in part, by VIP receptors because excess human VIP, but not PACAP(6-38) or galanin, significantly attenuated this response (p<0.05). Taken together, these data indicate that VIP-SSMM are actively targeted to human breast cancer cells through VIP receptors. We suggest that VIP-SSMM could be used as an actively targeted nanosized drug delivery platform for breast cancer cells over-expressing VIP receptors.     

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.     

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.     

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.     

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.     

Lysinibacillus composti sp. nov., isolated from compost

A Gram-negative, motile, rod-shaped, endospore-forming bacterial strain, designated as NCCP-36^T, was isolated from the compost of fruit and vegetable wastes. The strain NCCP-36^T grew within a temperature range of 10–45?^○C (optimum 28?^○C) and a pH range of 6.5–8.5 (optimum 7.0), and its cells tolerated <50 mM boron (optimum growth without boron) and 0–5 % NaCl (w/v) in tryptic soya broth medium. Based on comparative analysis of 16S rRNA gene sequence, strain NCCP-36^T showed the highest similarity to Lysinibacillus sinduriensis BLB-1^T (97.52 %) and L. xylanilyticus XDB9^T (96.96 %), and <97 % similarity with other closely related taxa. However, DNA–DNA relatedness between strain NCCP-36^T and the closely related type strains of genus Lysinibacillus was ≤37 %. Phylogenetic and chemotaxonomic analyses [major polar lipids: diphosphatidylglycerol, phosphatidylglycerol, phosphatidylethanolamine, and phospholipids; predominant menaquinone: MK-7; major cellular fatty acids: iso-C_15:0, antieso-C_15:0, and iso-C_16:0; DNA G+C contents: 37 mol %; Lys-Asp (type A4α) in cell-wall peptidoglycans as diagnostic amino acids] also support the affiliation of strain NCCP-36^T to genus Lysinibacillus. Based upon DNA–DNA relatedness as well as distinctive chemotaxonomic, phylogenetic, and genotypic data, we conclude that strain NCCP-36^T belongs to a novel species of genus Lysinibacillus, for which the name Lysinibacillus composti sp. nov. is proposed. The type strain is NCCP-36^T (JCM 18777^T?=?KCTC 13796^T?=?DSMZ 24785^T).     

Synthesis,Chemical Characterization,DNA Binding,Antioxidant, Antibacterial,and Antifungal Activities of Ferrocence Incorporated Selenoureas

Ferrocene‐incorporated selenoureas 1‐(4‐methoxybenzoyl)‐3‐(4‐ferrocenylphenyl)selenourea (P4Me), 1‐(3‐methoxybenzoyl)‐3‐(4‐ferrocenylphenyl)selenourea (P3Me), and 1‐(2‐methoxybenzoyl)‐3‐(4‐ferrocenylphenyl)selenourea (P2Me) were synthesized and characterized by nuclear magnetic resonance, Fourier transform infrared spectroscopy, atomic absorption spectroscopy, CHNS, and single‐crystal X‐ray diffraction. DNA interaction of the compounds was investigated with cyclic voltammetry, UV–visible spectroscopy, and viscometry, which is a prerequisite for anticancer agents. Drug‐DNA binding constant was found to vary in the sequence: K_P4Me (4.9000 × 10⁴ M^?1) > K_P2Me (2.318 × 10⁴ M^?1) > K_P3Me (1.296 × 10⁴ M^?1). Antioxidant (1,1‐diphenyl‐2‐picrylhydrazyl), antifungal (against Faussarium solani and Helmentosporium sativum), and antibacterial (against Escherichia coli, Pseudomonas aeruginosa, Staphylococcus aureus, and Bacillus subtilis) activities have also been reported in addition.     

Slip Effects on Mixed Convective Peristaltic Transport of Copper-Water Nanofluid in an Inclined Channel

Peristaltic transport of copper-water nanofluid in an inclined channel is reported in the presence of mixed convection. Both velocity and thermal slip conditions are considered. Mathematical modelling has been carried out using the long wavelength and low Reynolds number approximations. Resulting coupled system of equations is solved numerically. Quantities of interest are analyzed through graphs. Numerical values of heat transfer rate at the wall for different parameters are obtained and examined. Results showed that addition of copper nanoparticles reduces the pressure gradient, axial velocity at the center of channel, trapping and temperature. Velocity slip parameter has a decreasing effect on the velocity near the center of channel. Temperature of nanofluid increases with increase in the Grashoff number and channel inclination angle. It is further concluded that the heat transfer rate at the wall increases considerably in the presence of copper nanoparticles.