Machine learning models effectively distinguish attention-deficit/hyperactivity disorder using event-related potentials

Accurate diagnosis of Attention-Deficit/Hyperactivity Disorder (ADHD) is a significant challenge. Misdiagnosis has significant negative medical side effects. Due to the complex nature of this disorder, there is no computational expert system for diagnosis. Recently, automatic diagnosis of ADHD by machine learning analysis of brain signals has received an increased attention. This paper aimed to achieve an accurate model to discriminate between ADHD patients and healthy controls by pattern discovery. Event-Related Potentials (ERP) data were collected from ADHD patients and healthy controls. After pre-processing, ERP signals were decomposed and features were calculated for different frequency bands. The classification was carried out based on each feature using seven machine learning algorithms. Important features were then selected and combined. To find specific patterns for each model, the classification was repeated using the proposed patterns. Results indicated that the combination of complementary features can significantly improve the performance of the predictive models. The newly developed features, defined based on band power, were able to provide the best classification using the Generalized Linear Model, Logistic Regression, and Deep Learning with the average accuracy and Receiver operating characteristic curve > %99.85 and > 0.999, respectively. High and low frequencies (Beta, Delta) performed better than the mid, frequencies in the discrimination of ADHD from control. Altogether, this study developed a machine learning expert system that minimises misdiagnosis of ADHD and is beneficial for the evaluation of treatment efficacy.Graphical abstract      

Structure,chaperone activity,and aggregation of wild-type and R12C mutant αB-crystallins in the presence of thermal stress and calcium ion – Implications for role of calcium in cataract pathogenesis

The current study was performed with the aim to evaluate the chaperoning ability, structural features, and aggregation propensity of wild-type and R12C mutant αB-crystallins (αB-Cry) under thermal stress and in the presence of calcium ion. The results of different spectroscopic analyses suggest that wild-type and mutant αB-Cry have dissimilar secondary and tertiary structures. Moreover, αB-Cry indicates slightly improved chaperone activity upon the R12C mutation. Thermal stress and calcium, respectively, enhance and reduce the extent of solvent-exposed hydrophobic surfaces accompanying formation of ordered and non-ordered aggregate entities in both proteins. Compared to the wild-type protein, the R12C mutant counterpart shows significant resistance against thermal and calcium-induced aggregation. In addition, in the presence of calcium, significant structural variation was accompanied by reduction in the solvent-exposed hydrophobic patches and attenuation of chaperone activity in both proteins. Additionally, gel mobility shift assay indicates the intrinsic propensity of R12C mutant αB-Cry for disulfide bridge-mediated protein dimerization. Overall, the results of this study are of high significance for understanding the molecular details of different factors that are involved in the pathomechanism of cataract disorders.     

Oxidative stress‐induced renal telomere shortening as a mechanism of cyclosporine‐induced nephrotoxicity

Due to the association of oxidative stress and telomere shortening, it was aimed in the present study to investigate the possibility whether cyclosporine‐A exerts its nephrotoxic side effects via induction of oxidative stress‐induced renal telomere shortening and senescent phenotype in renal tissues of rats. Renal oxidative stress markers, 8‐hydroxydeoxyguanosine, malondialdehyde, and protein carbonyl groups were measured by standard methods. Telomere length and telomerase activity were also evaluated in kidney tissue samples. Results showed that cyclosporine‐A treatment significantly (P < 0.05) enhanced renal malondialdehyde, 8‐hydroxydeoxyguanosine, and protein carbonyl groups levels, decreased renal telomere length, and deteriorated renal function compared with the controls. Renal telomerase activity was not affected by cyclosporine‐A. Renal telomere length could be considered as an important parameter of both oxidative stress and kidney function. Telomere shortening and accelerated kidney aging may be caused by cyclosporine‐induced oxidative stress, indicating the potential mechanism of cyclosporine‐induced nephrotoxicity.     

Progress on lipid extraction from wet algal biomass for biodiesel production

Lipid recovery and purification from microalgal cells continues to be a significant bottleneck in biodiesel production due to high costs involved and a high energy demand. Therefore, there is a considerable necessity to develop an extraction method which meets the essential requirements of being safe, cost‐effective, robust, efficient, selective, environmentally friendly, feasible for large‐scale production and free of product contamination. The use of wet concentrated algal biomass as a feedstock for oil extraction is especially desirable as it would avoid the requirement for further concentration and/or drying. This would save considerable costs and circumvent at least two lengthy processes during algae‐based oil production. This article provides an overview on recent progress that has been made on the extraction of lipids from wet algal biomass. The biggest contributing factors appear to be the composition of algal cell walls, pre‐treatments of biomass and the use of solvents (e.g. a solvent mixture or solvent‐free lipid extraction). We compare recently developed wet extraction processes for oleaginous microalgae and make recommendations towards future research to improve lipid extraction from wet algal biomass.     

Response of Pseudomonas tolaasii,the causal agent of mushroom brown blotch disease to the volatile compounds produced by endofungal bacteria

Volatile organic compounds (VOCs) produced by bacteria have significant potential to control phytopathogens. In this study, the VOCs produced by endofungal bacteria Pseudomonas sp. Bi1, Bacillus sp. De3, Pantoea sp. Ma3 and Pseudomonas sp. De1 isolated from wild growing mushrooms were evaluated in vitro for their antagonistic activity against Pseudomonas tolaasii Pt18, the causal agent of mushroom brown blotch disease. The gas chromatography–mass spectrometry (GC–MS) analysis revealed that strains Pseudomonas sp. Bi1, Pseudomonas sp. De1, Bacillus sp. De3 and Pantoea sp. Ma3 produced eight, sixteen, nine, and twelve VOCs, respectively. All antagonistic endofungal bacteria produced VOCs which significantly reduced brown blotch symptoms on mushroom caps and inhibited the growth of P. tolaasii Pt18 at the varying levels. Scanning electron microscopy revealed severe morphological changes in cells of P. tolaasii Pt18 following exposure to the VOCs of Pseudomonas sp. Bi1 and De1. Furthermore, The VOCs produced by endofungal bacteria significantly reduced swarming, swimming, twitching, chemotaxis motility and biofilm formation by P. tolaasii Pt18 cells, which are essential contributors to pathogenicity. This is to first report about the inhibition effects of VOCs produced by antagonistic bacteria on virulence traits of P. tolaasii. Our findings provide new insights regarding the potential of antibacterial VOCs as a safe fumigant to control mushroom brown blotch disease.

     

Brain Insulin Dysregulation: Implication for Neurological and Neuropsychiatric Disorders

Arduous efforts have been made in the last three decades to elucidate the role of insulin in the brain. A growing number of evidences show that insulin is involved in several physiological function of the brain such as food intake and weight control, reproduction, learning and memory, neuromodulation and neuroprotection. In addition, it is now clear that insulin and insulin disturbances particularly diabetes mellitus may contribute or in some cases play the main role in development and progression of neurodegenerative and neuropsychiatric disorders. Focusing on the molecular mechanisms, this review summarizes the recent findings on the involvement of insulin dysfunction in neurological disorders like Alzheimer’s disease, Parkinson’s disease and Huntington’s disease and also mental disorders like depression and psychosis sharing features of neuroinflammation and neurodegeneration.     

Molecular characterization of Plasmodium vivax clinical isolates in Pakistan and Iran using pvmsp-1, pvmsp-3α and pvcsp genes as molecular markers

In this study, the diversity of Plasmodium vivax populations circulating in Pakistan and Iran has been investigated by using circumsporozoite protein (csp) and merozoite surface proteins 1 and 3α (msp-1 and msp-3α) genes as genetic markers. Infected P. vivax blood samples were collected from Pakistan (n = 187) and Iran (n = 150) during April to October 2008, and were analyzed using nested-PCR/RFLP and sequencing methods. Genotyping pvmsp-1 (variable block 5) revealed the presence of type 1, type 2 and recombinant type 3 allelic variants, with type 1 predominant, in both study areas. The sequence analysis of 33 P. vivax isolates from Pakistan and 30 from Iran identified 16 distinct alleles each, with one allele (R-8) from Iran which was not reported previously. Genotyping pvcsp gene also showed that VK210 type is predominant in both countries. Moreover, based on the size of amplified fragment of pvmsp-3α, three major types: type A (1800 bp), type B (1500 bp) and type C (1200 bp), were distinguished among the examined isolates that type A was predominant among Pakistani (72.7%) and Iranian (77.3%) parasites. PCR/RFLP products of pvmsp-3α with HhaI and AluI have detected 40 and 39 distinct variants among Pakistani and Iranian examined isolates, respectively. Based on these three studied genes, the rate of combined multiple genotypes were 30% and 24.6% for Pakistani and Iranian P. vivax isolates, respectively. These results indicate an extensive diversity in the P. vivax populations in both studies.     

Pierce into the Native Structure of Ata,a Trimeric Autotransporter of Acinetobacter baumannii ATCC 17978

International Journal of Peptide Research and Therapeutics - Acinetobacter baumannii is an important pathogen responsible for nosocomial infections worldwide. Trimeric autotransporters, the...     

QT interval measurement using RMED curve; a novel approach based on wavelet techniques

Hypothesis/objective: Prolonged QT interval is an index of propensity for dangerous ventricular tachyarrhythmias. The aim of this article is to establish an automatic algorithm for QT interval measurement.

Method: The proposed method is based on the continuous wavelet transform. In this method, the concepts of the rescaled wavelet coefficients and dominant scales of the electrocardiogram (ECG) components are used to perform detection of ECG characteristic points. A new concept of rescaled maximum energy density is introduced so as to perform the estimation of the QT interval.

Results and conclusion: We have applied the algorithm to the PTB database of the Physiobank?Physionet in lead II. Then, the results were evaluated using pertinent reference QT. The criterion used for evaluation of the method's performance is the root mean square (RMS) error. The method approached the RMS error of 27.89 ms for 549 subjects. The proposed method is fast, simple and is applicable to a wide range of ECG cardio cycle morphologies.