Advances in Pharmacology of Isatin and its Derivatives: A Review

Isatin (1H-indole-2,3-dione), an indole derivative of plant origin, is involved in many pharmacological activities like antiallergic, antimalarial, antiviral and antimicrobial; isatin and its derivatives have been found to show promising results against various cancer cell lines. Isatin is a versatile precursor for many biologically active molecules and its diversified nature makes it a versatile substrate for further modifications. This review provides a brief overview on the recent advances and future perspectives on pharmacological aspects of isatin and its derivatives reported in the last decade.Keywords: Isatin, Anticancer, Antimicrobial, Monoamine oxidase, Antivira

Freshwater plastic pollution:Recognizing research biases and identifying knowledge gaps

The overwhelming majority of research conducted to date on plastic pollution (all size fractions) has focused on marine ecosystems. In comparison, only a few studies provide evidence for the presence of plastic debris in freshwater environments. However, owing to the numerous differences between freshwater studies (including studied species and habitats, geographical locations, social and economic contexts, the type of data obtained and also the broad range of purposes), they show only fragments of the overall picture of freshwater plastic pollution. This highlights the lack of a holistic vision and evidences several knowledge gaps and data biases. Through a bibliometric analysis we identified such knowledge gaps, inconsistencies and survey trends of plastic pollution research within freshwater ecosystems. We conclude that there is a continued need to increase the field-data bases about plastics (all size fractions) in freshwater environments. This is particularly important to estimate river plastic emissions to the world´s oceans. Accordingly, data about macroplastics from most polluted and larger rivers are very scarce, although macroplastics represent a huge input in terms of plastics weight. In addition, submerged macroplastics may play an important role in transporting mismanaged plastic waste, however almost no studies exist. Although many of the most plastic polluted rivers are in Asia, only 14% of the reviewed studies were carried out in this continent (even though the major inland fisheries of the world are located in Asia´s rivers). The potential damage caused by macroplastics on a wide range of freshwater fauna is as yet undetermined, even though negative impacts have been well documented in similar marine species. We also noted a clear supremacy of microplastic studies over macroplastic ones, even though there is no reason to assume that freshwater ecosystems remain unaffected by macro-debris. Finally, we recommend focusing monitoring efforts in most polluted rivers worldwide, but particularly in countries with rapid economic development and poor waste management.Fil: Blettler, Martin Cesar Maria. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto Nacional de Limnología. Universidad Nacional del Litoral. Instituto Nacional de Limnología; ArgentinaFil: Abrial, Elie. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto Nacional de Limnología. Universidad Nacional del Litoral. Instituto Nacional de Limnología; ArgentinaFil: Khan, Farhan R.. Roskilde University;Fil: Sivri, Nuket. Istanbul Üniversitesi;Fil: Espínola, Luis Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto Nacional de Limnología. Universidad Nacional del Litoral. Instituto Nacional de Limnología; Argentin

Bayesian, Maximum Parsimony and UPGMA Models for Inferring the Phylogenies of Antelopes Using Mitochondrial Markers

This investigation was aimed to compare the inference of antelope phylogenies resulting from the 16S rRNA, cytochrome-b (cyt-b) and d-loop segments of mitochondrial DNA using three different computational models including Bayesian (BA), maximum parsimony (MP) and unweighted pair group method with arithmetic mean (UPGMA). The respective nucleotide sequences of three Oryx species (Oryx leucoryx, Oryx dammah and Oryx gazella) and an out-group (Addax nasomaculatus) were aligned and subjected to BA, MP and UPGMA models for comparing the topologies of respective phylogenetic trees. The 16S rRNA region possessed the highest frequency of conserved sequences (97.65%) followed by cyt-b (94.22%) and d-loop (87.29%). There were few transitions (2.35%) and none transversions in 16S rRNA as compared to cyt-b (5.61% transitions and 0.17% transversions) and d-loop (11.57% transitions and 1.14% transversions) while comparing the four taxa. All the three mitochondrial segments clearly differentiated the genus Addax from Oryx using the BA or UPGMA models. The topologies of all the gamma-corrected Bayesian trees were identical irrespective of the marker type. The UPGMA trees resulting from 16S rRNA and d-loop sequences were also identical (Oryx dammah grouped with Oryx leucoryx) to Bayesian trees except that the UPGMA tree based on cyt-b showed a slightly different phylogeny (Oryx dammah grouped with Oryx gazella) with a low bootstrap support. However, the MP model failed to differentiate the genus Addax from Oryx. These findings demonstrate the efficiency and robustness of BA and UPGMA methods for phylogenetic analysis of antelopes using mitochondrial markers

Early MCI-to-AD Conversion Prediction Using Future Value Forecasting of Multimodal Features

In Alzheimer’s disease (AD) progression, it is imperative to identify the subjects with mild cognitive impairment before clinical symptoms of AD appear. This work proposes a technique for decision support in identifying subjects who will show transition from mild cognitive impairment (MCI) to Alzheimer’s disease (AD) in the future. We used robust predictors from multivariate MRI-derived biomarkers and neuropsychological measures and tracked their longitudinal trajectories to predict signs of AD in the MCI population. Assuming piecewise linear progression of the disease, we designed a novel weighted gradient offset-based technique to forecast the future marker value using readings from at least two previous follow-up visits. Later, the complete predictor trajectories are used as features for a standard support vector machine classifier to identify MCI-to-AD progressors amongst the MCI patients enrolled in the Alzheimer’s disease neuroimaging initiative (ADNI) cohort. We explored the performance of both unimodal and multimodal models in a 5-fold cross-validation setup. The proposed technique resulted in a high classification AUC of 91.2% and 95.7% for 6-month- and 1-year-ahead AD prediction, respectively, using multimodal markers. In the end, we discuss the efficacy of MRI markers as compared to NM for MCI-to-AD conversion prediction

Frequency and amplitude measurement of a cantilever beam using image processing: with a feedback system

Image processing techniques can be utilized in analyzing amplitude and frequency of vibrating structures. It is a form of non-contact method which is suitable for cases where application of contact devices could alter the frequency of structure. This paper covers the study based on vision system that performs amplitude and frequency measurement of a cantilever beam in near real time, using image processing and computer vision toolbox in MATLAB. The vision system then detects changes in amplitude followed by feedback mechanism to ensure operation at resonance frequency. The system includes a high speed camera which is able to detect amplitude and frequency of cantilever beam vibrating at a frequency with the help of mechanical exciter. The high speed camera captures images of the beam, that are processed by a MATLAB script for evaluation of amplitude and frequency. To locate amplitude of the vibrating beam, centroid recognition technique is used which tracks the centroids of the beam in consecutive frames and plots number of pixels moved by the centroid with respect to time. Later, frequency is found out on the basis of intensity change over the time. Amplitude analysis is done at different frequencies which are automatically adjusted with the help of microcontroller to determine the resonance point. Exciter continues to vibrate at the resonant frequency until a change in amplitude is detected, implying the formation of crack. At which point the system adjusts its vibrating frequency accordingly to adjust with the new resonant frequency. This paper covers proper experimental procedure backed with the results

Insights into the strong in-vitro anticancer effects for bis(triphenylphosphane)iminium compounds having perchlorate, tetrafluoridoborate and bis(chlorido)argentate anions

Three new compounds containing the bis(triphenylphosphane)iminium cation (PPN+) with ClO4−, BF4− and [AgCl2]− as counter anions have been synthesized and structurally characterized. The two derivatives with ClO4− and BF4− were found to be isostructural by single crystal X-ray diffraction. Interestingly, the three compounds show extremely potent antiproliferative effects against the human cancer cell line SKOV3. To gain insights into the possible mechanisms of biological action, several intracellular targets have been considered. Thus, DNA binding has been evaluated, as well as the effects of the compounds on the mitochondrial function. Furthermore, the compounds have been tested as possible inhibitors of the seleno-enzyme thioredoxin reductase

Artificial Intelligence and Bio-Inspired Soft Computing-Based Maximum Power Plant Tracking for a Solar Photovoltaic System under Non-Uniform Solar Irradiance Shading Conditions - A Review

Substantial progress in solar photovoltaic (SPV) dissemination in grid-connected and standalone power generation systems has been witnessed during the last two decades. However, weather intermittency has a non-linear characteristic impact on solar photovoltaic output, which can cause considerable loss in the system's overall output. To overcome these inevitable losses and optimize the SPV output, maximum power point tracking (MPPT) is mounted in the middle of the power electronics converters and SPV to achieve the maximum output with better precision from the SPV system under intermittent weather conditions. As MPPT is considered an essential part of the SPV system, up to now, many researchers have developed numerous MPPT techniques, each with unique features. A Google Scholar survey from 2015 - 2021 was performed to scrutinize the number of published review papers in this area. An online search established that on different MPPT techniques, overall, 100 review articles were published; out of these 100, seven reviews on conventional MPPT techniques under shading or partial shading and only four under non-uniform solar irradiance are published. Unfortunately, no dedicated review article has explicitly focused on soft computing MPPT (SC-MPPT) techniques. Therefore, a comprehensive review of articles on SC-MPPT techniques is desirable, in which almost all the familiar SC-MPPT techniques have to be summarized in one piece. This review article concentrates explicitly on soft computing-based MPPT techniques under non-uniform irradiance conditions along with their operating principles, block/flow diagram. It will not only be helpful for academics and researchers to provide a future direction in SC-MPPT optimization research, but also help the field engineers to select the appropriate SC-MPPT for SPV according to system design and environmental conditions

Comparative evaluation of PCR success with universal primers of maturase K (matK) and ribulose-1, 5-bisphosphate carboxylase oxygenase large subunit (rbcL) for barcoding of some arid plants

Abstract DNA barcoding is the use of short DNA sequences (~650 bp) of the standard segment of the genome for large scale species identification. The Consortium for the Barcode of Life (CBOL) plant-working group recommended the 2-locus combination of rbcL and matK as the standard plant barcode. These two regions of chloroplast DNA were chosen due to efficient recovery of quality sequences and high levels of species discrimination. We evaluated the success rates of universal primers for amplification of matK and rbcL loci in 26 different plant species (covering 14 families) from Saudi Arabia. Success rate in PCR was higher for rbcL (88%) compared with matK (69%). The universal primers of both matK and rbcL failed to amplify the DNA form 3 plant species belonging to the family Asteraceae (Anthemis deserti, Pulicaria undulate, and Sonchus oleraceus). Two plant species Malva parviflora (Malvaceae) and Salsola imbricate (Chenopodiaceae) indicated different primer binding site (matK) as the amplified PCR products were of lower size than expected for these species. These findings indicate that although currently used universal primers of rbcL and matK are able to amplify many of the plant species they may fail in certain cases due to primer mismatch at the annealing site. Further studies are therefore needed for protocol development, particularly designing of novel universal primers, to extend the barcoding for a broader coverage of plant species

Reinforcing synthetic data for meticulous survival prediction of patients suffering from left ventricular systolic dysfunction

Congestive heart failure is among leading genesis of concern that requires an immediate medical attention. Among various cardiac disorders, left ventricular systolic dysfunction is one of the well known cardiovascular disease which causes sudden congestive heart failure. The irregular functioning of a heart can be diagnosed through some of the clinical attributes, such as ejection fraction, serum creatinine etcetera. However, due to availability of a limited data related to the death events of patients suffering from left ventricular systolic dysfunction, a critical level of thresholds of clinical attributes can not be estimated with higher precision. Hence, this paper proposes a novel pseudo reinforcement learning algorithm which overcomes a problem of majority class skewness in a limited dataset by appending a synthetic dataset across minority data space. The proposed pseudo agent in the algorithm continuously senses the state of the dataset (pseudo environment) and takes an appropriate action to populate the dataset resulting into higher reward. In addition, the paper also investigates the role of statistically significant clinical attributes such as age, ejection fraction, serum creatinine etc., which tends to efficiently predict the association of death events of the patients suffering from left ventricular systolic dysfunctio