ANALYSIS OF GENETIC DIVERSITY IN TWELVE CULTIVARS OF PEA BASED ON MORPHOLOGICAL AND SIMPLE SEQUENCE REPEAT MARKERS

Pea(Pisum sativum L.)is the second most important legume crop worldwide after chickpea (Cicer arietinum L.) and valuable resources for their genetic improvement. This study aimed to analyze genetic diversity of pea cultivars through morphological and molecular markers. The present investigation was carried out with 12 pea cultivars using 28 simple sequence repeat markers. A total of 60 polymorphic bands with an average of 2.31 bands per primer were obtained. The polymorphic information content, diversity index and resolving power were ranged from 0.50 to 0.33, 0.61 to 0.86 and 0.44 to 1.0 with an average of 0.46, 0.73 and 0.76, respectively. The 12 pea cultivars were grouped into 3 clusters obtained from cluster analysis with a Jaccardd’s similarity coefficient range of 0.47-0.78, indicating the sufficient genetic divergence among these cultivars of pea. The principal component analysis showed that first three principal components explained 86.97% of the total variation, suggesting the contribution of quantitative traits in genetic variability. The contribution of 32.59% for number of seeds per plant, stem circumference, number of pods per plant and number of seeds per pod in the PC1 leads to the conclusion that these traits contribute more to the total variation observed in the 12 pea cultivars and would make a good parental stock material. Overall, this SSR analysis complements morphological characters of initial selection of these pea germplasms for future breeding program

Comprehensive Assessment of the Antioxidant and Anticancer Potential of Selected Ethnobotanical Plants

Globally, among different types of cancers, breast cancer is identified as the chief cause of mortality among females, and it is a challenge to find new effective treatment strategies with minimal side effects and increased efficacy. Plants are an integral part of the traditional indigenous healthcare system and are becoming the concrete source of new drug discovery. Thus, there is a need to obtain a scientific basis for applying traditionally used plants in cancer treatments that may harbour novel phytochemicals. Therefore, this study aims to investigate the antioxidant and anticancer potential of selected plants of ethnobotanical importance. Five plants of ethnobotanical importance were selected and screened to determine their antioxidant potential through various in vitro free radical scavenging assays (such as DPPH, ABTS, hydroxyl, and superoxide radical scavenging), ferric chelation, and total antioxidant potential, and the total phenolic and flavonoid content was estimated for the selected plants. In contrast, the anticancer potential of crude plant extracts was assessed using MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) against different breast cancer (MCF-7, MDA-MB-231, and MDA-MB-435S) and hepatic cancer cell lines (HepG2), and human PBMCs (peripheral blood mononuclear cells) were used for toxicity studies. The MTT results showed that among all of the crude plant extracts (CAN = Etlingera linguiformis, SES = Sesbania grandiflora, LEX = Smilax ovalifolia, DES = Desmodium triflorum, and CA = Chenopodium album), it was CAN and LEX that showed the best cytotoxic potential on exposed breast cancer cell lines in contrast to SES, DES, and CA. In addition, at the selected dosages that were exposed to breast cancer cells, none of the extracts from any of the five plants showed any cytotoxicity against human PBMCs. Thus, the crude extracts can be explored further for chemopreventive and anticancer activity on murine models to understand their underlying mechanism for effective cancer management

Adsorption-Desorption Surface Bindings, Kinetics, and Mass Transfer Behavior of Thermally and Chemically Treated Great Millet Husk towards Cr(VI) Removal from Synthetic Wastewater

This study reports the efficacy of adsorbents synthesized by thermal (TT-GMH) and chemical (CT-GMH) modification of great millet husk (GMH) for the treatment of synthetic wastewater containing Cr(VI). The chemical modification of raw GMH was done by concentrated H2SO4 to increase the porosity and heterogeneity on the surface. The comparative investigations of physicochemical properties of synthesized adsorbents were examined by point of zero charge (pHpzc), BET surface area, SEM-EDX, FTIR, and XRD analyses. The results revealed that CT-GMH had around three times higher surface area and more porous structure as compared to TT-GMH. The adsorption experiments were executed in batch mode to examine the impact of parameters governing the adsorption process. For Cr(VI) solution of 25 mg/L, adsorbent dose of 4 g/L, temperature of 25°C, and shaking speed of 150 RPM, the maximum removal for TT-GMH was attained at pH 1 and contact time 150 min, while for CT-GMH, maximum removal was attained at pH 2 and contact time 120 min. The experimental results fitted to the rate kinetic equations showed that for both TT-GMH and CT-GMH, adsorbents followed the quasi-second-order kinetic model during the adsorption process. Further, results revealed that the adsorption process was endothermic and Sips isotherm model was followed for both TT-GMH and CT-GMH. Based on the Sips isotherm, maximum uptake capacity for TT-GMH and CT-GMH was noted to be 16 and 22.21 mg/g, respectively. Among the tested mass transfer models, liquid film diffusion model was followed during the adsorption process of both the adsorbents. The desorption study revealed that TT-GMH and CT-GMH give 69.45% and 74.48% removal, respectively, up to six cycles

Biogenic nanosized gold particles: Physico-chemical characterization and its anticancer response against breast cancer

With the advancement of nanotechnology, the nano-sized particles make an imprint on our daily lives.The present investigation revealed that biomolecules present in seed exudates of Vigna radiata are responsible for the synthesis of AuNPs, confirmed by the routine characterization techniques. Anticancer efficacy showed by AuNPs might be due to the release of phytochemicals in the exudate which is being adsorbed on the surface of AuNPs referencing their anticancer efficacy against the tested breast cancer cell lines. Inhibition of clonogenicity and cell cycle arrest at G2/M phase then apoptosis of AuNPs was also observed, but found nontoxic to the human PBMC cells which further confirms its biocompatible property Among the various physicochemical study, present AuNPs shows unique information, they show photoluminescent property which may be used for bioimaging purposes. However, further molecular analysis needs to be explored to understand the underlying mechanism for therapeutic and biomedical application

Multi-Class Pixel Certainty Active Learning Model for Classification of Land Cover Classes Using Hyperspectral Imagery

An accurate identification of objects from the acquisition system depends on the clear segmentation and classification of remote sensing images. With the limited financial resources and the high intra-class variations, the earlier proposed algorithms failed to handle the sub-optimal dataset. The building of an efficient training set iteratively in active learning (AL) approaches improves classification performance. The heuristics-based AL provides better results with the inheritance of contextual information and the robustness to noise variations. The uncertainty exists pixel variations make the heuristics-based AL fail to handle the remote sensing image classification. Previously, we focused on the extraction of clear textural pattern information by using the extended differential pattern-based relevance vector machine (EDP-AL). This paper extends that work into the novel pixel-certainty activity learning (PCAL) based on the information about textural patterns obtained from the extended differential pattern (EDP). Initially, distributed intensity filtering (DIF) is used to eliminate noise from the image, and then histogram equalization (HE) is used to improve the image quality. The EDP is used to merge and classify different labels for each image sample, and this algorithm expresses the textural information. The PCAL technique is used to classify the HSI patterns that are important in remote sensing applications using this pattern collection. Pavia University and Indian Pines (IP) are the datasets used to validate the performance of the proposed PCAL (PU). The ability of PCAL to accurately categorize land cover types is demonstrated by a comparison of the proposed PCAL with existing algorithms in terms of classification accuracy and the Kappa coefficient

Performances of a prototype point-contact germanium detector immersed in liquid nitrogen for light dark matter search

The CDEX-10 experiment searches for light weakly interacting massive particles, a form of dark matter, at the China Jinping Underground Laboratory, where approximately 10 kg of germanium detectors are arranged in an array and immersed in liquid nitrogen. Herein, we report on the experimental apparatus, detector characterization, and spectrum analysis of one prototype detector. Owing to the higher rise-time resolution of the CDEX-10 prototype detector as compared with CDEX-1B, we identified the origin of an observed category of extremely fast events. For data analysis of the CDEX-10 prototype detector, we introduced and applied an improved bulk/surface event discrimination method. The results of the new method were compared to those of the CDEX-1B spectrum. Both sets of results showed good consistency in the 0-12 keVee energy range, except for the 8.0 keV K-shell X-ray peak from the external copper