In vitro and in vivo antioxidant therapeutic evaluation of phytochemicals from different parts of Dodonaea viscosa Jacq.

Introduction: Natural antioxidants are vital to promote health and treat critical disease conditions in the modern healthcare system. This work adds to the index of natural medicines by exploring the antioxidant potential of Dodonaea viscosa Jacq. (Plant-DV). Material and Methods: The aqueous extract of leaves and flower-containing seeds from plant-DV in freshly prepared phosphate buffer is evaluated for antioxidant potential. In vitro antioxidant potential of the nascent and oxidatively stressed extracts was analyzed through glutathione (GSH) assay, hydrogen peroxide (H2O2) scavenging effect, glutathione-S-transferase (GST) assay, and catalase (CAT) activity. In vivo therapeutic assessment is performed in Wistar Albino rats using vitamin C as a positive control. The livers and kidneys of individual animals are probed for glutathione, glutathione-S-transferase, and catalase activities. Results: flower-containing seeds have GSH contents (59.61 µM) and leaves (32.87 µM) in the fresh aqueous extracts. The hydrogen peroxide scavenging effect of leaves is superior to flower-containing seeds with 17.25% and 14.18% respectively after 30 min incubation. However, oxidatively stressed extracts with Ag(I) and Hg(II) show declining GSH and GST levels. The plant extracts are non-toxic in rats at 5000 mg/Kg body weight. Liver and kidneys homogenate reveal an increase in GSH, GST, and CAT levels after treatment with 150 ± 2 mg/kg and 300 ± 2 mg/kg body weight plant extract compared with normal saline-treated negative and vitamin C treated positive control. Discussion: The crude aqueous extracts of leaves and flower-containing seeds of plant-DV show promising antioxidant potential both in in vitro and in vivo evaluation.

Development of reduced graphene oxide-supported novel hybrid nanomaterials (Bi2WO6@rGO and Cu-WO4@rGO) for green and efficient oxidative desulfurization of model fuel oil for environmental depollution.

For the first time, two new kinds of inorganic-organic hybrid nanomaterials (Bi2WO6@rGO and Cu-WO4@rGO) were fabricated by simple hydrothermal treatment and employed for green and efficient oxidative desulfurization of real fuel. The characterization of newly synthesized nanocomposites was performed by SEM, EDX, P-XRD, FT-IR and TGA. SEM and XRD analyses revealed well decoration of dopants (Cu-WO4 and Bi-WO3) on the surface of rGO with a crystallite size of <50 nm. The catalytic activity of both nanocatalysts was examined for model (dibenzothiophene) and real fuel (kerosene and diesel) by oxidative desulfurization route. Experimental findings revealed a high efficiency of over 90% under optimal reaction conditions of 0.1 g catalyst, 1 mL of oxidant, and 100 mg/L after 120 min at 30 °C. The major factors affecting desulfurization efficiency (time, temperature, catalyst amount, dibenzothiophene (DBT) concentration and amount of oxidant) and kinetic studies were described. The DBT removal via oxidative desulfurization followed pseudo first-order kinetics with an activation energy of 14.57 and 16.91 kJ/mol for Cu-WO4@rGO and Bi2WO6@rGO, respectively. The prepared catalysts showed promising reusability for the ODS process up to 5 times with no significant decrease in efficiency. In conclusion, the findings confirm the robustness of newly prepared nanocomposite for efficient production of sulfur-free oil.

Coronavirus (COVID-19) detection from chest radiology images using convolutional neural networks.

Coronavirus disease (Covid-19) has been spreading all over the world and its diagnosis is attracting more research every moment. It is need of the hour to develop automated methods, which could detect this disease at its early stage, in a non-invasive way and within lesser time. Currently, medical specialists are analyzing Computed Tomography (CT), X-Ray, and Ultrasound (US) images or conducting Polymerase Chain Reaction (PCR) for its confirmation on manual basis. In Pakistan, CT scanners are available in most hospitals at district level, while X-Ray machines are available in all tehsil (large urban towns) level hospitals. Being widely used imaging modalities to analyze chest related diseases, produce large volume of medical data each moment clinical environments. Since automatic, time efficient and reliable methods for Covid-19 detection are required as alternate methods, therefore an automatic method of Covid-19 detection using Convolutional Neural Networks (CNN) has been proposed. Three publically available and a locally developed dataset, obtained from Department of Radiology (Diagnostics), Bahawal Victoria Hospital, Bahawalpur (BVHB), Pakistan have been used. The proposed method achieved on average accuracy (96.68 %), specificity (95.65 %), and sensitivity (96.24 %). Proposed model is trained on a large dataset and is being used at the Radiology Department, (BVHB), Pakistan.

Comparison of acute and chronic effects of Bacopa monnieri, Ginkgo biloba, and Lavandula angustifolia and their mixture on learning and memory in mice.

Forty-seven million people are living with memory-related disorders worldwide. Phytomedicines are gaining extensive interest in the treatment of these ailments. Memory-enhancing (acute and chronic) potentials of commercial grade extracts of Bacopa monnieri (200 mg/kg, po), Ginkgo biloba (150 mg/kg, po), and Lavandula angustifolia (200 mg/kg, po) and their mixture (B. monnieri 100 mg/kg, G. biloba 75 mg/kg, and L. angustifolia 100 mg/kg, po) were compared for their synergistic/additive effects on the Morris water maze (MWM) test and elevated plus maze (EPM) test in scopolamine-induced amnesia in mice. Escape latency and accumulative path length were significantly reduced both in acute (up to day 6) and chronic trials (days 8-14) in B. monnieri-, G. biloba-, and L. angustifolia-treated animals and their mixtures (n = 8, p < .05) in MWM. Furthermore, in probe trials (acute on day 7 and chronic on day 15), the number of crossing-overs at platform position and time spent in platform quadrant were significantly increased, while transfer latency in EPM was decreased in treated animals as compared to the saline group (n = 8, p < .05). The mixture showed synergistic effects on memory enhancement as compared to each extract individually in mice. Further studies may be carried out on the active compounds of B. monnieri at the cellular and molecular levels.

Reconfiguring and ramping-up ventilator production in the face of COVID-19: Can robots help?

As the COVID-19 pandemic expands, the shortening of medical equipment is swelling. A key piece of equipment getting far-out attention has been ventilators. The difference between supply and demand is substantial to be handled with normal production techniques, especially under social distancing measures in place. The study explores the rationale of human-robot teams to ramp up production using advantages of both the ease of integration and maintaining social distancing. The paper presents a model for faster integration of collaborative robots and design guidelines for workstations. The scenario is evaluated for an open source ventilator through continuous human-robot simulation and amplification of results in a discrete event simulation.

Repurposing factories with robotics in the face of COVID-19.

Can collaborative robots ramp up the production of medical ventilators?

Genome-wide association mapping in bread wheat subjected to independent and combined high temperature and drought stress.

Most investigations to date aiming to identify the genetic basis of the stress response of wheat (Triticum aestivum L.) have focused on the response to single stress agents such as high temperature or drought, even though in the natural situation, these stresses tend often to occur together. Here, a panel of 108 spring type bread wheat cultivars was phenotyped for 15 yield and yield related traits for two years (2014/15 and 2015/16) under non-stressed conditions, under high temperature stress, under drought and under a combined high temperature and drought regime. The mean loss in grain yield caused by all stress regimes was 51.33%. Analysis of variance (ANOVA) of yield trait showed significant differences among genotypes environments and their interactions (G×E). All the studied traits had higher heritability values which ranged from 0.35-0.94 under [C], 0.58-0.95 under [D], 0.62-0.93 under [H] and 0.60-0.95 under [HD]. GWAS was performed by using 9,646 informative SNP markers and based on these polymorphic SNPs population structure analysis divided whole germplasm into five major sub-populations. Mixed model association analysis detected 503 marker-trait associations (MTAs) at P ≤0.001 while 329 MTAs crossed FDR ≤ 0.05 for all traits with phenotypic variances (R2) ranged from 24.83% to 12.51%. Seven new pleiotropic SNPs on chromosome 7D and IAAV8258 (86.91cM) and wsnp_Ex_c7168_12311649 (57.93cM) on chromosome 5A were most stable association in present study. Furthermore, candidate genes Psy and Sr25 (TG0040) were also significant in present study, these genes were previously mapped on 7A and 7D. The region on 7D was assiociated with 7DL.7Ag translocation from Lophopyrum carring rust resistance Yr16 and many other genes. Similarly region on chromosome 7A which was associated with Psy gene was linked with grain yellow pigment content QTLs. Favourable alleles controlling grain yield were of vital importance and incorporation of these alleles after validation through marker assisted selection and fine mapping could be helpful in wheat yield improvement stress and non-stress conditions.