Histone Deacetylase 3 Is Required for Development and Metamorphosis in the Red Flour Beetle, \u3cem\u3eTribolium castaneum\u3c/em\u3e

Background Hormones are chemical communication signaling molecules released into the body fluids to stimulate target cells of multicellular organisms. We recently showed that histone deacetylase 1 (HDAC1) plays an important role in juvenile hormone (JH) suppression of metamorphosis in the red flour beetle, Tribolium castaneum. Here, we investigated the function of another class I HDAC member, HDAC3, and show that it is required for the normal development of T. castaneum. Results RNA interference-mediated knockdown of the HDAC3 gene affected development resulting in abnormally folded wings in pupae and adults. JH analog, hydroprene, suppressed the expression of HDAC3 in T. castaneum larvae. The knockdown of HDAC3 during the final instar larval stage resulted in an increase in the expression of genes coding for proteins involved in JH action. Sequencing of RNA isolated from larvae injected with dsRNA targeting malE (E. coli gene, control) or HDAC3 followed by differential gene expression analysis identified 148 and 741 differentially expressed genes based on the P-value \u3c 0.01 and four-fold difference, and the P-value \u3c 0.05 and two-fold difference, respectively. Several genes, including those coding for myosin-I heavy chain (Myosin 22), Shaven, and nuclear receptor corepressor 1 were identified as differentially expressed genes in HDAC3 knockdown larvae. An increase in histone H3 acetylation, specifically H3K9, H3K18, and H3K27, was detected in HDAC3 knockdown insects. Conclusion Overall, these data suggest that HDAC3 affects the acetylation levels of histones and influences the expression of genes coding for proteins involved in the regulation of growth, development, and metamorphosis

Techniques of deep learning and image processing in plant leaf disease detection: a review

Computer vision techniques are an emerging trend today. Digital image processing is gaining popularity because of the significant upsurge in the usage of digital images over the internet. Digital image processing is a practice that can help in designing sophisticated high-end machines, which can hold the ophthalmic functionality of the human eye. In agriculture, leaf examination is important for disease identification and fair warning for any deficiency within the plant. Many prominent plant species are facing extinction because of a lack of knowledge. A proper realization of computer vision techniques aid in extracting a significant amount of information from leaf image. This necessitates the requirement of an automatic leaf disease detection method to diagnose disease occurrences and severity, for timely crop management, by spraying pesticides. This study focuses on techniques of digital image processing and machine learning rendered in plant leaf disease detection, which has great potential in precision agriculture. To support this study, techniques exercised by various researchers in recent years are tabulated

Antidiabetic, Antihyperlipidemic and Antioxidant Activities of Buchanania lanzan Spreng Methanol Leaf Extract in Streptozotocin-Induced Types I and II Diabetic Rats

Purpose: To evaluate the antidiabetic, antihyperlipidemic and antioxidant activities of Buchanania lanzan.Methods: Wistar rats were divided into nine groups of six animals each, and 40 mg/kg of streptozotocin or streptozotocin + nicotinamide was administered intraperitonially to induce types I and II diabetes. Those with blood glucose levels > 190 ± 8 mg/dl were administered the methanol leaf extract of Buchanania lanzan (MEBL, 100 or 200 mg/kg, p.o.) or positive control for 21 days. Blood glucose, lipid profile, antioxidant enzymes and oxidative stress markers were evaluated.Results: Following induction, blood glucose level rose to 327.7 ± 47.4 mg/dl, compared to the normal value of 910 ± 3.2 mg/dl. Administration of MEBL (100 or 200 mg/kg) significantly (p < 0.05) decreased blood glucose level, serum lipid profile, and significantly (p < 0.05) increased antioxidant activity as evidenced by increase in super oxide dismutase (SOD), catalas, glutathione (GSH), and decrease in the activity of lipid peroxidation (LPO).Conclusion: MEBL exhibits antidiabetic, antihyperlipidemic and antioxidant activities in diabetic rat and needs to be further investigated for the treatment of both types I and II diabetes mellitus.Keywords: Antidiabetic, Antihyperlipidemic, Antioxidant, Buchanania lanzan

Sustainable Production of Algal Biodiesel Using Chlorella Pyrenoidosa

The excessive consumption and utilization of fossil fuels, has had deleterious effect on the global fuel supply. It also has a detrimental effect on the environment, a growing concern in the last century. The key is in finding alternative and sustainable fuel sources, such as Biodiesel, and their efficient production and utilization to meet the surplus demand. Food crops and Microalgae have been identified to be potent producers of biodiesel. Microalgae trump the food crops on account of higher fatty acid content, that aid in the synthesis of biodiesel. In this study, we have utilized the microalgae, Chlorella pyrenoidosa as a source, having a high lipid content. The microalgae was cultured under optimal conditions and the extraction of the oil rich constituents was done by sonication. Further, trans-esterification was carried out to produce biodiesel. We then characterized the fuel based on its Saponification value, thin layer chromatography, types of fatty

Livelihood gains and ecological costs of NTFP dependence: assessing the roles of dependence, ecological knowledge and market structure in three contrasting human and ecological settings in south India

Non-timber forest products (NTFPs) constitute the single largest determinant of livelihoods for scores of forest fringe communities and poor people in the tropics. In India over 50 million people are believed to be directly dependent upon NTFPs for their subsistence. However, such human dependence on NTFPs for livelihood gains (win) has most frequently been at a certain ecological cost (lose). If livelihoods are to be maintained, the existing ‘win-lose’ settings have to be steered to a ‘win-win’ mode, otherwise, there could be severe erosion of the biological resources and loss of livelihoods (‘lose-lose’). Examining the dependence of forest fringe communities on NTFPs at three sites in south India with contrasting human and ecological settings, three key factors (extent of dependence on NTFPs, indigenous ecological knowledge and market organization) are likely to constrain reaching the win-win situation. How these factors shape the ecological cost of harvesting NTFPs at the three sites is examined. Within the parameter space of these factors, it is possible to predict outcomes and associations that will conform to win-win or win-lose situations. Empirical data derived from the three study sites demonstrate the causality of the observed associations. The key for long-term livelihood gains lies in reducing the ecological cost. Certain interventions and recommendations that could optimize the balance between livelihood gains and ecological cost are proposed

Robotic surgery a boon in medical science

Objectives: To compare the outcomes of robotic assisted laparoscopic versus open hysterectomy with pelvic lymphadenectomy in endometrial cancer. Methods: Prospective analysis done for the two cohorts underwent hysterectomy with lymphadenectomy by open and robotic assisted route in the duration of May 2012 to April 2014. The analysis done for patient demographics, operative time, blood loss, complications, conversion rate, and length of hospital stay. Conclusion: Robotic assisted route for hysterectomy can replace open technique because it provides better vision, easy access in lymph node dissection, less morbidity in view of less blood loss, short hospital stay and minimal usage of analgesics as compared to open technique. But there are limitation of the technique, because of its high cost and monopoly

A Machine learning Classification approach for detection of Covid 19 using CT images

Coronavirus disease 2019 popularly known as COVID 19 was first found in Wuhan, China in December 2019. World Health Organization declared Covid 19 as a transmission disease. The symptoms were cough, loss of taste, fever, tiredness, respiratory problem. These symptoms were likely to show within 11 –14 days. The RT-PCR and rapid antigen biochemical tests were done for the detection of COVID 19. In addition to biochemical tests, X-Ray and Computed Tomography (CT) images are used for the minute details of the severity of the disease. To enhance efficiency and accuracy of analysis/detection of COVID images and to reduce of doctors' time for analysis could be addressed through Artificial Intelligence. The dataset from Kaggle was utilized to analyze. The statistical and GLCM features were extracted from CT images for the classification of COVID and NON-COVID instances in this study. CT images were used to extract statistical and GLCM features for categorization. In the proposed/prototype model, we achieved the classification accuracy of 91%, and 94.5% using SVM and Random Forest respectively

A road map for the generation of a near-infrared guide star catalog for thirty meter telescope observations

The near-infrared instruments in the upcoming Thirty Meter Telescope (TMT) will be assisted by a multi conjugate Adaptive Optics (AO) system. For the efficient operation of the AO system, during observations, a near-infrared guide star catalog which goes as faint as 22 mag in JVega band is essential and such a catalog does not exist. A methodology, based on stellar atmospheric models, to compute the expected near-infrared magnitudes of stellar sources from their optical magnitudes is developed. The method is applied and validated in JHKs bands for a magnitude range of JVega 16–22 mag. The methodology is also applied and validated using the reference catalog of PAN STARRS. We verified that the properties of the final PAN STARRS optical catalog will satisfy the requirements of TMT IRGSC and will be one of the potential sources for the generation of the final catalog. In a broader context, this methodology is applicable for the generation of a guide star catalog for any existing/upcoming near-infrared telescopes

Propagation of pure fetal and maternal mesenchymal stromal cells from terminal chorionic villi of human term placenta

Long term propagation of human fetal Mesenchymal Stromal Cells (MSC) in vitro has proven elusive due to limited availability of fetal tissue sources and lack of appropriate methodologies. Here, we have demonstrated the presence of fetal and maternal cells within the tips of Terminal Chorionic Villi (TCV) of normal human term placenta and we have exploited inherent differences in the adhesive and migratory properties of maternal vs. fetal cells, to establish pure MSC cultures of both cell types. The origin and purity of each culture was confirmed by X-Y chromosome-specific Fluorescence In Situ Hybridization (FISH) and Short Tandem Repeat (STR) genotyping. This is the first demonstration of fetal and maternal cells in the TCV of human term placenta and also of deriving pure fetal MSC cultures from them. The concomitant availability of pure cultures of adult and fetal MSC from one tissue provides a good system to compare genetic and epigenetic differences between adult and fetal MSCs and also to generate new models of cell based therapies in regenerative medicine