Angiotensin type 1a receptor-deficient mice develop diabetes-induced cardiac dysfunction, which is prevented by renin-angiotensin system inhibitors

BACKGROUND: Diabetes-induced organ damage is significantly associated with the activation of the renin-angiotensin system (RAS). Recently, several studies have demonstrated a change in the RAS from an extracellular to an intracellular system, in several cell types, in response to high ambient glucose levels. In cardiac myocytes, intracellular angiotensin (ANG) II synthesis and actions are ACE and AT(1) independent, respectively. However, a role of this system in diabetes-induced organ damage is not clear. METHODS: To determine a role of the intracellular ANG II in diabetic cardiomyopathy, we induced diabetes using streptozotocin in AT(1a) receptor deficient (AT(1a)-KO) mice to exclude any effects of extracellular ANG II. Further, diabetic animals were treated with a renin inhibitor aliskiren, an ACE inhibitor benazeprilat, and an AT(1) receptor blocker valsartan. RESULTS: AT(1a)-KO mice developed significant diastolic and systolic dysfunction following 10 wks of diabetes, as determined by echocardiography. All three drugs prevented the development of cardiac dysfunction in these animals, without affecting blood pressure or glucose levels. A significant down regulation of components of the kallikrein-kinin system (KKS) was observed in diabetic animals, which was largely prevented by benazeprilat and valsartan, while aliskiren normalized kininogen expression. CONCLUSIONS: These data indicated that the AT(1a) receptor, thus extracellular ANG II, are not required for the development of diabetic cardiomyopathy. The KKS might contribute to the beneficial effects of benazeprilat and valsartan in diabetic cardiomyopathy. A role of intracellular ANG II is suggested by the inhibitory effects of aliskiren, which needs confirmation in future studies

Ion Selectivity in Multilayered Stacked Nanoporous Graphene

Nanoporous graphene is an ideal candidate for molecular filtration as it can potentially combine high permeability with high selectivity at molecular levels. To make use of graphene in filtration setups, the defects formed during its growth and during the transfer of graphene to the carrier support pose a challenge. These uncontrolled pores can be avoided by stacking graphene layers, and then, controlled pores can be initiated with oxygen plasma. Here, we show that two-layer stacks provide the best balance of defect coverage and high selectivity compared with other stacks. Using the electrical characterization of ionic solutions in the standard diffusion cell, we compare the ionic transport and ionic selectivity of up to three-layered stacks of graphene that have been plasma-treated. We find that there is a decrease in the ionic selectivity of a two-layered stack as one more layer of graphene is added. We provide a model for this occurrence. Our results will be helpful for making practical and high-performance filtration systems from two-dimensional materials

Rice crop yield prediction in India using support vector machines

Food production in India is largely dependent on cereal crops including rice, wheat and various pulses. The sustainability and productivity of rice growing areas is dependent on suitable climatic conditions. Variability in seasonal climate conditions can have detrimental effect, with incidents of drought reducing production. Developing better techniques to predict crop productivity in different climatic conditions can assist farmer and other stakeholders in better decision making in terms of agronomy and crop choice. Machine learning techniques can be used to improve prediction of crop yield under different climatic scenarios. This paper presents the review on use of such machine learning technique for Indian rice cropping areas. This paper discusses the experimental results obtained by applying SMO classifier using the WEKA tool on the dataset of 27 districts of Maharashtra state, India. The dataset considered for the rice crop yield prediction was sourced from publicly available Indian Government records. The parameters considered for the study were precipitation, minimum temperature, average temperature, maximum temperature and reference crop evapotranspiration, area, production and yield for the Kharif season (June to November) for the years 1998 to 2002. For the present study the mean absolute error (MAE), root mean squared error (RMSE), relative absolute error (RAE) and root relative squared error (RRSE) were calculated. The experimental results showed that the performance of other techniques on the same dataset was much better compared to SMO

An automated chemical vapor deposition setup for 2D materials

Chemical vapour deposition (CVD) provides a versatile and scalable route to synthesize various 2D materials. Lowering the barrier for access, customization, and cost of CVD equipment will benefit a large and multidisciplinary research community. We report an open-source and automated CVD setup which can be built incrementally to cover a large parameter space of CVD growth. Extensions are also discussed. The setup was validated by CVD graphene growth and characterization on Cu foils. The software controller forms a crucial part of the system. Its plug-in based approach for devices and abstraction of interactions as structured text, enables easy automation, extension, and accessibility. These features also allow the same controller core to be used for control of diverse laboratory equipment, of which we provide a couple of examples. Together, the hardware and software design provides an easy and versatile package for CVD setup, which can also be a starting point for several other automated instruments

Impact of Herbicides on Soil Fertility and Nutrient Uptake by Transplanted Rice (Oryza sativa L.) in Eastern U.P, India

A field experiment was carried out at Agricultural Research Farm, Institute of Agricultural Sciences, Varanasi during kharif 2017 and 2018 to evaluate the nitrogen intake by transplanted rice (Oryza sativa L.) and the available nutrient status of soil under ten weed control treatments. The treatment bispyribac-Na 9.1% (24.57 g/ha) + metsulfuron-methyl 1.2% (3.24 g/ha) + chlorimuron ethyl 1.2% (3.24 g/ha) recorded higher Organic carbon (0.47%), pH (7.38), EC(0.18 dS m-1), available N193.48 kg/ha, P22.46 kg/ha, and K 221.56 kg/ha in soil, higher nutrient (N, P and K)  content in grain 1.14, 0.33, 0.38%,  and straw  0.74, 0.12, 1.74% and protein content 6.81 & 4.42% in grain and straw, respectively. improved N, P, K uptake in grain 58.57, 17.06, 19.23 kg/ha and straw 71.00, 11.36, 166 kg/ha, respectively over weedy check (grain 46.09, 13.35, 15.10 kg/ha and straw 58.58, 9.38 and 137.65 N, P and K respectively). This treatment exhibited positive performance of soil fertility and N, P and K uptake by transplanted rice

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Not AvailableImprovement of nutrient use efficiency in cereal crops is highly essential not only to reduce the cost of cultivation but also to save the environmental pollution, reduce energy consumption for production of these chemical fertilizers, improve soil health, and ultimately help in mitigating climate change. In the present investigation, we have studied the morphological (with special emphasis on root system architecture) and biochemical responses (in terms of assay of the key enzymes involved in N assimilation) of two N-responsive wheat genotypes, at the seedling stage, under nitrate-optimum and nitrate-starved conditions grown in hydroponics. Expression profile of a few known wheat micro RNAs (miRNAs) was also studied in the root tissue. Total root size, primary root length, and first- and second-order lateral root numbers responded significantly under nitrate-starved condition. Morphological parameters in terms of root and shoot length and fresh and dry weight of roots and shoots have also been observed to be significant between N-optimum and N-starved condition for each genotypes. Nitrate reductase (NR), glutamine synthatase (GS), and glutamate dehydrogenase (GDH) activity significantly decreased under N-starved condition. Glutamine oxoglutarate amino transferase (GOGAT) and pyruvate kinase (PK) activity was found to be genotype dependent. Most of the selected miRNAs were expressed in root tissues, and some of them showed their differential N-responsive expression. Our studies indicate that one of the N-responsive genotype (NP-890) did not get affected significantly under nitrogen starvation at seedling stage.Not Availabl

Effect of Continuous Application of Nitrogen, Phosphorus and Potassium on Growth Parameters and Yield of Rice

A Long term (37 years) field experiment was conducted at Agronomical Research farm of Birsa Agricultural University, Kanke, Ranchi during Kharif season in 2020 to study the effect of Nitrogen, phosphorus and potassium on growth parameter and yield of rice. The experiment was conducted in Partially Confounded Design with nineteen treatments replicated four times. The rice variety used was Sahabhagi Dhan. Nitrogen, Phosphorus and potassium level used were 40, 80 and 120 kg N ha-1, 0, 40 and 80 kg P2O5 ha-1 and 0 and 40 kg K2O ha-1.Application of 120 kg N ha-1, 80 kg P kg P2O5 ha-1 and 40 kg K2O ha-1 significantly increased plant height, produced maximum numbers of tillers, dry matter and leaf area index at 30, 60, 90 DAS and at harvest. The maximum grain and straw yield was recorded under with application of 120 kg N ha-1, 80 kg P kg P2O5 ha-1 and 40 kg K2O ha-1

Stability assessment of selected chrysanthemum (Dendranthema grandiflora Tzvelev) hybrids over the years through AMMI and GGE biplot in the mid hills of North-Western Himalayas

Abstract Dendranthema grandiflora is an important cut flower with high economic importance in the floriculture industry. Identification of stable and high yielding genotypes of Dendranthema grandiflora, hence becomes paramount for ensuring its year-round production. In this context, the genotype by environment interaction effects on 22 chrysanthemum hybrids across six test environments were investigated. The experiment was conducted using Randomized Complete Block Design with three replications for 6 years and data on various agro-morphological and yield-contributing traits were evaluated. Our analysis revealed significant mean sum of squares due to environmental, genotypic and genotype by environment interaction variations for all examined traits. A 2D GGE biplot constructed using first two principal components computed as 59.2% and 23.3% of the differences in genotype by environment interaction for flower yield per plant. The GGE biplot identified two top-performing genotypes, G2 and G5, while the AMMI model highlighted genotypes G17, G15, G6, G5, and G2 as the best performers. Genotype G17 ranked highest for multiple traits, while G2 displayed high mean flower yield as well as stability across all environments. According to AEC line, genotypes G2 and G5 exhibited exceptional stability, whereas genotypes G4, G18 and G19 demonstrated lower stability but maintained high average flower yields. Hence, our findings provide valuable insights into chrysanthemum hybrids that were not only best performing but also hold promise to meet the growers demand of the cut flower industry and can be recommended for large scale commercial cultivation