Transcriptome analysis provides insights for understanding the adverse effects of endosulfan in Drosophila melanogaster

Indiscriminate use of agrochemicals worldwide, particularly, persistent organic pollutants (POPs), is of concern. Endosulfan, a POP, is used by various developing/developed nations and is known to adversely affect the development and the hormonal profiles of humans and animals. However, little is known about the molecular players/pathways underlying the adverse effects of endosulfan. We therefore analyzed the global gene expression changes and subsequent adverse effects of endosulfan using Drosophila. We used Drosophila melanogaster keeping in view of its well annotated genome and the wealth of genetic/molecular reagents available for this model organism. We exposed third instar larvae of D. melanogaster to endosulfan (2.0 μg mL⁻¹) for 24 h and using microarray, we identified differential expression of 256 genes in exposed organisms compared to controls. These genes are associated with cellular processes such as development, stress and immune response and metabolism. Microarray results were validated through quantitative PCR and biochemical assay on a subset of genes/proteins. Taking cues from microarray data, we analyzed the effect of endosulfan on development, emergence and survival of the organism. In exposed organisms, we observed deformities in hind-legs, reminiscent of those observed in higher organisms exposed to endosulfan. In addition, we observed delayed and/or reduced emergence in exposed organisms when compared to their respective controls. Together, our studies not only highlight the adverse effects of endosulfan on the organism but also provide an insight into the possible genetic perturbations underlying these effects, which might have potential implications to higher organisms.     

An evaluation of the dissimilarity in heat and momentum transport through quadrant analysis for an unstable atmospheric surface layer flow

Environmental Fluid Mechanics - To elucidate the role of each fluid motion in the transport of momentum and heat fluxes in an unstable atmospheric surface layer (ASL) flow from single point...     

Correction to: Water‑induced erosion potentiality and vulnerability assessment in Kangsabati river basin,eastern India

Environment, Development and Sustainability -     

New particle formation observed from a rain shadow region of the Western Ghats,India

Abstract

This study reports on new particle formation (NPF) and characteristic features observed from a rural site falling in the rainshadow of the Western Ghats in peninsular India. A total of 35 NPF events observed during August 2018 - January 2019 are classified and analyzed here. The apparent formation rates ranged from 0.2 to 10.0?cm^–3 s^–1, while the growth rates of nucleation mode particles ranged from 1.2 to 13.8?nm h^–1. The frequency of occurrence was least during August (core monsoon) and highest during post-monsoon. The local winds were calm and southeasterly to easterly (from the urban centre) supplying the essential precursor gases during October and November, leading to a frequent occurrence of nucleation events. Observations suggest that an increased condensation sink could limit the NPF while promoting Aitken mode growth. The newly formed particles accounted for about 10–80% of the total aerosol concentration. These newly formed particles were able to act as cloud condensation nuclei after growing to approximately 50?nm with an average activation fraction of 0.4.     

Unravelling the turbulent structures of temperature variations during a gust front event: a case study

Environmental Fluid Mechanics - The simultaneous observations from a Doppler weather radar and an instrumented micrometeorological tower, offer an opportunity to dissect the effects of a gust front...     

Water-induced erosion potentiality and vulnerability assessment in Kangsabati river basin,eastern India

Environment, Development and Sustainability - The large-scale water-induced erosion is one of the most determining elements on land degradation in subtropical monsoon-dominated region. From this...     

GIS-based statistical model for the prediction of flood hazard susceptibility

At present, flood is the most significant environmental problem in the entire world. In this work, flood susceptibility (FS) analysis has been done in the Dwarkeswar River basin of Bengal basin, India. Fourteen flood causative factors extracted from different datasets like DEM, satellite images, geology, soil and rainfall data have been considered to predict FS. Three heuristic models and one statistical model fuzzy Logic (FL), frequency ratio (FR), multi-criteria decision analysis (MCDA) and logistic regression (LR) have been used. The validating datasets are used to validate these models. The result shows that 68.71%, 68.7%, 60.56% and 48.51% area of the basin is under the moderate to very high FS by the MCDA, FR, FL and LR, respectively. The ROC curve with AUC analysis has shown that the accuracy level of the LR model (AUC?=?0.916) is very much successful to predict the flood. The rest of the models like FL, MCDA and FR (AUC?=?0.893, 0.857 and 0.835, respectively) have lesser accuracy than the LR model. The elevation was the most dominating factor with coefficient value of 19.078 in preparation of the FS according to the LR model. The outcome of this study can be implemented by local and state authority to minimize the flood hazard.