Identification and characterization of domain-specific inhibitors of DENV NS3 and NS5 proteins by in silico screening methods.

The dengue virus (DENV) infects approximately 400 million people annually worldwide causing significant morbidity and mortality. Despite advances in understanding the virus life cycle and infectivity, no specific treatment for this disease exists due to the lack of therapeutic drugs. In addition, vaccines available currently are ineffective with severe side effects. Therefore, there is an urgent need for developing therapeutics suitable for effective management of DENV infection. In this study, we adopted a drug repurposing strategy to identify new therapeutic use of existing FDA approved drug molecules to target DENV2 non-structural proteins NS3 and NS5 using computational approaches. We used Drugbank database molecules for virtual screening and multiple docking analysis against a total of four domains, the NS3 protease and helicase domains and NS5 MTase and RdRp domains. Subsequently, MD simulations and MM-PBSA analysis were performed to validate the intrinsic atomic interactions and the binding affinities. Furthermore, the internal dynamics in all four protein domains, in presence of drug molecule binding were assessed using essential dynamics and free energy landscape analyses, which were further coupled with conformational dynamics-based clustering studies and cross-correlation analysis to map the regions that exhibit these structural variations. Our comprehensive analysis identified tolcapone, cefprozil, delavirdine and indinavir as potential inhibitors of NS5 MTase, NS5 RdRp, NS3 protease and NS3 helicase functions, respectively. These high-confidence candidate molecules will be useful for developing effective anti-DENV therapy to combat dengue infection.Communicated by Ramaswamy H. Sarma.

Bringing revolution through quadcopter technology in the field of supplying medicine in the Himalayan regions of Uttarakhand: Case example of Pithoragarh.

BACKGROUND: Quadcopters are used in various forms in the civil arena, from crop insurance to agricultural drones, as loudspeakers for announcing government guidelines, resilience tools in infrastructure monitoring, real-time vehicle detection, etc. However, the usage of quadcopters and hexacopters in supplying medical aid to inhospitable and far-flung terrains is being studied and researched in less detail throughout the globe. AIM: This paper focuses on the basics of quadcopter technology in supplying medicines and its advantages to the affected patients who get life-saving medicines from earlier inaccessible roads. The efficacy of quadcopters in terms of time, economy, and manpower in supplying essential and inescapable medical supplies is exponentially high, especially in the Pithoragarh Region of Uttarakhand State, where the villages are not connected to the roads. METHODS: The road structure of the hilly terrain of Uttarakhand, India, was studied in detail to know the state of people who do not get access to life-saving drugs due to the non-availability of roads near them. RESULTS: The result informs us that the quad/hexacopter if used in abundance can provide a glimmer of hope to people in remote places. CONCLUSION: The quadcopter can provide hope to the residents of the Pithoragarh district of Uttarakhand, India, located in far-flung places devoid of basic medical facilities.

Effect of thermal annealing on an emissive layer containing a blend of a small molecule and polymer as host for application in OLEDs.

In order to improve the performance of OLEDs, a host-guest mixture was used as an emissive layer. To have better host properties, a mixture of different materials with suitable properties can also be used as a host. In this study, we used a mixture of a polymer and a small molecule as the host and studied the effect of thermal annealing on the emissive layer properties by using Ir(ppy)3 as the emitter. UV-visible absorption, steady-state and time-resolved photoluminescence, scanning electron microscopy, atomic force microscopy, and optical microscopic studies were performed to study the film properties. Devices were fabricated and their current-voltage and luminance-voltage characteristics were studied. Charge-carrier mobility in the devices was studied by dark CELIV and transient electroluminescence methods. We show that, below the glass transition temperature of the polymer, the small molecules formed aggregates due to thermal annealing, which was beneficial for the device performance in the lower-temperature range, mainly due to the improved electron mobility. However, this aggregate formation was detrimental in the higher-temperature range, as it led to inefficient energy transfer due to the increased pure phase formation. At temperatures above the glass transition temperature of the polymer, the small molecules were seen to be distributed more uniformly into the polymer matrix. However, as a result of the degradation of the polymer property due to degradation of the primary chain of the phenyl ring of the polymer, this uniform distribution was not of any use and the device performance deteriorated.

Validation of CRISPR activation system in Aedes cells using multicistronic plasmid vectors.

Aedes mosquitoes transmit several pathogens including flaviviruses to humans which result in high morbidity and mortality. Owing to adaptability and climate change, these mosquito vectors are predicted to establish in new geographical areas thus exposing larger populations to the risk of infection. Therefore, control of Aedes vector is necessary to prevent disease transmission. Recently, genetic approaches to vector control have shown promise; however, the tools and methods for manipulating the mosquito genome are rather limited. While CRISPR-Cas9 system has been adapted for gene editing purposes in Aedes mosquito, the dCas9-based transcription control of genes remain unexplored. In this study we report implementation of the CRISPR activation system in Aedes cells. For this we designed, constructed and tested a bi-partite plasmid-based strategy that allows expression of the dCas9-VPR and targeting guide RNA together with a reporter cassette. Quantitative analysis of the fluorescent reporter gene levels showed a robust over-expression validating CRISPR activation in Aedes cells. This strategy and the biological parts will be useful resource for synthetic transcription factor-based robust upregulation of Aedes genes for application of synthetic biology approaches for vector control.

Bayesian Adaptive Beamformer for Robust Electromagnetic Brain Imaging of Correlated Sources in High Spatial Resolution.

Reconstructing complex brain source activity at a high spatiotemporal resolution from magnetoencephalography (MEG) or electroencephalography (EEG) remains a challenging problem. Adaptive beamformers are routinely deployed for this imaging domain using the sample data covariance. However adaptive beamformers have long been hindered by 1) high degree of correlation between multiple brain sources, and 2) interference and noise embedded in sensor measurements. This study develops a novel framework for minimum variance adaptive beamformers that uses a model data covariance learned from data using a sparse Bayesian learning algorithm (SBL-BF). The learned model data covariance effectively removes influence from correlated brain sources and is robust to noise and interference without the need for baseline measurements. A multiresolution framework for model data covariance computation and parallelization of the beamformer implementation enables efficient high-resolution reconstruction images. Results with both simulations and real datasets indicate that multiple highly correlated sources can be accurately reconstructed, and that interference and noise can be sufficiently suppressed. Reconstructions at 2-2.5mm resolution (  âˆ¼  150K voxels) are possible with efficient run times of 1-3 minutes. This novel adaptive beamforming algorithm significantly outperforms the state-of-the-art benchmarks. Therefore, SBL-BF provides an effective framework for efficiently reconstructing multiple correlated brain sources with high resolution and robustness to interference and noise.

A joint subspace mapping between structural and functional brain connectomes.

Understanding the connection between the brain's structural connectivity and its functional connectivity is of immense interest in computational neuroscience. Although some studies have suggested that whole brain functional connectivity is shaped by the underlying structure, the rule by which anatomy constraints brain dynamics remains an open question. In this work, we introduce a computational framework that identifies a joint subspace of eigenmodes for both functional and structural connectomes. We found that a small number of those eigenmodes are sufficient to reconstruct functional connectivity from the structural connectome, thus serving as low-dimensional basis function set. We then develop an algorithm that can estimate the functional eigen spectrum in this joint space from the structural eigen spectrum. By concurrently estimating the joint eigenmodes and the functional eigen spectrum, we can reconstruct a given subject's functional connectivity from their structural connectome. We perform elaborate experiments and demonstrate that the proposed algorithm for estimating functional connectivity from the structural connectome using joint space eigenmodes gives competitive performance as compared to the existing benchmark methods with better interpretability.

ß-Cyclodextrin Stabilized Nanoceria for Hydrolytic Cleavage of Paraoxon in Aqueous and Cationic Micellar Media.

Beta-cyclodextrin (ß-CD) stabilized cerium oxide nanoparticles (ß-CD@CeO2 NPs) were synthesized through a hydrothermal route. The electronic properties, surface functional group, surface composition, size, and morphologies of the as-synthesized ß-CD@CeO2 NPs were characterized using UV-visible spectroscopy, FTIR analysis, high resolution X-ray photoelectron spectroscopy (HRXPS), high resolution transmission electron microscopy (HRTEM), and field emission scanning electron microscopy (FESEM). The pH-dependent variation of the ζ-potential of ß-CD@CeO2 NPs and the catalytic activity of the NPs for the hydrolysis of paraoxon were investigated. The observed pseudo-first-order rate constant (kobs) for the hydrolysis of paraoxon is increased with increasing pH and the ζ-potential of ß-CD@CeO2 NPs. The kinetics and mechanism of hydrolysis of paraoxon in the aqueous and cationic micellar media have been discussed.

Multi-tasking deep network for tinnitus classification and severity prediction from multimodal structural MR images.

Objective:Subjective tinnitus is an auditory phantom perceptual disorder without an objective biomarker. Fast and efficient diagnostic tools will advance clinical practice by detecting or confirming the condition, tracking change in severity, and monitoring treatment response. Motivated by evidence of subtle anatomical, morphological, or functional information in magnetic resonance images of the brain, we examine data-driven machine learning methods for joint tinnitus classification (tinnitus or no tinnitus) and tinnitus severity prediction.Approach:We propose a deep multi-task multimodal framework for tinnitus classification and severity prediction using structural MRI (sMRI) data. To leverage complementary information multimodal neuroimaging data, we integrate two modalities of three-dimensional sMRI-T1 weighted (T1w) and T2 weighted (T2w) images. To explore the key components in the MR images that drove task performance, we segment both T1w and T2w images into three different components-cerebrospinal fluid, grey matter and white matter, and evaluate performance of each segmented image.Main results:Results demonstrate that our multimodal framework capitalizes on the information across both modalities (T1w and T2w) for the joint task of tinnitus classification and severity prediction.Significance:Our model outperforms existing learning-based and conventional methods in terms of accuracy, sensitivity, specificity, and negative predictive value.

Joint Learning of Full-structure Noise in Hierarchical Bayesian Regression Models.

We consider the reconstruction of brain activity from electroencephalography (EEG). This inverse problem can be formulated as a linear regression with independent Gaussian scale mixture priors for both the source and noise components. Crucial factors influencing the accuracy of the source estimation are not only the noise level but also its correlation structure, but existing approaches have not addressed the estimation of noise covariance matrices with full structure. To address this shortcoming, we develop hierarchical Bayesian (type-II maximum likelihood) models for observations with latent variables for source and noise, which are estimated jointly from data. As an extension to classical sparse Bayesian learning (SBL), where across-sensor observations are assumed to be independent and identically distributed, we consider Gaussian noise with full covariance structure. Using the majorization-maximization framework and Riemannian geometry, we derive an efficient algorithm for updating the noise covariance along the manifold of positive definite matrices. We demonstrate that our algorithm has guaranteed and fast convergence and validate it in simulations and with real MEG data. Our results demonstrate that the novel framework significantly improves upon state-of-the-art techniques in the real-world scenario where the noise is indeed non-diagonal and fullstructured. Our method has applications in many domains beyond biomagnetic inverse problems.

In-vivo protein nitration facilitates Vibrio cholerae cell survival under anaerobic, nutrient deprived conditions.

Protein tyrosine nitration (PTN), a highly selective post translational modification, occurs in both prokaryotic and eukaryotic cells under nitrosative stress. However, its physiological function is not yet clear. Like many gut pathogens, Vibrio cholerae also faces nitrosative stress, which makes its proteome more vulnerable to PTN. Here, we report for the first time in-vivo PTN in V. cholerae by immunoblotting and LC-ESI-MS/MS proteomic analysis. Our results indicated that in-vivo PTN in V. cholerae was culture media independent. Surprisingly, in-vivo PTN was reduced in V. cholerae proteome under anaerobic or hypoxic condition in a nutrient deprived state. Interestingly, intracellular nitrate content was more than the nitrite content in V. cholerae under anaerobic conditions. Additionally, biochemical measurement of GSH/GSSG ratio, activities of catalase and SOD, ROS and RNS imaging by confocal microscopy confirmed a relative intracellular oxidizing environment in V. cholerae under anaerobic conditions. This altered redox environment favors the oxidation of nitrite which may be generated from protein denitration enriching the intracellular nitrate pool. The cell survival of V. cholerae can finally be facilitated by nitrate reductase (NapA) utilizing that nitrate pool. Our cell viability study using wild type and ΔnapA strain of V. cholerae also supported the role of NapA mediated cell survival under nutrient deprived anaerobic conditions. In spite of having nitrate reductase (NapA), V. cholerae lacks any nitrite reductase (NiR). Hence, in-vivo nitration may provide an avenue for toxic nitrite storage and also may help in nitrosative stress tolerance mechanism preventing further unnecessary protein nitration in V. cholerae proteome.

Secretome Analysis of Macrophomina phaseolina Identifies an Array of Putative Virulence Factors Responsible for Charcoal Rot Disease in Plants.

Macrophomina phaseolina is a global devastating necrotrophic fungal pathogen. It causes charcoal rot disease in more than 500 host plants including major food crops, pulse crops, fiber crops, and oil crops. Despite having the whole-genome sequence of M. phaseolina, understanding the M. phaseolina genome-based plant-pathogen interactions is limited in the absence of direct experimental proof of secretion. Thus, it is essential to understand the host-microbe interaction and the disease pathogenesis, which can ensure global agricultural crop production and security. An in silico-predicted secretome of M. phaseolina is unable to represent the actual secretome. We could identify 117 proteins present in the secretome of M. phaseolina using liquid chromatography-electrospray ionization-tandem mass spectrometry. Data are available via ProteomeXchange with identifier PXD032749. An array of putative virulence factors of M. phaseolina were identified in the present study using solid-state culture. Similar virulence factors have been reported in other plant pathogenic fungi also. Among the secretory fungal proteins with positive economic impacts, lignocellulolytic enzymes are of prime importance. Further, we validated our results by detecting the cell wall-degrading enzymes xylanase, endoglucanase, and amylase in the secretome of M. phaseolina. The present study may provide a better understanding about the necrotrophic fungi M. phaseolina, which modulate the host plant defense barriers using secretory proteins.

Secretome analysis identified extracellular superoxide dismutase and catalase of Macrophomina phaseolina.

Macrophomina phaseolina, a necrotrophic fungal pathogen is known to cause charcoal rot disease in food crops, pulse crops, oil crops and cotton and fibre crops. Necrotrophic fungi survive on dead plant tissue. It is well known that reactive oxygen species (ROS) are produced by the host plant during plant-pathogen interaction. However, it is still unclear how M. phaseolina can overcome the ROS-induced cellular damage. To mimic the invasion of M. phaseolina inside the plant cell wall, we developed solid substrate fermentation where M. phaseolina spore suspension was inoculated on a wheat bran bed and incubated for vegetative growth. To analyse the secretome of M. phaseolina after different day interval, its secretory material was collected and concentrated. Both superoxide dismutase (SOD) and catalase were detected in the secretome by zymogram. The presence of SOD and catalase was further confirmed by liquid chromatography based mass spectrometry. The physicochemical properties of M. phaseolina catalase in terms of stability towards pH, temperature, metal ions and chaotropic agent and inhibitors indicated its fitness at different environmental conditions. Apart from the production of catalase in SSF, the studies on this particular microorganism may also have significance in necrotrophic fungal pathogen and their susceptible host plant interaction.

Validation of absolute point dosimetry by the analytical anisotropic algorithm and Acuros XB algorithm employing intensity-modulated radiotherapy technique on an in-house develop cost-effective heterogeneous thorax phantom.

INTRODUCTION: Dose validation inside the human body needs a medium which can simulate the actual heterogeneities of a specific body site. The aim of the present work is to study the properties of a cost-effective heterogeneous thorax phantom (HTP) developed in-house by the author and its application for the evaluation of patient-specific absolute point dosimetry by employing analytic anisotropic algorithm (AAA) and Acuros XB (AXB) algorithm. MATERIALS AND METHODS: HTP was made from the dust of porous pinewood, rib cage, and honeybee's wax. Density and central axis isodose depth distribution was measured on computed tomography images of actual patient and on HTP. Absolute point dose verification of 35 patients was done using AAA and AXB algorithm. The difference in the calculated dose by AAA and AXB was compared using the Wilcoxon signed-rank test. RESULTS: Density distribution and central axis depth dose inside the HTP compare well with that of an actual patient. The mean percentage variation between the planned and the measured doses inside the HTP was found to be 4.85 (standard deviation [SD] = 3.38) and 1.3 (SD = 2.93), respectively, using AAA and AXB algorithm. The difference in the measured dose and the planned dose was found to be significant for AAA with the significance level of 0.01 (p-value < 0.00001), whereas it was found to be insignificant (p-value < 0.00001) for AXB. CONCLUSION: The results of this study showed that the HTP is resembled with the human thorax in terms of its heterogeneities and radiological properties and can be used for pretreatment plan verification.

RDD2020: An annotated image dataset for automatic road damage detection using deep learning.

This data article provides details for the RDD2020 dataset comprising 26,336 road images from India, Japan, and the Czech Republic with more than 31,000 instances of road damage. The dataset captures four types of road damage: longitudinal cracks, transverse cracks, alligator cracks, and potholes; and is intended for developing deep learning-based methods to detect and classify road damage automatically. The images in RDD2020 were captured using vehicle-mounted smartphones, making it useful for municipalities and road agencies to develop methods for low-cost monitoring of road pavement surface conditions. Further, the machine learning researchers can use the datasets for benchmarking the performance of different algorithms for solving other problems of the same type (image classification, object detection, etc.). RDD2020 is freely available at [1]. The latest updates and the corresponding articles related to the dataset can be accessed at [2].

Ribosome profiling reveals ribosome stalling on tryptophan codons and ribosome queuing upon oxidative stress in fission yeast.

Translational control is essential in response to stress. We investigated the translational programmes launched by the fission yeast Schizosaccharomyces pombe upon five environmental stresses. We also explored the contribution of defence pathways to these programmes: The Integrated Stress Response (ISR), which regulates translation initiation, and the stress-response MAPK pathway. We performed ribosome profiling of cells subjected to each stress, in wild type cells and in cells with the defence pathways inactivated. The transcription factor Fil1, a functional homologue of the yeast Gcn4 and the mammalian Atf4 proteins, was translationally upregulated and required for the response to most stresses. Moreover, many mRNAs encoding proteins required for ribosome biogenesis were translationally downregulated. Thus, several stresses trigger a universal translational response, including reduced ribosome production and a Fil1-mediated transcriptional programme. Surprisingly, ribosomes stalled on tryptophan codons upon oxidative stress, likely due to a decrease in charged tRNA-Tryptophan. Stalling caused ribosome accumulation upstream of tryptophan codons (ribosome queuing/collisions), demonstrating that stalled ribosomes affect translation elongation by other ribosomes. Consistently, tryptophan codon stalling led to reduced translation elongation and contributed to the ISR-mediated inhibition of initiation. We show that different stresses elicit common and specific translational responses, revealing a novel role in Tryptophan-tRNA availability.

High rise in carbonaceous aerosols under very low anthropogenic emissions over eastern Himalaya, India: Impact of lockdown for COVID-19 outbreak.

The present study has been conducted to investigate the relative changes of carbonaceous aerosols (CA) over a high altitude Himalayan atmosphere with and without (very low) anthropogenic emissions. Measurements of atmospheric organic (OC) and elemental carbon (EC) were conducted during the lockdown period (April 2020) due to global COVID 19 outbreak and compared with the normal period (April 2019). The interesting, unexpected and surprising observation is that OC, EC and the total CA (TCA) during the lockdown (OC: 12.1 ± 5.5 µg m-3; EC: 2.2 ± 1.1 µg m-3; TCA: 21.5 ± 10 µg m-3) were higher than the normal period (OC: 7.04 ± 2.2 µg m-3; EC: 1.9 ± 0.7 µg m-3; TCA: 13.2 ± 4.1 µg m-3). The higher values for OC/EC ratio too was observed during the lockdown (5.7 ± 0.9) compared to the normal period (4.2 ± 1.1). Much higher surface O3 during the lockdown (due to very low NO) could better promote the formation of secondary OC (SOC) through the photochemical oxidation of biogenic volatile organic compounds (BVOCs) emitted from Himalayan coniferous forest cover. SOC during the lockdown (7.6 ± 3.5 µg m-3) was double of that in normal period (3.8 ± 1.4 µg m-3). Regression analysis between SOC and O3 showed that with the same amount of increase in O3, the SOC formation increased to a larger extent when anthropogenic emissions were very low and biogenic emissions dominate (lockdown) compared to when anthropogenic emissions were high (normal). Concentration weighted trajectory (CWT) analysis showed that the anthropogenic activities over Nepal and forest fire over north-east India were the major long-distant sources of the CA over Darjeeling during the normal period. On the other hand, during lockdown, the major source regions of CA over Darjeeling were regional/local. The findings of the study indicate the immense importance of Himalayan biosphere as a major source of organic carbon.

Epidemiological Pattern of Contact Dermatitis among Urban and Rural Patients Attending a Tertiary Care Center in a Semi-urban Area in Eastern India.

BACKGROUND: There is a trend of increase in number of contact dermatitis cases. Studies on the prevalence and epidemiological pattern of allergic skin disorders in Indian scenario are not much available. The present study was designed to assess the epidemiological pattern of contact dermatitis in rural and urban areas in a peripheral district in eastern India. AIMS AND OBJECTIVES: This study was undertaken to find the prevalence of contact dermatitis and to assess the epidemiological pattern of contact dermatitis both in rural and urban community. MATERIALS AND METHODS: The study was conducted in a medical college located at a semi-urban area in eastern India with written informed consent obtained from each participant. This hospital-based cross-sectional study was done from May 2017 to April 2018. Study population consisted of patients attending the dermatology OPD and having lesions clinically suggestive of contact dermatitis and there were 268 such patients. Patients attending the OPD were divided into urban and rural as per their address. Data analysis was done using suitable, standard, and appropriate statistical methods. RESULTS: The prevalence of contact dermatitis was 4.38% among the dermatology OPD attendees. Urban prevalence was statistically significantly (P < 0.05) higher than rural prevalence. Contact dermatitis was common in the age group of 41-50 years. In urban areas, females were more affected than those in rural areas. Occupationally, the difference between urban and rural patients of contact dermatitis was statistically significant (P < 0.05). Cosmetic history in the urban group was significantly more (P < 0.05). CONCLUSIONS: Contact dermatitis prevalence and patient profile in certain factors showed a statistically significant difference between urban and rural patients.

Relative role of black carbon and sea-salt aerosols as cloud condensation nuclei over a high altitude urban atmosphere in eastern Himalaya.

The present study is an attempt to investigate the relative role of black carbon (BC) and sea-salt aerosols on the CCN activation over a high altitude station, Darjeeling (27.1° N and 88.15° E, 2200 m asl) at eastern Himalaya. Aerosols (CN, CCN, BC and PM2.5) were measured during premonsoon and monsoon in 2017 and 2018. A unique sampling strategy and a novel methodology were adopted that enabled us to quantitatively and separately determine the contributions of local emissions (LE), valley wind transport (VWT) and long-range transport (LRT) to BC aerosols and their role in CCN activation. On the other hand, the contributions of transported sea-salt (NaCl) aerosols to CCN activation were also determined when they interact with the local anthropogenic soluble species and when they do not. CCN (0.5% super-saturation) concentrations were found to be increased when BC aerosols were more aged (~ 80 cm-3 and 218 cm-3 increase in CCN for 1 µg m-3 increase in BCLE and BCLRT with activation ratios of 0.17 and 0.55 respectively). Local anthropogenic acidic species (SO42-/H2SO4 (g) and NO3-/HNO3 (g)) interact with NaCl resulting to Cl- depletion. Cl- depletion was increased with the increase in NO3- + SO42-(45% for1 µg m-3increase in NO3- + SO42-) that in turn sharply decreased the AR of NaCl (0.04 for 1% increase in Cl- depletion). On the other hand, higher the NO3- + SO42-, higher were the CCN activation of transported BC which could be due to the soluble coating on BC. The important and interesting fact is that when transported and interacted with anthropogenic soluble species, BC aerosols (though hydrophobic) act as much better CCN than NaCl (though hydrophilic).

Identification of most preferable reaction pathways for chloride depletion from size segregated sea-salt aerosols: A study over high altitude Himalaya, tropical urban metropolis and tropical coastal mangrove forest in eastern India.

Depletion of chloride from sea-salt aerosols affects their hygroscopicity, cloud condensation nuclei activity as well as microphysical and chemical properties of aerosols and clouds modifying earth-atmosphere radiative balance. Here, we proposed five possible reaction pathways through which the inorganic acids (H2SO4 and HNO3) could deplete chloride from sea-salt aerosols. We determined "maximum potential contribution" (MPC) of each acid and compared the MPC with actual chloride depletion. This step-by-step approach enables us to identify the most preferable reaction pathway(s) for coarse, superfine, accumulation and ultrafine aerosols over a Himalayan station (Darjeeling), a tropical urban station (Kolkata) and a tropical mangrove forest at the north-east coast of Bay of Bengal (Sundarban) in India. Over Kolkata and Darjeeling, locally generated acids reacted with transported sea-salts. Over Sundarban, the locally generated sea-salts from the Bay of Bengal reacted with the acids of biomass burning plume transported from Eastern Ghat and continental haze transported from upper Indo-Gangetic Plain. The average chloride depletion in PM10 ranged between 70 and 74% over Sundarban and 31-34% over Kolkata and Darjeeling. We observed that HNO3(g) depleted the larger (>1 µm) chlorides whereas H2SO4(g) depleted the smaller (<1 µm) chlorides over Kolkata and Darjeeling. However, in addition to H2SO4(g) and HNO3(g), some other species could be involved in chloride depletion over Sundarban mainly during winter. The study reveals that Sundarban acts as the major sink of the inorganic acids transported from Eastern Ghat biomass burning plume inhibiting their further advection towards inland regions.