Complex Hygroscopic Behavior of Ambient Aerosol Particles Revealed by a Piezoelectric Technique.

Understanding the complex interactions between atmospheric aerosols and water vapor in subsaturated regions of the atmosphere is crucial for modeling and predicting aerosol-cloud-radiation-climate interactions. However, the microphysical mechanisms of these interactions for ambient aerosols remain poorly understood. For this study, size-resolved samples were collected from a high-altitude, relatively clean site situated in the Western Ghats of India during the monsoon season, in order to study background and preindustrial processes as a baseline for climate functioning within the context of the most polluted region of the world. Measurements of humidity-dependent mass-based growth factors, hygroscopicity, deliquescence behavior, and aerosol liquid water content (ALWC) were made by a novel approach using a quartz crystal microbalance based on a piezo-electric sensor. The climate-relevant fine-mode aerosols (≤2.5 µm) exhibited strong size-dependent variations in their interactions with water vapor and contributed a high fraction of ALWC. Deliquescence occurred for relatively large aerosols (diameter >180 nm) but was absent for smaller aerosols. The deliquescence relative humidity for ambient aerosols was significantly lower than that of pure inorganic salts, suggesting a strong influence of organic species. Our study establishes an improved approach for accurately measuring aerosol water uptake characteristics of ambient aerosols in the subsaturated regime, aiding in the assessment of radiative forcing effects and improving climate models.

IBDTransDB: a manually curated transcriptomic database for inflammatory bowel disease.

Inflammatory Bowel Disease (IBD) therapies are ineffective in at least 40% patients, and transcriptomic datasets have been widely used to reveal the pathogenesis and to identify the novel drug targets for these patients. Although public IBD transcriptomic datasets are available from many web-based tools/databases, due to the unstructured metadata and data description of these public datasets, most of these tools/databases do not allow querying datasets based on multiple keywords (e.g. colon and infliximab). Furthermore, few tools/databases can compare and integrate the datasets from the query results. To fill these gaps, we have developed IBDTransDB (https://abbviegrc.shinyapps.io/ibdtransdb/), a manually curated transcriptomic database for IBD. IBDTransDB includes a manually curated database with 34 transcriptomic datasets (2932 samples, 122 differential comparisons) and a query system supporting 35 keywords from 5 attributes (e.g. tissue and treatment). IBDTransDB also provides three modules for data analyses and integration. IBDExplore allows interactive visualization of differential gene list, pathway enrichment, gene signature and cell deconvolution analyses from a single dataset. IBDCompare supports comparisons of selected genes or pathways from multiple datasets across different conditions. IBDIntegrate performs meta-analysis to prioritize a list of genes/pathways based on user-selected datasets and conditions. Using two case studies related to infliximab treatment, we demonstrated that IBDTransDB provides a unique platform for biologists and clinicians to reveal IBD pathogenesis and identify the novel targets by integrating with other omics data. Database URL: https://abbviegrc.shinyapps.io/ibdtransdb/.

An open-hardware community ice nucleation cold stage for research and teaching.

Aerosol particles with rare specific properties act as nuclei for ice formation. The presence of ice nucleating particles in the atmosphere leads to heterogeneous freezing at warm temperatures and thus these particles play an important role in modulating microphysical properties of clouds. This work presents an ice nucleation cold stage instrument for measuring the concentration of ice nucleating particles in liquids. The cost is âˆ¼ $10 k including an external chiller. Using a lower cost heat sink reduces the cost to âˆ¼ $6 k. The instrument is suitable for studying ambient ice nucleating particle concentrations and laboratory-based process-level studies of ice nucleation. The design plans allow individuals to self-manufacture the cold-stage using 3D printing, off-the-shelf parts, and a handful of standard tools. Software to operate the instrument and analyze the data is also provided. The design is intended to be simple enough that a graduate student can build it as part of a course or thesis project. Costs are kept to a minimum to facilitate use in classroom demonstrations and laboratory classes.

A Novel RP-HPLC Method for Simultaneous Estimation of Vilanterol Trifenatate, Umeclidinium Bromide and Fluticasone Furoate in Inhalation Dry Powder Formulation.

The dry powder inhalation formulation containing vilanterol trifenatate, umeclidinium bromide and fluticasone furoate intended for the therapy of bronchospasm related to chronic obstructive pulmonary disease and bronchial asthma was selected for the development and validation of a novel, selective, accurate, precise, quick and cost-efficient reversed-phase, high-performance liquid chromatography method. Neither an official monograph nor a single method has yet been published for the simultaneous estimation of these three compounds, which makes this method novel. The stationary phase of an ACE-C18-PFP column (250 mm × 4.6 mm, 5 µ) was used with a mobile phase of 25-mM sodium perchlorate buffer (pH 2.5 adjusted with ortho-phosphoric acid) and acetonitrile (40:60% v/v) at a flow rate of 1 mL/min to optimize chromatographic variables. The column temperature was kept at 40°C, and detection was at 224 nm, which was the isosbestic point of these three drugs. Well-resolved good peak symmetry was obtained for all three molecules by isocratic elution in less than 10 min, and the retention times of vilanterol trifenatate, umeclidinium bromide and fluticasone furoate were found to be 3.7, 5.4 and 8.3 min, respectively. The proposed method was validated as per ICH Q2 (R1) guidelines, and the calibration curves were linear in concentration ranges of 5-35 µg/mL for vilanterol trifenatate, 5-80 µg/mL for umeclidinium bromide and 5-150 µg/mL for fluticasone furoate, with mean % recoveries of 99-100%. The limits of detection and quantitation are 0.15 and 0.45 µg/mL for vilanterol trifenatate, 0.58 and 1.77 µg/mL for umeclidinium bromide and 0.32 and 0.96 µg/mL for fluticasone furoate, respectively. Hence, the proposed RP-HPLC technique was successfully used to quantify the inhalation formulation containing all three compounds.

Mechanism of action of certain medicinal plants for the treatment of asthma.

ETHNOPHARMACOLOGICAL RELEVANCE: Asthma is often treated and prevented using the pharmacological properties of traditional medicinal plants. These healthcare systems are among the most well-known, conveniently accessible, and economically priced in India and several other Asian countries. Traditional Indian Ayurvedic plants have the potential to be used as phyto-therapeutics, to create novel anti-asthmatic drugs, and as a cost-effective source of pharmaceuticals. Current conventional therapies have drawbacks, including serious side effects and expensive costs that interfere with treatment compliance and affect the patient's quality of life. The primary objective of the article is to comprehensively evaluate the advancement of research on the protective phytochemicals of traditional plants that target immune responses and signaling cascades in inflammatory experimental asthma models. The study would assist in paving the way for the creation of natural phytomedicines that are protective, anti-inflammatory, and immunomodulatory against asthma, which may then be used in individualized asthma therapy. AIM OF THE STUDY: The study demonstrates the mechanisms of action of phytochemicals present in traditional medicinal plants, diminish pulmonary disorder in both in vivo and in vitro models of asthma. MATERIALS AND METHODS: A comprehensive review of the literature on conventional plant-based asthma therapies was performed from 2006 to 2022. The study uses authoritative scientific sources such as PubMed, PubChem Compound, Wiley Online Library, Science Direct, Springer Link, and Google Scholar to collect information on potential phytochemicals and their mechanisms of action. World Flora Online (http://www.worldfloraonline.org) and Plants of the World Online (https://wcsp.science.kew.org) databases were used for the scientific names of medicinal plants. RESULTS: The study outlines the phytochemical mechanisms of some traditional Ayurveda botanicals used to treat asthma. Active phytochemicals including curcumin, withaferin-A, piperine, glabridin, glycyrrhizin, 18ß-glycyrrhetinic acid, trans-cinnamaldehyde, α-hederin, thymoquinone, eugenol, [6]-shogoal, and gingerol may treat asthma by controlling inflammation and airway remodeling. The study concluded that certain Ayurvedic plants' phytochemicals have the ability to reduce inflammation and modulate the immune system, that can effectively cure asthma. CONCLUSION: Plants used in traditional Ayurvedic medicine have been utilized for millennia, advocating phyto-therapy as a treatment for a variety of illnesses. A theoretical foundation for the use of cutting-edge asthma treatments has been built with the growth of experimental research on traditional phytochemicals. In-depth phytochemical research for the treatment of asthma using Indian Traditional Ayurvedic herbs is compiled in the study. The approach for preventative therapeutics and cutting-edge alternatives to battle the molecular pathways in the pathophysiology of asthma are the key themes of the study. The phytochemical mechanism of action of traditional Ayurvedic herbs is explained to get the attention of the pharmaceutical industry so they can make future anti-asthma drugs for personalized asthma care in the community. The study develops strategies for customized phyto-therapeutics, concentrating on low-cost, side-effect-free approaches that employ bioactive phytochemicals from plants as the major source of effective anti-asthmatic therapy.

CHQ- SocioEmo: Identifying Social and Emotional Support Needs in Consumer-Health Questions.

General public, often called consumers, are increasingly seeking health information online. To be satisfactory, answers to health-related questions often have to go beyond informational needs. Automated approaches to consumer health question answering should be able to recognize the need for social and emotional support. Recently, large scale datasets have addressed the issue of medical question answering and highlighted the challenges associated with question classification from the standpoint of informational needs. However, there is a lack of annotated datasets for the non-informational needs. We introduce a new dataset for non-informational support needs, called CHQ-SocioEmo. The Dataset of Consumer Health Questions was collected from a community question answering forum and annotated with basic emotions and social support needs. This is the first publicly available resource for understanding non-informational support needs in consumer health-related questions online. We benchmark the corpus against multiple state-of-the-art classification models to demonstrate the dataset's effectiveness.

GC-MS based untargeted metabolomics reveals the metabolic response of earthworm (Eudrilus eugeniae) after chronic combinatorial exposure to three different pesticides.

In this study GC-MS-based untargeted metabolomics was used to identify the metabolic response of earthworm; Eudrilus eugeniae exposed to sub-lethal concentrations of chlorpyrifos-CHL, cypermethrin-CYP, Glyphosate-GLY, and Combined-C (all three pesticides) at the concentrations of 3, 6, and 12 mg/kg. Principal component analysis of the obtained datasets revealed a clear distinction between the control and treatment groups. The mean weight of the worms in the treated groups decreased significantly (p < 0.05). Among the identified metabolites, oleic acid (~ 93.47%), lysine (~ 92.20%), glutamic acid (~ 91.81%), leucine (~ 90.20%), asparagine (~ 94.20%), methionine (~ 92.27%), malic acid (~ 93.37%), turanose (~ 95.04%), maltose (~ 92.36%), cholesta-3,5-diene (~ 86.11%), galactose (~ 93.20%), cholesterol (~ 91.56%), tocopherol (~ 85.09%), decreased significantly (p < 0.05), whereas myoinositol (~ 83%) and isoleucine (78.09%) increased significantly (p < 0.05) upon exposure to the CHL, CYP, GLY, and C. Overall, the findings suggest that earthworms might be a new entry point for the pesticides into the food chain. The present study highlights that metabolomics can be a reliable approach to understand the effect of different xenobiotics including pesticides on the metabolic response of earthworms.

Modeling and optimization of chlorpyrifos and glyphosate biodegradation using RSM and ANN: Elucidating their degradation pathways by GC-MS based metabolomics.

Ongoing and extensive use of pesticides negatively impact the environment and human health. Microbe-based remediation bears importance as it is an eco-friendly and cost-effective technique. The present study investigated chlorpyrifos (CHL) and glyphosate (GLY) degrading potential of Bacillus cereus AKAD 3-1, isolated from the soybean rhizosphere. Optimization and validation of different process variables were carried out by response surface methodology (RSM) and artificial neural network (ANN). Critical parameters which affect the degradation process are initial pesticide concentration, pH, and inoculum size. At optimum conditions, the bacterial strain demonstrated 94.52% and 83.58% removal of chlorpyrifos and glyphosate, respectively. Both Central-composite design (CCD-RSM) and ANN approaches proved to perform well in modeling and optimizing the growth conditions. The optimum ANN-GA model resulted in R2 ≥ 0.99 for chlorpyrifos and glyphosate, while in the case of RSM, the obtained R2 value was 0.96 and 0.95, respectively. Results indicated that the process variables significantly (p < 0.05) impact chlorpyrifos and glyphosate biodegradation. Moreover, the predicted RSM model had a "lack of fit p-value" of "0.8849" and "0.2502" for chlorpyrifos and glyphosate, respectively. GC-MS analysis revealed that the strain first converted chlorpyrifos into 3,5,6-trichloro pyridin-2-ol & O, O-diethyl O-hydrogen phosphorothiate. Later, these intermediate metabolites were broken and completely mineralized into non-toxic by-products. Similarly, glyphosate was first converted into 2-(methylamino) acetic acid and amino-oxyphosphonic acid, which were further mineralized without any toxic by-products. Taken together, the results of this study clarify the biodegradation pathways and highlights the promising potential of B. cereus AKAD 3-1 in the bioremediation of chlorpyrifos and glyphosate-polluted environments.

Current Status of Ponds in India: A Framework for Restoration, Policies and Circular Economy.

Healthy pond ecosystems are critical for achieving several sustainable development goals (SDG) through numerous ecosystem services (e.g., flood control, nutrient retention, and carbon sequestration). However, the socio-economic and ecological value of ponds is often underestimated compared to the larger water bodies. Ponds are highly vulnerable to mounting land-use pressures (e.g., urban expansion, and agriculture intensification) and environmental changes, leading to degradation and loss of the pond ecosystem. The narrow utilitarian use-based conservation fails to recognize the multiple anthropogenic pressures and provides narrow solutions which are inefficient to regenerate the degraded pond ecosystem. In this paper, we holistically examined the legal challenges (policies) and key anthropogenic and environmental pressures responsible for pond degradation in India. The country is strongly dedicated to attaining SDG and circular economy (CE) through aquatic ecosystem conservation and restoration. Considerable efforts are required at the administration level to recognize the contribution of pond ecosystem services in attaining global environmental goals and targets. Worldwide restoration strategies were reviewed, and a framework for pond restoration and conservation was proposed, which includes policies and incentives, technologies such as environmental-DNA (e-DNA), life cycle assessment (LCA), and other ecohydrological measures. Nature-based solutions (NBS) offer a sustainable and cost-effective approach to restoring the pond's natural processes. Furthermore, linkage between the pond ecosystem and the CE was assessed to encourage a regenerative system for biodiversity conservation. This study informs the need for extensive actions and legislative reforms to restore and conserve the pond ecosystems. Supplementary Information: The online version contains supplementary material available at 10.1007/s13157-022-01624-9.

Ecotoxicity assessment for environmental risk and consideration for assessing the impact of silver nanoparticles on soil earthworms.

Silver nanoparticles (AgNPs) are found in a range of commercial products due to their proven antibacterial properties. The unused silver nanoparticles (AgNPs) may make its way into the soil via biosolids that come from wastewater treatment or the effluent that comes from industrialisation processes, where it could be harmful to the organism that live in terrestrial ecosystems. In addition, silver ions are one of the most toxic forms of heavy metal released from dissolved silver nitrate (AgNO3) and AgNPs through dissolution or oxidation. The study examined the effect of engineered AgNPs, and AgNO3 on earthworms which are one of the most important bioindicator for determining toxicity in soil environment. Epigeic earthworm, Eudrilus eugeniae was exposed to soils spiked with equivalent concentrations of AgNPs or AgNO3 at 0, 10, 100, and 200 mg kg-1 in soil for 56 days of experiments. The survival and growth rate was recorded at 7th, 14th, 21st, 28th days and accumulation of Ag in earthworm tissue at 14th and 28th days, antioxidant enzymes at 28th days and reproduction at 56th days of experiment. Further, a short-term exposure of AgNPs and AgNO3 was conducted to observe avoidance behaviour after 48 h of exposure. The result indicated that survivability was relatively low on exposure of AgNO3 (83.3%) than AgNPs (86.7%) in 200 mg kg-1 spiked soils, besides the growth was inhibited in both AgNPs (3.68%) and AgNO3 (3.25%) at 28th days. The uptake of Ag from AgNO3 in the earthworm tissue was slightly higher than uptake of Ag from AgNPs and it showed concentration-dependent inhibitory effects on reproduction. In AgNO3 spiked soil, a high level of the Malondialdehyde (MDA) based lipid peroxidation and increased activity of antioxidant enzyme catalase (CAT) was observed than AgNPs spiked soil. Similarly, glutathione (GSH), a cofactor for GPx and GST enzymes, was lower in AgNO3-spiked soil than in AgNPs-spiked soil. In terms of avoidance behaviour, there was no discernible difference between the distribution of earthworms in AgNPs and AgNO3 after 48 h. The study found E. eugeniae exhibits concentration-dependent alterations in its competence to survive, antioxidant enzymes, and reproduction. AgNO3 was found to be more sensitive than AgNPs in the study. The research investigates the effect of AgNPs on earthworms in the soil ecosystem since this understanding is crucial for a comprehensive evaluation of AgNPs' environmental consequences.

Metagenomic Insights into the Gut Microbiota of Eudrilus eugeniae (Kinberg) and Its Potential Roles in Agroecosystem.

Gut microbiomes, a consortium of microorganisms that live in the animal gut, are highly engineered microbial communities. It makes a major contribution to digestive health, metabolism management, and the development of a strong immune system in the host. The present study was taken up to answer the long-running question about the existence of truly indigenous microflora of the epigeic earthworm gut. This is due to the general difficulties of culturing many of the microorganisms found in soil or earthworms' gut. Keeping this fact in a view, the metagenomics approach using 16S rRNA marker gene incorporated with amplicon-based sequencing was used to explore microbiota of commercially overriding, diversely fed epigeic earthworm Eudrilus eugeniae (Kinberg) in three varied habitats viz., artificial soil (AS), organic agricultural farm soil (OAFS) and conventional agriculture farm soil (CAFS). There are predominant bacteria that belong to different phyla such as Proteobacteria (29.72-76.81%), Actinobacteria (11.06-34.42%), Firmicutes (6.02-19.81%), and Bacteroidetes (2.40-9.22%) present in the gut of E. eugeniae. The alpha diversity (Observed species, Chao1, ACE, Shannon, Simpson, and Fisher alpha) indices showed that OAFS had significantly higher alpha diversity than AS and CAFS groups. The core microbiota analysis showed that OAFS and AS groups had a relatively similar bacterial panel in comparison to the CAFS group. Various statistical tools i.e. MetagenomeSeq, LEfSe, and Random Forest analysis were performed and the findings demonstrated prevalence of the most significant bacterial genera; Aeromonas, Gaiella, and Burkholderia in CAFS group. Nonetheless, in AS and OAFS groups, the common existence of Anaerosporobacter and Aquihabitans were found respectively. Metagenomic functional prediction revealed that earthworms' gut microbial communities were actively involved in multiple organic and xenobiotics compound degradation-related pathways. This is the first research to use high-throughput 16S rRNA gene amplicon sequencing to show the gut microbiota of E. eugeniae in diverse agricultural systems. The findings suggest the configuration of the gut microbiota of earthworms and its potential role in the soil ecosystem depends on the microbial communities of the soil.

Variations in the concentration, source activity, and atmospheric processing of PM2.5-associated water-soluble ionic species over Jammu, India.

Concentrations, sources, and atmospheric processing of water-soluble ionic species associated with PM2.5 collected from 2015 to 2017 were studied in Jammu, an urban location in the North-Western Himalayan Region (NWHR). Being ecologically sensitive and sparsely studied for dynamics in PM2.5 and associated WSIS, the present study is important for developing robust air pollution abatement strategies for the air-shed of NWHR. Twenty-four hourly PM2.5 samples were collected on weekly basis at a receptor site and analyzed for WSIS using ion chromatography system. On annual basis, total sum of WSIS (ΣWSIS) contributed about 28.5% of PM2.5, where the contribution of sulfate-nitrate-ammonium, a proxy for secondary inorganic aerosols (SIA), was found to be 18.7% of PM2.5. The ΣWSIS and PM2.5 concentration showed a seasonal cycle with the maximum concentration during winters and the minimum in summers. Mass fraction of ΣWSIS in PM2.5 showed an anti-phase seasonal pattern indicating more source activity during summers. Season-wise, dominant WSIS constituting PM2.5 were NO3-, SO42-, NH4+, and K+ during winters; whereas summer was marked with dominant contributions from SO42-, NH4+, Ca2+, and K+. Seasonal variability exhibited among SIA constituents underscored the crucial role of air temperature and relative humidity regime. It was observed that nss-K+ + NH4+ were sufficient to neutralize most of the acidic species arising from precursor gases (NOx and SOx). Using principal component analysis, five major sources and processes, viz. (a) biomass burning activities, (b) secondary inorganic aerosol formation, (c) input from re-suspended dust, (d) transported dust, and (e) fertilizer residue, were identified for the emissions of PM2.5-associated WSIS over Jammu. In future studies, impacts of dry and/or wet deposition of aerosol-associated WSIS on the crop productivity in the region should be studied.

The bioactive potential of phytohormones: A review.

Plant hormones play an important role in growth, defence and plants productivity and there are several studies on their effects on plants. However, their role in humans and animals is limitedly studied. Recent studies suggest that plant hormone also works in mammalian systems, and have the potential to reduce human diseases such as cancer, diabetes, and also improve cell growth. Plant hormones such as indole-3-acetic acid (IAA) works as an antitumor, anti-cancer agent, gibberellins help in apoptosis, abscisic acid (ABA) as antidepressant compounds and regulation of glucose homeostasis whereas cytokinin works as an anti-ageing compound. The main aim of this review is to explore and correlate the relation of plant hormones and their important roles in animals, microbes and plants, and their interrelationships, emphasizing mainly human health. The most important and well-known plant hormones e.g., IAA, gibberellins, ABA, cytokinin and ethylene have been selected in this review to explore their effects on humans and animals.

Metagenomic analysis displays the potential predictive biodegradation pathways of the persistent pesticides in agricultural soil with a long record of pesticide usage.

Microbes are crucial in removing various xenobiotics, including pesticides, from the environment, specifically by mineralizing these hazardous pollutants. However, the specific procedure of microbe-mediated pesticide degradation and its consequence on the environment remain elusive owing to limitations in culturing techniques. Therefore, in this study, we have investigated i) the physicochemical and elemental compositions of PCAS (pesticide-contaminated agricultural soils) and NS (natural soils); ii) the bacterial communities and degradation pathways, as well as some novel biodegradation genes (BDGs) and pesticide degradation genes (PDGs) across two different landscapes (PCAS and NS) by applying high-throughput sequencing. The chemical and elemental composition analyses showed that all nutrients (P, K, N, S, Mn, B, and Zn) were significantly higher in PCAS than in NS (p ≤ 0.05). The results of the 16S rRNA amplicon sequencing analysis of pesticide-contaminated (PCAS-1, PCAS-2, PCAS-3, PCAS-4) samples showed that the relative abundance of the phylum Proteobacteria (30-36%) > Actinobacteria (15-20%) > Firmicutes (13-14%) > Bacteroidetes (7-13%), were higher compared to the natural soil (NS-1, NS2). Consistent with this, a phylogenetic shift was observed with (alpha, beta, and gamma Proteobacteria) being abundant in PCAS, whereas delta and epsilon groups were more prevalent in NS. The functional characterization of the PCAS and NS by PICRUSt2 revealed that bacterial communities play a significant role in pesticide metabolism. Predictive metagenome analysis of contaminated soils showed the role of core degrading genes in membrane transport, stress response, regulatory genes, resource transport, and environmental sensing. Furthermore, 14 BDGs and 30 PDGs were examined, with a relative abundance of 0.081-1.029 % and 0.107-0.8903 % in each PCAS, respectively. The major BDGs and PDGs, with the compounds they hydrolyze, include ppo (polyphenol oxidase and laccase), CYP (cytochrome p450 protein), lip gene (lignin peroxidase), similarly, among the PDGs mhel (carbendazim), opd (organophosphate), mpd (methyl parathion), atzA, atzB, atzD, atzF and trzN (atrazine), chd (chlorothalonil), hdx (metamitron), hdl-1 (isoproturon) and fmo (nicosulfuron). Overall, our findings demonstrated the significance of utilizing metagenomic methods to predict microbial aided degradation in the ecology of contaminated environments.

Process optimization of cypermethrin biodegradation by regression analysis and parametric modeling along with biochemical degradation pathway.

Pyrethroid pesticides are of great environmental and health concern with regard to neurotoxicity and ubiquitous occurrence. Here, we reported a new bacterial strain identified as Bacillus cereus AKAD 3-1 that degraded 88.1% of 50 mg/l of cypermethrin in an aqueous medium. The biodegradation of cypermethrin was optimized by CCD (central composite design) and validated by ANN-GA (artificial neural network-genetic algorithm). Both the approaches proved to possess good performance in modeling and optimizing the growth conditions. Results indicated that the process variables have a significant (< 0.0001) impact on cypermethrin biodegradation. Moreover, the predicted CCD model had a "lack of fit p-value" of "0.9975." The optimum CCD and ANN model had an R2 value of 0.9703 and 0.9907, indicating that the two models' experimental and predicted values are closely fitted. The isolate successfully converted cypermethrin to CO2 and phenol without producing any toxic metabolite. Finally, a degradation pathway was proposed with the intermediate compounds identified by GC-MS. The present study highlights an important potential application of strain AKAD 3-1 for the in situ bioremediation of cypermethrin-contaminated environments.

Apportionment of long-term trends in different sections of total ozone column over tropical region.

The additive time-series decomposition analysis was performed on National Oceanic and Atmospheric Administration Solar Backscatter Ultraviolet Instrument Merge satellite dataset version 8.6 for the period January 1979 to December 2019 with an objective to detect and apportion long-term trends present in the total ozone column (TOC) and the long-term trends exist in the respective ozone contents present in the vertical sub-columns constituting the TOC viz. upper, middle and lower stratosphere as well as near-surface for the tropical region. Linear regression analysis was performed on the deseasonalized monthly mean time series of TOC and corresponding ozone contents present in each partitioned layer for three different time spans, viz. 1979-2019 (complete time series), 1979-1998 (pre-inflection years), and 1999-2019 (post-inflection years), where 1998 was taken as inflection year. For the complete time-series, statistically significant negative trends were observed in TOC and corresponding ozone contents in the sub-columns over most of the tropical region. Expectedly, during pre-inflection years, strong negative trends were noted for TOC and ozone contents in the partitioned vertical layers. In contrast, during the post-inflection year time span, long-term trends in TOC were statistically insignificant over two-third of the tropical region, but one-third of the subtropical region exhibited negative trends in TOC. During this time span, positive trends were observed in the ozone contents present in the upper stratospheric sub-column. However, negative trends in ozone contents persisted in the middle and the lower stratosphere. It was interesting to note that the ozone contents confined in near-surface layer manifested strong negative trends during pre-inflection years and the same reversed into strong positive trends that in post-inflection span. The observed, contrasting, long-term trends and variability in the respective partitioned layer of the TOC confounded any clear sign of recovery in the TOC over the tropical region. The continuation of declining trends in the middle stratosphere and increasing trends in the near-surface layer of ozone contents is a matter of concern.

Question-aware transformer models for consumer health question summarization.

Searching for health information online is becoming customary for more and more consumers every day, which makes the need for efficient and reliable question answering systems more pressing. An important contributor to the success rates of these systems is their ability to fully understand the consumers' questions. However, these questions are frequently longer than needed and mention peripheral information that is not useful in finding relevant answers. Question summarization is one of the potential solutions to simplifying long and complex consumer questions before attempting to find an answer. In this paper, we study the task of abstractive summarization for real-world consumer health questions. We develop an abstractive question summarization model that leverages the semantic interpretation of a question via recognition of medical entities, which enables generation of informative summaries. Towards this, we propose multiple Cloze tasks (i.e. the task of filing missing words in a given context) to identify the key medical entities that enforce the model to have better coverage in question-focus recognition. Additionally, we infuse the decoder inputs with question-type information to generate question-type driven summaries. When evaluated on the MeQSum benchmark corpus, our framework outperformed the state-of-the-art method by 10.2 ROUGE-L points. We also conducted a manual evaluation to assess the correctness of the generated summaries.

Emerging frontiers in microbe-mediated pesticide remediation: Unveiling role of omics and In silico approaches in engineered environment.

The overuse of pesticides for augmenting agriculture productivity always comes at the cost of environment, biodiversity, and human health and has put the land, water, and environmental footprints under severe threat throughout the globe. Underpinning and maximizing the microbiome functions in pesticide-contaminated environments has become a prerequisite for a sustainable environment and resilient agriculture. It is imperative to elucidate the metabolic network of the microbial communities and environmental variables at the contaminated site to predict the best strategy for remediation and soil microbe-pesticide interactions. High throughput next-generation sequencing and in silico analysis allow us to identify and discern the members and characteristics of core microbiomes at the contaminated site. Integration of modern high throughput multi-omics investigations and informatics pipelines provide novel approaches and pathways to capitalize on the core microbiomes for enhancing environmental functioning and mitigation. The role of eco-genomics tools in visualising the microbial network, taxonomy, functional potential, and environmental variables in contaminated habitats is discussed in this review. The integrated role of the potential microbe identification as individual or consortia, mechanistic approach for pesticide degradation, identification of responsible enzymes/genes, and in silico approach is emphasized for the prospects of the area.

Relation Extraction From Biomedical and Clinical Text: Unified Multitask Learning Framework.

MOTIVATION: To minimize the accelerating amount of time invested on the biomedical literature search, numerous approaches for automated knowledge extraction have been proposed. Relation extraction is one such task where semantic relations between the entities are identified from the free text. In the biomedical domain, extraction of regulatory pathways, metabolic processes, adverse drug reaction or disease models necessitates knowledge from the individual relations, for example, physical or regulatory interactions between genes, proteins, drugs, chemical, disease or phenotype. RESULTS: In this paper, we study the relation extraction task from three major biomedical and clinical tasks, namely drug-drug interaction, protein-protein interaction, and medical concept relation extraction. Towards this, we model the relation extraction problem in a multi-task learning (MTL)framework, and introduce for the first time the concept of structured self-attentive network complemented with the adversarial learning approach for the prediction of relationships from the biomedical and clinical text. The fundamental notion of MTL is to simultaneously learn multiple problems together by utilizing the concepts of the shared representation. Additionally, we also generate the highly efficient single task model which exploits the shortest dependency path embedding learned over the attentive gated recurrent unit to compare our proposed MTL models. The framework we propose significantly improves over all the baselines (deep learning techniques)and single-task models for predicting the relationships, without compromising on the performance of all the tasks.

Three uncharted endemic earthworm species of the genus Eutyphoeus (Oligochaeta: Octochaetidae) from Mizoram, India.

Integrative approach of taxonomy drives us to the discovery of three new species of the genus Eutyphoeus Michaelsen 1900, namely Eutyphoeus phawngpuiensis sp. nov., Eutyphoeus serei sp. nov. and Eutyphoeus tawi sp. nov. from protected forests of Mizoram, India. E. phawngpuiensis sp. nov. belongs to the Eutyphoeus hastatus group, and is characterized by holandric male organs, having spermathecal pores at a or ab, bidiverticulate spermathecae, and lack of genital marking glands. While, E. tawi sp. nov. has spermathecal pores at b or lateral to b, without lateral intestinal caeca. E. serei sp. nov. belongs to the Eutyphoeus gigas group, and is distinguished by having metandric male organs, lacking female pore of right side, and having spoon shaped tip of penial setae without ornamentation. Molecular characterization using coi gene marker also supports the findings. The maximum intraspecific distances and distance to the nearest neighbour of E. phawngpuiensis sp. nov., E. serei sp. nov. and E. tawi sp. nov. were recorded 3.5%, 9.37%; 2.35%, 14.83%; and 2.28%, 12.86% respectively. The key to Eutyphoeus species of India was also updated.