University of Kalyani

Abstract The genetic make-up of an individual contributes to the susceptibility and response to viral infection. Although environmental, clinical and social factors have a role in the chance of exposure to SARS-CoV-2 and the severity of COVID-19 1,2 , host genetics may also be important. Identifying host-specific genetic factors may reveal biological mechanisms of therapeutic relevance and clarify causal relationships of modifiable environmental risk factors for SARS-CoV-2 infection and outcomes. We formed a global network of researchers to investigate the role of human genetics in SARS-CoV-2 infection and COVID-19 severity. Here we describe the results of three genome-wide association meta-analyses that consist of up to 49,562 patients with COVID-19 from 46 studies across 19 countries. We report 13 genome-wide significant loci that are associated with SARS-CoV-2 infection or severe manifestations of COVID-19. Several of these loci correspond to previously documented associations to lung or autoimmune and inflammatory diseases 3–7 . They also represent potentially actionable mechanisms in response to infection. Mendelian randomization analyses support a causal role for smoking and body-mass index for severe COVID-19 although not for type II diabetes. The identification of novel host genetic factors associated with COVID-19 was made possible by the community of human genetics researchers coming together to prioritize the sharing of data, results, resources and analytical frameworks. This working model of international collaboration underscores what is possible for future genetic discoveries in emerging pandemics, or indeed for any complex human disease.

In a previous communication, we reported a new method of synthesis of stable metallic copper nanoparticles (Cu-NPs), which had high potency for bacterial cell filamentation and cell killing. The present study deals with the mechanism of filament formation and antibacterial roles of Cu-NPs in E. coli cells. Our results demonstrate that NP-mediated dissipation of cell membrane potential was the probable reason for the formation of cell filaments. On the other hand, Cu-NPs were found to cause multiple toxic effects such as generation of reactive oxygen species, lipid peroxidation, protein oxidation and DNA degradation in E. coli cells. In vitro interaction between plasmid pUC19 DNA and Cu-NPs showed that the degradation of DNA was highly inhibited in the presence of the divalent metal ion chelator EDTA, which indicated a positive role of Cu(2+) ions in the degradation process. Moreover, the fast destabilization, i.e. the reduction in size, of NPs in the presence of EDTA led us to propose that the nascent Cu ions liberated from the NP surface were responsible for higher reactivity of the Cu-NPs than the equivalent amount of its precursor CuCl2; the nascent ions were generated from the oxidation of metallic NPs when they were in the vicinity of agents, namely cells, biomolecules or medium components, to be reduced simultaneously.

River Ganga is considered sacred by people of India for providing life sustenance to environment and ecology. Anthropogenic activities have generated important transformations in aquatic environments during the last few decades. Advancement of human civilization has put serious questions to the safe use of river water for drinking and other purposes. The river water pollution due to heavy metals is one of the major concerns in most of the metropolitan cities of developing countries. These toxic heavy metals entering the environment may lead to bioaccumulation and biomagnifications. These heavy metals are not readily degradable in nature and accumulate in the animal as well as human bodies to a very high toxic amount leading to undesirable effects beyond a certain limit. Heavy metals in riverine environment represent an abiding threat to human health. Exposure to heavy metals has been linked to developmental retardation, kidney damage, various cancers, and even death in instances of very high exposure. The following review article presents the findings of the work carried out by the various researchers in the past on the heavy metal pollution of river Ganga.

< .001) that is a matter of concern. Moreover, the chronic stress of living through a pandemic led to a host of physical symptoms, like headaches, insomnia, digestive problems, hormonal imbalances, and fatigue.

The aim of any data mining technique is to build an efficient predictive or descriptive model of a large amount of data. Applications of evolutionary algorithms have been found to be particularly useful for automatic processing of large quantities of raw noisy data for optimal parameter setting and to discover significant and meaningful information. Many real-life data mining problems involve multiple conflicting measures of performance, or objectives, which need to be optimized simultaneously. Under this context, multiobjective evolutionary algorithms are gradually finding more and more applications in the domain of data mining since the beginning of the last decade. In this two-part paper, we have made a comprehensive survey on the recent developments of multiobjective evolutionary algorithms for data mining problems. In this paper, Part I, some basic concepts related to multiobjective optimization and data mining are provided. Subsequently, various multiobjective evolutionary approaches for two major data mining tasks, namely feature selection and classification, are surveyed. In Part II of this paper, we have surveyed different multiobjective evolutionary algorithms for clustering, association rule mining, and several other data mining tasks, and provided a general discussion on the scopes for future research in this domain.

The next-generation of cloud computing will thrive on how effectively the infrastructure are instantiated and available resources utilized dynamically. Load balancing which is one of the main challenges in Cloud computing, distributes the dynamic workload across multiple nodes to ensure that no single resource is either overwhelmed or underutilized. This can be considered as an optimization problem and a good load balancer should adapt its strategy to the changing environment and the types of tasks. This paper proposes a novel load balancing strategy using Genetic Algorithm (GA). The algorithm thrives to balance the load of the cloud infrastructure while trying minimizing the make span of a given tasks set. The proposed load balancing strategy has been simulated using the CloudAnalyst simulator. Simulation results for a typical sample application shows that the proposed algorithm outperformed the existing approaches like First Come First Serve (FCFS), Round Robing (RR) and a local search algorithm Stochastic Hill Climbing (SHC).

Machine learning is one of the most exciting recent technologies in Artificial Intelligence. Learning algorithms in many applications that's we make use of daily. Every time a web search engine like Google or Bing is used to search the internet, one of the reasons that works so well is because a learning algorithm, one implemented by Google or Microsoft, has learned how to rank web pages. Every time Facebook is used and it recognizes friends' photos, that's also machine learning. Spam filters in email saves the user from having to wade through tons of spam email, that's also a learning algorithm. In this paper, a brief review and future prospect of the vast applications of machine learning has been made.

This is a continuity of a series of taxonomic and phylogenetic papers on the fungi where materials were collected from many countries, examined and described. In addition to extensive morphological descriptions and appropriate asexual and sexual connections, DNA sequence data are also analysed from concatenated datasets to infer phylogenetic relationships and substantiate systematic positions of taxa within appropriate ranks. Wherever new species or combinations are proposed, we apply an integrative approach using morphological and molecular data as well as ecological features wherever applicable. Notes on 112 fungal taxa are compiled in this paper including Biatriosporaceae and Roussoellaceae, Didysimulans gen. nov., 81 new species, 18 new host records and new country records, five reference specimens, two new combinations, and three sexual and asexual morph reports. The new species are Amanita cornelii, A. emodotrygon, Angustimassarina alni, A. arezzoensis, A. italica, A. lonicerae, A. premilcurensis, Ascochyta italica, A. rosae, Austroboletus appendiculatus, Barriopsis thailandica, Berkleasmium ariense, Calophoma petasitis, Camarosporium laburnicola, C. moricola, C. grisea, C. ossea, C. paraincrustata, Colletotrichum sambucicola, Coprinopsis cerkezii, Cytospora gelida, Dacrymyces chiangraiensis, Didysimulans italica, D. mezzanensis, Entodesmium italica, Entoloma magnum, Evlachovaea indica, Exophiala italica, Favolus gracilisporus, Femsjonia monospora, Fomitopsis flabellata, F. roseoalba, Gongronella brasiliensis, Helvella crispoides, Hermatomyces chiangmaiensis, H. chromolaenae, Hysterium centramurum, Inflatispora caryotae, Inocybe brunneosquamulosa, I. luteobrunnea, I. rubrobrunnea, Keissleriella cirsii, Lepiota cylindrocystidia, L. flavocarpa, L. maerimensis, Lophiotrema guttulata, Marasmius luculentus, Morenoina calamicola, Moelleriella thanathonensis, Mucor stercorarius, Myrmecridium fluviae, Myrothecium septentrionale, Neosetophoma garethjonesii, Nigrograna cangshanensis, Nodulosphaeria guttulatum, N. multiseptata, N. sambuci, Panus subfasciatus, Paraleptosphaeria padi, Paraphaeosphaeria viciae, Parathyridaria robiniae, Penicillium punicae, Phaeosphaeria calamicola, Phaeosphaeriopsis yuccae, Pleurophoma italica, Polyporus brevibasidiosus, P. koreanus, P. orientivarius, P. parvovarius, P. subdictyopus, P. ulleungus, Pseudoasteromassaria spadicea, Rosellinia mearnsii, Rubroboletus demonensis, Russula yanheensis, Sigarispora muriformis, Sillia italica, Stagonosporopsis ailanthicola, Strobilomyces longistipitatus, Subplenodomus galicola and Wolfiporia pseudococos. The new combinations are Melanomma populina and Rubroboletus eastwoodiae. The reference specimens are Cookeina tricholoma, Gnomoniopsis sanguisorbae, Helvella costifera, Polythrincium trifolii and Russula virescens. The new host records and country records are Ascochyta medicaginicola, Boletellus emodensis, Cyptotrama asprata, Cytospora ceratosperma, Favolaschia auriscalpium, F. manipularis, Hysterobrevium mori, Lentinus sajor-caju, L. squarrosulus, L. velutinus, Leucocoprinus cretaceus, Lophiotrema vagabundum, Nothophoma quercina, Platystomum rosae, Pseudodidymosphaeria phlei, Tremella fuciformis, Truncatella spartii and Vaginatispora appendiculata and three sexual and asexual morphs are Aposphaeria corallinolutea, Dothiora buxi and Hypocrella calendulina.

An important approach for unsupervised landcover classification in remote sensing images is the clustering of pixels in the spectral domain into several fuzzy partitions. In this paper, a multiobjective optimization algorithm is utilized to tackle the problem of fuzzy partitioning where a number of fuzzy cluster validity indexes are simultaneously optimized. The resultant set of near-Pareto-optimal solutions contains a number of nondominated solutions, which the user can judge relatively and pick up the most promising one according to the problem requirements. Real-coded encoding of the cluster centers is used for this purpose. Results demonstrating the effectiveness of the proposed technique are provided for numeric remote sensing data described in terms of feature vectors. Different landcover regions in remote sensing imagery have also been classified using the proposed technique to establish its efficiency

With the and of the notion of weighted sharing we prove some uniqueness theorems of meromorphic functions which improve some earlier results.

In the present study, we report the aqueous extract of Pithophora oedogonia to produce silver nanoparticles (AgNPs) by reduction of silver nitrate. It was noted that synthesis process was considerably rapid and silver nanoparticles were generated within few minutes of silver ions coming in contact with the algal extract. A peak at 445 nm corresponding to the plasmon absorbance of AgNPs was noted in the UV–vis spectrum of the aqueous medium that contained silver ions. Scanning electron microscopic (SEM) and dynamic light scattering analysis of colloidal AgNPs indicated the size of 34.03 nm. Energy-dispersive X-ray spectroscopy revealed strong signals in the silver region and confirmed of the AgNPs. Fourier transform infrared spectroscopic analysis of the nanoparticles indicated the presence of protein which was regarding a capping agent surrounding the AgNPs. Moreover, the antibacterial activity of synthesized nanoparticles exhibited potential inhibitory activity against seven tested pathogenic bacteria.

Since 2000, many countries have achieved considerable success in improving child survival, but localized progress remains unclear. To inform efforts towards United Nations Sustainable Development Goal 3.2-to end preventable child deaths by 2030-we need consistently estimated data at the subnational level regarding child mortality rates and trends. Here we quantified, for the period 2000-2017, the subnational variation in mortality rates and number of deaths of neonates, infants and children under 5 years of age within 99 low- and middle-income countries using a geostatistical survival model. We estimated that 32% of children under 5 in these countries lived in districts that had attained rates of 25 or fewer child deaths per 1,000 live births by 2017, and that 58% of child deaths between 2000 and 2017 in these countries could have been averted in the absence of geographical inequality. This study enables the identification of high-mortality clusters, patterns of progress and geographical inequalities to inform appropriate investments and implementations that will help to improve the health of all populations.

BACKGROUND: Pigeonpea [Cajanus cajan (L.) Millspaugh], one of the most important food legumes of semi-arid tropical and subtropical regions, has limited genomic resources, particularly expressed sequence based (genic) markers. We report a comprehensive set of validated genic simple sequence repeat (SSR) markers using deep transcriptome sequencing, and its application in genetic diversity analysis and mapping. RESULTS: In this study, 43,324 transcriptome shotgun assembly unigene contigs were assembled from 1.696 million 454 GS-FLX sequence reads of separate pooled cDNA libraries prepared from leaf, root, stem and immature seed of two pigeonpea varieties, Asha and UPAS 120. A total of 3,771 genic-SSR loci, excluding homopolymeric and compound repeats, were identified; of which 2,877 PCR primer pairs were designed for marker development. Dinucleotide was the most common repeat motif with a frequency of 60.41%, followed by tri- (34.52%), hexa- (2.62%), tetra- (1.67%) and pentanucleotide (0.76%) repeat motifs. Primers were synthesized and tested for 772 of these loci with repeat lengths of ≥ 18 bp. Of these, 550 markers were validated for consistent amplification in eight diverse pigeonpea varieties; 71 were found to be polymorphic on agarose gel electrophoresis. Genetic diversity analysis was done on 22 pigeonpea varieties and eight wild species using 20 highly polymorphic genic-SSR markers. The number of alleles at these loci ranged from 4-10 and the polymorphism information content values ranged from 0.46 to 0.72. Neighbor-joining dendrogram showed distinct separation of the different groups of pigeonpea cultivars and wild species. Deep transcriptome sequencing of the two parental lines helped in silico identification of polymorphic genic-SSR loci to facilitate the rapid development of an intra-species reference genetic map, a subset of which was validated for expected allelic segregation in the reference mapping population. CONCLUSION: We developed 550 validated genic-SSR markers in pigeonpea using deep transcriptome sequencing. From these, 20 highly polymorphic markers were used to evaluate the genetic relationship among species of the genus Cajanus. A comprehensive set of genic-SSR markers was developed as an important genomic resource for diversity analysis and genetic mapping in pigeonpea.

Withania somnifera (L.) Dunal (Solanaceae) has been used as a traditional Rasayana herb for a long time. Traditional uses of this plant indicate its ameliorative properties against a plethora of human medical conditions, viz. hypertension, stress, diabetes, asthma, cancer etc. This review presents a comprehensive summary of the geographical distribution, traditional use, phytochemistry, and pharmacological activities of W. somnifera and its active constituents. In addition, it presents a detailed account of its presence as an active constituent in many commercial preparations with curative properties and health benefits. Clinical studies and toxicological considerations of its extracts and constituents are also elucidated. Comparative analysis of relevant in-vitro, in-vivo, and clinical investigations indicated potent bioactivity of W. somnifera extracts and phytochemicals as anti-cancer, anti-inflammatory, apoptotic, immunomodulatory, antimicrobial, anti-diabetic, hepatoprotective, hypoglycaemic, hypolipidemic, cardio-protective and spermatogenic agents. W. somnifera was found to be especially active against many neurological and psychological conditions like Parkinson's disease, Alzheimer's disease, Huntington's disease, ischemic stroke, sleep deprivation, amyotrophic lateral sclerosis, attention deficit hyperactivity disorder, bipolar disorder, anxiety, depression, schizophrenia and obsessive-compulsive disorder. The probable mechanism of action that imparts the pharmacological potential has also been explored. However, in-depth studies are needed on the clinical use of W. somnifera against human diseases. Besides, detailed toxicological analysis is also to be performed for its safe and efficacious use in preclinical and clinical studies and as a health-promoting herb.

With the rapid advancement in nanotechnology, release of nanoscale materials into the environment is inevitable. Such contamination may negatively influence the functioning of the ecosystems. Many manufactured nanoparticles (NPs) contain heavy metals, which can cause soil and water contamination. Proteomic techniques have contributed substantially in understanding the molecular mechanisms of plant responses against various stresses by providing a link between gene expression and cell metabolism. As the coding regions of genome are responsible for plant adaptation to adverse conditions, protein signatures provide insights into the phytotoxicity of NPs at proteome level. This review summarizes the recent contributions of plant proteomic research to elaborate the complex molecular pathways of plant response to NPs stress.

A variable-string-length genetic algorithm (GA) is used for developing a novel nonparametric clustering technique when the number of clusters is not fixed a-priori. Chromosomes in the same population may now have different lengths since they encode different number of clusters. The crossover operator is redefined to tackle the concept of variable string length. A cluster validity index is used as a measure of the fitness of a chromosome. The performance of several cluster validity indices, namely the Davies-Bouldin (1979) index, Dunn's (1973) index, two of its generalized versions and a recently developed index, in appropriately partitioning a data set, are compared.

The problem of classifying an image into different homogeneous regions is viewed as the task of clustering the pixels in the intensity space. Real-coded variable string length genetic fuzzy clustering with automatic evolution of clusters is used for this purpose. The cluster centers are encoded in the chromosomes, and the Xie-Beni index is used as a measure of the validity of the corresponding partition. The effectiveness of the proposed technique is demonstrated for classifying different landcover regions in remote sensing imagery. Results are compared with those obtained using the well-known fuzzy C-means algorithm.

Pharmaceutical and personal care products (PPCPs) are considered as emerging contaminants (ECs) in the environment due to their known or suspected adverse ecological effects and human health risks. Wastewater, compost, and manure application release PPCPs into the agricultural soil systems. Since the plants can take up such ECs, they are considered as a primary window of human exposure to the PPCPs via the route of consumption of contaminated plants. This may lead to deleterious human health effects. However, as PPCPs are of various kinds, differential uptake and bioaccumulation in the plant have recently received research interest. Therefore, the present article reviewed the occurrence of PPCPs as antibiotics, anti-inflammatory drugs, hormones, cytostatic drugs, contrast media, β-blockers, blood lipid regulators, antiepileptic drugs, antimicrobials, ultra-violet filters, preservatives, insect repellents, and synthetic musks in the environment by assembling the literature. Moreover, plant uptake and translocation under the realistic and greenhouse condition, and the factors influencing the uptake and translocation through the plants are explicitly demonstrated in this review. Also, the human risk connected with the consumption of the contaminated plants and the research gap areas were investigated with future perspectives.

Introducing the idea of weighted sharing of values we prove some uniqueness theorems for meromorphic functions which improve some existing results.

A set of theoretical atomic radii corresponding to the principal maximum in the radial distribution function, 4πr2R2 for the outermost orbital has been calculated for the ground state of 103 elements of the periodic table using Slater orbitals. The set of theoretical radii are found to reproduce the periodic law and the Lother Meyer’s atomic volume curve and reproduce the expected vertical and horizontal trend of variation in atomic size in the periodic table. The d-block and f-block contractions are distinct in the calculated sizes. The computed sizes qualitatively correlate with the absolute size dependent properties like ionization potentials and electronegativity of elements. The radii are used to calculate a number of size dependent periodic physical properties of isolated atoms viz., the diamagnetic part of the atomic susceptibility, atomic polarizability and the chemical hardness. The calculated global hardness and atomic polarizability of a number of atoms are found to be close to the available experimental values and the profiles of the physical properties computed in terms of the theoretical atomic radii exhibit their inherent periodicity. A simple method of computing the absolute size of atoms has been explored and a large body of known material has been brought together to reveal how many different properties correlate with atomic size.