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Not AvailableAgroforestry trees are now well known to play a central role in the build up of nutrients pools and their transformations similar to that of forest ecosystem, however, information on the potential of homegarden trees accumulating and releasing nitrogen (mineralization) is lacking. The present study reports seasonal variations in pool sizes of mineral N (NH4+-N and NO3 -N), and net N-mineralization rate in relation to rainfall and temperature under coconut (Cocos nucifera L.), clove (Eugenia caryophyllata Thunb) and nutmeg (Myristica fragrans Houtt. Nees) trees in a coconut-spice trees plantation for two annual cycles in the equatorial humid climate of South Andaman Island of India. Concentration of NH4+-N was the highest during wet season (May– October) and the lowest during post-wet season (November–January) under all the tree species. On the contrary, concentration of NO3 -N was the lowest in the wet season and the highest during the post-wet season. However, concentrations of the mineral N were the highest under the nutmeg and the lowest under the coconut trees. Like the pool sizes, mean annual mineralization was the highest under the nutmeg (561 mg kg 1 yr 1) and the lowest under the coconut trees (393 mg kg 1 yr 1). Rate of mineralization was the highest during the post-wet season and the lowest during the dry season (February– April) under all the tree species. High rainfall during the wet season, however, reduced the rate of nitrification under all the tree species. The mean annual mineralization was logarithmically related with rainfall amount and mean monthly temperature.Not Availabl

Pre-prescription testing in psychiatry: an overview

Drug therapy ‘tailored’ towards an individual based on his/her genetic profile is becoming increasingly popular in the era of personalised medicine. Pre-prescription testing which enables this, exploits the link between a relevant set of genetic variants and drug metabolism profile to maximise drug efficacy and lower the risk of adverse drug reactions. Since the conception over 50 years ago that drug response might be linked to underlying genetic makeup, the science around this field has evolved rapidly across a wide range of drugs including antipsychotics. Over 80% of both typical and atypical antipsychotics are known to be metabolised by phase-I drug metabolising enzymes such as cytochrome P450 (CYP450) family of genes which harbour extensive genetic variations. This has encouraged variant testing in these genes among patients with neuropsychiatric disorders. A confluence of accelerated variant discovery and next generation sequencing offers a fast and cost-effective approach. However, genomic literacy among the end users, i.e., the psychiatrists, patients, and their primary caregivers remains low, posing a major hindrance in the realisation of this pharmacogenetic goal. A well-oiled, multi-disciplinary machinery comprising of researchers, psychiatrists, and genetic counsellors would be the key for optimal dissemination of this intervention. This review presents a broad conceptual background of pharmacogenetics/pharmacogenomics, its potential in psychiatry in particular, together with clinical evidence, and the accompanying challenges for its effective implementation in clinical settings

Histopathological spectrum of lichen sclerosus Et atrophicus

Introduction: Lichen sclerosus (LS) et atrophicus is an inflammatory disorder of unknown etiology affecting skin and mucosa, especially the genital area. Clinically, its main features are whitish papules which converge to form plaques and atrophic patches. Histopathology of LS et atrophicus is characterized by the constellation of an atrophic epidermis with loss of rete ridges, some lymphocytes in the basal layer, a subepidermal band of sclerosis, and a lichenoid infiltrate of lymphocytes beneath that band is diagnostic of LS. Materials and Methods: Skin specimens from 25 patients with LS were collected from the hospital records for 5 years. The diagnosis of all cases was made on the basis of clinical morphology and histopathologic features. Sections were stained with hematoxylin and eosin, periodic acid-Schiff, and Elastic-Van Gieson. Criteria evaluated included hyperkeratosis, epidermal atrophy, follicular plugging, basal cell vacuolation, vascular ectasia, hyalinosis, inflammatory infiltrate, dermal edema, and deep dermal fibrosis. Results and Conclusion: Of a total of 25 patients, 18 patients had extragenital (EG) LS and 7 had genital manifestations. Mean age of patients with EG was 28 years, and genital was 38 years. To summarize, the main histopathological findings seen in LS are essentially the same as reported in literature, namely, hyperkeratosis, epidermal atrophy, follicular plugging, basal cell vacuolation, vascular ectasia, hyalinosis, inflammatory infiltrate, dermal edema, and deep dermal fibrosis. Moreover, some interesting differences between the EG and genital forms of LS were seen. However, since the figures are too small to comment on, studies comprising larger series of patients are required to bring out a statistical significance

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Not AvailableAssembly of genome sequences of a microbial community is computationally challenging and complex than its single genome counterparts. Keeping in view the volume, diversity and varied abundance of different microbes, number of metagenome assemblers have been developed addressing specific associated computational issues mainly following De Bruijn Graph (DBG) and Overlap Layout Consensus (OLC) approaches. It is very pertinent to understand different computational approaches and issues of metagenomic assembly to further improve them with respect to time and computational resource requirements. Therefore, the main objective of this article is to discuss various etagenomics assemblers with respect to their development addressing major computational issues. Initially the computational perspective of single genome assemblers based on OLC and DBG graph construction approaches was described. This is followed by review of metagenomic assemblers with respect to the algorithm implemented for addressing issues in metagenome assembly. Further, performance of some of the popular metagenome assemblers were empirically evaluated with respect to their run time and memory requirements by taking diversified benchmark metagenomics data at ICAR-IASRI, New Delhi in 2019. It was concluded that performance of assemblers varied considerably on these datasets and there is further need to make an effort to develop new tools or to modify the existing ones using efficient algorithms and data structures.Not Availabl

Air Pollution and Cognitive Impairment across the Life Course in Humans : A Systematic Review with Specific Focus on Income Level of Study Area

Cognitive function is a crucial determinant of human capital. The Lancet Commission (2020) has recognized air pollution as a risk factor for dementia. However, the scientific evidence on the impact of air pollution on cognitive outcomes across the life course and across different income settings, with varying levels of air pollution, needs further exploration. A systematic review was conducted, using Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) Guidelines to assess the association between air pollution and cognitive outcomes across the life course with a plan to analyze findings as per the income status of the study population. The PubMed search included keywords related to cognition and to pollution (in their titles) to identify studies on human participants published in English until 10 July 2020. The search yielded 84 relevant studies that described associations between exposure to air pollutants and an increased risk of lower cognitive function among children and adolescents, cognitive impairment and decline among adults, and dementia among older adults with supportive evidence of neuroimaging and inflammatory biomarkers. No study from low-and middle-income countries (LMICs)was identified despite high levels of air pollutants and high rates of dementia. To conclude, air pollution may impair cognitive function across the life-course, but a paucity of studies from reLMICs is a major lacuna in research

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Not AvailableLate blight is a serious disease in potato caused by Phytophthora infestans. To date only few miRNA have been discovered which are related to late blight disease of potato during host pathogen interaction. Recent studies showed that miRNA, an important gene expression regulator, plays a very important role in host-pathogen interaction by silencing genes either by destructing or blocking of translation of mRNA.Not Availabl

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Not AvailableBackground: Binning of metagenomic reads is an active area of research, and many unsupervised machine learning-based techniques have been used for taxonomic independent binning of metagenomic reads. Objective: It is important to find the optimum number of the cluster as well as develop an efficient pipeline for deciphering the complexity of the microbial genome. Methods: Applying unsupervised clustering techniques for binning requires finding the optimal number of clusters beforehand and is observed to be a difficult task. This paper describes a novel method, MetaConClust, using coverage information for grouping of contigs and automatically finding the optimal number of clusters for binning of metagenomics data using a consensus-based clustering approach. The coverage of contigs in a metagenomics sample has been observed to be directly proportional to the abundance of species in the sample and is used for grouping of data in the first phase by MetaConClust. The Partitioning Around Medoid (PAM) method is used for clustering in the second phase for generating bins with the initial number of clusters determined automatically through a consensus- based method. Results: Finally, the quality of the obtained bins is tested using silhouette index, rand Index, recall, precision, and accuracy. Performance of MetaConClust is compared with recent methods and tools using benchmarked low complexity simulated and real metagenomic datasets and is found better for unsupervised and comparable for hybrid methods.Not Availabl

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Not AvailableCereals are the most important food crops and are considered key contributors to global food security. Loss due to abiotic stresses in cereal crops is limiting potential productivity in a significant manner. The primary reasons for abiotic stresses are abrupt temperature, variable rainfall, and declining nutrient status of the soil. Varietal development is the key to sustaining productivity under influence of multiple abiotic stresses and must be studied in context with genomics and molecular breeding. Recently, advances in a plethora of Next Generation Sequencing (NGS) based methods have accelerated the enormous genomic data generation associated with stress-induced transcripts such as microarray, RNAseq, Expressed Sequenced Tag (ESTs), etc. Many databases related to microarray and RNA-seq based transcripts have been developed and profusely utilized. However, an abundant amount of transcripts related to abiotic stresses in various cereal crops arising from EST technology are available but still remain underutilized in absence of a consolidated database. In this study, an attempt has been made with a primary goal to integrate, analyse, and characterise the available resources of ESTs responsive to abiotic stresses in major cereals. The developed CerealESTdb presents a customisable search in two different ways in the form of searchable content for easy access and potential use. This database comprises ESTs from four major cereal crops, namely rice (Oryza sativa L.), wheat (Triticum aestivum L.), sorghum (Sorghum bicolour L.), and maize (Zea mays L.), under a set of abiotic stresses. The current statistics of this cohesive database consists of 55,826 assembled EST sequences, 51,791 predicted genes models, and their 254,609 gene ontology terms including extensive information on 1,746 associated metabolic pathways. We anticipate that developed CerealESTdb will be helpful in deciphering the knowledge of complex biological phenomena under abiotic stresses to accelerate the molecular breeding programs towards the development of crop cultivars resilient to abiotic stresses. The CerealESTdb is publically available with the URL http://cabgrid.res.in/CerealESTDb.Not Availabl

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Not AvailableRice is an important staple food grain consumed by most of the population around the world. With climate and environmental changes, rice has undergone a tremendous stress state which has impacted crop production and productivity. Plant growth hormones are essential component that controls the overall outcome of the growth and development of the plant. Cytokinin is a hormone that plays an important role in plant immunity and defense systems. Trans-zeatin is an active form of cytokinin that can affect plant growth which is mediated by a multi-step two-component phosphorelay system that has different roles in various developmental stages. Systems biology is an approach for pathway analysis to trans-zeatin treated rice that could provide a deep understanding of different molecules associated with them. In this study, we have used a weighted gene co-expression network analysis method to identify the functional modules and hub genes involved in the cytokinin pathway. We have identified nine functional modules comprising of different hub genes which contribute to the cytokinin signaling route. The biological significance of these identified hub genes has been tested by applying well-proven statistical techniques to establish the association with the experimentally validated QTLs and annotated by the DAVID server. The establishment of key genes in different pathways has been confirmed. These results will be useful to design new stress-resistant cultivars which can provide sustainable yield in stress-specific conditions.Not Availabl