Wealth-based disparities in the prevalence of short birth interval in India: insights from NFHS-5.

BACKGROUND: Short birth interval (SBI) has profound implications for the health of both mothers and children, yet there remains a notable dearth of studies addressing wealth-based inequality in SBI and its associated factors in India. This study aims to address this gap by investigating wealth-based disparities in SBI and identifying the underlying factors associated with SBI in India. METHODS: We used information on 109,439 women of reproductive age (15-49 years) from the fifth round of the National Family Health Survey (2019-21). We assessed wealth-based inequality in SBI for India and its states using the Erreygers Normalised Concentration Index (ECI). Additionally, we used a multilevel binary logistic regression to assess the factors associated with SBI in India. RESULTS: In India, the prevalence of SBI was 47.8% [95% CI: 47.4, 48.3] during 2019-21, with significant variation across states. Bihar reported the highest prevalence of SBI at 61.2%, while Sikkim the lowest at 18.1%. SBI prevalence was higher among poorer mothers compared to richer ones (Richest: 33.8% vs. Poorest: 52.9%). This wealth-based inequality was visible in the ECI as well (ECI= -0.13, p < 0.001). However, ECI varied considerably across the states. Gujarat, Punjab, and Manipur exhibited the highest levels of wealth-based inequality (ECI= -0.28, p < 0.001), whereas Kerala showed minimal wealth-based inequality (ECI= -0.01, p = 0.643). Multilevel logistic regression analysis identified several factors associated with SBI. Mothers aged 15-24 (OR: 12.01, p < 0.001) and 25-34 (2.92, < 0.001) were more likely to experience SBI. Women who married after age 25 (3.17, < 0.001) and those belonging to Scheduled Caste (1.18, < 0.001), Scheduled Tribes (1.14, < 0.001), and Other Backward Classes (1.12, < 0.001) also had higher odds of SBI. Additionally, the odds of SBI were higher among mothers in the poorest (1.97, < 0.001), poorer (1.73, < 0.001), middle (1.62, < 0.001), and richer (1.39, < 0.001) quintiles compared to the richest quintile. Women whose last child had passed away were also significantly more likely to have SBI (2.35, < 0.001). Furthermore, mothers from communities with lower average schooling levels (1.18, < 0.001) were more likely to have SBI. Geographically, mothers from eastern (0.67, < 0.001) and northeastern (0.44, < 0.001) regions of India were less likely to have SBI. CONCLUSION: The significant wealth-based inequality in SBI in India highlights the need for targeted interventions focusing on economically disadvantaged women, particularly in states with high SBI prevalence. Special attention should be given to younger mothers and those from socially disadvantaged groups to enhance maternal and child health outcomes across the country.

Comparative transcriptomic analysis of the nodulation-competent zone and inference of transcription regulatory network in silicon applied Glycine max [L.]-Merr. Roots.

KEY MESSAGE: The study unveils Si's regulatory influence by regulating DEGs, TFs, and TRs. Further bHLH subfamily and auxin transporter pathway elucidates the mechanisms enhancing root development and nodulation. Soybean is a globally important crop serving as a primary source of vegetable protein for millions of individuals. The roots of these plants harbour essential nitrogen fixing structures called nodules. This study investigates the multifaceted impact of silicon (Si) application on soybean, with a focus on root development, and nodulation employing comprehensive transcriptomic analyses and gene regulatory network. RNA sequence analysis was utilised to examine the change in gene expression and identify the noteworthy differentially expressed genes (DEGs) linked to the enhancement of soybean root nodulation and root development. A set of 316 genes involved in diverse biological and molecular pathways are identified, with emphasis on transcription factors (TFs) and transcriptional regulators (TRs). The study uncovers TF and TR genes, categorized into 68 distinct families, highlighting the intricate regulatory landscape influenced by Si in soybeans. Upregulated most important bHLH subfamily and the involvement of the auxin transporter pathway underscore the molecular mechanisms contributing to enhanced root development and nodulation. The study bridges insights from other research, reinforcing Si's impact on stress-response pathways and phenylpropanoid biosynthesis crucial for nodulation. The study reveals significant alterations in gene expression patterns associated with cellular component functions, root development, and nodulation in response to Si.

Microbial genomics: a potential toolkit for forensic investigations.

Microbial forensics is a new discipline of science that analyzes evidence related to biological crime through the uniqueness and abundance of microorganisms and their toxins. Microorganisms remain alive longer than any other trace of biological evidence, such as DNA, fingerprints, and fibers, because of the protective cell membrane or capsules. Microbiological research has opened up various possibilities for forensic investigations of microbial flora. Current molecular technologies, including DNA sequencing, whole-genome sequencing, metagenomics, DNA fingerprinting, and molecular phylogeny, provide valid results for forensic investigations. Recent advancements in genome sequencing technologies, genetic data generation, and bioinformatic tools have significantly improved microbial sampling methods and forensic analyses. In this review, we discuss the applications of microbial genomic tools and technologies in forensic investigations, including human identification, geolocation, and causes of death.

Spatiotemporal change in socioeconomic inequality in hygienic menstrual product use among adolescent girls in India during 2015-2019.

BACKGROUND: The use of hygienic products, such as sanitary napkins, tampons, and menstrual cups, to absorb menstrual blood is vital for the health and well-being of adolescent girls in India. However, the degree of inequity in the use of such products among this subpopulation remains inadequately explored. To fill this critical knowledge gap, this study aims to investigate the spatiotemporal dynamics of hygienic product use among adolescent girls in India from 2015 to 2020. METHODS: In this cross-sectional study, we analyzed data from 117,749 to 114,839 adolescent girls aged 15-19, obtained from two consecutive rounds of the National Family Health Survey (NFHS) conducted in India during 2015-16 and 2019-21. Our approach involved utilizing Erreygers' Concentration Index (ECI) and Concentration Curve to quantitatively assess and visually represent socioeconomic inequality in hygienic product usage. Additionally, we investigated the spatiotemporal variation in this inequality over the study period and decomposed the ECI to identify the key contributing factors. RESULTS: The findings reveal that hygienic product usage among adolescent girls in India has increased by 13 percentage points (PP), from 37% in 2015-16 to 50% in 2019-21. This increase is also visible across all household wealth quintiles. However, the bottom quintiles experienced a greater rise (+ 15 to 16 PP) than the top quintile (+ 8 PP). During the study period, the ECI reduced marginally, from 0.48 in 2015-16 to 0.43 in 2019-21. However, the extent of this reduction varied across different states. The greatest reduction in ECI was recorded in Punjab (-0.23 points), Telangana (-0.16 points), and West Bengal (-0.14 points). In contrast, there were a number of states with high socioeconomic inequality (ECI > 0.30) in 2015-16, where inequality reduction was minimal (< 0.05 points) over the study period. This included more developed states of Kerala, Karnataka, Maharashtra and Gujarat and relatively less developed states of Odisha, Jharkhand, Chhattisgarh, Uttar Pradesh, and Assam. Some states, such as Bihar and Madhya Pradesh, recorded an increase in socioeconomic inequality over the study period, with ECI rising to 0.31 and 0.46 (highest in the country) in 2019-21. The decomposition analysis revealed that the inequality in using hygienic products was primarily explained by place of residence, exposure to mass-media, education, and region of residence. CONCLUSIONS: The findings suggest the need for targeted policies to reduce existing socioeconomic inequality in the usage of hygienic products among adolescent girls in India. Specifically, interventions should target regions with low use of hygienic products, economically disadvantaged groups, and poor and vulnerable populations. State-specific policies and programs are also necessary to address the disparities in socioeconomic inequality. Additionally, efforts to reduce inequality should address the underlying factors contributing to inequality.

Novel CRISPR-Cas Systems: An Updated Review of the Current Achievements, Applications, and Future Research Perspectives.

According to Darwin's theory, endless evolution leads to a revolution. One such example is the Clustered Regularly Interspaced Palindromic Repeats (CRISPR)-Cas system, an adaptive immunity system in most archaea and many bacteria. Gene editing technology possesses a crucial potential to dramatically impact miscellaneous areas of life, and CRISPR-Cas represents the most suitable strategy. The system has ignited a revolution in the field of genetic engineering. The ease, precision, affordability of this system is akin to a Midas touch for researchers editing genomes. Undoubtedly, the applications of this system are endless. The CRISPR-Cas system is extensively employed in the treatment of infectious and genetic diseases, in metabolic disorders, in curing cancer, in developing sustainable methods for fuel production and chemicals, in improving the quality and quantity of food crops, and thus in catering to global food demands. Future applications of CRISPR-Cas will provide benefits for everyone and will save countless lives. The technology is evolving rapidly; therefore, an overview of continuous improvement is important. In this review, we aim to elucidate the current state of the CRISPR-Cas revolution in a tailor-made format from its discovery to exciting breakthroughs at the application level and further upcoming trends related to opportunities and challenges including ethical concerns.

T-DNA-genome junctions form early after infection and are influenced by the chromatin state of the host genome.

Agrobacterium tumefaciens mediated T-DNA integration is a common tool for plant genome manipulation. However, there is controversy regarding whether T-DNA integration is biased towards genes or randomly distributed throughout the genome. In order to address this question, we performed high-throughput mapping of T-DNA-genome junctions obtained in the absence of selection at several time points after infection. T-DNA-genome junctions were detected as early as 6 hours post-infection. T-DNA distribution was apparently uniform throughout the chromosomes, yet local biases toward AT-rich motifs and T-DNA border sequence micro-homology were detected. Analysis of the epigenetic landscape of previously isolated sites of T-DNA integration in Kanamycin-selected transgenic plants showed an association with extremely low methylation and nucleosome occupancy. Conversely, non-selected junctions from this study showed no correlation with methylation and had chromatin marks, such as high nucleosome occupancy and high H3K27me3, that correspond to three-dimensional-interacting heterochromatin islands embedded within euchromatin. Such structures may play a role in capturing and silencing invading T-DNA.

Root Response to Drought Stress in Rice (Oryza sativa L.).

The current unpredictable climate changes are causing frequent and severe droughts. Such circumstances emphasize the need to understand the response of plants to drought stress, especially in rice, one of the most important grain crops. Knowledge of the drought stress response components is especially important in plant roots, the major organ for the absorption of water and nutrients from the soil. Thus, this article reviews the root response to drought stress in rice. It is presented to provide readers with information of use for their own research and breeding program for tolerance to drought stress in rice.

A novel alignment-free method to classify protein folding types by combining spectral graph clustering with Chou's pseudo amino acid composition.

The present work employs pseudo amino acid composition (PseAAC) for encoding the protein sequences in their numeric form. Later this will be arranged in the similarity matrix, which serves as input for spectral graph clustering method. Spectral methods are used previously also for clustering of protein sequences, but they uses pair wise alignment scores of protein sequences, in similarity matrix. The alignment score depends on the length of sequences, so clustering short and long sequences together may not good idea. Therefore the idea of introducing PseAAC with spectral clustering algorithm came into scene. We extensively tested our method and compared its performance with other existing machine learning methods. It is consistently observed that, the number of clusters that we obtained for a given set of proteins is close to the number of superfamilies in that set and PseAAC combined with spectral graph clustering shows the best classification results.

Isolation and molecular characterization of multidrug­resistant Escherichia coli from chicken meat.

Antibiotics in animal farms play a significant role in the proliferation and spread of antibiotic-resistant genes (ARGs) and antibiotic-resistant bacteria (ARB). The dissemination of antibiotic resistance from animal facilities to the nearby environment has become an emerging concern. The present study was focused on the isolation and molecular identification of Escherichia coli (E. coli) isolates from broiler chicken meat and further access their antibiotic-resistant profile against different antibiotics. Broiler chicken meat samples were collected from 44 retail poultry slaughter shops in Prayagraj district, Uttar Pradesh, India. Standard bacteriological protocols were followed to first isolate the E. coli, and molecular characterization was performed with genus-specific PCR. Phenotypic and genotypic antibiotic-resistant profiles of all confirmed 154 E. coli isolates were screened against 09 antibiotics using the disc diffusion and PCR-based method for selected resistance genes. In antibiotic sensitivity testing, the isolates have shown maximum resistance potential against tetracycline (78%), ciprofloxacin (57.8%), trimethoprim (54.00%) and erythromycin (49.35%). E. coli bacterial isolates have shown relative resistant to amoxicillin-clavulanic acid (43.00%) and against ampicillin (44.15%). Notably, 64.28% E. coli bacteria were found to be multidrug resistant. The results of PCR assays exposed that tetA and blaTEM genes were the most abundant genes harboured by 83 (84.0%) and 82 (82.0%) out of all 99 targeted E. coli isolates, followed by 48.0% for AmpC (CITM) gene and cmlA (23.00%) for chloramphenicol resistance. It is notable that most of the isolates collected from chicken meat samples were multidrug resistant (> 3 antibiotics), with more than 80% of them carrying tetracycline (tetA) and beta-lactam gene (blaTEM). This study highlights the high risk associated with poultry products due to MDR-E. coli and promote the limited use of antibiotics in poultry farms. Supplementary Information: The online version contains supplementary material available at 10.1007/s13205-024-03950-7.

Phylogenetic Analysis of Anti-CRISPR and Member Addition in the Families.

CRISPR-Cas is a widespread anti-viral adaptive immune system in the microorganisms. Viruses living in bacteria or some phages carry anti-CRISPR proteins to evade immunity by CRISPR-Cas. The anti-CRISPR proteins are prevalent in phages capable of lying dormant in a CRISPR-carrying host, while their orthologs frequently found in virulent phages. Here, we propose a probabilistic strategy of ancestral sequence reconstruction (ASR) and Hidden Markov Model (HMM) profile search to fish out sequences of anti-CRISPR proteins from environmental metagenomic, human microbiome metagenomic, human microbiome reference genome, and NCBI's non-redundant databases. Our results revealed that the metagenome database dark matter might contain anti-CRISPR encoding genes.

Prevalence and determinants of anaemia among men in rural India: Evidence from a nationally representative survey.

Anaemia among men is a significant health issue which has not been given due importance. Only a handful of studies have captured the prevalence of anaemia among men. There is dearth of evidence base on anaemia among men in India. Therefore, this study attempts to fill this research gap by examining the socioeconomic, geographic, health-related, and behavioural differentials of anaemia among rural men in India. We analysed a cross-sectional sample of 61,481 men aged between 15-54 and living in rural areas from the National Family Health Survey (NFHS-5), conducted in 2019-21. Bivariate statistics and multivariable logistic regression were employed to assess the factors associated with anaemia. In rural India, three out of ten men were found to be anaemic. Older men [49-54 years] (Odds Ratio: 1.10, 95% CI, 1.00-1.21), men without a formal education (OR: 1.36, 95% CI, 1.26-1.47), those from Scheduled Tribes (OR: 1.48, 95% CI, 1.39-1.58) and men who belonged to the poorest wealth quintile (OR: 1.24, 95% CI: 1.25-1.35) had a higher risk of anaemia. Men who were underweight were more likely to be anaemic (OR: 1.36, 95% CI: 1.30-1.43). When compared to the central region, men from the eastern (OR: 1.47, 95% CI: 1.39-1.55) parts of India had higher a risk of anaemia. The findings suggest the need to recognise anaemia among men as a public health issue. When developing policy, significant variation in socioeconomic, geographic, health-related, and behavioural factors must be taken into account. Men should also be screened on a regular basis in order to reduce the national burden of anaemia.

High-Throughput Root Imaging Analysis Reveals Wide Variation in Root Morphology of Wild Adzuki bean (Vigna angularis) Accessions.

Root system architecture and morphological diversification in wild accessions are important for crop improvement and productivity in adzuki beans. In this study, via analysis using 2-dimensional (2D) root imaging and WinRHIZO Pro software, we described the root traits of 61 adzuki bean accessions in their early vegetative growth stage. These accessions were chosen for study because they are used in Korea's crop improvement programs; however, their root traits have not been sufficiently investigated. Analysis of variance revealed a significant difference between the accessions of all measured root traits. Distribution analysis demonstrated that most of the root traits followed normal distribution. The accessions showed up to a 17-fold increase in the values in contrasting accessions for the root traits. For total root length (TRL), the values ranged from 82.43 to 1435 cm, and for surface area (SA), they ranged from 12.30 to 208.39 cm2. The values for average diameter (AD) ranged from 0.23 to 0.56 mm. Significant differences were observed for other traits. Overall, the results showed that the accession IT 305544 had the highest TRL, SA, and number of tips (NT), whereas IT 262477 and IT 262492 showed the lowest values for TRL, SA, and AD. Principal component analysis showed an 89% variance for PC1 and PC2. K-mean clustering explained 77.4% of the variance in the data and grouped the accessions into three clusters. All six root traits had greater coefficients of variation (≥15%) among the tested accessions. Furthermore, to determine which root traits best distinguished different accessions, the correlation within our set of accessions provided trait-based ranking depending on their contribution. The identified accessions may be advantageous for the development of new crossing combinations to improve root features in adzuki beans during the early growth stage. The root traits assessed in this study could be attributes for future adzuki bean crop selection and improvement.

Silicon Application Differentially Modulates Root Morphology and Expression of PIN and YUCCA Family Genes in Soybean (Glycine max L.).

Silicon (Si) is absorbed and accumulated by some plant species; it has been shown to improve plant growth and performance. The beneficial role of Si in plants is based on the fundamental assumptions, and the biological function of Si is still being researched due to its complex nature, distinctiveness, and interaction. The present study included two distinct experiment sets: a screening test and an advanced test. In the initial examination, we used 21 soybean (Glycine max L.) cultivars. Following the evaluation, we chose four cultivars to investigate further. In particular, the positive response cultivars, Taeseon and Geomjeongsaeol, showed a 14% increase in net photosynthesis (P N ), and a 19-26% increase in transpiration in Si-treated plants when compared to the control plants. Si-treated Taeseon, Geomjeongsaeol, and Somyongkong, Mallikong cultivars showed significant differences in root morphological traits (RMTs) and root system architecture (RSA) when compared to the control plants. Taeseon and Geomjeongsaeol showed a 26 and 46% increase in total root length (TRL) after Si application, respectively, compared to the control, whereas Mallikong and Somyongkong showed 26 and 20% decrease in TRL after Si treatment, respectively, compared to the control. The Si application enhanced the overall RMTs and RSA traits in Taeseon and Geomjeongsaeol; however, the other two cultivars, Somyongkong and Mallikong, showed a decrease in such RMTs and RATs. Furthermore, to understand the underlying molecular mechanism and the response of various cultivars, we measured the Si content and analyzed the gene expression of genes involved in auxin transport and root formation and development. We showed that the Si content significantly increased in the Si-treated Somyongkong (28%) and Taeseon (30%) compared to the control cultivars. Overall, our results suggested that Si affects root development as well as the genes involved in the auxin synthesis, transport pathway, and modulates root growth leading to cultivar-dependent variation in soybeans.

A case of ischemic stroke and transient thrombocytopenia in a young female following adenoviral vector-based COVID-19 vaccination: Was the association incidental or causal?

Since March 2021, cases with unusual clots, particularly cerebral venous sinus thrombosis and splanchnic vein thrombosis, have been reported worldwide following adenoviral vector-based coronavirus disease 2019 (COVID-19) vaccination. This entity has been termed vaccine-induced thrombotic thrombocytopenia (VITT). We report a 23-year-old healthy female who developed seizures, altered sensorium, and left hemiparesis, 20 days after receiving the first dose of adenoviral vector-based COVID-19 vaccine "Covishield™." The patient had transient thrombocytopenia. The D-dimer level was 2460 ng/mL. Magnetic resonance imaging (MRI) demonstrated occlusion of M2 segment of the middle cerebral artery and cerebral infarction. Platelet factor-4 antibodies level was normal. Treatment with aspirin and antiepileptic drugs resulted in a remarkable recovery. This is the first Indian case report of ischemic stroke and transient thrombocytopenia following SARS-CoV-2 ChAdOx1 nCoV-19 vaccination. Our case had clinical features consistent with the diagnosis of probable VITT. Familiarity with VITT is crucial because timely treatment with non-heparin anticoagulants and intravenous immunoglobulin improves the outcome.

Silicon Effects on the Root System of Diverse Crop Species Using Root Phenotyping Technology.

Roots play an essential function in the plant life cycle, as they utilize water and essential nutrients to promote growth and plant productivity. In particular, root morphology characteristics (such as length, diameter, hairs, and lateral growth) and the architecture of the root system (spatial configuration in soil, shape, and structure) are the key elements that ensure growth and a fine-tuned response to stressful conditions. Silicon (Si) is a ubiquitous element in soil, and it can affect a wide range of physiological processes occurring in the rhizosphere of various crop species. Studies have shown that Si significantly and positively enhances root morphological traits, including root length in rice, soybean, barley, sorghum, mustard, alfalfa, ginseng, and wheat. The analysis of these morphological traits using conventional methods is particularly challenging. Currently, image analysis methods based on advanced machine learning technologies allowed researchers to screen numerous samples at the same time considering multiple features, and to investigate root functions after the application of Si. These methods include root scanning, endoscopy, two-dimensional, and three-dimensional imaging, which can measure Si uptake, translocation and root morphological traits. Small variations in root morphology and architecture can reveal different positive impacts of Si on the root system of crops, with or without exposure to stressful environmental conditions. This review comprehensively illustrates the influences of Si on root morphology and root architecture in various crop species. Furthermore, it includes recommendations in regard to advanced methods and strategies to be employed to maintain sustainable plant growth rates and crop production in the currently predicted global climate change scenarios.

Investigation of Root Morphological Traits Using 2D-Imaging among Diverse Soybeans (Glycine max L.).

Roots are the most important plant organ for absorbing essential elements, such as water and nutrients for living. To develop new climate-resilient soybean cultivars, it is essential to know the variation in root morphological traits (RMT) among diverse soybean for selecting superior root attribute genotypes. However, information on root morphological characteristics is poorly understood due to difficulty in root data collection and visualization. Thus, to overcome this problem in root research, we used a 2-dimensional (2D) root image in identifying RMT among diverse soybeans in this research. We assessed RMT in the vegetative growth stage (V2) of 372 soybean cultivars propagated in polyvinyl chloride pipes. The phenotypic investigation revealed significant variability among the 372 soybean cultivars for RMT. In particular, RMT such as the average diameter (AD), surface area (SA), link average length (LAL), and link average diameter (LAD) showed significant variability. On the contrary RMT, as with total length (TL) and link average branching angle (LABA), did not show differences. Furthermore, in the distribution analysis, normal distribution was observed for all RMT; at the same time, difference was observed in the distribution curve depending on individual RMT. Thus, based on overall RMT analysis values, the top 5% and bottom 5% ranked genotypes were selected. Furthermore, genotypes that showed most consistent for overall RMT have ranked accordingly. This ultimately helps to identify four genotypes (IT 16538, IT 199127, IT 165432, IT 165282) ranked in the highest 5%, whereas nine genotypes (IT 23305, IT 208266, IT 165208, IT 156289, IT 165405, IT 165019, IT 165839, IT 203565, IT 181034) ranked in the lowest 5% for RMT. Moreover, principal component analysis clustered cultivar 2, cultivar 160, and cultivar 274 into one group with high RMT values, and cultivar 335, cultivar 40, and cultivar 249 with low RMT values. The RMT correlation results revealed significantly positive TL and AD correlations with SA (r = 0.96) and LAD (r = 0.85), respectively. However, negative correlations (r = -0.43) were observed between TL and AD. Similarly, AD showed a negative correlation (r = -0.22) with SA. Thus, this result suggests that TL is a more vital factor than AD for determining SA compositions.

A Large Root Phenome Dataset Wide-Opened the Potential for Underground Breeding in Soybean.

The root is the most critical plant organ for water and nutrient acquisition. Although the root is vital for water and nutrient uptake, the diverse root characters of soybean still need to be identified owing to the difficulty of root sampling. In this study, we used 150 wild and 50 cultivated soybean varieties to collect root image samples. We analyzed root morphological traits using acquired-image. Except for the main total length (MTL), the root morphological traits for most cultivated and wild plants were significantly different. According to correlation analysis, the wild and cultivated plants showed a significant correlation among total root length (TRL), projected area (PA), forks, total lateral length (TLL), link average diameter, and MTL. In particular, TRL was highly correlated with PA in both cultivated (0.92) and wild (0.82) plants compared with between MTL (0.43 for cultivated and 0.27 for wild) and TLL (0.82 for cultivated and 0.52 for wild). According to principal component analysis results, both plants could be separated; however, there was some overlap of the traits among the wild and cultivated individuals from some regions. Nevertheless, variation among the cultivated plants was higher than that found in the wild plants. Furthermore, three groups, including MTL, TLL, and the remaining traits, could explain all the variances.

Potential Environmental and Human Health Risks Caused by Antibiotic-Resistant Bacteria (ARB), Antibiotic Resistance Genes (ARGs) and Emerging Contaminants (ECs) from Municipal Solid Waste (MSW) Landfill.

The disposal of municipal solid waste (MSW) directly at landfills or open dump areas, without segregation and treatment, is a significant concern due to its hazardous contents of antibiotic-resistant bacteria (ARB), antibiotic resistance genes (ARGs), and metal resistance genes (MGEs). The released leachate from landfills greatly effects the soil physicochemical, biological, and groundwater properties associated with agricultural activity and human health. The abundance of ARB, ARGs, and MGEs have been reported worldwide, including MSW landfill sites, animal husbandry, wastewater, groundwater, soil, and aerosol. This review elucidates the occurrence and abundance of ARB, ARGs, and MRGs, which are regarded as emerging contaminants (ECs). Recently, ECs have received global attention because of their prevalence in leachate as a substantial threat to environmental and public health, including an economic burden for developing nations. The present review exclusively discusses the demands to develop a novel eco-friendly management strategy to combat these global issues. This review also gives an intrinsic discussion about the insights of different aspects of environmental and public health concerns caused due to massive leachate generation, the abundance of antibiotics resistance (AR), and the effects of released leachate on the various environmental reservoirs and human health. Furthermore, the current review throws light on the source and fate of different ECs of landfill leachate and their possible impact on the nearby environments (groundwater, surface water, and soil) affecting human health. The present review strongly suggests the demand for future research focuses on the advancement of the removal efficiency of contaminants with the improvement of relevant landfill management to reduce the potential effects of disposable waste. We propose the necessity of the identification and monitoring of potential environmental and human health risks associated with landfill leachate contaminants.

Detecting antimicrobial peptides by exploring the mutual information of their sequences.

The rise of antibiotic resistance in pathogenic bacteria is a growing concern for every part of the world. The present study shows the prediction efficiency of mutual information for the classification of antimicrobial peptides. The proven role of antimicrobial peptides (AMPs) to fight against multidrug-resistant pathogens and AMP's low toxic properties laid the foundation of computational methods to play their role in detecting AMPs from non-AMPs. Mutual information vectors (MIV) were created for AMP/non-AMP sequences and then fed to different machine learning classifiers out of which a random forest (RF) classifier showed best results for predicting AMPs. Random forest classifiers were evaluated on benchmark datasets by 10-fold cross-validation. The proposed MIV-RF method showed better prediction accuracy, MCC (Matthews correlation coefficient), and AUC-ROC (Area Under The Curve-Receiver Operating Characteristics) than available methods for detecting AMPs.Communicated by Ramaswamy H. Sarma.

Next-Generation Sequencing: An Emerging Tool for Drug Designing.

BACKGROUND: With the outbreak of high throughput next-generation sequencing (NGS), the biological research of drug discovery has been directed towards the oncology and infectious disease therapeutic areas, with extensive use in biopharmaceutical development and vaccine production. METHOD: In this review, an effort was made to address the basic background of NGS technologies, potential applications of NGS in drug designing. Our purpose is also to provide a brief introduction of various Nextgeneration sequencing techniques. DISCUSSIONS: The high-throughput methods execute Large-scale Unbiased Sequencing (LUS) which comprises of Massively Parallel Sequencing (MPS) or NGS technologies. The Next geneinvolved necessarily executes Largescale Unbiased Sequencing (LUS) which comprises of MPS or NGS technologies. These are related terms that describe a DNA sequencing technology which has revolutionized genomic research. Using NGS, an entire human genome can be sequenced within a single day. CONCLUSION: Analysis of NGS data unravels important clues in the quest for the treatment of various lifethreatening diseases and other related scientific problems related to human welfare.