Browsing by Author "Rajesh Kumar Singh"

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A genetic framework for regulation and seasonal adaptation of shoot architecture in hybrid aspen
(National Academy of Sciences, 2020) Jay P. Maurya; Pal C. Miskolczi; Sanatkumar Mishra; Rajesh Kumar Singh; Rishikesh P. Bhalerao
Shoot architecture is critical for optimizing plant adaptation and productivity. In contrast with annuals, branching in perennials native to temperate and boreal regions must be coordinated with seasonal growth cycles. How branching is coordinated with seasonal growth is poorly understood. We identified key components of the genetic network that controls branching and its regulation by seasonal cues in the model tree hybrid aspen. Our results demonstrate that branching and its control by seasonal cues is mediated by mutually antagonistic action of aspen orthologs of the flowering regulators TERMINAL FLOWER 1 (TFL1) and APETALA1 (LIKE APETALA 1/LAP1). LAP1 promotes branching through local action in axillary buds. LAP1 acts in a cytokinin-dependent manner, stimulating expression of the cellcycle regulator AIL1 and suppressing BRANCHED1 expression to promote branching. Short photoperiod and low temperature, the major seasonal cues heralding winter, suppress branching by simultaneous activation of TFL1 and repression of the LAP1 pathway. Our results thus reveal the genetic network mediating control of branching and its regulation by environmental cues facilitating integration of branching with seasonal growth control in perennial trees. © 2020 National Academy of Sciences. All rights reserved.
A mathematical model to restore water quality in urban lakes using phoslock
(American Institute of Mathematical Sciences, 2021) Pankaj Kumar Tiwari; Rajesh Kumar Singh; Subhas Khajanchi; Yun Kang; Arvind Kumar Misra
Urban lakes are the life lines for the population residing in the city. Excessive amounts of phosphate entering water courses through household discharges is one of the main causes of deterioration of water quality in these lakes because of the way it drives algal productivity and undesirable changes in the balance of aquatic life. The ability to remove biologically available phosphorus in a lake is therefore a major step towards improving water quality. By removing phosphate from the water column using Phoslock essentially deprives algae and its proliferation. In view of this, we develop a mathematical model to investigate whether the application of Phoslock would significantly reduce the bio-availability of phosphate in the water column. We consider phosphorus, algae, detritus and Phoslock as dynamical variables. In the modeling process, the introduction rate of Phoslock is assumed to be proportional to the concentration of phosphorus in the lake. Further, we consider a discrete time delay which accounts for the time lag involved in the application of Phoslock. Moreover, we investigate behavior of the system by assuming the application rate of Phoslock as a periodic function of time. Our results evoke that Phoslock essentially reduces the concentration of phosphorus and density of algae, and plays crucial role in restoring the quality of water in urban lakes. We observe that for the gradual increase in the magnitude of the delay involved in application of Phoslock, the autonomous system develops limit cycle oscillations through a Hopf-bifurcation while the corresponding nonautonomous system shows chaotic dynamics through quasi-periodic oscillations. © 2021 American Institute of Mathematical Sciences. All rights reserved.
A nonautonomous mathematical model to assess the impact of algae on the abatement of atmospheric carbon dioxide
(World Scientific, 2021) Pankaj Kumar Tiwari; Rajesh Kumar Singh; Debaldev Jana; Yun Kang; Arvind Kumar Misra
The world's oceans have played an important role in sequestering atmospheric carbon dioxide through solubility and the action of algae. Fixation of atmospheric carbon dioxide by photoautotrophic algal cultures has the potential to diminish the release of carbon dioxide into the atmosphere, thereby helping to alleviate the trend toward global warming. This work investigates the role of algae in controlling the level of atmospheric carbon dioxide. Partial Rank Correlation Coefficients (PRCCs) technique is used to address how the concentration of atmospheric carbon dioxide is affected by changes in a specific parameter disregarding the uncertainty over the rest of the model parameters. Parameters related to algal growth are shown to significantly reduce the level of atmospheric CO2. Further, we explore the dynamics of nonautonomous system by incorporating the seasonal variations of some ecologically important model parameters. Our nonautonomous system exhibits globally attractive positive periodic solution, and also the appearance of double periodic solution is observed. Moreover, by letting the seasonally forced parameters as almost periodic functions of time, we show almost periodic behavior of the system. Our findings suggest that the policy makers should focus on continuous addition of nutrients in the ocean to accelerate the algal growth thereby reducing the level of carbon dioxide in the atmosphere. © 2021 World Scientific Publishing Company.
A regulatory module mediating temperature control of cell-cell communication facilitates tree bud dormancy release
(EMBO Press, 2024) Shashank K Pandey; Jay Prakash Maurya; Bibek Aryal; Kamil Drynda; Aswin Nair; Pal Miskolczi; Rajesh Kumar Singh; Xiaobin Wang; Yujiao Ma; Tatiana de Souza Moraes; Emmanuelle M Bayer; Etienne Farcot; George W Bassel; Leah R Band; Rishikesh P Bhalerao
The control of cell–cell communication via plasmodesmata (PD) plays a key role in plant development. In tree buds, low-temperature conditions (LT) induce a switch in plasmodesmata from a closed to an open state, which restores cell-to-cell communication in the shoot apex and releases dormancy. Using genetic and cell-biological approaches, we have identified a previously uncharacterized transcription factor, Low-temperature-Induced MADS-box 1 (LIM1), as an LT-induced, direct upstream activator of the gibberellic acid (GA) pathway. The LIM1-GA module mediates low temperature-induced plasmodesmata opening, by negatively regulating callose accumulation to promote dormancy release. LIM1 also activates expression of FT1 (FLOWERING LOCUS T), another LT-induced factor, with LIM1-FT1 forming a coherent feedforward loop converging on low-temperature regulation of gibberellin signaling in dormancy release. Mathematical modeling and experimental validation suggest that negative feedback regulation of LIM1 by gibberellin could play a crucial role in maintaining the robust temporal regulation of bud responses to low temperature. These results reveal genetic factors linking temperature control of cell–cell communication with regulation of seasonally-aligned growth crucial for adaptation of trees. © The Author(s) 2024.
Advancements of Glucose Monitoring Biosensor: Current State, Generations of Technological Progress and Innovation Dynamics
(Bentham Science Publishers, 2025) Arpita Dua; Abhijit Debnath; Kunal Kumar; Rupa Mazumder; Avijit Mazumder; Rajesh Kumar Singh; Saloni Mangal; Jahanvi Sanchitra; Fahad Khan; Soumya Tripathi; Sukriti Vishwas; Hema Chaudhary; Parul Sharma; Shikha Srivastava
Glucose monitoring is essential for managing diabetes, and continuous glucose monitoring biosensors can offer real-time monitoring with little invasiveness. However, challenges remain in improving sensor accuracy, selectivity, and overall performance. This article aims to review current trends and recent advancements in glucose-monitoring biosensors while evaluating their benefits and limitations for diabetes monitoring. An analysis of current literature on transdermal glucose sensors was conducted, focusing on detection techniques, novel nanomaterials, and integrated sensor systems. Recent research has led to advancements in electrochemical, optical, electromagnetic, and sonochemical sensors for transdermal glucose detection. The use of novel nanomaterials and integrated sensor designs has improved sensitivity, selectivity, and accuracy. However, issues like calibration requirements, motion artifacts, and skin irritation persist. Transdermal glucose sensors show promise for non-invasive, convenient diabetes monitoring but require further enhancements to address limitations in accuracy, reliability, and biocompatibility. Continued research and innovation focusing on sensor materials, designs, and surface chemistry is needed to optimize biosensor performance and utility. The study offers a comprehensive analysis of the present status of technological advancement and highlights areas that need more research. © 2025 Bentham Science Publishers.
ALMOST UNBIASED ESTIMATOR FOR UNKNOWN POPULATION MEDIAN USING AUXILIARY INFORMATION
(ISOSS PUBLICATIONS, 2025) Rajesh Kumar Singh; Sunil Kumar Yadav; Prayas Sharma
This article proposes an innovative estimator for estimating the unknown population median, designed to be nearly unbiased. The bias and mean squared error (MSE) of the proposed estimator are derived upto the first order of approximation. Performance of the proposed estimator is evaluated using MSE and percent relative efficiency (PRE) as key criteria. To validate the theoretical results, three distinct datasets are analyzed. The findings reveal that the proposed estimator consistently outperforms existing alternatives, demonstrating near-unbiasedness and superior efficiency up to the first-order approximation. © 2025 Pakistan Journal of Statistics.
Anticancer natural product from marine invertebrates
(Elsevier Science Ltd., 2020) Rajesh Kumar Singh; Amit Ranjan; Monika Singh; Akhileshwar Kumar Srivastava
Marine invertebrates have been used as therapeutics as well as food since a long time, because of varieties of bioactive compounds and nutrients. The invertebrate marine animals which belong to phylum Porifera, Cnidaria, Annelida, Arthropoda, Mollusca, and Echinodermata represent the animals with the richest biodiversity. These invertebrates have been identified as the main source for marine-derived drug discovery, attributing about 65% of the marine natural products reported to date. The cnidarians have described in many traditional medicine system for medicine for therapeutic use. Most of anticancer marine natural compounds have been isolated from cnidarians, especially from corals. The extensive research on marine natural compounds isolated from invertebrates has showed an opportunity for development of several potent anticancer drugs, as these molecules have been reported for their various modes of action, targeting cell receptors to genetic materials of cancer cells. The anticancer natural product isolated from marine invertebrate have described in this chapter with their mode of action and molecular targets. © 2021 Elsevier Inc. All rights reserved.
Application of Neutrosophic Stratified Ranked Set Sampling: An Efficient Sampling Technique in the Estimation of Average Relative Humidity in USA
(American Scientific Publishing Group (ASPG), 2025) Vishwajeet Singh; Rajesh Kumar Singh; Anamika Kumari
The study examined the shortcomings of conventional statistical techniques in managing unclear or ambiguous data and emphasized the necessity of implementing neutrosophic statistical techniques as a more enhanced remedy. Advanced techniques like neutrosophic statistics (NS) were developed since traditional statistical methods are unable to handle the uncertainty present in ambiguous data. In order to tackle this problem, the study suggested an innovative and novel sampling method called "neutrosophic stratified ranked set sampling (NSRSS)" in addition to specialized neutrosophic estimators for precisely predicting the population mean in the proximity of uncertainty. This novel strategy adjusted ranked set sampling (RSS) techniques to allow the special features of neutrosophic data. Furthermore, the study improved the precision of estimating the population mean in uncertain situations by introducing neutrosophic estimators that use subsidiary information inside the structure of stratified ranked set sampling (SRSS). The work provided theoretical insights into the performance of these estimators by presenting comprehensive formulations of bias and mean squared error (MSE). To illustrate the efficacy of the suggested techniques, the study includes simulation studies, numerical examples conducted using the computer language R. Evaluations utilizing MSE, and percentage relative efficiency (PRE) demonstrated the higher accuracy of the suggested estimators over conventional alternatives. The findings demonstrated the NSRSS's applicability, particularly for predicting population means in situations where heterogeneity and uncertainty are prevalent. Furthermore, it was demonstrated that the estimators and technique produced interval-based findings, which provided a more accurate depiction of the uncertainty related to population parameters. The reliability of the estimators in estimating population means was greatly improved by this interval estimation in combination with a lower MSE. A significant vacuum in the field of statistical research is filled by the study's introduction of estimators and a customized sampling approach made especially for neutrosophic data. This research significantly advances statistical theory and practice by extending traditional statistical approaches to efficiently handle ambiguous data, especially for applications where exact data is few, heterogeneous, or uncertain. The empirical validation through numerical illustrations and simulations conducted in R further solidifies the practicality and robustness of the proposed techniques, reinforcing their applicability to real-world scenarios. © 2025, American Scientific Publishing Group (ASPG). All rights reserved.
Application to Road Traffic Accidents: An Almost Unbiased Estimator for Population Mean Under Ranked Set Sampling and Stratified Ranked Set Sampling
(Springer Science and Business Media B.V., 2025) Sunil Kumar Yadav; Rajesh Kumar Singh; Anamika Kumari
Ranked Set Sampling (RSS) serves as an effective and efficient alternative to Simple Random Sampling (SRS), especially when ranking items is easier than taking precise measurements. Stratified sampling is used for better estimation when the population is heterogeneous. In this work, we introduce a new family of nearly unbiased estimators for estimating the population mean under the RSS and SRSS framework. These estimators are formulated as linear combinations of three established estimators and are specifically developed to minimize bias to the first order. We analytically derive their theoretical properties, including bias and Mean Squared Error (MSE), to evaluate their statistical performance. To support our theoretical claims, we apply the proposed estimators to real-world data and perform extensive simulation experiments under varying sample sizes and correlation settings. We benchmark our estimator against existing ones such as the conventional sample mean, the exponential ratio estimator, and the logarithmic estimator. The assessment is based on key metrics like MSE and Percentage Relative Efficiency (PRE). The findings consistently show that the proposed estimator yields lower MSE and higher PRE, indicating better accuracy and efficiency under both sampling frames. Furthermore, its near-unbiased behaviour enhances its practical applicability, particularly in scenarios where ranking is more feasible than direct measurement. © The Author(s) 2025.
Biopriming with Bacillus subtilis Enhanced the Sulphur Use Efficiency of Indian Mustard under Graded Levels of Sulphur Fertilization
(MDPI, 2023) Sonam Singh; Deepranjan Sarkar; S. Rakesh; Rajesh Kumar Singh; Amitava Rakshit
This study investigated the effect of bioinoculants (Bacillus subtilis and Pseudomonas fluorescens) as biopriming agents under varied sulphur (S) fertilizer levels (0, 20, 30, and 40 kg S ha−1) to enhance sulphur use efficiency (SUE) in Indian mustard. The experiment was conducted during the 2018–19 and 2019–20 winter seasons at the research farm of the Institute of Agricultural Sciences, Banaras Hindu University, Varanasi (25°26′ N, 82°99′ E). A randomized block design was employed to assess the combined effect of biopriming and S fertilization on the partitioning of S in different parts of mustard plants, S uptake, SUE, and soil urease, dehydrogenase, alkaline phosphatase, and arylsulphatase activity. Results showed that the application of S fertilizers along with biopriming significantly increased the S content, uptake, and SUE by plants and enzymes involved in the S mineralization process. Application of 40 kg S ha−1 + B. subtilis resulted in the highest S content in the root (0.12%), stover (0.30%), and seed (0.67%), and the highest total S uptake (2.97 g m−2 in the first year and 3.37 g m−2 in the second year), agronomic use efficiency (8.80 g g−1), apparent S recovery (22.37%), urease activity (156.68 µg NH4+ g−1 hr−1), dehydrogenase activity (42.80 µg TPF g−1 24 hr−1), and arylsulphatase activity (39.94 µg pNP g−1 hr−1). However, the highest alkaline phosphatase activity (129.17 µg pNP g−1 hr−1) was found in the treatment that received 40 kg S ha−1 + P. fluorescens. Further, the different indices of SUE revealed that the effect of biopriming was more prominent in apparent recovery efficiency than agronomic SUE and physiological SUE. Conclusively, the present study demonstrated that seed biopriming with B. subtilis along with S fertilization is more rewarding and can promote sustainable production of Indian mustard. © 2023 by the authors.
Challenges and Progress of Orphan Drug Development for Rare Diseases
(Bentham Science Publishers, 2025) Abhijit Debnath; Rupa Mazumder; Avijit Mazumder; Pankaj Kumar Tyagi; Rajesh Kumar Singh
Rare diseases, defined as conditions affecting fewer than 200,000 people in the United States or less than 1 in 2,000 people in Europe, pose significant challenges for healthcare systems and pharmaceutical research. This comprehensive review examines the evolving landscape of orphan drug development, analyzing scientific, economic, and regulatory challenges while highlighting recent technological breakthroughs and innovative approaches. We explore how artificial intelligence, next-generation sequencing, and personalized medicine are revolutionizing rare disease research and treatment development. The review details key advances in therapeutic approaches, including gene therapy, cell-based treatments, and drug repurposing strategies, which have led to breakthrough treatments for previously untreatable conditions. We analyze the impact of international collaborations, such as the International Rare Diseases Research Consortium, and discuss how regulatory frameworks worldwide have evolved to accelerate orphan drug development. The paper highlights the growing market for orphan drugs, projected to reach $242 billion by 2024 while examining the complex challenges of ensuring treatment accessibility and economic sustainability. We assess innovative clinical trial designs, patient registry development, and emerging strategies in personalized medicine that are transforming the field. Despite notable advancements, significant gaps remain in diagnosis, treatment accessibility, and sustainable funding for rare disease research. The review concludes by proposing specific actions for enhancing international collaboration, improving patient registries, and aligning incentives to address the unmet medical needs of rare disease patients, emphasizing the critical role of continued public-private partnerships and technological innovation in advancing orphan drug development. © 2025 Bentham Science Publishers.
Characterization and evaluation of mycosterol secreted from endophytic strain of Gymnema sylvestre for inhibition of α-glucosidase activity
(Nature Research, 2019) Amit Ranjan; Rajesh Kumar Singh; Saumya Khare; Ruchita Tripathi; Rajesh Kumar Pandey; Anurag Kumar Singh; Vibhav Gautam; Jyoti Shankar Tripathi; Santosh Kumar Singh
Endophytic fungi produce various types of chemicals for establishment of niche within the host plant. Due to symbiotic association, they secrete pharmaceutically important bioactive compounds and enzyme inhibitors. In this research article, we have explored the potent α-glucosidse inhibitor (AGI) produced from Fusarium equiseti recovered from the leaf of Gymnema sylvestre through bioassay-guided fraction. This study investigated the biodiversity, phylogeny, antioxidant activity and α-glucosidse inhibition of endophytic fungi isolated from Gymnema sylvestre. A total of 32 isolates obtained were grouped into 16 genera, according to their morphology of colony and spores. A high biodiversity of endophytic fungi were observed in G. sylvestre with diversity indices. Endophytic fungal strain Fusarium equiseti was identified through DNA sequencing and the sequence was deposited in GenBank database (https://ncbi.nim.nih.gov) with acession number: MF403109. The characterization of potent compound was done by FTIR, LC-ESI-MS and NMR spectroscopic analysis with IUPAC name 17-(5-ethyl-6-methylheptan-2-yl)-10,13-dimethyl-2,3,4,7,8,9,10,11,12,13,14,15,16,17-tetradecahydro-1H-cyclopenta[a] phenanthren-3-ol. The isolated bioactive compound showed significant α-amylase and α-glucosidase inhibition activity with IC50 values, 4.22 ± 0.0005 µg/mL and 69.72 ± 0.001 µg/mL while IC50 values of acarbose was 5.75 ± 0.007 and 55.29 ± 0.0005 µg/mL respectively. This result is higher in comparison to other previous study. The enzyme kinetics study revealed that bioactive compound was competitive inhibitor for α-amylase and α-glucosidase. In-silico study showed that bioactive compound binds to the binding site of α-amylase, similar to that of acarbose but with higher affinity. The study highlights the importance of endophytic fungi as an alternative source of AGI (α-glucosidase inhibition) to control the diabetic condition in vitro. © 2019, The Author(s).
Clean and Efficient Synthesis of Graphene Nanosheets and Rectangular Aligned-Carbon Nanotubes Bundles Using Green Botanical Hydrocarbon Precursor: Sesame Oil
(American Scientific Publishers, 2014) Rajesh Kumar; Rajesh Kumar Singh; Pradip Kumar; Pawan Kumar Dubey; R.S. Tiwari; O.N. Srivastava
A facile and rapid approach was used for the clean and efficient synthesis of graphene nanosheets (GNSs) and rectangular aligned carbon nanotubes (RA-CNTs) bundles. These structures were formed at different hot zones of the furnace. The sesame oil, a green natural precursor is used first time as a hydrocarbon precursor for the synthesis of GNSs and well packed RA-CNTs bundles. GNSs and RA-CNTs bundles were synthesized by spray pyrolysis of sesame oil with ferrocene as a catalyst, inside silica tube at 800 °C. This new precursor is appropriate for the synthesis of high quality and clean GNSs and RA-CNTs bundles. GNSs show the formation of few layers graphene which contains 6-8 graphene layers. FTIR spectra confirm that there is no more functional group attached on the surface of as synthesized materials. Growth of these nanostructures strongly depends on the temperature inside the tube. Raman studies show intense 2D peak as compared to G peak, signifying presence of GNSs. The investigations reveal that these novel carbon nanostructures synthesized by sesame oil are clean from carbonaceous impurities. © 2014 by American Scientific Publishers.
Common techniques and methods for screening of natural products for developing of anticancer drugs
(Elsevier Science Ltd., 2020) Monika Singh; Sukanya Patra; Rajesh Kumar Singh
Cancer is a multifaceted disease with different hallmarks. The development procedure of anticancer drugs needs different screening methods and disease models to examine the basic mechanism of action of natural products. At present, more than 60% of anticancer drugs are natural products which are either isolates of plants or their derivatives, indicating the opportunity for new drug development from natural product. The mode of action and targets of different compounds are generally different, leading to a challenge for researcher to elucidate the action and mechanism appropriately. For an anticancer drug development, several experimental procedures are required such as extraction, fractionation, purification, identification and finally evaluation. This procedure is completed through different experimental models and assays such as biochemical characterization, antioxidant assay, anticancer assay, ROS assay, apoptosis assay, cell migration assay, pharmacological assays, computer-based evaluation, etc. The screening and development of anticancer drugs are well discussed in this chapter. © 2021 Elsevier Inc. All rights reserved.
Construction Of Almost Unbiased Estimator For Population Mean Using Neutrosophic Information
(University of New Mexico, 2025) Rajesh Kumar Singh; Anamika Kumari; Florentin Smarandache; Shobh Nath Tiwari
In classical statistics, the population mean is estimated using determinate, crisp data value when auxiliary information is known. These estimates can often be biased. The main objective of this study is to introduce the neutrosophic estimator with the minimum mean squared error (MSE) for the unknown value of the population mean as well as overcome the limitations of classical statistics when dealing with ambiguous or indeterminate data. Neutrosophic statistics was introduced by Florentin Smarandache. It is a generalisation of classical statistics that addresses ambiguous, unclear, vague, and indeterminate data. In this study, we have proposed neutrosophic almost unbiased estimator that use known neutrosophic auxiliary parameters to estimate the neutrosophic population mean of the primary variable. Equations for bias and mean squared error are calculated for the suggested estimators up to the first order of approximation. The proposed estimator performs better than the other existing estimators with respect to the MSE and percent relative efficiency (PRE) criteria. The estimator with the highest PRE or lowest MSE is advised for practical utility in various kinds of application areas. The theoretical conclusions are validated by the empirical analysis, which made use of the real data sets. © 2025, University of New Mexico. All rights reserved.
Construction Of Almost Unbiased Estimator for Population Median Using Neutrosophic Information
(University of New Mexico, 2025) Rajesh Kumar Singh; Anamika Kumari; Florentin Smarandache; Sunil Kumar Yadav
This paper introduces the development of an almost unbiased estimator for estimating the unknown population median of the primary variable. The proposed estimator leverages neutrosophic auxiliary information and employs simple random sampling without replacement (SRSWOR). In order to establish the efficacy of the proposed method, we derive the mathematical formulations for the mean square error (MSE), bias, and the minimum MSE of the estimator, providing approximations up to the first order. These derivations allow for a comprehensive analysis of the estimator's performance and its suitability for accurate population median estimation. To validate the theoretical results, we conduct an empirical study using two real-world datasets, ensuring that the proposed estimator's behavior aligns with theoretical predictions in practical scenarios. The study shows that the proposed estimator remains nearly unbiased, with minimal bias when approximated to the first order. This result further demonstrates that the estimator performs robustly across various data conditions. In comparison to existing estimators, the proposed estimator outperforms the others in terms of efficiency, as evidenced by the MSE and PRE values derived. The proposed method not only minimizes bias but also provides more accurate population median estimates with reduced estimation error, making it a more reliable tool in the context of uncertain or incomplete data, where traditional estimators might fall short. By bridging the gap between classical estimation techniques and modern methods that account for uncertainty, the proposed estimator offers a significant advancement in the field of statistical estimation, particularly in real-world applications involving uncertain datasets. The findings presented in this study contribute to the growing body of knowledge in statistical estimation, particularly in the use of neutrosophic information for enhancing estimator accuracy. Furthermore, the results provide a valuable foundation for future research aimed at developing more efficient and reliable statistical estimators for a variety of practical applications. © 2025, University of New Mexico. All rights reserved.
Correction to: Discovery of novel HBV core protein inhibitors by high throughput virtual screening (Scientific Reports, (2025), 15, 1, (13054), 10.1038/s41598-025-97242-6)
(Nature Research, 2025) Jahanvi Sanchitra; Abhijit Debnath; Anil Kumar Singh; A. K. Jha; Rajesh Kumar Singh
Correction to: Scientific Reportshttps://doi.org/10.1038/s41598-025-97242-6, published online 16 April 2025 The original version of this Article contained errors. In the Introduction section, “Upon entering the body, HBV targets hepatocytes10, the major cells of the liver11. The virus’s envelope protein E2 binds to human CD81, a receptor on hepatocytes, facilitating entry12.” now reads: “Upon entering the human body, HBV targets hepatocytes10, the major cells of the liver11. The virus’s envelope protein PreS1 domain of large surface antigen (L-HBsAg) binds to human NTCP (Sodium Taurocholate Co-transporting Polypeptide), a receptor on hepatocytes, facilitating entry through Receptor-mediated endocytosis12”. In addition, Reference 12 was incorrect. “12. Pileri, P. et al. Binding of hepatitis C virus to CD81. Science282, 938–941 (1998)” now reads: “12. Asami J. et al. Structural basis of hepatitis B virus receptor binding. Nat. Struct. Mol. Biol. 31(3):447–454 (2024).” The original Article has been corrected. © The Author(s) 2025.
Crop growth under heavy metals stress and its mitigation
(Springer Singapore, 2020) Reshu Bhardwaj; Shiv Poojan Yadav; Rajesh Kumar Singh; V.K. Tripathi
Heavy metals are biologically magnified due to continuous accumulation in the natural resources which not only threatens the plants and animals survival but also puts mankind at higher risk lacking excellent defense mechanism. Even at a lower concentration these metals may interact with several biomolecules thereby hampering the physicochemical processes in plants resulting in enzyme deactivation, protein denaturation, or disruption of various metabolic activities. Plants have been continuously known to adapt themselves under any of the prevailing environmental stress condition since their origin on this terrestrial planet through various physical and cellular defense mechanisms. Plants in association with the arbuscular mycorrhizae also limit the translocation of these heavy metals in the shoot system, thus immobilizing these metals in soil. Maximum arable acreage is being degraded by the heavy metals accumulation in the soils thereby reducing the cropping intensity, therefore the faulty practices leading to the biomagnification of these heavy metals should be avoided both at primary and secondary stages of its accumulation. This chapter summarizes the growth and development of plants under heavy metals stress condition, the defense mechanisms, and the mitigation options involved. © Springer Nature Singapore Pte Ltd. 2020. All rights reserved.
Cropping geometry and nutrient management study on winter maize {Zea mays) + potato (Solatium tuberosum) intercropping
(Indian Council of Agricultural Research, 2021) V.K. Verma; R.N. Meena; D.N. Singh; P.K. Upadhyay; Rajesh Kumar Singh; Rajiv Kumar Singh
Field experiment was conducted during rabi during 2015-16 and 2016-17 at Varanasi (UP) to study the effect of cropping geometry and nutrient management on winter maize (Zea mays L.) + potato (Solatium tuberosum L.) •intercropping.Among the crop geometry, winter maize intercropped with potato (1:1) in replacement series showed significantly higher growth parameters of maize, viz.dry matter accumulation, crop growth rate and number of green leaves per plant as compared to additive series but it was found at par when winter maize grown with potato (1:2) in replacement series.However, growth parameters of potato differed interchangeably as compared to maize in winter maize + potato intercropping system during both the years.Significantly higher grain yield of winter maize and potato were found in intercropping with 1:1 and 1:2 in additive series, respectively.Assessment of intercropping indices and economics of maize and potato proved to be better in additive series as compared to replacement series during both the years of experimentation.Amongst nutrient management, growth parameters, yield attributes and yield, intercropping indices and economics of winter maize + potato were recorded significantly higher with the application of 100% RDF + 25% N through poultry manure followed by the application of 100% RDF + 25% N through vermicompost as compared to rest of the treatments during both Uie years.Thus, it may be concluded that the maize + potato intercropping in additive series with integration of poultry manure as N source gives better yield and economics of both the crops. © 2021 Indian Council of Agricultural Research. All rights reserved.
Cytotoxic and apoptotic inducing activity of Amoora rohituka leaf extracts in human breast cancer cells
(Elsevier B.V., 2020) Rajesh Kumar Singh; Amit Ranjan; Akhileshwar Kumar Srivastava; Monika Singh; Anil Kumar Shukla; Neelam Atri; Anurag Mishra; Anil Kumar Singh; Santosh Kumar Singh
Background: Amoora rohituka is described in Ayurveda, an Indian traditional system of medicine for management of disorders of blood, diseases of eye, helminthiasis disease, ulcer, liver disorders and splenomegaly. However, the leaves were not reported to have anticancer properties till date. Objective: This study was carried out to evaluate the cytotoxic potential of leaf extracts of Amoora rohituka. Materials and methods: The leaves powder was macerated in petroleum ether, ethyl acetate and methanol and evaluated their anticancer activities in vitro. The phytochemical constituents of the active (ethyl acetate) extract were screened by FTIR analysis and phytochemical screening methods. Results: The ethyl acetate extract (RLEA) showed the presence of alkaloids, flavonoids, steroids, tannins, saponins and terpenoids. The RLEA exhibited high cytotoxic effect against human breast cancer cells, MCF-7 (IC50 = 9.81 μg/mL) and induced apoptosis by altering nuclear morphology and DNA laddering. Wound healing assays explained the potency of extract to decrease the cell migration. Conclusion: The extract of Amoora rohituka leaves exhibited anticancer activity with less toxicity and it could be used for development of alternative drugs in the treatment of human breast cancer. © 2019 Transdisciplinary University, Bangalore and World Ayurveda Foundation