Bioactive Molecules Derived from Plants in Managing Dengue Vector Aedes aegypti (Linn.).

Mosquitoes are the potential vectors of several viral diseases such as filariasis, malaria, dengue, yellow fever, Zika fever and encephalitis in humans as well as other species. Dengue, the most common mosquito-borne disease in humans caused by the dengue virus is transmitted by the vector Ae. aegypti. Fever, chills, nausea and neurological disorders are the frequent symptoms of Zika and dengue. Thanks to various anthropogenic activities such as deforestation, industrialized farming and poor drainage facilities there has been a significant rise in mosquitoes and vector-borne diseases. Control measures such as the destruction of mosquito breeding places, a reduction in global warming, as well as the use of natural and chemical repellents, mainly DEET, picaridin, temephos and IR-3535 have proven to be effective in many instances. Although potent, these chemicals cause swelling, rashes, and eye irritation in adults and children, and are also toxic to the skin and nervous system. Due to their shorter protection period and harmful nature towards non-target organisms, the use of chemical repellents is greatly reduced, and more research and development is taking place in the field of plant-derived repellents, which are found to be selective, biodegradable and harmless to non-target species. Many tribal and rural communities across the world have been using plant-based extracts since ancient times for various traditional and medical purposes, and to ward off mosquitoes and various other insects. In this regard, new species of plants are being identified through ethnobotanical surveys and tested for their repellency against Ae. aegypti. This review aims to provide insight into many such plant extracts, essential oils and their metabolites, which have been tested for their mosquitocidal activity against different life cycle forms of Ae. Aegypti, as well as for their efficacy in controlling mosquitoes.

Identification of QTLs for zinc deficiency tolerance in a recombinant inbred population of rice (Oryza sativa L.).

BACKGROUND: Deficiency of Zn is a major soil constraint in rice plant growth and yield. Edaphic factors such as Zn deficiency in soil in relation to plant performance are still poorly understood. Here, we report promising quantitative trait loci (QTL) conferring tolerance to Zn deficiency, which were identified through biparental mapping. The experiment was conducted using the 236 F7 recombinant inbred line mapping population derived from the cross of Kinandang Patong (Zn deficiency sensitive) and A69-1 (Zn deficiency tolerant). RESULTS: A total of six QTLs (qLB-2B, qLB-4B, qPM-4B, qPM-6B, qRZC-4B, qSZC-4B) on chromosomes 2, 4 and 6 were identified for environment 1, whereas five QTLs (qLB-2 N, qLB-4 N, qPM-4 N, qRZC-4 N, qSZC-4 N) on chromosomes 2 and 4 were detected for environment 2. Among these, five major (51.30, 48.70, 28.60, 56.00, 52.00 > 10 R2 ) and one minor (5.40 < 10 R2 ) QTLs for environment 1 and four major (51.48, 50.20, 53.00, 48.00 > 10 R2 ) and one minor (4.44 < 10) QTLs for environment 2 for Zn deficiency tolerance with a logarithm of odd threshold value higher than 3 were identified. The QTLs (qLB-4B, qPM-4B, qRZC-4B, qSZC-4B, qLB-4 N, qPM-4 N, qRZC-4 N, qSZC-4 N) for leaf bronzing, plant mortality root zinc concentration and shoot zinc concentration identified on chromosome 4 were found to be the most promising and highly reproducible across the locations that explained phenotypic variation from 48.00% to 56.00% with the same marker interval RM6748-RM303. CONCLUSION: The new QTLs and its linked markers identified in the present study can be utilized for Zn deficiency tolerance in elite cultivars using marker-assisted backcrossing. © 2022 Society of Chemical Industry.

Transcript profiling and gene expression analysis under drought stress in Ziziphus nummularia (Burm.f.) Wright & Arn.

Drought is one of the prime abiotic stresses responsible for limiting agricultural productivity. A number of drought responsive genes have been isolated and functionally characterized but these studies have been restricted to a few model plant systems. Very few drought responsive genes have been reported till date from non model drought tolerant plants. The present study aimed at identifying differentially expressed genes from a drought tolerant, non-model plant, Ziziphus nummularia (Burm.f.) Wight & Arn. One month old seedlings of Z. nummularia were subjected to drought stress by 30% Polyethylene glycol (PEG 6000) treatment for 6, 12, 24, 48 and 72 h. A significant reduction in RWC and increase in proline was observed at 24 h and 48 h of treatment. Suppression subtractive hybridization (SSH) library was constructed with drought stressed seedlings after 24 h and 48 h of PEG 6000 treatment. A total of 142 and 530 unigenes from 24 h and 48 h library were identified respectively. Gene ontology studies revealed that about 9.78% and 15.07% unigenes from 24 h and 48 h SSH libraries were expressed in "response to stress". Fifteen putative drought responsive genes identified in SSH library were validated for drought responsive differential expression by RT-qPCR. Significant changes in fold expressions were observed with time in the treated samples compared to the control. A heat map revealing the expression profile of genes was constructed by hierarchical clustering. Various genes identified in SSH libraries can serve as a resource for marker discovery and selection of candidate genes to improve drought tolerance in other susceptible crops.

Vaccine hesitancy in the post-vaccination COVID-19 era: a machine learning and statistical analysis driven study.

Background The COVID-19 pandemic has badly affected people of all ages globally. Therefore, its vaccine has been developed and made available for public use in unprecedented times. However, because of various levels of hesitancy, it did not have general acceptance. The main objective of this work is to identify the risk associated with the COVID-19 vaccines by developing a prognosis tool that will help in enhancing its acceptability and therefore, reducing the lethality of SARS-CoV-2. Methods: The obtained raw VAERS dataset has three files indicating medical history, vaccination status, and post vaccination symptoms respectively with more than 354 thousand samples. After pre-processing, this raw dataset has been merged into one with 85 different attributes however, the whole analysis has been subdivided into three scenarios ((i) medical history (ii) reaction of vaccination (iii) combination of both). Further, Machine Learning (ML) models which includes Linear Regression (LR), Random Forest (RF), Naive Bayes (NB), Light Gradient Boosting Algorithm (LGBM), and Multilayer feed-forward perceptron (MLP) have been employed to predict the most probable outcome and their performance has been evaluated based on various performance parameters. Also, the chi-square (statistical), LR, RF, and LGBM have been utilized to estimate the most probable attribute in the dataset that resulted in death, hospitalization, and COVID-19. Results: For the above mentioned scenarios, all the models estimates different attributes (such as cardiac arrest, Cancer, Hyperlipidemia, Kidney Disease, Diabetes, Atrial Fibrillation, Dementia, Thyroid, etc.) for death, hospitalization, and COVID-19 even after vaccination. Further, for prediction, LGBM outperforms all the other developed models in most of the scenarios whereas, LR, RF, NB, and MLP perform satisfactorily in patches. Conclusion: The male population in the age group of 50-70 has been found most susceptible to this virus. Also, people with existing serious illnesses have been found most vulnerable. Therefore, they must be vaccinated in close observations. Generally, no serious adverse effect of the vaccine has been observed therefore, people must vaccinate themselves without any hesitation at the earliest. Also, the model developed using LGBM establishes its supremacy over all the other prediction models. Therefore, it can be very helpful for the policymakers in administrating and prioritizing the population for the different vaccination programs.

Primary Mucoepidermoid Carcinoma of the Lung Coexisting With Pulmonary Tuberculosis: A Rare Case Report.

Mucoepidermoid carcinoma (MEC) is a well-established neoplasm of the salivary glands. However, the MEC of the lung is an exceedingly rare neoplasm that falls under the category of salivary gland-type tumors of the lung. Pulmonary MEC is recognized for its indolent progression. Pulmonary tuberculosis (TB) is a prevalent infectious disease in India and ranks among the leading causes of death from infectious diseases. Nevertheless, the co-occurrence of pulmonary MEC with pulmonary TB is a rare phenomenon that has not been documented in the literature. In this report, we describe a 54-year-old male patient who presented with symptoms of dysphagia, weight loss, and fever. Histopathological examination diagnosed him with pulmonary MEC, and concurrent cytology and Gene-Xpert tests confirmed tuberculosis. This case represents the first documented instance of this particular co-occurrence. It underscores the limitations of radiology in diagnosing such a rare neoplasm, especially when there is an absence of lung parenchyma infiltration and a mass lesion. Additionally, this case supports the possibility of an interdependent relationship between malignancies and tuberculosis.

Towards smart surveillance as an aftereffect of COVID-19 outbreak for recognition of face masked individuals using YOLOv3 algorithm.

The eruption of COVID-19 pandemic has led to the blossoming usage of face masks among individuals in the communal settings. To prevent the transmission of the virus, a mandatory mask-wearing rule in public areas has been enforced. Owing to the use of face masks in communities at different workplaces, an effective surveillance seems essential because several security analyses indicate that face masks may be used as a tool to hide the identity. Therefore, this work proposes a framework for the development of a smart surveillance system as an aftereffect of COVID-19 for recognition of individuals behind the face mask. For this purpose, transfer learning approach has been employed to train the custom dataset by YOLOv3 algorithm in the Darknet neural network framework. Moreover, to demonstrate the competence of YOLOv3 algorithm, a comparative analysis with YOLOv3-tiny has been presented. The simulated results verify the robustness of YOLOv3 algorithm in the recognition of individuals behind the face mask. Also, YOLOv3 algorithm achieves a mAP of 98.73% on custom dataset, outperforming YOLOv3-tiny by approximately 62%. Moreover, YOLOv3 algorithm provides adequate speed and accuracy on small faces.

Diagnosis of COVID-19 using chest X-ray images based on modified DarkCovidNet model.

Coronavirus disease, also known as COVID-19, is an infectious disease caused by SARS-CoV-2. It has a direct impact on the upper and lower respiratory tract and threatened the health of many people around the world. The latest statistics show that the number of people diagnosed with COVID-19 is growing exponentially. Diagnosing positive cases of COVID-19 is important for preventing further spread of the disease. Currently, Coronavirus is a serious threat to scientists, medical experts and researchers around the world from its detection to its treatment. It is currently detected using reverse transcription polymerase chain reaction (RT-PCR) analysis at the most test centers around the world. Yet, knowing the reliability of a deep learning based medical diagnosis is important for doctors to build confidence in the technology and improve treatment. The goal of this study is to develop a model that automatically identifies COVID-19 by using chest X-ray images. To achieve this, we modified the DarkCovidNet model which is based on a convolutional neural network (CNN) and plotted the experimental results for two scenarios: binary classification (COVID-19 versus No-findings) and multi-class classification (COVID-19 versus pneumonia versus No-findings). The model is trained on more than 10 thousand X-ray images and achieved an average accuracy of 99.53% and 94.18% for binary and multi-class classification, respectively. Therefore, the proposed method demonstrates the effectiveness of COVID-19 detection using X-ray images. Our model can be used to test the patient via cloud and also be used in situations where RT-PCR tests and other options aren't available.

Oxazoline/amide derivatives against M. tuberculosis: experimental, biological and computational investigations.

Tuberculosis (TB) is a treatable contagious disease that continuously kills approximately 2 million people yearly. Different oxazoline/amide derivatives were synthesized, and their anti-tuberculosis activity was performed against different strains of Mtb. This study designed the anti-Mtb compounds based on amide and oxazoline, two different structural moieties. The compounds were further synthesized and characterized by spectral techniques. Their anti-Tb activity was evaluated against strain (M. tuberculosis: H37Rv). Selectivity and binding affinity of all synthesized compounds (2a-2e, 3a-3e) against PanK in Mtb were investigated through molecular docking. Molecular dynamics simulation studies for the promising compounds 2d and 3e were performed for 100 ns. The stability of these complexes was assessed by calculating the root mean square deviation, solvent-accessible surface area, and gyration radius relative to their parent structures. Additionally, free energy of binding calculations were performed. Among all synthesized compounds, 2d and 3e had comparable antitubercular activity against standard drug, validated by their computational and biological study.

Collagen-IV supported embryoid bodies formation and differentiation from buffalo (Bubalus bubalis) embryonic stem cells.

Embryoid bodies (EBs) are used as in vitro model to study early extraembryonic tissue formation and differentiation. In this study, a novel method using three dimensional extracellular matrices for in vitro generation of EBs from buffalo embryonic stem (ES) cells and its differentiation potential by teratoma formation was successfully established. In vitro derived inner cell masses (ICMs) of hatched buffalo blastocyst were cultured on buffalo fetal fibroblast feeder layer for primary cell colony formation. For generation of EBs, pluripotent ES cells were seeded onto four different types of extracellular matrices viz; collagen-IV, laminin, fibronectin and matrigel using undifferentiating ES cell culture medium. After 5 days of culture, ESCs gradually grew into aggregates and formed simple EBs having circular structures. Twenty-six days later, they formed cystic EBs over collagen matrix with higher EBs formation and greater proliferation rate as compared to other extracellular matrices. Studies involving histological observations, fluorescence microscopy and RT-PCR analysis of the in vivo developed teratoma revealed that presence of all the three germ layer derivatives viz. ectoderm (NCAM), mesoderm (Flk-1) and endoderm (AFP). In conclusion, the method described here demonstrates a simple and cost-effective way of generating EBs from buffalo ES cells. Collagen-IV matrix was found cytocompatible as it supported buffalo EBs formation, their subsequent differentiation could prove to be useful as promising candidate for ES cells based therapeutic applications.

Evaluation of transgenic chickpea harboring codon-modified Vip3Aa against gram pod borer (Helicoverpa armigera H.).

The gram pod borer is a major pest of chickpea, accounting for average annual yield losses to the tune of 40-50%. VIP3Aa, a class of insecticidal protein with different receptor binding site in the insect's midgut compared to Bt-crystal protein, offers an alternative protection strategy against Lepidopteran insects. Here, we report evaluation of genetically engineered chickpea lines harboring codon modified Vip3Aa (cmVip3Aa) against the Lepidopteran insect pest, gram pod borer. The synthetic codon modified, cmVip3Aa gene of 2,370 bp was sub-cloned in modified plant expression vector and used for direct transformation of embryonic axis explants of chickpea (cv. DCP 92-3), with transformation efficiency of 4.30%. Presence and transmission of transgene across two generations were confirmed by PCR and Southern blot analyses in the five selected transgenic chickpea lines. Real Time PCR analyses indicated variable levels of cmVip3Aa expression in the transgenic chickpea lines (average Cq values 15.01±0.86 to 19.32±0.10), which were absent in the non-transgenic counterpart. Detached leaf insect bioassay indicate larval mortality (up to 39.75%), reduced larval feeding (up to 82.91%) and reduced larval weight gain (up to 68.23%), compared to control lines. Evaluation of gene offers a platform to identify efficacious insecticidal gene that can be used for insect resistance management in chickpea.

Energy optimization of Multiple Stage Evaporator system using Water Cycle Algorithm.

Black liquor, a residual stream from the Kraft recovery process of paper mills is an incipient biomass energy resource which finds prospective biofuel-based industrial applications to ensure process self-sufficiency and sustainability. Black liquor is concentrated using Multiple Stage Evaporator, the utmost energy intensive unit, before using it as biofuel. Pertaining to the contemporary global energy scenario, improvement in energy efficiency of Multiple Stage Evaporator becomes indispensable. The present work investigates the non-linear modeling and simulation-based optimization of Heptads' stage based Multiple Stage Evaporator in backward feed flow configuration integrated with various energy saving strategies. A novel metaheuristic approach, Water Cycle Algorithm has been employed to search the optimum estimates of unknown process variables and therefore, the optimum energy efficiency parameters. The optimization results demonstrate the efficiency of Water Cycle Algorithm in screening the most appropriate operating strategy, i.e., hybrid model of all energy saving strategies (steam-split, feed-split and feed-preheating) with optimum energy efficiency i.e. Steam Economy of 7.092 and Steam Consumption of 1.919 kg/s. Moreover, a comparative analysis of the results with previous literature and real-time plant estimates reveal that the hybrid model offers improvement of 52.84% in Steam Economy and reduction in Steam Consumption by 28.13% when compared to the real plant data.

Three newly identified Immediate Early Genes of Bovine herpesvirus 1 lack the characteristic Octamer binding motif- 1.

Only three immediate early genes (IE) BICP0, BICP4 and BICP22 of Bovine herpesvirus 1 (BoHV-1) are known. These genes are expressed coordinately and their promoters are well characterized. We provide evidence for expression of three additional IE genes of BoHV-1 i.e. UL21, UL33 and UL34. These genes are expressed in the presence of cycloheximide (CH) at the same time as known IE genes. Surprisingly, the promoters of newly identified IE genes (UL21, UL33, UL34) lack the OCT-1 binding site, a considered site of transactivation of the BoHV-1 IE genes. The other difference in the promoters of the newly identified IE genes is the presence of TATA box at near optimal site. However, all the IE genes have similar spatial placements of C/EBPα, DPE and INR elements.

Expression and quantification of Oct-4 gene in blastocyst and embryonic stem cells derived from in vitro produced buffalo embryos.

The POU-domain transcription factor Pou5f1 (Oct-4) is involved in transcriptional regulation during early embryonic development and cell differentiation. Despite highly conserved genomic organization of Oct-4 gene in mammals, expression pattern of Oct-4 is highly variable in different species. In the present study, expression pattern of Oct-4 in buffalo blastocyst, trophoectoderm (TE), and embryonic stem cells (ESCs) was investigated. For the derivation and characterization of buffalo ESCs, inner cell masses (ICMs) were isolated from 18 hatched and 21 expanded in vitro produced buffalo blastocyst and cultured over mitomycin-C-treated buffalo fetal fibroblast feeder layer. Alkaline phosphatase (AP) activity, SSEA-1 and 4, TRA 1-60 and 1-81, and Oct-4 proteins were localized in ICM, TE, and ESCs. Quantification of Oct-4 was done by amplifying a transcript of 125 base pairs by real-time polymerase chain reaction. Primary cell colony formation was higher (P < 0.05) in hatched blastocyst (83.33%, 15/18) compared to mechanically isolated ICMs from expanded blastocyst (52.38%, 11/21). Undifferentiated buffalo ESCs were positive for AP and expressed Oct-4, SSEA-1 and 4, TRA-1-60, and TRA-1-81 proteins. Oct-4 transcripts and proteins were detected in the ICM, TE cells and were invariably present in ESCs; however, expression level of Oct-4 transcript were significantly higher in ICM and ESCs as compared to TE cells. In conclusion, expression of Oct-4 is not only restricted to the ICM and ESCs but its expression was also detected in TE cells suggesting that instead of using Oct-4 as a single marker, it is better to have other flanking molecular markers for the identification of buffalo pluripotent embryonic stem cells.

In vivo differentiation potential of buffalo (Bubalus bubalis) embryonic stem cell.

Embryonic stem cells (ESCs) derived from inner cell mass (ICM) of mammalian blastocyst are having indefinite proliferation and differentiation capability for any type of cell lineages. In the present study, ICMs of in vitro-derived buffalo blastocysts were cultured into two different culture systems using buffalo fetal fibroblast as somatic cell support and Matrigel as synthetic support to obtain pluripotent buffalo embryonic stem cell (buESC) colonies. Pluripotency of the ESCs were characterised through pluripotency markers whereas, their differentiation capability was assessed by teratoma assay using immuno-compromised mice. Cumulus ooccyte complexes from slaughter house-derived ovaries were subjected to in vitro maturation, in vitro fertilization and in vitro culture to generate blastocysts. Total 262 blastocysts were derived through IVEP with 11.83 % (31/262) hatching rate. To generate buESCs, 15 ICMs from hatched blastocysts were cultured on mitomycin-C-treated homologous fetal fibroblast feeder layer, whereas the leftover 16 ICMs were cultured on extra-cellular matrix (Matrigel). No significant differences were observed for primary ESCs colony formation between two culture systems. Primary colonies as well as passaged ESCs were characterised by alkaline phosphatase staining, karyotyping and expression of transcription-based stem cell markers, OCT-4 and cell surface antigens SSEA-4 and TRA-1-60. Batch of ESCs found positive for pluripotency markers and showing normal karyotype after fifteenth passage were inoculated into eight immuno-compromised mice through subcutaneous and intramuscular route. Subcutaneous route of inoculation was found to be better than intramuscular route. Developed teratomas were excised surgically and subjected to histological analysis. Histological findings revealed presence of all the three germinal layer derivatives in teratoma sections. Presence of germinal layer derivatives were further confirmed by reverse transcriptase-polymerase chain reaction for the presence of differentiation markers like nerve cell adhesion molecule, fetal liver kinase-1 and alpha-feto protein for ectoderm, mesoderm and endoderm, respectively.