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BACKGROUND: To analyze the impact of online classes on eye health of children and young adults during the COVID-19 pandemic. MATERIALS AND METHODS: An observational study with a written questionnaire and comprehensive ophthalmic evaluation at a tertiary eye care center in South India, during the COVID-19 pandemic. RESULTS: Of the 496 patients, most were 5–10 years old, attending online classes 1–2 h/day with majority (84.7%) having

Okra [Abelmoschus esculentus (L.) Moench] also known as bhindi or lady’s finger is an important vegetable crop in India, West Africa, South Africa, Brazil, USA and Turkey. It belongs to the family Malvaceae. Okra is mainly grown in tropics and subtropics of the world. The studies regarding the molecular marker development are very limited; still there is no SSR development from comprehensive transcriptome data in this crop. This study presents the first comprehensive transcriptome data, using RNA from different parts of okra such as root, stem, leaf, bud, flower, different stages of developing pod and from twenty days old plantlets of heat, drought and salt stressed. A total of 10,492 SSRs were identified in this study. Among these tri repeats (2112) were found to be predominant followed by di (1285), tetra (149), penta (24) and hexa. Thirty four SSRs were standardized for PCR and screened for 36 okra genotypes and accessions. Among these 18 SSR primers were found to be highly polymorphic with the PIC values more than 0.5. And the overall results of analysis showed that expected heterozygosity ranged from 0.000 to 0.971 with a mean of 0.593; the values for observed heterozygosity ranged from 0.000 to 0.794 with the mean of 0.254; the number of allele per locus ranged from 1 to 30 and the Polymorphic Information Content (PIC) ranged from 0.000 to 0.940 with the mean value of 0.5546. The genic SSR markers developed will help in germplasm characterization mapping, genetic diversity studies, molecular assisted breeding and also in gene discovery.

VANET provides communication between vehicles. VANET nodes are highly dynamic. Therefore, it is essential to increase the stability of the communication between nodes. The cluster head and cluster node provide stable communication between vehicles. Vehicle communications are being challenged by factors such as security, confidential communication, and severe delay. This work proposes an Artificial Intelligence (AI)-based Sugeno fuzzy inference system to overcome these issues. The proposed secure trust-based cluster techniques are less complex, with lesser communication delays, lower overhead, and more efficient in accurately locating trusted nodes for communication. Vehicular Ad hoc Networks (VANET) should send data between vehicles and use traffic safety indicators using an Enhanced Cluster-based routing protocol. AI-TASFIS is Artificial Intelligence-based Trust Authentication Sugeno fuzzy inference system that uses ANFIS-based Sugeno Fuzzy inference systems to calculate the node weights for choosing trusted cluster head and cluster member that reduces malicious attacks like Black Hole Attacks, Wormhole attacks, and Timing Attacks while transferring data packets. Simulation results show that the proposed Artificial Intelligence (AI)-based Sugeno fuzzy inference system provides network security, reduces end-to-end delay, and increases packet delivery ratio and throughput.

Objectives: The present study aimed to evaluate CD4 cell counts, lipid profile, and oral manifestations in human immunodeficiency virus (HIV)-infected and acquired immune deficiency syndrome (AIDS) patients and their correlation with seronegative controls. Materials and Methods: In this cross-sectional, hospital-based study, there were three groups of subjects: group A consisting of 500 healthy patients (controls), group B composed of 500 HIV-infected patients, and group C comprised of 500 AIDS patients based on their CD4 cell counts. CD4 cell counts were assessed using the CyFlow counter. Lipid profile was evaluated with the Erba EM 360 analyzer. Results: The results were statistically significant for CD4 cell counts (P

MicroRNAs (miRNAs) are small, highly conserved non-coding RNA molecules involved in the regulation of gene expression in eukaryotes. Gene expression involves post-transcriptional gene regulation by miRNAs. miRNAs are formed from precursor RNA molecules that fold into a stem loop secondary structure. The mature miRNA is one end of the precursor miRNA, defined by the cut from ‘Drosha’ on either the 5’ or 3’ arm. In this study, we have used a bioinformatics approach to identify miRNAs in 3,361 contigs obtained from partial genome sequence data of Abelmoschus esculentus (okra) sequenced by NGS technology. Using C-mii and psRNA Target tools, we identified two miRNAs and their target RNAs for which a regulatory miRNA binding has been verified. Their targets consisted of transcription factors involved in growth and development, gene regulation and metabolism. Phylogenetic analysis of the newly identified miRNA family has been done to compare their level of conservation with respect to the other members of the plant kingdom.

Pomegranate genotypes have been characterized mainly on the basis of morphological traits; but, these traits are affected to a large extent by environmental and cultivation conditions, resulting in their ambiguous discrimination. Molecular markers are more suited for accurate discrimination of genotypes and cultivars. Sequence-Related Amplified Polymorphism (SRAP) markers were used in the present study to analyze polymorphism among the important pomegranate genotypes grown in India. The total number of bands generated by 30 SRAP primers for 12 genotypes was 1448, with an average of 48.3 bands per primer. Polymorphism varied from 2.7 to 73.9, with an average of 40.95%. Similarity-value based on Jaccard's Coefficient ranged from 0.63 (between cvs. Naina and Amlidana) to 0.95 (between cvs. Kabul Yellow and Jalore Seedless). UPGMA (un-weighted pair group method with arithmetic mean) analysis was performed and a dendrogram was constructed using Jaccard's similarity matrix. The 12 genotypes used grouped into 5 clusters. SRAP markers were found suitable for determining variability among the pomegranate genotypes studied.

Chlorophytum comosum is a plant with medicinal potential traditionally used to treat different diseases. The present study aimed to determine the bioactive compounds, hypoglycemic and antioxidant potential of C. comosum root and leaf. The ethyl acetate extracts of C. comosum root and leaf were analyzed by GC-MS to determine the bioactive compounds. The hypoglycemic potential of the extracts was evaluated by α-amylase, α-glucosidase, glucose diffusion inhibitory assays, and glucose adsorption assay. The ethyl acetate extract of C. comosum root inhibited α-amylase, α-glucosidase, and glucose diffusion in a concentration-dependent manner with IC50 values of 205.39 ± 0.15, 179.34 ± 0.3 and 535.248 μg/mL, respectively, and the leaf extract inhibited α-amylase and α-glucosidase enzymes with IC50 values of 547.99 ± 0.09, and 198.18 ± 0.25 μg/mL respectively. C. comosum root and leaf extracts also improved glucose adsorption. Heptadecanoic acid and dodecanoic acid were identified as potential compounds with hypoglycemic properties through molecular docking. The extracts were also assessed for their antioxidant activity using DPPH, ABTS, and FRAP assays. C. comosum root and leaf extracts were also able to scavenge DPPH radicals with IC50 values of 108.37 ± 0.06 and 181.79 ± 0.09 µM and ABTS radicals with IC50 values of 126.24 ± 0.13 and 264.409 ± 0.08 µM, respectively. The root and leaf extracts also reduced the ferricyanide complex to ferrocyanide with higher reducing powers of 2.24 ± 0.02 and 1.65 ± 0.03, respectively. The results showed that the ethyl acetate extract of C. comosum root has significant antioxidant and hypoglycemic potential compared to the leaf extract. Thus, it can also be studied to isolate the potential compounds with antihyperglycemic activities.

Tomato, the important vegetable crop, is severely affected by Orthotospovirus arachinecrosis which impacts heavy economic losses. The application of insecticide to manage viral diseases is not an environmentally safe approach. In view of these issues, we investigated the antiviral efficacy of 21 bacterial endophytes against GBNV in local lesion host (Cowpea-VBN3). Based on the reduction in lesion number and virus titer as estimated through both DAC ELISA and qPCR in cowpea, the bacterial endophytes viz., Bacillus licheniformis Soya1, Bacillus tequilensis NBL6, and Bacillus velezensis VB7 were selected and further tested in tomato. The study revealed the well-defined antiviral efficacy of these endophytes against GBNV. The percentage of disease incidence ranged from 16 to 24% in endophyte-treated tomato plants compared with untreated plants (88%). In addition, symptom severity was reduced, and the application of endophytes also in promotion of the growth compared with untreated control. DAC ELISA revealed that the tomato plants treated with bacterial endophytes challenged with GBNV showed reduction in the virus titer (0.26–0.39 @ OD 405 nm) at different days of interval after inoculation (0, 5, and 10 days) compared with untreated control (3.475 @ OD 405 nm). Additionally, reduction in the viral copy number in bacterial endophyte-treated plants was evident by real-time PCR. Furthermore, tomato plants bacterized with endophytes depicted significant correlation and reduction in viral load and disease incidence as revealed by the principal-component biplot analysis. Thus, the application of bacterial endophytes has a potential role in reducing the disease incidence, severity, and titer value of GBNV, which will be the promising management approach in future to mitigate the virus infection in tomato plants.

A public key infrastructure-enabled system authentication model is developed to provide essential security functions for Vehicular ad hoc networks (VANETs). An intelligent transportation system is provided by VANET, an emerging technology. Dedicated short-range communication is used to disseminate messages wirelessly. Communications may be hacked, and messages can be stolen or fabricated. Hence, authenticated communication is crucial in the VANET environment. Some parameters such as trust, authentication, privacy, and security are at high risk. This article suggests a VANET with secure authentication and trust-based clustering mechanisms to provide stable and secure communication. Initially, the Restricted Boltzmann Machine learning algorithm (RBMA) is used to select the cluster head, which depends upon trust, vehicle lifetime, and buffer level. Then, cluster members are formed, followed by grouping. Diffie–Hellman Hyperelliptic Curve Cryptography and cryptographic hash functions are used by signcryption for secure communication in VANET. Therefore, the essential component of the key agreement strategy that will give superior authentication is this signcryption mechanism. Over the medium access protocol layer, all of these security characteristics are updated. The proposed method of clustering signcryption key agreement scheme (CSKAS) approach reduces time complexity and increases packet delivery ratio which is vital in providing stable, secure communication.

The tobacco caterpillar, Spodoptera litura, a major pest of soybean in India is under surveillance in all soybean growing areas in Maharashtra in order to issue alerts to farmers and prevent economic losses. In this context, two linear models were fitted to developmental data of S. litura life stages reared on soybean at five constant temperatures viz. 15, 20, 25, 30 and 35°C through laboratory experiments. Optimum temperature for development (Topt) and upper temperature threshold (Tmax) were estimated from three nonlinear models by additionally including developmental response at >35°C. Topt estimates for the total immature development were 34.5°C (Lactin-2), 33.7°C (Briere-1) and 33.2°C (Simplified Beta type function) while Tmax estimates were in the range of 38 to 40°C. Application of a thermodynamic non-linear model (Optim SSI) gave estimate ofintrinsic optimum temperature (Tφ) for development of egg (28.3°C), larva (27.5°C) and pupal stage (30.3°C). The phenology model of S. litura on soybean based on estimated developmental threshold temperatures and thermal constants was validated using available field surveillance data to facilitate informed pest management decisions.