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The main purpose of the present study is to analyse the working condition of women agricultural workers in Virudhunagar District. Women workers play an inevitable role in agriculture field. In India more than 60 percent of the workers in agriculture sector are women. The problems of agricultural labourers have been sought to be tackled through multi-dimensional course of action viz., improvement of infrastructural facilities, diversification to nonfarm activities, skill improvement programmes, financial assistance to promote self-employment, optimising the use of land resources and so on through a variety of rural development, employment generation and poverty alleviation programmes. Therefore, the researcher has taken this topic for research. [ABSTRACT FROM AUTHOR]

Objective(s): Electromagnetic radiations which have lethal effects on the living cells are currently also considered as a disinfective physical agent. Materials and Methods: In this investigation, silver nanoparticles were applied to enhance the lethal action of low powers (100 and 180 W) of 2450 MHZ electromagnetic radiation especially against Escherichia coli ATCC 8739. Silver nanoparticles were biologically prepared and used for next experiments. Sterile normal saline solution was prepared and supplemented by silver nanoparticles to reach the sub-inhibitory concentration (6.25 μg/mL). Such diluted silver colloid as well as free-silver nanoparticles solution was inoculated along with test microorganisms, particularly E. coli. These suspensions were separately treated by 2450 MHz electromagnetic radiation for different time intervals in a microwave oven operated at low powers (100 W and 180 W). The viable counts of bacteria before and after each radiation time were determined by colony-forming unit (CFU) method. Results: Results showed that the addition of silver nanoparticles significantly decreased the required radiation time to kill vegetative forms of microorganisms. However, these nanoparticles had no combined effect with low power electromagnetic radiation when used against Bacillus subtilis spores. Conclusion: The cumulative effect of silver nanoparticles and low powers electromagnetic radiation may be useful in medical centers to reduce contamination in polluted derange and liquid wastes materials and some devices.

Objective(s): Electromagnetic radiations which have lethal effects on the living cells are currently also considered as a disinfective physical agent. Materials and Methods: In this investigation, silver nanoparticles were applied to enhance the lethal action of low powers (100 and 180 W) of 2450 MHZ electromagnetic radiation especially against Escherichia coli ATCC 8739. Silver nanoparticles were biologically prepared and used for next experiments. Sterile normal saline solution was prepared and supplemented by silver nanoparticles to reach the sub-inhibitory concentration (6.25 μg/mL). Such diluted silver colloid as well as free-silver nanoparticles solution was inoculated along with test microorganisms, particularly E. coli. These suspensions were separately treated by 2450 MHz electromagnetic radiation for different time intervals in a microwave oven operated at low powers (100 W and 180 W). The viable counts of bacteria before and after each radiation time were determined by colony-forming unit (CFU) method. Results: Results showed that the addition of silver nanoparticles significantly decreased the required radiation time to kill vegetative forms of microorganisms. However, these nanoparticles had no combined effect with low power electromagnetic radiation when used against Bacillus subtilis spores. Conclusion: The cumulative effect of silver nanoparticles and low powers electromagnetic radiation may be useful in medical centers to reduce contamination in polluted derange and liquid wastes materials and some devices.

The present study was an attempt to investigate the hepatoprotective and antioxidant properties of aqueous fruit extract of Embilica officinalis (E.O) and silver nanoparticles synthesized using Embilica officinalis (E.O) fruit extract in wistar male albino rats. The rats were divided into eight groups with six animals each. Group I control rats received normal feed. Group II rats were treated with hepatotoxic agent CCl4 (2 ml/kg/day). Group III was given E.O (300 mg/kg) aqueous fruit extract. Group IV was treated with E.O (300 mg/kg) aqueous fruit extract and CCl4 (2 ml/kg/day). Group V rats received E.O silver nanoparticles and CCl4 (2 ml/kg/day). Group VI was treated with Silymarin (100 mg/kg). Group VII received Silymarin (100 mg/kg) along with CCl4 (2ml/kg/day).Group VIII rats were treated with Silymarin silver nanoparticles and CCl4 (2 ml/kg/day). The substantially elevated enzymatic levels of Aspartate aminotransferase (AST), Alanine aminotransferase (ALT), Alkaline Phosphatase (ALP), Lactate dehydrogenase (LDH) and Bilirubin by CCl4 were restored toward normal when treated with aqueous fruit extract of Embilica officinalis. The total protein level has also been increased toward the normal value. Silymarin was used as standard reference and it has significant hepatoprotective effect against the CCl4 induced hepatotoxicity in rats. The E.O and Silymarin silver nanoparticles also significantly restored the enzymes level to normal. The biochemical observation along with histopathological examination shows that they have the antioxidant and hepatoprotective activity. The fruit extract of E.O, Silymarin and its silver nanoparticles could be effective antioxidants and has hepatoprotective activity. [ABSTRACT FROM AUTHOR]

The SARS-CoV-2 pandemic enables the analysis of immune responses induced against a novel coronavirus infecting immunologically naïve individuals. This provides an opportunity for analysis of immune responses and associations with age, sex and disease severity. Here we measured an array of solid-phase binding antibody and viral neutralising Ab (nAb) responses in participants (n=337) of the ISARIC4C cohort and characterised their correlation with peak disease severity during acute infection and early convalescence. Overall, the responses in a Double Antigen Binding Assay (DABA) for antibody to the receptor binding domain (anti-RBD) correlated well with IgM as well as IgG responses against viral spike, S1 and nucleocapsid protein (NP) antigens. DABA reactivity also correlated with nAb. As we and others reported previously, there is greater risk of severe disease and death in older men, whilst the sex ratio was found to be equal within each severity grouping in younger people. In older males with severe disease (mean age 68 years), peak antibody levels were found to be delayed by one to two weeks compared with women, and nAb responses were delayed further. Additionally, we demonstrated that solid-phase binding antibody responses reached higher levels in males as measured via DABA and IgM binding against Spike, NP and S1 antigens. In contrast, this was not observed for nAb responses. When measuring SARS-CoV-2 RNA transcripts (as a surrogate for viral shedding) in nasal swabs at recruitment, we saw no significant differences by sex or disease severity status. However, we have shown higher antibody levels associated with low nasal viral RNA indicating a role of antibody responses in controlling viral replication and shedding in the upper airway. In this study, we have shown discernible differences in the humoral immune responses between males and females and these differences associate with age as well as with resultant disease severity., Competing Interests: PO is the Imperial College Lead Investigator of the EMINENT consortium, supported by the Medical Research Council UK MR/R502121/1. This grant supports collaborative testing of compounds developed by GlaxoSmithKline in UK universities. PO is also on advisory boards for Affnivax, Oxford Immunotech, Nestle and Pfizer in relation to immunity to viruses fees paid to Imperial College London. PO is also on an advisory board for Janssen/J&J. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Parker, Thomas, Roper, Ijaz, Edwards, Marchesin, Katsanovskaja, Lett, Jones, Hardwick, Davis, Vink, McDonald, Moore, Dicks, Jegatheesan, Cook, Hope, Cherepanov, McClure, Baillie, Openshaw, Turtle, Ho, Semple, Paxton, Tedder, Pollakis and ISARIC4C Investigators.)

Seroepidemiological studies to monitor antibody kinetics are important for assessing the extent and spread of SARS-CoV-2 in a population. Noninvasive sampling methods are advantageous for reducing the need for venipuncture, which may be a barrier to investigations, particularly in pediatric populations. Oral fluids are obtained by gingiva-crevicular sampling from children and adults and are very well accepted. Enzyme immunoassays (EIAs) based on these samples have acceptable sensitivity and specificity compared to conventional serum-based antibody EIAs and are suitable for population-based surveillance. We describe the development and evaluation of SARS-CoV-2 IgG EIAs using SARS-CoV-2 viral nucleoprotein (NP) and spike (S) proteins in IgG isotype capture format and an indirect receptor-binding-domain (RBD) IgG EIA, intended for use in children as a primary endpoint. All three assays were assessed using a panel of 1,999 paired serum and oral fluids from children and adults participating in school SARS-CoV-2 surveillance studies during and after the first and second pandemic wave in the United Kingdom. The anti-NP IgG capture assay was the best candidate, with an overall sensitivity of 75% (95% confidence interval [CI]: 71 to 79%) and specificity of 99% (95% CI: 78 to 99%) compared with paired serum antibodies. Sensitivity observed in children (80%, 95% CI: 71 to 88%) was higher than that in adults (67%, CI: 60% to 74%). Oral fluid assays (OF) using spike protein and RBD antigens were also 99% specific and achieved reasonable but lower sensitivity in the target population (78%, 95% CI [68% to 86%] and 53%, 95% CI [43% to 64%], respectively). IMPORTANCE We report on the first large-scale assessment of the suitability of oral fluids for detection of SARS-CoV-2 antibody obtained from healthy children attending school. The sample type (gingiva-crevicular fluid, which is a transudate of blood but is not saliva) can be self collected. Although detection of antibodies in oral fluids is less sensitive than that in blood, our study suggests an optimal format for operational use. The laboratory methods we have developed can reliably measure antibodies in children, who are able to take their own samples. Our findings are of immediate practical relevance for use in large-scale seroprevalence studies designed to measure exposure to infection, as they typically require venipuncture. Overall, our data indicate that OF assays based on the detection of SARS-CoV-2 antibodies are a tool suitable for population-based seroepidemiology studies in children and highly acceptable in children and adults, as venipuncture is no longer necessary.

Context: Chemical toxicity prediction at early stage drug discovery phase has been researched for years, and newest methods are always investigated. Research data comprising chemical physicochemical properties, toxicity, assay, and activity details create massive data which are becoming difficult to manage. Identifying the desired featured chemical with the desired biological activity from millions of chemicals is a challenging task., Aims: In this study, we investigate and explore big data technologies and machine learning approaches to do an efficient chemical data mining for endocrine receptor disruption prediction and virtual compound screening. The power of artificial neural network (ANN) in predicting chemicals' activity toward androgen receptor (AR) and estrogen receptor (ER) and thereby classifying into human endocrine disruptor or nondisruptor is investigated., Subjects and Methods: Molecules are collected along with their Inhibitory Concentration (IC 50 ) values toward AR and ER. Training and test datasets are created with active and inactive classes of molecules. Molecular fingerprints of Electro Topological State (E-State) are generated for describing every compound. ANN machine learning model is created using Apache Spark and implemented in Hadoop big data environment. Test chemical's structural similarity toward active class of training compounds is estimated and combined with ANN model for improving prediction accuracy., Results: AR and ER predictive models applied on corresponding test datasets gave 86.31% and 89.57% accuracies, respectively, in correctly classifying molecules as disruptor or nondisruptor. Molecular fragments and functional groups are ranked based on their importance in forming ANN model and influence toward the AR and ER disruption behavior. Training molecules that are specific to the test molecules' endocrine disruption prediction are retrieved based on the structural similarity values., Conclusions: The current study demonstrates a new approach of chemical endocrine receptor disruption prediction combining ANN machine learning method and molecular similarity in a big data environment. This method of predictive modeling can be further tested with more receptors and hormones and predictive power can be examined., Competing Interests: There are no conflicts of interest.