In vitro anti-HIV activity of some Indian medicinal plant extracts

Background Human Immunodeficiency Virus (HIV) persists to be a significant public health issue worldwide. The current strategy for the treatment of HIV infection, Highly Active Antiretroviral Therapy (HAART), has reduced deaths from AIDS related disease, but it can be an expensive regime for the underdeveloped and developing countries where the supply of drugs is scarce and often not well tolerated, especially in persons undergoing long term treatment. The present therapy also has limitations of development of multidrug resistance, thus there is a need for the discovery of novel anti-HIV compounds from plants as a potential alternative in combating HIV disease. Methods Ten Indian medicinal plants were tested for entry and replication inhibition against laboratory adapted strains HIV-1IIIB, HIV-1Ada5 and primary isolates HIV-1UG070, HIV-1VB59 in TZM-bl cell lines and primary isolates HIV-1UG070, HIV-1VB59 in PM1 cell lines. The plant extracts were further evaluated for toxicity in HEC-1A epithelial cell lines by transwell epithelial model. Results The methanolic extracts of Achyranthes aspera, Rosa centifolia and aqueous extract of Ficus benghalensis inhibited laboratory adapted HIV-1 strains (IC80 3.6–118 μg/ml) and primary isolates (IC80 4.8–156 μg/ml) in TZM-bl cells. Methanolic extract of Strychnos potatorum, aqueous extract of Ficus infectoria and hydroalcoholic extract of Annona squamosa inhibited laboratory adapted HIV-1 strains (IC80 4.24–125 μg/ml) and primary isolates (IC80 18–156 μg/ml) in TZM-bl cells. Methanolic extracts of Achyranthes aspera and Rosa centifolia, (IC801-9 μg/ml) further significantly inhibited HIV-1 primary isolates in PM1cells. Methanolic extracts of Tridax procumbens, Mallotus philippinensis, Annona reticulate, aqueous extract of Ficus benghalensis and hydroalcoholic extract of Albizzia lebbeck did not exhibit anti-HIV activity in all the tested strains. Methanolic extract of Rosa centifolia also demonstrated to be non-toxic to HEC-1A epithelial cells and maintained epithelial integrity (at 500 μg/ml) when tested in transwell dual-chamber. Conclusion These active methanolic extracts of Achyranthes aspera and Rosa centifolia, could be further subjected to chemical analysis to investigate the active moiety responsible for the anti-HIV activity. Methanolic extract of Rosa centifolia was found to be well tolerated maintaining the epithelial integrity of HEC-1A cells in vitro and thus has potential for investigating it further as candidate microbicide

Impact of global warming (1.5ºC) on the productivity of selected C3 and C4 crops across Tamil Nadu

Over the last century, mean annual temperatures increased by ~1°C. UNFCCC has proposed to limit warming below 1.5°C relative to pre-industrial levels. A study was conducted on rice (C3 pathway) and maize (C4 pathway) over Tamil Nadu using DSSAT to understand the climate change impacts with projected temperature increase of 1.5°C.The future climate under RCP 4.5 and RCP 8.5 indicated 1.5°C increase in temperature to happen by 2053 and 2035, respectively over Tamil Nadu.Annual rainfall deviations in RCP4.5 showed drier than current condition and RCP8.5 projected wetter SWM and drier NEM (90 % of current rainfall).Impact of 1.5°C warming on crop phenology indicated 8 days reduction in duration for rice and maize. The W UE of rice would decrease by 17 per cent at current CO2 whereas, enrichment (430 ppm) would reduce by12 per cent and rice yield is reduced by 21 per cent with 360 ppm CO2 and 430 ppm reducedby 17 per cent. There is no considerable varaition (- 5 to 1 %) in maize productivity with 1.5 ºC warming. The above results indicated that 1.5 ºC warming has more negative impacts on plants with C3 compared to C4 pathwa

A nomadic multi-agent based privacy metrics for e-health care : a deep learning approach

In recent years, there has been a surge in the use of deep learning systems for e-healthcare applications. While these systems can provide significant benefits regarding improved diagnosis and treatment, they also pose substantial privacy risks to patients' sensitive data. Privacy is a crucial issue in e-healthcare, and it is essential to keep patient information secure. A new approach based on multi-agent-based privacy metrics for e-healthcare deep learning systems has been proposed to address this issue. This approach uses a combination of deep learning and multi-agent systems to provide a more robust and secure method for e-healthcare applications. The multi-agent system is designed to monitor and control the access to patients' data by different agents in the system. Each agent is assigned a specific role and has specific data access permissions. The system employs a set of privacy metrics to a substantial privacy level of the data accessed by each agent. These metrics include confidentiality, integrity, and availability, evaluated in real-time and used to identify potential privacy violations. In addition to the multi-agent system, the deep learning component is also integrated into the system to improve the accuracy of diagnoses and treatment plans. The deep learning model is trained on a large dataset of medical records and can accurately predict the diagnosis and treatment plan based on the patient's symptoms and medical history. The multi-agent-based privacy metrics for the e-healthcare deep learning system approach have several advantages. It provides a more secure system for e-healthcare applications by ensuring only authorized agents can access patients' data. Privacy metrics enable the system to identify potential privacy violations in real-time, thereby reducing the risk of data breaches. Finally, integrating deep learning improves the accuracy of diagnoses and treatment plans, leading to better patient outcomes. [Abstract copyright: © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Extension of energy band gap in ternary photonic crystal using left-handed materials

We investigate the extension of energy band gap in one-dimensional ternary photonic crystal. We assume one of the layers constituting the ternary photonic crystal to be left-handed material (LHM) of simultaneously negative electric permittivity and magnetic permeability. The photonic crystal has the structure dielectric/LHM/dielectric. We show in this work, the energy band gap in one-dimensional ternary photonic crystal can be dramatically enlarged with the increase of the LHM layer thickness. Moreover, it can also be enlarged with the decrease of both the negative permittivity and permeability of the LHM layer. The effects of the angle of incidence and the number of layers are also investigated