Madurai Medical College

Metal organic frameworks (MOFs) are a class of porous crystalline materials that feature a series of unique properties, such as large surface area and porosity, high content of transition metals, and possibility to be designed and modified after synthesis, that make these solids especially suitable as heterogeneous catalysts. The active sites can be coordinatively unsaturated metal ions, substituents at the organic linkers or guest species located inside the pores. The defects on the structure also create these open sites. The present review summarizes the current state of the art in the use of MOFs as solid catalysts according to the type of site, making special emphasis on the more recent strategies to increase the population of these active sites and tuning their activity, either by adapting the synthesis conditions or by post-synthetic modification. This review highlights those reports illustrating the synergy derived from the presence of more than one of these types of sites, leading to activation of a substrate by more than one site or to the simultaneous activation of different substrates by complementary sites. This synergy is frequently the main reason for the higher catalytic activity of MOFs compared to homogeneous catalysts or other alternative solid materials. Besides dark reactions, this review also summarizes the use of MOFs as photocatalysts emphasizing the uniqueness of these materials regarding adaptation of the linkers as light absorbers and metal exchange at the nodes to enhance photoinduced electron transfer, in comparison with conventional inorganic photocatalysts. This versatility and flexibility that is offered by MOFs to optimize their visible light photocatalytic activity explains the current interest in exploiting these materials for novel photocatalytic reactions, including hydrogen evolution and photocatalytic CO2 reduction.

Graphenes and related materials have attracted growing interest as metal-free catalysts. The present review is focused on describing the active sites that have been proposed to be responsible for the catalytic activity observed for such systems. It will be shown that diverse defects and chemical functionalities on the graphene layers can catalyze reactions, including oxygenated functional groups, carbon vacancies and holes, edge effects, and the presence of dopant elements. Besides discrete active sites, the catalytic activity arising from the collective properties of graphenes as materials by adsorbing substrates and reagents and activating them by charge transfer is also commented. The review has an introductory general section summarizing the general methodologies that have been used to support the proposed structure of the active sites, including theoretical calculations, comparison of the catalytic activity of graphene samples with different compositions, the use of organic molecules as models of the active centers, and selective masking of functional groups. The review is concluded with our view on future developments in the field.

BACKGROUND: For more than three decades, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) has provided a framework to quantify health loss due to diseases, injuries, and associated risk factors. This paper presents GBD 2023 findings on disease and injury burden and risk-attributable health loss, offering a global audit of the state of world health to inform public health priorities. This work captures the evolving landscape of health metrics across age groups, sexes, and locations, while reflecting on the remaining post-COVID-19 challenges to achieving our collective global health ambitions. METHODS: The GBD 2023 combined analysis estimated years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs) for 375 diseases and injuries, and risk-attributable burden associated with 88 modifiable risk factors. Of the more than 310 000 total data sources used for all GBD 2023 (about 30% of which were new to this estimation round), more than 120 000 sources were used for estimation of disease and injury burden and 59 000 for risk factor estimation, and included vital registration systems, surveys, disease registries, and published scientific literature. Data were analysed using previously established modelling approaches, such as disease modelling meta-regression version 2.1 (DisMod-MR 2.1) and comparative risk assessment methods. Diseases and injuries were categorised into four levels on the basis of the established GBD cause hierarchy, as were risk factors using the GBD risk hierarchy. Estimates stratified by age, sex, location, and year from 1990 to 2023 were focused on disease-specific time trends over the 2010-23 period and presented as counts (to three significant figures) and age-standardised rates per 100 000 person-years (to one decimal place). For each measure, 95% uncertainty intervals [UIs] were calculated with the 2·5th and 97·5th percentile ordered values from a 250-draw distribution. FINDINGS: Total numbers of global DALYs grew 6·1% (95% UI 4·0-8·1), from 2·64 billion (2·46-2·86) in 2010 to 2·80 billion (2·57-3·08) in 2023, but age-standardised DALY rates, which account for population growth and ageing, decreased by 12·6% (11·0-14·1), revealing large long-term health improvements. Non-communicable diseases (NCDs) contributed 1·45 billion (1·31-1·61) global DALYs in 2010, increasing to 1·80 billion (1·63-2·03) in 2023, alongside a concurrent 4·1% (1·9-6·3) reduction in age-standardised rates. Based on DALY counts, the leading level 3 NCDs in 2023 were ischaemic heart disease (193 million [176-209] DALYs), stroke (157 million [141-172]), and diabetes (90·2 million [75·2-107]), with the largest increases in age-standardised rates since 2010 occurring for anxiety disorders (62·8% [34·0-107·5]), depressive disorders (26·3% [11·6-42·9]), and diabetes (14·9% [7·5-25·6]). Remarkable health gains were made for communicable, maternal, neonatal, and nutritional (CMNN) diseases, with DALYs falling from 874 million (837-917) in 2010 to 681 million (642-736) in 2023, and a 25·8% (22·6-28·7) reduction in age-standardised DALY rates. During the COVID-19 pandemic, DALYs due to CMNN diseases rose but returned to pre-pandemic levels by 2023. From 2010 to 2023, decreases in age-standardised rates for CMNN diseases were led by rate decreases of 49·1% (32·7-61·0) for diarrhoeal diseases, 42·9% (38·0-48·0) for HIV/AIDS, and 42·2% (23·6-56·6) for tuberculosis. Neonatal disorders and lower respiratory infections remained the leading level 3 CMNN causes globally in 2023, although both showed notable rate decreases from 2010, declining by 16·5% (10·6-22·0) and 24·8% (7·4-36·7), respectively. Injury-related age-standardised DALY rates decreased by 15·6% (10·7-19·8) over the same period. Differences in burden due to NCDs, CMNN diseases, and injuries persisted across age, sex, time, and location. Based on our risk analysis, nearly 50% (1·27 billion [1·18-1·38]) of the roughly 2·80 billion total global DALYs in 2023 were attributable to the 88 risk factors analysed in GBD. Globally, the five level 3 risk factors contributing the highest proportion of risk-attributable DALYs were high systolic blood pressure (SBP), particulate matter pollution, high fasting plasma glucose (FPG), smoking, and low birthweight and short gestation-with high SBP accounting for 8·4% (6·9-10·0) of total DALYs. Of the three overarching level 1 GBD risk factor categories-behavioural, metabolic, and environmental and occupational-risk-attributable DALYs rose between 2010 and 2023 only for metabolic risks, increasing by 30·7% (24·8-37·3); however, age-standardised DALY rates attributable to metabolic risks decreased by 6·7% (2·0-11·0) over the same period. For all but three of the 25 leading level 3 risk factors, age-standardised rates dropped between 2010 and 2023-eg, declining by 54·4% (38·7-65·3) for unsafe sanitation, 50·5% (33·3-63·1) for unsafe water source, and 45·2% (25·6-72·0) for no access to handwashing facility, and by 44·9% (37·3-53·5) for child growth failure. The three leading level 3 risk factors for which age-standardised attributable DALY rates rose were high BMI (10·5% [0·1 to 20·9]), drug use (8·4% [2·6 to 15·3]), and high FPG (6·2% [-2·7 to 15·6]; non-significant). INTERPRETATION: Our findings underscore the complex and dynamic nature of global health challenges. Since 2010, there have been large decreases in burden due to CMNN diseases and many environmental and behavioural risk factors, juxtaposed with sizeable increases in DALYs attributable to metabolic risk factors and NCDs in growing and ageing populations. This long-observed consequence of the global epidemiological transition was only temporarily interrupted by the COVID-19 pandemic. The substantially decreasing CMNN disease burden, despite the 2008 global financial crisis and pandemic-related disruptions, is one of the greatest collective public health successes known. However, these achievements are at risk of being reversed due to major cuts to development assistance for health globally, the effects of which will hit low-income countries with high burden the hardest. Without sustained investment in evidence-based interventions and policies, progress could stall or reverse, leading to widespread human costs and geopolitical instability. Moreover, the rising NCD burden necessitates intensified efforts to mitigate exposure to leading risk factors-eg, air pollution, smoking, and metabolic risks, such as high SBP, BMI, and FPG-including policies that promote food security, healthier diets, physical activity, and equitable and expanded access to potential treatments, such as GLP-1 receptor agonists. Decisive, coordinated action is needed to address long-standing yet growing health challenges, including depressive and anxiety disorders. Yet this can be only part of the solution. Our response to the NCD syndemic-the complex interaction of multiple health risks, social determinants, and systemic challenges-will define the future landscape of global health. To ensure human wellbeing, economic stability, and social equity, global action to sustain and advance health gains must prioritise reducing disparities by addressing socioeconomic and demographic determinants, ensuring equitable health-care access, tackling malnutrition, strengthening health systems, and improving vaccination coverage. We live in times of great opportunity. FUNDING: Gates Foundation and Bloomberg Philanthropies.

In this review, the recent progress in the electrochemical sensing of dopamine with various graphene and their nanocomposite materials modified electrodes are presented.

Biomass is increasingly used as a source of fuels and chemicals as a renewable alternative to fossil feedstocks. Cellulose, hemicellulose and lignin are converted into platform chemicals from which a large range of compounds are derived with different structures. These biomass transformation processes require the use of efficient and durable catalysts that should drive the selectivity of the process. This review focuses on the use of metal-organic frameworks (MOFs) and derivatives as catalysts for biomass conversion. After an introduction setting up the importance of the field and the MOF features that justify their prevalence as heterogeneous catalysts for liquid phase reactions, the two main parts of the review are the description of MOF synthesis and adaptation and coverage of the catalytic reactions involving biomass substrates organized according to the type of MOF. The last section summarizes the current state of the art and our outlook for the future development of the field.

Abstract The present study is to design an eco-friendly mode to rapidly synthesize selenium nanoparticles (SeNPs) through Ceropegia bulbosa tuber’s aqueous extracts and confirming SeNPs synthesis by UV–Vis spectroscopy, FT-IR, XRD, FE-SEM-EDS mapping, HR-TEM, DLS and zeta potential analysis. In addition, to assess the anti-cancer efficacy of the SeNPs against the cultured MDA-MB-231, as studies have shown SeNPs biosynthesis downregulates the cancer cells when compared to normal HBL100 cell lines. The study observed the IC 50 value of SeNPs against MDA-MB-231 cells was 34 µg/mL for 48 h. Furthermore, the SeNPs promotes growth inhibitory effects of certain clinical pathogens such as Bacillus subtilis and Escherichia coli . Apart, from this the SeNPs has shown larvicidal activity after 24 h exposure in Aedes albopitus mosquito’s larvae with a maximum of 250 g/mL mortality concentration. This is confirmed by the histopathology results taken at the 4th larval stage. The histopathological studies revealed intense deterioration in the hindgut, epithelial cells, mid gut and cortex region of the larvae. Finally, tried to investigate the photocatalytic activity of SeNPs against the toxic dye, methylene blue using halogen lamp and obtained 96% degradation results. Withal computational study SeNPs was shown to exhibit consistent stability towards breast cancer protein BRCA2. Overall, our findings suggest SeNPs as a potent disruptive agent for MDA-MB-231 cells, few pathogens, mosquito larvae and boosts the photocatalytic dye degradation.

-SGO composite membranes can be used to address various critical problems associated with commercial Nafion membranes in PEMFC applications.

Brain cancer is one of the cell synthesis diseases. Brain cancer cells are analyzed for patient diagnosis. Due to this composite cell, the conceptual classifications differ from each and every brain cancer investigation. In the gene test, patient prognosis is identified based on individual biocell appearance. Classification of advanced artificial neural network subtypes attains improved performance compared to previous enhanced artificial neural network (EANN) biocell subtype investigation. In this research, the proposed features are selected based on improved gene expression programming (IGEP) with modified brute force algorithm. Then, the maximum and minimum term survivals are classified by using PCA with enhanced artificial neural network (EANN). In this, the improved gene expression programming (IGEP) effectual features are selected by using remainder performance to improve the prognosis efficiency. This system is estimated by using the Cancer Genome Atlas (CGA) dataset. Simulation outputs present improved gene expression programming (IGEP) with modified brute force algorithm which achieves accurate efficiency of 96.37%, specificity of 96.37%, sensitivity of 98.37%, precision of 78.78%, F ‐measure of 80.22%, and recall of 64.29% when compared to generalized regression neural network (GRNN), improved extreme learning machine (IELM) with minimum redundancy maximum relevance (MRMR) method, and support vector machine (SVM).

The integration of artificial intelligence (AI) into healthcare promises groundbreaking advancements in patient care, revolutionizing clinical diagnosis, predictive medicine, and decision-making. This transformative technology uses machine learning, natural language processing, and large language models (LLMs) to process and reason like human intelligence. OpenAI's ChatGPT, a sophisticated LLM, holds immense potential in medical practice, research, and education. However, as AI in healthcare gains momentum, it brings forth profound ethical challenges that demand careful consideration. This comprehensive review explores key ethical concerns in the domain, including privacy, transparency, trust, responsibility, bias, and data quality. Protecting patient privacy in data-driven healthcare is crucial, with potential implications for psychological well-being and data sharing. Strategies like homomorphic encryption (HE) and secure multiparty computation (SMPC) are vital to preserving confidentiality. Transparency and trustworthiness of AI systems are essential, particularly in high-risk decision-making scenarios. Explainable AI (XAI) emerges as a critical aspect, ensuring a clear understanding of AI-generated predictions. Cybersecurity becomes a pressing concern as AI's complexity creates vulnerabilities for potential breaches. Determining responsibility in AI-driven outcomes raises important questions, with debates on AI's moral agency and human accountability. Shifting from data ownership to data stewardship enables responsible data management in compliance with regulations. Addressing bias in healthcare data is crucial to avoid AI-driven inequities. Biases present in data collection and algorithm development can perpetuate healthcare disparities. A public-health approach is advocated to address inequalities and promote diversity in AI research and the workforce. Maintaining data quality is imperative in AI applications, with convolutional neural networks showing promise in multi-input/mixed data models, offering a comprehensive patient perspective. In this ever-evolving landscape, it is imperative to adopt a multidimensional approach involving policymakers, developers, healthcare practitioners, and patients to mitigate ethical concerns. By understanding and addressing these challenges, we can harness the full potential of AI in healthcare while ensuring ethical and equitable outcomes.

OBJECTIVE: To assess the impact of supplementing newborn infants with vitamin A on mortality at age 6 months. DESIGN: Community based, randomised, double blind, placebo controlled trial. SETTING: Two rural districts of Tamil Nadu, southern India. PARTICIPANTS: 11 619 newborn infants allocated 24 000 IU oral vitamin A or placebo on days 1 and 2 after delivery. MAIN OUTCOME MEASURE: Primary outcome measure was mortality at age 6 months. RESULTS: Infants in the vitamin A group had a 22% reduction in total mortality (95% confidence interval 4% to 37%) compared with those in the placebo group. Vitamin A had an impact on mortality between two weeks and three months after treatment, with no additional impact after three months. CONCLUSION: Supplementing newborn infants with vitamin A can significantly reduce early infant mortality.

Leachate and groundwater samples were collected from Vendipalayam, Semur and Vairapalayam landfill sites in Erode city, Tamil Nadu, India, to study the possible impact of leachate percolation on groundwater quality. Concentrations of various physicochemical parameters including heavy metals (Cd, Cr, Cu, Fe, Ni, Pb, Fe and Zn) were determined in leachate samples and are reported. The concentrations of Cl-, NO3-, SO42-, NH4+ were found to be in considerable levels in the groundwater samples particularly near to the landfill sites, likely indicating that groundwater quality is being significantly affected by leachate percolation. Further they were proved to be the tracers for groundwater contamination near Semur and Vendipalayam dumpyards. The presence of contaminants in groundwater particularly near the landfill sites warns its quality and thus renders the associated aquifer unreliable for domestic water supply and other uses. Although some remedial measures are suggested to reduce further groundwater contamination via leachate percolation, the present study demands for the proper management of waste in Erode city.

The exfoliation of graphene from pristine graphite in a liquid phase was achieved successfully via sonication followed by centrifugation method. Ultraviolet–visible (UV–vis) spectra of the obtained graphene dispersions at different exfoliation time indicated that the concentration of graphene dispersion increased markedly with increasing exfoliation time. The sheet-like morphology of the exfoliated graphene was revealed by Scanning Electron Microscopy (SEM) image. Further, the morphological change in different exfoliation time was investigated by Atomic Force Microscopy (AFM). A complete structural and defect characterization was probed using micro-Raman spectroscopic technique. The shape and position of the 2D band of Raman spectra revealed the formation of bilayer to few layer graphene. Also, Raman mapping confirmed the presence of uniformly distributed bilayer graphene sheets on the substrate.

Lannea coromandelica leaf extract (LCLE) as a corrosion inhibitor in 1 M H2SO4 was investigated by weight loss and electrochemical techniques. Inhibition efficiency of LCLE was found to increase with increasing concentration but decreased with increasing temperature. Polarization measurements revealed that the LCLE acted as a mixed type inhibitor. Nyquist plots showed that on increasing the LCLE concentration, the charge transfer resistance increased and the double layer capacitance decreased. The adsorption of LCLE on mild steel obeyed the Langmuir adsorption isotherm. FT-IR, XRD, SEM and AFM techniques confirmed the adsorption of LCLE on mild steel surface.

Cardiovascular diseases (CVDs) are the leading cause of death worldwide. An expanding body of evidence supports the role of human microbiome in the establishment of CVDs and, this has gained much attention recently. This work was aimed to study the circulating human microbiome in CVD patients and healthy subjects. The levels of circulating cell free DNA (circDNA) was higher in CVD patients (n = 80) than in healthy controls (n = 40). More specifically, the relative levels of circulating bacterial DNA and the ratio of 16S rRNA/β-globin gene copy numbers were higher in the circulation of CVD patients than healthy individuals. In addition, we found a higher circulating microbial diversity in CVD patients (n = 3) in comparison to healthy individuals (n = 3) by deep shotgun sequencing. At the phylum level, we observed a dominance of Actinobacteria in CVD patients, followed by Proteobacteria, in contrast to that in healthy controls, where Proteobacteria was predominantly enriched, followed by Actinobacteria. The circulating virome in CVD patients was enriched with bacteriophages with a preponderance of Propionibacterium phages, followed by Pseudomonas phages and Rhizobium phages in contrast to that in healthy individuals, where a relatively greater abundance of eukaryotic viruses dominated by Lymphocystis virus (LCV) and Torque Teno viruses (TTV) was observed. Thus, the release of bacterial and viral DNA elements in the circulation could play a major role leading to elevated circDNA levels in CVD patients. The increased circDNA levels could be either the cause or consequence of CVD incidence, which needs to be explored further.

This perspective summarizes the catalytic activity of K10 montmorillonite as a multifunctional catalyst for organic reactions.

Transdermal patches of verapamil hydrochloride were prepared using four different polymers (individual and combination): Eudragit RL100 (ERL100), Eudragit RS100 (ERS100), hydroxypropyl methylcellulose 15 cps (HPMC), and ethyl cellulose (EC), of varying degrees of hydrophilicity and hydrophobicity. The effect of the polymers on the technological properties, i.e., drug release, water vapor transmission rate (WVTR), and percentage moisture loss (ML), percentage moisture absorption (MA), folding endurance, and thickness, was investigated. Different formulations were prepared in accordance with the 2(3) factorial design, with ERL100 being the parent polymer. The patch containing ERL100 alone showed maximum WVTR, % MA, and % ML, which could be attributed to its hydrophilic nature. As expected, substitution with ERS100, HPMC, and EC decreased all the above values in accordance with their decreasing degree of hydrophilicity. In vitro release studies showed zero-order release of the drug from all the patches, and the mechanism of release was diffusion mediated. Moreover, the release of the drug was sustained and it extended over a period of 24 hr in all formulations. A12 emerged as the most satisfactory formulation insofar as its technological properties were concerned. Further, release and permeation of the drug from the most satisfactory formulation (A12) was evaluated through different biological barriers (shed snake skin, rabbit skin, and rat skin) to get an idea of the drug permeation through human skin. Shed snake's skin was found to be most permeable (82.56% drug release at 24 hr) and rat skin was least permeable (52.38%). Percutaneous absorption studies were carried out in rabbits. The pharmacokinetic parameters calculated from blood levels of the drug revealed a profile typical of a sustained release formulation, with the ability to maintain adequate plasma levels for 24 hr. [AUC: 3.09 mg/mL hr, Cmax: 203.95 microg/mL, Tmax: 8 hr]. It can therefore be concluded that the patch containing ERL100 and HPMC in the ratio 8:2 has achieved the objectives of transdermal drug delivery system, such as avoidance of first pass effect, extended release, and reduced frequency of administration.

Solid lipid nanoparticles are typically spherical with an average diameter between 1 and 1000 nm. It is an alternative carrier system to tradition colloidal carriers, such as, emulsions, liposomes, and polymeric micro and nanoparticles. Ramipril is an antihypertensive agent used in the treatment of hypertension. Its oral bioavailability is 28% and it is rapidly excreted through the renal route. This drug has many side effects such as, postural hypotension, hyperkalemia, and angioedema, when given as an immediate dosage form. To overcome the side effects and to increase the bioavailability of ramipril, solid lipid nanoparticles of ramipril are prepared by using lipids (glyceryl monostearate and glyceryl monooleate) with stabilizers (tween 80, poloxamer 188, and span 20). The prepared formulations have been evaluated for entrapment efficiency, drug content, in-vitro drug release, particle size analysis, scanning electron spectroscopy, Fourier transform-infrared studies, and stability. A formulation containing glyceryl monooleate, stabilized with span 20 as surfactant showed prolonged drug release, smaller particle size, and narrow particle size distribution, as compared to other formulations with different surfactants and lipids.

A rhodamine based derivative RDD-1 bearing dimethylaminobenzaldehyde has been designed and synthesized.

A material based on palladium nanoparticles supported on nitrogen rich mesoporous covalent organic polymers exhibiting excellent catalytic activity towards Mizoroki–Heck cross coupling reaction.

Photovoltaic (PV) panels convert a portion of the incident solar radiation into electrical energy and the remaining energy (>70 %) is mostly converted into thermal energy. This thermal energy is trapped within the panel which, in turn, increases the panel temperature and deteriorates the power output as well as electrical efficiency. To obtain high-efficiency solar photovoltaics, effective thermal management systems is of utmost. This article presents a comprehensive review that explores recent research related to thermal management solutions as applied to photovoltaic technology. The study aims at presenting a wide range of proposed solutions and alternatives in terms of design approaches and concepts, operational methods and other techniques for performance enhancement, with commentary on their associated challenges and opportunities. Both active and passive thermal management solutions are presented, which are classified and discussed in detail, along with results from a breadth of experimental efforts into photovoltaic panel performance improvements. Approaches relying on radiative, as well as convective heat transfer principles using air, water, heat pipes, phase change materials and/or nanoparticle suspensions (nanofluids) as heat-exchange media, are discussed while including summaries of their unique features, advantages, disadvantages and possible applications. In particular, hybrid photovoltaic-thermal (PV-T) collectors that use a coolant to capture waste heat from the photovoltaic panels in order to deliver an additional useful thermal output are also reviewed, and it is noted that this technology has a promising potential in terms of delivering high-efficiency solar energy conversion. The article can act as a guide to the research community, developers, manufacturers, industrialists and policymakers in the design, manufacture, application and possible promotion of high-performance photovoltaic-based technologies and systems.