A series comprising 20 novel benzenesulfonamide bearing 1.2.3-triazoles 6a-6d, 7a-7d, 8a-8d, 9a-9d, 10a-10d has been synthesized and investigated as antifungal agents. The synthesized compounds were tested against two fungal strains Aspergillus fumigatus 3007 and Candida albicans 3018. Among the tested compounds, three gave the lowest inhibitory concentration of 0.039 (mg/ml) against A. fumigatus 3007 and two compounds gave the lowest inhibitory concentration of 0.019 mg/ml against C. albicans 3018. The antifungal potential of the synthessied compounds was in par with the reported drug fluconazole. To elucidate the antifungal mechanism of the synthesized compounds confocal images of the treated fungal cells were analysed. The cells depicted porous nature of fungal membrane indicating the probable inhibition of fungal lanosterol 14-α demethylase enzyme. In silico tools like molecular docking, ADME analysis including physicochemical properties, lipophilicity, solubility in water, pharmacokinetic properties, drug likeness, medicinal chemistry properties and toxicity analysis was also carried to establish the significance of the synthesized compounds.

Bilirubin (BR) is a key biomarker for haemolytic disorders, with levels >2.5 mg dl(-1) indicating hyperbilirubinemia. Accurate and sensitive detection of BR, therefore, assumes importance in clinical diagnostics. This study investigates radio-frequency (RF) sputtered MoO3 thin films as a matrix for sensitive BR sensors, deposited on indium tin oxide (ITO) coated glass under varying Ar (50%-80%) in the sputtering gas mixture. The film deposited at 65% Ar ambient was noted to exhibit optimal electrochemical characteristics. The same was functionalized with bilirubin oxidase (BOx) via EDC-NHS coupling to develop a MoO3-based bioelectrode. Cyclic voltammetry (CV) measurements demonstrated a sensitivity of 50.55 mu A (mg/dl)(-1) in the linear range of 0.05-2.5 mg dl(-1) and a sensitivity of 11.30 mu A (mg/dl)(-1) in the linear range of 2.5-7.5 mg dl(-1). Differential Pulse Voltammetry (DPV) studies further enhanced detection performance, exhibiting sensitivities of 83.27 mu A (mg/dl)(-1) and 48.19 mu A (mg/dl)(-1) in the ranges of 0.05-2.5 mg dl(-1) and 2.5-7.5 mg dl(-1), respectively, showing a limit of detection of 0.03 mg dl(-1). The developed BOx/MoO3/ITO bioelectrode demonstrated excellent reproducibility, stability and selectivity, confirming the potential of RF-sputtered MoO3 thin films for reliable bilirubin biosensing applications.

Sustainable and eco-friendly biosensing technologies are emerging as a potential approach for healthcare improvement while simultaneously reducing environmental impact. In this study, a novel uric acid biosensor has been developed using green-synthesized molybdenum oxide (MoO3) thin films, which demonstrates a creative way to repurpose waste for advanced technological applications. The structural and morphological studies confirmed the uniformity and high quality of the MoO3 thin films, which played a key role in enhancing sensor performance. The fabricated biosensor demonstrated high sensitivity [244.76 µA/(mM cm2)], a fast response time of 5 s, and excellent selectivity against common interferents which are typically found in blood plasma. Additionally, the low Michaelis–Menten constant (Kₘ = 0.07311 mM) indicates that the enzyme maintained a strong affinity for uric acid, ensuring reliable detection even at low concentrations. In addition to its strong analytical performance, this work highlights the potential of green synthesis in the development of biosensors. By integrating eco-conscious material synthesis with high-performance sensing capabilities, this work lays the foundation for more sustainable, cost-effective, and efficient biosensors for healthcare applications. This approach not only enhances biosensing technology but also aligns with global efforts to minimize waste and promote greener alternatives in scientific innovation.

The current work investigates the influence of the Au catalyst layer on the development of ZnO nanostructures using the vapour liquid solid (VLS) modification of the vapour phase transport technique and their suitability as an efficient platform for detection of free cholesterol. ZnO nanostructures were prepared with and without the catalyst and subsequently, were characterized for structural, morphological, electrical and electrochemical properties. These ZnO nanostructures were deposited on platinum coated silicon (Pt/Si) to fabricate bioelectrodes forming ZnO/Pt/Si and ZnO/Au/Pt/Si configuration. The presence of catalyst was seen to considerably enhance the crystallinity, mobility, shape and morphology of the fabricated nanostructures. Most importantly, it was seen to enhance the electron transfer characteristics leading to a better electrochemical response. It was observed that the bioelectrode with Au as a catalyst layer leads to enhancement in sensitivity of ZnO nanostructures towards the detection of free cholesterol. The enhanced biosensing performance with sensitivity of 280 µAmM-1cm-1, linearity across a wide range from 0.12–12.93 mM of cholesterol and shelf life of 10 weeks is attributed to the presence of Au catalyst. Additionally, the study demonstrated that the Au-catalyzed ZnO nanostructures exhibit excellent reproducibility and stability, essential for practical biosensor applications.

In this study, sol gel technique is used to fabricate manganese (Mn) doped ZnO thin films and further utilize them as a platform for uric acid biosensors. The objective was to introduce manganese into the ZnO matrix to enhance its redox properties, capitalizing on the multivalent nature of manganese. The Mn-doped thin films of concentrations varying from 3 %,5 %,7 % and 10 % were prepared and further characterized using UV-vis spectroscopy, X-ray diffraction (XRD) spectroscopy, Fourier transform infrared spectroscopy (FTIR), field emission scanning electron microscopy (FESEM) and cyclic voltammetry (CV) measurements. The ZnO thin films with 7 % doping of Mn exhibited improved redox behaviour, as evident by the distinct redox peaks. In order to immobilise the uricase enzyme, the 7 % Mn doped composition was used, creating a highly sensitive and focused uric acid detection platform. The fabricated biosensor exhibits excellent performance in terms of sensitivity (40 mu AmM(-1)cm(-2)), selectivity with <5 % deviation found in presence of other known markers present in human sera, and shelf life >12 weeks, enabling precise and sensitive uric acid detection. This study brings to light an alternate approach in developing point of care biosensors using transition metal doped ZnO thin films.

Plants are vulnerable to phytopathogens including bacteria, fungi, and viruses, which result in significant financial losses (both before and after harvest) and risk the security of the global food supply. Climate change has been rapidly causing aggravation of plant disease impacts, with existing pathogens showing pandemic behavior making the development of efficient long-term disease management approaches difficult. Plants have two layers of resistance against these phytopathogens, called PAMP-triggered immunity (PTI) or effectors-triggered immunity (ETI). The development of pathogen-resistant plants has been made possible by advances in high-throughput molecular techniques and our growing understanding of plant–molecular interactions. In this respect, genome-editing (GE) technology has been revolutionized by clustered regularly interspaced short palindromic repeats (CRISPR)–CRISPR-associated protein (Cas) and is now being used to modify characteristics. Here, we've outlined the intricacies of the plant immune system and how CRISPR/Cas can be used to alter the system's many parts to give plants enduring resistance against phytopathogens.

One of the largest industries in the world is agriculture, and it is also the main contributor to diseases that affect human health due to the excessive use of antibiotics. The use of antimicrobials in food production and agriculture has a direct or indirect impact on the emergence of bacteria linked to plants and animals that may enter the food chain through the consumption of meat, fish, vegetables, or other food sources. Antibiotic resistance, or AMR, is a severe threat to public health systems around the world because of the overuse of antibiotics. The failure of antibiotics to treat infectious diseases portends uncertainty for the future of healthcare. Furthermore, spontaneous evolution, bacterial mutation, and the transmission of resistant genes via horizontal gene transfer are significant contributors to antimicrobial resistance. Numerous routes related to agriculture, including wastewater, soils, manure applications, direct contact between people and animals, and food intake, can result in the transmission of AMR bacteria and genes across systems. Through the complex network of the agricultural ecology, antibiotics, antibiotic resistance bacteria, and antibiotic resistance genes ultimately enter the food chain, leading to unpredictable health consequences in humans. Since various farming techniques and market niches may individually have a unique influence on the growth and proliferation of antibiotic resistance, the situation in the agricultural ecosystem is more challenging. This review focuses on antimicrobial resistance in agriculture, its detection techniques, how it affects human health, and several countermeasures that can be taken to combat antimicrobial resistance.

ABSTRACT: This appraisal overviews Persistent Organic Pollutants and suggests a novel approach to their bioremediation using algae as an agent. Compared to older techniques using different bacteria, a greenway for wastewater treatment is more environmentally sustainable and friendlier. It has a lot of potential to use new bioremediation technology that uses cyanobacteria and algae to remove variety of organic pollutants. Several organisms' health and well-being may be at risk due to the abundance of organic pollutants in the environment. Household garbage, agriculture, and industry are some of the numerous man-caused contributors to organic pollutants that pollute water across the planet. Wastewater needs to be cleaned before it may be discharged into rivers. As algae-based wastewater treatment systems don't produce any secondary pollutants and are environmentally sustainable, they are growing in popularity. A variety of organic pollutants can be absorbed and accumulated by algae and cyanobacteria at different rates, contingent upon the type of contaminant, the physio-chemical assets of waste water, as well as the specific species of algae involved. Moreover, phytoremediation is a more affordable option for breaking down organic pollutants than traditional methods. Algal biomass produced through phycoremediation might also play a significant role in the bioenergy value chain. Hence the emphasis of this paper is on an over view of Persistent Organic Pollutants, cyanobacteria and microalgae species, which have the potential to rid water systems of several organic pollutants.

A comprehensive investigation was engaged to determine the spatial distribution of Uranium (U) and the consequential chemical and radiological health risk associated due to the consumption of groundwater containing U, in Panchkula district. A well -ac-cepted technique of fluorescence of U estimation in an aqueous medium was employed having a detection limit of 0.50 mu gL-1. The chemo-radiological health risk and water quality index was computed using a standard equation of concerned agencies to deter-mine the suitability for human health. The concentration of U was observed to vary from 1.70 - 12.28 mu gL-1 with the mean value of 5.89 mu gL-1 The concentration of U was far below the standard prescribed limits as per World Health Organisation, Atomic Energy Regulatory Board, and United Nation Environmental Protection Agency. Ex-cept nitrate and total alkalinity in few samples, all water quality paramters were within the recommended limit of BIS. The annual effective dose (AED), excess cancer risk (ECR), and lifetime average daily dose (LADD) indicated no potential health issue due to the consumption of groundwater of studied locations. The correlation was computed between U and various macro-anions and cations present in water samples. U was ob-served to have a significant weak positive correlation with total dissolved solids (TDS), electrical conductivity (EC), and salinity.

Despite huge advancements in biosensing technologies in the last few years, there remains a gap in comprehending the intricate relationship between growth parameters and the corresponding biosensing response characteristics. The present work investigates the correlation between the physical properties of ZnO thin films and their biosensing response to address this gap and further fabricate a urea sensor based on the optimized conditions. The Vapor Phase Transport (VPT) method was used to grow ZnO thin films, with biosensing performance observed to be highly dependent on growth conditions. Under optimal conditions, ZnO films demonstrated biosensing-friendly properties such as low stress, strong carrier mobility for electron transfer, and a large surface area for effective biomolecule loading. The prepared bioelectrode (Urs-GLDH/ZnO/Pt/Si) showed excellent performance in detecting urea with a high sensitivity of 41 μ AmM −1 cm −2 over a wide range of urea concentrations (5–200 mg dl −1 or 0.83–33.33 mM). The urea sensor also exhibited a low limit of detection (LOD) of 1.82 mg dl −1 , a high shelf life lasting for 12 weeks, and superior selectivity. Thus, the present study not only aims at enhancing our understanding of the fundamental properties of ZnO thin films and their relation to processing conditions, but also emphasises their potential for enhanced biosensing applications.

The intricate interdependence shared between humans and plants spans across a diverse spectrum of plant categories, encompassing those that bear fruits, offer medicinal properties, and yield valuable products. The undeniable reliance we place upon these plants for our growth, sustenance, and holistic well-being underscores their fundamental importance. The presence of plants and trees in our surroundings is not just an aesthetic element, but a cornerstone of our lives that confers numerous advantages. In their pursuit, the authors have devised a two-phased study. The initial phase is dedicated to the identification of noteworthy and significant medicinal/aromatic plants through the application of machine learning methodologies. The goal is to proactively fortify these plants against potential diseases by deploying sophisticated modeling techniques. In the subsequent phase, the authors are dedicated to instituting a mechanism for the early detection of contagious ailments that jeopardize the aforementioned plant species. Through the implementation of such an AI based disese prediction model, the authors aim to limit the harm sustained by these plants, thus mitigating the scarcity of these vital species and kindred vegetation.

To be effective, evidence-driven disaster risk management (DRM) relies on a wide variety of data types, information sources, and models. Weather modeling, the rupture of earthquake fault lines, and the creation of dynamic urban exposure measures all require extensive data collection from a variety of sources in addition to complex science. There are various methodologies to utilize AI to recognize necessities and asset accessibility by the likes of Twitter; however, the foremost broadly recognized and exact strategies remain cloudy. Within the occurrence of a catastrophe, machine learning apparatuses for designating assets are required to instantly help those in need. This overview appears to be necessary for additional examination with respect to an assertion on endorsed methods for calculation to demonstrate assurance, benchmarking datasets, crisis word references, word embedding techniques, and evaluation methods. As fiascos of all sorts become more common, these devices have the potential to improve real-time crisis administration over all stages of a catastrophe. This study aims to provide readers, including data scientists, with a clear and uncomplicated reference on how disaster risk management systems can benefit from machine learning. There are numerous sources of information on this set of technologies, which are both complicated and constantly changing. The volume of sensor data that can be analyzed has increased exponentially because of enormous increases in computational speed and capacity over the past few decades.

Augmented Reality interfaces have been extensively researched throughout the past few decades, with many user studies being conducted. This paper examines the landscape of research on augmented reality. We summarise the overall contribution of each field and will then present examples of influential user studies. We identify other areas of research that would be advantageous to possible future studies. There is a trend toward hands-free applications and most user testing is carried out in the laboratory. This research will also help researchers learning the best practices when conducting AR user studies.

The most important limiting variables for agricultural output are abiotic stresses. Microorganisms, the most common residents of a wide range of habitats, have incredible metabolic skills that help them to cope up with abiotic challenges. Microbial interactions with plants are complex, crucial and dynamic process that influence local and systemic mechanisms in plants to provide defence against harsh external conditions because they are intrinsic part of the living ecosystem. At the same time, we need to have a better insights of plant responses to abiotic stresses as well as plant-microbe interactions that mitigate the effect of abiotic stress. The plant-microbe interaction is more sustainable, long term alternative and also a practical approach for feeding the world’s population with limited resources and minimal impact on environmental health. This paper outlines plant responses to abiotic stresses in terms of biochemical and molecular pathways and also highlight the phenomena of microbe-mediated stress reduction.

Aim & background: Drugs with multiple bioactive moieties have the advantages of multiple modes of action and fewer chances of drug resistance. In continuation of our previous work of developing hybrid antimalarials, we present herein the synthesis and antimalarial activity of two different series of 7-chloroquinoline-sulfonamide hybrids. Materials & methods: The first series of compounds were synthesized by using p-dodecylbenzenesulfonic acid as a Bronsted acid catalyst in ethanol. The second series' compounds were synthesized by 1,3-dipolar cycloaddition of azides and alkynes under click reaction conditions. Results & conclusion: The majority of these compounds demonstrated noncytotoxicity and significant antimalarial activity against Plasmodium falciparum (3D7) with IC50 values in the range of 1.49-13.49 μM. The most promising hybrids (12d, 13a and 13c) may be good starting points for next-generation antimalarials.

Agriculture sustains the livelihoods of over 2.5 billion people worldwide. The growing nature of disasters, the systemic nature of risk, a more recent pandemic along with abiotic stress factors are endangering our entire food system. In these stressful environment, it is widely reprimanded that strategies should be encompassed to attain increased crop yield and economic returns which would alleviate food and nutritional scarcity in developing countries. To study the physiological responses to salt stress, Vigna radiata seedlings subjected to varying levels of salt stress (0, 25, 50, 100 and 200 mM NaCl) were evaluated by tracking changes in Chl a fluorescence, pigment content, free proline and carotenoids content by HPLC. The ability of plants to adapt to salt stress is related with the plasticity and resilience of photosynthesis. As salt concentration increased, chlorophyll fluorescence indices decreased and a reduction in the PSII linear electron transport rate was observed. Chlorophyll fluorescence parameters can be used for in vitro non-invasive monitoring of plants responses to salt stress. Overall, Vigna responded to salt stress by the changes in avoidance mechanism and protective systems. Chl fluorescence indices, enzymatic contents of POD, CAT and free proline were sensitive to salt stress. The study is significant to evaluate the tolerance mechanisms of plants to salt stress and may develop insights for breeding new salt-tolerant varieties.

Blockchain technology provides a secure and decentralized nature. The existing library management system are completely centralized, i.e., based on a central database solely. This means that in case the database crashes or maybe attacked by some intruder, the data stored in it will be at risk. To conquer, this we are proposing a blockchain-based decentralized and secure library management system. Not only this cover the book owning organization but also this can be implemented to propose a system where any person owning a book can give his book to someone who is in need. The addition of new book owner and new book borrower will be managed by verification at different nodes, hence providing it a secure and authenticated way. We have implemented it in python with the help of its advanced libraries ( https://manavrachna.edu.in ).

A systematic measurement of outdoor gamma radiations in Panchkula district of Haryana, India, was done using a radiation monitor based on Geiger–Muller technique. The gamma dose rate was found to be in the range from 70.0 ± 3.5 to 168.0 ± 8.4 nSv/h. The annual effective dose (AED) due to the outdoor gamma radiation in Panchkula district was computed to range from 0.086 ± 0.004 to 0.206 ± 0.010 mSv/year. The value of excess lifetime cancer risk (ELCR) was found to be in the range from 0.322 × 10–3 to 0.773 × 10–3.