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In the recent era of the Internet of Things, the dominant role of sensors and the Internet provides a solution to a wide variety of real-life problems. Such applications include smart city, smart healthcare systems, smart building, smart transport and smart environment. However, the real-time IoT sensor data include several challenges, such as a deluge of unclean sensor data and a high resource-consumption cost. As such, this paper addresses how to process IoT sensor data, fusion with other data sources, and analyses to produce knowledgeable insight into hidden data patterns for rapid decision-making. This paper addresses the data processing techniques such as data denoising, data outlier detection, missing data imputation and data aggregation. Further, it elaborates on the necessity of data fusion and various data fusion methods such as direct fusion, associated feature extraction, and identity declaration data fusion. This paper also aims to address data analysis integration with emerging technologies, such as cloud computing, fog computing and edge computing, towards various challenges in IoT sensor network and sensor data analysis. In summary, this paper is the first of its kind to present a complete overview of IoT sensor data processing, fusion and analysis techniques.

Aerobic living is thought to generate reactive oxygen species (ROS), which are an inevitable chemical component. They are produced exclusively in cellular compartments in aerobic metabolism involving significant energy transfer and are regarded as by-products. ROS have a significant role in plant response to pathogenic stress, but the pattern varies between necrotrophs and biotrophs. A fine-tuned systemic induction system is involved in ROS-mediated disease development in plants. In regulated concentrations, ROS act as a signaling molecule and activate different pathways to suppress the pathogens. However, an excess of these ROS is deleterious to the plant system. Along with altering cell structure, ROS cause a variety of physiological reactions in plants that lower plant yield. ROS also degrade proteins, enzymes, nucleic acids, and other substances. Plants have their own mechanisms to overcome excess ROS and maintain homeostasis. Microbes, especially endophytes, have been reported to maintain ROS homeostasis in both biotic and abiotic stresses by multiple mechanisms. Endophytes themselves produce antioxidant compounds and also induce host plant machinery to supplement ROS scavenging. The structured reviews on how endophytes play a role in ROS homeostasis under biotic stress were very meager, so an attempt was made to compile the recent developments in ROS homeostasis using endophytes. This review deals with ROS production, mechanisms involved in ROS signaling, host plant mechanisms in alleviating oxidative stress, and the roles of endophytes in maintaining ROS homeostasis under biotic stress.

Cancer is one of the major healthcare challenges across the globe. Several anticancer drugs are available on the market but they either lack specificity or have poor safety, severe side effects, and suffer from resistance. So, there is a dire need to develop safer and target-specific anticancer drugs. More than 85% of all physiologically active pharmaceuticals are heterocycles or contain at least one heteroatom. Nitrogen heterocycles constituting the most common heterocyclic framework. In this study, we have compiled the FDA approved heterocyclic drugs with nitrogen atoms and their pharmacological properties. Moreover, we have reported nitrogen containing heterocycles, including pyrimidine, quinolone, carbazole, pyridine, imidazole, benzimidazole, triazole, β-lactam, indole, pyrazole, quinazoline, quinoxaline, isatin, pyrrolo-benzodiazepines, and pyrido[2,3-d]pyrimidines, which are used in the treatment of different types of cancer, concurrently covering the biochemical mechanisms of action and cellular targets.

Cancer is a complex disease, and its treatment is a big challenge, with variable efficacy of conventional anticancer drugs. A two-drug cocktail hybrid approach is a potential strategy in recent drug discovery that involves the combination of two drug pharmacophores into a single molecule. The hybrid molecule acts through distinct modes of action on several targets at a given time with more efficacy and less susceptibility to resistance. Thus, there is a huge scope for using hybrid compounds to tackle the present difficulties in cancer medicine. Recent work has applied this technique to uncover some interesting molecules with substantial anticancer properties. In this study, we report data on numerous promising hybrid anti-proliferative/anti-tumor agents developed over the previous 10 years (2011–2021). It includes quinazoline, indole, carbazole, pyrimidine, quinoline, quinone, imidazole, selenium, platinum, hydroxamic acid, ferrocene, curcumin, triazole, benzimidazole, isatin, pyrrolo benzodiazepine (PBD), chalcone, coumarin, nitrogen mustard, pyrazole, and pyridine-based anticancer hybrids produced via molecular hybridization techniques. Overall, this review offers a clear indication of the potential benefits of merging pharmacophoric subunits from multiple different known chemical prototypes to produce more potent and precise hybrid compounds. This provides valuable knowledge for researchers working on complex diseases such as cancer.

The increasing adoption of Internet of Things (IoT) devices in smart healthcare systems has revolutionized real-time data collection and processing, substantially improving healthcare delivery and operational efficiency. However, the sensitivity of medical data and the resource limitations of IoT devices demand blockchain solutions that are secure, lightweight, and scalable. This paper presents two core contributions: (1) Resource Efficiency-Driven Consensus (REDC), a machine learning–enhanced consensus protocol tailored for healthcare IoT networks, and (2) Dynamic Lightweight Hashing (DLH), a cryptographic algorithm designed for energy-constrained environments. REDC achieves up to 70% higher throughput, 43% Energy Efficiency (EE), and 25% lower latency compared to Proof of Elapsed Work and Luck (PoEWAL) in networks up to 100 nodes. DLH further enhances performance by reducing hash attempts and energy use while maintaining strong collision resistance across 100,000 trials. Together, REDC and DLH form a scalable and secure blockchain framework tailored for healthcare IoT.

Climate change is a critical yield–limiting factor that has threatened the entire global crop production system in the present scenario. The use of biostimulants in agriculture has shown tremendous potential in combating climate change–induced stresses such as drought, salinity, temperature stress, etc. Biostimulants are organic compounds, microbes, or amalgamation of both that could regulate plant growth behavior through molecular alteration and physiological, biochemical, and anatomical modulations. Their nature is diverse due to the varying composition of bioactive compounds, and they function through various modes of action. To generate a successful biostimulatory action on crops under different parameters, a multi– omics approach would be beneficial to identify or predict its outcome comprehensively. The ‘ omics’ approach has greatly helped us to understand the mode of action of biostimulants on plants at cellular levels. Biostimulants acting as a messenger in signal transduction resembling phytohormones and other chemical compounds and their cross–talk in various abiotic stresses help us design future crop management under changing climate, thus, sustaining food security with finite natural resources. This review article elucidates the strategic potential and prospects of biostimulants in mitigating the adverse impacts of harsh environmental conditions on plants.

In the present study, ten (10) selected bacteria isolated from chasmophytic wild Chenopodium were evaluated for alleviation of drought stress in chickpea. All the bacterial cultures were potential P, K and Zn solubilizer. About 50% of the bacteria could produce Indole-3-acetic acid (IAA) and 1-aminocyclopropane-1-carboxylate (ACC) deaminase. The bacteria showed wide range of tolerance towards pH, salinity, temperature and osmotic stress. Bacillus paralicheniformis L38, Pseudomonas sp. LN75, Enterobacter hormachei subsp. xiangfengensis LJ89, B. paramycoides L17 and Micrococcus luteus LA9 significantly improved growth and nutrient (N, P, K, Fe and Zn) content in chickpea under water stress during a green house experiment conducted following a completely randomized design (CRD). Application of Microbacterium imperiale LJ10, B. stercoris LN74, Pseudomonas sp. LN75, B. paralicheniformis L38 and E. hormachei subsp. xiangfengensis LJ89 reduced the antioxidant enzymes under water stress. During field experiments conducted following randomized block design (RBD), all the bacterial inoculations improved chickpea yield under water stress. Highest yield (1363 kg ha −1 ) was obtained in plants inoculated with Pseudomonas sp. LN75. Pseudomonas sp. LN75, B. paralicheniformis L38 and E. hormachei subsp. xiangfengensis LJ89 have potential as microbial stimulants to alleviate the water stress in chickpea. To the best of our knowledge this is the first report of using chasmophyte associated bacteria for alleviation of water stress in a crop plant.

The unpredictable nature of our world can introduce a variety of errors in our actions, including sensory prediction errors (SPEs) and task performance errors (TPEs). SPEs arise when our existing internal models of limb-environment properties and interactions become miscalibrated due to changes in the environment, while TPEs occur when environmental perturbations hinder achievement of task goals. The precise mechanisms employed by the sensorimotor system to learn from such limb- and task-related errors and improve future performance are not comprehensively understood. To gain insight into these mechanisms, we performed a series of learning experiments wherein the location and size of a reach target were varied, the visual feedback of the motion was perturbed in different ways, and instructions were carefully manipulated. Our findings indicate that the mechanisms employed to compensate SPEs and TPEs are dissociable. Specifically, our results fail to support theories that suggest that TPEs trigger implicit refinement of reach plans or that their occurrence automatically modulates SPE-mediated learning. Rather, TPEs drive improved action selection, that is, the selection of verbally sensitive, volitional strategies that reduce future errors. Moreover, we find that exposure to SPEs is necessary and sufficient to trigger implicit recalibration. When SPE-mediated implicit learning and TPE-driven improved action selection combine, performance gains are larger. However, when actions are always successful and strategies are not employed, refinement in behavior is smaller. Flexibly weighting strategic action selection and implicit recalibration could thus be a way of controlling how much, and how quickly, we learn from errors.

Background Fluorosis caused by excess intake of fluoride can affects various soft tissues of the body, such as the gastrointestinal tract, blood, brain tissues and thyroid gland apart from dental fluorosis and skeletal fluorosis. Nonskeletal fluorosis is considered reversible if diagnosed early and treated promptly. Therefore, diagnostic methods that can be easily performed even by primary health care workers and depict any ongoing health problems, should be validated. Dental fluorosis, assessment of fluoride in urine and water are tests that fulfill these requirements. To date, no study has correlated haemoglobin (Hb) with dental fluorosis; moreover, studies focusing on intelligence quotient (IQ) had conflicting results and need further research. Hence, study was conducted to determine any relationship among different fluoride assessment parameters (severity of dental fluorosis, fluoride level in urine and drinking water) with IQ status and hemoglobin level of children aged 8–12 years, affected with or without dental fluorosis. Methods A total of 300 children aged 8–12 years were evaluated for dental fluorosis via Dean’s index, IQ level via Raven’s coloured progressive matrices test, Hb level, and fluoride content in water and urine. Results Water fluoride, age and gender were significantly associated with Hb. Intelligence was significantly related to urinary fluoride levels. Presence or absence of dental fluorosis and its severity were not significantly related to IQ or Hb. Conclusions Excess fluoride intake has adverse effects on hematological parameters and children’s cognitive neurodevelopment, which were evaluated by current fluoride exposure markers, i.e., water and urinary fluoride. However, dental fluorosis cannot be used as a definitive assessment marker for these conditions, as it is not significantly correlated with these conditions.