Peptide-Directed Synthesis of Aggregation-Induced Emission Enhancement-Active Gold Nanoclusters for Single- and Two-Photon Imaging of Lysosome and Expressed αvß3 Integrin Receptors.

This study explores the synthesis and characterization of aggregation-induced emission enhancement (AIEE)-active gold nanoclusters (AuNCs), focusing on their near-infrared luminescence properties and potential applications in biological imaging. These AIEE-active AuNCs were synthesized via the NaBH4-mediated reduction of HAuCl4 in the presence of peptides. We systematically investigated the influence of the peptide sequence on the optical features of the AuNCs, highlighting the role of glutamic acid in enhancing their quantum yield (QY). Among the synthesized peptide-stabilized AuNCs, EECEE-stabilized AuNCs exhibited the maximum QY and a pronounced AIEE effect at pH 5.0, making them suitable for the luminescence imaging of intracellular lysosomes. The AIEE characteristic of the EECEE-stabilized AuNCs was demonstrated through examinations using transmission electron microscopy, dynamic light scattering, zeta potential analysis, and single-particle imaging. The formation of the EECEE-stabilized AuNCs was confirmed by size-exclusion chromatography and mass spectrometry. Spectroscopic and electrochemical examinations uncover the formation process of EECEE-stabilized AuNCs, comprising EECEE-mediated reduction, NaBH4-induced nucleation, complex aggregation, and subsequent cluster growth. Furthermore, we demonstrated the utility of these AuNCs as luminescent probes for intracellular lysosomal imaging, leveraging their pH-responsive AIEE behavior. Additionally, cyclic arginylglycylaspartic acid (RGD)-modified AIEE dots, derived from cyclic RGD-linked peptide-induced aggregation of EECEE-stabilized AuNCs, were developed for single- and two-photon luminescence imaging of αvß3 integrin receptor-positive cancer cells.

Baryon Electric Charge Correlation as a Magnetometer of QCD.

The correlation between net baryon number and electric charge, χ_{11}^{BQ}, can serve as a magnetometer of QCD. This is demonstrated by lattice QCD computations using the highly improved staggered quarks with physical pion mass of M_{π}=135 MeV on N_{τ}=8 and 12 lattices. We find that χ_{11}^{BQ} along the transition line starts to increase rapidly with magnetic field strength eB≳2M_{π}^{2} and by a factor 2 at eB≃8M_{π}^{2}. Furthermore, the ratio of electric charge chemical potential to baryon chemical potential, µ_{Q}/µ_{B}, shows significant dependence on the magnetic field strength and varies from the ratio of electric charge to baryon number in the colliding nuclei in heavy ion collisions. These results can provide baselines for effective theory and model studies, and both χ_{11}^{BQ} and µ_{Q}/µ_{B} could be useful probes for the detection of magnetic fields in relativistic heavy ion collision experiments as compared with corresponding results from the hadron resonance gas model.

Genetic insights of antibiotic resistance, pathogenicity (virulence) and phylogenetic relationship of Escherichia coli strains isolated from livestock, poultry and their handlers - a one health snapshot.

BACKGROUND: Pathogenic and non-pathogenic strains of Escherichia coli harbouring antibiotic resistance genes (ARGs) from any source (clinical samples, animal settings, or environment) might be transmitted and contribute to the spread and increase of antibiotic resistance in the biosphere. The goal of this study was to investigate the genome to decipher the repertoire of ARGs, virulence genes carried by E. coli strains isolated from livestock, poultry, and their handlers (humans), and then unveil the genetic relatedness between the strains. METHODS: Whole genome sequencing was done to investigate the genetic makeup of E. coli isolates (n = 20) [swine (n = 2), cattle (n = 2), sheep (n = 4), poultry (n = 7), and animal handlers (n = 5)] from southern India. The detection of resistome, virulome, biofilm forming genes, mobile genetic elements (MGE), followed by multilocus sequence typing (MLST) and phylogenetic analyses, were performed. RESULTS: E. coli strains were found to be multi drug resistant, with a resistome encompassing > 20 ARGs, the virulome-17-22 genes, and > 20 key biofilm genes. MGE analysis showed four E. coli isolates (host: poultry, swine and cattle) harbouring composite transposons with ARGs/virulence genes (blaTEM, dfr, qnr/nleB, tir, eae,and esp) with the potential for horizontal transfer. MLST analyses revealed the presence of ST937 and ST3107 in both livestock/poultry and their handlers. Phylogenomic analyses with global E. coli isolates (human/livestock/poultry hosts) showed close relatedness with strains originating from different parts of the world (the United States, China, etc.). CONCLUSION: The current study emphasizes the circulation of strains of pathogenic sequence types of clinical importance, carrying a diverse repertoire of genes associated with antibiotic resistance, biofilm formation and virulence properties in animal settings, necessitating immediate mitigation measures to reduce the risk of spread across the biosphere.

Association of Pharmacist Interventions With Adverse Drug Events and Potential Adverse Drug Events.

BACKGROUND: Adverse drug events (ADEs) are a frequent cause of injury in patients. Our aim was to assess whether pharmacist interventions compared with no pharmacist intervention results in reduced ADEs and potential adverse drug events (PADEs). METHODS: We searched MEDLINE, Embase, and two other databases through September 19, 2022 for any RCT assessing the effect of a pharmacist intervention compared with no pharmacist intervention and reporting on ADEs or PADEs. The risk of bias was assessed using the Cochrane tool for RCTs. A random-effects model was used to pool summary results from individual RCTs. RESULTS: Fifteen RCTs met the inclusion criteria. The pooled results showed a statistically significant reduction in ADE associated with pharmacist intervention compared with no pharmacist intervention (RR = 0.86; [95% CI 0.80-0.94]; p = 0.0005) but not for PADEs (RR = 0.79; [95% CI 0.47-1.32]; p = 0.37). The heterogeneity was insignificant (I2 = 0%) for ADEs and substantial (I2 = 77%) for PADEs. Patients receiving a pharmacist intervention were 14% less likely for ADE than those who did not receive a pharmacist intervention. The estimated number of patients needed to prevent one ADE across all patient locations was 33. CONCLUSIONS: To our knowledge, this is the first systematic review and meta-analysis of RCTs seeking to understand the association of pharmacist interventions with ADEs and PADEs. The risk of having an ADE is reduced by a seventh for patients receiving a pharmacist care intervention versus no such intervention. The estimated number of patients needed to be followed across all patient locations to prevent one preventable ADE across all patient locations is 33.

Knowledge, attitude, and practice of breast self-examination is associated with general self-care and cultural factors: a study from Tamil Nadu, India.

AIM: Breast cancer is the most prevalent type of cancer among women. One form of care related to early detection of breast cancer is breast self-examination (BSE). However, evidence on knowledge, attitude, and practice (KAP) of BSE and its determining factors are minuscule in an Indian context. Therefore, the present study primarily examined the prevalence of KAP of BSE. Further, its association with general self-care and cultural factors was determined. METHODS: This cross-sectional study obtained data from 412 women (Mn age = 26.63) from two rural localities of Vellore district, Tamil Nadu, India. Self-reported questionnaires of KAP of BSE, self-care, and cultural factors were applied. Statistical analyses include independent sample t-test and binomial logistic regression. RESULTS: The majority of the sample had inadequate knowledge (58%), unfavourable attitudes (73.8%), and poor practice (89.6%) of BSE. The general self-care among the sample was moderate. Self-care was found to be a significant predictor of knowledge (b = 0.07, p < .05) and attitude (b = 0.092, p < .05) toward BSE. Shyness was identified as a negative predictor of KAP. Discouraged breast health discussions predicted inadequate knowledge, and not being educated by family/friends had a negative impact on knowledge and practice. A preference for same-gender physicians led to an unfavourable attitude toward BSE. CONCLUSION: The observed negative trends in KAP of BSE are concerning. The results imply that girls and women should be educated and encouraged to practice BSE and promote self-care behaviours. At the same time, efforts to reduce cultural barriers may be helpful to promote the KAP of BSE.

Improving safety: neuraxial blockade guided by thromboelastography for patients with uncertain coagulation profile.

ABSTRACT: Neuraxial blockade procedures are essential for anesthesia and pain management but pose risks in patients with uncertain coagulation profiles. Traditional coagulation tests often fail to predict bleeding risks associated with neuraxial blockade. Thromboelastography (TEG) offers real-time insights into coagulation status, potentially improving safety outcomes. In this case series, six patients underwent neuraxial blockade guided by TEG analysis.An individualized anesthetic plan was formulated based on TEG findings to mitigate bleeding risks while ensuring pain management. Tailoring anesthetic techniques to real-time TEG data improved safety outcomes with minimized bleeding complications and satisfactory pain control. In conclusion, neuraxial blockade guided by TEG enhances safety in patients with uncertain coagulation profiles. Further studies are needed to validate benefits in broader clinical settings.

Life cycle GHG emissions assessment of vanadium recovery from bitumen-derived petcoke fly ash.

Petcoke generated during bitumen upgrading is a potential source of vanadium for the global market. Recovering vanadium from the fly ash originating from the combustion of petcoke appears to be a suitable route for commercial implementation, given its high extraction rate. Although the technical feasibility of the recovery process has been proven, the environmental impact should be addressed. Information on the greenhouse (GHG) emissions from the process is scarce in the public domain. Therefore, a framework was developed for assessment of life cycle GHG emissions for extraction of vanadium from petcoke-based fly ash. This framework was used to perform a life cycle GHG emissions assessment of a water leaching and salt roasting process to extract vanadium from fly ash. For the upstream GHG emissions, we collected direct emissions data and energy consumption from the literature, and, for the process emissions, we developed a model to estimate energy and material balances based on process conditions. The emission factors for electricity production, fuel combustion, production of consumables, and gas treatment were used to obtain the life cycle GHG emissions. The results show that the life cycle GHG emission of vanadium recovery are 26.6-3.9+0.9 kg CO2eq/kg V2O5; 66% of these are direct GHG emissions. The process GHG emissions from fly ash decarbonization contribute the most to the life cycle GHG emissions. The air-to-fuel ratio for roasting and the GHG emission factors for petcoke combustion and the gas treatment operation are the inputs that most effect the model output. Compared with the production of V2O5 from vanadium titano-magnetite ore and bitumen upgrading spent catalyst, the petcoke fly ash pathway generates about twice the life cycle GHG emissions. This study's results can help determine areas of improvement in the upstream operations and the recovery process to reduce the life cycle GHG emissions to levels that can compete with primary and alternative routes to produce vanadium pentoxide. The results of this study can help in decision-making associated with vanadium extract from fly ash produced from combustion of petcoke.

Efficient synthesis of 3D ZnO nanostructures on ITO surfaces for enhanced photoelectrochemical water splitting.

New photoactive materials with uniform and well-defined morphologies were developed for efficient and sustainable photoelectrochemical (PEC) water splitting and hydrogen production. The investigation is focused on hydrothermal deposition of zinc oxide (ZnO) onto indium tin oxide (ITO) conductive surfaces and optimization of hydrothermal temperature for growing uniform sized 3D ZnO morphologies. Fine-tuning of hydrothermal temperature enhanced the scalability, efficiency, and performance of ZnO-decorated ITO electrodes used in PEC water splitting. Under UV light irradiation and using eco-friendly low-cost hydrothermal process in the presence of stable ZnO offered uniform 3D ZnO, which exhibited a high photocurrent of 0.6 mA/cm2 having stability up to 5 h under light-on and light-off conditions. The impact of hydrothermal temperature on the morphological properties of the deposited ZnO and its subsequent performance in PEC water splitting was investigated. The work contributes to advancement of scalable and efficient fabrication technique for developing energy converting photoactive materials.

Subtle membrane changes in cryopreserved bull spermatozoa when modified temperature drop rates are used during the first phase of freezing.

BACKGROUND: Cryopreservation of spermatozoa involves reduction of temperature to a subzero level, leading to increased longevity. However, temperature reduction has a significant effect on sperm membranes. OBJECTIVE: To evaluate the impact of the rate of temperature drop during the first phase of freezing on subtle membrane changes in cryopreserved bull spermatozoa. MATERIALS AND METHODS: Thirty-two ejaculates from four bulls (eight ejaculates/bull) were collected using artificial vagina while keeping a 3 to 4 days gap between two collections. Diluted semen samples were equilibrated at 5 degree C for 4 hours. The samples were then placed in a pre-programmed semen freezer. The first phase of freezing, that is, 5 degree C till -10 degree C was subjected to three different temperature drop rates: accelerated (F1), moderate (F2), and slow (F3), at 20 degree C per min, 10 degree C per min and 5 degree C per min, respectively. After thawing, spermatozoa were assessed for percentage live, plasma, and acrosomal membrane integrity, along with the external appearance of phosphatidyl serine, indicating apoptosis. RESULTS: A significant difference (p < 0.05) in viability, plasma membrane integrity (HOS test), and acrosome membrane integrity (PSA test) was observed between F3 and the other groups. However, the parameters did not significantly differ between F1 and F2. The annexin V-PI assay (AN/PI) categorized four types of sperm populations: non-apoptotic and viable (AN-/PI-), apoptotic and viable (AN+/PI-), non-apoptotic and non-viable (AN-/PI+), and apoptotic and non-viable (AN+/PI+). The proportion of spermatozoa with (AN-/PI-) and (AN+/PI+) differed significantly (p < 0.05) between F3 and the other groups. The values for apoptotic and viable (AN+/PI-) and non-apoptotic and non-viable (AN-/PI+) sperm were not significantly different among all freezing categories. CONCLUSION: A slower temperature drop rate (freezing rate) during the first phase of freezing results in less damaging, subtle membrane changes. Doi.org/10.54680/fr24410110312.

Rice-based integrated farming system improves the soil quality, bacterial community structure and system productivity under sub-humid tropical condition.

Rice-based integrated farming system improves the productivity and profitability by recycling resources efficiently. In the sub-humid tropics, rice production without sufficient nutrient replenishment often leads to soil health and fertility degradation. There has been very limited research on soil health and fertility after adopting a multi-enterprising rice-based integrated farming system (IFS), notably in the rice-fish-livestock and agroforestry system, when compared to a conventional farming system (CS). Therefore, the present study analyzed the dynamics of soil properties, soil bacterial community structure and their possible interaction mechanisms, as well as their effect on regulating soil quality and production in IFS, IFSw (water stagnant area of IFS) and CS. The results indicated that soil nutrient dynamics, bacterial diversity indices (Shannon index, Simpson index, Chao 1, ACE and Fisher index) and system productivity were higher in IFSw and IFS compared to CS. Moreover, relative operational taxonomic units of dominant bacterial genera (Chloroflexi, Acidobacteria, Verrucomicrobia, Planctomycetes, Cyanobacteria, Crenarchaeota and Gemmatimonadetes) were also higher in IFSw and IFS compared to CS. Mean soil quality index (SQI) was highest in IFSw (0.780 ± 0.201) followed by IFS (0.770 ± 0.080) and CS (0.595 ± 0.244). Moreover, rice equivalent yields (REY) and rice yields were well correlated with the higher levels of soil biological indices (SQIBiol) in IFS. Overall, our results revealed that rice-based IFS improved the soil health and fertility and ensuing crop productivity through positive interaction with soil bacterial communities and nutrient stoichiometry leading to agroecosystem sustainability.

Associations between neighbourhood safety, social cohesion, sleep quality and sleep duration among older adults in India: Findings from the Study on Global Aging and Adult Health (WHO-SAGE), 2015.

BACKGROUND: Most studies on later-life health in India focus on families, with far less attention given to the health repercussions of neighbourhood conditions among older Indians. We address this limitation in existing research by examining the associations between perceptions of neighbourhood safety and social cohesion and sleep duration and sleep quality among older adults in India. METHODS: Data come from the Study on Global Aging and Adult Health (WHO-SAGE), India 2015 wave 2, with a sample of 7118 adults aged 50 years and above. Sleep quality and duration were assessed using subjective responses. Multivariable logistic and linear regression analyses were employed to test the research hypotheses. RESULTS: Prevalence of poor sleep quality was higher among older adults living in unsafe neighbourhoods (4.46%) than peers residing in safe neighbourhoods (3.52%), and it was also higher among those living in neighbourhoods with poor social cohesion (5.31%) than counterparts who lived in socially cohesive communities (3.10%). Older adults in neighbourhoods with poor social cohesion had higher odds of reporting compromised sleep quality (adjusted odds ratio 1.75, CI: 1.22-2.51) than those living in socially cohesive neighbourhoods. Moreover, compared to those who perceived they were living in safe neighbourhoods, their peers who perceived their neighbourhoods as unsafe reported shorter sleep duration, with a negative beta coefficient of -0.27 (CI: -0.45 to -0.085). CONCLUSION: That perceived unsafety and poor social cohesion within one's neighbourhood are associated with compromised sleep reflects the significance of making neighbourhoods safer and more integrated for later-life sleep health. In addition to micro-level strategies (e.g., balanced nutrition and physical activity), efforts to improve sleep health should optimise macro-level opportunities, such as rehabilitating and revitalising neighbourhoods, which may alleviate sleep disturbances and improve sleep outcomes among older adults.

Danger Down Under: A Pediatric Case of Penile Trauma with a Saw.

Partial penile amputation in the pediatric age group is an emergency and occurs mainly due to iatrogenic trauma or road traffic accidents. Such lesions are incapacitating and have a devastating psychological impact. We present the case of a 16-year-old boy who presented with an accidental, near-total penile amputation, and highlight our management plan as a favorable one.

PAEDIATRIC SYMPTOMATIC SEIZURES IN INDIA: UNRAVELLING VARIED ETIOLOGIES AND NEUROIMAGING PATTERNS - A MULTICENTRIC STUDY.

Pediatric neuroimaging presents a unique set of challenges, primarily stemming from the intricacies of normal myelination processes occurring within the initial two years of life. This complexity is particularly pronounced in the context of pediatric epilepsy, where a substantial proportion of neuroimaging cases appears normal, especially in instances of idiopathic or provoked seizures. Nevertheless, abnormalities in neuroimaging tend to manifest in cases of acute or remote symptomatic seizures. Notably, the etiological landscape of seizures in children diverges significantly from that observed in adults, with neurodevelopmental, neurometabolic, and neuro-infectious factors emerging as predominant contributors. This multicentric study, conducted between November 2021 and November 2023, spanned diverse hospitals across various states in India. Encompassing children from birth to 12 years of age experiencing acute and remote symptomatic seizures, the study meticulously documented clinical and demographic profiles. Exclusion criteria were applied, excluding typical febrile seizures and idiopathic epilepsy syndromes to ensure a focused analysis. The study encompassed a total of 109 cases, revealing a spectrum of neuroimaging findings. Noteworthy among these were cortical malformations, including focal cortical dysplasia (12 cases), tuberous sclerosis (6 cases), polymicrogyria (3 cases), hemimegalencephaly (1 case), lissencephaly (1 case), schizencephaly (2 cases), heterotopias (3 cases), cavernous hemangioma (1 case), and AV malformation (1 case). Additionally, neoplastic lesions (6 cases), neurocysticercosis (5 cases), tuberculoma (4 cases), hippocampal sclerosis (3 cases), post-hypoxic and cerebrovascular accident gliosis (3 cases), leukodystrophies (2 cases), and non-lesional cases (58 cases) were documented. Pediatric neuroimaging in symptomatic seizures may present with normal findings, influenced by interpreter bias and the non-uniform availability of 3T MRI across different medical centers. The diverse causative factors for symptomatic seizures underscore the impact of demographic features, including the endemicity of specific infections and birth injuries, on the observed variability across medical centers. These findings underscore the imperative for a comprehensive understanding and standardization in pediatric neuroimaging practices.

Multiple ocean parameter-based potential fishing zone (PFZ) location generation and validation in the Western Bay of Bengal.

A new conceptual framework based on satellite data, including chlorophyll (CHL), sea surface temperature (SST) fronts, relative winds, current vectors, Ekman transport, and eddies, has been developed to identify potential fishing zones (PFZ) in the Bay of Bengal (BoB). The framework aims to provide persistent forecasts, even under cloudy conditions, based on feature propagation. The validation of the PFZ was carried out using fish catch data collected by the Fishery Survey of India (FSI) between 2016 and 2018. Hooking rates (HR) from longlines and catch per unit effort (CPUE) from trawl nets were used to analyse the data points in hook rate categories (1.0-3.0 and > 3.0) and CPUE categories (50-100 kg and > 100 kg) and interpret them with the PFZ maps. The analysis showed that the high fish catch locations were consistent with persisting features in the BoB, such as high chlorophyll patches, SST fronts, and cyclonic eddies. The high fish catch locations based on hook rate and high CPUE were found to be collocated with the high chlorophyll persisting features and thermal gradients in the BoB. The regression analysis shows that availability of the food (CHL) had the strongest correlation with fish catch, followed by the comfort condition (fronts and eddies).

EMERGING NATIONS' LEARNING SYSTEMS AND THE COVID-19 PANDEMIC: AN ANALYSIS.

National learning systems improve training and proficiency. In order to support education during the COVID-19 epidemic, the rate of online and remote learning accelerated. Since there were some available technologies, strong, flexible educational infrastructures were required to accommodate a range of student demands. Digital resources and inclusive education need government investment. This study highlights the vital role that adaptable educational frameworks play in lessening the effects of the crisis and fostering resilience in the face of uncertainty by examining the complex relationship between the COVID-19 pandemic and the creation of national education methodologies. This study offers a detailed analysis of the intricacy, challenges, and opportunities that have emerged in this significant field by investigating the ways in which the COVID-19 pandemic has affected educational institutions in developing countries. Twenty selected, peer-reviewed scientific journal articles from 2019 to 2023 were included in the research after a comprehensive search of relevant literature. Taking into consideration the viewpoints of parents, children, teachers, and administrators, this extensive and professionally handled research study provides a critical and nuanced examination of many consequences of the COVID-19 epidemic on the educational system. By using a comprehensive analysis of 25 academic articles, it achieves this. A broad number of useful tools and tactics are highlighted in this research, which offers an in-depth analysis of the intricate area of information and computational model deployment. Employing analysis of variance (ANOVA) as a robust statistical method, this analysis uncovers and scrutinizes the complex dynamics at play with the educational systems of developing nations amidst the unprecedented challenges brought by the global COVID-19 crisis. The COVID-19 epidemic has spurred rising countries to rethink and improve their education institutions, accelerating technology-driven education. The epidemic has underlined the need for inclusive and resilient learning infrastructures that respond to emergencies despite the digital device and access inequities.

Comparison of TL characteristics of natural quartz and zircon.

The dosimetry of different minerals is carried out to investigate the dose received by the population in case of a nuclear accident. Retrospective dosimetry is a field where there is a continuous search to find new materials. Beach sand minerals, namely quartz and zircon, were exposed to beta and gamma radiation and studied separately. A comparison of the thermoluminescence (TL) output of different peaks of quartz for beta and gamma was studied. Comparison of quartz peaks with the TL output of zircon peaks was carried out. TL output for a constant dose of gamma is always higher compared to the TL output received due to beta.

Multi-organ segmentation of organ-at-risk (OAR's) of head and neck site using ensemble learning technique.

INTRODUCTION: This paper presents a novel approach to automate the segmentation of Organ-at-Risk (OAR) in Head and Neck cancer patients using Deep Learning models combined with Ensemble Learning techniques. The study aims to improve the accuracy and efficiency of OAR segmentation, essential for radiotherapy treatment planning. METHODS: The dataset comprised computed tomography (CT) scans of 182 patients in DICOM format, obtained from an institutional image bank. Experienced Radiation Oncologists manually segmented seven OARs for each scan. Two models, 3D U-Net and 3D DenseNet-FCN, were trained on reduced CT scans (192 × 192 x 128) due to memory limitations. Ensemble Learning techniques were employed to enhance accuracy and segmentation metrics. Testing was conducted on 78 patients from the institutional dataset and an open-source dataset (TCGA-HNSC and Head-Neck Cetuximab) consisting of 31 patient scans. RESULTS: Using the Ensemble Learning technique, the average dice similarity coefficient for OARs ranged from 0.990 to 0.994, indicating high segmentation accuracy. The 95% Hausdorff distance (mm) ranged from 1.3 to 2.1, demonstrating precise segmentation boundaries. CONCLUSION: The proposed automated segmentation method achieved efficient and accurate OAR segmentation, surpassing human expert performance in terms of time and accuracy. IMPLICATIONS FOR PRACTICE: This approach has implications for improving treatment planning and patient care in radiotherapy. By reducing manual segmentation reliance, the proposed method offers significant time savings and potential improvements in treatment planning efficiency and precision for head and neck cancer patients.

Dynamic task offloading edge-aware optimization framework for enhanced UAV operations on edge computing platform.

Resource optimization, timely data capture, and efficient unmanned aerial vehicle (UAV) operations are of utmost importance for mission success. Latency, bandwidth constraints, and scalability problems are the problems that conventional centralized processing architectures encounter. In addition, optimizing for robust communication between ground stations and UAVs while protecting data privacy and security is a daunting task in and of itself. Employing edge computing infrastructure, artificial intelligence-driven decision-making, and dynamic task offloading mechanisms, this research proposes the dynamic task offloading edge-aware optimization framework (DTOE-AOF) for UAV operations optimization. Edge computing and artificial intelligence (AI) algorithms integrate to decrease latency, increase mission efficiency, and conserve onboard resources. This system dynamically assigns computing duties to edge nodes and UAVs according to proximity, available resources, and the urgency of the tasks. Reduced latency, increased mission efficiency, and onboard resource conservation result from dynamic task offloading edge-aware implementation framework (DTOE-AIF)'s integration of AI algorithms with edge computing. DTOE-AOF is useful in many fields, such as precision agriculture, emergency management, infrastructure inspection, and monitoring. UAVs powered by AI and outfitted with DTOE-AOF can swiftly survey the damage, find survivors, and launch rescue missions. By comparing DTOE-AOF to conventional centralized methods, thorough simulation research confirms that it improves mission efficiency, response time, and resource utilization.

First report on pesticide sub-chronic and chronic toxicities against dogs using QSAR and chemical read-across.

Excessive use of chemicals is the outcome of the industrialization of agricultural sectors which leads to disturbance of ecological balance. Various agrochemicals are widely used in agricultural fields, urban green areas, and to protect from various pest-associated diseases. Due to their long-term health and environmental hazards, chronic toxicity assessment is crucial. Since in vivo and in vitro toxicity assessments are costly, lengthy, and require a large number of animal experiments, in silico toxicity approaches are better alternatives to save time, cost, and animal experimentation. We have developed the first regression-based 2D-QSAR models using different sub-chronic and chronic toxicity data of pesticides against dogs employing 2D descriptors. From the statistical results (ntrain=53-62, r2 = 0.614 to 0.754, QLOO2 = 0.501 to 0.703 and QF12 = 0.531 to 0.718, QF22=0.523-0.713), it was concluded that the models are robust, reliable, interpretable, and predictive. Similarity-based read-across algorithm was also used to improve the predictivity (QF12=0.595-0.813,QF22=0.573-0.809) of the models. 5132 chemicals obtained from the CPDat and 1694 pesticides obtained from the PPDB database were also screened using the developed models, and their predictivity and reliability were checked. Thus, these models will be helpful for eco-toxicological data-gap filling, toxicity prediction of untested pesticides, and development of novel, safer & eco-friendly pesticides.

q-RASTR modelling for prediction of diverse toxic chemicals towards T. pyriformis.

A series of diverse organic compounds impose serious detrimental effects on the health of living organisms and the environment. Determination of the structural aspects of compounds that impart toxicity and evaluation of the same is crucial before public usage. The present study aims to determine the structural characteristics of compounds for Tetrahymena pyriformis toxicity using the q-RASTR (Quantitative Read Across Structure-Toxicity Relationship) model. It was developed using RASTR and 2-D descriptors for a dataset of 1792 compounds with defined endpoint (pIGC50) against a model organism, T. pyriformis. For the current study, the whole dataset was divided based on activity/property into the training and test sets, and the q-RASTR model was developed employing six descriptors (three latent variables) having r2, Q2F1 and Q2 values of 0.739, 0.767, and 0.735, respectively. The generated model was thoroughly validated using internationally recognized internal and external validation criteria to assess the model's dependability and predictability. It was highlighted that high molecular weight, aromatic hydroxyls, nitrogen, double bonds, and hydrophobicity increase the toxicity of organic compounds. The current study demonstrates the applicability of the RASTR algorithm in QSTR model development for the prediction of toxic chemicals (pIGC50) towards T. pyriformis.