Post-symptomatic detection of COVID-2019 grade based mediative fuzzy projection.

The concept of fuzzy set, intuitionistic set, and mediative fuzzy set as a generalization of a crisp set have been introduced in many real-life applications. The concept of crisp relation between elements of sets can be extended to fuzzy relations. Extended relations will be considered as relations on fuzzy sets. In this work, we developed the concept of mediative fuzzy relation and meditative fuzzy projection in the context of fuzzy relation and fuzzy projection. We extended the basic operations of fuzzy projection into intuitionistic fuzzy projection and then in the mediative fuzzy projection. We have shown the credibility and impact of mediative index factor involves in the mediative fuzzy projection in context of prediction work in relation to the proposed model. Further, we applied the mediative fuzzy projection in the medical diagnosis in post-COVID-19 patients. The obtained results have also been discussed with their geometrical representation.

Mediative fuzzy logic mathematical model: A contradictory management prediction in COVID-19 pandemic.

This paper presents a model based on mediative fuzzy logic in this COVID-19 pandemic. COVID-19 (novel coronavirus respiratory disease) has become a pandemic now and the whole world has been affected by this disease. Different methodologies and many prediction techniques based on various models have been developed so far. In the present article, we have developed a mediative fuzzy correlation technique based on the parameters for COVID-19 patients from different parts of India. The proposed mediative fuzzy correlation technique provides the relation between the increments of COVID-19 positive patients in terms of the passage of increment with respect to time. The peaks of infected cases in connection with the other condition are estimated from the available data. The mediative fuzzy logic mathematical model can be utilized to find a good fit or a contradictory model for any pandemic model. The proposed approach to the prediction in COVID-19 based on mediative fuzzy logic has produced promising results for the continuous contradictory prediction in India.

Targeted Smart pH and Thermoresponsive N,O-Carboxymethyl Chitosan Conjugated Nanogels for Enhanced Therapeutic Efficacy of Doxorubicin in MCF-7 Breast Cancer Cells.

In cancer treatment, developing ideal anticancer drug delivery systems to target tumor microenvironment by circumventing various physiological barriers still remains a daunting challenge. Here, in our work, a series of pH- and temperature-responsive nanogels based on poly(N-isopropylacrylamide-co-1-propene-2-3-dicarboxylate-co-2-acrylamido-2-methyl-1-propanesulfonate [poly(NIPAAm-IA-AMPS)] cross-linked by ethylene glycol dimethacrylate (EGDMA) were synthesized by random copolymerization. The molar ratio between monomer-comonomers-cross-linker was varied to fine-tune the optimum responsiveness of the nanogels. These optimized nanogels were further coupled to N,O-carboxymethyl chitosan (NOCC) stoichiometrically using EDC-NHS coupling chemistry to enhance the swelling behavior at lower pH. Interestingly, these NOCC-g-nanogels, when dispersed in aqueous media under sonication, attain nanosize and retain their high water-retention capacity with conspicuous pH and temperature responsiveness (viz. nanogel shrinkage in size beyond 35 °C and swelled at acidic pH) in vitro, as reflected by dynamic light scattering data. Doxorubicin (DOX), a potent anticancer drug, was loaded into these nanogels using the physical entrapment method. These drug-loaded nanogels exhibited a slow and sustained DOX release profile at physiological temperature and cytosolic pH. Furthermore, confocal and TEM results demonstrate that these nanogels were swiftly internalized by MCF-7 cells, and cell viability data showed preferential heightened cytotoxicity toward cancer cells (MCF-7 and MDA-MB231) compared to the MCF10A cells (human breast epithelial cell). Furthermore, intracellular DNA damage and cell cycle arrest assays suggest a mitochondrial mediated apoptosis in MCF-7 cells. This study substantiates our NOCC-g-nanogel platform as an excellent modality for passive diffusive loading and targeted release of entrapped drug(s) at physiological conditions in a controlled way for the improved therapeutic efficacy of the drug in anticancer treatment.

Improving ML-based landslide susceptibility using ensemble method for sample selection: a case study of Kangra district in Himachal Pradesh, India.

Developing effective strategies to predict areas susceptible to landslides and reducing risk is vital. This involves using ensemble methods to meet the precise prediction and addressing challenges like data limitation. Recent studies have highlighted the potential of using ensemble methods to enhance the prediction of landslide susceptibility maps (LSM). Ensemble methods present a sampling of landslides and non-landslide points from high and low susceptible areas, respectively. Extensive research has explored their application in machine learning processes, particularly in classification-related problems. This study delves into strategies of ensemble as a promising method in future landslide applications. The proposed method was tested considering Kangra district of Himachal Pradesh as study area where three datasets were prepared consisting of presence and absence points. Dataset 1 consisted of initial landslide and randomly generated non-landslide points. In dataset 2, additional landslide points obtained from the very high susceptibility of initial LSM were supplemented with initial landslide data, while the non-landslide points were generated randomly from the study area. Finally, dataset 3 was composed of the landslide points as in dataset 2, and the non-landslide points were obtained from the very low susceptible areas of initial LSM. These datasets are used with random forest (RF) and support vector machine (SVM), thereby preparing six landslide susceptibility maps. To analyze the applicability of the proposed method, we have used metrics such as AUC-ROC, precision, recall, F-score, accuracy and Mathew's correlation coefficient (MCC). The AUC for dataset 1 with SVM and RF is 0.89, which increased to 0.898 and 0.952 for datasets 2 and 3 with SVM and 0.937 and 0.954 with RF. Among all the methods, the precision and recall values were highest for dataset 3 with SVM as well as RF. Hence, based on several accuracy metrics, we conclude that when the landslides and non-landslides samples were sampled from very high and very low susceptible areas respectively, the LSM performed better than all the other methods. Sampling landslides from very high susceptible areas only (dataset 2) does not perform well thereby committing misclassification error. The study demonstrated that the landslide and non-landslide data were obtained from very high and very low susceptibility; the predictive capability of the LSM increased significantly. Thus, the results demonstrate the effectiveness of the proposed ensemble approach in providing precise delineation of landslide zones, facilitating informed decision-making for land and hazard management.

Evaluating causative factors for landslide susceptibility along the Imphal-Jiribam railway corridor in the North-Eastern part of India using a GIS-based statistical approach.

The Northeast part of India is experiencing an increase in infrastructure projects as well as landslides. This study aims to prepare the landslide susceptibility map of Tamenglong and Senapati districts, Manipur, India, and evaluates the state of landslide susceptibility along the Imphal-Jiribam railway corridor. Efficient statistical methods such as frequency ratio (FR), information value (IoV), weight of evidence (WoE), and weighted linear combination (WLC) were used in model preparation. A total of 322 landslide points were randomly divided into training (70%) and testing (30%) datasets. Nine causative factors were utilized for landslide susceptibility mapping (LSM). The importance of which was obtained using the information gain (IG) method. FR, IoV, WoE, and WLC were used to prepare the LSM using the training datasets and nine causative factors. Moreover, the accuracy and consistency were evaluated using AUC-ROC, precision, recall, overall accuracy (OA), balanced accuracy (BA), and F-score. The validation results showed that all methods performed well with the highest AUC and precision values of 0.913 and 0.95, respectively, for the IoV method, while the WLC method had the highest OA, BA, and F-score values of 0.808, 0.81, and 0.812, respectively. Finally, the results from LSM were used to evaluate the state of landslide susceptibility along the Imphal-Jiribam railway corridor. The results showed that 34% of the areas had high and very high susceptibility, while 40% were under less and significantly less susceptibility. The Tupul landslide area lay in medium susceptibility where the disastrous landslide occurred on 30 June 2022. Susceptibility values around the Noney and Khongsag railway station ranged from high to very high susceptibility. Thus, the study manifests the need for LSM preparation in rapidly constructing areas, which in turn will help the policymakers and planners for adopting strategies to minimize losses caused due to landslides.

Characterization and properties of the biosurfactant produced by PAH-degrading bacteria isolated from contaminated oily sludge environment.

The aim of the present study was to investigate biosurfactant production ability of five different polyaromatic hydrocarbon (PAH)-metabolizing bacteria, such as Ochrobactrum anthropi IITR07, Pseudomonas mendocina IITR46, Microbacterium esteraromaticum IITR47, Pseudomonas aeruginosa IITR48, and Stenotrophomonas maltophilia IITR87. These bacteria showed biosurfactant production using 2% glucose as rich substrate; strain IITR47 yielded the highest with 906 and 534 mg/L biosurfactant in the presence of naphthalene and crude oil as the unique carbon sources. P. aeruginosa IITR48 showed the least surface tension at 29 N/m and the highest emulsification index at 63%. The biosurfactants produced were identified as glycolipid and rhamnolipid based on Fourier transform infrared spectroscopy analysis. In particular, the biosurfactant produced by bacteria S. maltophilia IITR87 efficiently emulsified mustard oil with an E24 value of 56%. It was observed that, all five biosurfactants from these degrader strains removed 2.4-, 1.7-, 0.9-, 3.8-, and 8.3-fold, respectively, crude oil from contaminated cotton cloth. Rhamnolipid derived from IITR87 was most efficient, exhibiting highest desorption of crude oil. These biosurfactants exhibited good stability without significantly losing its emulsification ability under extreme conditions, thus can be employed for bioremediation of PAHs from diverse contaminated ecosystem. Graphical Abstract.

Advances in controlled release pesticide formulations: Prospects to safer integrated pest management and sustainable agriculture.

As the world is striving hard towards sustainable agricultural practices for a better tomorrow, one of the primary focuses is on effective pest management for enhanced crop productivity. Despite newer and potent chemicals as pesticides, there are still substantial crop losses, and if by any means this loss can be tackled; it will alleviate unwanted excessive use of chemical pesticides. Scientific surveys have already established that pesticides are not being utilized by the crops completely rather a significant amount remains unused due to various limiting factors such as leaching and bioconversion, etc., resulting in an adverse effect on human health and ecosystems. Concerted efforts from scientific diaspora toward newer and innovative strategies are already showing promise, and one such viable approach is controlled release systems (CRS) of pesticides. Moreover, to bring these smart formulations within the domain of current pesticide regulatory framework is still under debate. It is thus, paramount to discuss the pros and cons of this new technology vis-à-vis the conventional agrarian methods. This review deliberates on the developmental updates in this innovative field from the past decades and also appraises the challenges encumbered. Additionally, critical information and the foreseeable research gaps in this emerging area are highlighted.

Rhamnolipids from Planococcus spp. and their mechanism of action against pathogenic bacteria.

Two bacterial species with the ability to produce biosurfactants were isolated from a pesticide contaminated soil and identified as Planococcus rifietoensis IITR53 and Planococcus halotolerans IITR55. Formation of froth indicating the surfactant production was observed when grown in basal salt medium containing 2% glucose. The culture supernatant after 72 h showed reduction in surface tension from 72 N/m to 46 and 42 N/m for strain IITR53 and IITR55 with emulsification index of 51 and 54% respectively. The biosurfactant identified as rhamnolipid based on liquid chromatography-mass spectrometry analysis, was found to inhibit the growth of both gram- positive and negative pathogenic bacteria. Both the rhamnolipids at 40 mg/mL exhibited the release of extracellular DNA and protein content. Also at one third of the MIC, a significant generation of reactive oxygen species was recorded. These rhamnolipids effectively emulsified different vegetable oils suggesting their possible utilization as antimicrobial agent.

Biosynthesis and characterization of sophorolipid biosurfactant by Candida spp.: Application as food emulsifier and antibacterial agent.

Biosurfactants from the yeast strains Candida albicans SC5314 and Candida glabrata CBS138 were isolated and characterized. Surface tension of the cell-free broth was reduced from 72 N/m to 42 N/m and 55 N/m respectively. The biosurfactants showed emulsifying ability as the indices against castor oil were determined to be 51% and 53% for C. albicans and C. glabrata respectively and were found stable between pH 2 and 10, temperature 4-120 °C and salt concentration 2-14%. The partially purified surfactants were identified as sophorolipid using Fourier transform infrared spectroscopy. Isolated sophorolipid showed antibacterial properties against pathogenic bacteria and generated reactive oxygen species in Bacillus subtilis and Escherichia coli. Flow cytometric analysis revealed that 60 mg/L of C. glabrata biosurfactant killed 65.8% B. subtilis and 4% E. coli. The data here obtained indicates applications of biosurfactant focusing mainly as antimicrobial and therapeutic perspectives.

Polymer-Assisted In Situ Synthesis of Silver Nanoparticles with Epigallocatechin Gallate (EGCG) Impregnated Wound Patch Potentiate Controlled Inflammatory Responses for Brisk Wound Healing.

INTRODUCTION: An ideal wound dressing material needs to be predisposed with desirable attributes like anti-infective effect, skin hydration balance, adequate porosity and elasticity, high mechanical strength, low wound surface adherence, and enhanced tissue regeneration capability. In this work, we have synthesized hydrogel-based wound patches having antibacterial silver nanoparticles and antioxidant epigallocatechin gallate (EGCG) and showed fast wound closure through their synergistic interaction without any inherent toxicity. METHODS AND RESULTS: Wound patches were synthesized from modified guar gum polymer and assessed to determine accelerated wound healing. The modified polymer beget chemical-free in-situ synthesis of monodispersed silver NPs (~12 nm), an antimicrobial agent, besides lending ionic surface charges. EGCG impregnated during ionotropic gelation process amplified the efficacy of wound patches that possess apt tensile strength, porosity, and swellability for absorbing wound exudates. Further, in vitro studies endorsed them as non-cytotoxic and the post agent effect following exposure to the patch showed an unbiased response to E coli K12 and B. subtilis. In vivo study using sub-cutaneous wounds in Wistar rats validated its accelerated healing properties when compared to a commercially available wound dressing material (skin graft; Neuskin-F®) through better wound contraction, promoted collagen deposition and enhanced vascularization of wound region by modulating growth factors and inflammatory cytokines. CONCLUSION: Synthesized wound patches showed all the desired attributes of a clinically effective dressing material and the results were validated in various in vitro and in vivo assays.

Sub-acute oral exposure of zinc oxide nanoparticles causes alteration in iron homeostasis through acute phase response: A protective effect by surface modification.

Zinc oxide nanoparticles (ZnO NPs) are one of the most widely used nanomaterials. Following oral exposure, these NPs can accumulate in various organs and induce the toxicity due to their physiochemical characteristics. In present study to reduce the toxicity, surface engineered ZnO NPs (c-ZnO NPs) were in-situ synthesized by using polyacrylamide grafted guar gum (PAm-g-GG) polymer in alkaline media. Further, the comparative effect of bared ZnO NPs (b-ZnO NPs) and c-ZnO NPs were assessed on secondary target organ liver and kidneys of Swiss mice at doses of 10, 50 and 300 mg/kg following 28 days repeated oral treatment. The b-ZnO NPs were incited severe damages in liver and kidney tissue than c-ZnO NPs as seen by transmission electron microscopy and histopathology. The increased levels of serum biomarkers (AST, ALT, ALP, creatinine, uric acid, and urea) were also observed, that remarking a disturbance in the function of liver and kidney. After sub-acute oral treatment of b-ZnO NPs, the hepatic pro-inflammatory cytokines (IL-6, TNF-α, and MMP-9) were up-regulated that causes the activation of acute phase response (APR). We also observed significantly increased in expression of hepatic acute phase proteins (hepcidin and haptoglobin) and altered interlinked iron (Fe) signaling biomarkers (hephaestin, TF, TFR-1, LDH, and ferroportin). This study emphasizes that exposure to ZnO NPs may cause inflammation mediated APR through ultra-structural damage of tissue that could escort the progression of anemia. Nevertheless, the capping with PAm-g-GG in c- ZnO NPs has reduced the toxicity by altering the surface reactive property of ZnO NPs.

Impact of Surface-Engineered ZnO Nanoparticles on Protein Corona Configuration and Their Interactions With Biological System.

In biological system, the interaction between nanoparticles (NPs) and serum biomolecules results in the formation of a dynamic corona of different affinities. The formed corona enriched with opsonin protein is recognized by macrophages and immune effector cells, resulting in rapid clearance with induced toxicity. Hence, to reduce corona genesis, surface-engineered ZnO (c-ZnO) NPs were in situ synthesized using a polyacrylamide-grafted guar gum (PAm-g-GG) polymer that provided surface neutrality to the NPs. Furthermore, we studied the characteristics of the corona formed onto uncapped anionic ZnO (bared ZnO [b-ZnO]) NPs and c-ZnO NPs by serum incubation. The result shows that b-ZnO NPs were wrapped with a high amount of serum proteins, particularly opsonin (IgG and complement), compared with c-ZnO NPs. These corona findings helped us substantially in interpretation of in vivo biokinetics studies. The in vivo study was accomplished by oral administration of NPs to Swiss mice at doses of 300 and 2000 mg/kg body weight. The studies performed on the cellular uptake, intracellular particle distribution, cytotoxicity, and pharmacokinetics of NPs indicated that b-ZnO NPs experienced higher immune cell recognition, hepatic inflammation, and resultant rapid clearance from the system, unlike c-ZnO NPs. Thus, capping of NPs by a neutral polymer has provided limited binding sites for undesired proteins around NPs, which limits immune system activation.

Author Correction: Physico-chemical properties based differential toxicity of graphene oxide/reduced graphene oxide in human lung cells mediated through oxidative stress.

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Statistical optimization and artificial neural network modeling for acridine orange dye degradation using in-situ synthesized polymer capped ZnO nanoparticles.

ZnO NPs were synthesized by a prudent green chemistry approach in presence of polyacrylamide grafted guar gum polymer (pAAm-g-GG) to ensure uniform morphology, and functionality and appraised for their ability to degrade photocatalytically Acridine Orange (AO) dye. These ZnO@pAAm-g-GG NPs were thoroughly characterized by various spectroscopic, XRD and electron microscopic techniques. The relative quantity of ZnO NPs in polymeric matrix has been estimated by spectro-analytical procedure; AAS and TGA analysis. The impact of process parameters viz. NP's dose, contact time and AO dye concentration on percentage photocatalytic degradation of AO dyes were evaluated using multivariate optimizing tools, Response Surface Methodology (RSM) involving Box-Behnken Design (BBD) and Artificial Neural Network (ANN). Congruity of the BBD statistical model was implied by R2 value 0.9786 and F-value 35.48. At RSM predicted optimal condition viz. ZnO@pAAm-g-GG NP's dose of 0.2g/L, contact time of 210min and AO dye concentration 10mg/L, a maximum of 98% dye degradation was obtained. ANOVA indicated appropriateness of the model for dye degradation owing to "Prob.>F" less than 0.05 for variable parameters. We further, employed three layers feed forward ANN model for validating the BBD process parameters and suitability of our chosen model. The evaluation of Levenberg-Marquardt algorithm (ANN1) and Gradient Descent with adaptive learning rate (ANN2) model employed to scrutinize the best method and found experimental values of AO dye degradation were in close to those with predicated value of ANN 2 modeling with minimum error.

Physico-chemical properties based differential toxicity of graphene oxide/reduced graphene oxide in human lung cells mediated through oxidative stress.

Graphene derivatives (GD) are currently being evaluated for technological and biomedical applications owing to their unique physico-chemical properties over other carbon allotrope such as carbon nanotubes (CNTs). But, the possible association of their properties with underlying in vitro effects have not fully examined. Here, we assessed the comparative interaction of three GD - graphene oxide (GO), thermally reduced GO (TRGO) and chemically reduced GO (CRGO), which significantly differ in their lateral size and functional groups density, with phenotypically different human lung cells; bronchial epithelial cells (BEAS-2B) and alveolar epithelial cells (A549). The cellular studies demonstrate that GD significantly ineternalize and induce oxidative stress mediated cytotoxicity in both cells. The toxicity intensity was in line with the reduced lateral size and increased functional groups revealed more toxicity potential of TRGO and GO respectively. Further, A549 cells showed more susceptibility than BEAS-2B which reflected cell type dependent differential cellular response. Molecular studies revealed that GD induced differential cell death mechanism which was efficiently prevented by their respective inhibitors. This is prior study to the best of our knowledge involving TRGO for its safety evaluation which provided invaluable information and new opportunities for GD based biomedical applications.