Biosorption of Escherichia coli Using ZnO-Trimethyl Chitosan Nanocomposite Hydrogel Formed by the Green Synthesis Route.

In this study, we tested the biosorption capacity of trimethyl chitosan (TMC)-ZnO nanocomposite (NC) for the adsorptive removal of Escherichia coli (E. coli) in aqueous suspension. For the formation of ZnO NPs, we followed the green synthesis route involving Terminalia mantaly (TM) aqueous leaf extract as a reducing agent, and the formed ZnO particles were surface-coated with TMC biopolymer. On testing of the physicochemical characteristics, the TM@ZnO/TMC (NC) hydrogel showed a random spherical morphology with an average size of 31.8 ± 2.6 nm and a crystal size of 28.0 ± 7.7 nm. The zeta potential of the composite was measured to be 23.5 mV with a BET surface area of 3.01 m2 g-1. The spectral profiles of TM@ZnO/TMC NC hydrogel on interaction with Escherichia coli (E. coli) revealed some conformational changes to the functional groups assigned to the stretching vibrations of N-H, C-O-C, C-O ring, and C=O bonds. The adsorption kinetics of TM@ZnO/TMC NC hydrogel revealed the pseudo-second-order as the best fit mechanism for the E. coli biosorption. The surface homogeneity and monolayer adsorption of the TM@ZnO/TMC NC hydrogel reflects majorly the entire adsorption mechanism, observed to display the highest correlation for Jovanovic, Redlich-Peterson, and Langmuir's isotherm models. Further, with the use of TM@ZnO/TMC NC hydrogel, we measured the highest adsorption capacity of E. coli to be 4.90 × 10 mg g-1, where an in-depth mechanistic pathway was proposed by making use of the FTIR analysis.

Magnetically controlled drug delivery and hyperthermia effects of core-shell Cu@Mn3O4 nanoparticles towards cancer cells in vitro.

Recent increase in the integration of nanotechnology and nanosciences to the biomedical sector fetches the human wellness through the development of sustainable treatment methodologies for cancerous tumors at all stages of their initiation and progression. This involves the development of multifunctional theranostic probes that effectively support for the early cancer diagnosis, avoiding non-target cell toxicity, controlled and customized anticancer drug release etc. Therefore, to advance the field of nanotechnology-based sustainable cancer treatment, we fabricated and tested the efficacy of anticancer drug-loaded magnetic hybrid nanoparticles (NPs) towards in vitro cell culture systems. The developed conjugate of NPs was incorporated with the functions of both controlled drug delivery and heat-releasing ability using Mn3O4 (manganese oxide) magnetic core with Cu shell encapsulated within trimethyl chitosan (TMC) biopolymer. On characterization, the Cu@Mn3O4-TMC NPs were confirmed to have an approximate size of 130 nm with full agglomeration (as observed by the HRTEM) and crystal size of 92.95 ± 18.38 nm with tetragonal hausmannite phase for Mn3O4 spinel structure (XRD). Also, the UV-Vis and FTIR analysis provided the qualitative and quantitative effects of 5-fluororacil (5-Fu) anticancer drug loading (max 68 %) onto the Cu@Mn3O4-TMC NPs. The DLS analysis indicated for the occurrence of no significant changes to the particle size (around 100 nm) of Cu@Mn3O4-TMC due to the solution dispersion thereby confirming for the aqueous stability of developed NPs. In addition, the magnetization values of Cu@Mn3O4-TMC NPs were measured to be 34 emu/g and a blocking temperature of 42 K. Further tests of magnetic hyperthermia by the Cu@Mn3O4-TMC/5-Fu NPs provided that the heat-releasing capacity (% ΔT at 15 min) increases with that of increased frequency, i.e. 28 % (440 Hz) > 22.6 % (240 Hz) > 18 % (44 Hz), and the highest specific power loss (SPL) value observed to be 488 W/g for water. Moreover, the 5-Fu drug release studies indicate that the release is high at a pH of 5.2 and almost all the loaded drug is getting delivered under the influence of the external magnetic field (430 Hz) due to the influence of both Brownian-rotation and Néel relaxation heat-mediated mechanism. The pharmacokinetic drug release studies have suggested for the occurrence of more than one model, i.e. First-order, Higuchi (diffusion), and Korsemeyer-Peppas (non-Fickian), in addition to hyperthermia. Finally, the in vitro cell culture systems (MCF-7 cancer and MCF-10 non-cancer) helped to differentiate the physiological changes due to the effects of hyperthermia and 5-Fu drug individually and as a combination of both. The observed differences of cell viability losses among both cell types are measured and discussed with the expression of heat shock proteins (HSPs) by the MCF-10 cells as against the MCF-7 cancer cells. We believe that the results generated in this project can be helpful for the designing of new cancer therapeutic models with nominal adverse effects on healthy normal cells and thus paving a way for the treatment of cancer and other deadly diseases in a sustainable manner.

The Health Risk and Source Assessment of Polycyclic Aromatic Hydrocarbons (PAHs) in the Soil of Industrial Cities in India.

Industrial areas play an important role in the urban ecosystem. Industrial site environmental quality is linked to human health. Soil samples from two different cities in India, Jamshedpur and Amravati, were collected and analyzed to assess the sources of polycyclic aromatic hydrocarbons (PAHs) in industrial areas and their potential health risks. The total concentration of 16 PAHs in JSR (Jamshedpur) varied from 1662.90 to 10,879.20 ng/g, whereas the concentration ranged from 1456.22 to 5403.45 ng/g in the soil of AMT (Amravati). The PAHs in the samples were dominated by four-ring PAHs, followed by five-ring PAHs, and a small percentage of two-ring PAHs. The ILCR (incremental lifetime cancer risk) of the soil of Amravati was lower compared to that of Jamshedpur. The risk due to PAH exposure for children and adults was reported to be in the order of ingestion > dermal contact > inhalation while for adolescents it was dermal contact > ingestion > inhalation in Jamshedpur. In contrast, in the soil of Amravati, the PAH exposure path risk for children and adolescents were the same and showed the following order: dermal contact > ingestion > inhalation while for the adulthood age group, the order was ingestion > dermal contact > inhalation. The diagnostic ratio approach was used to assess the sources of PAHs in various environmental media. The PAH sources were mainly dominated by coal and petroleum/oil combustion. As both the study areas belong to industrial sites, the significant sources were industrial emissions, followed by traffic emissions, coal combustion for domestic livelihood, as well as due to the geographical location of the sampling sites. The results of this investigation provide novel information for contamination evaluation and human health risk assessment in PAH-contaminated sites in India.

A Comparative Study on Predication of Appropriate Mechanical Ventilation Mode through Machine Learning Approach.

Ventilation mode is one of the most crucial ventilator settings, selected and set by knowledgeable critical care therapists in a critical care unit. The application of a particular ventilation mode must be patient-specific and patient-interactive. The main aim of this study is to provide a detailed outline regarding ventilation mode settings and determine the best machine learning method to create a deployable model for the appropriate selection of ventilation mode on a per breath basis. Per-breath patient data is utilized, preprocessed and finally a data frame is created consisting of five feature columns (inspiratory and expiratory tidal volume, minimum pressure, positive end-expiratory pressure, and previous positive end-expiratory pressure) and one output column (output column consisted of modes to be predicted). The data frame has been split into training and testing datasets with a test size of 30%. Six machine learning algorithms were trained and compared for performance, based on the accuracy, F1 score, sensitivity, and precision. The output shows that the Random-Forest Algorithm was the most precise and accurate in predicting all ventilation modes correctly, out of the all the machine learning algorithms trained. Thus, the Random-Forest machine learning technique can be utilized for predicting optimal ventilation mode setting, if it is properly trained with the help of the most relevant data. Aside from ventilation mode, control parameter settings, alarm settings and other settings may also be adjusted for the mechanical ventilation process utilizing appropriate machine learning, particularly deep learning approaches.

Surface-Enhanced Carboxyphenyl Diazonium Functionalized Screen-Printed Carbon Electrode for the Screening of Tuberculosis in Sputum Samples.

Curbing tuberculosis (TB) requires a combination of good strategies, including a proper prevention measure, diagnosis, and treatment. This study proposes an improvised tuberculosis diagnosis based on an amperometry approach for the sensitive detection of MPT64 antigen in clinical samples. An MPT64 aptamer specific to the target antigen was covalently attached to the carboxyphenyl diazonium-functionalized carbon electrode via carbodiimide chemistry. The electrochemical detection assay was adapted from a sandwich assay format to trap the antigen between the immobilized aptamer and horseradish peroxidase (HRP) tagged polyclonal anti-MPT64 antibody. The amperometric current was measured from the catalytic reaction response between HRP, hydrogen peroxide, and hydroquinone, which is used as an electron mediator. From the analysis, the detection limit in the measurement buffer was 1.11 ng mL-1. Additionally, the developed aptasensor exhibited a linear relationship between the current signal and the MPT64 antigen-spiked serum concentration ranging from 10 to 150 ng mL-1 with a 1.38 ng mL-1 detection limit. Finally, an evaluation using the clinical sputum samples from both TB (+) and TB (-) individuals revealed a sensitivity and specificity of 88% and 100%, respectively. Based on the analysis, the developed aptasensor was found to be simple in its fabrication, sensitive, and allowed for the efficient detection and diagnosis of TB in sputum samples.