Nanobiofunctionalized chitosan nanocomposite hydrogel as a highly biocompatible cancer drug carrier

A bio-inspired drug carrier was developed by dual functionalization of chitosan using L-glutamic acid (GA) and phyto-synthesized zinc oxide nanoparticles (ZNPs). A highly porous, three-dimensional network of nanocomposite hydrogel (GA-CHGZ) was obtained upon cross-linking chitosan using biomass-derived dialdehyde cellulose. The hydrogel was optimally loaded with naringenin (NRG) and further characterized using nuclear magnetic resonance (NMR), Fourier-transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), scanning electron microscopy (SEM), and swelling studies. An enhanced NRG loading efficiency of 85.23% was obtained using functionalized hydrogel compared to 52.54% using non-functionalized hydrogel. Delivery studies displayed a maximum release of 69.63% for 1.0 mg/ml of initial NRG concentration at pH 5, which is a highly preferred condition for cancer therapeutics. While ZNPs’ embedment was instrumental in improving the NRG loading and delivery rates, the GA conjugation increased the stability of NRG in the GA-CHGZ, aiding sustained NRG release, which followed a non-Fickian diffusion mechanism with polymer swelling. Antimicrobial potential was explored against Staphylococcus aureus and Trichophyton rubrum strains. The biocompatibility assay using L929 normal cells showed enhanced cell proliferation characteristics for the materials, revealing significant cell viability. The anticancer activity of NRG tested against A431 human skin carcinoma cells increased up to nine-fold with a reduced IC₅₀ value when a functionalized hydrogel was used instead of pure NRG without the nanocomposite carrier. Thus, the bio-functionalized drug–carrier system has a promising application for wound healing and topical skin cancer therapies.     

A novel automated depression detection technique using text transcript

Depression is one of the most common mental illnesses, impacting billions of people worldwide. The lack of existing resources is impeding the country's economic prosperity. As a result, new approaches for detecting and treating mental diseases as well as reaching out to individuals are required so that people can overcome their daily challenges and become more productive. An automated depression detection system can greatly aid in clinical findings and early treatment of depression. Automatic detection, like in a clinical interview can be derived from various modalities that include video, audio, and text. Among these modalities, audio characteristics are the most commonly researched while text elements are seldom investigated. In the light of the above, this paper proposes a novel automated depression identification approach based on linguistic material gathered from patient interviews. The focus is to enhance both the accuracy and efficiency of detection. The proposed approach is made up of two parts: a Bidirectional Gated Recurrent Unit (BGRU) network for dealing with linguistic information and a fully coupled network that integrates the model outputs to measure the depressed state. The proposed approach is validated using Distress Analysis Interview Corpus-Wizard-of-Oz interviews dataset. To evaluate the performance precision, recall, and F1 score are computed using the proposed approach and then the comparative analysis is done with the existing approaches. The proposed approach yielded an F1 score of 0.92, indicating the existence of depression as well as the projected severity level. It is realized from the generated results that the proposed approach has outperformed the previous ones. The proposed approach can not only automatically assess the severity of depression but also enhances both the accuracy and efficiency of detection. The proposed approach indicates the feasibility of BGRU over Long Short Term Memory by achieving exceptional results for recognition of depression.     

Efficient photocatalytic degradation of bisphenol A by green synthesized CuO decorated nickel hexacyanoferrate nanocomposite

Bisphenol A (BPA), a chemical additive in polycarbonate plastics and epoxy resins, is suspected to be an endocrine-disrupter. Extensive use and irregular treating methods have led to frequent detection of BPA in wastewater, raising demand for their removal by efficient nanomaterials-based technique. Nanocomposite CuO@NiHCF was synthesized via green method using Citrus aurantium peel extract. Crystalline structure (particle size <50 nm) of CuO@NiHCF was analysed by microscopic and spectroscopic analysis. This nanocomposite showed 97% degradation of BPA (50 mg L⁻¹) at neutral pH in sunlight. Moreover, improved particle stability (zeta potential: −56.2 mV; 2.0 eV) and high surface area, pore volume (81 m²g⁻¹, 13.9 nm) resulted from synergism of NiHCF (−26.3 mV; 2.4 eV), and CuO (−11.5 mV; 1.9 eV) led to efficient photodegradation of BPA. Degradation of BPA was found photo-adsorptive. Moreover, degradation was carried out by OH radicals based with ring-opening mechanisms by GC–MS. High efficiency and sustainability of CuO@NiHCF were revealed by its multiple reusability (n = 10), leading to a promising and sustainable photocatalyst.     

Features of the exponential form of internal heat generation,Cattaneo–Christov heat theory on water-based graphene–CNT–titanium ternary hybrid nanofluid flow

To increase energy efficiency, the flow of fluids containing nanoparticles is crucial in industrial applications notably in nuclear reactors and nuclear system cooling. In light of this, this study examines the flow of a water-based ternary hybrid nanofluid (graphene, single-walled carbon nanotubes, and titanium dioxide) across a curved stretching sheet with suction. The non-Fourier heat flux model is also considered in the modeling. The existing partial differential equations are converted into ordinary differential equations through the use of similarity variables. These ordinary differential equations are then numerically solved using the Runge–Kutta–Fehlberg fourth- and fifth-order method along with a shooting approach. The collection of graphical findings for the key variables on the temperature and velocity profiles is investigated. Results reveal that the heat transport in ternary hybrid nanoliquid rises as the heat source/sink parameter rises. The Biot number influences the thermal profile positively, whereas the increasing curvature parameter values reduce heat transport. The curvature parameter has a positive impact on skin friction but the suction parameter has a negative impact on skin friction.     

Complete Cototal Roman Domination Number of a Graph for User Preference Identification in Social Media

Many graph domination applications can be expanded to achieve complete cototal domination. If every node in a dominating set is regarded as a record server for a PC organization, then each PC affiliated with the organization has direct access to a document server. It is occasionally reasonable to believe that this gateway will remain available even if one of the scrape servers fails. Because every PC has direct access to at least two documents’ servers, a complete cototal dominating set provides the required adaptability to non-critical failure in such scenarios. In this paper, we presented a method for calculating a graph’s complete cototal roman domination number. We also examined the properties and determined the bounds for a graph’s complete cototal roman domination number, and its applications are presented. It has been observed that one’s interest fluctuate over time, therefore inferring them just from one’s own behaviour may be inconclusive. However, it may be able to deduce a user’s constant interest to some level if a user’s networking is also watched for similar or related actions. This research proposes a method that considers a user’s and his channel’s activity, as well as common tags, persons, and organizations from their social media posts in order to establish a solid foundation for the required conclusion.