Zinc oxide nanoparticle-coated films: fabrication, characterization, and antibacterial properties

In this article, novel antibacterial PVC-based films coated with ZnO nanoparticles (NPs) were fabricated, characterized, and studied for their antibacterial properties. It was shown that the ZnO NPs were coated on the surface of the PVC films uniformly and that the coating process did not affect the size and shape of the NPs on the surface of PVC films. Films coated with concentrations of either 0.2 or 0.075 g/L of ZnO NPs exhibited antibacterial activity against both Gram-positive (Staphylococcus aureus) and Gram-negative (Escherichia coli) bacteria, but exhibited no antifungal activity against Aspergillus flavus and Penicillium citrinum. Smaller particles (100 nm) exhibited more potent antibacterial activity than larger particles (1000 nm). All ZnO-coated films maintained antibacterial activity after 30 days in water

Cyber-Physical Systems Integration in Healthcare: AI-Enabled Decision Support Systems

Abstract structured in: The convergence of Cyber-Physical Systems (CPS) and healthcare is bringing about a transformation in the delivery of patient care by bridging the gap between the digital and physical realms. By utilizing modern technologies, these systems make it possible to make intelligent decisions and gain insights that are driven by data in real time.Introduction: The complexity of data integration, the mitigation of sophisticated cyber threats, and the guaranteeing of system scalability within a variety of healthcare infrastructures are among the most significant obstacles. Methods: This research presents the Artificial Intelligence-Enabled Intrusion Quantum Predictive Detection System (AI-IQPDS), an innovative approach that is intended to improve the operational reliability of healthcare CPS, as well as the security and predictive analytics capabilities of the system. AI-IQPDS combine quantum computing and machine learning to provide accurate intrusion detection and predictive decision assistance. Intelligent patient monitoring systems powered by AI can optimize hospital resource management, transmit data securely between connected devices, and detect emergencies early working. Results: Simulation results show that the system outperforms modern techniques in terms of precision of detection, speed of processing, and reduction of false-positives. The results of this research demonstrate the revolutionary possibilities of using CPS driven by AI in healthcare. Conclusion: Healthcare ecosystems that are both intelligent and scalable may be possible as a result of this integration, which might lead to better efficiency, security, and patient outcomes.

A Novel Nanocomposite (SR/HA/-nZnO) Material for Medical Application

Access full text - https://doi.org/10.1007/978-3-030-31866-6_63In this work, hydroxyapatite synthesized by sol-gel technique. Ca(NO3)2.4H2O and (NH4)2HPO4 used as precursors, and nano ZnO was prepared and modify the surface using Oleic acid to get uniform distribution Within the matrix and reduce nanoparticles agglomeration ZnO. Silicone rubber composites were prepared as a second part by using HA as to increase the biocompatibility ,mechanical properties of SR, and to get antibacterial nanocomposites ZnO modified were used

3D Hepatic Cultures Simultaneously Maintain Primary Hepatocyte and Liver Sinusoidal Endothelial Cell Phenotypes

Developing in vitro engineered hepatic tissues that exhibit stable phenotype is a major challenge in the field of hepatic tissue engineering. However, the rapid dedifferentiation of hepatic parenchymal (hepatocytes) and non-parenchymal (liver sinusoidal endothelial, LSEC) cell types when removed from their natural environment in vivo remains a major obstacle. The primary goal of this study was to demonstrate that hepatic cells cultured in layered architectures could preserve or potentially enhance liver-specific behavior of both cell types. Primary rat hepatocytes and rat LSECs (rLSECs) were cultured in a layered three-dimensional (3D) configuration. The cell layers were separated by a chitosan-hyaluronic acid polyelectrolyte multilayer (PEM), which served to mimic the Space of Disse. Hepatocytes and rLSECs exhibited several key phenotypic characteristics over a twelve day culture period. Immunostaining for the sinusoidal endothelial 1 antibody (SE-1) demonstrated that rLSECs cultured in the 3D hepatic model maintained this unique feature over twelve days. In contrast, rLSECs cultured in monolayers lost their phenotype within three days. The unique stratified structure of the 3D culture resulted in enhanced heterotypic cell-cell interactions, which led to improvements in hepatocyte functions. Albumin production increased three to six fold in the rLSEC-PEM-Hepatocyte cultures. Only rLSEC-PEM-Hepatocyte cultures exhibited increasing CYP1A1/2 and CYP3A activity. Well-defined bile canaliculi were observed only in the rLSEC-PEM-Hepatocyte cultures. Together, these data suggest that rLSEC-PEM-Hepatocyte cultures are highly suitable models to monitor the transformation of toxins in the liver and their transport out of this organ. In summary, these results indicate that the layered rLSEC-PEM-hepatocyte model, which recapitulates key features of hepatic sinusoids, is a potentially powerful medium for obtaining comprehensive knowledge on liver metabolism, detoxification and signaling pathways in vitro

Discovering Networks of Perturbed Biological Processes in Hepatocyte Cultures

The liver plays a vital role in glucose homeostasis, the synthesis of bile acids and the detoxification of foreign substances. Liver culture systems are widely used to test adverse effects of drugs and environmental toxicants. The two most prevalent liver culture systems are hepatocyte monolayers (HMs) and collagen sandwiches (CS). Despite their wide use, comprehensive transcriptional programs and interaction networks in these culture systems have not been systematically investigated. We integrated an existing temporal transcriptional dataset for HM and CS cultures of rat hepatocytes with a functional interaction network of rat genes. We aimed to exploit the functional interactions to identify statistically significant linkages between perturbed biological processes. To this end, we developed a novel approach to compute Contextual Biological Process Linkage Networks (CBPLNs). CBPLNs revealed numerous meaningful connections between different biological processes and gene sets, which we were successful in interpreting within the context of liver metabolism. Multiple phenomena captured by CBPLNs at the process level such as regulation, downstream effects, and feedback loops have well described counterparts at the gene and protein level. CBPLNs reveal high-level linkages between pathways and processes, making the identification of important biological trends more tractable than through interactions between individual genes and molecules alone. Our approach may provide a new route to explore, analyze, and understand cellular responses to internal and external cues within the context of the intricate networks of molecular interactions that control cellular behavior

Descoloração do corante Azul Brilhante de Remazol R por leveduras isoladas de moluscos do Rio Subaé, no estado da Bahia, Brasil

RESUMO Os objetivos deste trabalho foram estudar o potencial de descoloração do corante Azul Brilhante de Remazol R (RBBR) por cinco isolados de leveduras identificados como OJU2, SJL6, SF5, SJ10 e SJU5, otimizar as condições de crescimento das leveduras e verificar a toxicidade do produto obtido após a descoloração. Para isso, foram realizados ensaios em batelada variando os seguintes parâmetros: pH (2 a 8), concentração de glicose (0 a 3%), concentração do corante (25 a 100 ppm) e temperatura (20 a 40ºC). As leveduras mostraram capacidade de descolorir o RBBR com eficiência entre 80 e 93%, depois de 24 horas. A melhor condição para descoloração do RBBR ocorreu em pH ácido, 2% de glicose, 25 ppm do corante e 25ºC. Com os ensaios com Artemia salina, foi observado diminuição da toxicidade após tratamento com os isolados SJ10 e SJU5, depois de 120 horas de incubação

Synthesis of ZnO nanoparticles by flame spray pyrolysis and characterisation protocol

There is uncertainty concerning the potential toxicity of zinc oxide (ZnO) nanoparticles, which may be attributed in part to a lack of understanding with regard to the physiochemical properties of the nanoparticles used in toxicological investigations. This paper reports the synthesis of a ZnO nanopowder by flame spray pyrolysis and demonstrates that the typically employed characterisation techniques such as specific surface area measurement and X-ray diffraction provide insufficient information on the sample, especially if it is intended for use in toxicity studies. Instead, a more elaborate characterisation protocol is proposed that includes particle morphology as well as detailed compositional analysis of the nanoparticle surface. Detailed transmission electron microscopy analysis illustrated the polydispersity within the sample: particles were elongated in the c-crystallographic direction, with average Ferret length ∼23 nm and Ferret width ∼14 nm. Dynamic light scattering (0.1 w/v% in deionised water, pH 7.4) revealed the particles were agglomerated with a modal secondary particle size of ∼1.5 μm. Fourier transform infrared spectroscopy and X-ray photoelectron spectroscopy indicated the presence of carbonate and hydroxide impurities on the surface of the ZnO nanoparticles and an increase of such impurities was observed as the sample was aged, which might influence the nanoparticle dissolution and/or cellular uptake behaviour. These data will be utilised, in order to facilitate the interpretation and understanding of results from toxicological investigations using in vitro cell lines