Investigation of Mechanical, Chemical, and Antibacterial Properties of Electrospun Cellulose-Based Scaffolds Containing Orange Essential Oil and Silver Nanoparticles.

This study demonstrated a controllable release properties and synergistic antibacterial actions between orange essential oil (OEO) and silver nanoparticles (AgNPs) incorporated onto cellulose (CL) nanofibers. The preparation of AgNPs attached on CL nanofibers was conducted through multiple processes including the deacetylation process to transform cellulose acetate (CA) nanofibers to CL nanofibers, the in situ synthesis of AgNPs, and the coating of as-prepared silver composite CL nanofibers using OEO solutions with two different concentrations. The success of immobilization of AgNPs onto the surface of CL nanofibers and the incorporation of OEO into the polymer matrix was confirmed by SEM-EDS, TEM, XRD, and FT-IR characterizations. The tensile strength, elongation at break, and Young's modulus of the nanofibers after each step of treatment were recorded and compared to pristine CA nanofibers. The high antibacterial activities of AgNPs and OEO were assessed against Gram-positive B. subtilis and Gram-negative E. coli microorganisms. The combined effects of two antimicrobials, AgNPs and OEO, were distinctively recognized against E. coli.

Liver cancer prediction in a viral hepatitis cohort: A deep learning approach.

Viral hepatitis is the primary cause of liver diseases, among which liver cancer is the leading cause of death from cancer. However, this cancer is often diagnosed in the later stages, which makes treatment difficult or even impossible. This study applied deep learning (DL) models for the early prediction of liver cancer in a hepatitis cohort. In this study, we surveyed 1 million random samples from the National Health Insurance Research Database (NHIRD) to analyze viral hepatitis patients from 2002 to 2010. Then, we used DL models to predict liver cancer cases based on the history of diseases of the hepatitis cohort. Our results revealed the annual prevalence of hepatitis in Taiwan increased from 2002 to 2010, with an average annual percentage change (AAPC) of 5.8% (95% CI: 4.2-7.4). However, young people (aged 16-30 years) exhibited a decreasing trend, with an AAPC of -5.6 (95% CI: -8.1 to -2.9). The results of applying DL models showed that the convolution neural network (CNN) model yielded the best performance in terms of predicting liver cancer cases, with an accuracy of 0.980 (AUC: 0.886). In conclusion, this study showed an increasing trend in the annual prevalence of hepatitis, but a decreasing trend in young people from 2002 to 2010 in Taiwan. The CNN model may be applied to predict liver cancer in a hepatitis cohort with high accuracy.

Fabrication of Silver Nano-Dendrites on Optical Fibre Core by Laser-Induced Method for Surface-Enhanced Raman Scattering Applications.

In this work, we present a novel fabrication method for making the surface-enhanced Raman scattering (SERS) probe based on silver (Ag) nano-dendrites which are grown and deposited on the end of multi-mode fibre core by a simple and low-cost laser-induced technique. The morphology of the Ag-nanoparticles (AgNPs) could be controlled by the experimental conditions such as laser power, illumination time, and concentration of the reaction solution. The morphology and chemical composition of SERS fibre probes are characterized by high-resolution scanning electron microscope (HR-SEM) and Energy dispersive X-ray spectroscopy (EDX), respectively. These results confirmed how the Ag nanostructures morphology is modified as a function of illumination time of laser irradiation, and the growth and deposition of Ag nanostructures occur only in the main laser-irradiated part on the end of multi-mode fibre core. The achieved SERS-activity substrates on the fibre probes are testing with the detection of low concentration of Rhodamine 6G aqueous solutions in the range of 10-5-10-10 M. This study shows that SERS activity coupled with Ag nano-dendrites substrate on the fibre probe has the best enhancement factor of 1.93×107 for Rhodamine 6G due to the creation of many of hot-spots for amplifying Raman signals by Ag nano-dendrite structures, which is a promising candidate with low-cost SERS probe of chemical compact optical fibre sensors for direct, rapid, real-time and non-destructive detection of chemical compounds in liquid environment.

Detection of Permethrin pesticide using silver nano-dendrites SERS on optical fibre fabricated by laser-assisted photochemical method.

Permethrin, 3-Phenoxybenzyl (1 RS)-cis,trans-3-(2,2-dichlorovinyl)- 2,2-dimethylcyclopropanecarboxylate, has a wide range of applications like insecticide, insect repellent and prevents mosquito-borne diseases, such as dengue fever and malaria in tropical areas. In this work, we develop a prominent monitoring method for the detection of permethrin pesticide using surface-enhanced Raman scattering (SERS) optical fibre substrates. The novel SERS-active optical fibre substrates were grown and deposited silver (Ag) nano-dendrites on the end of multi-mode fibre core by laser-assisted photochemical method. The characteristic of the Ag-nanostructures could be controlled by the experimental conditions, namely, laser illumination time. Ag nanoparticles optical fibre substrates and Ag nano-dendrites optical fibre substrates were prepared with laser illumination time of 3 min and 8 min, respectively. The achieved SERS-activity optical fibre substrates were tested with Rhodamine 6G aqueous solutions. We demonstrate that the SERS activity coupled with Ag nano-dendrites optical fibre substrate has higher Raman enhancement factor due to the creation of many of hot-spots for amplifying Raman signals. Besides, the stability and reproducibility of the Ag nano-dendrites optical fibre substrate were also evaluated with stored time of 1000 hours and relative standard deviation of less than 3%. The Ag nano-dendrite optical fibre substrate was selected for detection of permethrin pesticide in the concentration range of 0.1 ppm-20 ppm with limit of quantification (LOQ) of 0.1 ppm and calculated limit of detection (LOD) of 0.0035 ppm, proving its great potential for direct, rapid detection and monitoring of permethrin.

Chirality manifestation in elastic coupling between the layers of double-walled carbon nanotubes.

The search for new relatively easy physicochemical methods for the structural identification of carbon nanotubes represents a key challenge. Here, analyzing the experimental data on double-walled carbon nanotubes (DWCNTs) obtained by us and taken from the literature, we have expressed the magnitude of elastic coupling between two tubular walls forming a DWCNT as a simple function dependent not only on DWCNT diameters but also on the difference between the chirality angles of the constituent nanotubes. To get this quite unexpected result, which allows us to relate more precisely the structural parameters of a DWCNT with frequencies of its radial breathing-like modes (RBLM), we have developed a new model for the RBLM dynamics that takes into account a possible deposition of water molecules from ambient air onto the DWCNT surface. The model constructed allows us to predict the higher prevalence of DWCNTs comprising two walls with identical handedness. The application of the results obtained for the identification of DWCNTs is also considered.