ProbioMinServer: an integrated platform for assessing the safety and functional properties of potential probiotic strains.

Motivation: ProbioMinServer is a platform designed to help researchers access information on probiotics regarding a wide variety of characteristics, such as safety (e.g. antimicrobial resistance, virulence, pathogenic, plasmid, and prophage genes) and functionality (e.g. functional classes, carbohydrate-active enzyme, and metabolite gene cluster profile). Because probiotics are functional foods, their safety and functionality are a crucial part of health care. Genomics has become a crucial methodology for investigating the safety and functionality of probiotics in food and feed. This shift is primarily attributed to the growing affordability of next-generation sequencing technologies. However, no integrated platform is available for simultaneously evaluating probiotic strain safety, investigating probiotic functionality, and identifying known phylogenetically related strains. Results: Thus, we constructed a new platform, ProbioMinServer, which incorporates these functions. ProbioMinServer accepts whole-genome sequence files in the FASTA format. If the query genome belongs to the 25 common probiotic species collected in our database, the server performs a database search and analyzes the core-genome multilocus sequence typing. Front-end applications were implemented in JavaScript with a bootstrap framework, and back-end programs were implemented using PHP, Perl, and Python. ProbioMinServer can help researchers quickly and easily retrieve information on the safety and functionality of various probiotics. Availability and implementation: The platform is available at https://probiomindb.imst.nsysu.edu.tw.

Exploring the Advantages of Quantum Generative Adversarial Networks in Generative Chemistry.

De novo drug design with desired biological activities is crucial for developing novel therapeutics for patients. The drug development process is time- and resource-consuming, and it has a low probability of success. Recent advances in machine learning and deep learning technology have reduced the time and cost of the discovery process and therefore, improved pharmaceutical research and development. In this paper, we explore the combination of two rapidly developing fields with lead candidate discovery in the drug development process. First, artificial intelligence has already been demonstrated to successfully accelerate conventional drug design approaches. Second, quantum computing has demonstrated promising potential in different applications, such as quantum chemistry, combinatorial optimizations, and machine learning. This article explores hybrid quantum-classical generative adversarial networks (GAN) for small molecule discovery. We substituted each element of GAN with a variational quantum circuit (VQC) and demonstrated the quantum advantages in the small drug discovery. Utilizing a VQC in the noise generator of a GAN to generate small molecules achieves better physicochemical properties and performance in the goal-directed benchmark than the classical counterpart. Moreover, we demonstrate the potential of a VQC with only tens of learnable parameters in the generator of GAN to generate small molecules. We also demonstrate the quantum advantage of a VQC in the discriminator of GAN. In this hybrid model, the number of learnable parameters is significantly less than the classical ones, and it can still generate valid molecules. The hybrid model with only tens of training parameters in the quantum discriminator outperforms the MLP-based one in terms of both generated molecule properties and the achieved KL divergence. However, the hybrid quantum-classical GANs still face challenges in generating unique and valid molecules compared to their classical counterparts.

5NosoAE: a web server for nosocomial bacterial antibiogram investigation and epidemiology survey.

5NosoAE is a webserver that can be used for nosocomial bacterial analysis including the identification of similar strains based on antimicrobial resistance profiles (antibiogram) and the spatiotemporal distribution visualization and phylogenetic analysis of identified strains with similar antibiograms. The extensive use of antibiotics has caused many pathogenic bacteria to develop multiple drug resistance, resulting in clinical infection treatment challenges and posing a major threat to global public health. Relevant studies have investigated the key determinants of antimicrobial resistance in the whole-genome sequence of bacteria. However, a web server is currently not available for performing large-scale strain searches according to antimicrobial resistance profiles and visualizing epidemiological information including the spatiotemporal distribution, antibiogram heatmap, and phylogeny of identified strains. Here, we implemented these functions in the new server, referred to as 5NosoAE. This server accepts the genome sequence file in the FASTA format of five nosocomial bacteria, namely Acinetobacter baumannii, Pseudomonas aeruginosa, Klebsiella pneumoniae, Enterococcus faecium and Staphylococcus aureus for query. All visualizations are implemented in JavaScript and PHP. This server will be useful for physicians and epidemiologists involved in research on infectious disease. The 5NosoAE platform is available at https://nosoae.imst.nsysu.edu.tw.

Influence of Ti Content on the Partial Oxidation of TixFeCoNi Thin Films in Vacuum Annealing.

This study investigated the effects of Ti content and vacuum annealing on the microstructure evolution of TixFeCoNi (x = 0, 0.5, and 1) thin films and the underlying mechanisms. The as-deposited thin film transformed from an FCC (face center cubic) structure at x = 0 into an amorphous structure at x = 1, which can be explained by determining topological instability and a hard ball model. After annealing was performed at 1000 °C for 30 min, the films presented a layered structure comprising metal solid solutions and oxygen-deficient oxides, which can be major attributed to oxygen traces in the vacuum furnace. Different Ti contents provided various phase separation and layered structures. The underlying mechanism is mainly related to the competition among possible oxides in terms of free energy production at 1000 °C.

Synthesis of Pt@TiO2@CNTs Hierarchical Structure Catalyst by Atomic Layer Deposition and Their Photocatalytic and Photoelectrochemical Activity.

Pt@TiO2@CNTs hierarchical structures were prepared by first functionalizing carbon nanotubes (CNTs) with nitric acid at 140 °C. Coating of TiO2 particles on the CNTs at 300 °C was then conducted by atomic layer deposition (ALD). After the TiO2@CNTs structure was fabricated, Pt particles were deposited on the TiO2 surface as co-catalyst by plasma-enhanced ALD. The saturated deposition rates of TiO2 on a-CNTs were 1.5 Å/cycle and 0.4 Å/cycle for substrate-enhanced process and linear process, respectively. The saturated deposition rate of Pt on TiO2 was 0.39 Å/cycle. The photocatalytic activities of Pt@TiO2@CNTs hierarchical structures were higher than those without Pt co-catalyst. The particle size of Pt on TiO2@CNTs was a key factor to determine the efficiency of methylene blue (MB) degradation. The Pt@TiO2@CNTs of 2.41 ± 0.27 nm exhibited the best efficiency of MB degradation.