Metagenomic analysis of core differential microbes between traditional starter and Round-Koji-mechanical starter of Chi-flavor Baijiu.

Xiaoqu starter serves as the saccharifying and fermenting agent in the production of Cantonese soybean-flavor (Chi-flavor) Baijiu, and the complex microbial communities determine the flavor and quality of the product. Round-Koji-mechanical starter (produced by using an automated starter-making disk machine) is advantageous as it decreases operator influence, labor costs, and fermentation time, but the product quality is lower compared to traditional starter. Thus, two types of starters (traditional and Round-Koji-mechanical starter) from a Cantonese Baijiu factory were compared in a metagenomic analysis to investigate the differences in microbial community composition and core microbes. The results showed that several core microbes related to carbohydrate metabolism, amino acid metabolism and lipid metabolism, were differentially enriched in the traditional starter. Mucor lusitanicus and Rhizopus delemar were significantly positively correlated with the three key metabolic pathways. Saccharomyces cerevisiae, Cyberlindnera fabianii, Kluyveromyces marxianus, Lactobacillus fermentum, Mucor ambiguous, Rhizopus microspores, Rhizopus azygosporus, Mucor circinelloides, and Ascoidea rubescens were significantly positively correlated with two of the three key metabolic pathways. The results of this study provide a basis for understanding the differential core microbes in traditional and Round-Koji-mechanical starters of Chi-flavor Baijiu, and they also provide guidance for improving Round-Koji-mechanical starter.

Progress on Two-Dimensional Transitional Metal Dichalcogenides Alloy Materials: Growth, Characterisation, and Optoelectronic Applications.

Two-dimensional (2D) transitional metal dichalcogenides (TMDs) have garnered remarkable attention in electronics, optoelectronics, and hydrogen precipitation catalysis due to their exceptional physicochemical properties. Their utilisation in optoelectronic devices is especially notable for overcoming graphene's zero-band gap limitation. Moreover, TMDs offer advantages such as direct band gap transitions, high carrier mobility, and efficient switching ratios. Achieving precise adjustments to the electronic properties and band gap of 2D semiconductor materials is crucial for enhancing their capabilities. Researchers have explored the creation of 2D alloy phases through heteroatom doping, a strategy employed to fine-tune the band structure of these materials. Current research on 2D alloy materials encompasses diverse aspects like synthesis methods, catalytic reactions, energy band modulation, high-voltage phase transitions, and potential applications in electronics and optoelectronics. This paper comprehensively analyses 2D TMD alloy materials, covering their growth, preparation, optoelectronic properties, and various applications including hydrogen evolution reaction catalysis, field-effect transistors, lithium-sulphur battery catalysts, and lasers. The growth process and characterisation techniques are introduced, followed by a summary of the optoelectronic properties of these materials.

Applications and Advances in Machine Learning Force Fields.

Force fields (FFs) form the basis of molecular simulations and have significant implications in diverse fields such as materials science, chemistry, physics, and biology. A suitable FF is required to accurately describe system properties. However, an off-the-shelf FF may not be suitable for certain specialized systems, and researchers often need to tailor the FF that fits specific requirements. Before applying machine learning (ML) techniques to construct FFs, the mainstream FFs were primarily based on first-principles force fields (FPFF) and empirical FFs. However, the drawbacks of FPFF and empirical FFs are high cost and low accuracy, respectively, so there is a growing interest in using ML as an effective and precise tool for reconciling this trade-off in developing FFs. In this review, we introduce the fundamental principles of ML and FFs in the context of machine learning force fields (MLFF). We also discuss the advantages and applications of MLFF compared to traditional FFs, as well as the MLFF toolkits widely employed in numerous applications.

Mollicellins S-U, three new depsidones from Chaetomium brasiliense SD-596 with anti-MRSA activities.

Fungi are important resources for drug development, as they have a diversity of genes, that can produce novel secondary metabolites with effective bioactivities. Here, five depsidone-based analogs were isolated from the rice media of Chaetomium brasiliense SD-596. Their structures were elucidated using NMR and mass spectrometry analysis. Five compounds, including three new depsidone analogs, mollicellin S (1), mollicellin T (2), and mollicellin U (3), and two known compounds, mollicellin D (4) and mollicellin H (5), exhibited significant inhibition against Staphylococcus aureus and methicillin-resistant Staphylococcus aureus (MRSA), with MIC values ranging from 6.25 to 12.5 µg ml-1. Herein, we identified the predicted plausible biosynthetic cluster of the compounds and discussed the structure-activity relationship. Finally, we found that the introduction of aldehyde and methoxyl groups provide marked improvement for the inhibition against MRSA.

Neuroprotective agents for neonatal hypoxic-ischemic brain injury.

Hypoxic-ischemic (H-I) brain injury in newborns is a major cause of morbidity and mortality that claims thousands of lives each year. In this review, we summarize the promising neuroprotective agents tested on animal models and pilot clinical studies of neonatal H-I brain injury according to the different phases of the disease. These agents target various phases of injury including the early phase of excitotoxicity, oxidative stress and apoptosis as well as late-phase inflammatory reaction and neural repair. We analyze the cell survival and cell death pathways modified by these agents in neonatal H-I brain injury. We aim to 'build a bridge' between animal trials of neuroprotective agents and potential candidate treatments for future clinical applications against H-I encephalopathy.