MIST-CF: Chemical Formula Inference from Tandem Mass Spectra.

Chemical formula annotation for tandem mass spectrometry (MS/MS) data is the first step toward structurally elucidating unknown metabolites. While great strides have been made toward solving this problem, the current state-of-the-art method depends on time-intensive, proprietary, and expert-parametrized fragmentation tree construction and scoring. In this work, we extend our previous spectrum Transformer methodology into an energy-based modeling framework, MIST-CF: Metabolite Inference with Spectrum Transformers for Chemical Formula prediction, for learning to rank chemical formula and adduct assignments given an unannotated MS/MS spectrum. Importantly, MIST-CF learns in a data-dependent fashion using a Formula Transformer neural network architecture and circumvents the need for fragmentation tree construction. We train and evaluate our model on a large open-access database, showing an absolute improvement of 10% top 1 accuracy over other neural network architectures. We further validate our approach on the CASMI2022 challenge data set, achieving nearly equivalent performance to the winning entry within the positive mode category without any manual curation or postprocessing of our results. These results demonstrate an exciting strategy to more powerfully leverage MS2 fragment peaks for predicting MS1 precursor chemical formulas with data-driven learning.

A comprehensive review of radioactive pollution treatment of uranium mill tailings.

Natural uranium is a crucial resource for clean nuclear energy, which has brought significant economic and social benefits to humanity. However, the development and utilization of uranium resources have also resulted in the accumulation of vast amounts of uranium mill tailings (UMTs), which pose a potential threat to human health and the ecological environment. This paper reviews the research progress on UMTs treatment technologies, including cover disposal, solidification disposal, backfilling disposal, and bioremediation methods. It is found that cover disposal is a versatile method for the long-term management of UMTs, the engineering performance and durability of the cover system can be improved by choosing suitable stabilizers for the cover layer. Solidification disposal can convert UMTs into solid waste for permanent disposal, but it produces a large amount of waste and requires high operating costs; it is necessary to explore the effectiveness and efficiency of solidification disposal for UMTs, while minimizing the bad environmental impact. Backfilling disposal realizes the resource utilization of solid waste, but the high radon exhalation rate caused by the UMTs backfilling also needs to be considered. Bioremediation methods have low investment costs and are less likely to cause secondary pollution, but the remediation efficiency is low, it can be combined with other treatment technologies to remedy the defects of a single remediation method. The article concludes with key issues and corresponding suggestions for the current UMTs treatment methods, which can provide theoretical guidance and reference for further development and application of radioactive pollution treatment of UMTs.

Response mechanisms of microalgal-bacterial granular sludge to zinc oxide nanoparticles.

Currently, zinc oxide nanoparticles (ZnO-NPs) with their widespread applications lead to their increasing dosages in wastewater, posing an urgent threat to wastewater treatment. Herein, the responses of the emerging microalgal-bacterial granular sludge (MBGS) to ZnO-NPs were investigated. The results showed that the performance of MBGS was significantly affected when the concentration of ZnO-NPs reached 10 mg/L, especially for the removal of ammonia and phosphorus. ZnO-NPs on the granular surface could affect microalgae photosynthesis by shading, while antioxidant enzymes could be generated against overproduced reactive oxygen species. Specifically, ZnO-NPs addition to MBGS systems altered the microbial community structure (e.g. Cyanobacteria) and function (e.g. biosynthesis) of prokaryotes rather than eukaryotes. Overall, the MBGS could exhibit multiple mechanisms to alleviate the ZnO-NPs toxicity. This study is expected to add knowledge on MBGS in the treatment of wastewater containing nanoparticles.