Materials Informatics Transformer: A Language Model for Interpretable Materials Properties Prediction

Recently, the remarkable capabilities of large language models (LLMs) have been illustrated across a variety of research domains such as natural language processing, computer vision, and molecular modeling. We extend this paradigm by utilizing LLMs for material property prediction by introducing our model Materials Informatics Transformer (MatInFormer). Specifically, we introduce a novel approach that involves learning the grammar of crystallography through the tokenization of pertinent space group information. We further illustrate the adaptability of MatInFormer by incorporating task-specific data pertaining to Metal-Organic Frameworks (MOFs). Through attention visualization, we uncover the key features that the model prioritizes during property prediction. The effectiveness of our proposed model is empirically validated across 14 distinct datasets, hereby underscoring its potential for high throughput screening through accurate material property prediction

Isolation of starch and protein degrading strain Bacillus subtilis FYZ1-3 from tobacco waste and genomic analysis of its tolerance to nicotine and inhibition of fungal growth

Aerobic fermentation is an effective technique for the large-scale processing of tobacco waste. However, the specificity of the structure and composition of tobacco-derived organic matter and the toxic alkaloids in the material make it currently difficult to directly use microbial agents. In this study, a functional strain FYZ1-3 was isolated and screened from thermophilic phase samples of tobacco waste composting. This strain could withstand temperatures as high as 80°C and grow normally at 0.6% nicotine content. Furthermore, it had a strong decomposition capacity of tobacco-derived starch and protein, with amylase activity of 122.3  U/mL and protease activity and 52.3  U/mL, respectively. To further understand the mechanism of the metabolic transformation of the target, whole genome sequencing was used and the secondary metabolite gene cluster was predicted. The inhibitory effect of the strain on common tobacco fungi was verified using the plate confrontation and agar column methods. The results showed that the strain FYZ1-3 was Bacillus subtilis, with a genome size of 4.17  Mb and GC content of 43.68%; 4,338 coding genes were predicted. The genome was annotated and analyzed using multiple databases to determine its ability to efficiently degrade starch proteins at the molecular level. Moreover, 14 functional genes related to nicotine metabolism were identified, primarily located on the distinct genomic island of FYZ1-3, giving a speculation for its nicotine tolerance capability on the molecular mechanism. By mining the secondary metabolite gene cluster prediction, we found potential synthetic bacteriocin, antimicrobial peptide, and other gene clusters on its chromosome, which may have certain antibacterial properties. Further experiments confirmed that the FYZ1-3 strain was a potent growth inhibitor of Penicillium chrysogenum, Aspergillus sydowii, A. fumigatus, and Talaromyces funiculosus. The creation and industrial use of the functional strains obtained in this study provide a theoretical basis for its industrial use, where it would be of great significance to improve the utilization rate of tobacco waste

Genetic identification and expression optimization of a novel protease HapR from Bacillus velezensis

Due to the broad application and substantial market demand for proteases, it was vital to explore the novel and efficient protease resources. The aim of this study was to identify the novel protease for tobacco protein degradation and optimize the expression levels. Firstly, the tobacco protein was used as the sole nitrogen resource for isolation of protease-producing strains, and a strain with high protease production ability was obtained, identified as Bacillus velezensis WH-7. Then, the whole genome sequencing was conducted on the strain B. velezensis WH-7, and 7 proteases genes were mined by gene annotation analysis. By further heterologous expression of the 7 protease genes, the key protease HapR was identified with the highest protease activity (144.19 U/mL). Moreover, the catalysis mechanism of HapR was explained by amino acid sequence analysis. The expression levels of protease HapR were further improved through optimization of promoter, signal peptide and host strain, and the maximum protease activity reaced 384.27 U/mL in WX-02/pHY-P43-SPyfkD-hapR, increased by 167% than that of initial recombinant strain HZ/pHY-P43-SPhapR-hapR. This study identified a novel protease HapR and the expression level was significantly improved, which provided an important enzyme resource for the development of enzyme preparations in tobacco protein degradation

Genomic analyses provide insights into peach local adaptation and responses to climate change

The environment has constantly shaped plant genomes, but the genetic bases underlying how plants adapt to environmental influences remain largely unknown. We constructed a high-density genomic variation map of 263 geographically representative peach landraces and wild relatives. A combination of whole-genome selection scans and genome-wide environmental association studies (GWEAS) was performed to reveal the genomic bases of peach adaptation to diverse climates. A total of 2092 selective sweeps that underlie local adaptation to both mild and extreme climates were identified, including 339 sweeps conferring genomic pattern of adaptation to high altitudes. Using genome-wide environmental association studies (GWEAS), a total of 2755 genomic loci strongly associated with 51 specific environmental variables were detected. The molecular mechanism underlying adaptive evolution of high drought, strong UVB, cold hardiness, sugar content, flesh color, and bloom date were revealed. Finally, based on 30 yr of observation, a candidate gene associated with bloom date advance, representing peach responses to global warming, was identified. Collectively, our study provides insights into molecular bases of how environments have shaped peach genomes by natural selection and adds candidate genes for future studies on evolutionary genetics, adaptation to climate changes, and breeding.info:eu-repo/semantics/publishedVersio

CdSe Quantum Dot (QD)-Induced Morphological and Functional Impairments to Liver in Mice

Quantum dots (QDs), as unique nanoparticle probes, have been used in in vivo fluorescence imaging such as cancers. Due to the novel characteristics in fluorescence, QDs represent a family of promising substances to be used in experimental and clinical imaging. Thus far, the toxicity and harmful health effects from exposure (including environmental exposure) to QDs are not recognized, but are largely concerned by the public. To assess the biological effects of QDs, we established a mouse model of acute and chronic exposure to QDs. Results from the present study suggested that QD particles could readily spread into various organs, and liver was the major organ for QD accumulation in mice from both the acute and chronic exposure. QDs caused significant impairments to livers from mice with both acute and chronic QD exposure as reflected by morphological alternation to the hepatic lobules and increased oxidative stress. Moreover, QDs remarkably induced the production of intracellular reactive oxygen species (ROS) along with cytotoxicity, as characterized by a significant increase of the malondialdehyde (MDA) level within hepatocytes. However, the increase of the MDA level in response to QD treatment could be partially blunted by the pre-treatment of cells with beta-mercaptoethanol (β-ME). These data suggested ROS played a crucial role in causing oxidative stress-associated cellular damage from QD exposure; nevertheless other unidentified mediators might also be involved in QD-mediated cellular impairments. Importantly, we demonstrated that the hepatoxicity caused by QDs in vivo and in vitro was much greater than that induced by cadmium ions at a similar or even a higher dose. Taken together, the mechanism underlying QD-mediated biological influences might derive from the toxicity of QD particles themselves, and from free cadmium ions liberated from QDs as well

Effect of live poultry market interventions on influenza A(H7N9) virus, Guangdong, China

Since March 2013, three waves of human infection with avian influenza A(H7N9) virus have been detected in China. To investigate virus transmission within and across epidemic waves, we used surveillance data and whole-genome analysis of viruses sampled in Guangdong during 2013–2015. We observed a geographic shift of human A(H7N9) infections from the second to the third waves. Live poultry market interventions were undertaken in epicenter cities; however, spatial phylogenetic analysis indicated that the third-wave outbreaks in central Guangdong most likely resulted from local virus persistence rather than introduction from elsewhere. Although the number of clinical cases in humans declined by 35% from the second to the third waves, the genetic diversity of third-wave viruses in Guangdong increased. Our results highlight the epidemic risk to a region reporting comparatively few A(H7N9) cases. Moreover, our results suggest that live-poultry market interventions cannot completely halt A(H7N9) virus persistence and dissemination

The maximal subgroups of Sylow subgroups and the structure of finite groups

In this paper we investigate the influence of some subgroups of Sylow subgroups with semi cover-avoiding property and $E$-supplementation on the structure of finite groups. Some recent results are generalized and unified