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Abstract: Background and aims: Both drought and vegetation restoration can have dramatic effects on plant community composition, but how they influence soil microbial community diversity, structure, and co-occurrence networks remain less well known. Methods: To better understand the regulatory mechanisms of drought and vegetation restoration on soil microorganisms, we planted 12 native species in precipitation manipulation experimental plots in an invaded coastal grassland in California, USA. We measured soil bacterial and fungal community composition by amplicon sequencing, and quantified plant species richness and coverage in the third experimental year. Results: Our results showed that drought significantly altered soil bacterial diversity and composition; however, neither drought nor vegetation restoration had significant effects on fungal diversity and composition. The control plots had the most cooperative interactions (greatest number of correlations) among bacterial and/or fungal species, while drought plots yielded the most complex co-occurrence network with the highest modularity and clustering coefficient. Structural equation modeling revealed that plant species richness, net gains, and soil moisture played dominant roles in shaping bacterial community structure. Drought and bacterial community structure directly affected fungal community structure. Plant dominant species cover, common species cover, and bacterial diversity were the key drivers in regulating the microbial co-occurrence network complex. Conclusion: We conclude that soil bacterial and fungal communities differ in their responses to abiotic and biotic environmental changes, which may weaken the interspecies interactions among soil microorganisms.

In order to improve soy sauce koji making technology and to stabilize its quality, high-throughput sequencing and headspace solid-phase microextraction coupled with gas chromatography-mass spectrometry (HS-SPME-GC-MS) were used to analyze the microbial community succession and the changes of total acid, moisture, protease, glucoamylase, amylase and volatile flavor substances during the fermentation of soy sauce koji, and the correlation between microbial community succession and volatile flavor substances was investigated. The results showed that 10 bacterial genera with relative abundance greater than 1% including Weissella, Staphylococcus and Lactobacillus, and three fungal genera with relative abundance greater than 1% including Kodamaea, Aspergillus and Candida were identified, with Weissella, Kodamaea and Aspergillus being dominant throughout the whole fermentation period. With the increase in fermentation time, the moisture content decreased, the total acid content and the activities of protease, amylase and glucoamylase increased, and the total content of volatile flavor substances showed an increasing trend, reaching 4 381.31 μg/100 g at the end of fermentation (48 h). Correlation analysis showed that dominant microorganisms, such as Weissella, Lactobacillus and Kodamaea, affected the activities of protease, glucoamylase and amylase, and significantly influenced the formation of various volatile flavor substances, such as alcohols, aldehydes, esters, acids and pyrazines. This study provides a scientific basis and theoretical foundation for the improvement of the quality of soy sauce koji and the development of koji making technology.

Purposes How to perform bias-correction for precipitation data based on terrain information has been an important problem in meteorological big data research. However, the existing precipitation terrain-based bias-correction methods mostly suffer from two limitations. First, most of them are designed based on statistical models or conventional machine learning models, thus fails to go beyond to the deep learning models with more powerful feature learning ability. Second, they also lack the ability to incorporate the spatiotemporal correlation information in meteorological data for enhancing the bias-correction quality. Methods To address these limitations, in this paper, a terrain-based bias-correction method for precipitation data based on deep learning and spatiotemporal correlation modeling is presented. First, the precipitation data and multi-source terrain information with alignment and encoding based on the longitude and latitude are preprocessed, and thus the corresponding data matrices are constructed. Then the precipitation and terrain data in the spatial and temporal neighborhood of each grid are adopted to achieve the multi-source spatiotemporal information modeling, and a down-sampling strategy is used to alleviate the imbalance between the precipitation grids and the non-precipitation grids. Finally, the deep neural network is constructed for regression and bias-correction. The experiments are conducted on the real meteorological data from over 4 000 meteorological observation stations and over 150 thousand meteorological grids in Guangdong Province. Findings Experimental results have verified the significance influence of the spatiotemporal modeling strategy over precipitation bias correction quality and performance advantage of the proposed method over the baseline methods.

CD44 is associated with a high risk of metastasis, recurrence, and drug resistance in various cancers. Here we report that platelet endothelial aggregation receptor 1 (PEAR1) is a CD44 chaperone protein that protected CD44 from endocytosis-mediated degradation and enhances cleavage of the CD44 intracellular domain (CD44-ICD). Furthermore, we found that lysyl oxidase-like protein 2 (LOXL2), an endogenous ligand of PEAR1, bound to the PEAR1-EMI domain and facilitated the interaction between PEAR1 and CD44 by inducing PEAR1 Ser891 phosphorylation in a manner that was independent of its enzyme activity. Levels of PEAR1 protein and PEAR1 phosphorylation at Ser891 were increased in patients with triple-negative breast cancer (TNBC), were positively correlated with expression of LOXL2 and CD44, and were negatively correlated with overall survival. The level of PEAR1 Ser891 phosphorylation was identified as the best independent prognostic factor in TNBC patients. The prognostic efficacy of the combination of PEAR1 phosphorylation at Ser891 and CD44 expression was superior to that of PEAR1 phosphorylation at Ser891 alone. Blocking the interaction between LOXL2 and PEAR1 with monoclonal antibodies significantly inhibited TNBC metastasis, representing a promising therapeutic strategy for TNBC., Introduction Breast cancer is the most prevalent malignancy in women, and its incidence is increasing (1). Of particular concern is triple-negative breast cancer (TNBC), which is an exceptionally aggressive and [...]

Due to the limitation of inherent ultra-high electron concentration, the electrical properties of In2O3 resemble those of conductors rather than semiconductors prior to special treatment. In this study, the effect of various annealing treatments on the microstructure, optical properties, and oxygen vacancies of the films and transistors is systematically investigated. Our finding reveals a progressive crystallization trend in the films with increasing annealing temperature. In addition, a higher annealing temperature is also associated with the reduction in the concentration of oxygen vacancies, as well as an elevation in both optical transmittance and optical bandgap. Furthermore, with the implementation of annealing process, the devices gradually transform from no pronounced gate control to exhibit with excellent gate control and electrical performances. The atomic layer deposited Hf-doped In2O3 thin film transistor annealed at 250 °C exhibits optimal electrical properties, with a field-effect mobility of 18.65 cm2 V−1 s−1, a subthreshold swing of 0.18 V/dec, and an Ion/Ioff ratio of 2.76 × 106. The results indicate that the impact of varying annealing temperatures can be attributed to the modulation of oxygen vacancies within the films. This work serves as a complementary study for the existing post-treatment of oxide films and provides a reliable reference for utilization of the annealing process in practical applications. [ABSTRACT FROM AUTHOR]

Following a large-scale radiological event, timely collection of samples from all potentially exposed individuals may be precluded, and high-throughput bioassays capable of rapid and individualized dose assessment several days post-exposure will be essential for population triage and efficient implementation of medical treatment. The objective of this work was to validate the performance of a biomarker panel of radiosensitive intracellular leukocyte proteins (ACTN1, DDB2, and FDXR) and blood cell counts (CD19+ B-cells and CD3+ T-cells) for retrospective classification of exposure and dose estimation up to 7 days post-exposure in an in-vivo C57BL/6 mouse model. Juvenile and adult C57BL/6 mice of both sexes were total body irradiated with 0, 1, 2, 3, or 4 Gy, peripheral blood was collected 1, 4, and 7-days post-exposure, and individual blood biomarkers were quantified by imaging flow cytometry. An ensemble machine learning platform was used to identify the strongest predictor variables and combine them for biodosimetry outputs. This approach generated successful exposure classification (ROC AUC = 0.94, 95% CI: 0.90–0.97) and quantitative dose reconstruction (R2 = 0.79, RMSE = 0.68 Gy, MAE = 0.53 Gy), supporting the potential utility of the proposed biomarker assay for determining exposure and received dose in an individual. [ABSTRACT FROM AUTHOR]

After a large-scale radiological or nuclear event, hundreds of thousands of people may be exposed to ionizing radiation and require subsequent medical management. Acute exposure to moderate doses (2–6 Gy) of radiation can lead to the hematopoietic acute radiation syndrome, in which the bone marrow (BM) is severely compromised, and severe hemorrhage and infection are common. Previously, we have developed a panel of intracellular protein markers (FDXR, ACTN1, DDB2, BAX, p53 and TSPYL2), designed to reconstruct absorbed radiation dose from human peripheral blood (PB) leukocyte samples in humanized mice up to 3 days after exposure. The objective of this work was to continue to use the humanized mouse model to evaluate biomarker dose-/ time- kinetics in human PB leukocytes in vivo, at an earlier (day 2) and later (day 7) time point, after exposure to total-body irradiation (TBI) doses of 0 to 2 Gy of X rays. In addition, to assess hematological sensitivity and radiation-induced injury, PB leukocyte cell counts, human BM hematopoietic stem cell (HSC) and progenitor cell [multipotent progenitor (MPP), common myeloid progenitor (CMP), granulocyte myeloid progenitor (GMP), megakaryocyte/erythrocyte progenitor (MEP) and multi-lymphoid progenitor (MLP)] levels were measured, and their correlation was also examined as the BM damages are difficult to assess by routine tests. Peripheral blood B-cells were significantly lower after TBI doses of 0.5 Gy on day 2 and 2 Gy on days 2 and 7; T-cells were significantly reduced only on day 2 after 2 Gy TBI. Bone marrow HSCs and MPP cells showed a dose-dependent depletion after irradiation with 0.5 Gy and 2 Gy on day 2, and after 1 Gy and 2 Gy on day 7. Circulating B cells correlated with HSCs, MPP and MLP cells on day 2, whereas T cells correlated with MPP, and myeloid cells correlated with MLP cells. On day 7, B cells correlated with MPP, CMP, GMP and MEP, while myeloid cells correlated with CMP, GMP and MEP. The intracellular leukocyte biomarkers were able to discriminate unirradiated and irradiated samples at different time points calculated by receiver operating characteristic (ROC) curve. Using machine learning algorithm methods, combining ACTN1, p53, TSPYL2 and PBT cell and PB-B cell counts served as a strong predictor (area under the ROC >0.8) to distinguish unirradiated and irradiated samples independent of the days after TBI. The results further validated our biomarker-based triage assay and additionally evaluated the radiation sensitivity of the hematopoietic system after TBI exposures. [ABSTRACT FROM AUTHOR]

To improve the quality of summer-autumn tea, the fermentation of summer-autumn tea was investigated by using Eurotium cristatum. The contents of tea polyphenols, total free amino acids, total flavonoids, water leachate, and sensory scores of summer-autumn tea were used as the indicators for the one-way experiment, and four factors and three levels were selected for orthogonal experiments to optimize the fermentation process. The volatile compounds of fermented summer-autumn tea under the optimal process were analyzed by gas chromatography-mass spectrometry (GC-MS) technology. The results showed that the optimal fermentation process was 30% water content, 15% inoculum of Eurotium cristatum, fermentation time of 9 d, and fermentation temperature of 30 °C, and the water leachate content of summer-autumn tea processed under these conditions was significantly increased by 22.51% (P<0.05), the tea polyphenol content was significantly decreased by 27.71% (P<0.05), and the total flavonoid content was significantly decreased by 6.41% (P<0.01), free amino acids did not change significantly, and the sensory score was significantly improved by 10.33 points (P<0.01). In addition, the total amount of flavor compounds was elevated by 296.76% after fermentation, and the content of linalool, linalool oxide I, α-Terpineol, methyl salicylate, and phenethyl acetate substances increased especially significantly throughout the fermentation process, which brought rich fruity and floral aroma to the summer-autumn tea. Thus, the overall quality of summer-autumn tea improved after fermentation treatment. [ABSTRACT FROM AUTHOR]

In order to investigate the quality differences of cigar tobacco leaves from Yunnan production areas, microbial community structure, free amino acids and volatile flavor compounds of cigar tobacco leaves produced in Yunnan province were analyzed by high-throughput sequencing and metabolomics. O2PLS analysis and correlation analysis were used to systematically reveal the relationship between microorganisms of origin and tobacco flavor quality, and to identify functional microorganisms and synergistic taxa in tobacco. The results showed that there were differences in the microbial community structure of cigar tobacco leaves produced in Yunnan province, in which the dominant bacteria were mainly Aerococcus, Staphylococcus and Corynebacterium, and the dominant fungi were mainly Aspergillus, Cladosporium and Alternaria. 17 free amino acids were detected, and the overall amino acid content showed that Asp was the highest and Met was the lowest, with higher TAV Asp and Glu contributed more to its flavor presentation. The free amino acid flavor profiles of Lincang Yunxue No. 2 and Pu'er Yunxue No. 2 cigar tobacco leaves was more prominent. A total of 65 volatile flavor compounds were detected, mainly ketones, among which 16 different flavor compounds, including 6-Methyl-5-hepten-2-one, ß-Damascone, Phenylethyl alcohol, Decanal, and Dihydroactinidiolide, played an important role in the formation of its flavor. The overall flavor characteristics of Pu'er No. 2 were more prominent. Sphingomonas, Staphylococcus, Pseudomonas, and Oceanobacillus acted synergistically to contribute to cigar tobacco leaves flavor formation, while the relative abundance of Penicillium was negatively correlated with tobacco quality. [ABSTRACT FROM AUTHOR]