Mycobiome mediates the interaction between environmental factors and mycotoxin contamination in wheat grains.

Environmental factors significantly impact grain mycobiome assembly and mycotoxin contamination. However, there is still a lack of understanding regarding the wheat mycobiome and the role of fungal communities in the interaction between environmental factors and mycotoxins. In this study, we collected wheat grain samples from 12 major wheat-producing provinces in China during both the harvest and storage periods. Our aim was to evaluate the mycobiomes in wheat samples with varying deoxynivalenol (DON) contamination levels and to confirm the correlation between environmental factors, the wheat mycobiome, and mycotoxins. The results revealed significant differences in the wheat mycobiome and co-occurrence network between contaminated and uncontaminated wheat samples. Fusarium was identified as the main differential taxon responsible for inducing DON contamination in wheat. Correlation analysis identified key factors affecting mycotoxin contamination. The results indicate that both environmental factors and the wheat mycobiome play significant roles in the production and accumulation of DON. Environmental factors can affect the wheat mycobiome assembly, and wheat mycobiome mediates the interaction between environmental factors and mycotoxin contamination. Furthermore, a random forest (RF) model was developed using key biological indicators and environmental features to predict DON contamination in wheat with accuracies exceeding 90 %. The findings provide data support for the accurate prediction of mycotoxin contamination and lay the foundation for the research on biological control technologies of mycotoxin through the assembly of synthetic microbial communities.

Temporal and spatial variation of microbial communities in stored rice grains from two major depots in China.

Microbial activity in stored rice grains could cause quality deterioration and mycotoxin accumulation that may lead to serious economic losses and food safety risks. However, limited studies have examined the spatial and temporal variation of microbial communities associated with stored rice grains. Here, we performed amplicon sequence analysis to investigate the temporal and spatial distribution of microbes in stored rice grains from Chongqing grain depot (Southern China) and Liaoning grain depot (Northern China). Bacterial and fungal diversities, in addition to community structures of rice grains in Chongqing were significantly different from those in Liaoning in terms of α diversity (Chongqing > Liaoning, p <001) and ß diversity (p < 0.001, bacterial communities: R = 0.9293, fungal communities: R = 1.0). The core bacterial taxa among stored rice grains comprised Pantoea, Pseudomonas, Rhizobium, and Methylobacterium, while the core fungal taxa comprised Alternaria, Aspergillus, and Cladosporium. In addition, different microbial communities were observed at different stored time points (i.e., post-harvest period, storage for one year, and storage for two years), and along different stored vertical depths (upper, middle, and lower layers) within the Chinese horizontal warehouse. The relative abundances of Aspergillus increased over storage time, but decreased with the increase of stored vertical depth within the warehouse. Temperature was the most important factor associated with differences in microbial communities across storage periods. The potential mycotoxin producing fungal species A. flavus and A. niger exhibited significantly higher abundances in rice grains of Chongqing compared to those of Liaoning. These data could be useful for evaluating potential risks of toxigenic fungi and mycotoxin contamination of stored rice grains. Further, these insights can help grain depot managers optimize storage conditions and reduce risks of deleterious fungi during rice grains storage.

Applying meta-data of soybean grain in origin trace and quarantine inspection.

Soybean and derived products are among the most important food for both humans and animals. China is the world's largest importer of soybeans, with more than 100 million tons of annual imports, mainly from the United States of America (US), Brazil, and Argentina. However, there have been limited studies on the microbiota associated with imported soybean grains. Here, we reveal the soybean microbiota using amplicon sequencing based on samples from four countries on three continents of North America (US), South America (Argentina, Brazil), and Asia (China). Our results showed that the soybean-associated microbiota from different continents significantly separated, presenting strong geographic variations. The core microbial taxa and geographically specified taxa were defined, with Alternaria, Enterobacter, Plectosphaerella, Stenotrophomanas, and Xeromyces defined as the core microbiota for soybean from Asia; Amanita, Aspergillus, Fusarium, Nigrospora, Herbiconiux, Pseudomonas, Saccharopolyspora, and Schumannella from North America; and Bradyrhizobium, Colletotrichum, Filobasidium, Phialosimplex, Mycosphaerella, Septoria, Sphingomonas, and Weissalla, from South America. In addition, we build the Random Forest (RF) model to predict the source of imported soybean grains. We could accurately predict the original countries of imported soybean grains within the RF prediction models, with accuracies greater than 95 %. We constructed a database of soybean-related quarantine pathogens using full-length sequences of fungal ITS region and bacterial 16S rDNA region. Two phytopathogenic fungi, Diaporthe caulivora and Cladosporium cucumerinum, listed in the Chinese quarantine catalog, were intercepted through metabarcoding sequencing. The former was further confirmed using an available national standard protocol of qPCR diagnosis. In summary, our NGS-based approach revealed the microbiota associated with soybeans. It could provide comprehensive information and valuable method on the trace the origin of soybean and detection of quarantine pathogens at Customs and departments of inspection and quarantine.

Association of glioma CD44 expression with glial dynamics in the tumour microenvironment and patient prognosis.

Because of the heterogeneity of lower-grade gliomas (LGGs), patients show various survival outcomes that are not reliably predicted by histological classification. The tumour microenvironment (TME) contributes to the initiation and progression of brain LGGs. Identifying potential prognostic markers based on the immune and stromal components in the TME will provide new insights into the dynamic modulation of these two components of the TME in LGGs. We applied ESTIMATE to calculate the ratio of immune and stromal components from The Cancer Genome Atlas database. After combined differential gene expression analysis, protein-protein interaction network construction and survival analysis, CD44 was screened as an independent prognostic factor and subsequently validated utilizing data from the Chinese Glioma Genome Atlas database. To decipher the association of glioma cell CD44 expression with stromal cells in the TME and tumour progression, RT-qPCR, cell viability and wound healing assays were employed to determine whether astrocytes enhance glioma cell viability and migration by upregulating CD44 expression. Surprisingly, M1 macrophages were identified as positively correlated with CD44 expression by CIBERSORT analysis. CD44+ glioma cells were further suggested to interact with microglia-derived macrophages (M1 phenotype) via osteopontin signalling on the basis of single-cell sequencing data. Overall, we found that astrocytes could elevate the CD44 expression level of glioma cells, enhancing the recruitment of M1 macrophages that may promote glioma stemness via osteopontin-CD44 signalling. Thus, glioma CD44 expression might coordinate with glial activities in the TME and serve as a potential therapeutic target and prognostic marker for LGGs.

Investigating the Causal Relationship Between Physical Activity and Chronic Back Pain: A Bidirectional Two-Sample Mendelian Randomization Study.

Background: Recent observational studies have reported a negative association between physical activity and chronic back pain (CBP), but the causality of the association remains unknown. We introduce bidirectional Mendelian randomization (MR) to assess potential causal inference between physical activity and CBP. Materials and Methods: This two-sample MR used independent genetic variants associated with physical activity and CBP as genetic instruments from large genome-wide association studies (GWASs). The effects of both directions (physical activity to CBP and CBP to physical activity) were examined. Inverse variance-weighted meta-analysis and alternate methods (weighted median and MR-Egger) were used to combine the MR estimates of the genetic instruments. Multiple sensitivity analyses were conducted to examine the robustness of the results. Results: The MR set parallel GWAS cohorts, among which, those involved in the primary analysis were comprised of 337,234 participants for physical activity and 158,025 participants (29,531 cases) for CBP. No evidence of a causal relationship was found in the direction of physical activity to CBP [odds ratio (OR), 0.98; 95% CI, 0.85-1.13; p = 0.81]. In contrast, a negative causal relationship in the direction of CBP to physical activity was detected (ß = -0.07; 95% CI, -0.12 to -0.01; p = 0.02), implying a reduction in moderate-vigorous physical activity (approximately 146 MET-minutes/week) for participants with CBP relative to controls. Conclusion: The negative relationship between physical activity and CBP is probably derived from the reduced physical activity of patients experiencing CBP rather than the protective effect of physical activity on CBP.

Stretchable Micromotion Sensor with Enhanced Sensitivity Using Serpentine Layout.

The application of the serpentine mesh layout in stretchable electronics provides a feasible method to achieve the desired stretchability by structural design instead of modifying the intrinsic mechanical properties of the applied materials. However, previous works using the serpentine layout mainly focused on the optimization of structural stretchability. In this paper, the serpentine mesh design concept is used to transform the high-performance but hard-to-stretch piezoelectric film into a stretchable form. The serpentine layout design strategies for the piezoelectric film, which aim at not only desired stretchability but also high utilization of the strain in the piezoelectric film during deformation, are discussed with experimental and computational results. A stretchable micromotion sensor with high sensitivity is realized using the piezoelectric film with a serpentine layout. Human voice recognition applications of the sensor, including speech pattern recognition with machine learning, are demonstrated with the sensor integrated with a wireless module. The stretchable micromotion sensor with a serpentine layout illustrates the broader application of serpentine layout design in the functional materials of stretchable electronics, which can further extend the range of available functional materials for novel stretchable electronic devices.