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Background The nutrient availability of roughages could affect the dietary utilization efficiency of ruminants even in isocaloric and isonitrogenous diets. Here, we analyzed the bacterial composition and their metabolic pathways in the gastrointestinal tracts (GITs) of Hu sheep fed with wheat straw (WS) instead of alfalfa (AL) in isocaloric and isonitrogenous diets, trying to explore the reasons from the perspective of GITs bacterial network structure changes. Results We employed 16S rRNA gene sequencing in combination with the Kruskal–Wallis test, Spearman correlation analysis, and other statistical methods to describe the microbiota composition in the GITs of Hu sheep. The results showed after the roughage was replaced from AL to WS, the most positive response occurred in the rumen microbiota, resulting in a more obvious microbiological and functional redundancy phenomenon. Whereas extended biogeographic studies of the GITs bacterial community found opposite results for the hindgut microbiota and metabolism networks compared to the forestomach. The abundance of fiber-degrading bacteria such as Prevotella , Oscillospiraceae NK4A214 group , and Treponema was significantly increased in GITs, but low-efficiency crude fiber degradation inhibited energy use efficiency, the pentose phosphate pathway, gluconeogenesis, and volatile acid synthesis. In addition, dietary shifting from AL to WS decreased the abundance of beneficial bacteria such as the Lachnospiraceae NK3A20 group and Alistipes , thereby enhancing the underlying inflammatory response. Conclusions These findings suggest that feeding untreated WS affected the structure and function of the bacterial network in the GITs due to limited total digestible nutrients, and in particular increases the complexity of the rumen bacterial network, and limit the abundance of bacteria involved in the crude fiber degradation in the hindgut.

Event cameras which transmit per-pixel intensity changes have emerged as a promising candidate in applications such as consumer electronics, industrial automation, and autonomous vehicles, owing to their efficiency and robustness. To maintain these inherent advantages, the trade-off between efficiency and accuracy stands as a priority in event-based algorithms. Thanks to the preponderance of deep learning techniques and the compatibility between bio-inspired spiking neural networks and event-based sensors, data-driven approaches have become a hot spot, which along with the dedicated hardware and datasets constitute an emerging field named event-based data-driven technology. Focusing on data-driven technology in event-based vision, this paper first explicates the operating principle, advantages, and intrinsic nature of event cameras, as well as background knowledge in event-based vision, presenting an overview of this research field. Then, we explain why event-based data-driven technology becomes a research focus, including reasons for the rise of event-based vision and the superiority of data-driven approaches over other event-based algorithms. Current status and future trends of event-based data-driven technology are presented successively in terms of hardware, datasets, and algorithms, providing guidance for future research. Generally, this paper reveals the great prospects of event-based data-driven technology and presents a comprehensive overview of this field, aiming at a more efficient and bio-inspired visual system to extract visual features from the external environment.

In this study, thin-film thermocouples (TFTCs) were combined with a smart bolt to design a smart bolt that can directly test high temperature in service monitoring and parameter calculation for gas turbine structure design. The first-principles calculation was used to analyze the design of the surface properties of nickel-based alloys and insulating layers, and finite element analysis was used to optimize dimension parameters by controlling the thermal stress matching of insulating layers and sensitive layers. The effect of the glass powder with different particle sizes on the microstructure of the ITO and In2O3 films was studied via SEM. The preferred particle size of the additive glass powder is 400 nm. The XRD pattern shows the (222) peak has the highest intensity. The intensities of the (222) and (622) peaks increase after the heat treatment. The calibration results show that the average Seebeck coefficient of the TFTCs can reach 64.9 μV/°C at 1100 °C with a maximum voltage of 71.4 mV. The repeatability error of the cycles of the sensor after heat treatment is ±1.05%. The repeatability of the sensor is up to 98.95%. The smart bolts were tested for application in small aero engines. It can be seen that under the impact of 1000 °C, the thermal response of the prepared smart bolt is better than that of the K-type armored thermocouple, and the thermal balance is achieved faster. The intelligent bolt sensor proposed in this work has better engineering application prospects owing to its convenience of installation in harsh environments.

Influenza virus infects the host and transmits through the respiratory tract (i.e., the mouth and nose); therefore, the development of intranasal influenza vaccines that mimic the natural infection, coupled with an efficient mucosal adjuvant, is an attractive alternative to current parenteral vaccines. However, with the withdrawal of cholera toxin and Escherichia coli heat-labile endotoxin from clinical use due to side effects, there are no approved adjuvants for intranasal vaccines. Therefore, safe and effective mucosal adjuvants are urgently needed. Previously, we reported that one derivative of α-Galactosylceramide (α-GalCer), 7DW8-5, could enhance the protective efficacy of split influenza vaccine by injection administration. However, the mucosal adjuvanticity of 7DW8-5 is still unclear. In this study, we found that 7DW8-5 promotes the production of secret IgA antibodies and IgG antibodies and enhances the protective efficacy of the split influenza vaccine by intranasal administration. Furthermore, co-administration of 7DW8-5 with the split influenza vaccine significantly reduces the virus shedding in the upper and lower respiratory tract after lethal challenge. Our results demonstrate that 7DW8-5 is a novel mucosal adjuvant for the split influenza vaccine.

Influenza virus only encodes a dozen of viral proteins, which need to use host machinery to complete the viral life cycle. Previously, KAP1 was identified as one host protein that potentially interacts with influenza viral proteins in HEK 293 cells. However, the role of KAP1 in influenza virus replication in human lung alveolar epithelial cells and the underlying mechanism remains unclear. In this study, we first generated KAP1 KO A549 cells by CRISPR/Cas9 gene editing. KAP1 deletion had no significant effect on the cell viability and lack of KAP1 expression significantly reduced the influenza A virus replication. Moreover, we demonstrated that KAP1 is involved in the influenza virus entry, transcription/replication of viral genome, and viral protein synthesis in human lung epithelial cells and confirmed that KAP1 interacted with PB2 and NS1 viral proteins during the virus infection. Further study showed that KAP1 inhibited the production of type I IFN and overexpression of KAP1 significantly reduced the IFN-β production. In addition, influenza virus infection induces the deSUMOylation and enhanced phosphorylation of KAP1. Our results suggested that KAP1 is required for the replication of influenza A virus and mediates the replication of influenza A virus by facilitating viral infectivity and synthesis of viral proteins, enhancing viral polymerase activity, and inhibiting the type I IFN production.

Background Colorectal cancer (CRC) is a common malignant tumor worldwide. The cholesterol synthesis (CS) pathway is crucial in the occurrence and development of cancer. This study aims to predict the prognosis of CRC patients based on the cholesterol synthesis-related genes (CSRGs). Methods The patient data of CRC were downloaded from the TCGA and GEO databases, and the CSRGs were downloaded from Genecards. In the TCGA-CRC training set, univariate Cox regression analysis was conducted on the CSRGs, and subtype classification was performed through consensus clustering. Combined with the PPI network and regression analysis, key CSRGs were identified to establish a prognostic model. ROC curves and Kaplan–Meier survival analysis were used to evaluate the model and validate it in the GSE17538 validation set. At the same time, immune analysis and drug sensitivity analysis were conducted. Finally, the functions of these characteristic genes were investigated in an in vitro cell model. Results The TCGA-CRC was divided into two subtypes. A 10-gene Cholesterol Synthesis-related Risk Signature (CSRS) was constructed. The patients were grouped according to the median value of the CSRS. The high-CSRS group had a poorer prognosis, and the abundance of macrophages, neutrophils, and TIL was higher in this group. The drug sensitivity prediction indicated that several candidate drugs (such as Linsitinib) might affect the progression of CRC through unique mechanisms. In vitro experiments demonstrated that EEF1A2 could promote the malignant progression of tumors. Conclusion The results of this project provide some guidance for elucidating potential CS-related biomarkers for predicting prognosis in CRC patients.

Anaerobic fungi (phylum Neocallimastigomycota), an early branching family of fungi, are commonly encountered in the digestive tract of mammalian herbivores. To date, isolates from ten described genera have been reported, and several novel taxonomic groupings are detected using culture-independent molecular methods. Anaerobic fungi are recognized as playing key roles in the decomposition of lignocellulose (up to 50% of the ingested and untreated lignocellulose), with their physical penetration and extracellular enzymatical secretion of an unbiased diverse repertoire of cell-wall-degrading enzymes. The secreted cell-wall-degrading enzymes of anaerobic fungi include both free enzymes and extracellular multi-enzyme complexes called cellulosomes, both of which have potential as fiber degraders in industries. In addition, anaerobic fungi can provide large amounts of substrates such as hydrogen, formate, and acetate for their co-cultured methanogens. Consequently, large amounts of methane can be produced. And thus, it is promising to use the co-culture of anaerobic fungi and methanogens in the biogas process to intensify the biogas yield owing to the efficient and robust degradation of recalcitrant biomass by anaerobic fungi and improved methane production from co-cultures of anaerobic fungi and methanogens.

The natural forest protection and restoration (NFPR) system is imperfect due to contradictions between the objectives of natural forest protection and the reality of situations, outdated cultivation concepts, conflicting interests among participating parties, and the lack of regulation guarantees and assessment criteria. These problems are not only common in China but also in international forest protection. As the NFPR system is more focused on the protection of natural forests, the level of natural forest restoration in China has been poor, with low natural forest quality and forest productivity. At the same time, the value of natural forest ecosystem services does not match the demand of farmers, forest management, and other multiple participating parties. As a result, except for the government, other multiple parties lack the intrinsic motivation to participate in NFPR, ultimately forming a sustainable management dilemma. Under the institutional analysis and development (IAD) framework, the objective of this research was to explore the influencing factors and outcomes of the participation of multiple parties in NFPR and to construct a multiple parties’ participation mechanism for solving this dilemma. This research found that among external variables, multiple parties’ characteristics, biophysical conditions, attributes of community, and rules-in-use jointly influence and constitute the driving mechanism of multiple parties’ participation in NFPR. The rules-in-use directly impact the participation action scenario and regulate the other three external variables. Various factors and mechanisms in NFPR interact in the action space and produce outcomes that create positive incentives for each external variable, thus promoting the whole mechanism to achieve a virtuous cycle of sustainable management. This study provides a theoretical contribution to understanding the behavior of multiple parties participating in NFPR.

In this study, thin-film thermocouples (TFTCs) were combined with a smart bolt to design a smart bolt that can directly test high temperature in service monitoring and parameter calculation for gas turbine structure design. The first-principles calculation was used to analyze the design of the surface properties of nickel-based alloys and insulating layers, and finite element analysis was used to optimize dimension parameters by controlling the thermal stress matching of insulating layers and sensitive layers. The effect of the glass powder with different particle sizes on the microstructure of the ITO and In[sub.2] O[sub.3] films was studied via SEM. The preferred particle size of the additive glass powder is 400 nm. The XRD pattern shows the (222) peak has the highest intensity. The intensities of the (222) and (622) peaks increase after the heat treatment. The calibration results show that the average Seebeck coefficient of the TFTCs can reach 64.9 μV/°C at 1100 °C with a maximum voltage of 71.4 mV. The repeatability error of the cycles of the sensor after heat treatment is ±1.05%. The repeatability of the sensor is up to 98.95%. The smart bolts were tested for application in small aero engines. It can be seen that under the impact of 1000 °C, the thermal response of the prepared smart bolt is better than that of the K-type armored thermocouple, and the thermal balance is achieved faster. The intelligent bolt sensor proposed in this work has better engineering application prospects owing to its convenience of installation in harsh environments.

Key messageThirty environmentally stable QTL controlling grain size and/or plant height were identified, among which QTgw.cau-7D was delimited into the physical interval of approximately 4.4 Mb.Grain size and plant height (PHT) are important agronomic traits in wheat breeding. To dissect the genetic basis of these traits, we conducted a quantitative trait locus (QTL) analysis using recombinant inbred lines (RILs). In total, 30 environmentally stable QTL for thousand grain weight (TGW), grain length (GL), grain width (GW) and PHT were detected. Notably, one major pleiotropic QTL on chromosome arm 3DS explained the highest phenotypic variance for TGW, GL and PHT, and two stable QTL (QGw.cau-4B and QGw.cau-7D) on chromosome arms 4BS and 7DS contributed greater effects for GW. Furthermore, the stable QTL controlling grain size (QTgw.cau-7D and QGw.cau-7D) were delimited into the physical interval of approximately 4.4 Mb harboring 56 annotated genes. The elite NILs of QTgw.cau-7D increased TGW by 12.79–21.75% and GW by 4.10–8.47% across all three environments. Collectively, these results provide further insight into the genetic basis of TGW, GL, GW and PHT, and the fine-mapped QTgw.cau-7D will be an attractive target for positional cloning and marker-assisted selection in wheat breeding programs.