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Microbial communication can drive coordinated functions through sensing, analyzing and processing signal information, playing critical roles in biomanufacturing and life evolution. However, it is still a great challenge to develop effective methods to construct a microbial communication system with coordinated behaviors. Here, we report an electron transfer triggered redox communication network consisting of three building blocks including signal router, optical verifier and bio-actuator for microbial metabolism regulation and coordination. In the redox communication network, the Fe 3+ /Fe 2+ redox signal can be dynamically and reversibly transduced, channeling electrons directly and specifically into bio-actuator cells through iron oxidation pathway. The redox communication network drives gene expression of electron transfer proteins and simultaneously facilitates the critical reducing power regeneration in the bio-actuator, thus enabling regulation of microbial metabolism. In this way, the redox communication system efficiently promotes the biomanufacturing yield and CO 2 fixation rate of bio-actuator. Furthermore, the results demonstrate that this redox communication strategy is applicable both in co-culture and microbial consortia. The proposed electron transfer triggered redox communication strategy in this work could provide an approach for reducing power regeneration and metabolic optimization and could offer insights into improving biomanufacturing efficiency. Microbial communication has significant implications for industrial applications, but constructing communication systems which support coordinated behaviors is challenging. Here, the authors report an electron transfer triggered redox communication network and demonstrate its ability to coordinate microbial metabolism.

Multi-fractured horizontal wells (MFHW) is one of the most effective technologies to develop tight gas reservoirs. The gas seepage from tight formations in MFHW can be divided into three stages: early stage with high productivity, transitional stage with declined productivity, and final stage with stable productivity. Considering the characteristics and mechanisms of porous flows in different regions and at different stages, we derive three coupled equations, namely the equations of porous flow from matrix to fracture, from fracture to near wellbore region, and from new wellbore region to wellbore then an unstable productivity prediction model for a MFHW in a tight gas reservoir is well established. Then, the reliability of this new model, which considers the multi-fracture interference, is verified using a commercial simulator (CMG). Finally, using this transient productivity prediction model, the sensitivity of horizontal well’s productivity to several relevant factors is analyzed. The results illustrate that threshold pressure gradient has the most significant influence on well productivity, followed by stress sensitivity, turbulence flow, and slippage flow. To summarize, the proposed model has demonstrated a potential practical usage to predict the productivity of multi-stage fractured horizontal wells and to analyze the effects of certain factors on gas production in tight gas reservoirs.

The real salt cores from drill-site was regarded as the prototype in this experiment. They are used to simulate solution mining process of salt caverns. In this paper the mathematical model of solution mining wasset up.Experimental parameters are obtained by similarity ratio. Afternumerous experiments on the artificial salt rock model,the results show that thecontrol experimental parametersand the references design are effective.This researchhas some guidance on field engineering of solution mining construction.

•Neural oscillations track hierarchical kinematic structures of biological motion/BM.•Tracking of higher-level structure specifically relates to visual BM processing.•Robust cortical tracking effects are observed across motion types and tasks.•Cortical encoding of BM reflects the spatiotemporal integration of kinematic cues. Biological motion (BM) perception is of great survival value to human beings. The critical characteristics of BM information lie in kinematic cues containing rhythmic structures. However, how rhythmic kinematic structures of BM are dynamically represented in the brain and contribute to visual BM processing remains largely unknown. Here, we probed this issue in three experiments using electroencephalogram (EEG). We found that neural oscillations of observers entrained to the hierarchical kinematic structures of the BM sequences (i.e., step-cycle and gait-cycle for point-light walkers). Notably, only the cortical tracking of the higher-level rhythmic structure (i.e., gait-cycle) exhibited a BM processing specificity, manifested by enhanced neural responses to upright over inverted BM stimuli. This effect could be extended to different motion types and tasks, with its strength positively correlated with the perceptual sensitivity to BM stimuli at the right temporal brain region dedicated to visual BM processing. Modeling results further suggest that the neural encoding of spatiotemporally integrative kinematic cues, in particular the opponent motions of bilateral limbs, drives the selective cortical tracking of BM information. These findings underscore the existence of a cortical mechanism that encodes periodic kinematic features of body movements, which underlies the dynamic construction of visual BM perception.

Underwater acoustic metasurfaces have broad application prospects for the stealth of underwater objects. However, problems such as a narrow operating frequency band, poor operating performance, and considerable thickness at low frequencies remain. In this study a reverse design method for ultra-thin underwater acoustic metasurfaces for low-frequency broadband is proposed using a tandem fully connected deep neural network. The tandem neural network consists of a pre-trained forward neural network and a reverse neural network, based on which a set of elements with flat phase variation and an almost equal phase shift interval in the range of 700–1150 Hz is designed. A diffuse underwater acoustic metasurface with 60 elements was designed, showing that the energy loss of the metasurface in the echo direction was greater than 10 dB. Our work opens a novel pathway for realising low-frequency wideband underwater acoustic devices, which will enable various applications in the future.

Conclusion In this study, we introduce a novel framework for cooperative anomaly detection in UAV swarms. The scheme integrates an anomaly detection model, consensus algorithm, and lightweight communication authentication algorithm. Tailored to address external eavesdroppers and malicious Byzantine nodes, it effectively manages and mitigates Byzantine behavior while safeguarding internal communication. Simultaneously, the framework incorporates a lightweight authentication scheme designed to verify node legitimacy and enhance swarm scalability. Compared with existing schemes, it demonstrates competitiveness in communication, computing costs, and consensus algorithm efficiency. Consequently, we assert that the proposed framework is effective and feasible for swarm anomaly detection. However, in more intricate scenarios, there is room for further refinement. Therefore, delineating attack dictionaries and formulating defense strategies emerge as noteworthy future directions for this work.

Background Early gut microbial colonization is important for postnatal growth and immune development of the chicken. However, at present, commercial chickens are hatched and raised without adult hens, thus are cut off from the microbiota transfer between hens and chicks. In this study, we compared the gut microbiota composition between hen-reared and separately reared chicks, and its impact on the resistance to H9N2 avian influenza virus, with the motive of investigating the impact of this cutoff in microbiota transfer. Results We used the 16SrRNA sequencing method to assess the composition of the gut microbiota in chicks represented by three hen-reared groups and one separately reared group. We found that the diversity of gut microbes in the chicks from the three hen-reared groups was more abundant than in the separately reared group, both at the phylum and genus levels. Our findings highlight the importance of early parental care in influencing the establishment of gut microbiota in the early life of chicks. SourceTracker analysis showed that the feather and cloaca microbiota of hens are the main sources of gut microbiota of chicks. After H9N2 exposure, the viral infection lasted longer in the separately reared chicks, with the viral titers in their oropharyngeal swabs being higher compared to the hen-reared chicks at day 5 post-infection. Interestingly, our results revealed that the gut microbiota of the hen-reared chicks was more stable after H9N2 infection in comparison to that of the separately reared chicks. Conclusions Microbiota transfer between the hens and their chicks promotes the establishment of a balanced and diverse microbiota in the early life of the chicks and improves microbiota stability after H9N2 challenge. These findings advance our understanding of the protective role of gut microbiota in the early life of chicks and should be instrumental in improving chick rearing in the commercial poultry industry. 9rWXktHvFNPuqpjj52kMkp Video Abstract

This study investigated the protective effects of corynoxeine, a natural alkaline compound, on colistin-caused nephrotoxicity using a murine model. Forty mice were divided randomly into control, corynoxeine-only (20 mg/kg/day, intraperitoneal injection), colistin-only (20 mg/kg/day, intraperitoneal injection), and colistin (20 mg/kg/day) + corynoxeine (5 and 20 mg/kg/day) groups (8 mice in each group). All treatments were maintained for seven consecutive days. Results showed that colistin treatment at 20 mg/kg/day for seven days significantly increased serum urea nitrogen and creatinine levels and induced the loss and degeneration of renal tubular epithelial cells, which were markedly ameliorated by corynoxeine co-treatment at 5 or 20 mg/kg/day. Corynoxeine supplementation also markedly attenuated colistin-induced increases in malondialdehyde levels and decreases in reduced glutathione levels and superoxide dismutase and catalase activities in the kidneys. Furthermore, corynoxeine supplementation significantly decreased the expression of transforming growth factor β (TGF-β) and nicotinamide adenine dinucleotide phosphate hydrogen oxidase 4 (NOX4) proteins and nuclear factor kappa B (NF-κB), interleukin-1beta (IL-1β), IL-6, and tumor necrosis factor-α mRNAs, while it significantly increased the expression of erythroid 2-related factor 2 (Nrf2) and heme oxygenase-1 (HO-1) proteins in the kidneys. In conclusion, these results reveal that corynoxeine can protect against colistin-induced nephrotoxicity in mice by inhibiting oxidative stress and inflammation, which may partly be attributed to its ability on the activation of the Nrf2/HO-1 pathway and the inhibition of the TGF-β/NOX4 and NF-κB pathways.

Human emotions are integral to daily tasks, and driving is now a typical daily task. Creating a multi-modal human emotion dataset in driving tasks is an essential step in human emotion studies. we conducted three experiments to collect multimodal psychological, physiological and behavioural dataset for human emotions (PPB-Emo). In Experiment I, 27 participants were recruited, the in-depth interview method was employed to explore the driver’s viewpoints on driving scenarios that induce different emotions. For Experiment II, 409 participants were recruited, a questionnaire survey was conducted to obtain driving scenarios information that induces human drivers to produce specific emotions, and the results were used as the basis for selecting video-audio stimulus materials. In Experiment III, 40 participants were recruited, and the psychological data and physiological data, as well as their behavioural data were collected of all participants in 280 times driving tasks. The PPB-Emo dataset will largely support the analysis of human emotion in driving tasks. Moreover, The PPB-Emo dataset will also benefit human emotion research in other daily tasks.Measurement(s)electroencephalogram measurement • driving behaviour measurement • face expression, body gesture and road scenario measurement • emotion and persionalityTechnology Type(s)electroencephalography (EEG) • driving simulator • visual observation method • self-reported scale

Background Osteoarthritis (OA) is marked by the progressive degradation of joint cartilage and subchondral bone. The precise molecular mechanisms driving meniscus deterioration in OA, especially at the single-cell level, remain poorly understood. Method We analyzed two datasets from the GEO database, GSE220243 and GSE98918, focusing on meniscus tissue sequencing data from OA and non-OA patients. The standard Seurat procedure was employed to process single-cell data and identify differentially expressed genes (DEGs). Immune cell infiltration was assessed using the Microenvironment Cell Populations (MCP) counter and CIBERSORT algorithms. For the microarray data, DEGs were identified with the limma package, and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed using ClusterProfiler. The overlapping DEGs from both datasets were imported into Cytoscape to generate protein-protein interaction (PPI) networks and identify hub genes. Transcription factor (TF) and miRNA interaction networks were analyzed using NetworkAnalyst, and gene-related predictive drugs were enriched through the DSigDB platform. Result After quality control, 34,763 cells from the OA patients and 34,145 cells from the healthy controls were analyzed. UMAP identified and SingleR annotated 14 cell clusters. The 10 largest cell clusters were selected for further analysis. The OA group exhibited a notable increase in macrophages and a reduction in cytotoxic lymphocytes and endothelial cells in the meniscus. In GSE98918, 220 DEGs were identified, and the MCODE plug-in in Cytoscape pinpointed a key module containing 12 candidate genes. The MCC methodfiltered the top 20 DEGs in each GSE220243 cluster. Overlapping DEGs from GSE220243 and GSE98918 identified COL1A1, COL3A1, COL5A2, COL6A3, LOX, and VEGFA as significantly decreased in OA, with COL3A1, COL5A2, LOX, and VEGFA upregulated in meniscal chondrocytes. The interaction network highlighted 3 key miRNAs and 13 shared TFs. Ten gene-related predictive drug molecules were identified. Conclusion This research highlights crucial genes in the OA meniscus and uncovers their differing regulatory patterns between chondrocytes and non-chondrocytes. These findings enhance our understanding of the molecular mechanisms driving OA pathogenesis and aid in identifying potential drug targets.