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Schwann cells (SCs) undergo phenotypic transformation and then orchestrate nerve repair following PNS injury. The ligands and receptors that activate and sustain SC transformation remain incompletely understood. Proteins released by injured axons represent important candidates for activating the SC Repair Program. The low-density lipoprotein receptor-related protein-1 (LRP1) is acutely up-regulated in SCs in response to injury, activating c-Jun, and promoting SC survival. To identify novel LRP1 ligands released in PNS injury, we applied a discovery-based approach in which extracellular proteins in the injured nerve were captured using Fc-fusion proteins containing the ligand-binding motifs of LRP1 (CCR2 and CCR4). An intracellular neuron-specific protein, Protein Kinase C and Casein Kinase Substrate in Neurons (PACSIN1) was identified and validated as an LRP1 ligand. Recombinant PACSIN1 activated c-Jun and ERK1/2 in cultured SCs. Silencing Lrp1 or inhibiting the LRP1 cell-signaling co-receptor, the NMDA-R, blocked the effects of PACSIN1 on c-Jun and ERK1/2 phosphorylation. Intraneural injection of PACSIN1 into crush-injured sciatic nerves activated c-Jun in wild-type mice, but not in mice in which Lrp1 is conditionally deleted in SCs. Transcriptome profiling of SCs revealed that PACSIN1 mediates gene expression events consistent with transformation to the repair phenotype. PACSIN1 promoted SC migration and viability following the TNFα challenge. When Src family kinases were pharmacologically inhibited or the receptor tyrosine kinase, TrkC, was genetically silenced or pharmacologically inhibited, PACSIN1 failed to induce cell signaling and prevent SC death. Collectively, these studies demonstrate that PACSIN1 is a novel axon-derived LRP1 ligand that activates SC repair signaling by transactivating TrkC.

Biological nitrogen fixation by free-living bacteria and rhizobial symbiosis with legumes plays a key role in sustainable crop production. Here, we study how different crop combinations influence the interaction between peanut plants and their rhizosphere microbiota via metabolite deposition and functional responses of free-living and symbiotic nitrogen-fixing bacteria. Based on a long-term (8 year) diversified cropping field experiment, we find that peanut co-cultured with maize and oilseed rape lead to specific changes in peanut rhizosphere metabolite profiles and bacterial functions and nodulation. Flavonoids and coumarins accumulate due to the activation of phenylpropanoid biosynthesis pathways in peanuts. These changes enhance the growth and nitrogen fixation activity of free-living bacterial isolates, and root nodulation by symbiotic Bradyrhizobium isolates. Peanut plant root metabolites interact with Bradyrhizobium isolates contributing to initiate nodulation. Our findings demonstrate that tailored intercropping could be used to improve soil nitrogen availability through changes in the rhizosphere microbiome and its functions.

Correction to: Nature Communicationshttps://doi.org/10.1038/s41467-024-47159-x, published online 04 April 2024 In this article the affiliation ‘State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008, China’ for Xinhua Peng was missing. The original article has been corrected.

Large language models (LLMs) were trained to predict words without having explicit semantic word representations as humans do. Here we compared LLMs and humans in re-solving semantic ambiguities at the word/token level by ex-amining the case of segmenting overlapping ambiguous strings in Chinese sentence reading, where three characters “ABC” could be segmented in either “AB/C” or “A/BC” depending on the context. We showed that although LLMs performed worse than humans, they demonstrated a similar interaction effect between segmentation structure and word frequency order, suggesting that this effect observed in humans could be accounted for by statistical learning of word/token occurrence regularities without assuming an explicit semantic word representation. Nevertheless, across stimuli LLMs' responses were not correlated with any hu-man performance or eye movement measures, suggesting differences in the underlying processing mechanisms. Thus, it is essential to understand these differences through XAI methods to facilitate LLM adoption.

The overall treatment rate of rural domestic sewage in Northwest China is lower than that of national average level. In order to effectively improve regional rural sewage treatment capacity and enhance management level of water environment during local villages，the governments of northwest provinces （autonomous regions） have successively promulgated the discharge standards for pollutants of rural domestic sewage treatment. By comparing the discharge standards of rural domestic sewage in Shanxi Province，Shaanxi Province，Gansu Province，Qinghai Province，Ningxia Hui Autonomous Region，Xinjiang Uygur Autonomous Region and Inner Mongolia Autonomous Region with Pollutant Discharge Standards of Urban Sewage Treatment Plants and the Water Quality Standards of Farmland Irrigation，it is revealed that the standard classification of the seven northwest provinces （autonomous regions） is mainly based on the surface water environmental quality standards and the scale of treatment facilities. In addition，the control index selection of local standards is basically consistent with the pollutant discharge standards of urban sewage treatment plants while the standard limitation is relatively loose. Meanwhile，the third level of the seven Northwest provinces（autonomous regions） is suitable to the water quality requirements of farmland irrigation，of which the Inner Mongolia Autonomous Region，Gansu Province and Xinjiang Uygur Autonomous also specified clear provisions. Moreover，with in-depth summary and analysis of the discharge standards of rural domestic sewage in northwest China，the thinking for the priority selection of the discharge standards for pollutants of rural domestic sewage treatment would be guided to the suitable discharge standard for the treatment of rural domestic sewage. In addition，It will provide not only ideas for the applicable technical system and treatment mode of rural domestic sewage treatment in the arid region of northwest China，but also for the contributions to improve the policy decision-making level on rural water environment treatment of local governments.

The risk factor of the receiving water body is one of the important factors that affect the self-purification ability of the water body. Analyzing the concentration and removal rate of the target substances such as suspended solid (SS), chemical oxygen demand (COD), total nitrogen (TN), and total phosphorus (TP) in the receiving water body during the life cycle can trace the risk factor. Based on this, this article takes a sewage treatment plant and its receiving water body in Nanjing as the research object, sets up five sampling points, and calculates the target concentration and removal rate using the cellular automata-Markov chain Monte Carlo method. Thus, risk assessment of water bodies can be achieved. The results show that: (1) the concentration of the target substance in each process stage has obviously decreased during the life cycle, with an average concentration of 3–18 mg/L; (2) in the life cycle, the highest removal rate of target concentration in each process section can reach 85%; (3) the concentration of target substances SS, COD, TN, TN, TP, and TP at the outlet of the sewage treatment plant is relatively high. Practice has proven that this research method can assess the risk factors of receiving water bodies, so as to improve the scientific, refined and standardized environmental management.