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Distinct mammary stem cells orchestrate long-term homeostasis of adult mammary gland

The murine mammary gland is sustained by distinct pools of stem cells that are limited in space and time, exhibiting both unipotency and bipotency. However, the specific identities of the bipotent and unipotent mammary stem cells remain unclear. In this study, we investigated spatial heterogeneity of the mammary gland at the single-cell transcriptional level. We found that mammary basal cells exhibited spatially distinct populations and characteristics, which can be further divided based on the expression of CD34 and CD200 markers. Notably, CD34−CD200+ basal cells enriched at the nipple region demonstrated strong long-term self-renewal ability and possessed the highest stem cell frequency, while CD34+CD200− basal cells enriched in the terminal end buds (TEBs) showed reduced stem cell potency. Through lineage tracing experiments based on their signature genes, we discovered that Bcl11b+ cells were enriched in the CD34−CD200+ population and exhibited bipotency even in the postnatal mammary gland, with an increasing contribution to mammary epithelia observed during long-term tracing and after multiple rounds of pregnancies. Conversely, lineage tracing of Sema3a+ cells, enriched in the CD34+CD200− population, predominantly revealed their unipotent nature and significant contribution during alveologenesis. Notably, the Bcl11b+ cells displayed a slow response to pregnancy but contributed to long-term mammary homeostasis, in contrast to the rapid response observed in Sema3a+ cells. In addition, Bcl11b progenies survived much better than Sema3a progenies during involution stage, thereby exhibiting increased coverage in the mammary gland after multiple rounds of pregnancies. Importantly, depletion of Bcl11b in Krt14+ mammary basal cells resulted in reduced bipotency of mammary stem cells and impaired their long-term contribution to the mammary gland. Overall, our study identifies distinct bipotent and unipotent populations of mammary basal cells with different dynamic properties that play critical roles in maintaining postnatal mammary homeostasis. These findings are crucial for advancing our understanding of breast health and breast cancer research.

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Senescence-induced p21high macrophages contributed to CD8+ T cells-related immune hyporesponsiveness in kidney transplantation via Zfp36/IL-27 axis

Recipients’ age has emerged as a key factor that impacts on acute renal allograft rejection and graft survival. Age-related functional and structural changes in the immune system have been observed, yet the precise influence of aged immunity on kidney transplant remains unclear. In an initial retrospective analysis of clinical data gathered from two major centers in China and Germany, we found a correlation between aging and mitigated rejection outcomes in kidney recipients. To study the mechanism, we performed kidney transplantation on mice and observed attenuated allograft rejection in senescent recipients. Single-cell transcriptome analysis of allograft kidneys indicated a protective role of p21high macrophages in aged mice. Supernatant collected from p21high macrophage primary culture inhibited the cytotoxic function and proliferation of CD8+ T cells. Zfp36 is highly expressed in senescent p21high macrophages. To determine its role in renal allograft rejection, we studied mice with Zfp36 conditionally deleted in macrophages (Zfp36-cKO). These mice developed exacerbated allograft rejection with enhanced IL-27 production and CD8+ T cell hyperactivation. Inhibition of IL-27 with neutralizing antibody or deletion of IL-27 receptor on CD8+ T cells reversed acute renal allograft rejection in Zfp36-cKO mice. Moreover, in vitro silencing Zfp36 with siRNA led to impaired degradation of IL-27 p28 mRNA and a subsequent increase of IL-27 in p21high macrophages. In conclusion, senescent macrophages protect renal allograft rejection by suppressing CD8+ T cells via a Zfp36/IL-27-dependent mechanism. These findings may provide innovative therapeutic strategies for addressing kidney allograft rejection.

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ShennongAlpha: an AI-driven sharing and collaboration platform for intelligent curation, acquisition, and translation of natural medicinal material knowledge

Natural Medicinal Materials (NMMs) have a long history of global clinical applications and a wealth of records and knowledge. Although NMMs are a major source for drug discovery and clinical application, the utilization and sharing of NMM knowledge face crucial challenges, including the standardized description of critical information, efficient curation and acquisition, and language barriers. To address these, we developed ShennongAlpha, an artificial intelligence (AI)-driven sharing and collaboration platform for intelligent knowledge curation, acquisition, and translation. For standardized knowledge curation, the platform introduced a Systematic Nomenclature to enable accurate differentiation and identification of NMMs. More than fourteen thousand Chinese NMMs have been curated into the platform along with their knowledge. Furthermore, the platform pioneered chat-based knowledge acquisition, standardized machine translation, and collaborative knowledge updating. Together, our study represents the first major advance in leveraging AI to empower NMM knowledge sharing, which not only marks a novel application of AI for science, but also will significantly benefit the global biomedical, pharmaceutical, physician, and patient communities.

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