Introduction: As the space field has developed and our population ages, people engaged in space travel and those on prolonged bed rest are at increasing risk for bone loss and fractures. Disuse osteoporosis occurs frequently in these instances, for which the currently available anti-osteoporosis agents are far from satisfactory and have undesirable side effects. CEFFE is a cell-free fraction isolated from nanofat that is enriched with a variety of growth factors, and we aim to investigate its potential therapeutic effects on disuse osteoporosis.Methods: A tail suspension–induced osteoporosis model was applied in this study. Three weeks after tail suspension, CEFFE was intraperitoneally injected, and PBS was used as a control. The trabecular and cortical bone microstructures of the tibia in each group were assessed by μCT after 4 weeks of administration. Osteocyte lacunar-canalicularity was observed by HE and silver staining. In vitro, MLO-Y4 cell apoptosis was induced by reactive oxygen species (ROSUP). TUNEL staining and flow cytometry were used to detect apoptosis. CCK-8 was used to detect cell proliferation, and Western blotting was used to detect MAPK signaling pathway changes.Results: CEFFE increased the bone volume (BV/TV) and trabecular number (Tb.N) of the trabecular bone and increased the thickness of the cortical bone. HE and silver staining results showed that CEFFE reduced the number of empty lacunae and improved the lacuna-canalicular structure. CEFFE promoted osteocyte proliferative capacity in a dose-dependent manner. CEFFE protected MLO-Y4 from apoptosis by activating the serine/threonine-selective protein kinase (ERK) signaling pathways.Conclusion: CEFFE attenuated immobilization-induced bone loss by decreasing osteocyte apoptosis. CEFFE increased the survival of osteocytes and inhibited osteocyte apoptosis by activating the ERK signaling pathway in vitro.

Background: Ovarian cancer (OV) is the deadliest gynecologic malignancy owing to its late diagnosis and high metastatic propensity. Current biomarkers lack sufficient sensitivity and specificity for the detection of early-stage cancer. To address this gap, we integrated single‐cell transcriptomic profiling of tumor tissues with analysis of circulating exosomal RNA, aiming to uncover candidate markers that reflect tumor heterogeneity and metastatic potential and that may serve as sensitive, non‐invasive diagnostics.Methods: We integrated single-cell RNA sequencing (scRNA-seq) data from primary tumors and metastatic lesions with bulk tissue transcriptomes and plasma-derived exosomal RNA sequencing (RNA-seq). Differentially expressed genes (DEGs) shared across tumor cells, metastatic subpopulations, and exosomes were identified through intersection analysis. Candidate genes were validated in clinical specimens using qPCR and immunohistochemistry. We then applied ten machine learning algorithm to exosomal transcriptomic data to evaluate diagnostic performance and identify the optimal classifier. Tumor cell differentiation states were evaluated using CytoTRACE, and intercellular communication was analyzed with CellChat.Results: Intersection analysis highlighted 52 overlapping DEGs, of which SCNN1A and EFNA1 emerged as the top prognostic indicators. Both genes were significantly upregulated in tumor tissues, metastatic foci, and plasma exosomes (P < 0.01). The exosome-based Adaboost model had an area under the curve of 0.955 in an independent test cohort. Single-cell subcluster analyses revealed high SCNN1A/EFNA1 expression correlated with stem-like differentiation states and enriched pathways associated with immune evasion and adhesion. CellChat analysis demonstrated that highly differentiated tumor cells extensively engaged with fibroblasts and endothelial cells, implying their role in niche formation.Conclusions: By coupling single-cell, bulk tissue, and exosomal transcriptomics, we elucidated the key molecular drivers of OV metastasis and established SCNN1A and EFNA1 as promising non-invasive biomarkers. This multi-omics framework provides an effective strategy for early detection and a better understanding of metastatic progression in OV.