Background: Hepcidin encoded by HAMP is vital to regulating proliferation, metastasis, and migration. Hepcidin is secreted specifically by the liver. This study sought to examine the functional role of hepcidin in hepatocellular carcinoma (HCC). Methods: Data in the Cancer Genome Atlas database was used to analyze HAMP expression as it relates to HCC prognosis. We then used the 5-ethynyl-20-deoxyuridine (EdU) incorporation assay, transwell assay, and flow cytometric analysis, respectively, to assess proliferation, migration, and the cell cycle. Gene set enrichment analysis (GSEA) was used to find pathways affected by HAMP. Results: HAMP expression was lower in hepatocellular carcinoma samples compared with adjacent normal tissue controls. Low HAMP expression was linked with a higher rate of metastasis and poor disease-free status. Downregulation of HAMP induced SMMC-7721 and HepG-2 cell proliferation and promoted their migration. HAMP could affect the cell cycle pathway and Western blotting, confirming that reduced HAMP levels activated cyclin-dependent kinase-1/stat 3 pathway. Conclusion: Our findings indicate that HAMP functions as a tumor suppressor gene. The role of HAMP in cellular proliferation and metastasis is related to cell cycle checkpoints. HAMP could be considered as a diagnostic biomarker and targeted therapy in HCC.

It is always challenging to tackle timeliness and privacy security problems in sensing data in mobile crowdsensing (MCS) systems, and the key is in how to realize data freshness optimization in privacy-preserving scenarios. In view of the fact that existing studies on timeliness optimization of sensing data and those on privacy security enhancement are independent of each other, this paper systematically investigates data freshness optimization techniques for privacy-preserving MCS systems. Firstly, the preliminaries about MCS, privacy preservation, and sensing data quality are introduced. Then, a coupling mechanism, which intricately links the dynamics of privacy preservation and data freshness, is unveiled. This intertwining relationship introduces complexities that make the problem particularly challenging to address. Next, effective measures are summarized to realize data freshness performance enhancement in MCS. Finally, implementation, potential applications, and future directions on timely and secure MCS are discussed.