Current health data sharing frameworks encounter significant challenges in genetic data management, including issues related to privacy protection, constraints on access control, and a lack of effective incentive mechanisms. These deficiencies expose patients and researchers to risks of information leakage and result in inefficiencies in collaboration throughout the entire lifecycle of genetic data—from creation and access to sharing and revocation. Such problems have impeded the advancement of precision medicine and escalated the costs of data acquisition in medical research. Notably, the security and efficiency of data circulation become particularly acute when genetic information is shared across institutional boundaries to support the development of personalized treatment regimens or pharmaceutical research. To tackle these challenges, we propose a genetic data sharing framework based on consortium blockchain, BioLedger. In contrast to traditional centralized storage models, this framework leverages the FISCO BCOS consortium blockchain to construct a decentralized architecture. By integrating smart contracts with HCE (Hybrid CP-ABE with ECIES Encryption), it achieves fine-grained access control while ensuring a high standard of security and privacy for genetic data. Each user retains a high degree of control over their genetic data and can earn token rewards through data contribution, thereby incentivizing user participation in data sharing. Our solution aims to establish an ecosystem that not only safeguards data security and privacy but also enables efficient data exchange, with applications spanning genetic research, pharmaceutical development, and personalized medicine.

Nanobodies are a unique class of antibodies with significant therapeutic potential. However, existing nanobody databases often lack standardized data, advanced search capabilities, and integrated analysis tools. We previously developed NanoLAS to address data integration. Here, we present NanoLAS 2.0, a comprehensive update that introduces a multi-condition associative search, an enhanced 3D viewer with molecular docking simulation, an improved sequence viewer, and integrated binding site prediction via NanoBERTa-ASP. The platform features an updated database backend and a redesigned user interface. NanoLAS 2.0 (available at https://www.nanolas2.online) provides a powerful all-in-one platform to accelerate nanobody research.

BACKGROUND: Two main subclasses of macrophages are found in almost all solid tissues: embryo-derived resident tissue macrophages and bone marrow-derived infiltrated macrophages. These macrophage subtypes show transcriptional and functional divergence, and the programs that have shaped the evolution of renal macrophages and related signaling pathways remain poorly understood. To clarify these processes, we performed data analysis based on single-cell transcriptional profiling of renal tissue-resident and infiltrated macrophages in human, mouse and rat. RESULTS: In this study, we (i) characterized the transcriptional divergence among species and (ii) illustrated variability in expression among cells of each subtype and (iii) compared the gene regulation network and (iv) ligand-receptor pairs in human and mouse. Using single-cell transcriptomics, we mapped the promoter architecture during homeostasis. CONCLUSIONS: Transcriptionally divergent genes, such as the differentially TF-encoding genes expressed in resident and infiltrated macrophages across the three species, vary among cells and include distinct promoter structures. The gene regulatory network in infiltrated macrophages shows comparatively better species-wide consistency than resident macrophages. The conserved transcriptional gene regulatory network in infiltrated macrophages among species is uniquely enriched in pathways related to kinases, and TFs associated with largely conserved regulons among species are uniquely enriched in kinase-related pathways.

Objective: To explore the association rules between medicines, core combinations and new prescriptions, and to analyze the medication rules of traditional Chinese medicine(TCM) in consolidation period of breast cancer based on data mining of medical records of TCM treatment in consolidation period of breast cancer in outpatient clinic of Hunan University of TCM in recent 10 years. Method: Use Python 3.7 software to select association rule algorithm with the minimum support degree greater than 60% and the minimum confidence greater than 0.9 to conduct data mining of the collected medical records.Results: A total of 9739 medical records and 178 Chinese herbal medicines were selected for data mining. The TCMs with higher frequency are atractylodes macrocephala, astragalus membranaceus, poria cocos, codonopsis pilosula, coix seed, hedyotis diffusa and scutellaria barbata. The top five bi-linked medicines in confidence are scutellaria barbata with atractylodes macrocephala, hedyotis diffusa with atractylodes macrocephala, liquor-saturated ligustrum lucidum with atractylodes macrocephala, coii with atractylodes macrocephala, and poria cocos with atractylodes macrocephala. The top five triple-linked medicines in confidence are liquor-saturated ligustrum lucidum with scutellaria barbata with atractylodes macrocephala, poria cocos with coix seed with atractylodes macrocephala, liquor-saturated ligustrum lucidum with coix seed with atractylodes macrocephala, and poria cocos with scutellaria barbata with atractylodes macrocephala. The top five quadr-linked medicine in confidence are poria cocos with liquor-saturated ligustrum lucidum with coix seed with atractylodes macrocephala, poria cocos with liquor-saturated ligustrum lucidum with scutellaria barbata with atractylodes macrocephala, hedyotis diffusa with poria cocos with liquor-saturated ligustrum lucidum with atractylodes macrocephala, codonopsis pilosula with poria cocos with liquor-saturated ligustrum lucidum with astragalus membranaceus, and codonopsis pilosula with atractylodes macrocephala with liquor-saturated ligustrum lucidum with astragalus membranaceus.Conclusion: The main pathogenesis of consolidation period of breast cancer is Qi deficiency and toxin stagnation, and the most important treatment is enriching Qi and detoxify, strengthening the spleen and tonifying the kidney.