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Macrophages are involved in tissue homeostasis and are critical for innate immune responses, yet distinct macrophage populations in different tissues exhibit diverse gene expression patterns and biological processes. While tissue-specific macrophage epigenomic and transcriptomic profiles have been reported, proteomes of different macrophage populations remain poorly characterized. Here we use mass spectrometry and bulk RNA sequencing to assess the proteomic and transcriptomic patterns, respectively, of 10 primary macrophage populations from seven mouse tissues, bone marrow-derived macrophages and the cell line RAW264.7. The results show distinct proteomic landscape and protein copy numbers between tissue-resident and recruited macrophages. Construction of a hierarchical regulatory network finds cell-type-specific transcription factors of macrophages serving as hubs for denoting tissue and functional identity of individual macrophage subsets. Finally, Il18 is validated to be essential in distinguishing molecular signatures and cellular function features between tissue-resident and recruited macrophages in the lung and liver. In summary, these deposited datasets and our open proteome server (http://macrophage.mouseprotein.cn) integrating all information will provide a valuable resource for future functional and mechanistic studies of mouse macrophages.

In our paper, we put our efforts to find a solution for resources sharing among manufacturing enterprises. Since grid technologies are applied in network widely, resources can be shared more conveniently. We want to apply these technologies to our solution and build a grid application called Manufacturing Grid (MG). In our solution we adopt thoughts of peer-to-peer system to construct manufacturing grid architecture. Through creating classifications dynamically, presentation of resources is solved simply. Distributed hash table (DHT) is introduced to our solution for quickly locating requested resources. Then we present algorithms based on classifications and DHT to resolve the most important issues for resource sharing, resource publishing and searching. We also discussed the issue about fuzzy searching of resource caused by DHT. Finally, we build a prototype system to testify that our solution is feasible and efficient.

With the development of grid technology, manufacturing grid (MG) has been proposed to standardize networked manufacturing modes in industry. As manufacturing resources are complicated, heterogeneous, geographically distributed, and owned by different enterprises, manufacturing resource sharing is much more complicated in MG. Resource owners and users have respective requirements, and then MG should provide capability to trade between them. This paper presents a trading supported manufacturing resources sharing model. Organized in a P2P pattern, Hubs, computer nodes deployed core services required, make up the backbone of the model and responsible for aggregating manufacturing resource. In the model, the resource selection process includes two phases: resource discovering and resource trading. Firstly, discover all the potential appreciate resources by multi-keys hashing; Secondly, gain the best appreciate resources by resource trading to make the benefits of both sides best. This model supports many kinds of economic models. The resources owners and users can use any one or some of these models or even combinations of them in meeting their objectives. The procedure of the competitive bidding trade and the method of evaluating tenders are discussed in detail.