17β-Estradiol (E2) is the major estrogen secreted by the premenopausal ovary and shows dual effects on cell apoptosis under pathological conditions. E2 was previously shown to increase CD38 mRNA and protein expression in myometrial smooth muscle, but its function and mechanism remain largely unknown. Here we investigated the role of E2 in hypoxia-induced apoptosis in mouse airway smooth muscle cells (ASMCs) and explored the underlying mechanisms. Results showed that E2 significantly increased CD38 expression at both mRNA and protein levels, accompanied with decreased SIRT1 levels in ASMCs. By using primary ASMCs from the wild type (WT) and the smooth muscle-specific CD38 knockout (CD38 KO) mice, we found that the down-regulation of SIRT1 induced by E2 was abolished in CD38 KO AMSCs. E2 promoted the acetylation of p53 in WT cells, and this effect was also diminished in the absence of CD38. In addition, E2 further activated CD38/SIRT1/p53 signal pathway and promoted cell apoptosis during hypoxia. However, these effects were reversed in CD38 KO ASMCs and by the specific SIRT1 activator Resveratrol. We also found that E2 enhanced CD38 expression through estrogen receptor. The data suggested that CD38 is a direct target for E2 which promotes hypoxia-induced AMSC apoptosis through SIRT1/p53 signal pathway.

The traditional data automatic office system has limited mining and computing capabilities. Due to the iterative complexity of data mining algorithms, it is difficult to discover the relationships and rules existing in the Internet of Things data as well as impossible to advance the efficiency of the office system based on the existing Internet of Things data. This paper combines cloud computing and machine learning to construct an intelligent network office system, realizes large-scale IoT data processing through the combination of IoT data mining technology and cloud computing framework, and constructs the functional module structure of the intelligent network office system through demand analysis. On this basis, this paper conducts system performance verification and conducts experimental design based on network intelligent system demand. The experimental results show that the system constructed in this paper has certain practical effects, which can provide theoretical reference for subsequent related research.

This paper presents a distributed constructing algorithm (PdisGodin) of concept lattice, using pruning method to eliminate redundant information which appear in the concept lattice's distributed incremental construction process, so that the comparing times of inserted concept are reduced, and the distributed constructing efficiency of concept lattice is effectively improved. The experiment results validate the correctness and validity of the algorithm by using the celestial spectrum data as the formal context.

To date, most of the constructions of provably secure identity based signature (IBS) scheme are based on the approach of attaching certificates to non-identity based signatures in the random oracle. In ACISP'06, Paterson et al. proposed the first direct construction of IBS in the standard model. However, Paterson et al.'s scheme has a large size of the public parameter, which is not suitable for environments with limited storage capacity. In this paper, we proposed an efficient provably secure IBS scheme in the standard model based on bilinear pairings. To the best of our knowledge, our scheme is another direct construction and more efficient by reducing about half the size of public parameters than Paterson et al.'s scheme. Assuming the intractability of the Computational Diffie-Hellman problem, our IBS scheme is unforgeable under an adaptive chosen-message attack without resorting to random oracle.