Transplanted MSCs promote alveolar bone repair via hypoxia-induced extracellular vesicle secretion.

OBJECT: Mesenchymal stem cell (MSC) therapy is a potential strategy for promoting alveolar bone regeneration. This study evaluated the effects and mechanisms of transplanted MSCs on alveolar bone repair. METHODS: Mouse alveolar bone defect model was treated using mouse bone marrow mesenchymal stem cell (BMSC) transplantation. The bone repair was evaluated by micro-CT and Masson staining. The conditioned medium of hypoxia-treated BMSCs was co-cultured with normal BMSCs in vitro to detect the regulatory effect of transplanted MSCs on the chemotactic and migratory functions of host cells. The mechanisms were investigated using Becn siRNA transfection and western blotting. RESULTS: BMSC transplantation promoted bone defect regeneration. The hypoxic microenvironment induces BMSCs to release multiple extracellular vesicle (EV)-mediated regulatory proteins that promote the migration of host stem cells. Protein array analysis, western blotting, GFP-LC3 detection, and Becn siRNA transfection confirmed that autophagy activation in BMSCs plays a key role during this process. CONCLUSION: The local hypoxic microenvironment induces transplanted MSCs to secrete a large number of EV-mediated regulatory proteins, thereby upregulating the migration function of the host stem cells and promoting alveolar bone defect regeneration. This process depends on the autophagy-related mechanism of the transplanted MSCs.

A multipopulation PSO based memetic algorithm for permutation flow shop scheduling.

The permutation flow shop scheduling problem (PFSSP) is part of production scheduling, which belongs to the hardest combinatorial optimization problem. In this paper, a multipopulation particle swarm optimization (PSO) based memetic algorithm (MPSOMA) is proposed in this paper. In the proposed algorithm, the whole particle swarm population is divided into three subpopulations in which each particle evolves itself by the standard PSO and then updates each subpopulation by using different local search schemes such as variable neighborhood search (VNS) and individual improvement scheme (IIS). Then, the best particle of each subpopulation is selected to construct a probabilistic model by using estimation of distribution algorithm (EDA) and three particles are sampled from the probabilistic model to update the worst individual in each subpopulation. The best particle in the entire particle swarm is used to update the global optimal solution. The proposed MPSOMA is compared with two recently proposed algorithms, namely, PSO based memetic algorithm (PSOMA) and hybrid particle swarm optimization with estimation of distribution algorithm (PSOEDA), on 29 well-known PFFSPs taken from OR-library, and the experimental results show that it is an effective approach for the PFFSP.

High Tiam1 expression predicts positive lymphatic metastasis and worse survival in patients with malignant solid tumors: a systematic review and meta-analysis.

BACKGROUND: Many studies have explored the prognostic value of T-cell lymphoma invasion and metastasis inducing factor 1 (Tiam1) and its association with lymphatic metastasis in malignant solid tumors, but the conclusions remain controversial. Therefore, we performed a meta-analysis to systematically assess the prognostic value of Tiam1 expression and its association with lymphatic metastasis in malignant solid tumors. METHODS: We searched eligible studies in PubMed, Web of Science and EMBASE databases (from inception up to October 2018). The combined HR with 95% CI was used to estimate the prognostic value of Tiam1 expression. The correlation between Tiam1 expression and lymphatic metastasis was assessed using the combined odds ratio (OR) with 95% CI. RESULTS: A total of 17 studies with 2,228 patients with solid tumors were included in this meta-analysis. The overall estimated results showed that high Tiam1 expression was significantly associated with shorter overall survival (HR= 2.08, 95% CI: 1.62-2.68, P<0.01), and disease-free survival (HR = 1.86, 95% CI: 1.49-2.32, P<0.01). Besides, we also found that there was a close relationship between high Tiam1 expression and positive lymphatic metastasis (OR=2.63; 95% CI: 1.79-3.84, P<0.01). CONCLUSION: High Tiam1 expression was significantly associated with shorter survival and positive lymphatic metastasis in patients with malignant solid tumors. Therefore, Tiam1 may be a promising prognostic biomarker and an effective therapeutic target for malignant solid tumors.