The Angiopoietin-1 Variant COMP-Ang1 Enhances BMP2-Induced Bone Regeneration with Recruiting Pericytes in Critical Sized Calvarial Defects

Craniofacial bone defects are observed in a variety of clinical situations, and their reconstructions require coordinated coupling between angiogenesis and osteogenesis. In this study, we explored the effects of cartilage oligomeric matrix protein-angiopoietin 1 (COMP-Ang1), a synthetic and soluble variant of angiopoietin 1, on bone morphogenetic protein 2 (BMP2)-induced cranial bone regeneration, and recruitment and osteogenic differentiation of perivascular pericytes. A critical-size calvarial defect was created in the C57BL/6 mouse and COMP-Ang1 and/or BMP2 proteins were delivered into the defects with absorbable collagen sponges. After 3 weeks, bone regeneration was evaluated using micro-computed tomography and histologic examination. Pericyte recruitment into the defects was examined using immunofluorescence staining with anti-NG2 and anti-CD31 antibodies. In vitro recruitment and osteoblastic differentiation of pericyte cells were assessed with Boyden chamber assay, staining of calcified nodules, RT-PCR and Western blot analyses. Combined administration of COMP-Ang1 and BMP2 synergistically enhanced bone repair along with the increased population of CD31 (an endothelial cell marker) and NG2 (a specific marker of pericyte) positive cells. In vitro cultures of pericytes consistently showed that pericyte infiltration into the membrane pore of Boyden chamber was more enhanced by the combination treatment. In addition, the combination further increased the osteoblast-specific gene expression, including bone sialoprotein (BSP), osteocalcin (OCN) and osterix (OSX), phosphorylation of Smad/1/5/8, and mineralized nodule formation. COMP-Ang1 can enhance BMP2-induced cranial bone regeneration with increased pericyte recruitment. Combined delivery of the proteins might be a therapeutic strategy to repair cranial bone damage.     

Splenic gene expression profiling in White Leghorn layer inoculated with the Salmonella enterica serovar Enteritidis

Salmonella enterica serovar Enteritidis (SE) is a foodborne pathogen that can threaten human health through contaminated poultry products. Live poultry, chicken eggs and meat are primary sources of human salmonellosis. To understand the genetic resistance of egg‐type chickens in response to SE inoculation, global gene expression in the spleen of 20‐week‐old White Leghorn was measured using the Agilent 4 × 44 K chicken microarray at 7 and 14 days following SE inoculation (dpi). Results showed that there were 1363 genes significantly differentially expressed between inoculated and non‐inoculated groups at 7 dpi (I7/N7), of which 682 were up‐regulated and 681 were down‐regulated genes. By contrast, 688 differentially expressed genes were observed at 14 dpi (I14/N14), of which 371 were up‐regulated genes and 317 were down‐regulated genes. There were 33 and 28 immune‐related genes significantly differentially expressed in the comparisons of I7/N7 and I14/N14 respectively. Functional annotation revealed that several Gene Ontology (GO) terms related to immunity were significantly enriched between the inoculated and non‐inoculated groups at 14 dpi but not at 7 dpi, despite a similar number of immune‐related genes identified between I7/N7 and I14/N14. The immune response to SE inoculation changes with different time points following SE inoculation. The complicated interaction between the immune system and metabolism contributes to the immune responses to SE inoculation of egg‐type chickens at 14 dpi at the onset of lay. GC, TNFSF8, CD86, CD274, BLB1 and BLB2 play important roles in response to SE inoculation. The results from this study will deepen the current understanding of the genetic response of the egg‐type chicken to SE inoculation at the onset of egg laying.     

Ginsenoside Rg1 protects H9c2 cells against nutritional stress-induced injury via aldolase /AMPK/PINK1 signalling

Insufficient nutrients supply will greatly affect the function of cardiac myocytes. The adaptive responses of cardiac myocytes to nutritional stress are not fully known. Ginsenoside Rg1 is one of the most pharmacologically active components in Panax Ginseng and possesses protective effects on cardiomyocyte. Here, we investigate the effects of ginsenoside Rg1 on H9c2 cells which were subjected to nutritional stress. Nutritional stress-induced by glucose deprivation strongly induced cell death and this response was inhibited by ginsenoside Rg1. Importantly, glucose deprivation decreased intracellular ATP levels and mitochondrial membrane potential. Ginsenoside Rg1 rescued ATP levels and mitochondrial membrane potential in nutrient-starved cells. For molecular mechanisms, ginsenoside Rg1 increased the expressions of PTEN-induced kinase 1 (PINK1) and p-AMPK in glucose deprivation treated H9c2 cells. Reducing the expression of aldolase in H9c2 cells inhibited ginsenoside Rg1′s actions on PINK1 and p-AMPK. Further, the nutritional stress mice were used to verify the mechanisms obtained in vitro. Ginsenoside Rg1 increased the expressions of aldolase, p-AMPK, and PINK1 in starved mice heart. Taken together, our results reveal that ginsenoside Rg1 limits nutritional stress-induced H9c2 cells injury by regulating the aldolase /AMP-activated protein kinase/PINK1 pathway.     

Advances in research on signal molecules regulating biofilms

World Journal of Microbiology and Biotechnology - Antibiotic and arsenic (As) contaminations are worldwide public health problems. Previously, the bacterial ABC-type efflux protein MacAB reportedly...     

Bayesian nonparametric inference for panel count data with an informative observation process

In this paper, the panel count data analysis for recurrent events is considered. Such analysis is useful for studying tumor or infection recurrences in both clinical trial and observational studies. A bivariate Gaussian Cox process model is proposed to jointly model the observation process and the recurrent event process. Bayesian nonparametric inference is proposed for simultaneously estimating regression parameters, bivariate frailty effects, and baseline intensity functions. Inference is done through Markov chain Monte Carlo, with fully developed computational techniques. Predictive inference is also discussed under the Bayesian setting. The proposed method is shown to be efficient via simulation studies. A clinical trial dataset on skin cancer patients is analyzed to illustrate the proposed approach.