Lindgrenmarsh3090

Beef-based medium beef extract (BE) and standard medium tryptic soy broth (TSB) are used as minimally processed food models to study the effects on Escherichia coli O157H7 biofilm formation. The effects of temperatures (4, 10, 25, 37, and 42°C), pH values (4.5, 5.0, 5.5, 6.0, 7.0, and 8.0), strain characteristics, and the expression of functional genes on the biofilm formation ability of the bacteria were determined. The three tested E. coli O157H7 strains produced biofilm in both media. Biofilm formation was greater in BE than in TSB (P < 0.05). The strongest biofilm formation capacity of E. coli O157H7 was achieved at 37°C and pH 7.0. Biofilm formation was significantly inhibited for three tested strains incubated at 4°C. Biofilm formation ability was correlated with swarming in TSB. Biofilm formation was significantly and positively correlated with autoaggregation or hydrophobicity in BE (P < 0.05). At the initial stage of biofilm formation, the expressions of luxS, sdiA, csgD, csgA, flhC, adrA, and rpoS were significantly higher in BE than in TSB (P < 0.05). At the maturity stage, the expressions of luxS, sdiA, csgD, csgA, flhC, csrA, adrB, adrA, iraM, and rpoS were significantly higher in TSB than in BE (P < 0.05). Such information could help in the development of effective biofilm removal technologies to deal with risks of E. coli O157H7 biofilms in the beef industry.

Potato, the third most important food crop worldwide, is rich in nutrients but low in protein. In contrast, milk is rich in protein. Yogurt produced through the cofermentation of potatoes and milk is a highly nutritious food. The quality and shelf life of yogurt are important topics in the dairy industry. The objective of this study was to explore the effect of the addition of essential oil (EO) on the shelf life and quality of potato yogurt. The antimicrobial effects of several EOs, the effect of perilla leaf EO (PLEO) concentration on potato yogurt, and the volatile flavor components of PLEO and PLEO potato yogurt were evaluated. The effects of storage time and temperature on the pH, microbial counts, and sensory characteristics of PLEO potato yogurt also were analyzed to establish a shelf-life model. PLEO had an antimicrobial effect and was the appropriate EO for use in the potato yogurt. A total of 69 compounds were detected in PLEO, and limonene was the main compound. PLEO had an effect on the pH, sensory characteristics, and viable bacterial counts of potato yogurt during storage. The optimal concentration of added PLEO was 0.04%. PLEO had considerable influence on volatile flavor components, and the consumer acceptance of 0.04% PLEO potato yogurt was higher than that of potato yogurt without PLEO in the later stage of storage. The shelf life of potato yogurt with PLEO was 6 days longer than that of the control yogurt. PLEO also improved the concentrations of active terpene substances in potato yogurt. The prediction models based on pH and sensory scores at 5°C were established as A = A0e0.00323t and A = A0e0.00355t, respectively. Comparison of the accuracy factor and the deviation factor of the models revealed that the sensory prediction model was more accurate than the pH prediction model. The results of this study provide theoretical and data support for the industrial development of yogurt with EOs, including extension and prediction of its shelf life.

In-stent restenosis and late stent thrombosis are complications associated with the use of metallic and drug-coated stents. Strategies that inhibit vascular smooth muscle cell (SMC) proliferation without affecting endothelial cell (EC) growth would be helpful in reducing complications arising from percutaneous interventions. Our group previously showed that the forced expression of the injury-inducible zinc finger (ZNF) transcription factor, yin yang-1 (YY1) comprising 414 residues inhibits neointima formation in carotid arteries of rabbits and rats. YY1 inhibits SMC proliferation without affecting EC growth. Identifying a shorter version of YY1 retaining cell-selective inhibition would make it more amenable for potential use as a gene therapeutic agent.

We dissected YY1 into a range of shorter fragments (YY1A-D, YY1Δ) and found that the first two ZNFs in YY1 (construct YY1B, spanning 52 residues) repressed SMC proliferation. Receptor Binding Domain analysis predicts a three residue (339KLK341) interactio the therapeutic potential of YY1B in vascular proliferative disease.

These studies identify a truncated form of YY1 (YY1B) that can interact with BASP1 and inhibits SMC proliferation, migration and intimal hyperplasia after balloon injury of rat carotid arteries as effectively as full length YY1. We demonstrate the therapeutic potential of YY1B in vascular proliferative disease.

The analysis of gene co-expression network (GCN) is critical in examining the gene-gene interactions and learning the underlying complex yet highly organized gene regulatory mechanisms. Numerous clustering methods have been developed to detect communities of co-expressed genes in the large network. The assumed independent community structure, however, can be oversimplified and may not adequately characterize the complex biological processes.

We develop a new computational package to extract interconnected communities from gene co-expression network. BMS202 ic50 We consider a pair of communities be interconnected if a subset of genes from one community is correlated with a subset of genes from another community. The interconnected community structure is more flexible and provides a better fit to the empirical co-expression matrix. To overcome the computational challenges, we develop efficient algorithms by leveraging advanced graph norm shrinkage approach. We validate and show the advantage of our method by extensive simulation studies. We then apply our interconnected community detection method to an RNA-seq data from The Cancer Genome Atlas (TCGA) Acute Myeloid Leukemia (AML) study and identify essential interacting biological pathways related to the immune evasion mechanism of tumor cells.

The software is available at Github https//github.com/qwu1221/ICN and Figshare https//figshare.com/articles/software/ICN-package/13229093.

Supplementary data are available at Bioinformatics online.

Supplementary data are available at Bioinformatics online.