Impact of 2-bromopropane on mouse embryonic stem cells and related regulatory mechanisms

2-Bromopropane (2-BP), a cleaning agent, is used as an alternative to ozone-depleting solvents. Previously, 2-BP was shown to have cytotoxic effects on mouse blastocysts and is associated with defects in their subsequent development, both in vitro and in vivo. In addition, it was found that 2-BP also has cytotoxic effects on oocyte maturation and subsequent pre- and post implantation development in vitro and in vivo, and significantly reduces the rate of oocyte maturation, fertilization, and embryonic development in vitro. This study shows that 2-BP (5 to 10 μM) induces apoptotic processes in mouse embryonic stem cells (ESC-B5), but exerts no effects at treatment dosages below 5 μM. In ESC-B5 cells, 2-BP directly increased the content of reactive oxygen species (ROS), significantly increased the cytoplasmic free calcium and nitric oxide (NO) levels, triggered a loss of mitochondrial membrane potential (MMP), activated caspases-9 and -3, and induced cell death. Pre-treatment with NO scavengers suppressed the apoptotic biochemical changes induced by 10 μM 2-BP and promoted the gene expression levels of p53 and p21, which are involved in apoptotic signaling. These results demonstrate for the first time that 2-BP triggers apoptosis in mouse embryonic stem cells via ROS, NO and the activation of mitochondria-dependent cell death signaling.Keywords: 2-Bromopropane, apoptosis, oxidative stress, calcium, nitric oxideAfrican Journal of Biotechnology Vol. 12(20), pp. 3012-302

A Multi-criteria Decision-making Model for Evaluating Suppliers in Green SCM

In order to develop recycle economy and friendly saving environment, many business enterprises have deployed green supply chain management (GSCM) practices. By employing related theorise of GSCM, organizations expect to minimize the environment impact caused by their commercial and industrial activities in supply chain. Different suppliers may provide different GSCM practices, so evaluating their GSCM performance to rank the green suppliers is an important aspect in practice. In this paper, a novel decision method named fuzzy generalized regret decision-making method is proposed. The fuzzy generalized regret decision-making method is based on ordered weighted averaging (OWA) operator, which is used to effectively aggregate individual regrets related to all stats of nature for an alternative under fuzzy decision-making environment. By combing the proposed method with the application background of GSCM practices, a novel fuzzy decision model for evaluating GSCM performance is further proposed. In the proposed model, the regret of decision maker is taken into consideration with an aim of minimizing the dissatisfaction when choosing the best green supplier. Individual regrets related to all criteria for a green supplier are aggregated to obtain effective regret. Finally, the green suppliers can be ranked according to the effective regrets. A numerical example is used to illustrate the effectiveness of the proposed method

On the Influencing Factors of Dictionary App Interface Design for the Elders

AbstractEnglish learning is becoming one of the popular movements towards the Globalization. In recent years especially, more people use smartphones to learn English. However, it was found in the current market that most dictionary apps were designed for the younger generation and neglected the needs of the elderly. The issue of memory over-load turned out to be the critical problem of the usability for the elderly, due to the complex menu structures. Thus this study is meant to explore a suitable menu structure for the senior user, and provide suggestions for the relative researches.The study results are:1.Gender: There is no significant between male and female in the operating performance.2.Menu structure: the performance of the hybrid structure is superior to the linear structure.3.Display mode: There is no significant between the horizontal and vertical display modes in operating performance.4.Task Complexity: A positive ratio between task complexity and menu topological structure was revealed, the harder the task complexity, the better performance of mixed structure can be expected

Learning to predict expression efficacy of vectors in recombinant protein production

<p>Abstract</p> <p>Background</p> <p>Recombinant protein production is a useful biotechnology to produce a large quantity of highly soluble proteins. Currently, the most widely used production system is to fuse a target protein into different vectors in <it>Escherichia coli </it>(<it>E. coli</it>). However, the production efficacy of different vectors varies for different target proteins. Trial-and-error is still the common practice to find out the efficacy of a vector for a given target protein. Previous studies are limited in that they assumed that proteins would be over-expressed and focused only on the solubility of expressed proteins. In fact, many pairings of vectors and proteins result in no expression.</p> <p>Results</p> <p>In this study, we applied machine learning to train prediction models to predict whether a pairing of vector-protein will express or not express in <it>E. coli</it>. For expressed cases, the models further predict whether the expressed proteins would be soluble. We collected a set of real cases from the clients of our recombinant protein production core facility, where six different vectors were designed and studied. This set of cases is used in both training and evaluation of our models. We evaluate three different models based on the support vector machines (SVM) and their ensembles. Unlike many previous works, these models consider the sequence of the target protein as well as the sequence of the whole fusion vector as the features. We show that a model that classifies a case into one of the three classes (no expression, inclusion body and soluble) outperforms a model that considers the nested structure of the three classes, while a model that can take advantage of the hierarchical structure of the three classes performs slight worse but comparably to the best model. Meanwhile, compared to previous works, we show that the prediction accuracy of our best method still performs the best. Lastly, we briefly present two methods to use the trained model in the design of the recombinant protein production systems to improve the chance of high soluble protein production.</p> <p>Conclusion</p> <p>In this paper, we show that a machine learning approach to the prediction of the efficacy of a vector for a target protein in a recombinant protein production system is promising and may compliment traditional knowledge-driven study of the efficacy. We will release our program to share with other labs in the public domain when this paper is published.</p

Resveratrol Protects against 2-Bromopropane-Induced Apoptosis and Disruption of Embryonic Development in Blastocysts

2-Bromopropane (2-BP) is used as an alternative to ozone-depleting cleaning solvents. Previously, we reported that 2-BP has cytotoxic effects on mouse blastocysts and is associated with defects in subsequent development. In the present work, we show that 2-BP induces apoptosis in the inner cell mass of mouse blastocysts, and inhibits cell proliferation. Both effects are suppressed by resveratrol, a grape-derived phytoalexin with known antioxidant and anti-inflammatory properties. 2-BP-treated blastocysts displayed lower levels of implantation (compared to controls) when plated on culture dishes in vitro, and a reduced ability to proceed to later stages of embryonic development. Pretreatment with resveratrol prevented 2-BP-induced disruption of embryonic development, both in vitro and in vivo. Further investigation of these processes revealed that 2-BP directly promotes ROS generation, loss of mitochondrial membrane potential (MMP), and activation of caspase-3, whereas resveratrol effectively blocks 2-BP-induced ROS production and the accompanying apoptotic biochemical changes. Our results collectively imply that 2-BP triggers the mitochondrion-dependent apoptotic pathway via ROS generation, and the antioxidant activity of resveratrol prevents 2-BP-induced toxicity

Prevention of Dental Damage and Improvement of Difficult Intubation Using a Paraglossal Technique With a Straight Miller Blade

Patients with diseased teeth, or those who are difficult to intubate, have a higher risk of dental injury during laryngoscopy. We report 3 cases of smooth endotracheal intubation using a paraglossal technique with a straight Miller blade in patients with poor dentition. Three patients with poor dentition were scheduled to undergo surgery under general anesthesia. All patients presented with extremely loose upper central incisors and had lost the other right upper teeth, while micrognathia and prominent, loose upper incisors were noted in 1 case. We elected to use a straight Miller blade using a paraglossal approach. A nasopharyngeal airway was inserted after induction of general anesthesia to facilitate mask ventilation and prevent air leakage from the mask. The Miller blade was then inserted from the right corner of the mouth, avoiding contact with the vulnerable incisors, and advanced along the groove between the tongue and tonsil. The endotracheal tube was subsequently smoothly inserted after obtaining a grade 1 Cormack and Lehane view without dental trauma in all 3 cases. Direct laryngoscopy using the paraglossal straight blade technique avoids dental damage in patients with mobile upper incisors and no right maxillary molars. It is a practical alternative method that differs from the traditional Macintosh laryngoscope in patients with a high risk of dental injury during the procedure. This technique, which provides an improved view of the larynx, might also be helpful with patients in whom intubation is difficult