Dynamin-related protein 1 is required for normal mitochondrial bioenergetic and synaptic function in CA1 hippocampal neurons.

Disrupting particular mitochondrial fission and fusion proteins leads to the death of specific neuronal populations; however, the normal functions of mitochondrial fission in neurons are poorly understood, especially in vivo, which limits the understanding of mitochondrial changes in disease. Altered activity of the central mitochondrial fission protein dynamin-related protein 1 (Drp1) may contribute to the pathophysiology of several neurologic diseases. To study Drp1 in a neuronal population affected by Alzheimer's disease (AD), stroke, and seizure disorders, we postnatally deleted Drp1 from CA1 and other forebrain neurons in mice (CamKII-Cre, Drp1lox/lox (Drp1cKO)). Although most CA1 neurons survived for more than 1 year, their synaptic transmission was impaired, and Drp1cKO mice had impaired memory. In Drp1cKO cell bodies, we observed marked mitochondrial swelling but no change in the number of mitochondria in individual synaptic terminals. Using ATP FRET sensors, we found that cultured neurons lacking Drp1 (Drp1KO) could not maintain normal levels of mitochondrial-derived ATP when energy consumption was increased by neural activity. These deficits occurred specifically at the nerve terminal, but not the cell body, and were sufficient to impair synaptic vesicle cycling. Although Drp1KO increased the distance between axonal mitochondria, mitochondrial-derived ATP still decreased similarly in Drp1KO boutons with and without mitochondria. This indicates that mitochondrial-derived ATP is rapidly dispersed in Drp1KO axons, and that the deficits in axonal bioenergetics and function are not caused by regional energy gradients. Instead, loss of Drp1 compromises the intrinsic bioenergetic function of axonal mitochondria, thus revealing a mechanism by which disrupting mitochondrial dynamics can cause dysfunction of axons

The intracellular domain of homomeric glycine receptors modulates agonist efficacy

Like other pentameric ligand-gated channels, glycine receptors (GlyRs) contain long intracellular domains (ICDs) between transmembrane helices 3 and 4. Structurally characterized GlyRs are generally engineered to have a very short ICD. We show here that for one such construct, zebrafish GlyREM, the agonists glycine, β-alanine, taurine, and GABA have high efficacy and produce maximum single-channel open probabilities greater than 0.9. In contrast, for full-length human α1 GlyR, taurine and GABA were clearly partial agonists, with maximum open probabilities of 0.46 and 0.09, respectively. We found that the elevated open probabilities in GlyREM are not due to the limited sequence differences between the human and zebrafish orthologs, but rather to replacement of the native ICD with a short tripeptide ICD. Consistent with this interpretation, shortening the ICD in the human GlyR increased the maximum open probability produced by taurine and GABA to 0.90 and 0.70, respectively, but further engineering it to resemble GlyREM (by introducing the zebrafish transmembrane helix 4 and C terminus) had no effect. Furthermore, reinstating the native ICD to GlyREM converted taurine and GABA to partial agonists, with maximum open probabilities of 0.66 and 0.40, respectively. Structural comparison of transmembrane helices 3 and 4 in short- and long-ICD GlyR subunits revealed that ICD shortening does not distort the orientation of these helices within each subunit. This suggests that the effects of shortening the ICD stem from removing a modulatory effect of the native ICD on GlyR gating, revealing a new role for ICD in pentameric ligand-gated channels

Acupuncture for chronic neck pain: a pilot for a randomised controlled trial

Background: Acupuncture is increasingly being used for many conditions including chronic neck pain. However the evidence remains inconclusive, indicating the need for further well-designed research. The aim of this study was to conduct a pilot randomised controlled parallel arm trial, to establish key features required for the design and implementation of a large-scale trial on acupuncture for chronic neck pain. Methods: Patients whose GPs had diagnosed neck pain were recruited from one general practice, and randomised to receive usual GP care only, or acupuncture ( up to 10 treatments over 3 months) as an adjunctive treatment to usual GP care. The primary outcome measure was the Northwick Park Neck Pain Questionnaire (NPQ) at 3 months. The primary analysis was to determine the sample size for the full scale study. Results: Of the 227 patients with neck pain identified from the GP database, 28 (12.3%) consenting patients were eligible to participate in the pilot and 24 (10.5%) were recruited to the trial. Ten patients were randomised to acupuncture, receiving an average of eight treatments from one of four acupuncturists, and 14 were randomised to usual GP care alone. The sample size for the full scale trial was calculated from a clinically meaningful difference of 5% on the NPQ and, from this pilot, an adjusted standard deviation of 15.3%. Assuming 90% power at the 5% significance level, a sample size of 229 would be required in each arm in a large-scale trial when allowing for a loss to follow-up rate of 14%. In order to achieve this sample, one would need to identify patients from databases of GP practices with a total population of 230,000 patients, or approximately 15 GP practices roughly equal in size to the one involved in this study (i.e. 15,694 patients). Conclusion: This pilot study has allowed a number of recommendations to be made to facilitate the design of a large-scale trial, which in turn will help to clarify the existing evidence base on acupuncture for neck pain

Stability Analysis of Frame Slotted Aloha Protocol

Frame Slotted Aloha (FSA) protocol has been widely applied in Radio Frequency Identification (RFID) systems as the de facto standard in tag identification. However, very limited work has been done on the stability of FSA despite its fundamental importance both on the theoretical characterisation of FSA performance and its effective operation in practical systems. In order to bridge this gap, we devote this paper to investigating the stability properties of FSA by focusing on two physical layer models of practical importance, the models with single packet reception and multipacket reception capabilities. Technically, we model the FSA system backlog as a Markov chain with its states being backlog size at the beginning of each frame. The objective is to analyze the ergodicity of the Markov chain and demonstrate its properties in different regions, particularly the instability region. By employing drift analysis, we obtain the closed-form conditions for the stability of FSA and show that the stability region is maximised when the frame length equals the backlog size in the single packet reception model and when the ratio of the backlog size to frame length equals in order of magnitude the maximum multipacket reception capacity in the multipacket reception model. Furthermore, to characterise system behavior in the instability region, we mathematically demonstrate the existence of transience of the backlog Markov chain.Comment: 14 pages, submitted to IEEE Transaction on Information Theor

An allocation Malmquist index with an application in the China securities industry

This paper proposes an allocation Malmquist index which is inspired by the work on the non-parametric cost Malmquist index. We first show that how to decompose the cost Malmquist index into the input-oriented Malmquist index and the allocation Malmquist index. An application in corporate management of the China securities industry with the panel data set of 40 securities companies during the period 2005–2011 shows the practicality of the propose model

Comparison of hospital charge prediction models for gastric cancer patients: neural network vs. decision tree models

<p>Abstract</p> <p>Background</p> <p>In recent years, artificial neural network is advocated in modeling complex multivariable relationships due to its ability of fault tolerance; while decision tree of data mining technique was recommended because of its richness of classification arithmetic rules and appeal of visibility. The aim of our research was to compare the performance of ANN and decision tree models in predicting hospital charges on gastric cancer patients.</p> <p>Methods</p> <p>Data about hospital charges on 1008 gastric cancer patients and related demographic information were collected from the First Affiliated Hospital of Anhui Medical University from 2005 to 2007 and preprocessed firstly to select pertinent input variables. Then artificial neural network (ANN) and decision tree models, using same hospital charge output variable and same input variables, were applied to compare the predictive abilities in terms of mean absolute errors and linear correlation coefficients for the training and test datasets. The transfer function in ANN model was sigmoid with 1 hidden layer and three hidden nodes.</p> <p>Results</p> <p>After preprocess of the data, 12 variables were selected and used as input variables in two types of models. For both the training dataset and the test dataset, mean absolute errors of ANN model were lower than those of decision tree model (1819.197 vs. 2782.423, 1162.279 vs. 3424.608) and linear correlation coefficients of the former model were higher than those of the latter (0.955 vs. 0.866, 0.987 vs. 0.806). The predictive ability and adaptive capacity of ANN model were better than those of decision tree model.</p> <p>Conclusion</p> <p>ANN model performed better in predicting hospital charges of gastric cancer patients of China than did decision tree model.</p

Understanding the adoption of business analytics and intelligence

Cruz-Jesus, F., Oliveira, T., & Naranjo, M. (2018). Understanding the adoption of business analytics and intelligence. In Á. Rocha, H. Adeli, L. P. Reis, & S. Costanzo (Eds.), Trends and Advances in Information Systems and Technologies, pp. 1094-1103. (Advances in Intelligent Systems and Computing; Vol. 745). Springer Verlag. DOI: 10.1007/978-3-319-77703-0_106Our work addresses the factors that influence the adoption of business analytics and intelligence (BAI) among firms. Grounded on some of the most prominent adoption models for technological innovations, we developed a conceptual model especially suited for BAI. Based on this we propose an instrument in which relevant hypotheses will be derived and tested by means of statistical analysis. We hope that the findings derived from our analysis may offer important insights for practitioners and researchers regarding the drivers that lead to BAI adoption in firms. Although other studies have already focused on the adoption of technological innovations by firms, research on BAI is scarce, hence the relevancy of our research.authorsversionpublishe

The incidence of liver injury in Uyghur patients treated for TB in Xinjiang Uyghur autonomous region, China, and its association with hepatic enzyme polymorphisms nat2, cyp2e1, gstm1 and gstt1.

BACKGROUND AND OBJECTIVE: Of three first-line anti-tuberculosis (anti-TB) drugs, isoniazid is most commonly associated with hepatotoxicity. Differences in INH-induced toxicity have been attributed to genetic variability at several loci, NAT2, CYP2E1, GSTM1and GSTT1, that code for drug-metabolizing enzymes. This study evaluated whether the polymorphisms in these enzymes were associated with an increased risk of anti-TB drug-induced hepatitis in patients and could potentially be used to identify patients at risk of liver injury. METHODS AND DESIGN: In a cross-sectional study, 2244 tuberculosis patients were assessed two months after the start of treatment. Anti-TB drug-induced liver injury (ATLI) was defined as an ALT, AST or bilirubin value more than twice the upper limit of normal. NAT2, CYP2E1, GSTM1 and GSTT1 genotypes were determined using the PCR/ligase detection reaction assays. RESULTS: 2244 patients were evaluated, there were 89 cases of ATLI, a prevalence of 4% 9 patients (0.4%) had ALT levels more than 5 times the upper limit of normal. The prevalence of ATLI was greater among men than women, and there was a weak association with NAT2*5 genotypes, with ATLI more common among patients with the NAT2*5*CT genotype. The sensitivity of the CT genotype for identifying patients with ATLI was 42% and the positive predictive value 5.9%. CT ATLI was more common among slow acetylators (prevalence ratio 2.0 (95% CI 0.95,4.20) )compared to rapid acetylators. There was no evidence that ATLI was associated with CYP2E1 RsaIc1/c1genotype, CYP2E1 RsaIc1/c2 or c2/c2 genotypes, or GSTM1/GSTT1 null genotypes. CONCLUSIONS: In Xinjiang Uyghur TB patients, liver injury was associated with the genetic variant NAT2*5, however the genetic markers studied are unlikely to be useful for screening patients due to the low sensitivity and low positive predictive values for identifying persons at risk of liver injury