How pharmacoepidemiology networks can manage distributed analyses to improve replicability and transparency and minimize bias

Several pharmacoepidemiology networks have been developed over the past decade that use a distributed approach, implementing the same analysis at multiple data sites, to preserve privacy and minimize data sharing. Distributed networks are efficient, by interrogating data on very large populations. The structure of these networks can also be leveraged to improve replicability, increase transparency, and reduce bias. We describe some features of distributed networks using, as examples, the Canadian Network for Observational Drug Effect Studies, the Sentinel System in the USA, and the European Research Network of Pharmacovigilance and Pharmacoepidemiology. Common protocols, analysis plans, and data models, with policies on amendments and protocol violations, are key features. These tools ensure that studies can be audited and repeated as necessary. Blinding and strict conflict of interest policies reduce the potential for bias in analyses and interpretation. These developments should improve the timeliness and accuracy of information used to support both clinical and regulatory decisions

Aspects of the chemistry of some phosphorus halides and pseudohalides

The preparation of pseudohalogeno derivatives of the simple phosphorus(V) species PC1(_4)(^+), PC1(_5) and PC1(_6)(^-) has been attempted. In the case of the tetrachlorophosphonium ion only azido-derivatives are observable in normal organic solvents, cyano and thiocyanato derivatives being more stable in liquid halogen media. Isolation of these compounds was not possible. Molecular derivatives based on PC1(_5) seem to be particularly unstable and are only readily observable under forcing conditions for cyanide. The derivatives of the hexachlorophosphate ion are all observable, PX(_6)(^-) being readily formed for X = N(_3), NCS, NCO and OCN although these and the intermediate species are all unstable. The series of cyanides PC1(_6-n)(CN)(_n)(^-) (0 < n < 3) have been isolated as solids and fully characterised, and the presence of isomers for n = 2 and 3 has been clearly established. The six-coordinate fluorochlorophosphates PF(_3)Cl(_3)(^-), PF(_2)C1(_4)(^-) and PFC1(_5)(^-) have been isolated as pure tetraalkylammonium salts and the reactions of these anions studied with respect to substitution by pseudohalides. The observation of PF(_6-n)X(_n)(^-) (X = pseudohalogen) has been carried out by ligand exchange between PF(_6)(^-) and PX(_6)(^-) (where known) or PX(_3) and attempts have been made to isolate compounds, where feasible, by other reactions such as the addition of pseudohalide ions to PF(_5).The use of pairwise interactions has proved invaluable in assigning formulae in the tetrahedral systems, and in both assigning formulae and identifying specific isomers in many of the six-coordinate systems. The substitution patterns in the six-coordinate systems can be rationalised in terms of a simple steric model, or on the basis of ligand field theory for the cyanides. Other six-coordinate systems have been studied with respect to substitution by azide and several new species have been identified

Vicarious Reinforcement in Rhesus Macaques (Macaca Mulatta)

What happens to others profoundly influences our own behavior. Such other-regarding outcomes can drive observational learning, as well as motivate cooperation, charity, empathy, and even spite. Vicarious reinforcement may serve as one of the critical mechanisms mediating the influence of other-regarding outcomes on behavior and decision-making in groups. Here we show that rhesus macaques spontaneously derive vicarious reinforcement from observing rewards given to another monkey, and that this reinforcement can motivate them to subsequently deliver or withhold rewards from the other animal. We exploited Pavlovian and instrumental conditioning to associate rewards to self (M1) and/or rewards to another monkey (M2) with visual cues. M1s made more errors in the instrumental trials when cues predicted reward to M2 compared to when cues predicted reward to M1, but made even more errors when cues predicted reward to no one. In subsequent preference tests between pairs of conditioned cues, M1s preferred cues paired with reward to M2 over cues paired with reward to no one. By contrast, M1s preferred cues paired with reward to self over cues paired with reward to both monkeys simultaneously. Rates of attention to M2 strongly predicted the strength and valence of vicarious reinforcement. These patterns of behavior, which were absent in non-social control trials, are consistent with vicarious reinforcement based upon sensitivity to observed, or counterfactual, outcomes with respect to another individual. Vicarious reward may play a critical role in shaping cooperation and competition, as well as motivating observational learning and group coordination in rhesus macaques, much as it does in humans. We propose that vicarious reinforcement signals mediate these behaviors via homologous neural circuits involved in reinforcement learning and decision-making

Inhibition in multiclass classification

The role of inhibition is investigated in a multiclass support vector machine formalism inspired by the brain structure of insects. The so-called mushroom bodies have a set of output neurons, or classification functions, that compete with each other to encode a particular input. Strongly active output neurons depress or inhibit the remaining outputs without knowing which is correct or incorrect. Accordingly, we propose to use a classification function that embodies unselective inhibition and train it in the large margin classifier framework. Inhibition leads to more robust classifiers in the sense that they perform better on larger areas of appropriate hyperparameters when assessed with leave-one-out strategies. We also show that the classifier with inhibition is a tight bound to probabilistic exponential models and is Bayes consistent for 3-class problems. These properties make this approach useful for data sets with a limited number of labeled examples. For larger data sets, there is no significant comparative advantage to other multiclass SVM approaches

Inhibition in multiclass classification

The role of inhibition is investigated in a multiclass support vector machine formalism inspired by the brain structure of insects. The so-called mushroom bodies have a set of output neurons, or classification functions, that compete with each other to encode a particular input. Strongly active output neurons depress or inhibit the remaining outputs without knowing which is correct or incorrect. Accordingly, we propose to use a classification function that embodies unselective inhibition and train it in the large margin classifier framework. Inhibition leads to more robust classifiers in the sense that they perform better on larger areas of appropriate hyperparameters when assessed with leave-one-out strategies. We also show that the classifier with inhibition is a tight bound to probabilistic exponential models and is Bayes consistent for 3-class problems. These properties make this approach useful for data sets with a limited number of labeled examples. For larger data sets, there is no significant comparative advantage to other multiclass SVM approaches

Prevalence of unilateral and bilateral deafness in border collies and association with phenotype

This is the final version. Available on open access from Wiley via the DOI in this recordBackground: Congenital sensorineural deafness (CSD) occurs in Border Collies, but its prevalence and inheritance are unknown. This study estimated the prevalence of CSD in Border Collies and investigated its association with phenotypic attributes linked to the merle gene, including coat pigmentation and iris color. Hypothesis: Deafness in Border Collies is associated with pigmentation patterns linked to the merle gene. Animals: A total of 2597 Border Collies from the United Kingdom. Methods: A retrospective study of Border Collies tested, during 1994-2002, by using brainstem auditory evoked responses. Associations between deafness and phenotypic attributes were assessed by using generalized logistic regression. Results: The prevalence of CSD in puppies was estimated as 2.8%. The corresponding rates of unilateral and bilateral CSD were 2.3 and 0.5%, respectively. Adjustment for clustering of hearing status by litter reduced the overall prevalence estimate to 1.6%. There was no association between CSD and sex (P = .2). Deaf Border Collies had higher rates of merle coat pigmentation, blue iris pigment, and excess white on the head than normal hearing Border Collies (all P < .001). The odds of deafness were increased by a factor of 14 for Border Collies with deaf dams, relative to the odds for dogs with normal dams (P = .007), after adjustment for phenotypic attributes. Conclusions and Clinical Importance: Associations between CSD and pigmentation patterns linked to the merle gene were demonstrated for Border Collies. Evidence for an inherited component to CSD in Border Collies supports selective breeding from only tested and normal parents to reduce the prevalence of this disease. Copyright © 2006 by the American College of Veterinary Internal Medicine

Effective Specific Impulse of a Pulsed Rocket Engine

The specific impulse achieved in a pulsed rocket engine augmented with a fissioning nuclear bomb could be greater than that of any continuous flow engine. To a certain extent, this increase in specific impulse would be obtained at the expense of motor weight and average thrust. This paper considers the first of these limitations, motor weight, and estimates the highest effective specific impulse to be expected from a nuclear-pulsed rocket motor with respect to the weight of the motor

Finding rare objects and building pure samples: Probabilistic quasar classification from low resolution Gaia spectra

We develop and demonstrate a probabilistic method for classifying rare objects in surveys with the particular goal of building very pure samples. It works by modifying the output probabilities from a classifier so as to accommodate our expectation (priors) concerning the relative frequencies of different classes of objects. We demonstrate our method using the Discrete Source Classifier, a supervised classifier currently based on Support Vector Machines, which we are developing in preparation for the Gaia data analysis. DSC classifies objects using their very low resolution optical spectra. We look in detail at the problem of quasar classification, because identification of a pure quasar sample is necessary to define the Gaia astrometric reference frame. By varying a posterior probability threshold in DSC we can trade off sample completeness and contamination. We show, using our simulated data, that it is possible to achieve a pure sample of quasars (upper limit on contamination of 1 in 40,000) with a completeness of 65% at magnitudes of G=18.5, and 50% at G=20.0, even when quasars have a frequency of only 1 in every 2000 objects. The star sample completeness is simultaneously 99% with a contamination of 0.7%. Including parallax and proper motion in the classifier barely changes the results. We further show that not accounting for class priors in the target population leads to serious misclassifications and poor predictions for sample completeness and contamination. (Truncated)Comment: MNRAS accepte

CNN Architectures for Large-Scale Audio Classification

Convolutional Neural Networks (CNNs) have proven very effective in image classification and show promise for audio. We use various CNN architectures to classify the soundtracks of a dataset of 70M training videos (5.24 million hours) with 30,871 video-level labels. We examine fully connected Deep Neural Networks (DNNs), AlexNet [1], VGG [2], Inception [3], and ResNet [4]. We investigate varying the size of both training set and label vocabulary, finding that analogs of the CNNs used in image classification do well on our audio classification task, and larger training and label sets help up to a point. A model using embeddings from these classifiers does much better than raw features on the Audio Set [5] Acoustic Event Detection (AED) classification task.Comment: Accepted for publication at ICASSP 2017 Changes: Added definitions of mAP, AUC, and d-prime. Updated mAP/AUC/d-prime numbers for Audio Set based on changes of latest Audio Set revision. Changed wording to fit 4 page limit with new addition

The Effect of Diluted Triple and Double Antibiotic Pastes on Dental Pulp Stem Cells and Established Enterococcus faecalis Biofilm

Objectives To investigate the effect of various dilutions of antibiotic medicaments used in endodontic regeneration on the survival of human dental pulp stem cells (DPSCs) and to determine their antibacterial effect against established Enterococcus faecalis biofilm. Materials and methods The cytotoxic and antibacterial effects of different triple (TAP) and double antibiotic paste (DAP) dilutions (0.125, 0.25, 0.5, 1, and 10 mg/ml) were tested against Enterococcus faecalis established biofilm and DPSC. Established bacterial biofilm were exposed to antibiotic dilutions for 3 days. Then, biofilms were collected, spiral plated, and the numbers of bacterial colony forming units (CFU/ml) were determined. For the cytotoxic effect, lactate dehydrogenase activity assays (LDH) and cell viability assays (WST-1) were used to measure the percentage of DPSC cytotoxicity after 3-day treatment with the same antibiotic dilutions. A general linear mixed model was used for statistical analyses (α = 0.05). Results All antibiotic dilutions significantly decreased the bacterial CFU/ml. For WST-1 assays, all antibiotic dilutions except 0.125 mg/ml significantly reduced the viability of DPSC. For LDH assays, the three lowest tested concentrations of DAP (0.5, 0.25, 0.125 mg/ml) and the two lowest concentrations of TAP (0.25 and 0.125 mg/ml) were non-toxic to DPSC. Conclusions All tested dilutions had an antibacterial effect against E. faecalis. However, 0.125 mg/ml of DAP and TAP showed a significant antibacterial effect with no cytotoxic effects on DPSCs. Clinical relevance Using appropriate antibiotic concentrations of intracanal medicament during endodontic regeneration procedures is critical to disinfect root canal and decrease the adverse effects on stem cells