Prototype of running clinical trials in an untrustworthy environment using blockchain.

Monitoring and ensuring the integrity of data within the clinical trial process is currently not always feasible with the current research system. We propose a blockchain-based system to make data collected in the clinical trial process immutable, traceable, and potentially more trustworthy. We use raw data from a real completed clinical trial, simulate the trial onto a proof of concept web portal service, and test its resilience to data tampering. We also assess its prospects to provide a traceable and useful audit trail of trial data for regulators, and a flexible service for all members within the clinical trials network. We also improve the way adverse events are currently reported. In conclusion, we advocate that this service could offer an improvement in clinical trial data management, and could bolster trust in the clinical research process and the ease at which regulators can oversee trials

The Equality of OLS and GLS Estimators in the Linear Regression Model When the Disturbances are Spatially Correlated

Necessary and sufficient conditions for the equality of ordinary least squares and generalized least squares estimators in the linear regression model with fifirst-order spatial error processes are given

The efficiency of OLS estimator in the linear regression model with spatially correlated errors

Bounds for the efficiency of ordinary least squares relative to generalized least squares estimator in the linear regression model with first order spatial error process are given

High-occupancy effects and stimulation phenomena in semiconductor microcavities

This paper describes recent work on high-occupancy effects in semiconductor microcavities, with emphasis on the variety of new physics and the potential for applications that has been demonstrated recently. It is shown that the ability to manipulate both exciton and photon properties, and how they interact together to form strongly coupled exciton-photon coupled modes, exciton polaritons, leads to a number of very interesting phenomena, which are either difficult or impossible to achieve in bulk semiconductors or quantum wells. The very low polariton density of states enables state occupancies greater than one to be easily achieved, and hence stimulation phenomena to be realized under conditions of resonant excitation. The particular form of the lower polariton dispersion curve in microcavities allows energy and momentum conserving polariton-polariton scattering under resonant excitation. Stimulated scattering of the bosonic quasi-particles occurs to the emitting state at the center of the Brillouin zone, and to a companion state at high wave vector. The stimulation phenomena lead to the formation of highly occupied states with macroscopic coherence in two specific regions of k space. The results are contrasted with phenomena that occur under conditions of nonresonant excitation. Prospects to achieve "polariton lasing" under nonresonant excitation, and high-gain, room-temperature ultrafast amplifiers and low-threshold optical parametric oscillator under resonant excitation conditions are discussed

Combination of forecasts: A bibliography

During the past thirty years, there has been considerable concern about combination of forecasts. Many of the articles and books dedicated to this specific area explain and demonstrate that combining multiple individual forecasts can improve forecast accuracy. The improvement in accuracy mainly depends on forecast combination techniques which range from simple combinations like averaging the forecasts to more complex ones that use the Bayesian approach. This paper provides a bibliography of selected articles and books related to the combination of forecasts in various disciplines and is intended to be a catalog for locating contributions in research areas focusing on the theory and applications of combining forecasts. The bibliography includes recent articles and is as up-to-date as possible

Effects of centrifugation on gonadal and adrenocortical steroids in rats

Many endocrine systems are sensitive to external changes in the environment. Both the pituitary adrenal and pituitary gonadal systems are affected by stress including centrifugation stress. The effect of centrifugation on the pituitary gonadal and pituitary adrenocortical systems was examined by measuring the gonadal and adrenal steroids in the plasma and brain following different duration and intensity of centrifugation stress in rats. Two studies were completed and the results are presented. The second study was carried out to describe the developmental changes of brain, plasma and testicular testosterone and dihydrotestosterone in Sprague Dawley rats so that the effect of centrifugation stress on the pituitary gonadal syatem could be better evaluated in future studies

Integration of disease-specific single nucleotide polymorphisms, expression quantitative trait loci and coexpression networks reveal novel candidate genes for type 2 diabetes.

Aims/hypothesisWhile genome-wide association studies (GWASs) have been successful in identifying novel variants associated with various diseases, it has been much more difficult to determine the biological mechanisms underlying these associations. Expression quantitative trait loci (eQTL) provide another dimension to these data by associating single nucleotide polymorphisms (SNPs) with gene expression. We hypothesised that integrating SNPs known to be associated with type 2 diabetes with eQTLs and coexpression networks would enable the discovery of novel candidate genes for type 2 diabetes.MethodsWe selected 32 SNPs associated with type 2 diabetes in two or more independent GWASs. We used previously described eQTLs mapped from genotype and gene expression data collected from 1,008 morbidly obese patients to find genes with expression associated with these SNPs. We linked these genes to coexpression modules, and ranked the other genes in these modules using an inverse sum score.ResultsWe found 62 genes with expression associated with type 2 diabetes SNPs. We validated our method by linking highly ranked genes in the coexpression modules back to SNPs through a combined eQTL dataset. We showed that the eQTLs highlighted by this method are significantly enriched for association with type 2 diabetes in data from the Wellcome Trust Case Control Consortium (WTCCC, p = 0.026) and the Gene Environment Association Studies (GENEVA, p = 0.042), validating our approach. Many of the highly ranked genes are also involved in the regulation or metabolism of insulin, glucose or lipids.Conclusions/interpretationWe have devised a novel method, involving the integration of datasets of different modalities, to discover novel candidate genes for type 2 diabetes

Integrating biomedical research and electronic health records to create knowledge-based biologically meaningful machine-readable embeddings.

In order to advance precision medicine, detailed clinical features ought to be described in a way that leverages current knowledge. Although data collected from biomedical research is expanding at an almost exponential rate, our ability to transform that information into patient care has not kept at pace. A major barrier preventing this transformation is that multi-dimensional data collection and analysis is usually carried out without much understanding of the underlying knowledge structure. Here, in an effort to bridge this gap, Electronic Health Records (EHRs) of individual patients are connected to a heterogeneous knowledge network called Scalable Precision Medicine Oriented Knowledge Engine (SPOKE). Then an unsupervised machine-learning algorithm creates Propagated SPOKE Entry Vectors (PSEVs) that encode the importance of each SPOKE node for any code in the EHRs. We argue that these results, alongside the natural integration of PSEVs into any EHR machine-learning platform, provide a key step toward precision medicine

The Consistency of s 2 in the Linear Regression Model When the Disturbances are Spatially Correlated

Conditions for the consistency of the estimator s2 of the variance of the disturbance a2u under first-order spatial error processes are given