Ethical and legal aspects of research involving older people with cognitive impairment: A survey of dementia researchers in Australia

© 2019 Elsevier Ltd People with dementia are under-represented in clinical research, in part due to the ethical and legal complexities of involving people in studies who may lack capacity to consent. Excluding this population from research limits the evidence to inform care. The attitudes and practices of researchers are key to the inclusion of people with dementia in research, however, there are few empirical studies on researchers' perspectives in this area. A cross-sectional study involved researchers in Australia who had experience in the ethical aspects of conducting dementia-related studies with human participants (n = 70). Data were collected via an online survey from November 2017 to January 2018. Most respondents (97%) agreed with the importance of including people at all stages of dementia in research, yet around three-quarters of respondents perceived ethical and legal rules and processes as unduly restrictive or time-consuming. Researchers reported variable practices in assessing prospective participants' capacity to consent to their studies. Various tools are used for this purpose, ranging from tools designed for research (eg, MacArthur Competence Assessment Tool for Clinical Research) to more general cognitive function screens (eg, Mini Mental State Exam). Few respondents (14%) routinely exclude people from studies who are unable to give their own consent, but instead seek permission from proxy decision-makers, such as legally appointed guardians or family carers. Respondents reported positive and negative outcomes of ethics review processes. Positive outcomes included strengthening the protections for participants with cognitive impairment while negative outcomes included delays and inconsistent decisions from different ethics committees. The findings suggest a need for improved strategies in the research context to assess and enhance the decision-making capacity of people with dementia to support appropriate opportunities for inclusion. Education for ethics committees, proxy decision-makers and other gatekeepers is also needed to reduce barriers to participation in research

The Rsb phosphoregulatory network controls availability of the primary sigma factor in Chlamydia trachomatis and influences the kinetics of growth and development

Chlamydia trachomatis is the leading cause of both bacterial sexually transmitted infection and infection-derived blindness world-wide. No vaccine has proven protective to date in humans. C. trachomatis only replicates from inside a host cell, and has evolved to acquire a variety of nutrients directly from its host. However, a typical human immune response will normally limit the availability of a variety of essential nutrients. Thus, it is thought that the success of C. trachomatis as a human pathogen may lie in its ability to survive these immunological stress situations by slowing growth and development until conditions in the cell have improved. This mode of growth is known as persistence and how C. trachomatis senses stress and responds in this manner is an important area of research. Our report characterizes a complete signaling module, the Rsb network, that is capable of controlling the growth rate or infectivity of Chlamydia. By manipulating the levels of different pathway components, we were able to accelerate and restrict the growth and development of this pathogen. Our results suggest a mechanism by which Chlamydia can tailor its growth rate to the conditions within the host cell. The disruption of this pathway could generate a strain incapable of surviving a typical human immune response and would represent an attractive candidate as an attenuated growth vaccine

Triplet-mediated spin entanglement between organic radicals: integrating first principles and open-quantum-system simulations

Controlling molecular spin quantum bits optically offers the potential to effectively reduce decoherence and raise the working temperature of quantum computers. Here, exchange interactions and spin dynamics, as mediated by an optically driven triplet state, are calculated for a molecule that consists of a pair of radicals and represents a potential quantum-circuit building block. Consistent with the previous experimental observation of spin coherence induced by the triplet state, our work demonstrates an optically driven quantum gate operation scheme in a molecule. A technological blueprint combining a two-dimensional molecular network and programmable nanophotonics, both of which are sufficiently developed, is proposed. We thus realize computational exploration of chemical databases to identify suitable candidates for molecular spin quantum bits and couplers to be hybridized with nanophotonic devices. The work presented here is proposed to realize a new approach for exploring molecular excited states and click chemistry, toward advancing molecular quantum technology

High-temperature antiferromagnetism in molecular semiconductor thin films and nanostructures

The viability of dilute magnetic semiconductors in applications is linked to the strength of the magnetic couplings, and room temperature operation is still elusive in standard inorganic systems. Molecular semiconductors are emerging as an alternative due to their long spin-relaxation times and ease of processing, but, with the notable exception of vanadium-tetracyanoethylene, magnetic transition temperatures remain well below the boiling point of liquid nitrogen. Here we show that thin films and powders of the molecular semiconductor cobalt phthalocyanine exhibit strong antiferromagnetic coupling, with an exchange energy reaching 100 K. This interaction is up to two orders of magnitude larger than in related phthalocyanines and can be obtained on flexible plastic substrates, under conditions compatible with routine organic electronic device fabrication. Ab initio calculations show that coupling is achieved via superexchange between the singly occupied a(1g) ([Image: see text]) orbitals. By reaching the key milestone of magnetic coupling above 77 K, these results establish quantum spin chains as a potentially useable feature of molecular films

Markov chain aggregation and its application to rule-based modelling

Rule-based modelling allows to represent molecular interactions in a compact and natural way. The underlying molecular dynamics, by the laws of stochastic chemical kinetics, behaves as a continuous-time Markov chain. However, this Markov chain enumerates all possible reaction mixtures, rendering the analysis of the chain computationally demanding and often prohibitive in practice. We here describe how it is possible to efficiently find a smaller, aggregate chain, which preserves certain properties of the original one. Formal methods and lumpability notions are used to define algorithms for automated and efficient construction of such smaller chains (without ever constructing the original ones). We here illustrate the method on an example and we discuss the applicability of the method in the context of modelling large signalling pathways

Fully-automated μMRI morphometric phenotyping of the Tc1 mouse model of Down Syndrome

We describe a fully automated pipeline for the morphometric phenotyping of mouse brains from μMRI data, and show its application to the Tc1 mouse model of Down syndrome, to identify new morphological phenotypes in the brain of this first transchromosomic animal carrying human chromosome 21. We incorporate an accessible approach for simultaneously scanning multiple ex vivo brains, requiring only a 3D-printed brain holder, and novel image processing steps for their separation and orientation. We employ clinically established multi-atlas techniques-superior to single-atlas methods-together with publicly-available atlas databases for automatic skull-stripping and tissue segmentation, providing high-quality, subject-specific tissue maps. We follow these steps with group-wise registration, structural parcellation and both Voxel- and Tensor-Based Morphometry-advantageous for their ability to highlight morphological differences without the laborious delineation of regions of interest. We show the application of freely available open-source software developed for clinical MRI analysis to mouse brain data: NiftySeg for segmentation and NiftyReg for registration, and discuss atlases and parameters suitable for the preclinical paradigm. We used this pipeline to compare 29 Tc1 brains with 26 wild-type littermate controls, imaged ex vivo at 9.4T. We show an unexpected increase in Tc1 total intracranial volume and, controlling for this, local volume and grey matter density reductions in the Tc1 brain compared to the wild-types, most prominently in the cerebellum, in agreement with human DS and previous histological findings

Coccidioidomycosis Incidence in Arizona Predicted by Seasonal Precipitation

The environmental mechanisms that determine the inter-annual and seasonal variability in incidence of coccidioidomycosis are unclear. In this study, we use Arizona coccidioidomycosis case data for 1995–2006 to generate a timeseries of monthly estimates of exposure rates in Maricopa County, AZ and Pima County, AZ. We reveal a seasonal autocorrelation structure for exposure rates in both Maricopa County and Pima County which indicates that exposure rates are strongly related from the fall to the spring. An abrupt end to this autocorrelation relationship occurs near the the onset of the summer precipitation season and increasing exposure rates related to the subsequent season. The identification of the autocorrelation structure enabled us to construct a “primary” exposure season that spans August-March and a “secondary” season that spans April–June which are then used in subsequent analyses. We show that October–December precipitation is positively associated with rates of exposure for the primary exposure season in both Maricopa County (R = 0.72, p = 0.012) and Pima County (R = 0.69, p = 0.019). In addition, exposure rates during the primary exposure seasons are negatively associated with concurrent precipitation in Maricopa (R = −0.79, p = 0.004) and Pima (R = −0.64, p = 0.019), possibly due to reduced spore dispersion. These associations enabled the generation of models to estimate exposure rates for the primary exposure season. The models explain 69% (p = 0.009) and 54% (p = 0.045) of the variance in the study period for Maricopa and Pima counties, respectively. We did not find any significant predictors for exposure rates during the secondary season. This study builds on previous studies examining the causes of temporal fluctuations in coccidioidomycosis, and corroborates the “grow and blow” hypothesis