Innovative research methods for studying treatments for rare diseases: methodological review

Objective: To examine methods for generating evidence on health outcomes in patients with rare diseases. Design: Methodological review of existing literature. Setting: PubMed, Embase, and Academic Search Premier searched for articles describing innovative approaches to randomized trial design and analysis methods and methods for conducting observational research in patients with rare diseases. Main outcome measures We assessed information related to the proposed methods, the specific rare disease being studied, and outcomes from the application of the methods. We summarize methods with respect to their advantages in studying health outcomes in rare diseases and provide examples of their application. Results: We identified 46 articles that proposed or described methods for studying patient health outcomes in rare diseases. Articles covered a wide range of rare diseases and most (72%) were published in 2008 or later. We identified 16 research strategies for studying rare disease. Innovative clinical trial methods minimize sample size requirements (n=4) and maximize the proportion of patients who receive active treatment (n=2), strategies crucial to studying small populations of patients with limited treatment choices. No studies describing unique methods for conducting observational studies in patients with rare diseases were identified. Conclusions: Though numerous studies apply unique clinical trial designs and considerations to assess patient health outcomes in rare diseases, less attention has been paid to innovative methods for studying rare diseases using observational data

Dynamical model of sequential spatial memory: winnerless competition of patterns

We introduce a new biologically-motivated model of sequential spatial memory which is based on the principle of winnerless competition (WLC). We implement this mechanism in a two-layer neural network structure and present the learning dynamics which leads to the formation of a WLC network. After learning, the system is capable of associative retrieval of pre-recorded sequences of spatial patterns.Comment: 4 pages, submitted to PR

Interactive Effects of Drought and Fire on Co-Existing Woody and Herbaceous Communities in a Temperate Mesic Grassland

Increased drought and woody encroachment are likely to have substantial and interactive effects on grassland carbon and water cycling in the future. However, we currently lack necessary information to accurately predict grassland responses to drought-by-fire interactions in areas experiencing woody encroachment. A more thorough understanding of these interactive effects on grass-shrub physiology would improve the effectiveness of demographic vegetation models and refine predictions of future changes in grassland ecosystem function. To this end, we constructed passive rainout shelters over mature Cornus drummondii shrubs and co-existing grasses in two fire treatments (1-year and 4-year burn frequency) at the Konza Prairie Biological Station (north-eastern Kansas, USA) that reduced precipitation by 50%. Plant responses to drought and fire were monitored at the leaf-level (gas exchange, predawn and midday water potential, turgor loss point) and the whole-plant level (aboveground biomass). Here, we report results from the 2020 growing season, after three years of treatment. Photosynthetic rates of C. drummondii and Andropogon gerardii, a dominant C4 grass, were lower in drought treatments at the end of the growing season. A. gerardii also exhibited higher photosynthetic rates in the 4-year burn watershed, but C. drummondii rates were not impacted by burn frequency. Predawn and midday leaf water potential for both species, as well as turgor loss point for C. drummondii, were lower in the 4-year burn treatment, indicating increased water stress. This trend was more pronounced in drought shelters for C. drummondii. These results indicate that three years of 50% precipitation reduction has resulted in modest impacts on water stress and gas exchange in both species. Long-term studies of co-existing grasses and shrubs are useful for informing management of woody encroachment during drought and help to identify whether multiple external pressures (drought and fire) are needed to reverse grassland-to-shrubland transitions in temperate mesic grasslands

Hydraulic Responses of Shrubs and Grasses to Fire Frequency and Drought in a Tallgrass Prairie Experiencing Bush Encroachment

The increase in abundance and density of woody plants in herbaceous ecosystems (i.e. bush encroachment) is occurring globally and is driven by reduced fire frequency, climate change, and the utilization of deeper, more reliable soil water by woody plants. Thus, a comprehensive understanding of the physiological processes through which woody and herbaceous plants use water will provide greater insight into the mechanisms of bush encroachment, as well as the trajectory of encroachment in a changing climate. Our objective was to assess how experimental changes in water availability and fire frequency impact belowground water-use traits in Cornus drummondii, the primary encroaching shrub within North American tallgrass prairies, and Andropogon gerardii, a dominant C4 grass. Shelters that reduced precipitation by 50% (drought) and 0% (control) were built over mature shrubs growing in sites that were burned at 1-year and 4-year frequencies. We assessed the water transport capability of shrubs and grasses growing in each treatment by measuring the maximum hydraulic conductance (Kmax) of entire root systems. We also assessed the vulnerability of shrub root segments to loss of hydraulic function by measuring the pressure at which 50% of the maximum hydraulic conductivity is lost (P50). Grass and shrub roots had opposite responses to drought and these patterns varied with fire treatment. Grasses growing in drought plots had lower root Kmax than control grasses. Conversely, root Kmax did not differ significantly between treatments in shrubs. However, drought shrub roots were less vulnerable to water stress than control roots (P50=-1.5 and -0.20 MPa, respectively). These results suggest that the ability of grass roots to use water declined with drought, while the ability of shrub roots to resist water stress increased with drought. Future work should investigate whether these drought responses are associated with altered root growth patterns

Predictive validity of the UK clinical aptitude test in the final years of medical school:a prospective cohort study

Peer reviewedPublisher PD

Prioritized Sweeping Neural DynaQ with Multiple Predecessors, and Hippocampal Replays

During sleep and awake rest, the hippocampus replays sequences of place cells that have been activated during prior experiences. These have been interpreted as a memory consolidation process, but recent results suggest a possible interpretation in terms of reinforcement learning. The Dyna reinforcement learning algorithms use off-line replays to improve learning. Under limited replay budget, a prioritized sweeping approach, which requires a model of the transitions to the predecessors, can be used to improve performance. We investigate whether such algorithms can explain the experimentally observed replays. We propose a neural network version of prioritized sweeping Q-learning, for which we developed a growing multiple expert algorithm, able to cope with multiple predecessors. The resulting architecture is able to improve the learning of simulated agents confronted to a navigation task. We predict that, in animals, learning the world model should occur during rest periods, and that the corresponding replays should be shuffled.Comment: Living Machines 2018 (Paris, France

Representational capacity of a set of independent neurons

The capacity with which a system of independent neuron-like units represents a given set of stimuli is studied by calculating the mutual information between the stimuli and the neural responses. Both discrete noiseless and continuous noisy neurons are analyzed. In both cases, the information grows monotonically with the number of neurons considered. Under the assumption that neurons are independent, the mutual information rises linearly from zero, and approaches exponentially its maximum value. We find the dependence of the initial slope on the number of stimuli and on the sparseness of the representation.Comment: 19 pages, 6 figures, Phys. Rev. E, vol 63, 11910 - 11924 (2000

Model of the Hippocampal Learning of Spatio-temporal Sequences

International audienceWe propose a model of the hippocampus aimed at learning the timed association between subsequent sensory events. The properties of the neural network allow it to learn and predict the evolution of con- tinuous rate-coded signals as well as the occurrence of transitory events, using both spatial and non-spatial information. The system is able to provide predictions based on the time trace of past sensory events. Per- formance of the neural network in the precise temporal learning of spatial and non-spatial signals is tested in a simulated experiment. The ability of the hippocampus proper to predict the occurrence of upcoming spatio- temporal events could play a crucial role in the carrying out of tasks requiring accurate time estimation and spatial localization