Biology subjects

Johnson, B.

Publications and source records attributed to Johnson, B..

5 recordsLinked to original sources

bioRxiv2018

Functional Connectivity of Corticostriatal Circuitry and Psychosis-Like Experiences in the General Community

BackgroundPsychotic symptoms are proposed lie on a continuum, ranging from isolated psychosis-like experiences (PLEs) in non-clinical populations to frank disorder. Here, we investigate neurobiological correlates of this symptomatologic continuum by examining whether functional connectivity of dorsal corticostriatal circuitry, which is disrupted in patients and high-risk individuals, is associated with the severity of subclinical PLEs.\n\nMethodsA community sample of 672 adults with no history of psychiatric or neurological illnesses completed a battery of seven questionnaires spanning various PLE domains. Principal component analysis (PCA) estimated major dimensions of PLEs from the questionnaires. PCA dimension scores were then correlated with whole-brain voxelwise functional connectivity (FC) maps of the striatum in a subset of 353 participants who completed a resting-state neuroimaging protocol.\n\nResultsPCA identified two dimensions of PLEs accounting for 62.57% of variance in the measures, corresponding to positive and negative PLEs. Reduced FC between the dorsal striatum and prefrontal cortex correlated with higher positive PLEs. Negative PLEs correlated with increased FC between the dorsal striatum and visual and sensorimotor areas. In the ventral corticostriatal system, positive and negative PLEs were both associated with FC between the ventro-rostral putamen and sensorimotor cortices.\n\nConclusionsConsistent with past findings in patients and high-risk individuals, subthreshold positive symptomatology is associated with reduced FC of the dorsal circuit. These findings suggest that the connectivity of this circuit tracks the expression of psychotic phenomena across a broad spectrum of severity, extending from the subclinical domain to clinical diagnosis.

neuroscience↗

bioRxiv2018

Large-scale experimental removal of non-native slider turtles has unexpected consequences on basking behavior for both conspecifics and a native, threatened turtle

The red-eared slider turtle (Trachemys scripta elegans; RES) is one of the worlds most invasive species. Native to the central United States, RES are now widely established in freshwater habitats across the globe, largely due to release of unwanted pets. Laboratory and mesocosm experiments suggest that introduced RES are competitively dominant to native turtles, but such competition remains untested in the wild. Here, we experimentally removed introduced RES to test whether they compete for critical basking habitat with native, threatened western pond turtles (Emys marmorata; WPT), a species being considered for listing under the U.S. Endangered Species Act. Following removal, we found that both the remaining RES as well as WPT altered their basking distribution but in a manner inconsistent with strong interspecific competition. However, these findings suggest strong intraspecific competition for basking sites amongst RES and that interspecific competition between WPT and introduced RES likely occurs at higher RES densities. Our works suggests RES influence the behavior of native species in the wild and indicates that RES removal may be most beneficial at high RES densities. This experiment highlights the importance of considering experimental venue when evaluating competition between native and non-native species and should encourage conservation biologists to treat removal efforts as experiments.

ecology↗

bioRxiv2018

Human hippocampal high-gamma activity during rest periods in a virtual navigation task

In rodents, hippocampal cell assemblies formed during learning of a navigation task are observed to re-emerge during resting (offline) periods, accompanied by high-frequency oscillations (HFOs). This phenomenon is believed to reflect mechanisms for strengthening newly-formed memory traces. Using magnetoencephalography recordings and a beamforming source location algorithm (synthetic aperture magnetometry), we investigated high-gamma (80 - 140 Hz) oscillations in the hippocampal region in 18 human participants during inter-trial rest periods in a virtual navigation task. We found right hippocampal gamma oscillations mirrored the pattern of theta power in the same region during navigation, varying as a function of environmental novelty. Gamma power during inter-trial rest periods was positively correlated with theta power during navigation in the first training set when the environment was new and predicted faster learning in the subsequent training set two where the environment became familiar. These findings provide evidence for human hippocampal reactivation accompanied by high-gamma activities immediately after learning and establish a link between hippocampal high-gamma activities and memory consolidation.

neuroscience↗

bioRxiv2017

MatchMiner: An open source computational platform for real-time matching of cancer patients to precision medicine clinical trials using genomic and clinical criteria

BackgroundMolecular profiling of cancers is now routine at many cancer centers, and the number of precision cancer medicine clinical trials, which are informed by profiling, is steadily rising. Additionally, these trials are becoming increasingly complex, often having multiple arms and many genomic eligibility criteria. Currently, it is a challenging for physicians to match patients to relevant clinical trials using the patients genomic profile, which can lead to missed opportunities. Automated matching against uniformly structured and encoded genomic eligibility criteria is essential to keep pace with the complex landscape of precision medicine clinical trials.\n\nResultsTo meet these needs, we built and deployed an automated clinical trial matching platform called MatchMiner at the Dana-Farber Cancer Institute (DFCI). The platform has been integrated with Profile, DFCIs enterprise genomic profiling project, which contains tumor profile data for >20,000 patients, and has been made available to physicians across the Institute. As no current standard exists for encoding clinical trial eligibility criteria, a new language called Clinical Trial Markup Language (CTML) was developed, and over 178 genomically-driven clinical trials were encoded using this language. The platform is open source and freely available for adoption by other institutions.\n\nConclusionMatchMiner is the first open platform developed to enable computational matching of patient-specific genomic profiles to precision cancer medicine clinical trials. Creating MatchMiner required developing clinical trial eligibility standards to support genome-driven matching and developing intuitive interfaces to support practical use-cases. Given the complexity of tumor profiling and the rapidly changing multi-site nature of genome-driven clinical trials, open source software is the most efficient, scalable, and economical option for matching cancer patients to clinical trials.

bioinformatics↗

bioRxiv2017

Phenology supports the eco-environmental hypothesis for Ebola spillover events

Ebola virus disease outbreaks in animals (including humans and great apes) start with sporadic host switches from unknown reservoir species. The factors leading to such spillover events are little explored. Filoviridae viruses have a wide range of natural hosts and are unstable once outside hosts. Spillover events, which involve the physical transfer of viral particles across species, could therefore be directly promoted by conditions of host ecology and environment. In this report we outline a proof of concept that temporal fluctuations of a set of ecological and environmental variables describing the dynamics of the host ecosystem are able to predict such events of Ebola virus spillover to humans and animals. We compiled a dataset of climate and plant phenology variables and Ebola virus disease spillovers in humans and animals. We identified critical biotic and abiotic conditions for spillovers via multiple regression and neural networks based time series regression. Phenology variables proved to be overall better predictors than climate variables. African phenology variables are not yet available as a comprehensive online resource. Given the likely importance of phenology for forecasting the likelihood of future Ebola spillover events, our results highlight the need for cost-effective transect surveys to supply phenology data for predictive modelling efforts.

epidemiology↗