An Observational Study With the Janssen Autism Knowledge Engine (JAKE((R))) in Individuals With Autism Spectrum Disorder

Objective: The Janssen Autism Knowledge Engine (JAKE(R)) is a clinical research outcomes assessment system developed to more sensitively measure treatment outcomes and identify subpopulations in autism spectrum disorder (ASD). Here we describe JAKE and present results from its digital phenotyping (My JAKE) and biosensor (JAKE Sense) components. Methods: An observational, non-interventional, prospective study of JAKE in children and adults with ASD was conducted at nine sites in the United States. Feedback on JAKE usability was obtained from caregivers. JAKE Sense included electroencephalography, eye tracking, electrocardiography, electrodermal activity, facial affect analysis, and actigraphy. Caregivers of individuals with ASD reported behaviors using My JAKE. Results from My JAKE and JAKE Sense were compared to traditional ASD symptom measures. Results: Individuals with ASD (N = 144) and a cohort of typically developing (TD) individuals (N = 41) participated in JAKE Sense. Most caregivers reported that overall use and utility of My JAKE was easy (69%, 74/108) or very easy (74%, 80/108). My JAKE could detect differences in ASD symptoms as measured by traditional methods. The majority of biosensors included in JAKE Sense captured sizable amounts of quality data (i.e., 93-100% of eye tracker, facial affect analysis, and electrocardiogram data was of good quality), demonstrated differences between TD and ASD individuals, and correlated with ASD symptom scales. No significant safety events were reported. Conclusions: My JAKE was viewed as easy or very easy to use by caregivers participating in research outside of a clinical study. My JAKE sensitively measured a broad range of ASD symptoms. JAKE Sense biosensors were well-tolerated. JAKE functioned well when used at clinical sites previously inexperienced with some of the technologies. Lessons from the study will optimize JAKE for use in clinical trials to assess ASD interventions. Additionally, because biosensors were able to detect features differentiating TD and ASD individuals, and also were correlated with standardized symptom scales, these measures could be explored as potential biomarkers for ASD and as endpoints in future clinical studies. Clinical Trial Registration: https://clinicaltrials.gov/ct2/show/NCT02668991 identifier: NCT02668991

Social attention to activities in children and adults with autism spectrum disorder: effects of context and age

BackgroundDiminished visual monitoring of faces and activities of others is an early feature of autism spectrum disorder (ASD). It is uncertain whether deficits in activity monitoring, identified using a homogeneous set of stimuli, persist throughout the lifespan in ASD, and thus, whether they could serve as a biological indicator ("biomarker") of ASD. We investigated differences in visual attention during activity monitoring in children and adult participants with autism compared to a control group of participants without autism.MethodsEye movements of participants with autism (n = 122; mean age [SD] = 14.5 [8.0] years) and typically developing (TD) controls (n = 40, age = 16.4 [13.3] years) were recorded while they viewed a series of videos depicting two female actors conversing while interacting with their hands over a shared task. Actors either continuously focused their gaze on each other's face (mutual gaze) or on the shared activity area (shared focus). Mean percentage looking time was computed for the activity area, actors' heads, and their bodies.ResultsCompared to TD participants, participants with ASD looked longer at the activity area (mean % looking time: 58.5% vs. 53.8%, p < 0.005) but less at the heads (15.2% vs. 23.7%, p < 0.0001). Additionally, within-group differences in looking time were observed between the mutual gaze and shared focus conditions in both participants without ASD (activity: Δ = - 6.4%, p < 0.004; heads: Δ = + 3.5%, p < 0.02) and participants with ASD (bodies: Δ = + 1.6%, p < 0.002).LimitationsThe TD participants were not as well characterized as the participants with ASD. Inclusion criteria regarding the cognitive ability [intelligence quotient (IQ) > 60] limited the ability to include individuals with substantial intellectual disability.ConclusionsDifferences in attention to faces could constitute a feature discriminative between individuals with and without ASD across the lifespan, whereas between-group differences in looking at activities may shift with development. These findings may have applications in the search for underlying biological indicators specific to ASD. Trial registration ClinicalTrials.gov identifier NCT02668991

A Radial Age Gradient in the Geometrically Thick Disk of the Milky Way

In the Milky Way, the thick disk can be defined using individual stellar abundances, kinematics, or age, or geometrically, as stars high above the midplane. In nearby galaxies, where only a geometric definition can be used, thick disks appear to have large radial scale lengths, and their red colors suggest that they are uniformly old. The Milky Way's geometrically thick disk is also radially extended, but it is far from chemically uniform: α-enhanced stars are confined within the inner Galaxy. In simulated galaxies, where old stars are centrally concentrated, geometrically thick disks are radially extended, too. Younger stellar populations flare in the simulated disks' outer regions, bringing those stars high above the midplane. The resulting geometrically thick disks therefore show a radial age gradient, from old in their central regions to younger in their outskirts. Based on our age estimates for a large sample of giant stars in the APOGEE survey, we can now test this scenario for the Milky Way. We find that the geometrically defined thick disk in the Milky Way has indeed a strong radial age gradient: the median age for red clump stars goes from ~9 Gyr in the inner disk to 5 Gyr in the outer disk. We propose that at least some nearby galaxies could also have thick disks that are not uniformly old, and that geometrically thick disks might be complex structures resulting from different formation mechanisms in their inner and outer parts

Comparisons of electron fluxes measured in the crustal fields at Mars by the MGS magnetometer/electron reflectometer instrument with a B field–dependent transport code

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/95296/1/jgre1782.pd

An Observational Study With the Janssen Autism Knowledge Engine (JAKE®) in Individuals With Autism Spectrum Disorder

Objective: The Janssen Autism Knowledge Engine (JAKE®) is a clinical research outcomes assessment system developed to more sensitively measure treatment outcomes and identify subpopulations in autism spectrum disorder (ASD). Here we describe JAKE and present results from its digital phenotyping (My JAKE) and biosensor (JAKE Sense) components.Methods: An observational, non-interventional, prospective study of JAKE in children and adults with ASD was conducted at nine sites in the United States. Feedback on JAKE usability was obtained from caregivers. JAKE Sense included electroencephalography, eye tracking, electrocardiography, electrodermal activity, facial affect analysis, and actigraphy. Caregivers of individuals with ASD reported behaviors using My JAKE. Results from My JAKE and JAKE Sense were compared to traditional ASD symptom measures.Results: Individuals with ASD (N = 144) and a cohort of typically developing (TD) individuals (N = 41) participated in JAKE Sense. Most caregivers reported that overall use and utility of My JAKE was “easy” (69%, 74/108) or “very easy” (74%, 80/108). My JAKE could detect differences in ASD symptoms as measured by traditional methods. The majority of biosensors included in JAKE Sense captured sizable amounts of quality data (i.e., 93–100% of eye tracker, facial affect analysis, and electrocardiogram data was of good quality), demonstrated differences between TD and ASD individuals, and correlated with ASD symptom scales. No significant safety events were reported.Conclusions: My JAKE was viewed as easy or very easy to use by caregivers participating in research outside of a clinical study. My JAKE sensitively measured a broad range of ASD symptoms. JAKE Sense biosensors were well-tolerated. JAKE functioned well when used at clinical sites previously inexperienced with some of the technologies. Lessons from the study will optimize JAKE for use in clinical trials to assess ASD interventions. Additionally, because biosensors were able to detect features differentiating TD and ASD individuals, and also were correlated with standardized symptom scales, these measures could be explored as potential biomarkers for ASD and as endpoints in future clinical studies.Clinical Trial Registration:https://clinicaltrials.gov/ct2/show/NCT02668991 identifier: NCT0266899

Nonstandard Errors

In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty-nonstandard errors (NSEs). We study NSEs by letting 164 teams test the same hypotheses on the same data. NSEs turn out to be sizable, but smaller for more reproducible or higher rated research. Adding peer-review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants

Non-Standard Errors

In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty: Non-standard errors (NSEs). We study NSEs by letting 164 teams test the same hypotheses on the same data. NSEs turn out to be sizable, but smaller for better reproducible or higher rated research. Adding peer-review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants