72 research outputs found
Para-infectious brain injury in COVID-19 persists at follow-up despite attenuated cytokine and autoantibody responses
To understand neurological complications of COVID-19 better both acutely and for recovery, we measured markers of brain injury, inflammatory mediators, and autoantibodies in 203 hospitalised participants; 111 with acute sera (1–11 days post-admission) and 92 convalescent sera (56 with COVID-19-associated neurological diagnoses). Here we show that compared to 60 uninfected controls, tTau, GFAP, NfL, and UCH-L1 are increased with COVID-19 infection at acute timepoints and NfL and GFAP are significantly higher in participants with neurological complications. Inflammatory mediators (IL-6, IL-12p40, HGF, M-CSF, CCL2, and IL-1RA) are associated with both altered consciousness and markers of brain injury. Autoantibodies are more common in COVID-19 than controls and some (including against MYL7, UCH-L1, and GRIN3B) are more frequent with altered consciousness. Additionally, convalescent participants with neurological complications show elevated GFAP and NfL, unrelated to attenuated systemic inflammatory mediators and to autoantibody responses. Overall, neurological complications of COVID-19 are associated with evidence of neuroglial injury in both acute and late disease and these correlate with dysregulated innate and adaptive immune responses acutely
Call Center Stress Recognition with Person-Specific Models
Nine call center employees wore a skin conductance sensor
on the wrist for a week at work and reported stress levels of each call.
Although everyone had the same job profile, we found large differences
in how individuals reported stress levels, with similarity from day to day
within the same participant, but large differences across the participants.
We examined two ways to address the individual differences to automat-
ically recognize classes of stressful/non-stressful calls, namely modifying
the loss function of Support Vector Machines (SVMs) to adapt to the
varying priors, and giving more importance to training samples from the
most similar people in terms of their skin conductance lability. We tested
the methods on 1500 calls and achieved an accuracy across participants
of 78.03% when trained and tested on different days from the same per-
son, and of 73.41% when trained and tested on different people using the
proposed adaptations to SVMs
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