A System to Monitor Cognitive Workload in Naturalistic High-Motion Environments

Across many careers, individuals face alternating periods of high and low attention and cognitive workload can impair cognitive function and undermine job performance. We have designed and are developing an unobtrusive system to Monitor, Extract, and Decode Indicators of Cognitive Workload (MEDIC) in naturalistic, high-motion environments. MEDIC is designed to warn individuals, teammates, or supervisors when steps should be taken to augment cognitive readiness. We first designed and manufactured a forehead sensor device that includes a custom fNIRS sensor and a three-axis accelerometer designed to be mounted on the inside of a baseball cap or headband, or standard issue gear such as a helmet or surgeon’s cap. Because the conditions under which MEDIC is designed to operate are more strenuous than typical research efforts assessing cognitive workload, motion artifacts in our data were a persistent issue. Results show wavelet-based filtering improved data quality to salvage data from even the highest-motion conditions. MARA spline motion correction did not further improve data quality. Our testing shows that each of the methods is extremely effective in reducing the effects of motion transients present in the data. In combination, they are able to almost completely remove the transients in the signal while preserving cardiac and low frequency information in the signal which was previously unrecoverable. This has substantially improved the stability of the physiological measures produced by the sensors in high noise conditions

An Unobtrusive System to Measure, Assess, and Predict Cognitive Workload in Real-World Environments

Across many careers, individuals face alternating periods of high and low attention and cognitive workload, which can result in impaired cognitive functioning and can be detrimental to job performance. For example, some professions (e.g., fire fighters, emergency medical personnel, doctors and nurses working in an emergency room, pilots) require long periods of low workload (boredom), followed by sudden, high-tempo operations during which they may be required to respond to an emergency and perform at peak cognitive levels. Conversely, other professions (e.g., air traffic controllers, market investors in financial industries, analysts) require long periods of high workload and multitasking during which the addition of just one more task results in cognitive overload resulting in mistakes. An unobtrusive system to measure, assess, and predict cognitive workload could warn individuals, their teammates, or their supervisors when steps should be taken to augment cognitive readiness. In this talk I will describe an approach to this problem that we have found to be successful across work domains including: (1) a suite of unobtrusive, field-ready neurophysiological, physiological, and behavioral sensors that are chosen to best suit the target environment; (2) custom algorithms and statistical techniques to process and time-align raw data originating from the sensor suite; (3) probabilistic and statistical models designed to interpret the data into the human state of interest (e.g., cognitive workload, attention, fatigue); (4) and machine-learning techniques to predict upcoming performance based on the current pattern of events, and (5) display of each piece of information depending on the needs of the target user who may or may not want to drill down into the functioning of the system to determine how conclusions about human state and performance are determined. I will then focus in on our experimental results from our custom functional near-infrared spectroscopy sensor, designed to operate in real-world environments to be worn comfortably (e.g., positioned into a baseball cap or a surgeons cap) to measure changes in brain blood oxygenation without adding burden to the individual being assessed

Effects of Sleep Deprivation on Brain Bioenergetics, Sleep, and Cognitive Performance in Cocaine-Dependent Individuals

In cocaine-dependent individuals, sleep is disturbed during cocaine use and abstinence, highlighting the importance of examining the behavioral and homeostatic response to acute sleep loss in these individuals. The current study was designed to identify a differential effect of sleep deprivation on brain bioenergetics, cognitive performance, and sleep between cocaine-dependent and healthy control participants. 14 healthy control and 8 cocaine-dependent participants experienced consecutive nights of baseline, total sleep deprivation, and recovery sleep in the research laboratory. Participants underwent [31]P magnetic resonance spectroscopy (MRS) brain imaging, polysomnography, Continuous Performance Task, and Digit Symbol Substitution Task. Following recovery sleep, [31]P MRS scans revealed that cocaine-dependent participants exhibited elevated global brain β-NTP (direct measure of adenosine triphosphate), α-NTP, and total NTP levels compared to those of healthy controls. Cocaine-dependent participants performed worse on the Continuous Performance Task and Digit Symbol Substitution Task at baseline compared to healthy control participants, but sleep deprivation did not worsen cognitive performance in either group. Enhancements of brain ATP levels in cocaine dependent participants following recovery sleep may reflect a greater impact of sleep deprivation on sleep homeostasis, which may highlight the importance of monitoring sleep during abstinence and the potential influence of sleep loss in drug relapse

Excretory/secretory proteome of females and males of the hookworm Ancylostoma ceylanicum

The dynamic host-parasite mechanisms underlying hookworm infection establishment and maintenance in mammalian hosts remain poorly understood but are primarily mediated by hookworm\u27s excretory/secretory products (ESPs), which have a wide spectrum of biological functions. We used ultra-high performance mass spectrometry to comprehensively profile and compare female and male ESPs from the zoonotic human hookwor

Immune boosting by B.1.1.529 (Omicron) depends on previous SARS-CoV-2 exposure

The Omicron, or Pango lineage B.1.1.529, variant of SARS-CoV-2 carries multiple spike mutations with high transmissibility and partial neutralizing antibody (nAb) escape. Vaccinated individuals show protection from severe disease, often attributed to primed cellular immunity. We investigated T and B cell immunity against B.1.1.529 in triple mRNA vaccinated healthcare workers (HCW) with different SARS-CoV-2 infection histories. B and T cell immunity against previous variants of concern was enhanced in triple vaccinated individuals, but magnitude of T and B cell responses against B.1.1.529 spike protein was reduced. Immune imprinting by infection with the earlier B.1.1.7 (Alpha) variant resulted in less durable binding antibody against B.1.1.529. Previously infection-naïve HCW who became infected during the B.1.1.529 wave showed enhanced immunity against earlier variants, but reduced nAb potency and T cell responses against B.1.1.529 itself. Previous Wuhan Hu-1 infection abrogated T cell recognition and any enhanced cross-reactive neutralizing immunity on infection with B.1.1.529

Quantitative, multiplexed, targeted proteomics for ascertaining variant specific SARS-CoV-2 antibody response

Determining the protection an individual has to severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) variants of concern (VoCs) is crucial for future immune surveillance, vaccine development, and understanding of the changing immune response. We devised an informative assay to current ELISA-based serology using multiplexed, baited, targeted proteomics for direct detection of multiple proteins in the SARS-CoV-2 anti-spike antibody immunocomplex. Serum from individuals collected after infection or first- and second-dose vaccination demonstrates this approach and shows concordance with existing serology and neutralization. Our assays show altered responses of both immunoglobulins and complement to the Alpha (B.1.1.7), Beta (B.1.351), and Delta (B.1.617.1) VoCs and a reduced response to Omicron (B1.1.1529). We were able to identify individuals who had prior infection, and observed that C1q is closely associated with IgG1 (r > 0.82) and may better reflect neutralization to VoCs. Analyzing additional immunoproteins beyond immunoglobulin (Ig) G, provides important information about our understanding of the response to infection and vaccination

Excretory/Secretory Proteome of Females and Males of the Hookworm <i>Ancylostoma ceylanicum</i>

The dynamic host-parasite mechanisms underlying hookworm infection establishment and maintenance in mammalian hosts remain poorly understood but are primarily mediated by hookworm’s excretory/secretory products (ESPs), which have a wide spectrum of biological functions. We used ultra-high performance mass spectrometry to comprehensively profile and compare female and male ESPs from the zoonotic human hookworm Ancylostoma ceylanicum, which is a natural parasite of dogs, cats, and humans. We improved the genome annotation, decreasing the number of protein-coding genes by 49% while improving completeness from 92 to 96%. Compared to the previous genome annotation, we detected 11% and 10% more spectra in female and male ESPs, respectively, using this improved version, identifying a total of 795 ESPs (70% in both sexes, with the remaining sex-specific). Using functional databases (KEGG, GO and Interpro), common and sex-specific enriched functions were identified. Comparisons with the exclusively human-infective hookworm Necator americanus identified species-specific and conserved ESPs. This is the first study identifying ESPs from female and male A. ceylanicum. The findings provide a deeper understanding of hookworm protein functions that assure long-term host survival and facilitate future engineering of transgenic hookworms and analysis of regulatory elements mediating the high-level expression of ESPs. Furthermore, the findings expand the list of potential vaccine and diagnostic targets and identify biologics that can be explored for anti-inflammatory potential