Considerations for quality assurance of multiplex malaria antigen detection assays with large sample sets.

Multiplex assays for malaria antigen detection can gather data from large sample sets, but considerations for the consistency and quality assurance (QA) of mass testing lack evaluation. We present a QA framework for a study occurring November 2019 to March 2020 involving 504 assay plates detecting four Plasmodium antigens: pan-Plasmodium aldolase and lactate dehydrogenase (LDH), histidine-rich protein 2 (HRP2), P. vivax LDH (PvLDH). Controls on each plate included buffer blank, antigen negative blood, and 4-point positive dilution curve. The blank and negative blood provided consistently low signal for all targets except for pAldolase, which showed variability. Positive curve signals decreased throughout the 5-month study duration but retained a coefficient of variation (CV) of < 5%, with the exception of HRP2 in month 5 (CV of 11%). Regression fittings for inter-plate control signals provided mean and standard deviations (SDs), and of 504 assay plates, 6 (1.2%) violated the acceptable deviation limits and were repeated. For the 40,272 human blood samples assayed in this study, of 161,088 potential data points (each sample × 4 antigens), 160,641 (99.7%) successfully passed quality checks. The QA framework presented here can be utilized to ensure quality of laboratory antigen detection for large sample sets.

Serial Reaction Time Task Performance in Older Adults with Neuropsychologically Defined Mild Cognitive Impairment.

BACKGROUND: Studies have found that individuals with mild cognitive impairment (MCI) exhibit a range of deficits outside the realm of primary explicit memory, yet the role of response speed and implicit learning in older adults with MCI have not been established. OBJECTIVE: The current study aims to explore and document response speed and implicit learning in older adults with neuropsychologically defined MCI using a simple serial reaction (SRT) task. In addition, the study aims to explore the feasibility of a novel utilization of the simple cognitive task using machine learning procedures as a proof of concept. METHOD: Participants were 22 cognitively healthy older adults and 20 older adults with MCI confirmed through comprehensive neuropsychological evaluation. Two-sample t-test, multivariate regression, and mixed-effect models were used to investigate group difference in response speed and implicit learning on the SRT task. We also explored the potential utility of SRT feature analysis through random forest classification. RESULTS: With demographic variables controlled, the MCI group showed overall slower reaction time and higher error rate compared to the cognitively healthy volunteers. Both groups showed significant simple motor learning and implicit learning. The learning patterns were not statistically different between the two groups. Random forest classification achieved overall accuracy of 80.9%. CONCLUSIONS: Individuals with MCI demonstrated slower reaction time and higher error rate compared to cognitively healthy volunteers but demonstrated largely preserved motor learning and implicit sequence learning. Preliminary results from random forest classification using features from SRT performance supported further research in this area.

Associations between cerebral blood flow and structural and functional brain imaging measures in individuals with neuropsychologically defined mild cognitive impairment.

Reduced cerebral blood flow (CBF), an indicator of neurovascular processes and metabolic demands, is a common finding in Alzheimer's disease. However, little is known about what contributes to CBF deficits in individuals with mild cognitive impairment (MCI). We examine regional CBF differences in 17 MCI compared with 21 age-matched cognitively healthy older adults. Next, we examined associations between CBF, white matter lesion (WML) volume, amplitude of low-frequency fluctuations, and cortical thickness to better understand whether altered CBF was detectable before other markers and the potential mechanistic underpinnings of CBF deficits in MCI. MCI had significantly reduced CBF, whereas cortical thickness and amplitude of low-frequency fluctuation were not affected. Reduced CBF was associated with the WML volume but not associated with other measures. Given the presumed vascular etiology of WML and relative worsening of vascular health in MCI, it may suggest CBF deficits result from early vascular as opposed to metabolic deficits in MCI. These findings may support vascular mechanisms as an underlying component of cognitive impairment.