Feasibility of Using a Wearable Biosensor Device in Patients at Risk for Alzheimer's Disease Dementia.

BACKGROUND: Alzheimer's disease (AD) is the most common and most costly chronic neurodegenerative disease globally. AD develops over an extended period prior to cognitive symptoms, leaving a "window of opportunity" for targeted risk-reduction interventions. Further, this pre-dementia phase includes early physiological changes in sleep and autonomic regulation, for which wearable biosensor devices may offer a convenient and cost-effective method to assess AD-risk. METHODS: Patients with a family history of AD and no or minimal cognitive complaints were recruited from the Alzheimer's Prevention Clinic at Weill Cornell Medicine and New York-Presbyterian. Of the 40 consecutive patients screened, 34 (85%) agreed to wear a wearable biosensor device (WHOOP). One subject (2.5%) lost the device prior to data collection. Of the remaining subjects, 24 were classified as normal cognition and were asymptomatic, 6 were classified as subjective cognitive decline, and 3 were amyloid-positive (one with pre-clinical AD, one with pre-clinical Lewy-Body Dementia, and one with mild cognitive impairment due to AD). Sleep-cycle, autonomic (heart rate variability [HRV]) and activity measures were collected via WHOOP. Blood biomarkers and neuropsychological testing sensitive to cognitive changes in pre-clinical AD were obtained. Participants completed surveys assessing their sleep-patterns, exercise habits, and attitudes towards WHOOP. The goal of this prospective observational study was to determine the feasibility of using a wrist-worn biosensor device in patients at-risk for AD dementia. Unsupervised machine learning was performed to first separate participants into distinct phenotypic groups using the multivariate biometric data. Additional statistical analyses were conducted to examine correlations between individual biometric measures and cognitive performance. RESULTS: 27 (81.8%) participants completed the follow-up surveys. Twenty-four participants (88.9%) were satisfied with WHOOP after six months, and twenty-three (85.2%) wanted to continue wearing WHOOP. K-means clustering separated participants into two groups. Group 1 was older, had lower HRV, and spent more time in slow-wave sleep (SWS) than Group 2. Group 1 performed better on two cognitive tests assessing executive function: Flanker Inhibitory Attention/Control (FIAC) (p=.031), and Dimensional Change Card Sort (DCCS) (p=.061). In Group 1, DCCS was correlated with SWS (ρ=.68, p=0.024) and HRV (ρ=.6, p=0.019). In Group 2, DCCS was correlated with HRV (ρ=.55, p=0.018). There were no significant differences in blood biomarkers between the two groups. CONCLUSIONS: Wearable biosensor devices may be a feasible tool to assess AD-related physiological changes. Longitudinal collection of sleep and HRV data may potentially be a non-invasive method for monitoring cognitive changes related to pre-clinical AD. Further study is warranted in larger populations.

Growth and enumeration of the meat spoilage bacterium Brochothrix thermosphacta.

Brochothrix thermosphacta is a common meat spoilage bacterium. The morphology of this bacterium changes from coccobacilli and short rods to chains during growth, which may give a false estimation in numbers using some enumeration techniques. Methods for the quantification of this bacterium have been compared. Turbidimetric readings showed good agreement with cell dry weight indicating that the former provides a good measure of the change in cell mass during growth. The turbidimetric method also correlated well with bacterial numbers determined by plate counts, flow cytometry and manual counts (by microscope) over a limited range of 10(7)-10(9) cells/ml. Flow cytometry and manual counts gave a linear relationship over a wider range of 10(5)-10(9) cells/ml. The sensitivity of analysis, growth rates and lag time attained using these methods were also compared. As a consequence of changes in bacterial cell size during growth, turbidimetry over-estimated the growth rate. The plate count method proved unable to detect the difference between bacteria existing as chains or single cells. The sensitivity of analysis and the calculated growth related parameters were similar for flow cytometry and manual counts. This suggests that flow cytometry is capable of counting individual cells in a chain. Further investigation showed that passage of B. thermosphacta cells through the flow cytometer resulted in the breakage of chains into single cells. The reliability, low error and rapidity of this technique make it attractive for bacterial enumeration, something which has been demonstrated using B. thermosphacta, a bacterium which exhibits complex morphologies.

Visualization and modelling of the thermal inactivation of bacteria in a model food.

A large number of incidents of food poisoning have been linked to undercooked meat products. The use of mathematical modelling to describe heat transfer within foods, combined with data describing bacterial thermal inactivation, may prove useful in developing safer food products while minimizing thermal overprocessing. To examine this approach, cylindrical agar blocks containing immobilized bacteria (Salmonella typhimurium and Brochothrix thermosphacta) were used as a model system in this study. The agar cylinders were subjected to external conduction heating by immersion in a water bath. They were then incubated, sliced open, and examined by image analysis techniques for regions of no bacterial growth. A finite-difference scheme was used to model thermal conduction and the consequent bacterial inactivation. Bacterial inactivation rates were modelled with values for the time required to reduce bacterial number by 90% (D) and the temperature increase required to reduce D by 90% taken from the literature. Model simulation results agreed well with experimental results for both bacteria, demonstrating the utility of the technique.

Virus removal from bioproducts using ultrafiltration membranes modified with latex particle pretreatment.

Ultrafiltration is an attractive process for virus removal from bioproducts owing to its high throughput as well as the fact that the operation is carried out under ambient conditions (damage to proteins is highly limited). The principal concern regarding the adoption of conventional ultrafiltration membranes for virus removal is the possibility of the virus passing through abnormally large pores or surface imperfections on the membrane surface. The chief principle behind the present work is to pretreat the membrane by blocking the abnormally large pores using latex particles. Experimental work was conducted to validate this pretreatment using the bacteriophage phi x 174 as a model virus. The results attained were highly encouraging. Different sizes of latex particles were tested by treating a 100 KD molecular weight cut-off membrane, and the transmission of phage (suspended in buffer) through this membrane assessed. In the absence of any particle pretreatment, a virus clearance of 4.78 log reduction value was observed for this membrane. The transmission of phage through the membrane could be reduced by an order of magnitude using 0.11 micron latex particles, or two orders of magnitude using a combination of 0.11 and 0.50 micron particles. The application of latex particles did not hinder the transport of protein through the 100 KD membrane. Protein sieving coefficients obtained using this membrane were 91%, 16% and 2%, for lysozyme, HSA and IgG, respectively.