The Effect of Propofol Versus Isoflurane Anesthesia on Human Cerebrospinal Fluid Markers of Alzheimer's Disease: Results of a Randomized Trial.

BACKGROUND: Preclinical studies have found differential effects of isoflurane and propofol on the Alzheimer's disease (AD)-associated markers tau, phosphorylated tau (p-tau) and amyloid-β (Aβ). OBJECTIVE: We asked whether isoflurane and propofol have differential effects on the tau/Aβ ratio (the primary outcome), and individual AD biomarkers. We also examined whether genetic/intraoperative factors influenced perioperative changes in AD biomarkers. METHODS: Patients undergoing neurosurgical/otolaryngology procedures requiring lumbar cerebrospinal fluid (CSF) drain placement were prospectively randomized to receive isoflurane (n = 21) or propofol (n = 18) for anesthetic maintenance. We measured perioperative CSF sample AD markers, performed genotyping assays, and examined intraoperative data from the electronic anesthesia record. A repeated measures ANOVA was used to examine changes in AD markers by anesthetic type over time. RESULTS: The CSF tau/Aβ ratio did not differ between isoflurane- versus propofol-treated patients (p = 1.000). CSF tau/Aβ ratio and tau levels increased 10 and 24 h after drain placement (p = 2.002×10-6 and p = 1.985×10-6, respectively), mean CSF p-tau levels decreased (p = 0.005), and Aβ levels did not change (p = 0.152). There was no interaction between anesthetic treatment and time for any of these biomarkers. None of the examined genetic polymorphisms, including ApoE4, were associated with tau increase (n = 9 polymorphisms, p > 0.05 for all associations). CONCLUSION: Neurosurgery/otolaryngology procedures are associated with an increase in the CSF tau/Aβ ratio, and this increase was not influenced by anesthetic type. The increased CSF tau/Aβ ratio was largely driven by increases in tau levels. Future work should determine the functional/prognostic significance of these perioperative CSF tau elevations.

Computer vision tools for the non-invasive assessment of autism-related behavioral markers

The early detection of developmental disorders is key to child outcome, allowing interventions to be initiated that promote development and improve prognosis. Research on autism spectrum disorder (ASD) suggests behavioral markers can be observed late in the first year of life. Many of these studies involved extensive frame-by-frame video observation and analysis of a child's natural behavior. Although non-intrusive, these methods are extremely time-intensive and require a high level of observer training; thus, they are impractical for clinical and large population research purposes. Diagnostic measures for ASD are available for infants but are only accurate when used by specialists experienced in early diagnosis. This work is a first milestone in a long-term multidisciplinary project that aims at helping clinicians and general practitioners accomplish this early detection/measurement task automatically. We focus on providing computer vision tools to measure and identify ASD behavioral markers based on components of the Autism Observation Scale for Infants (AOSI). In particular, we develop algorithms to measure three critical AOSI activities that assess visual attention. We augment these AOSI activities with an additional test that analyzes asymmetrical patterns in unsupported gait. The first set of algorithms involves assessing head motion by tracking facial features, while the gait analysis relies on joint foreground segmentation and 2D body pose estimation in video. We show results that provide insightful knowledge to augment the clinician's behavioral observations obtained from real in-clinic assessments.

Biomarkers of PTA

© Springer Science+Business Media New York 2015.Prognostic biomarkers may indicate the likelihood of disease development and speed of progression or may serve as predictive indicators of responsiveness to treatment. Joint injuries, particularly severe injuries, may result in post-traumatic osteoarthritis (PTOA), and pre- and post-injury prognostic biomarkers are needed to enhance primary and secondary prevention approaches for PTOA. Several macromolecules from joint structures found in serum, urine, and synovial fluid are promising biochemical markers for monitoring joint metabolism and health before and after joint injury. The use of metabolic profiling (analysis of small molecules) as a predictive tool for osteoarthritis (OA) has increased in the past decade. Although there is some question as to whether PTOA and idiopathic OA are comparable conditions, there is some evidence to suggest that components of their pathogenesis are similar. Potentially, biomarkers important to the high-risk PTOA profile translate to idiopathic OA. Further work is needed to confirm the utility of macromolecules and metabolites as biomarkers for PTOA, particularly focusing on those strongly correlated to clinical efficacy measures important to the patient (e.g., symptoms, physical function, and quality of life) and the causal pathway of PTOA.