ICT has good sensitivity/specificity for MHE diagnosis, is reliable and is equivalent to SPT for predicting OHE development.

Mild cognitive impairment (MCI) is associated with early memory loss, Alzheimer neuropathology, inefficient or ineffective neural processing, and increased risk for Alzheimer’s disease (AD). Unfortunately, treatments aimed at improving clinical symptoms or markers of brain function generally have been of limited value. Physical exercise is often recommended for people diagnosed with MCI, primarily because of its widely reported cognitive benefits in healthy older adults. However, it is unknown if exercise actually benefits brain function during memory retrieval in MCI. Here, we examined the effects of exercise training on semantic memory activation during functional magnetic resonance imaging. Seventeen MCI participants and 18 cognitively intact controls, similar in sex, age, education, genetic risk, and medication use, volunteered for a 12-week exercise intervention consisting of supervised treadmill walking at a moderate intensity. Both MCI and control participants significantly increased their cardiorespiratory fitness by approximately 10% on a treadmill exercise test. Before and after the exercise intervention, participants completed a fMRI famous name discrimination task and a neuropsychological battery, Performance on Trial 1 of a list-learning task significantly improved in the MCI participants. Eleven brain regions activated during the semantic memory task showed a significant decrease in activation intensity following the intervention that was similar between groups (p-values ranged .048 to .0001). These findings suggest exercise may improve neural efficiency during semantic memory retrieval in MCI and cognitively intact older adults, and may lead to improvement in cognitive function. Clinical trials are needed to determine if exercise is effective to delay conversion to AD.

Background: Exercise training has been associated with greater cerebral blood flow (CBF) in cognitively normal older adults (CN). Alterations in CBF, including compensatory perfusion in the prefrontal cortex, may facilitate changes to the brain’s neural infrastructure. Objective: To examine the effects of a 12-week aerobic exercise intervention on resting CBF and cognition in CN and those with mild cognitive impairment (MCI). We hypothesized individuals with MCI (vs. CN) would exhibit greater whole brain CBF at baseline and that exercise would mitigate these differences. We also expected CBF changes to parallel cognitive improvements. Methods: Before and after a 12-week exercise intervention, 18 CN and 17 MCI participants (aged 61–88) underwent aerobic fitness testing, neuropsychological assessment, and an MRI scan. Perfusion-weighted images were collected using a GE 3T MR system. Repeated measures analyses of covariance were used to test within- and between-group differences over time, followed by post-hoc analyses to examine links between CBF changes and cognitive improvement. Results: At baseline, individuals with MCI (vs. CN) exhibited significantly elevated perfusion in the left insula. Twelve weeks of aerobic exercise reversed this discrepancy. Additionally, exercise improved working memory (measured by the Rey Auditory Verbal Learning Test) and verbal fluency (measured by the Controlled Oral Word Association Test) and differentially altered CBF depending on cognitive status. Among those with MCI, decreased CBF in the left insula and anterior cingulate cortex was associated with improved verbal fluency. Conclusions: Exercise training alters CBF and improves cognitive performance in older adults with and without cognitive impairment. Future studies must evaluate the mediating effects of CBF on the association between exercise training and cognition.

Modern polymer science suffers from the curse of multidimensionality. The large chemical space imposed by including combinations of monomers into a statistical copolymer overwhelms polymer synthesis and characterization technology and limits the ability to systematically study structure–property relationships. To tackle this challenge in the context of 19F magnetic resonance imaging (MRI) agents, we pursued a computer-guided materials discovery approach that combines synergistic innovations in automated flow synthesis and machine learning (ML) method development. A software-controlled, continuous polymer synthesis platform was developed to enable iterative experimental–computational cycles that resulted in the synthesis of 397 unique copolymer compositions within a six-variable compositional space. The nonintuitive design criteria identified by ML, which were accomplished by exploring <0.9% of the overall compositional space, lead to the identification of >10 copolymer compositions that outperformed state-of-the-art materials.