Machine learning identifies novel markers predicting functional decline in older adults

The ability to carry out instrumental activities of daily living, such as paying bills, remembering appointments, and shopping alone decreases with age, yet there are remarkable individual differences in the rate of decline among older adults. Understanding variables associated with decline in instrumental activities of daily living is critical to providing appropriate intervention to prolong independence. Prior research suggests that cognitive measures, neuroimaging, and fluid-based biomarkers predict functional decline. However, a priori selection of variables can lead to the over-valuation of certain variables and exclusion of others that may be predictive. In the present study, we used machine learning techniques to select a wide range of baseline variables that best predicted functional decline in two years in individuals from the Alzheimer’s Disease Neuroimaging Initiative dataset. The sample included 398 individuals characterized as cognitively normal or mild cognitive impairment. Support vector machine classification algorithms were used to identify the most predictive modality from five different data modality types (demographics, structural MRI, fluorodeoxyglucose-PET, neurocognitive, and genetic/fluid-based biomarkers). In addition, variable selection identified individual variables across all modalities that best predicted functional decline in a testing sample. Of the five modalities examined, neurocognitive measures demonstrated the best accuracy in predicting functional decline (accuracy = 74.2%; area under the curve = 0.77), followed by fluorodeoxyglucose-PET (accuracy = 70.8%; area under the curve = 0.66). The individual variables with the greatest discriminatory ability for predicting functional decline included partner report of language in the Everyday Cognition questionnaire, the ADAS13, and activity of the left angular gyrus using fluorodeoxyglucose-PET. These three variables collectively explained 32% of the total variance in functional decline. Taken together, the machine learning model identified novel biomarkers that may be involved in the processing, retrieval, and conceptual integration of semantic information and which predict functional decline two years after assessment. These findings may be used to explore the clinical utility of the Everyday Cognition as a non-invasive, cost and time effective tool to predict future functional decline

Age of First Concussion and Cognitive, Psychological, and Physical Outcomes in NCAA Collegiate Student Athletes

Objective: Concussions are common among youth athletes and could disrupt critical neurodevelopment. This study examined the association between age of first concussion (AFC) and neurocognitive performance, psychological distress, postural stability, and symptoms commonly associated with concussion in healthy collegiate men and women student athletes. Methods: Participants included 4267 collegiate athletes from various contact, limited-contact, and non-contact sports (1818 women and 2449 men) who completed baseline assessments as part of the Concussion Assessment, Research and Education (CARE) Consortium. Psychological distress was assessed with the Brief Symptom Inventory 18; neurocognitive performance was assessed with the Immediate Post-Concussion Assessment and Cognitive Testing (ImPACT); symptoms commonly associated with concussion were assessed with the ImPACT Post-Concussion Symptom Scale; postural stability was assessed with the Balance Error Scoring System. Generalized linear models were used to examine the effects of AFC on clinical outcomes separately in men and women. Results: Later AFC was associated with lower global (Exp(B) = 0.96, P = 0.001) and somatic (Exp(B) = 0.96, P = 0.002) psychological distress on the Brief Symptom Inventory 18 and faster ImPACT reaction time (B = - 0.003, P = 0.001) in women. AFC was not associated with any clinical outcomes in men. Conclusion: Younger AFC was associated with some differences in psychological distress and reaction time among women but not men; however, these results are likely not clinically meaningful. Sociodemographic disparities, pre-existing conditions, and sport type may impact clinical and cognitive outcomes in collegiate athletes more than concussion history. Future work should examine the relationship between AFC and lifespan-related outcomes

Age of First Concussion and Cognitive, Psychological, and Physical Outcomes in NCAA Collegiate Student Athletes

Objective: Concussions are common among youth athletes and could disrupt critical neurodevelopment. This study examined the association between age of first concussion (AFC) and neurocognitive performance, psychological distress, postural stability, and symptoms commonly associated with concussion in healthy collegiate men and women student athletes. Methods: Participants included 4267 collegiate athletes from various contact, limited-contact, and non-contact sports (1818 women and 2449 men) who completed baseline assessments as part of the Concussion Assessment, Research and Education (CARE) Consortium. Psychological distress was assessed with the Brief Symptom Inventory 18; neurocognitive performance was assessed with the Immediate Post-Concussion Assessment and Cognitive Testing (ImPACT); symptoms commonly associated with concussion were assessed with the ImPACT Post-Concussion Symptom Scale; postural stability was assessed with the Balance Error Scoring System. Generalized linear models were used to examine the effects of AFC on clinical outcomes separately in men and women. Results: Later AFC was associated with lower global (Exp(B) = 0.96, P = 0.001) and somatic (Exp(B) = 0.96, P = 0.002) psychological distress on the Brief Symptom Inventory 18 and faster ImPACT reaction time (B = - 0.003, P = 0.001) in women. AFC was not associated with any clinical outcomes in men. Conclusion: Younger AFC was associated with some differences in psychological distress and reaction time among women but not men; however, these results are likely not clinically meaningful. Sociodemographic disparities, pre-existing conditions, and sport type may impact clinical and cognitive outcomes in collegiate athletes more than concussion history. Future work should examine the relationship between AFC and lifespan-related outcomes

Algae as a Potential Source of Biokerosene and Diesel – Opportunities and Challenges

In times of dwindling petroleum reserves, microalgae may pose an alternate energy resource. Their growth is vast under favorable conditions. However, producing microalgae for energy in an economically as well as ecologically feasible way is a difficult task and the prospects are challenging. The chapter gives an insight into perspectives of growing microalgae as a crop, highlighting some of their exceptional energy storage properties in regard to commercial exploitation. Large scale algae production techniques and concepts up to downstream processes are presented. Today, conversion to fuels is constrained by energy usage and costs – but future combination of fuel production with added value products may improve balances and lower the industrial CO2 footprint. These challenges drive research and industry worldwide to constant improvement, supported by numerous funding opportunities. Microalgae in their tremendous diversity are a young and still very much unexplored crop. It is a challenge worth addressing

Chapter 14 Algae as a Potential Source of Biokerosene and Diesel – Opportunities and Challenges

In times of dwindling petroleum reserves, microalgae may pose an alternate energy resource. Their growth is vast under favorable conditions. However, producing microalgae for energy in an economically as well as ecologically feasible way is a difficult task and the prospects are challenging. The chapter gives an insight into perspectives of growing microalgae as a crop, highlighting some of their exceptional energy storage properties in regard to commercial exploitation. Large scale algae production techniques and concepts up to downstream processes are presented. Today, conversion to fuels is constrained by energy usage and costs – but future combination of fuel production with added value products may improve balances and lower the industrial CO2 footprint. These challenges drive research and industry worldwide to constant improvement, supported by numerous funding opportunities. Microalgae in their tremendous diversity are a young and still very much unexplored crop. It is a challenge worth addressing