Abstract Bi-Allelic Insertions and Deletions (INDELs) are a powerful set of genetic markers for Human Identification (HID). They have certain desirable features, such as low mutation rates, no ...stutter, and potentially small amplicon sizes that could prove effective in some circumstances. In this study, we analyzed the distribution of 114 INDELs in four North American populations (Caucasian, African American, Southwest Hispanic, and Asian) to estimate their distribution in major global populations. Of the 114 INDELs a primary panel of 38 candidate markers was selected that met the criteria of (1) a minimum allele frequency of greater than 0.20 across the populations studied; (2) general concordance with Hardy–Weinberg equilibrium (HWE) expectations; (3) relatively low FST based on the major populations; (4) physical distance between markers greater than 40 Mbp; and (5) a lack of linkage disequilibria between syntenic markers. Additionally, another 11 supplemental markers were selected for an expanded panel of 49 markers which met the above criteria, with the exception that they are separated at least by 20 Mbp. The resulting panels had Random Match Probabilities that were at least 10−16 and 10−19 , respectively, and combined FST values of approximately 0.02. Given these findings, these INDELs should be useful for HID.
The objective of this work is to evaluate the effectiveness of a wearable physiological stress monitoring system in distinguishing between stressed and non-stressed state in older adults using ...machine learning techniques. This system utilizes EDA and BVP signal to detect occurrence of stress as indicated by salivary cortisol measurement which is a reliable objective measure of physiological stress. Data of 19 healthy older adults (11 female and 8 male) with mean age 73.15 ± 5.79 were used for this study. EDA and BVP signals were recorded using a finger tip sensor during the Trier Social Stress Test, which is a well known experimental protocol to reliably induce stress in humans in a social setting. 39 statistical measures of the peak characteristic of EDA and BVP signal were extracted. A supervised feature selection algorithm is used to select important features as an input to the machine learning model. Four machine learning algorithms were evaluated based on their performance in classifying between stressed and non-stressed states. Results indicate that the logistic regression performed the best among Random Forest,
κ
-NN, and Support Vector Machine achieving an macro-average and micro-average f1-score of 0.87 and 0.95 respectively and an AUC score of 0.81. We also evaluated the effectiveness of a novel deep learning Long Short-Term Memory (LSTM) based classifier in distinguishing between stressed and non-stressed state. Results on test data shows that LSTM based classifier achieved an improvement of 6.7% and 2% in terms of macro-average f1-score and micro-average f1-score respectively. Also the AUC score for LSTM classifier is found to be 0.9 which is about 11% higher than the best performing logistic regression model. This work can be used to design a convenient unobtrusive wearable device to monitor stress levels in older adults in their home environment, thereby facilitating aging in place and improving the quality of life.
Effective and practical recruitment strategies are needed to ensure successful recruitment into the Alzheimer disease clinical trials. To facilitate successful recruitment for the NIH-sponsored A4 ...(Anti-Amyloid treatment in Asymptomatic Alzheimer's disease, NCT02008357) trial for the secondary prevention of Alzheimer disease, we developed a small-group community information session to attract and recruit potential research participants. After a successful media campaign, 213 participants were screened through telephone for eligibility, identifying 127 potential participants. Participants were given the option of a traditional one-on-one recruitment session or a small-group session. One-on-one recruitment was performed for 15 participants requesting this procedure, and yielded an overall recruitment rate of 67% (n=10). Substantially more individuals (n=112, 88%) requested small-group sessions to learn about the study. After attending the small-group informational sessions, 98% of potential participants self-reported a greater understanding of the study; and the recruitment rate from these sessions was 90%. Small-group sessions not only improved recruitment success rates, but also contributed to significantly shorter median time for consent processes (20 vs. 60 min) and reduced staff time spent on persons not recruited. Small-group education programs are an effective strategy for enhancing recruitment success and facilitating practical recruitment into clinical trials with high recruitment demands.
Memory evaluation is a key component in the accurate diagnosis of cognitive disorders.One memory procedure that has shown promise in discriminating disease-related cognitive decline from normal ...cognitive aging is the New York University Paragraph Recall Test; however, the effects of education have been unexamined as they pertain to one's literacy level. The current study provides normative data stratified by estimated quality of education as indexed by irregular word reading skill.
Conventional norms were derived from a sample (N = 385) of cognitively intact elderly men who were initially recruited for participation in the PREADViSE clinical trial. A series of multiple linear regression models were constructed to assess the influence of demographic variables on mean NYU Paragraph Immediate and Delayed Recall scores.
Test version, assessment site, and estimated quality of education were significant predictors of performance on the NYU Paragraph Recall Test. Findings indicate that estimated quality of education is a better predictor of memory performance than ethnicity and years of total education. Normative data stratified according to estimated quality of education are presented.
The current study provides evidence and support for normativedata stratified by quality of education as opposed to years of education.
Abstract Adults with Down syndrome (DS) are at high risk for developing Alzheimer's disease after the age of 40 years. To detect white matter (WM) changes in the brain linked to dementia, fractional ...anisotropy (FA) from diffusion tensor imaging was used. We hypothesized that adults with DS without dementia (DS n = 10), DS with dementia (DSAD n = 10) and age matched non-DS subjects (CTL n = 10) would show differential levels of FA and an association with scores from the Brief Praxis Test and the Severe Impairment Battery. WM integrity differences in DS compared with CTL were found predominantly in the frontal lobes. Across all DS adults, poorer Brief Praxis Test performance correlated with reduced FA in the corpus callosum as well as several association tracts, primarily within frontoparietal regions. Our results demonstrate significantly lower WM integrity in DS compared with controls, particularly in the frontal tracts. DS-related WM integrity reductions in a number of tracts were associated with poorer cognition. These preliminary results suggest that late myelinating frontal pathways may be vulnerable to aging in DS.
Background
African American (AA) caregivers of patients with Alzheimer’s disease (AD) and related disorders can play a critical role in maintaining patient health. The Maya Angelou Center for Health ...Equity at Wake Forest University School of Medicine Caregiver College (MC2) aims to (1) improve informal caregivers’ knowledge of AD and related disorders, (2) enhance the quality of life for AD patients and caregiver’s by providing awareness of and access to resources that can help reduce caregiver burden, (3) provide strategies to effectively manage patient symptoms associated with AD, and (4) fill gaps in culturally relevant health education and awareness on AD, brain health, and dementia caregiving skills for AAs.
Method
The 40‐hour inaugural session of MC2 was conducted in‐person in October 2022. Educational sessions were facilitated by experts in various fields including AD, social work, nursing, aging, nutrition, and pharmacy. Topics covered over the course of the educational week included: Alzheimer’s Disease Overview, Health Disparities in AAs, Risk Factors for AD, End of Life Planning, and Caregiver Health. The 21‐item Dementia Knowledge Assessment Tool (DKAT), version 2 (Toye, et al. 2013) was used to track changes in AD knowledge and awareness. A DKAT pre‐test was administered before the educational sessions began on Day 1, and a post‐test assessment was administered at the end of the last educational session on Day 5.
Result
Attendees (N = 21) are African American (100%), primarily female (90.48%), with an average age of 66.8 years (range 42‐82 years, 1 missing value). DKAT assessments from the week‐long educational training, showed an 8% increase in knowledge about AD in this sample of dementia caregivers based on a 5.7 percentage point increase on the DKAT from an average of 71.4% correct pre‐training to an average of 77.1% correct post‐training.
Conclusion
Findings suggest that community‐based educational training is a useful strategy for improving AD knowledge and resource awareness for AA informal caregivers. Results will be used to expand this training to include community members who will be engaged through presentations by attendees of the MC2.
In this work, we have presented the validation of a stress detection model using cortisol as the stress biomarker. The proposed model uses two physiological signals: Galvanic Skin Response (GSR) and ...Photoplethysmograph (PPG) to classify stress into two levels. GSR and PPG signals were collected from a total of 13 participants along with saliva samples taken at time points throughout the duration of the experiment. We have used 10 out of the 13 participants to train our model. Data from the remaining 3 participants was used to test the robustness of the model in distinguishing stressed states from non-stressed states. We have achieved an overall accuracy of 92% with the model achieving precision, recall and f1-score of 93%, 99% and 96% respectively in predicting the occurrences of stressful events. Results indicate the promise of the proposed methodology in accurately detecting the presence of stressful events by generalizing the test data coming from a subset of population in contrast to the training data.
African Americans continue to have worse health outcomes despite attempts to reduce health disparities. This is due, in part, to inadequate access to healthcare, but also to the health care and ...medical mistrust experienced by communities of color. Churches and worship centers have historically served as cultural centers of trusted resources for educational, financial, and health information within African American communities and a growing number of collaborations have developed between academic institutions and community/faith entities. Herein, we describe the infrastructure of a true and sustainable partnership developed with > 100 prominent faith leaders within the Piedmont Triad region of North Carolina for the purpose of developing or expanding existing health ministries within houses of worship, to improve health literacy and overall health long-term. The Triad Pastors Network is an asset-based partnership between the Maya Angelou Center for Health Equity at Wake Forest University School of Medicine and faith leaders in the Piedmont Triad region of North Carolina that was created under the guiding principles of community engagement to improve health equity and decrease health disparities experienced by African American communities. A partnership in which co-equality and shared governance are the core of the framework provides an effective means of achieving health-related goals in a productive and efficient manner. Faith-based partnerships are reliable approaches for improving the health literacy needed to address health disparities and inequities in communities of color.
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