scholarly journals PL - 038 Habitual swimming exercise induced partial resistance to rat Alzheimer's disease

2018 ◽  
Vol 1 (1) ◽  
Author(s):  
Timon Cheng-Yi Liu ◽  
Quan-Guang Zhang ◽  
Chong-Yun Wu ◽  
Luo-Dan Yang ◽  
Ling Zhu ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Golden Section ◽  
Quantitative Difference ◽  
P Value ◽  
Data Sets ◽  
Self Similarity ◽  
Data Set ◽  
First Order ◽  
Self Similar

Objective  In MSSE, we have divided male 2.5-month-old Sprague-Dawley rats into the following 4 groups: control (C), habitual swimming (SW), Alzheimer’s disease (AD) induction without swimming (AD), and habitual swimming and then AD induction (SA), and found the perfect resistance of habitual swimming to AD induction by using the P value statistics of the 5 behavior parameters of rats and the 23 physiological and biochemical parameters of their hippocampus. The topological difference  of four groups were further calculated in this paper by using quantitative difference (QD) and self-similar approach. Methods 1. The logarithm to base golden section τ (lt) is called golden logarithm. It was found that σ=ltσ ≈ 0.710439287156503. 2. For a process from x1 to x2, lx(1,2)=lt(x2/x1) and its absolute vale are called the process logarithm and its QD, QDx(1,2). There are QD threshold values (αx,βx,γx) of function x which can be calculated in terms of σ. The function x is kept to be constant if QDx(1,2) < αx. A function in/far from its function-specific homeostasis is called a normal/dysfunctional function. A normal function can resist a disturbance under its threshold so that QDx(1,2) < βx. A dysfunctional function is defined as the QD is significant if βx ≦QDx(1,2) < γx and extraordinarily significant if QDx(1,2) ≧ γx. 3. Self-similarity was studied in the fractal literature: a pattern is self-similar if it does not vary with spatial or temporal scale. First-order self-similarity condition leads to the power law between two data sets A = {xi} and B = {yi}; yi = ai xi if the QDi of ai and the average of {ai} is smaller than βmin=min{βi} and the average QD of {QDi} is smaller than αmin=min{αi}. 4. The σ algorithm for integrative biology was established based on high-order self-similarity. Those parameters that contribute to the topological difference were the biomarkers. Results The 28 dimension data set consisted of all the 28 parameters. The first-order self-similarity held true for the 28 dimension data sets between groups C and SW. The topological algorithm of other groups suggested three AD biomarkers, protein carbonyl, granules density of presynaptic synaptophysin in the hippocampal CA1 and malondialdehyde intensity. The first two biomarkers were completely reversed by exercise pretreatment, but the third biomarker was partially reversed. Conclusions  Exercise pretraining exerts partial benefits on AD that support its use as a promising new therapeutic option for prevention of neurodegeneration in the elderly and/or AD population. 

scholarly journals OR-056 No cardiovascular responses to energy drink consumption in young healthy adult

2018 ◽  
Vol 1 (2) ◽  
Author(s):  
Rui Duan ◽  
Timon Cheng-Yi Liu ◽  
Quan-Guang Zhang
Keyword(s):  
Healthy Adult ◽  
Quantitative Difference ◽  
Cardiovascular Responses ◽  
Energy Drink ◽  
Healthy Adults ◽  
Data Sets ◽  
Self Similarity ◽  
Data Set ◽  
First Order ◽  
Energy Drink Consumption

Objective Svatikova et al. (2015) in JAMA have conducted a randomized trial of cardiovascular responses to energy drink consumption in healthy adults, and found it significantly increased levels of blood pressure and catecholamines in young healthy adults. Their data were re-analyzed in terms of fractal self-similarity and quantitative difference (QD) in this paper. Methods 1. The logarithm to base golden section τ (lt) is called golden logarithm. It was found that σ=ltσ ≈ 0.710439287156503. 2. For a process from x1 to x2, lx(1,2)=lt(x2/x1) and its absolute vale are called the process logarithm and its QD, QDx(1,2). There are QD threshold values (αx,βx,γx) of function x which can be calculated in terms of σ. The function x is kept to be constant if QDx(1,2) < αx. A function in/far from its function-specific homeostasis is called a normal/dysfunctional function. A normal function can resist a disturbance under its threshold so that QDx(1,2) < βx. A dysfunctional function is defined as the QD is significant if βx ≦QDx(1,2) < γx and extraordinarily significant if QDx(1,2) ≧ γx. 3. Self-similarity was studied in the fractal literature: a pattern is self-similar if it does not vary with spatial or temporal scale. First-order self-similarity condition leads to the power law between two data sets A = {xi} and B = {yi}; yi = ai xi if the QDi of ai and the average of {ai} is smaller than βmin=min{βi} and the average QD of {QDi} is smaller than αmin=min{αi}. 4. The σ algorithm for integrative biology was established based on high-order self-similarity. Results The 18 dimension data set consisted of all the 18 parameters. The first-order self-similarity held for the 18 dimension data sets between after and before for placebo or energy drink, and between placebo and energy drink for the 18 dimension ratio data set of after to before. Conclusions There may be no cardiovascular responses to energy drink consumption in young healthy adult.

scholarly journals Data Analysis With Shapley Values For Automatic Subject Selection in Alzheimer's Disease Data Sets Using Interpretable Machine Learning

2021 ◽  
Author(s):  
Louise Bloch ◽  
Christoph M. Friedrich
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Test Data ◽  
Noisy Data ◽  
Training Data ◽  
Data Sets ◽  
Data Set ◽  
Model Interpretation ◽  
Percentage Points ◽  
Shapley Values

Abstract Background: The prediction of whether Mild Cognitive Impaired (MCI) subjects will prospectively develop Alzheimer's Disease (AD) is important for the recruitment and monitoring of subjects for therapy studies. Machine Learning (ML) is suitable to improve early AD prediction. The etiology of AD is heterogeneous, which leads to noisy data sets. Additional noise is introduced by multicentric study designs and varying acquisition protocols. This article examines whether an automatic and fair data valuation method based on Shapley values can identify subjects with noisy data. Methods: An ML-workow was developed and trained for a subset of the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort. The validation was executed for an independent ADNI test data set and for the Australian Imaging, Biomarker and Lifestyle Flagship Study of Ageing (AIBL) cohort. The workow included volumetric Magnetic Resonance Imaging (MRI) feature extraction, subject sample selection using data Shapley, Random Forest (RF) and eXtreme Gradient Boosting (XGBoost) for model training and Kernel SHapley Additive exPlanations (SHAP) values for model interpretation. This model interpretation enables clinically relevant explanation of individual predictions. Results: The XGBoost models which excluded 116 of the 467 subjects from the training data set based on their Logistic Regression (LR) data Shapley values outperformed the models which were trained on the entire training data set and which reached a mean classification accuracy of 58.54 % by 14.13 % (8.27 percentage points) on the independent ADNI test data set. The XGBoost models, which were trained on the entire training data set reached a mean accuracy of 60.35 % for the AIBL data set. An improvement of 24.86 % (15.00 percentage points) could be reached for the XGBoost models if those 72 subjects with the smallest RF data Shapley values were excluded from the training data set. Conclusion: The data Shapley method was able to improve the classification accuracies for the test data sets. Noisy data was associated with the number of ApoEϵ4 alleles and volumetric MRI measurements. Kernel SHAP showed that the black-box models learned biologically plausible associations.

scholarly journals Open Access Series of Imaging Studies: Longitudinal MRI Data in Nondemented and Demented Older Adults

2010 ◽  
Vol 22 (12) ◽  
pp. 2677-2684 ◽  
Author(s):  
Daniel S. Marcus ◽  
Anthony F. Fotenos ◽  
John G. Csernansky ◽  
John C. Morris ◽  
Randy L. Buckner
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Open Access ◽  
Data Sets ◽  
Imaging Studies ◽  
Clinical Dementia Rating ◽  
Data Set ◽  
Wide Range ◽  
Neuroimaging Data ◽  
Mri Scans

The Open Access Series of Imaging Studies is a series of neuroimaging data sets that are publicly available for study and analysis. The present MRI data set consists of a longitudinal collection of 150 subjects aged 60 to 96 years all acquired on the same scanner using identical sequences. Each subject was scanned on two or more visits, separated by at least 1 year for a total of 373 imaging sessions. Subjects were characterized using the Clinical Dementia Rating (CDR) as either nondemented or with very mild to mild Alzheimer's disease. Seventy-two of the subjects were characterized as nondemented throughout the study. Sixty-four of the included subjects were characterized as demented at the time of their initial visits and remained so for subsequent scans, including 51 individuals with CDR 0.5 similar level of impairment to individuals elsewhere considered to have “mild cognitive impairment.” Another 14 subjects were characterized as nondemented at the time of their initial visit (CDR 0) and were subsequently characterized as demented at a later visit (CDR > 0). The subjects were all right-handed and include both men (n = 62) and women (n = 88). For each scanning session, three or four individual T1-weighted MRI scans were obtained. Multiple within-session acquisitions provide extremely high contrast to noise, making the data amenable to a wide range of analytic approaches including automated computational analysis. Automated calculation of whole-brain volume is presented to demonstrate use of the data for measuring differences associated with normal aging and Alzheimer's disease.

Computer-aided methods for 3-D visualization of serial sections and thick biological specimens

1992 ◽  
Vol 50 (2) ◽  
pp. 1060-1061
Author(s):  
Mark Ellisman ◽  
Maryann Martone ◽  
Gabriel Soto ◽  
Eleizer Masliah ◽  
David Hessler ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Three Dimensional ◽  
Neuritic Plaque ◽  
Dimensional Structure ◽  
Data Sets ◽  
Molecular Physiology ◽  
Research Activities ◽  
Computer Aided ◽  
Dimensional Reconstruction

Structurally-oriented biologists examine cells, tissues, organelles and macromolecules in order to gain insight into cellular and molecular physiology by relating structure to function. The understanding of these structures can be greatly enhanced by the use of techniques for the visualization and quantitative analysis of three-dimensional structure. Three projects from current research activities will be presented in order to illustrate both the present capabilities of computer aided techniques as well as their limitations and future possibilities.The first project concerns the three-dimensional reconstruction of the neuritic plaques found in the brains of patients with Alzheimer's disease. We have developed a software package “Synu” for investigation of 3D data sets which has been used in conjunction with laser confocal light microscopy to study the structure of the neuritic plaque. Tissue sections of autopsy samples from patients with Alzheimer's disease were double-labeled for tau, a cytoskeletal marker for abnormal neurites, and synaptophysin, a marker of presynaptic terminals.

Race-Related Association between APOE Genotype and Alzheimer’s Disease: A Systematic Review and Meta-Analysis

2021 ◽  
pp. 1-10
Author(s):  
Wei Qin ◽  
Wenwen Li ◽  
Qi Wang ◽  
Min Gong ◽  
Tingting Li ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Black People ◽  
Late Onset ◽  
Meta Analysis ◽  
Group Analysis ◽  
Apoe Genotype ◽  
Cochrane Library ◽  
Data Sets ◽  
Apoe Genotypes

Background: The global race-dependent association of Alzheimer’s disease (AD) and apolipoprotein E (APOE) genotype is not well understood. Transethnic analysis of APOE could clarify the role of genetics in AD risk across populations. Objective: This study aims to determine how race and APOE genotype affect the risks for AD. Methods: We performed a systematic search of PubMed, Embase, Web of Science, and the Cochrane Library since 1993 to Aug 25, 2020. A total of 10,395 reports were identified, and 133 were eligible for analysis with data on 77,402 participants. Studies contained AD clinical diagnostic and APOE genotype data. Homogeneous data sets were pooled in case-control analyses. Odds ratios and 95% confidence intervals for developing AD were calculated for populations of different races and APOE genotypes. Results: The proportion of APOE genotypes and alleles differed between populations of different races. Results showed that APOE ɛ4 was a risk factor for AD, whereas APOE ɛ2 protected against it. The effects of APOE ɛ4 and ɛ2 on AD risk were distinct in various races, they were substantially attenuated among Black people. Sub-group analysis found a higher frequency of APOE ɛ4/ɛ4 and lower frequency of APOE ɛ3/ɛ3 among early-onset AD than late-onset AD in a combined group and different races. Conclusion: Our meta-analysis suggests that the association of APOE genotypes and AD differ between races. These results enhance our understanding of APOE-related risk for AD across race backgrounds and provide new insights into precision medicine for AD.

scholarly journals Cognitive Effects of Aerobic Exercise in Alzheimer’s Disease: A Pilot Randomized Controlled Trial

2021 ◽  
pp. 1-12
Author(s):  
Fang Yu ◽  
David M. Vock ◽  
Lin Zhang ◽  
Dereck Salisbury ◽  
Nathaniel W. Nelson ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Older Adults ◽  
Alzheimer's Disease ◽  
Randomized Controlled Trial ◽  
Aerobic Exercise ◽  
Controlled Trial ◽  
Moderate Intensity ◽  
Cognitive Effects ◽  
Data Set ◽  
Randomized Controlled

Background: Aerobic exercise has shown inconsistent cognitive effects in older adults with Alzheimer’s disease (AD) dementia. Objective: To examine the immediate and longitudinal effects of 6-month cycling on cognition in older adults with AD dementia. Methods: This randomized controlled trial randomized 96 participants (64 to cycling and 32 to stretching for six months) and followed them for another six months. The intervention was supervised, moderate-intensity cycling for 20–50 minutes, 3 times a week for six months. The control was light-intensity stretching. Cognition was assessed at baseline, 3, 6, 9, and 12 months using the AD Assessment Scale-Cognition (ADAS-Cog). Discrete cognitive domains were measured using the AD Uniform Data Set battery. Results: The participants were 77.4±6.8 years old with 15.6±2.9 years of education, and 55%were male. The 6-month change in ADAS-Cog was 1.0±4.6 (cycling) and 0.1±4.1 (stretching), which were both significantly less than the natural 3.2±6.3-point increase observed naturally with disease progression. The 12-month change was 2.4±5.2 (cycling) and 2.2±5.7 (control). ADAS-Cog did not differ between groups at 6 (p = 0.386) and 12 months (p = 0.856). There were no differences in the 12-month rate of change in ADAS-Cog (0.192 versus 0.197, p = 0.967), memory (–0.012 versus –0.019, p = 0.373), executive function (–0.020 versus –0.012, p = 0.383), attention (–0.035 versus –0.033, p = 0.908), or language (–0.028 versus –0.026, p = 0.756). Conclusion: Exercise may reduce decline in global cognition in older adults with mild-to-moderate AD dementia. Aerobic exercise did not show superior cognitive effects to stretching in our pilot trial, possibly due to the lack of power.

scholarly journals Genetic Predisposition to Alzheimer’s Disease Is Associated with Enlargement of Perivascular Spaces in Centrum Semiovale Region

Genes ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 825
Author(s):  
Iacopo Ciampa ◽  
Grégory Operto ◽  
Carles Falcon ◽  
Carolina Minguillon ◽  
Manuel Castro de Moura ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Genetic Predisposition ◽  
Rating Scale ◽  
P Value ◽  
Perivascular Spaces ◽  
Centrum Semiovale ◽  
Logistic Regression Models ◽  
Visual Rating ◽  
Increased Risk

This study investigated whether genetic factors involved in Alzheimer’s disease (AD) are associated with enlargement of Perivascular Spaces (ePVS) in the brain. A total of 680 participants with T2-weighted MRI scans and genetic information were acquired from the ALFA study. ePVS in the basal ganglia (BG) and the centrum semiovale (CS) were assessed based on a validated visual rating scale. We used univariate and multivariate logistic regression models to investigate associations between ePVS in BG and CS with BIN1-rs744373, as well as APOE genotypes. We found a significant association of the BIN1-rs744373 polymorphism in the CS subscale (p value = 0.019; OR = 2.564), suggesting that G allele carriers have an increased risk of ePVS in comparison with A allele carriers. In stratified analysis by APOE-ε4 status (carriers vs. non-carriers), these results remained significant only for ε4 carriers (p value = 0.011; OR = 1.429). To our knowledge, the present study is the first suggesting that genetic predisposition for AD is associated with ePVS in CS. These findings provide evidence that underlying biological processes affecting AD may influence CS-ePVS.

scholarly journals Examining the possible causal relationship between lung function, COPD and Alzheimer’s disease: a Mendelian randomisation study

2021 ◽  
Vol 8 (1) ◽  
pp. e000759
Author(s):  
Daniel Higbee ◽  
Raquel Granell ◽  
Esther Walton ◽  
Roxanna Korologou-Linden ◽  
George Davey Smith ◽  
...  
Keyword(s):  
Risk Factors ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Lung Function ◽  
Causal Relationship ◽  
Mendelian Randomisation ◽  
P Value ◽  
Unmeasured Confounding ◽  
Increased Risk ◽  
Shared Risk

RationaleLarge retrospective case-control studies have reported an association between chronic obstructive pulmonary disease (COPD), reduced lung function and an increased risk of Alzheimer’s disease. However, it remains unclear if these diseases are causally linked, or due to shared risk factors. Conventional observational epidemiology suffers from unmeasured confounding and reverse causation. Additional analyses addressing causality are required.ObjectivesTo examine a causal relationship between COPD, lung function and Alzheimer’s disease.MethodsUsing two-sample Mendelian randomisation, we used single nucleotide polymorphisms (SNPs) identified in a genome wide association study (GWAS) for lung function as instrumental variables (exposure). Additionally, we used SNPs discovered in a GWAS for COPD in those with moderate to very severe obstruction. The effect of these SNPs on Alzheimer’s disease (outcome) was taken from a GWAS based on a sample of 24 807 patients and 55 058 controls.ResultsWe found minimal evidence for an effect of either lung function (OR: 1.02 per SD; 95% CI 0.91 to 1.13; p value 0.68) or liability for COPD on Alzheimer’s disease (OR: 0.97 per SD; 95% CI 0.92 to 1.03; p value 0.40).ConclusionNeither reduced lung function nor liability COPD are likely to be causally associated with an increased risk of Alzheimer’s, any observed association is likely due to unmeasured confounding. Scientific attention and health prevention policy may be better focused on overlapping risk factors, rather than attempts to reduce risk of Alzheimer’s disease by targeting impaired lung function or COPD directly.

scholarly journals RESTING HEART RATE MODERATES THE RELATIONSHIP BETWEEN NEUROPSYCHIATRIC SYMPTOMS, MCI, AND ALZHEIMER’S DISEASE

2019 ◽  
Vol 3 (Supplement_1) ◽  
pp. S641-S641
Author(s):  
Shanna L Burke
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Heart Rate ◽  
Relative Risk ◽  
Neuropsychiatric Symptoms ◽  
Cognitive Status ◽  
Resting Heart Rate ◽  
Data Set ◽  
Increased Risk ◽  
The Relationship

Abstract Little is known about how resting heart rate moderates the relationship between neuropsychiatric symptoms and cognitive status. This study examined the relative risk of NPS on increasingly severe cognitive statuses and examined the extent to which resting heart rate moderates this relationship. A secondary analysis of the National Alzheimer’s Coordinating Center Uniform Data Set was undertaken, using observations from participants with normal cognition at baseline (13,470). The relative risk of diagnosis with a more severe cognitive status at a future visit was examined using log-binomial regression for each neuropsychiatric symptom. The moderating effect of resting heart rate among those who are later diagnosed with mild cognitive impairment (MCI) or Alzheimer’s disease (AD) was assessed. Delusions, hallucinations, agitation, depression, anxiety, elation, apathy, disinhibition, irritability, motor disturbance, nighttime behaviors, and appetite disturbance were all significantly associated (p&lt;.001) with an increased risk of AD, and a reduced risk of MCI. Resting heart rate increased the risk of AD but reduced the relative risk of MCI. Depression significantly interacted with resting heart rate to increase the relative risk of MCI (RR: 1.07 (95% CI: 1.00-1.01), p&lt;.001), but not AD. Neuropsychiatric symptoms increase the relative risk of AD but not MCI, which may mean that the deleterious effect of NPS is delayed until later and more severe stages of the disease course. Resting heart rate increases the relative risk of MCI among those with depression. Practitioners considering early intervention in neuropsychiatric symptomology may consider the downstream benefits of treatment considering the long-term effects of NPS.

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