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    Home > Active Ingredient News > Study of Nervous System > Alzheimer's & Dementia Fractal Patterns of Daily Activities and Alzheimer's Disease or Dementia

    Alzheimer's & Dementia Fractal Patterns of Daily Activities and Alzheimer's Disease or Dementia

    • Last Update: 2021-10-21
    • Source: Internet
    • Author: User
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    Written by Ning Zi, edited by Wang Sizhen, homeostasis and homeostatic control have been guiding all aspects of medical and physiology research as early as the early 19th century
    .

    Based on the assumption of steady state, it is presumed that the body has many automatic suppression mechanisms in order to eliminate or suppress environmental interference, that is, a negative feedback mechanism
    .

    Also in the 19th century, physicists began to describe dynamic control systems through linear differential equations, opening the chapter of dynamic network control
    .

    Since having the language of mathematics, people have found that some dynamic network control adopts the opposite mechanism, that is, positive feedback
    .

    Although in general, positive feedback leads to unstable network response, under certain circumstances, depending on the dynamics of the network, its response can either amplify or suppress radial motion
    .

    The development of physics has also stimulated new thinking in physiology: Is steady control enough to describe the control mechanism of the physiological system? With the in-depth observation of the physical characteristics of physiological system signals, including long-term memory and fractal dimension [1], people have found that it is necessary to make certain corrections to the stability control to be better.
    In addition, allometric control (allometric control) may be able to describe physiological phenomena more accurately [2]
    .

    Fractal physiology is mainly produced and developed under this background.
    It is an interdisciplinary subject integrating fractal geometry, statistical physics, nonlinear dynamics and physiology [3]
    .

    The theme of fractal physiology is to better understand biological complexity
    .

    The Medical Biodynamics Program (MBP) team at Harvard Medical School and the affiliated Brigham and Women's Hospital has led a lot of relevant fractal physiology in medicine, especially sleep medicine and Research in the field of geriatrics
    .

    In September 2018 and June 2021, the team successively published recent research progress in Alzheimer's & Dementia: The Journal of the Alzheimer's Association and Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring, the top journals in the field of Alzheimer's disease.
    The papers are titled "Fractal regulation and incident Alzheimer's disease in elderly individuals" (Article 1) and "Fractal motor activity regulation and sex differences in preclinical Alzheimer's disease pathology" (Article 2)
    .

    In the two studies, Li Peng (the first author of Article 1 and the co-author of Article 2), Lei Gao (the co-senior author of Article 2) and Kun Hu (the senior author of Article 1 and the co-senior author of Article 2) respectively cooperated with Rush Alzheimer's Disease Center in the United States.
    The team of David A.
    Bennett and the team of Yo-El S.
    Ju of Washington University in St.
    Louis (Washing University in St.
    Louis) worked together to study the relationship between fractal patterns in daily activities and the risk of Alzheimer’s dementia.
    The relationship between Alzheimer's pathology
    .

    The results show that on a small time scale (less than 90 minutes), the reduction in the fractal correlation of daily activity signals is significantly related to the future increase in the risk of Alzheimer's dementia, and this correlation is independent of other known risk factors [4] In addition, the disorder of the fractal pattern of daily activity signals is significantly related to the increase of Alzheimer's in vivo pathological indicators in the preclinical stage, and this correlation is particularly significant in women [5]
    .

    In recent years, people's daily behaviors have gradually received attention in health or medical research
    .

    Figure 1 shows a wristwatch-type instrument commonly used in medical research.
    The wristwatch-type motion signal recorder (actigraph) is equipped with sensitive acceleration sensors to sense acceleration signals in three-dimensional directions in space
    .

    Based on a specific algorithm, the three-dimensional acceleration signal can be integrated into a one-dimensional signal that reflects the wearer's activity and the amount of activity, that is, an actigraphy
    .

    Figure 1 The fractal pattern in the motion picture of a sports watch (picture source: MBP team) was first reported in a study in 2004[6].
    Kun Hu was the first author of the study, and the senior author contributed to the field of sleep medicine.
    Rich Professor Steven A.
    Shea, the author also includes Professor H.
    Eugene Stanley, a dean of statistical physics and an academician of the American Academy of Sciences
    .

    At that time, the concept of fractal physiology was still in its infancy
    .

    The research was published in the journal Physica A: Statistical Mechanics and its Applications
    .

    The research results reveal for the first time that apparently random motion signals have robust scale invariant (a characteristic of fractal patterns) (Figure 2) and nonlinear characteristics, which are both present in daily life environments, It is also presented in a laboratory environment isolated from time, indicating that fractal patterns may be an intrinsic attribute of daily activities or sports
    .

    Figure 2 Fractal geometric structure and fractal statistical signal
    .

    Fractals are embodied in similarities on multiple scales.
    Small space or time scales simulate the structural or statistical characteristics of large space or time scales, and this similarity continues to expand to finer scales
    .

    (Picture source: MBP team) With the deepening of research, the fractal features in motion have been reported in other mammals (such as mice) [7] and even fruit flies [8]
    .

    Mechanism studies have shown that the generation of fractal features is causally related to the circadian clock center-suprachiasmatic nucleus (SCN).
    In the rat model with SCN removed, the fractal pattern of motion signals is eliminated, almost on a large time scale.
    Completely randomized [9], the study also implies that the regulation of SCN is not limited to the traditional biological rhythm-24 hours-this time scale.
    For example, further studies have shown that SCN removed mice can be controlled by feeding Time restricted feeding restores the 24-hour biological rhythm, but this fractal structure cannot be restored by this method [10]; in addition, the generation of fractal features may also be related to the control center of food anticipation—— Dorsomedial hypothalamic (dorsomedial hypothalamic)-has an association [11]
    .

     In terms of human research, two papers published on PNAS in 2004 and 2009 [12, 13] link the fractal patterns of human physiological signals (including heartbeat fluctuations and daily behavior) with biological rhythms and aging
    .

    The above studies have focused on understanding the fractal patterns of motion signals on large time scales, echoing the causal relationship between the fractal features on large time scales found in animal experiments and the biological clock
    .

    On small time scales, the generation mechanism of motion signal fractal patterns and the relationship with physiology and pathology still need further exploration and understanding
    .

     An RCT study in 2016 reported for the first time that the fractal correlation of motion signals on a small time scale is significantly positively correlated with cognition and emotion [14].
    At the same time, the study also implies that light therapy often used for circadian clock intervention can help alleviate the cause.
    The decline in fractal correlation caused by aging indicates to a certain extent the causal relationship between the fractal characteristics of motion signals and the biological clock in human subjects
    .

    The relationship between the fractal features of motion signals on small time scales and cognition and emotion reported by the research suggests that this characteristic time scale may be related to the activities of the higher cortex
    .

    To further explore this problem, MBP researchers studied whether the fractal pattern on this time scale predicts future cognitive decline or dementia risk through a longitudinal cohort (Article 1)
    .

     The study (article 1) involved a large sample of clinical data from approximately 1,400 subjects, all of whom came from a clinical study called "Memory and Aging Project" (MAP) [ 15]
    .

    In addition to participating in the annual system health follow-up, the subjects of the study also carried out daily activity monitoring for an average of 10 days per year
    .

    The MAP clinical study was led by Professor David A.
    Bennett and was carried out at Rush University, Rush Alzheimer's Disease Center in Chicago.
    The subjects were followed up for 15 years, with an average follow-up time of 6 years
    .

     The results of this study found that when the fractal correlation of motion signals on small time scales (less than 90 minutes) is reduced by one standard deviation, the risk of subjects suffering from Alzheimer's dementia in the future increases by 31%, The risk of suffering from mild cognitive impairment (MCI) increases by 15%.
    At the same time, the decrease in fractal correlation is significantly related to the vertical decline rate of cognitive function, which is related to the decrease in fractal correlation of one standard deviation.
    The increase in the rate of cognitive decline is equivalent to 2 years of aging
    .

    These findings are independent of other known risks, such as daily activity and sleep fragmentation, etc.
    , suggesting that the reduction of fractal correlation on small time scales is an independent risk factor for Alzheimer's dementia
    .

     In order to better describe the relationship between fractal correlation and long-term changes in cognitive function within an individual, MBP researchers also used multivariate statistical methods to model [16].
    The study was published in Neurobiology of Aging in 2019, The first author of the paper is Li Peng, and the senior author is Kun Hu
    .

    The study reported the longitudinal correlation between fractal correlation and cognitive function, suggesting from the individual that the two are significantly correlated with age
    .

    At the same time, the study also suggests that not only the fractal correlation on a small time scale predicts the future risk of Alzheimer’s dementia, but the clinical course of Alzheimer’s dementia will in turn influence it.
    This results in an accelerated decline, and the two processes are intertwined and deteriorated; although the fractal correlation on a large time scale does not independently predict the future risk of dementia, the clinical process of dementia still exerts an influence on the fractal characteristics on this scale and deteriorates Its aging rate
    .

    (For details, please refer to the Logical Neuroscience Report: Neurobiology of Aging︱ Sleep and Rhythm Aging Variations and Pathological Variations) In order to further confirm the relationship between fractal patterns and the pathology of Alzheimer's disease, MBP researchers and Knight Alzheimer's Disease Research of Washington University in St.
    Louis The Yo-El S.
    Ju team of the Center worked together to study the relationship between the pathological parameters of Alzheimer's disease in vivo (including PiB amyloid and cerebrospinal fluid tau) and the fractal pattern of motion signals (article 2)
    .

    Ju’s team recruited 178 adults with normal cognition.
    All subjects underwent daily activity monitoring for 1-2 weeks.
    Among them, 150 subjects underwent PiB PET imaging and 149 subjects underwent cerebrospinal fluid Check
    .

    Through the fractal analysis of the motion signal, MBP researchers found that the disordered fractal pattern is significantly related to the possibility of PiB positive (defined as the cortical standard absorption rate greater than 1.
    42), and the ratio of tau181-Aβ42 in the cerebrospinal fluid (the ratio is considered to be Alz A sensitive and specific indicator in the preclinical stage of Haimer’s disease) is significantly related
    .

    These correlations are related to age, daily activity level, exercise-rest pattern fragmentation, and APOE ε4 carrier status (APOE ε4 is the ε4 allele of apolipoprotein E.
    Carriers have a high risk of late-onset Alzheimer's.
    ) Irrelevant
    .

    In addition, the above-mentioned relationship is significant in women, but not in men, suggesting that this association also helps to understand the gender differences in Alzheimer's disease
    .

     Conclusion and discussion of the article, inspiration and prospects The above series of studies systematically revealed the relationship between the fractal pattern of daily activities and Alzheimer’s dementia and Alzheimer’s pathology from multiple perspectives, combining the fractal pattern and the regulation of the biological clock These studies help to better understand the timing or causal relationship between the circadian clock regulation disorder and dementia and its pathology; at the same time, these studies also help to discover new intervention targets for clinical applications.
    In order to carry out intervention work in the early or very early clinical stage, delay or even control the process
    .

    Before doing these work, there are still many basic questions that need to be explored more deeply: for example, is the above-mentioned association specific, that is, is the disorder of the fractal pattern specific to Alzheimer's dementia or its pathology? Judging from the current literature, this specificity may exist on different time scales.
    MBP researchers are currently conducting in-depth explorations in this perspective; in addition, the causal link between the disorder of the fractal pattern and the risk of the above-mentioned diseases depends on the cause and effect.
    It is confirmed by animal models or randomized controlled trials; the brain area mapping of fractal patterns on small time scales and/or the association with other pathologies is also worthy of further study
    .

    12211 Kun Hu (fourth from left), Peng Li (third from left), Lei Gao (first from left) (Photo provided by: MBP team) Selected previous articles [1] Cereb Cortex | Transcription-Neuroimaging Association Analysis Reveals Human The genetic mechanism of the resting state functional connection of visual cortex subregions [2] A new mechanism of Mol Cell︱ Alzheimer’s disease: Tau protein oligomerization induces nuclear cell transport of the RNA binding protein HNRNPA2B1 and mediates the enhancement of m6A-RNA modification [3 】Cereb Cortex | Li Tao's research group reported the abnormality of the cortical myelin covariation network with deep characteristics of the cerebral cortex in schizophrenia [4] Cell︱ hold hands, advance and retreat together! The formation of a cellular network between microglia to work together to degrade pathological α-syn [5] lipids and Alzheimer's disease! The lack of sulfatide in the myelin sheath in the central nervous system in adulthood can lead to Alzheimer’s disease-like neuroinflammation and cognitive impairment [6] Brain︱ new method! Plasma soluble TREM2 can be used as a potential detection marker for white matter damage in cerebral small vessel diseases [7] EMBO J︱ neuronal Miro1 protein deletion destroys mitochondrial autophagy and overactivates the integrated stress response [8] Science frontier review interpretation︱nicotinic acetylcholine The regulatory mechanism of receptor-assisted molecules and the application prospects of disease treatment and transformation [9] Cereb Cortex︱ oxytocin can regulate the individualized processing of facial identities and the classification and processing of facial races in early facial regions of the brain [10] Nat Commun | Qi Xin Project The group revealed that the compound CHIR99021 regulates the molecular mechanism of mitochondrial function to treat Huntington’s disease [11] Neurosci Bull︱ synapse-associated protein Dlg1 improves depression-like behavior in mice by inhibiting microglia activation [12] Brain | For the first time! PAX6 may be a key factor in the pathogenesis of Alzheimer's disease and a new therapeutic target [13] Sci Adv︱ blockbuster! DNA methylation protein DNMT1 mutation can induce neurodegenerative diseases [14] Nat Biomed Eng︱Academician Ye Yuru's team develops a new strategy for whole-brain gene editing-mediated treatment of Alzheimer’s disease [15]Luo Liqun Science Review System Interpretation︱ Neural loop structure-a high-quality scientific research training course recommendation for the system that makes the brain "computer" run at high speed [1] A guide to data graphs! How good is it to learn these software? 【2】Single-cell sequencing data analysis and project design network practical class (October 16-17)【3】JAMA Neurol︱Attention! Young people are more likely to suffer from "Alzheimer's disease"? [4] Patch Clamp and Optogenetics and Calcium Imaging Technology Seminar (October 30-31) References (slide up and down to view) [1] AL Goldberger, "Complex Systems," Proc Am Thorac Soc, vol.
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