Evidence map›Paper›PMID 34600936›Full record

ReviewMechanisms of ageing and development2021

Brain aging mechanisms with mechanical manifestations.

Yana Blinkouskaya, Andreia Caçoilo, Trisha Gollamudi, Shima Jalalian, Johannes Weickenmeier

Registry-linked trialAbstract readReview
In one paragraph

Review in Mechanisms of ageing and development, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07077460 (Innovative Hand Rehabilitation System With Synchronized Contralateral Haptic Feedback), which is not on this map. Cited by 129 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
129citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT07077460 narecruitingnot on this mapstarted 2024, after this paper: background citation

Innovative Hand Rehabilitation System With Synchronized Contralateral Haptic Feedback

TypeinterventionalSponsorNational Cheng-Kung University HospitalRan2024 to 2025Enrolled100ConditionsHealthy ElderlyArmsTIPr, Mirror Visual Feedback Device, Mirror Visual Feedback Device(Blocked mirror), Graded-Pressure Haptic Device (Passive press-feedback cushion)
3 · Its place in the literature

Who cites it

129 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Trial
  4. Trial
  5. Article
  6. Review
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Review
  16. Review
  17. Article
  18. Article
  19. The gut as a central hub for multi-organ crosstalk in aging.Cellular and molecular life sciences : CMLS · 2026
    Review
  20. Article

69 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Yana BlinkouskayaDepartment of Mechanical Engineering, Stevens Institute of Technology, Hoboken, NJ 07030, United States.
Andreia CaçoiloDepartment of Mechanical Engineering, Stevens Institute of Technology, Hoboken, NJ 07030, United States.
Trisha GollamudiDepartment of Biomedical Engineering, Stevens Institute of Technology, Hoboken, NJ 07030, United States.
Shima JalalianDepartment of Mechanical Engineering, Stevens Institute of Technology, Hoboken, NJ 07030, United States.
Johannes WeickenmeierDepartment of Mechanical Engineering, Stevens Institute of Technology, Hoboken, NJ 07030, United States. Electronic address: johannes.weickenmeier@stevens.edu.

Funding

Personalized predictions of biomarker progression in Alzheimer's diseaseR21AG067442 · NIA · THE TRUSTEES OF THE STEVENS INSTITUTE OF TECHNOLOGY · PI WEICKENMEIER, JOHANNES · 2020 to 2020
$424k
NIA NIH HHS R21 AG067442
6 · The paper itself

Abstract

Brain aging is a complex process that affects everything from the subcellular to the organ level, begins early in life, and accelerates with age. Morphologically, brain aging is primarily characterized by brain volume loss, cortical thinning, white matter degradation, loss of gyrification, and ventricular enlargement. Pathophysiologically, brain aging is associated with neuron cell shrinking, dendritic degeneration, demyelination, small vessel disease, metabolic slowing, microglial activation, and the formation of white matter lesions. In recent years, the mechanics community has demonstrated increasing interest in modeling the brain's (bio)mechanical behavior and uses constitutive modeling to predict shape changes of anatomically accurate finite element brain models in health and disease. Here, we pursue two objectives. First, we review existing imaging-based data on white and gray matter atrophy rates and organ-level aging patterns. This data is required to calibrate and validate constitutive brain models. Second, we review the most critical cell- and tissue-level aging mechanisms that drive white and gray matter changes. We focuse on aging mechanisms that ultimately manifest as organ-level shape changes based on the idea that the integration of imaging and mechanical modeling may help identify the tipping point when normal aging ends and pathological neurodegeneration begins.

Indexed as

AgingBrainAtrophyCellular SenescenceFunctional NeuroimagingHumansModels, BiologicalBrain aging mechanismsCerebral atrophyGray and white matter changesMorphological changesVascular changes

Identifiers

PMID34600936
PMCPMC8627478

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.