ReviewOncotarget2015
Dynamic self-guiding analysis of Alzheimer's disease.
Review in Oncotarget, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed.
- A tissue-specific collaborative mixed model for jointly analyzing multiple tissues in transcriptome-wide association studies.Nucleic acids research · 2020Article
- Effects of age-dependent changes in cell size on endothelial cell proliferation and senescence through YAP1.Aging · 2019Article
- Abnormal organization of white matter networks in patients with subjective cognitive decline and mild cognitive impairment.Oncotarget · 2016Article
- Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
We applied a self-guiding evolutionary algorithm to initiate the synthesis of the Alzheimer's disease-related data and literature. A protein interaction network associated with amyloid-beta precursor protein (APP) and a seed model that treats Alzheimer's disease as progressive dysregulation of APP-associated signaling were used as dynamic "guides" and structural "filters" in the recursive search, analysis, and assimilation of data to drive the evolution of the seed model in size, detail, and complexity. Analysis of data and literature across sub-disciplines and system-scale discovery platforms suggests a key role of dynamic cytoskeletal connectivity in the stability, plasticity, and performance of multicellular networks and architectures. Chronic impairment and/or dysregulation of cell adhesions/synapses, cytoskeletal networks, and/or reversible epithelial-to-mesenchymal-like transitions, which enable and mediate the stable and coherent yet dynamic and reconfigurable multicellular architectures, may lead to the emergence and persistence of the disordered, wound-like pockets/microenvironments of chronically disconnected cells. Such wound-like microenvironments support and are supported by pro-inflammatory, pro-secretion, de-differentiated cellular phenotypes with altered metabolism and signaling. The co-evolution of wound-like microenvironments and their inhabitants may lead to the selection and stabilization of degenerated cellular phenotypes, via acquisition of epigenetic modifications and mutations, which eventually result in degenerative disorders such as cancer and Alzheimer's disease.
Indexed as
Identifiers
What Socratic holds
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 Socratic graph.