ArticleCurrent opinion in systems biology2018
The paths of mortality: how understanding the biology of aging can help explain systems behavior of single cells.
Article in Current opinion in systems biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 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
13 citing papers in PubMed, 20 citations in OpenAlex.
- Behavioural changes in slime moulds over time.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2023Article
- Article
- Integrated OMICs unveil the bone-marrow microenvironment in human leukemia.Cell reports · 2021Article
- Protein interaction potential landscapes for yeast replicative aging.Scientific reports · 2021Article
- A programmable fate decision landscape underlies single-cell aging in yeast.Science (New York, N.Y.) · 2020Article
- Loss of vacuolar acidity results in iron-sulfur cluster defects and divergent homeostatic responses during aging in Saccharomyces cerevisiae.GeroScience · 2020Article
- Trajectories of Aging: How Systems Biology in Yeast Can Illuminate Mechanisms of Personalized Aging.Proteomics · 2020Review
- Advances in quantitative biology methods for studying replicative aging inTranslational medicine of aging · 2020Article
- Article
- Mechanisms by which PE21, an extract from the white willowOncotarget · 2019Article
- Current Stage of Marine Ceramic Grafts for 3D Bone Tissue Regeneration.Marine drugs · 2019Review
- Divergent Aging of Isogenic Yeast Cells Revealed through Single-Cell Phenotypic Dynamics.Cell systems · 2019Article
- Mechanisms through which lithocholic acid delays yeast chronological aging under caloric restriction conditions.Oncotarget · 2018Article
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 at 1 institution in 1 country.
Funding
Abstract
Aging is a fundamental aspect of life, yet also one of the most confounding. In individual cells, aging results in a progressive decline which affects all organelles and reduces a cell's ability to maintain homeostasis. Because of the interconnected nature of cellular systems, the failure of even a single organelle can have cascading effects. We are just beginning to understand the dramatic physiological changes that occur during aging. Because most aging research has focused on population dynamics, or differences between wild-type and mutant populations, single-cell behavior has been largely overlooked. An open question is whether aging cells are defined by predictable sequences of physiological changes, or whether they proceed along divergent aging trajectories defined by whichever system begins to fail first. Can aging be best characterized by a cell-cycle like model with stereotyped states all cells progress through, or a Waddington landscape with divergent trajectories? Here we present work on understanding the changing physiological states of aging cells, why it will impact systems and synthetic biologists, and how the systems community can contribute significantly to the study of aging.
Identifiers
What OpenQuestion 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 OpenQuestion graph.