ReviewSignal transduction and targeted therapy2026
Insights into the therapeutic strategies for aging and aging-associated diseases.
Review in Signal transduction and targeted therapy, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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
2 citing papers in PubMed.
- Aging-modulatory effects of Pausinystalia macroceras (K. Schum.) Pierre polysaccharides are associated with DAF-16/FOXO and SKN-1/Nrf2 signaling in multiple aging models.Biogerontology · 2026Article
- Environmental Carcinogenesis as a Stochastic Evolutionary Failure of Senescence-Control Systems.Cells · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Aging is a complex biological process characterized by progressive functional decline, driving the incidence of age-related diseases such as neurodegeneration, metabolic disorders, and cardiovascular diseases. Therapeutic strategies targeting aging hallmarks can delay aging and mitigate disease risk. Emerging interventions focus on modulating core aging mechanisms, including cellular senescence, metabolic dysfunction, epigenetic alterations, and mitochondrial impairment, etc. Recent advances have focused on three strategies: senolytics (eliminating senescent cells, e.g., dasatinib + quercetin), senomorphics (inhibiting the senescence-associated secretory phenotype, e.g., rapamycin), and senoreversion (rejuvenating senescent cells via epigenetic reprogramming). Additionally, metabolic interventions such as caloric restriction mimetics (e.g., spermidine, α-ketoglutarate, ergothioneine) enhance mitochondrial function, activate autophagy, and reprogram energy metabolism, demonstrating lifespan extension and healthspan improvement in preclinical models. Collectively, these approaches hold promise for delaying aging and alleviating age-related pathologies, facilitating the transition to precision longevity medicine. Concurrently, artificial intelligence (AI) accelerates discovery by integrating multiomics data, predicting candidate compounds, identifying biomarkers, and enabling personalized interventions. Despite advancements, challenges remain in target specificity, off-target effects, and clinical translation. The convergence of AI, multitarget strategies, and precision medicine signals a transformative era in extending healthspan and combating aging-associated diseases. This review systematically summarizes current breakthroughs, clinical landscapes, and future directions in aging therapeutics, underscoring interdisciplinary strategies to redefine healthy aging.
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.