ArticleGeroScience2025
Aging, mitochondrial dysfunction, and cerebral microhemorrhages: a preclinical evaluation of SS-31 (elamipretide) and development of a high-throughput machine learning-driven imaging pipeline for cerebromicrovascular protection therapeutic screening.
Article in GeroScience, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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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.
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Who cites it
8 citing papers in PubMed.
- Targeting Mitochondria for Postoperative Cognitive Dysfunction: From Mechanisms to Therapeutics.Molecular neurobiology · 2026Review
- Foreign Body Response to Neuroimplantation: Machine Learning-Assisted Quantitative Analysis of Astrogliosis.International journal of molecular sciences · 2026Article
- Corticotropin-releasing factor (CRF) in brain aging: from mitochondrial dysfunction to inflammaging.Frontiers in aging neuroscience · 2026Review
- Mitochondrial control of blood-brain barrier homeostasis in neuroinflammatory psychiatric disorders.Frontiers in molecular neuroscience · 2026Review
- Age-Related Alterations of Cerebral Autoregulation.Life (Basel, Switzerland) · 2025Review
- Intracerebral Hemorrhage in Aging: Pathophysiology, Clinical Challenges, and Future Directions.Life (Basel, Switzerland) · 2025Review
- Intermittent Fasting as a Neuroprotective Strategy: Gut-Brain Axis Modulation and Metabolic Reprogramming in Neurodegenerative Disorders.Nutrients · 2025Review
- Vitamin D and Colorectal Cancer Prevention: Immunological Mechanisms, Inflammatory Pathways, and Nutritional Implications.Nutrients · 2025Review
Corrections and comments
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Authors and funding
18 authors.
Funding
Abstract
Cerebral microhemorrhages (CMHs, also known as cerebral microbleeds) contribute to vascular cognitive impairment and dementia (VCID), with aging and hypertension being key risk factors. Mitochondrial oxidative stress is a hallmark of cerebrovascular aging, leading to endothelial dysfunction. This study tests the hypothesis that increased mitochondrial oxidative stress contributes to age-related CMH susceptibility and evaluates the mitochondrial-targeted antioxidative peptide SS-31 (elamipretide) as a potential protective agent in an aged, hypertensive mouse model. Concurrently, we developed a high-throughput, machine learning-driven imaging pipeline to enhance CMH quantification and facilitate the screening of anti-aging vasoprotective interventions. To detect CMHs, brain sections were labeled with diaminobenzidine (DAB) and digitized using a slide scanner-based imaging platform. We developed multiple quantification tools, including color space transformation for enhanced contrast separation and a supervised machine-learning approach utilizing a random forest algorithm to generate whole-brain 3D reconstructions and precisely localize CMHs. We optimized a semi-automated detection method integrating color space transformation and machine learning, benchmarking it against traditional manual counting and color deconvolution-based approaches. While SS-31 treatment did not significantly mitigate hypertension-induced CMH burden in aged mice, our high-throughput imaging pipeline provided a reliable, scalable, and unbiased approach to CMH detection, reducing processing time while improving accuracy. This methodological advancement paves the way for future preclinical studies evaluating therapeutic strategies for cerebrovascular protection in aging. Our findings underscore the need for multi-targeted interventions to mitigate CMH-related neurovascular impairments and prevent VCID.
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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.