BUFFALO, NY — November 20, 2025 — A new #research paper was #published in Volume 17, Issue 10 of Aging-US on October 10, 2025, titled “Developmental arrest rate of an embryo cohort correlates with advancing reproductive age, but not with the aneuploidy rate of the resulting blastocysts in good prognosis patients: a study of 25,974 embryos.”

In this large-scale study, Andres Reig of the IVIRMA Global Research Alliance and Robert Wood Johnson Medical School, along with Emre Seli of the IVIRMA Global Research Alliance and  Yale School of Medicine, investigated how female age and chromosomal abnormalities affect embryo development in patients undergoing in vitro fertilization (IVF). They found that embryo developmental arrest (EDA) becomes more common as women age. However, this arrest is not directly associated with the presence of chromosomal errors in the embryos that continue to develop. These findings could help improve fertility counseling and treatment strategies.

The researchers analyzed 25,974 embryos from 1,928 IVF cycles, all from patients with a good chance of success. The study showed that the percentage of embryos that stopped developing before reaching the blastocyst stage increased with age: from 33% in women under 35 to 44% in those over 42. Despite this rise, the rate of chromosomal abnormalities, known as aneuploidy, in the embryos that did reach the blastocyst stage did not show a strong connection with the rate of arrest after adjusting for age.

This distinction  is important  because both developmental arrest and aneuploidy reduce the number of embryos suitable for transfer. But this study suggests they are caused by different biological processes. In other words, an embryo may stop developing even if it has the correct number of chromosomes, and some embryos with chromosomal abnormalities may still grow to the blastocyst stage.

“A very weak positive correlation was identified between EDA rate and the rate of aneuploidy (r: 0.07, 95% CI 0.03–0.11; R2: 0.00, p < 0.01) when evaluating all cohorts.”

The authors suggest that other factors, such as the health of the egg’s mitochondria or mutations in maternal-effect genes, may explain why some embryos stop developing. These insights could help researchers identify new ways to improve embryo quality, especially for older women undergoing IVF.

Importantly, the study focused on embryos that developed far enough to be tested, which helped avoid technical problems that come with analyzing arrested embryos directly. This approach allowed for more reliable comparisons across age groups and embryo quality.

Overall, the study highlights the importance of maternal age as a key factor in embryo development, independent of chromosomal results. It also opens new directions for research, aiming to better understand why embryos fail to develop and how this knowledge might lead to improved fertility treatments in the future.

DOI - https://doi.org/10.18632/aging.206328

Corresponding author - Emre Seli - emre.seli@yale.edu

Abstract video - https://www.youtube.com/watch?v=g0oS3HBNmuQ

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Keywords - aging, ovarian aging, reproductive aging, embryonic arrest, embryonic aneuploidy, developmental arrest

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Aging-US

Embryo Arrest in IVF Linked to Maternal Age, Not Chromosomal Abnormalities

BUFFALO, NY — November 25, 2025 — A new #research paper was #published in Volume 17, Issue 10 of Aging-US on October 13, 2025, titled “Hospitalization with infections and risk of Dementia: a systematic review and meta-analysis.”

This large-scale meta-analysis, led by first author Wei Yu Chua from the National University of Singapore and corresponding author Eng-King Tan from the National Neuroscience Institute and Duke-NUS Medical School in Singapore, shows that adults hospitalized with infections have a significantly higher risk of developing dementia. The findings are especially important as global populations grow older and hospitalizations for infections increase, highlighting a potential new approach for dementia prevention.

“Out of 1900 studies that were screened initially, 16 studies comprising 4,266,276 patients were included for analysis.” 

The researchers analyzed data from over 4 million individuals across 16 studies, making this study the most comprehensive review to date on the association between infection-related hospital stays and long-term brain health. The results showed that being hospitalized for an infection raised the risk of all-cause dementia by 83%. Among the types of infections studied, sepsis carried the highest risk, followed by pneumonia, urinary tract infections, and skin or soft tissue infections. The risk of developing vascular dementia was notably higher than that of Alzheimer’s disease.

One possible explanation for the association between infections and dementia is that infections trigger systemic inflammation that may reach the brain. Inflammatory molecules can cross the blood-brain barrier, potentially leading to the buildup of damaging proteins and the death of brain cells. This process may be more severe in older adults, whose immune systems are often slower to respond and recover. The study also suggests that even a single infection-related hospitalization can speed up cognitive decline, especially in individuals already at higher risk.

Importantly, the risk of dementia was greatest within the first year following an infection but remained elevated for many years afterward. In fact, studies with follow-ups longer than a decade showed even stronger associations. These results suggest the need for early cognitive monitoring after hospital discharge, particularly in older adults recovering from infections.

These findings have important implications for healthcare systems, particularly those serving aging populations, and underscore the lasting impact that infections can have on the brain. This research highlights the importance of looking beyond genetics and lifestyle for prevention strategies. With over 50 million people affected by dementia worldwide and annual care costs in the U.S. exceeding $300 billion, identifying new and preventable risk factors is critical. Reducing infections, improving hospital care, and monitoring brain health after illness may offer promising ways to protect cognitive function in aging populations.

DOI - https://doi.org/10.18632/aging.206329

Corresponding author - Eng-King Tan - tan.eng.king@singhealth.com.sg

Abstract video - https://www.youtube.com/watch?v=uyv5VHHHIA4

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Hospital Infections Associated with Higher Risk of Dementia

Interest in healthier, longer lives is rising, supported by recent scientific advances in aging research. But turning those discoveries into everyday healthcare solutions remains a work in progress. In this landscape, longevity clinics have attracted attention as personalized alternatives to traditional medicine.

What Are Longevity Clinics?

Longevity clinics are private centers offering tailored programs designed to improve long-term health and slow biological aging. Using advanced diagnostics such as genetic sequencing, full-body imaging, and blood tests, they develop personalized plans that may include exercise, nutrition, hormone therapy, or experimental treatments. Frequently found in countries like the United States, Switzerland, and the United Arab Emirates, these clinics reflect a growing global interest in preventive healthcare, though their high costs and scientific credibility remain subjects of debate.

The Editorial

“Longevity clinics: between promise and peril,” an editorial by Marco Demaria, Editor-in-Chief of Aging-US, from the European Research Institute for the Biology of Ageing (ERIBA), University Medical Center Groningen (UMCG), University of Groningen (RUG), was published in Aging-US (Volume 17, Issue 10). 

Full blog - https://aging-us.org/2025/11/longevity-clinics-balancing-innovation-with-regulation/

Paper DOI - https://doi.org/10.18632/aging.206330

Corresponding author - Marco Demaria — m.demaria@umcg.nl

Abstract video - https://www.youtube.com/watch?v=Bt84xBdii0s

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Keywords - aging, longevity clinics, biomarkers, frailty, senescence

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Longevity Clinics: Balancing Innovation with Regulation

BUFFALO, NY — December 1, 2025 — A new #research paper featured on the #cover of Volume 17, Issue 11 of Aging-US was #published on October 30, 2025, titled “SAMP-Score: a morphology-based machine learning classification method for screening pro-senescence compounds in p16 positive cancer cells.”

In this study led by first author Ryan Wallis along with corresponding author Cleo L. Bishop, from Queen Mary University of London, researchers developed a machine learning tool to identify compounds that induce cancer cells into senescence. The tool, called SAMP-Score, offers a new strategy for drug discovery in cancers with poor treatment options like basal-like breast cancer.

Senescence is a process where damaged or aged cells stop dividing. In cancer therapy, inducing senescence is an approach to control tumor growth. However, it is difficult to detect true senescence in cancer cells that already appear aged. These cancers, often called Sen-Mark+ cancers, include basal-like breast cancer and typically lack reliable markers to confirm senescence. SAMP-Score was designed to address this problem.

Instead of relying on traditional markers, the researchers built a machine learning model trained to recognize patterns based on senescent cells’ shape and structure under a microscope. These visual patterns, known as senescence-associated morphological profiles (SAMPs), allowed the model to distinguish real signs of aging from other effects such as toxicity or normal variation. By analyzing thousands of cell images, the model learned to classify whether a cell had truly entered senescence.

“To demonstrate the potential application of SAMP-Score in p16 positive cancer therapeutic discovery, we assessed a diversity screen of 10,000 novel chemical entities in MB-468 cells (p16 positive BLBC).”

The team used SAMP-Score to screen more than 10,000 experimental compounds. One compound, QM5928, consistently triggered senescence in several cancer cell types without killing them, making it a promising candidate for further study. Importantly, it worked in cancers resistant to known drugs like palbociclib, which are often ineffective in cancers with high p16 expression like basal-like breast cancer. 

Further analysis revealed that QM5928 caused the p16 protein to move into the nucleus of cancer cells, a possible sign that the protein is helping stop cell division. This subtle effect was only detectable using the detailed imaging and analysis made possible by SAMP-Score, highlighting the tool’s ability to distinguish true senescence from toxic responses and making it a powerful resource in cancer drug discovery.

By combining machine learning with high-resolution imaging, this study introduces a new way to find and evaluate cancer therapies. SAMP-Score could accelerate efforts to develop treatments that exploit the body’s natural aging processes to fight cancer, especially for patients with resistant tumors. The tool is openly available at GitHub, making it accessible for other researchers exploring senescence-based cancer therapies.

DOI - https://doi.org/10.18632/aging.206333

Corresponding author - Cleo L. Bishop - c.l.bishop@qmul.ac.uk

Abstract video - https://www.youtube.com/watch?v=qXI_KI3EgHE

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Machine Learning Identifies Senescence-Inducing Compound for p16-Positive Cancer Cells

BUFFALO, NY — December 3, 2025 — A new #essay was #published in Volume 17, Issue 11 of Aging-US on November 19, 2025, titled “On the intergenerational transfer of ideas in aging and cancer research: from the hypothalamus according to V.M. Dilman to the mTOR protein complex according to M.V. Blagosklonny.”

In this work, Aleksei G. Golubev from the N.N. Petrov National Medical Research Center of Oncology reflects on the legacy of two influential Russian scientists, Vladimir M. Dilman and his son Mikhail V. Blagosklonny, who each introduced groundbreaking ideas about aging and cancer. Drawing from his own experience working in Dilman’s lab, Golubev explores how their ideas remain deeply relevant to today’s scientific understanding.

The essay connects Dilman’s “elevation theory” with Blagosklonny’s “hyperfunction theory,” two frameworks that challenge the conventional view of aging as a process of decline. Instead, both propose that aging results from continued biological processes that once supported growth but eventually become harmful when left unchecked.

Dilman believed that aging begins with reduced sensitivity in the hypothalamus, a brain region that regulates the body’s balance. This desensitization disrupts metabolism and hormone levels, setting the stage for many chronic illnesses. Decades later, Blagosklonny expanded on this idea at the molecular level. Central to his theory is the mTOR protein complex, which regulates growth and metabolism and is now a major focus in aging research.

Golubev also explores the historical and personal connections between the two scientists. Dilman, an endocrinologist trained in the Soviet Union, and Blagosklonny, a molecular biologist educated during the post-Soviet period, represent two generations shaped by a shared scientific tradition. 

“Dilman’s scientific legacy is not as well recognized as it should be, partly due to bias in citation practices.”

The essay also draws attention to a troubling trend in science: the tendency to overlook early contributions, especially from non-Western scholars. Many of Dilman’s insights, such as the connection between high blood sugar, insulin resistance, and cancer, have since been validated by modern tools, yet his work is rarely cited. Golubev points out how citation practices, language barriers, and historical isolation have contributed to this lack of recognition.

Finally, Golubev encourages the scientific community to look back and acknowledge the foundational work that shaped modern aging science. It also highlights the importance of cross-generational knowledge in moving science forward. By tracing the intellectual journey from hormonal regulation in the brain to molecular pathways in cells, this essay demonstrated the relevance of old ideas in a new biological era.

DOI - https://doi.org/10.18632/aging.206338

Corresponding author - Aleksei G. Golubev - lxglbv@rambler.ru

Abstract video - https://www.youtube.com/watch?v=LvrdghTKGws

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Keywords - aging, gerontology, history of science, hyperfunction, mTOR, hypothalamus, cancer, metabolism, immunity

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How Two Russian Scientists Changed the Way We Understand Aging and Cancer

In this episode, we meet the people behind Dementia Disco, a Stockport charity that organises discos for people affected by dementia.

You can visit alzheimers.org.uk/publications for our range of publications and factsheets designed to support and inform anyone affected by dementia.

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‘It's an uplifting and joyful thing’ – Dementia together podcast December 2025

Colorectal cancer (CRC) remains the second leading cause of cancer-related deaths globally. While early detection significantly improves outcomes, many patients are diagnosed at advanced stages when treatment options are limited and relapse is common. To address this challenge, researchers are exploring whether existing drugs can be repurposed for cancer therapy, a strategy that could accelerate drug development while reducing associated costs and risks.

One class of drugs under investigation is statins, commonly prescribed to reduce cholesterol and prevent cardiovascular disease. Several studies have observed a potential link between elevated cholesterol and increased CRC risk. Cholesterol may support tumor growth by promoting membrane synthesis and energy metabolism in rapidly dividing cells.

Building on this connection, researchers from leading Indian institutions, including the Indian Institute of Science Education and Research and the Center of Excellence in Epigenetics at Shiv Nadar Institution of Eminence, investigated how statins influence CRC cells at the molecular level. Their goal was to determine whether these widely used drugs could have a therapeutic role in oncology.

The Study: Investigating the Molecular Impact of Statins in CRC Cells

The study, titled “Statins exhibit anti-tumor potential by modulating Wnt/β-catenin signaling in colorectal cancer,” was published in Oncotarget (Volume 16). Using a combination of lipidomics, transcriptomics, proteomics, and 3D tumor models, the researchers explored how two widely prescribed statins, atorvastatin and simvastatin, affect molecular pathways associated with CRC progression. This integrative, multi-omics strategy enabled tracing statin-induced effects across different layers of cellular function, linking lipid, transcript, and protein changes to pathway-level shifts.

Full blog - https://www.oncotarget.org/2025/12/03/repurposing-statins-exploring-anti-tumor-effects-in-colorectal-cancer/

Paper DOI - https://doi.org/10.18632/oncotarget.28755

Correspondence to - Sanjeev Galande - sanjeev.galande@snu.edu.in

Abstract video - https://www.youtube.com/watch?v=A95ICULaH3Y

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Keywords - cancer, colorectal cancer, statins, SATB1, Wnt/β-catenin signaling, tumor-suppressive phenotype

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Oncotarget

Repurposing Statins: Exploring Anti-Tumor Effects in Colorectal Cancer

BUFFALO, NY — December 8, 2025 — A new #research paper was #published in Volume 17, Issue 11 of Aging-US on September 12, 2025, titled “Infusion of blood from young and old mice modulates amyloid pathology.”

This study was led by co-first authors Matias Pizarro from Universidad Adolfo Ibáñez and Ruben Gomez-Gutierrez from The University of Texas Health Science Center at Houston, alongside corresponding authors Claudia Duran-Aniotz from Universidad Adolfo Ibáñez and Rodrigo Morales from The University of Texas Health Science Center at Houston and Universidad Bernardo O’Higgins. The goal was to investigate how blood from young and old mice influences Alzheimer’s-related changes in a transgenic mouse model. The findings indicate that age-dependent circulating factors can either worsen or mitigate brain changes associated with dementia, highlighting blood and its components as potential therapeutic targets.

Alzheimer’s disease is a progressive neurodegenerative disorder characterized by misfolded amyloid proteins, inflammation, and gradual cognitive decline, with aging as its main risk factor. In this work, whole blood from young adult or very old wild-type mice was repeatedly infused into Tg2576 mice, a well-established model of amyloid accumulation and memory impairment. Over several months, recipient mice received 30 weekly blood infusions, followed by behavioral testing and detailed neuropathological analyses.

“Tg2576 mice express the human APP harboring the Swedish mutation.”

Mice that received blood from old donors performed worse in both short- and long-term spatial memory tasks than mice infused with young blood, suggesting that aged blood contains factors that impair cognition. When the team examined brain tissue, they found more cortical amyloid deposits detected by a specific antibody in mice treated with old blood, while overall amyloid levels measured biochemically did not change, suggesting differences in plaque type or compactness rather than total amount. The expression of amyloid precursor protein in the brain was also higher after old-blood infusion, which may partly explain the shift in amyloid pathology.​

Despite these changes in plaques and memory, classical markers of astrocyte activation, a sign of brain inflammation, did not differ between groups, pointing to more subtle molecular shifts. A broad proteomic analysis of brain samples revealed dysregulation of proteins involved in synapse formation, calcium signaling, and the endocannabinoid system, pathways important for neuronal communication and plasticity. Among them, the calcium channel–related protein CACNA2D2 and the signaling protein BRAF were increased in mice that received old blood, confirming that aged blood circulation can reshape key signaling networks linked to neuronal function and degeneration.

Overall, this study supports the idea that blood is not just a passive carrier but a powerful modulator of brain health during aging and disease. While young blood has been associated in previous work with improved synaptic function and reduced amyloid and tau changes, this study emphasizes the harmful impact of old blood, particularly on cortical amyloid patterns and memory. The identification of CACNA2D2 and BRAF as potential mediators of these effects suggests new avenues for targeting blood-borne factors or downstream brain pathways to slow or modify Alzheimer’s-related decline.

DOI - https://doi.org/10.18632/aging.206319

Corresponding authors - Claudia Duran-Aniotz - Claudia.Duran@uai.cl, and Rodrigo Morales - Rodrigo.MoralesLoyola@uth.tmc.edu

Abstract video - https://www.youtube.com/watch?v=zsBDSAipH3w

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Young and Old Mice Blood Differently Shapes Alzheimer’s-Related Brain Changes

The paper featured on the cover of this issue of Aging-US, published on October 30, 2025, entitled “SAMP-Score: a morphology-based machine learning classification method for screening pro-senescence compounds in p16-positive cancer cells,” represents an important methodological and conceptual advance at the interface of senescence biology, imaging and drug discovery.

In this study, led by first author Ryan Wallis and corresponding author Cleo L. Bishop (Queen Mary University of London), the authors introduce SAMP-Score, a machine-learning–based framework designed to identify bona fide senescence induction in cancer cells where canonical markers fail. This is a timely and much-needed contribution to the field.

Therapy-induced senescence has emerged as a powerful strategy to restrain tumor growth, yet its reliable detection in cancer cells remains a major bottleneckIn these contexts, cells often already display features associated with cellular aging, rendering conventional senescence markers ambiguous or misleading. Distinguishing true senescence from toxicity, stress responses or baseline “aged” phenotypes is therefore a critical unmet need.

Rather than relying on predefined molecular readouts, the authors take a different approach and train a machine-learning model to recognize senescence-associated morphological profiles (SAMPs) which are subtle but reproducible changes in cellular architecture captured through high-content microscopy. By learning directly from image-based phenotypes, SAMP-Score is able to identify senescence with a level of precision that is difficult to achieve using marker-based strategies alone.

The strength of the platform demonstrated through a large-scale screen of over 10,000 novel chemical entities in p16-positive basal-like breast cancer cells. From this screen, the compound QM5928 emerged as a robust inducer of senescence across multiple cancer models, notably without inducing cytotoxicity. Importantly, QM5928 retains activity in cellular contexts that are resistant to CDK4/6 inhibition, including palbociclib-refractory, p16-high tumors.

Mechanistically, the authors show that QM5928 promotes nuclear relocalization of p16, consistent with a functional engagement of cell-cycle arrest pathways. These nuanced phenotypic changes would likely have gone undetected without the resolution and discrimination provided by SAMP-Score, underscoring the platform’s ability to separate true senescence from confounding cellular states.

This work exemplifies how machine learning and quantitative imaging can be harnessed to solve long-standing problems in senescence research, moving the field beyond binary marker expression toward phenotype-driven classification. Beyond its immediate relevance for cancer therapy, SAMP-Score offers a broadly applicable framework for senescence-based screening efforts across biological contexts.

DOI - https://doi.org/10.18632/aging.206333

Corresponding author - Cleo L. Bishop - c.l.bishop@qmul.ac.uk

Abstract video - https://www.youtube.com/watch?v=qXI_KI3EgHE

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Aging-US Editors' Choice

Treating aggressive cancers that do not respond to standard therapies remains one of the most significant challenges in oncology. Among these are basal-like breast cancers (BLBC), which lack hormone receptors and HER2 amplification. This makes them unsuitable for many existing targeted treatments. As a result, therapeutic options are limited, and patient outcomes are often poor.

One emerging strategy is to induce senescence, a state in which cancer cells permanently stop dividing but remain metabolically active. This approach aims to slow or stop tumor growth without killing the cells directly. Although promising, the clinical application of senescence-based therapies has been limited by several challenges.

Senescence is typically identified using biomarkers such as p16, p21, and beta-galactosidase activity. However, these markers are often already present in aggressive cancers like BLBC (Sen‑Mark+ tumors), making it difficult to determine whether a treatment is truly inducing senescence or merely reflecting the tumor’s existing biology. Moreover, conventional screening methods may mistake reduced cell growth for senescence, cell death, or temporary growth arrest, leading to inaccurate assessments. This is especially problematic in large-scale drug screening, where thousands of compounds must be evaluated quickly and reliably.

To overcome these issues, researchers from Queen Mary University of London and the University of Dundee have developed a new machine learning–based method to improve the detection of senescence in cancer cells. Their findings were recently published in Aging-US.

The Study: Developing the SAMP-Score

The study, titled “SAMP-Score: a morphology-based machine learning classification method for screening pro-senescence compounds in p16-positive cancer cells,” was led by Ryan Wallis and corresponding author Cleo L. Bishop from Queen Mary University of London. This paper was featured on the cover of Aging-US Volume 17, Issue 11, and highlighted as our Editors’ Choice.

Full blog - https://aging-us.org/2025/12/using-machine-learning-to-identify-senescence-inducing-drugs-for-resistant-cancers/

Paper DOI - https://doi.org/10.18632/aging.206333

Corresponding author - Cleo L. Bishop - c.l.bishop@qmul.ac.uk

Abstract video - https://www.youtube.com/watch?v=qXI_KI3EgHE

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Keywords - aging, SAMP-Score, senescence, senescent marker positive cancer cells, Sen-Mark+, machine learning, pro-senescence, high-throughput compound screening

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Using Machine Learning to Identify Senescence-Inducing Drugs for Resistant Cancers

Aging-US is dedicated to advancing our understanding of the biological mechanisms that drive aging and the development of age-related diseases. Our mission is to serve as a platform for high-quality research that uncovers the cellular, molecular, and systemic processes underlying aging, and translates these insights into strategies to extend healthspan and delay the onset of chronic disease.

Read about the Aging (Aging-US) Scientific Integrity Process: https://aging-us.com/scientific-integrity

Embryo Arrest in IVF Linked to Maternal Age, Not Chromosomal Abnormalities

Aging-US Podcast

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