BUFFALO, NY - April 8, 2025 – A new #editorial was #published in Oncotarget, Volume 16, on April 4, 2025, titled “Deep learning-based uncertainty quantification for quality assurance in hepatobiliary imaging-based techniques."

Dr. Yashbir Singh from Mayo Clinic and his colleagues discussed how artificial intelligence (AI) can improve liver imaging by recognizing when it might be wrong. This approach, called “uncertainty quantification,” helps clinicians better detect liver cancer and other diseases by pointing out areas in medical scans that need a second look. The authors explain how these AI tools could make imaging results more accurate and reliable, which is especially important when diagnosing serious conditions like liver tumors.

Liver and bile duct imaging is difficult because of the organ’s complex structure and differences in image quality. Even skilled radiologists can struggle to identify small or hidden tumors, especially in patients with liver damage or scarring. The editorial explains how new AI models not only read medical images but also measure their own confidence. When the AI system is unsure, it can alert clinicians to take a closer look. This extra layer of information can reduce missed diagnoses and improve early detection of liver cancer.

One of the most advanced tools described in the editorial is called AHUNet (Anisotropic Hybrid Network). This AI model works with both 2D and 3D images and can highlight which parts of a scan it is most confident about. It performed well when measuring the entire liver and showed how its confidence dropped when scanning smaller or multiple lesions. This feature helps clinicians know when more testing or review is needed.

The authors also looked at other AI models used in liver imaging. Some tools were able to analyze liver fat using ultrasound images and give clinicians both a result and a confidence score. Others improved the speed and accuracy of liver magnetic resonance imaging (MRI) scans, helping to create clear images in less time. These advancements could help hospitals work faster and provide better care.

The editorial highlights how this technology can be especially helpful in smaller clinics. If they do not have liver specialists, they could still use AI systems that flag uncertain results and send them to larger centers for review. Such an approach could improve care in rural or less-resourced areas.

“Radiology departments should develop standardized reporting templates that incorporate uncertainty metrics alongside traditional imaging findings.”

By using AI tools that know when to second-guess themselves, clinicians may soon have more reliable methods for detecting liver cancer and monitoring liver disease. The authors suggest that uncertainty-aware AI may soon become a vital part of everyday medical imaging, supporting faster and more accurate decisions in liver disease care.

DOI: https://doi.org/10.18632/oncotarget.28709

Correspondence to: Yashbir Singh — singh.yashbir@mayo.edu

Video short - https://www.youtube.com/watch?v=Zm0QASQ_YSI

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Keywords: cancer, deep learning, uncertainty quantification, radiology, hepatobiliary imaging

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Oncotarget

AI That Measures Its Own Uncertainty Could Improve Liver Cancer Detection

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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Repurposing Statins: Exploring Anti-Tumor Effects in Colorectal Cancer

Karilyn Larkin, MD, is leading a new clinical trial that could change and improve the way acute myelogenous leukemia (AML) is treated. “AML is a good example of how the better you understand the disease and the more clever you are in designing the clinical trial allows you to start to see successes where there were none before,” said Larkin, a James physician and hematologist. “In the past 10 years there have been more than 10 new drugs approved for treating AML which is phenomenal.” AML is a rare cancer of the blood that spreads quickly. Larkin and her team discovered a novel surface target on AML cells: the CD37 protein. This protein had previously been seen on lymphomas (another type of blood cancer). A drug was developed but wasn’t more effective than the standard of care for treating lymphomas. “We discovered CD37 is expressed more in AML and starts on the surface of the cells and is quickly pulled into the cells and that nuance makes it a good target for delivering a toxic payload [through the drug previously developed for lymphoma].” A clinical trial began in June that included several other major cancer centers around the country. Larkin was the principal investigator. The trial is currently in Phase 1 of its development in which “we start with a low dose and then make incremental increases, and once we find the correct and safe dose we will enter Phase 2 and expand the number of patients in the trial,” Larkin said. This trial a great example of what’s known as the bench to bedside approach in the battle against cancer. Scientists in the lab – or the bench – find new targets and drugs and work with physicians to bring these advances to patients – the bedside.

Episode 201: A New Clinical Trial for Treating Acute Myeloid Leukemia (AML),  with Dr. Larkin

In today’s episode, I talk with a truly special group of scholars, Candace Borders, Alison Kibe, and Jeania Ree Moore. They met as Graduate Writing Fellows and connected by giving each other feedback on their writing. While they share academic fields and methodologies, their ethics of care and investment in each other’s work allowed them to try out a new form of peer-review group, as “group consultations.” Conjoining the structure and duration of a peer-review writing group with the feedback process of an individual consultation, their group offers a unique model that can be formed by grad students who share a department and discipline. Sharing a discipline or department can have its’ challenges with respect to going “too deep” into the content, possible competition, and uneven experiences with working with advisors and gaining access to resources. Our guests offer a pathway based on Black feminist writing practices and theory that can mediate these challenges to offer a truly collaborative, compassionate, and accountable group writing and feedback model. 

Jeania Ree Moore is a writer, clergyperson, and interdisciplinary scholar of theology, religion, and African American studies. She is a PhD candidate in African American Studies and Religious Studies at Yale University, where her research draws on theology, ethics, and related disciplines to engage a range of sites in Black history and culture.  

Alison H Kibbe is an Assistant Professor of African American Studies at the College of Charleston. She is a scholar, multidisciplinary artist, and cultural organizer. In her scholarly work, Alison specializes in critical food studies, Black geographies and Black mobilities, and cultural production across the Caribbean and African Diaspora.

Candace Borders is an interdisciplinary scholar, educator, and curator. Her research explores the intersections of race, gender, class, and the urban Midwest, with particular attention to role of Black women’s activism in shaping the urban landscape.  She is a Postdoctoral Fellow at The Center for the Humanities, Washington University in St. Louis and received her PhD in American Studies and African American Studies from Yale University. 


Synergies, not Thorns with Jeania Ree Moore, Dr. Candace Borders, and Alison H. Kibbe

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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Aging-US

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

If you’re considering applying to Berkeley Divinity School at Yale, this episode is for you! 

It’s the SEMINARIAN TAKEOVER episode of The Leader’s Way Podcast. Berkeley Divinity School at Yale students Whitney Kimball Coe ’26, Misty Krasawski ‘26, and Jae Kirkland Rice ’27, pull back the curtain on what it’s like to be at seminary and divinity school.  

Our seminarians tell stories about how they made the decision to apply to Yale Divinity School and the questions, longings, and experiences that led them here. In this episode, we learn that there is no single path that leads a person to seminary, but many. We hear about worship at Berkeley, favorite courses, the importance of staying “prayed up,” and the ways God surprises us throughout this journey. 

 

Learn more at the Berkeley at Yale website: https://berkeleydivinity.yale.edu/ 

Special episode: The Seminarian Takeover!

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

BUFFALO, NY — December 12, 2025 — A new #research paper was #published in Volume 17, Issue 11 of Aging-US on November 14, 2025, titled “Methylglyoxal-induced glycation stress promotes aortic stiffening: putative mechanistic roles of oxidative stress and cellular senescence.”

The study was led by first authors Parminder Singh of the Buck Institute for Research on Aging and Ravinandan Venkatasubramanian of the University of Colorado Boulder, with senior contributions from corresponding authors Pankaj Kapahi (Buck Institute for Research on Aging) and Zachary S. Clayton (University of Colorado Boulder and University of Colorado Anschutz Medical Campus). The researchers investigated how methylglyoxal (MGO), a toxic byproduct that builds up in blood vessels with age or metabolic dysfunction like diabetes, contributes to artery stiffening. Their findings are especially important to aging and diabetes-related cardiovascular risk.

Aortic stiffening, which reduces the flexibility of the body’s largest artery, is a key predictor of cardiovascular disease in older adults. The research team used young and aged mice to study how MGO affects vascular health. In young mice, chronic exposure to MGO increased aortic stiffness by 21%. However, when treated with Gly-Low, a supplement containing natural compounds such as nicotinamide and alpha-lipoic acid, this stiffening was completely prevented. Gly-Low also reduced the buildup of MGO and its harmful byproducts, particularly MGH-1, in both blood and tissue.

“Aortic stiffness was assessed in vivo via pulse wave velocity (PWV) and ex vivo through elastic modulus.”

The research showed that MGO’s damage goes beyond structural changes. It also caused the endothelial cells that line blood vessels to enter senescence, a state in which cells stop dividing and begin releasing inflammatory signals. This led to lower levels of nitric oxide, a molecule essential for blood vessel relaxation. In human vascular cells in lab culture, Gly-Low reversed these aging-like changes and restored nitric oxide production.

In older mice, which naturally develop stiffer arteries, Gly-Low treatment during four months significantly reduced stiffness and lowered MGO and MGH-1 levels. This suggests that Gly-Low may help slow or even reverse vascular aging by reducing glycation stress.

The study also identified the glyoxalase-1 pathway as a critical mechanism. This is a natural detox system that helps clear harmful molecules like MGO. Gly-Low appeared to boost this pathway. When the pathway was chemically blocked, Gly-Low’s protective effects disappeared, confirming its role in the process.

Overall, the findings highlight glycation stress as a modifiable contributor to vascular aging. The results suggest that natural compound-based therapies, like Gly-Low, may offer a potential strategy to protect arteries from age- and diabetes-related damage.

DOI - https://doi.org/10.18632/aging.206335

Corresponding authors: Pankaj Kapahi - pkapahi@buckinstitute.org; Zachary S. Clayton - Zachary.Clayton@cuanschutz.edu

Abstract video: https://www.youtube.com/watch?v=i_rtq8eIb8c

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Glycation Stress Promotes Arterial Stiffening and Is Reversed by a Natural Compound in Aging Mice

Socio-cultural anthropologist Todne Thomas, Associate Professor of Divinity and Religious Studies at Yale Divinity School, discusses researching a 2015 arson of a predominantly Black church in Tennessee, what it says about humanity, and why in-depth study of American religious life is critically important.

What a 2015 Church Burning Reveals About Race, Religion, and Life in America with Professor Todne Thomas

YJBM Science News is back with Part 1 of our very first Special Episode! Join Hanna, Majo, and Roxanna as they sit down with Dr. Diyendo Massilani, a researcher and professor at Yale investigating evolutionary genetics. We’ll hear from Dr. Massilani about the challenges and ethical considerations of working with ancient DNA, as well as the incredible doors it has opened to what we can interrogate and what we know about extinct human populations. Keep an eye out in the new year for Part 2, which will dive into the groundbreaking work of Dr. Massilani’s former mentor and 2022 Nobel prize winner Dr. Svante Pääbo.

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Science News Special Episode - Ancient DNA and Evolutionary Genetics: An Interview with Dr. Diyendo Massilani

Oncotarget is a primarily oncology-focused, peer-reviewed, open access journal. Papers are published continuously within yearly volumes in their final and complete form and then quickly released to Pubmed.

Oncotarget is now indexed by MEDLINE, PubMed and PMC/PubMed.

Read about the Oncotarget Scientific Integrity Process: https://www.oncotarget.com/scientific_integrity/

AI That Measures Its Own Uncertainty Could Improve Liver Cancer Detection

Oncotarget Podcast