(MedPage Today) -- A patient arrives for a visit, holding out a phone screen as evidence: an artificial intelligence (AI) tool has labeled their symptoms "high risk" and recommended a next step. The language is polished, the recommendation is specific...
npj Digital Medicine, Published online: 17 January 2026; doi:10.1038/s41746-026-02344-8
Wearable device derived electrocardiographic age and its association with atrial fibrillation
(MedPage Today) -- The FDA sent an early safety alert warning clinicians of deployment failures with certain Boston Scientific AXIOS Stent and Electrocautery Enhanced Delivery Systems that have been linked to three deaths and 167 serious injuries...
(MedPage Today) -- Concerns of hemolysis continued to swirl around the Sapien 3 Ultra Resilia, with yet another report indicating such harm after transcatheter aortic valve replacement (TAVR).
In a single-center retrospective study from Japan...
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No M&A. Some news but not a deluge. The weather was amazing. I took a walk in Golden Gate Park and came across the sculpture above, whatever it is.
The entire week was, dare I say it, chill. Just the way I wanted it to be.
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Nat Cancer. 2026 Jan 16. doi: 10.1038/s43018-025-01107-w. Online ahead of print.
ABSTRACT
The concept of cellular neighborhoods, defined as recurring structures within the tissue with characteristic cell compositions and interactions, has transformed our understanding of the complexity and dynamics of tumor ecosystems. Recent advances in spatial omics and computational modeling have enabled high-resolution mapping of these neighborhoods, providing unprecedented insights into their roles in shaping tumor heterogeneity, evolution and therapeutic responses. Despite these advances, a unified framework for interpreting cellular neighborhoods remains lacking. This Perspective synthesizes emerging concepts and insights, focusing on the definition and classification of cellular neighborhoods in cancer, computational methods for identifying and comparing them, and their clinical relevance.
PMID:41545713 | DOI:10.1038/s43018-025-01107-w
Nature Cancer, Published online: 16 January 2026; doi:10.1038/s43018-025-01110-1
Yabut and Drucker discuss clinical and preclinical evidence about the potential roles of GLP-1 medicines on cancer incidence, development and therapy and speculate about their mechanism on cancer cells and the tumor microenvironment.
Nature Medicine, Published online: 16 January 2026; doi:10.1038/s41591-025-04073-z
Analyses of liver biopsies from a child with spinal muscular atrophy treated with adeno-associated virus gene therapy who developed hepatitis reveal contaminating manufacturing plasmids and disrupted vector genomes, possibly resulting from recombination events.
Atherosclerosis. 2026 Jan 8;413:120637. doi: 10.1016/j.atherosclerosis.2026.120637. Online ahead of print.
ABSTRACT
BACKGROUND AND AIMS: Commercial high-throughput proteomics platforms, such as Olink and SomaLogic, enable large-scale epidemiological studies with integrated multi-omics measurements. While these proteomics approaches have been widely applied in biobanks, issues of data quality remain underappreciated. In this review, we discuss these limitations and outline a way forward for realizing the clinical translation of proteomics as a comprehensive 'liquid health check'.
METHODS: We reviewed the recent literature for artificial intelligence (AI) and multi-omics, particularly proteomics in atherosclerotic cardiovascular disease (ASCVD).
RESULTS: AI-driven multi-omics analyses have the potential to advance our understanding of multifactorial causes of ASCVD, including aging. Emerging concepts such as "ageotypes" suggest the potential for personalized intervention to slow aging processes. Commercial proteomics platforms have accelerated biomarker discovery in ASCVD, but challenges remain in clinical translation. Limited correlation between Olink and SomaLogic necessitates orthogonal validation of findings. Platform-specific issues, such as epitope effects and cross-reactivity, can yield divergent protein quantitative trait loci for the same protein, complicating causal inference. While tissue proteomics provides complementary insights to plasma proteomics, reliance on autopsy samples raises concerns about protein degradation and measurement reliability. Increasingly, single-cell and spatial proteomics are being explored to better capture plaque heterogeneity, complementing bulk proteomics in larger cohorts.
CONCLUSION: Beyond risk prediction, proteomics offers opportunities to elucidate disease mechanisms and enable drug repurposing. To realize the clinical potential of plasma proteomics, absolute or reliably recalibratable relative quantification will be required to guide patient care. Ultimately, the clinical value of proteomics will be determined by the quality rather than the quantity of protein measurements.
PMID:41539063 | DOI:10.1016/j.atherosclerosis.2026.120637
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