ReviewBiology of reproduction2024
Targeted nanoparticles for imaging and therapy of endometriosis†.
Review in Biology of reproduction, 2024. 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
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
8 citing papers in PubMed.
- Towards clinical translation of nanomedicines: Formulation scale-up and model systems.Advanced drug delivery reviews · 2026Review
- The Association of Primate Veterinarians and the European Primate Veterinarians Position Statement on the Value of Nonhuman Primates in Research.Journal of the American Association for Laboratory Animal Science : JAALAS · 2026Article
- Endometriosis as a Systemic and Complex Disease: Toward Phenotype-Based Classification and Personalized Therapy.International journal of molecular sciences · 2026Review
- Noninvasive Detection and Thermal Ablation Therapy of Endometriosis Using Silica-Coated Gold Nanorods.Advanced nanobiomed research · 2025Article
- Nanotechnology strategies for endometrium health: Are we on the right track?Bioactive materials · 2025Review
- Analysis of diagnostic apoptosis-related biomarkers and immune cell infiltration characteristics in endometriosis by integrating bioinformatics and machine learning.Scientific reports · 2025Article
- Clinical applications, advances, and future directions in hysterosalpingography.Frontiers in medicine · 2025Review
- A Comprehensive Review of Advanced Diagnostic Techniques for Endometriosis: New Approaches to Improving Women's Well-Being.Medicina (Kaunas, Lithuania) · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
Abstract
In this brief review, we discuss our efforts to validate nanoplatforms for imaging and treatment of endometriosis. We specifically highlight our use of nonhuman primates and primate tissues in this effort. Endometriosis is a painful disorder of women and nonhuman primates where endometrium-like tissue exists outside of the uterus. There are no reliable, specific, and noninvasive diagnostic tests for endometriosis. Laparoscopic imaging remains the gold standard for identifying small endometriotic lesions in both women and monkeys. Visualizing and surgically removing microscopic lesions remains a clinical challenge. To address this challenge, we have created nanoparticle reagents that, when administered intravenously, enter endometriotic lesions both passively and by targeting endometriotic cells. The particles can carry payloads, including near-infrared fluorescent dyes and magnetic nanoparticles. These agents can be used for imaging and thermal ablation of diseased tissues. We evaluated this approach on macaque endometriotic cells, human and macaque endometrium engrafted into immunodeficient mice, in endometrium subcutaneously autografted in macaques, and in rhesus monkeys with spontaneous endometriosis. Employing these models, we report that nanoplatform-based reagents can improve imaging and provide thermal ablation of endometriotic tissues.
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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 OpenQuestion graph.