ArticleCancers2020
Synergistic Analysis of Protein Corona and Haemoglobin Levels Detects Pancreatic Cancer.
Article in Cancers, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 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
14 citing papers in PubMed, 28 citations in OpenAlex.
- Exploiting differences in personal nanoparticle corona profiles for cancer diagnostics.Nanomedicine (London, England) · 2025Article
- A Review for Uncovering the "Protein-Nanoparticle Alliance": Implications of the Protein Corona for Biomedical Applications.Nanomaterials (Basel, Switzerland) · 2024Review
- Graphene Oxide Nanoparticles and Organoids: A Prospective Advanced Model for Pancreatic Cancer Research.International journal of molecular sciences · 2024Review
- The influence of protein corona on Graphene Oxide: implications for biomedical theranostics.Journal of nanobiotechnology · 2023Review
- Article
- The Yin and Yang of the protein corona on the delivery journey of nanoparticles.Nano research · 2023Review
- Article
- Nanotechnology Meets Oncology: A Perspective on the Role of the Personalized Nanoparticle-Protein Corona in the Development of Technologies for Pancreatic Cancer Detection.International journal of molecular sciences · 2022Review
- Machine Learning-Assisted FTIR Analysis of Circulating Extracellular Vesicles for Cancer Liquid Biopsy.Journal of personalized medicine · 2022Article
- Nanoparticle personalized biomolecular corona: implications of pre-existing conditions for immunomodulation and cancer.Biomaterials science · 2022Review
- Article
- Sensing red blood cell nano-mechanics: Toward a novel blood biomarker for Alzheimer's disease.Frontiers in aging neuroscience · 2022Article
- Detection of Pancreatic Ductal Adenocarcinoma by Ex Vivo Magnetic Levitation of Plasma Protein-Coated Nanoparticles.Cancers · 2021Article
- CA19.9 Serum Level Predicts Lymph-Nodes Status in Resectable Pancreatic Ductal Adenocarcinoma: A Retrospective Single-Center Analysis.Frontiers in oncology · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors at 3 institutions in 2 countries.
Funding
Abstract
Simultaneous detection of multiple analytes from a single biological sample is gaining more attention in the development of more reliable and point-of-care diagnostic devices. We developed a multiplexed strategy that combined outcomes of clinical biomarkers with analysis of the protein corona that forms around graphene oxide sheets upon exposure to patient's plasma. As a paradigmatic case study, we selected pancreatic ductal adenocarcinoma (PDAC), mainly because of the absence of effective detection strategies that resulted in an extremely low five-year survival rate after diagnosis (<10%). Association of protein corona analysis and haemoglobin levels discriminated PDAC patients from healthy volunteers in up to 90% of cases. If further confirmed in larger-cohort studies, this approach may be used in the detection of PDAC.
Indexed as
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What OpenQuestion holds
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.