ReviewCellular and molecular bioengineering2020
Sticking to the Problem: Engineering Adhesion in Molecular Endoscopic Imaging.
Review in Cellular and molecular bioengineering, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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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.
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Authors and funding
7 authors.
Funding
Abstract
Cancers of the digestive tract cause nearly one quarter of the cancer deaths worldwide, and nearly half of these are due to cancers of the esophagus and colon. Early detection of cancer significantly increases the rate of survival, and thus it is critical that cancer within these organs is detected early. In this regard, endoscopy is routinely used to screen for transforming/cancerous (i.e. dysplastic to fully cancerous) tissue. Numerous studies have revealed that the biochemistry of the luminal surface of such tissue within the colon and esophagus becomes altered throughout disease progression. Molecular endoscopic imaging (MEI), an emerging technology, seeks to exploit these changes for the early detection of cancer. The general approach for MEI is as follows: the luminal surface of an organ is exposed to molecular ligands, or particulate probes bearing a ligand, cognate to biochemistry unique to pre-cancerous/cancerous tissue. After a wash, the tissue is imaged to determine the presence of the probes. Detection of the probes post-washing suggests pathologic tissue. In the current review we provide a succinct, but extensive, review of ligands and target moieties that could be, or are currently being investigated, as possible cognate chemistries for MEI. This is followed by a review of the biophysics that determines, in large part, the success of a particular MEI design. The work draws an analogy between MEI and the well-advanced field of cell adhesion and provides a road map for engineering MEI to achieve assays that yield highly selective recognition of transforming/cancerous tissue
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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.