Good news! Cancer is history (soon)!
"Researchers have been exploring the use of injectable nanoparticles that can quickly home in on a microscopic tumor. It’s a novel technique that could pave the way for the early detection of small tumors that may not show up on traditional imaging technologies. ...
existing medical imaging techniques offer limited resolution when it comes to detecting microscopic tumors less than 0.5 millimeters in diameter. ...
However, it can be difficult to develop these “nanoswimmers,” which can efficiently disperse throughout a patient’s body, while sufficiently accumulating at the cancer site. Past studies show that only 0.7 percent of the injected nanoparticles reach their target. ...
Another option is to develop self-propelled nanoswimmers, which autonomously move inside the human body and have a chemical tendency to accumulate in tumors. For example, nanoswimmers designed to gravitate toward acidic environments will gravitate toward tumors, which tend to be more acidic than healthy tissues. But, autonomous nanoswimmers tend to move much slower than the magnetically guided nanoswimmers. ...
the semi-autonomous swarm can then be magnetically guided more quickly in the optimal direction: toward the tumor. ..."
the semi-autonomous swarm can then be magnetically guided more quickly in the optimal direction: toward the tumor. ..."
"Abstract:
Magnetically assembled bioresorbable nanoswimmers (NSs) can be used to highlight small tumors, thereby increasing the diagnostic capability of existing medical imaging techniques. Built upon our earlier work, this article proposes a novel in vivo computational framework for early cancer detection. Engineered NSs experience a change in their physical properties under the influence of tumor-induced biological gradients. The biologically sensed data by such bio-nano things (NSs) can either trigger an autonomous target-directed motion or be assisted through external manipulation for steering the swarm toward the target. Previously developed externally manipulable in vivo computation requires constant monitoring of NSs, introducing positioning and steering errors along with a limit on the swarm size. A parallel approach called autonomous in vivo computation helps to resolve the above drawbacks, but the tumor homing is slow contributing to a higher percentage of predetection loss of NSs. We propose the spot sampling strategy for an autonomous swarm which considers the whole swarm as a single entity for the purpose of its tracking and steering. We show through computational experiments: 1) that the proposed semi-autonomous in vivo framework can achieve faster tumor sensitization in complex environments having static and mobile obstacles and 2) that the spot sampling provides sufficiently precise data to steer the swarm toward the target, saving around 90% of the monitoring resource. Our proposed framework also helps to achieve a large swarm size (number of NSs) which in return can achieve a higher deposition of NSs on malignant tumors."
Semi-Autonomous In Vivo Computation in Internet of Bio-Nano Things (no public access)
No comments:
Post a Comment