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3D-Printed Flexible Polylactic Acid/ Thermoplatic Polyurethane (PLA/TPU) Stents for Esophageal Malignancies
Title
3D-Printed Flexible Polylactic Acid/ Thermoplatic Polyurethane (PLA/TPU) Stents for Esophageal Malignancies.
Creator
Lin, Maohua, Kang, Yunqing, Tsai, Chi-Tay, Florida Atlantic University, College of Engineering and Computer Science, Department of Ocean and Mechanical Engineering
Abstract/Description
Palliation therapy for dysphagia using esophageal stents is the current treatment of choice for those patients with inoperable esophageal malignancies. However, the stents currently used in the clinical setting, regardless of the type of metal mesh or plastic mesh stents (covered/uncovered), may cause complications, such as tumor ingrowth and stent migration into the stomach. Furthermore, metal mesh stents have limited capacities for loading anti-cancer drugs. To effectively reduce/overcome...
Show morePalliation therapy for dysphagia using esophageal stents is the current treatment of choice for those patients with inoperable esophageal malignancies. However, the stents currently used in the clinical setting, regardless of the type of metal mesh or plastic mesh stents (covered/uncovered), may cause complications, such as tumor ingrowth and stent migration into the stomach. Furthermore, metal mesh stents have limited capacities for loading anti-cancer drugs. To effectively reduce/overcome those complications and enhance the efficacy of drug release, we designed and 3D-printed a tubular, flexible polymer stent with spirals, and then load anti-cancer drug, paclitaxel, on the stent for drug release. Non- spiral 3D-printed tubular and mesh polymer stents served as controls. The self-expansion and anti migration properties, cytotoxicity, drug release profile, and cancer cell inhibition of the 3D-printed stent were fully characterized. Results showed the self-expansion force of the 3D-printed polymer stent with spirals was slightly higher than the stent without spirals. The anti-migration force of the 3D-printed stent with spirals was significantly higher than the anti-migration force of a non-spiral stent. Furthermore, the stent with spirals significantly decreased the migration distance compared to the migration distance of the non-spiral 3D-printed polymer stent. The in vitro cytotoxicity of the new stent was examined through the viability test of human esophagus epithelial cells, and results indicated that the polymer stent does not have any cytotoxicity. The results of in vitro cell viability of esophageal cancer cells further indicated that the paclitaxel in the spiral stent treated esophageal cancer cells much more efficiently than that in the mesh stent. Furthermore, the results of the in vitro drug release profile and drug permeation showed that the dense tubular drug-loaded stent could efficiently be delivered more paclitaxel through the esophageal mucosa/submucosa layers in a unidirectional way than mesh stent that delivered less paclitaxel to the esophageal mucosa/submucosa but more to the lumen. In summary, these results showed that the 3D-printed dense polymer stent with spirals has promising potential to treat esophageal malignancies.
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Date Issued
2019
PURL
http://purl.flvc.org/fau/fd/FA00013230
Subject Headings
Paclitaxel, Stents, Esophageal Neoplasms, 3-D printing, Polymers in medicine
Format
Document (PDF)
Feeling the beat: a smart hand exoskeleton for learning to play musical instruments
Title
Feeling the beat: a smart hand exoskeleton for learning to play musical instruments.
Creator
Maohua Lin, Rudy Paul, Moaed Abd, James Jones, Darryl Dieujuste, Harvey Chim, Erik D. Engeberg
Abstract/Description
Individuals who have suffered neurotrauma like a stroke or brachial plexus injury often experience reduced limb functionality. Soft robotic exoskeletons have been successful in assisting rehabilitative treatment and improving activities of daily life but restoring dexterity for tasks such as playing musical instruments has proven challenging. This research presents a soft robotic hand exoskeleton coupled with machine learning algorithms to aid in relearning how to play the piano by ‘feeling’...
Show moreIndividuals who have suffered neurotrauma like a stroke or brachial plexus injury often experience reduced limb functionality. Soft robotic exoskeletons have been successful in assisting rehabilitative treatment and improving activities of daily life but restoring dexterity for tasks such as playing musical instruments has proven challenging. This research presents a soft robotic hand exoskeleton coupled with machine learning algorithms to aid in relearning how to play the piano by ‘feeling’ the difference between correct and incorrect versions of the same song. The exoskeleton features piezoresistive sensor arrays with 16 taxels integrated into each fingertip. The hand exoskeleton was created as a single unit, with polyvinyl acid (PVA) used as a stent and later dissolved to construct the internal pressure chambers for the five individually actuated digits. Ten variations of a song were produced, one that was correct and nine containing rhythmic errors. To classify these song variations, Random Forest (RF), K-Nearest Neighbor (KNN), and Artificial Neural Network (ANN) algorithms were trained with data from the 80 taxels combined from the tactile sensors in the fingertips. Feeling the differences between correct and incorrect versions of the song was done with the exoskeleton independently and while the exoskeleton was worn by a person. Results demonstrated that the ANN algorithm had the highest classification accuracy of 97.13% ± 2.00% with the human subject and 94.60% ± 1.26% without. These findings highlight the potential of the smart exoskeleton to aid disabled individuals in relearning dexterous tasks like playing musical instruments.
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Date Issued
2023
PURL
http://purl.flvc.org/fau/fd/FAUIR000534
Format
Document (PDF)