| Title |
Progress and challenges of the bioartificial pancreas
|
|---|---|
| Published in |
Nano Convergence, November 2016
|
| DOI | 10.1186/s40580-016-0088-4 |
| Pubmed ID | |
| Authors |
Patrick T. J. Hwang, Dishant K. Shah, Jacob A. Garcia, Chae Yun Bae, Dong-Jin Lim, Ryan C. Huiszoon, Grant C. Alexander, Ho-Wook Jun |
| Abstract |
Pancreatic islet transplantation has been validated as a treatment for type 1 diabetes since it maintains consistent and sustained type 1 diabetes reversal. However, one of the major challenges in pancreatic islet transplantation is the body's natural immune response to the implanted islets. Immunosuppressive drug treatment is the most popular immunomodulatory approach for islet graft survival. However, administration of immunosuppressive drugs gives rise to negative side effects, and long-term effects are not clearly understood. A bioartificial pancreas is a therapeutic approach to enable pancreatic islet transplantation without or with minimal immune suppression. The bioartificial pancreas encapsulates the pancreatic islets in a semi-permeable environment which protects islets from the body's immune responses, while allowing the permeation of insulin, oxygen, nutrients, and waste. Many groups have developed various types of the bioartificial pancreas and tested their efficacy in animal models. However, the clinical application of the bioartificial pancreas still requires further investigation. In this review, we discuss several types of bioartificial pancreases and address their advantages and limitations. We also discuss recent advances in bioartificial pancreas applications with microfluidic or micropatterning technology. |
Mendeley readers
The data shown below were compiled from readership statistics for 80 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 80 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 14 | 18% |
| Student > Bachelor | 14 | 18% |
| Researcher | 11 | 14% |
| Student > Doctoral Student | 6 | 8% |
| Student > Master | 6 | 8% |
| Other | 9 | 11% |
| Unknown | 20 | 25% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 17 | 21% |
| Medicine and Dentistry | 13 | 16% |
| Engineering | 11 | 14% |
| Agricultural and Biological Sciences | 6 | 8% |
| Immunology and Microbiology | 2 | 3% |
| Other | 10 | 13% |
| Unknown | 21 | 26% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 23 April 2022.
All research outputs
#7,756,853
of 23,578,176 outputs
Outputs from Nano Convergence
#38
of 112 outputs
Outputs of similar age
#114,918
of 313,353 outputs
Outputs of similar age from Nano Convergence
#3
of 5 outputs
Altmetric has tracked 23,578,176 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 112 research outputs from this source. They receive a mean Attention Score of 4.8. This one has gotten more attention than average, scoring higher than 55% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 313,353 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 51% of its contemporaries.
We're also able to compare this research output to 5 others from the same source and published within six weeks on either side of this one. This one has scored higher than 2 of them.