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Attention Score in Context
| Title |
Designing and testing regenerative pulp treatment strategies: modeling the transdentinal transport mechanisms
|
|---|---|
| Published in |
Frontiers in Physiology, September 2015
|
| DOI | 10.3389/fphys.2015.00257 |
| Pubmed ID | |
| Authors |
Agathoklis D. Passos, Aikaterini A. Mouza, Spiros V. Paras, Christos Gogos, Dimitrios Tziafas |
| Abstract |
The need for simulation models to thoroughly test the inflammatory effects of dental materials and dentinogenic effects of specific signaling molecules has been well recognized in current dental research. The development of a model that simulates the transdentinal flow and the mass transfer mechanisms is of prime importance in terms of achieving the objectives of developing more effective treatment modalities in restorative dentistry. The present protocol study is part of an ongoing investigation on the development of a methodology that can calculate the transport rate of selected molecules inside a typical dentinal tubule. The transport rate of biological molecules has been investigated using a validated CFD code. In that framework we propose a simple algorithm that, given the type of molecules of the therapeutic agent and the maximum acceptable time for the drug concentration to attain a required value at the pulpal side of the tubules, can estimate the initial concentration to be imposed. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 12 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 12 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 4 | 33% |
| Professor > Associate Professor | 2 | 17% |
| Student > Doctoral Student | 1 | 8% |
| Student > Bachelor | 1 | 8% |
| Student > Ph. D. Student | 1 | 8% |
| Other | 3 | 25% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 5 | 42% |
| Chemical Engineering | 3 | 25% |
| Materials Science | 2 | 17% |
| Unspecified | 1 | 8% |
| Unknown | 1 | 8% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 18 September 2015.
All research outputs
#20,291,881
of 22,828,180 outputs
Outputs from Frontiers in Physiology
#9,376
of 13,603 outputs
Outputs of similar age
#225,742
of 268,887 outputs
Outputs of similar age from Frontiers in Physiology
#66
of 91 outputs
Altmetric has tracked 22,828,180 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,603 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.6. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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We're also able to compare this research output to 91 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.