| Title |
Characterization of miRNA processing machinery in the embryonic chick lung
|
|---|---|
| Published in |
Cell and Tissue Research, July 2015
|
| DOI | 10.1007/s00441-015-2240-6 |
| Pubmed ID | |
| Authors |
Rute Silva Moura, Patrícia Vaz-Cunha, Carla Silva-Gonçalves, Jorge Correia-Pinto |
| Abstract |
Lung development is a very complex process that relies on the interaction of several signaling pathways that are controlled by precise regulatory mechanisms. Recently, microRNAs (miRNAs), small non-coding regulatory RNAs, have emerged as new players involved in gene expression regulation controlling several biological processes, such as cellular differentiation, apoptosis and organogenesis, in both developmental and disease processes. Failure to correctly express some specific miRNAs or a component of their biosynthetic machinery during embryonic development is disastrous, resulting in severe abnormalities. Several miRNAs have already been identified as modulators of lung development. Regarding the spatial distribution of the processing machinery of miRNAs, only two of its members (dicer1 and argonaute) have been characterized. The present work characterizes the expression pattern of drosha, dgcr8, exportin-5 and dicer1 in early stages of the embryonic chick lung by whole mount in situ hybridization and cross-section analysis. Overall, these genes are co-expressed in dorsal and distal mesenchyme and also in growing epithelial regions. The expression pattern of miRNA processing machinery supports the previously recognized regulatory role of this mechanism in epithelial and mesenchymal morphogenesis. |
Mendeley readers
The data shown below were compiled from readership statistics for 17 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 6% |
| Unknown | 16 | 94% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 5 | 29% |
| Student > Bachelor | 3 | 18% |
| Student > Ph. D. Student | 3 | 18% |
| Student > Master | 2 | 12% |
| Professor | 1 | 6% |
| Other | 1 | 6% |
| Unknown | 2 | 12% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 6 | 35% |
| Medicine and Dentistry | 5 | 29% |
| Agricultural and Biological Sciences | 3 | 18% |
| Chemical Engineering | 1 | 6% |
| Unknown | 2 | 12% |
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 24 July 2015.
All research outputs
#21,178,329
of 23,839,820 outputs
Outputs from Cell and Tissue Research
#2,002
of 2,279 outputs
Outputs of similar age
#222,480
of 265,764 outputs
Outputs of similar age from Cell and Tissue Research
#17
of 24 outputs
Altmetric has tracked 23,839,820 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 2,279 research outputs from this source. They receive a mean Attention Score of 3.3. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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 265,764 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 24 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.