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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Regulators of Tfh Cell Differentiation
|
|---|---|
| Published in |
Frontiers in immunology, November 2016
|
| DOI | 10.3389/fimmu.2016.00520 |
| Pubmed ID | |
| Authors |
Gajendra M. Jogdand, Suchitra Mohanty, Satish Devadas |
| Abstract |
The follicular helper T (Tfh) cells help is critical for activation of B cells, antibody class switching, and germinal center (GC) formation. The Tfh cells are characterized by the expression of CXC chemokine receptor 5 (CXCR5), ICOS, programed death 1 (PD-1), B cell lymphoma 6 (BCL-6), and IL-21. They are involved in clearing infections and are adversely linked with autoimmune diseases and also have a role in viral replication as well as clearance. On the one hand, Tfh cells are generated from naive CD4(+) T cells with sequential steps involving cytokine signaling (IL-21, IL-6, IL-12, activin A), migration, and positioning in the GC by CXCR5, surface receptors (ICOS/ICOSL, signaling lymphocyte activation molecule-associated protein/signaling lymphocyte activation molecule) as well as transcription factor (BCL-6, c-Maf, and signal transducer and activator of transcription 3) signaling and repressor miR155. On the other hand, Tfh generation is negatively regulated at specific steps of Tfh generation by specific cytokine (IL-2, IL-7), surface receptor (PD-1, CTLA-4), transcription factors B lymphocyte maturation protein 1, signal transducer and activator of transcription 5, T-bet, KLF-2 signaling, and repressor miR 146a. Interestingly, miR-17-92 and FOXO1 act as a positive as well as a negative regulator of Tfh differentiation depending on the time of expression and disease specificity. Tfh cells are also generated from the conversion of other effector T cells as exemplified by Th1 cells converting into Tfh during viral infection. The mechanistic details of effector T cells conversion into Tfh are yet to be clear. To manipulate Tfh cells for therapeutic implication and or for effective vaccination strategies, it is important to know positive and negative regulators of Tfh generation. Hence, in this review, we have highlighted and interlinked molecular signaling from cytokines, surface receptors, transcription factors, ubiquitin ligase, and microRNA as positive and negative regulators for Tfh differentiation. |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Italy | 1 | 11% |
| Mexico | 1 | 11% |
| Venezuela, Bolivarian Republic of | 1 | 11% |
| Switzerland | 1 | 11% |
| Unknown | 5 | 56% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 6 | 67% |
| Practitioners (doctors, other healthcare professionals) | 2 | 22% |
| Scientists | 1 | 11% |
Mendeley readers
The data shown below were compiled from readership statistics for 202 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 202 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 40 | 20% |
| Researcher | 30 | 15% |
| Student > Bachelor | 27 | 13% |
| Student > Master | 21 | 10% |
| Student > Doctoral Student | 14 | 7% |
| Other | 23 | 11% |
| Unknown | 47 | 23% |
| Readers by discipline | Count | As % |
|---|---|---|
| Immunology and Microbiology | 61 | 30% |
| Biochemistry, Genetics and Molecular Biology | 27 | 13% |
| Medicine and Dentistry | 26 | 13% |
| Agricultural and Biological Sciences | 23 | 11% |
| Pharmacology, Toxicology and Pharmaceutical Science | 4 | 2% |
| Other | 9 | 4% |
| Unknown | 52 | 26% |
Attention Score in Context
This research output has an Altmetric Attention Score of 5. 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 14 February 2020.
All research outputs
#7,301,532
of 25,371,288 outputs
Outputs from Frontiers in immunology
#8,400
of 31,513 outputs
Outputs of similar age
#121,203
of 415,170 outputs
Outputs of similar age from Frontiers in immunology
#76
of 240 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. This one has received more attention than most of these and is in the 71st percentile.
So far Altmetric has tracked 31,513 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.4. This one has gotten more attention than average, scoring higher than 72% 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 415,170 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 70% of its contemporaries.
We're also able to compare this research output to 240 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 67% of its contemporaries.