The DOI matches its Crossref record; 17 of the 17 references it cites were found in a registry or an index; none of the 19 sources its claims cite is checked for support yet.
Differential expression of microRNAs in hematopoietic cell lineages
Open accessAbstract
Objectives: MicroRNAs (miRNAs) play key roles in a wide variety of normal and pathological cellular processes. A number of studies identified hematopoietic‐specific miRNAs that are necessary for correct function of blood cells. Out of our microarray data, we chose 13 miRNAs that showed differential expression in peripheral blood cells (miR‐15b, miR‐16, miR‐24, miR‐30c, miR‐106b, miR‐142‐3p, miR‐142‐5p, miR‐150, miR‐155, miR‐181, miR‐223, miR‐342, and miR‐451) and examined their expression in separated hematopoietic cell lineages. Methods: Using quantitative real‐time polymerase chain reaction, we measured relative expression of the miRNAs in fractions of reticulocytes, platelets, granulocytes, monocytes, B‐ and T‐lymphocytes as well as in several hematopoietic cell lines. Results: We observed that miR‐16 and miR‐142‐3p were highly expressed in all native cell lineages, miR‐451 reached the maximal expression in reticulocytes, miR‐223 in platelets, granulocytes and monocytes, and miR‐150 in B‐ and T‐lymphocytes. Hierarchical clustering analysis grouped the lineage samples according to their origin based on the expression of these miRNAs. To validate discrimination power of the miRNAs, we quantified expression of the 13 miRNAs in several immortalized cell lines. Although the cell lines showed miRNA expression patterns considerably different from those of native cell lineages, clustering analysis distinguished between myeloid, lymphoid and non‐hematopoietic cells. Conclusions: In conclusion, the study reports the expression levels of 13 miRNAs in particular blood cell lineages as well as immortalized cell lines. We demonstrate that the expression profiles of these miRNAs may be used for discrimination of the hematopoietic cell lineages.
Overview
AI snapshot
Written from the paper’s full text.
TL;DR
This study measured 13 microRNAs by qRT-PCR in separated peripheral blood cell lineages from 10 healthy donors and in immortalized cell lines, identifying lineage-specific expression patterns. It concludes that these miRNA profiles can discriminate hematopoietic cell lineages, although immortalized cell lines showed expression patterns considerably different from native lineages.
Key findings
- miR-16 and miR-142-3p were highly expressed in most native hematopoietic lineages; miR-451 reached maximal expression in reticulocytes, miR-223 in platelets, granulocytes, and monocytes, and miR-150 in B- and T-lymphocytes.
- Reticulocytes and platelets showed apparently higher expression across all tested miRNAs (average 10^3 arbitrary units) than other cell types (average 10–10^2 arbitrary units); mean CT values of RNU6B were higher in reticulocytes (31.1 ± 0.4) and platelets (29.8 ± 0.5) than in granulocytes (26.1 ± 0.2), mononuclear cells (27.0 ± 0.2), monocytes (28.0 ± 0.3), B-cells (28.3 ± 0.2), and T-cells (27.6 ± 0.3).
- Hierarchical clustering grouped lineage samples according to origin; reticulocytes formed the most distinct group, B- and T-lymphocytes clustered together, and most platelets grouped with myeloid cells, though several platelet samples mixed into granulocyte and monocyte clusters.
- In immortalized cell lines, miR-16 was highly expressed in all samples including non-hematopoietic 293T and HeLa; miR-142 was almost absent in HeLa and 293T; miR-223 was present in myeloid cells; miR-155 was highly expressed only in lymphoblastic UHKT132 and UHKT133; clustering separated non-hematopoietic, myeloid, and lymphoid cell lines.
Methods
- Peripheral blood was obtained from 10 healthy adult donors (age 25–74 years, median 35; equal male/female distribution). Mononuclear cells and granulocytes were separated by Ficoll-Paque density gradient centrifugation; platelets by centrifugation; reticulocyte RNA from blood lysates by sucrose/KCl centrifugation. Mononuclear cells were further separated into CD3+ T-cells, CD19+ B-cells, and CD14+ monocytes using MACS kits; purity was controlled by FACS and ranged 96.5–99%.
- Immortalized cell lines included K-562, KU812, MOLM9, ML2, MV4-11, UHKT132, UHKT133, 293T, and HeLa; cells were cultured in RPMI 1640 with 10% fetal bovine serum and antibiotics and harvested after the fourth passage.
- miRNA expression was measured by qRT-PCR using TaqMan MicroRNA Expression Assays, normalized to endogenous control RNU6B, with relative expression calculated by the delta CT method. Hierarchical clustering used average linkage and Pearson correlation.
Limitations
- The paper does not include a formal limitations section. The authors state that higher expression levels in reticulocytes and platelets may have been caused by partial disintegration of RNAs not seen by routine techniques, resulting in distinct levels of RNU6B transcript.
- The authors state that misclassification of some platelet samples in clustering may be due to similarity between platelets and myeloid cells or possible contamination in platelets.
- Evident from the text: the native cell analysis used 10 healthy donors, and the immortalized cell lines showed miRNA expression patterns considerably different from those of native cell lineages.
Model-written summary. Check it against the paper before relying on it.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
31 Own result · 13 Sources not found · 7 Own interpretation · 2 Own method
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“We observed that miR-16 and miR-142-3p were highly expressed in all native cell lineages”
§ Differential expression of microRNAs in hematopoietic cell lineages > Abstract
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Rests on an assumption: RNU6B is a stable endogenous control suitable for normalizing miRNA expression across the tested hematopoietic cell lineages and cell lines.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“We detected apparently higher expression levels across all tested miRNAs in reticulocytes and platelets (relative levels reached at average 10 3 arbitrary units) in comparison to other cell types (at average 10-10 2 arbitrary units).”
§ Differential expression of microRNAs in hematopoietic cell lineages > Expression levels of miRNAs in hematopoietic cell lineages
hedgedcorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Rests on an assumption: RNU6B is a stable endogenous control suitable for normalizing miRNA expression across the tested hematopoietic cell lineages and cell lines.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Mean C T values of RNU6B ranged 26.1 ± 0.2 in granulocytes, 27.0 ± 0.2 in mononuclear cells, 28.0 ± 0.3 in monocytes, 28.3 ± 0.2 in B-cells and 27.6 ± 0.3 in T cells; however, there were higher C T values of RNU6B in reticulocytes and platelets (31.1 ± 0.4 and 29.8 ± 0.5, respectively).”
§ Differential expression of microRNAs in hematopoietic cell lineages > Expression levels of miRNAs in hematopoietic cell lineages
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Rests on an assumption: RNU6B is a stable endogenous control suitable for normalizing miRNA expression across the tested hematopoietic cell lineages and cell lines.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“clustering analysis distinguished between myeloid, lymphoid and non-hematopoietic cells”
§ Differential expression of microRNAs in hematopoietic cell lineages > Abstract
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Rests on an assumption: The immortalized cell lines used represent the hematopoietic lineages from which they were derived (myeloid, lymphoid, non-hematopoietic).
- Rests on an assumption: RNU6B is a stable endogenous control suitable for normalizing miRNA expression across the tested hematopoietic cell lineages and cell lines.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“miR-16 and miR-142-3p showed high expression in most hematopoietic cells.”
§ Differential expression of microRNAs in hematopoietic cell lineages > Expression levels of miRNAs in hematopoietic cell lineages
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Rests on an assumption: RNU6B is a stable endogenous control suitable for normalizing miRNA expression across the tested hematopoietic cell lineages and cell lines.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Hierarchical clustering analysis grouped the lineage samples according to their origin based on the expression of these miRNAs.”
§ Differential expression of microRNAs in hematopoietic cell lineages > Abstract
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Rests on an assumption: RNU6B is a stable endogenous control suitable for normalizing miRNA expression across the tested hematopoietic cell lineages and cell lines.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“miR-223 in platelets, granulocytes and monocytes”
- Also stated in: § Expression levels of miRNAs in hematopoietic cell lineages · plain
“miR-223 in platelets, granulocytes and monocytes”
- Also stated in: § Conclusion · plain
“miR-223 in platelets, granulocytes and monocytes”
§ Differential expression of microRNAs in hematopoietic cell lineages > Abstract
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Rests on an assumption: RNU6B is a stable endogenous control suitable for normalizing miRNA expression across the tested hematopoietic cell lineages and cell lines.
- Also stated in: § Expression levels of miRNAs in hematopoietic cell lineages · plain
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Relatively uniform pattern of low expression across the tested lineages exhibited miR-155, miR-181a, and miR-342.”
§ Differential expression of microRNAs in hematopoietic cell lineages > Expression levels of miRNAs in hematopoietic cell lineages
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Rests on an assumption: RNU6B is a stable endogenous control suitable for normalizing miRNA expression across the tested hematopoietic cell lineages and cell lines.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“miR-451 reached the maximal expression in reticulocytes”
- Also stated in: § Expression levels of miRNAs in hematopoietic cell lineages · plain
“miR-451 reached the maximal expression in reticulocytes”
- Also stated in: § Conclusion · plain
“up-regulation of miR-451 in reticulocytes”
§ Differential expression of microRNAs in hematopoietic cell lineages > Abstract
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Rests on an assumption: RNU6B is a stable endogenous control suitable for normalizing miRNA expression across the tested hematopoietic cell lineages and cell lines.
- Also stated in: § Expression levels of miRNAs in hematopoietic cell lineages · plain
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“miR-150 in B-and T-lymphocytes”
- Also stated in: § Expression levels of miRNAs in hematopoietic cell lineages · plain
“miR-150 in B-and T-lymphocytes”
- Also stated in: § Conclusion · plain
“miR-150 in lymphocytes”
§ Differential expression of microRNAs in hematopoietic cell lineages > Abstract
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Rests on an assumption: RNU6B is a stable endogenous control suitable for normalizing miRNA expression across the tested hematopoietic cell lineages and cell lines.
- Also stated in: § Expression levels of miRNAs in hematopoietic cell lineages · plain
- It may state two separate claims as one. 24
- Probably not a substantial claim. 8
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In reticulocytes, most of the miRNAs were expressed at high level and low expression was observed only for miR-150, miR-155, miR-181a, and miR-342.”
§ Differential expression of microRNAs in hematopoietic cell lineages > Expression levels of miRNAs in hematopoietic cell lineages
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Rests on an assumption: RNU6B is a stable endogenous control suitable for normalizing miRNA expression across the tested hematopoietic cell lineages and cell lines.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“that miR-451 was expressed in reticulocytes about 10 4fold more than in mononuclear cells (in platelets 10 2 -fold more and in granulocytes 10-fold more).”
§ Differential expression of microRNAs in hematopoietic cell lineages > Expression levels of miRNAs in hematopoietic cell lineages
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Rests on an assumption: RNU6B is a stable endogenous control suitable for normalizing miRNA expression across the tested hematopoietic cell lineages and cell lines.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“miR-16 and miR-451 reached the maximal expression; their expression exceed other miRNAs more than 10-fold.”
§ Differential expression of microRNAs in hematopoietic cell lineages > Expression levels of miRNAs in hematopoietic cell lineages
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Rests on an assumption: RNU6B is a stable endogenous control suitable for normalizing miRNA expression across the tested hematopoietic cell lineages and cell lines.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Each cell lineage was characterized by specific miRNA profile with a predominantly expressed gene: miR-451 reached the maximal expression in reticulocytes, miR-223 in platelets, granulocytes and monocytes, miR-150 in B-and T-lymphocytes.”
§ Differential expression of microRNAs in hematopoietic cell lineages > Expression levels of miRNAs in hematopoietic cell lineages
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Rests on an assumption: RNU6B is a stable endogenous control suitable for normalizing miRNA expression across the tested hematopoietic cell lineages and cell lines.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Based on similarity of the profiles, the analysis clustered together (i) miRNAs with similar expression and (ii) samples of each cell lineage.”
§ Differential expression of microRNAs in hematopoietic cell lineages > Hierarchical clustering
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Rests on an assumption: RNU6B is a stable endogenous control suitable for normalizing miRNA expression across the tested hematopoietic cell lineages and cell lines.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Although majority of the platelets formed a proper subgroup as a part of the myeloid cluster, several platelet samples were mixed into the other groups of myeloid cells, i.e. granulocyte and monocyte clusters.”
§ Differential expression of microRNAs in hematopoietic cell lineages > Hierarchical clustering
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Rests on an assumption: RNU6B is a stable endogenous control suitable for normalizing miRNA expression across the tested hematopoietic cell lineages and cell lines.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“miR-181a showed low expression levels in all tested samples (the lowest level in B-cells) except of reticulocytes and platelets.”
§ Differential expression of microRNAs in hematopoietic cell lineages > Expression levels of miRNAs in hematopoietic cell lineages
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Rests on an assumption: RNU6B is a stable endogenous control suitable for normalizing miRNA expression across the tested hematopoietic cell lineages and cell lines.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In our study, miR-150 was highly expressed in both B-and T-lymphocytes and was nearly absent in monocytes.”
§ Differential expression of microRNAs in hematopoietic cell lineages > Expression levels of miRNAs in hematopoietic cell lineages
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Rests on an assumption: RNU6B is a stable endogenous control suitable for normalizing miRNA expression across the tested hematopoietic cell lineages and cell lines.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“There was predominant expression of miR-16, miR142-3p, and miR-150 and the only significant difference was in the amount of miR-342 (it reached approximately 10-fold higher expression in T-cells than in B-cells).”
§ Differential expression of microRNAs in hematopoietic cell lineages > Expression levels of miRNAs in hematopoietic cell lineages
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Rests on an assumption: RNU6B is a stable endogenous control suitable for normalizing miRNA expression across the tested hematopoietic cell lineages and cell lines.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“however using qRT-PCR, we quantified its expression in all cell types and demonstrated its highest expression in platelets and the lowest level in granulocytes compared to the other cells.”
§ Differential expression of microRNAs in hematopoietic cell lineages > Expression levels of miRNAs in hematopoietic cell lineages
boostedcorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Rests on an assumption: RNU6B is a stable endogenous control suitable for normalizing miRNA expression across the tested hematopoietic cell lineages and cell lines.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“As expected, miR-142-3p and miR-142-5p were clustered together.”
§ Differential expression of microRNAs in hematopoietic cell lineages > Hierarchical clustering
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Rests on an assumption: RNU6B is a stable endogenous control suitable for normalizing miRNA expression across the tested hematopoietic cell lineages and cell lines.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Across all tested lineages, they had similar expression profiles but miR-142-3p was approximately 10-fold more expressed than miR-142-5p.”
§ Differential expression of microRNAs in hematopoietic cell lineages > Expression levels of miRNAs in hematopoietic cell lineages
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Rests on an assumption: RNU6B is a stable endogenous control suitable for normalizing miRNA expression across the tested hematopoietic cell lineages and cell lines.
In the paper
“Chen et al. (8) cloned approximately 150 miRNAs from murine bone marrow and found that miR-181a, miR-223 and miR-142 were preferentially expressed in hematopoietic tissues.”
§ Differential expression of microRNAs in hematopoietic cell lineages > Abstract
What the sources say
- Not matchedcites [8]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may state two separate claims as one.
- Not matched
In the paper
“As we previously reported, miR-16 and miR-451 are up-regulated and miR-150 down-regulated in late stages of erythropoiesis and therefore may function as positive ⁄ negative regulators in this process (11).”
§ Differential expression of microRNAs in hematopoietic cell lineages > Expression levels of miRNAs in hematopoietic cell lineages
What the sources say
- Not matchedcites [11]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Not matched
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“miR-16 was highly expressed in all examined samples (native hematopoietic cell lineages as well as cell lines including non-hematopoietic cells 293T a HeLa), demonstrating its ubiquitous expression.”
§ Differential expression of microRNAs in hematopoietic cell lineages > Immortalized cell lines
boosted- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Rests on an assumption: The immortalized cell lines used represent the hematopoietic lineages from which they were derived (myeloid, lymphoid, non-hematopoietic).
- Rests on an assumption: RNU6B is a stable endogenous control suitable for normalizing miRNA expression across the tested hematopoietic cell lineages and cell lines.
In the paper
“Moreover, miRNAs have been shown to be more stable in formalin-fixed paraffin-embedded tissues and showed reliable expression levels compared to mRNAs, demonstrating that miRNAs are more robust analytes for the molecular characterization of archival material (17).”
§ Differential expression of microRNAs in hematopoietic cell lineages > Conclusion
What the sources say
- Not matchedcites [17]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
boostedcorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Not matched
None of the sources cited for this claim could be matched to a paper in Crossref, so there is nothing to check it against.
In the paper
“It has been reported that the expression of miRNAs is regulated during hematopoietic differentiation, suggesting miRNA involvement in this process (7-12).”
§ Differential expression of microRNAs in hematopoietic cell lineages > Abstract
What the sources say
- Not matchedcites [7]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Not matchedcites [8]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Not matchedcites [9]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Not matchedcites [10]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Not matchedcites [11]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Not matchedcites [12]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
hedgedcorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may state two separate claims as one.
- Not matched
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“miR-155 was highly expressed only in lymphoblastic cell lines UHKT132 and UHKT133 that suggests its exclusive expression in this lineage.”
§ Differential expression of microRNAs in hematopoietic cell lineages > Immortalized cell lines
hedgedcorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Rests on an assumption: The immortalized cell lines used represent the hematopoietic lineages from which they were derived (myeloid, lymphoid, non-hematopoietic).
- Rests on an assumption: RNU6B is a stable endogenous control suitable for normalizing miRNA expression across the tested hematopoietic cell lineages and cell lines.
In the paper
“Previously, we performed miRNA expression profiling in peripheral blood cells from five donors using Com-biMatrix MicroRNA CustomArrays.”
- Also stated in: § Abstract · plain
“Hierarchical clustering analysis defined miRNA expression clusters in mononuclear cells, granulocytes, platelets and reticulocytes and revealed specifically expressed miRNAs in particular cell lineages (up-regulation of miR-15b in reticulocytes, up-regulation of miR-24 in granulocytes and platelets, up-regulation of miR-30c, miR-223 and miR-142-5p in granulocytes, down-regulation of miR-142-3p, mi”
§ Differential expression of microRNAs in hematopoietic cell lineages > Abstract
What the sources say
- Not matchedcites [12]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plaincorrelationaln = 5- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Also stated in: § Abstract · plain
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“The purity of isolated cell lineages was controlled using FACS and it ranged 96.5-99%.”
§ Differential expression of microRNAs in hematopoietic cell lineages > Expression levels of miRNAs in hematopoietic cell lineages
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“Another study showed that miR-150 was specifically expressed in mature lymphocytes and its premature expression blocked B-cell development (10).”
§ Differential expression of microRNAs in hematopoietic cell lineages > Abstract
What the sources say
- Not matchedcites [10]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
- Not matched
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“The data were normalized to an endogenous control RNU6B (Applied Biosystems).”
§ Differential expression of microRNAs in hematopoietic cell lineages > Quantitative real-time polymerase chain reaction
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The misclassification of these samples may be due to the similarity between platelets and myeloid cells or by possible contamination in platelets.”
§ Differential expression of microRNAs in hematopoietic cell lineages > Hierarchical clustering
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
In the paper
“Moreover, it was shown that miR-155 activity is necessary for antibody production and memory response in B-cells (16).”
§ Differential expression of microRNAs in hematopoietic cell lineages > Immortalized cell lines
What the sources say
- Not matchedcites [16]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
- Not matched
In the paper
“miR-150 is known to be specifically expressed in mature lymphocytes and it is necessary for their differentiation from progenitors (10).”
§ Differential expression of microRNAs in hematopoietic cell lineages > Expression levels of miRNAs in hematopoietic cell lineages
What the sources say
- Not matchedcites [10]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
boosteddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
- Not matched
In the paper
“miR-223 expression was specifically present in all tested myeloid cells and absent in the other cells, reflecting its myeloid specificity (9).”
§ Differential expression of microRNAs in hematopoietic cell lineages > Immortalized cell lines
What the sources say
- Not matchedcites [9]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Rests on an assumption: The immortalized cell lines used represent the hematopoietic lineages from which they were derived (myeloid, lymphoid, non-hematopoietic).
- Rests on an assumption: RNU6B is a stable endogenous control suitable for normalizing miRNA expression across the tested hematopoietic cell lineages and cell lines.
- Not matched
The paper relies on this without support.
The immortalized cell lines used represent the hematopoietic lineages from which they were derived (myeloid, lymphoid, non-hematopoietic).
“K-562 has erythrocytic-megakaryocytic origin, KU812 expresses basophilic features, ML2 and MV4-11 originate in monocytes, and UHKT132 and UHKT133 were established from B-lymphoblasts”
The paper relies on this without support.
RNU6B is a stable endogenous control suitable for normalizing miRNA expression across the tested hematopoietic cell lineages and cell lines.
“The data were normalized to an endogenous control RNU6B (Applied Biosystems).”
“Since these cells are enucleated with a short lifespan, we may speculate that this observation was caused by partial disintegration of RNAs (not seen by routine techniques) resulting in distinct levels of RNU6B transcript.”
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
Each contradiction between two passages listed here was confirmed by an independent check.
Rated minor: it would not touch a result — a value no result rests on, a p-value that stays on the same side of the significance level, or a conflict that is clerical, resolved elsewhere in the paper, or outside its own findings.
In the paper
§ Differential expression of microRNAs in hematopoietic cell lineages > Expression levels of miRNAs in hematopoietic cell lineages
“In reticulocytes, most of the miRNAs were expressed at high level and low expression was observed only for miR-150, miR-155, miR-181a, and miR-342.”
§ Differential expression of microRNAs in hematopoietic cell lineages > Expression levels of miRNAs in hematopoietic cell lineages
“miR-181a showed low expression levels in all tested samples (the lowest level in B-cells) except of reticulocytes and platelets.”
Citations
Cites
Analysis of Relative Gene Expression Data Using Real-Time Quantitative PCR and the 2−ΔΔCT Method
Livak, K. J., & Schmittgen, T. D. (2001) · Methods · doi:10.1006/meth.2001.1262 · Cited by 180,860
Bartel (2004) · doi:10.1016/s0092-8674(04)00045-5 · Cited by 34,714
A microRNA expression signature of human solid tumors defines cancer gene targets
Volinia, S., Calin, G. A., Liu, C.-G., Ambs, S., Cimmino, A., Petrocca, F., Visone, R., Iorio, M., Roldo, C., Ferracin, M., et al. (2006) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0510565103 · Cited by 5,697
Calin, G. A., Dumitru, C. D., Shimizu, M., Bichi, R., Zupo, S., Noch, E., Aldler, H., Rattan, S., Keating, M., Rai, K., et al. (2002) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.242606799 · Cited by 5,111
MicroRNAs Modulate Hematopoietic Lineage Differentiation
Chen, C.-Z., Li, L., Lodish, H. F., & Bartel, D. P. (2004) · Science · doi:10.1126/science.1091903 · Cited by 3,257
Identification of hundreds of conserved and nonconserved human microRNAs
Bentwich, I., Avniel, A., Karov, Y., Aharonov, R., Gilad, S., Barad, O., Barzilai, A., Einat, P., Einav, U., Meiri, E., et al. (2005) · Nature Genetics · doi:10.1038/ng1590 · Cited by 1,841
The Drosophila MicroRNA Mir-14 Suppresses Cell Death and Is Required for Normal Fat Metabolism
Xu, P., Vernooy, S. Y., Guo, M., & Hay, B. A. (2003) · Current Biology · doi:10.1016/s0960-9822(03)00250-1 · Cited by 1,011
A microRNA controlling left/right neuronal asymmetry in Caenorhabditis elegans
Johnston, R. J., & Hobert, O. (2003) · Nature · doi:10.1038/nature02255 · Cited by 760
Zhou, B., Wang, S. Y., Mayr, C., Bartel, D. P., & Lodish, H. F. (2007) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0702409104 · Cited by 609
Li, J., Smyth, P. C., Flavin, R., Cahill, S., Denning, K. M., Aherne, S. T., Guenther, S. M., O’Leary, J. J., & Sheils, O. M. (2007) · BMC Biotechnology · doi:10.1186/1472-6750-7-36 · Cited by 344
Cited by
Sorted by citations
Items 101–200 of 240
Morita, M., Chen, J., Fujino, M., Kitazawa, Y., Sugioka, A., Zhong, L., & Li, X. (2014) · Scientific Reports · doi:10.1038/srep06649 · Cited by 41
Role of microRNAs in HTLV-1 infection and transformation
Ruggero, K., Corradin, A., Zanovello, P., Amadori, A., Bronte, V., Ciminale, V., & D’Agostino, D. M. (2010) · Molecular Aspects of Medicine · doi:10.1016/j.mam.2010.05.001 · Cited by 41
Consequences of genetic variants in miRNA genes
Machowska, M., Galka-Marciniak, P., & Kozlowski, P. (2022) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2022.11.036 · Cited by 40
Asaoka, T., Sotolongo, B., Island, E. R., Tryphonopoulos, P., Selvaggi, G., Moon, J., Tekin, A., Amador, A., Levi, D., García, J., et al. (2011) · American Journal of Transplantation · doi:10.1111/j.1600-6143.2011.03807.x · Cited by 40
Ishida, W., Fukuda, K., Higuchi, T., Kajisako, M., Sakamoto, S., & Fukushima, A. (2010) · Investigative Ophthalmology & Visual Science · doi:10.1167/iovs.10-6115 · Cited by 41
High-Throughput Sequencing of Plasma MicroRNA in Chronic Fatigue Syndrome/Myalgic Encephalomyelitis
Brenu, E., Ashton, K. J., Batovska, J., Staines, D., & Marshall‐Gradisnik, S. (2014) · PLoS ONE · doi:10.1371/journal.pone.0102783 · Cited by 41
Systematic analysis of microRNA fingerprints in thrombocythemic platelets using integrated platforms
Xu, X., Gnatenko, D. V., Ju, J., Hitchcock, I. S., Martin, D. W., Zhu, W., & Bahou, W. F. (2012) · Blood · doi:10.1182/blood-2012-02-411264 · Cited by 39
Zernecke, A. (2012) · Thrombosis and Haemostasis · doi:10.1160/th11-08-0603 · Cited by 38
Katzerke, C., Madan, V., Gerloff, D., Bräuer-Hartmann, D., Hartmann, J.-U., Wurm, A. A., Müller‐Tidow, C., Schnittger, S., Tenen, D. G., Niederwieser, D. W., et al. (2013) · Blood · doi:10.1182/blood-2012-12-472183 · Cited by 38
MicroRNAs Contribute to Induced Pluripotent Stem Cell Somatic Donor Memory
Vitaloni, M., Pulecio, J., Bilić, J., Kuebler, B., Laricchia‐Robbio, L., & Belmonte, J. C. I. (2013) · Journal of Biological Chemistry · doi:10.1074/jbc.m113.538702 · Cited by 37
Stroke-induced microRNAs: The potential therapeutic role for stroke
Wu, P., Zuo, X., & Ji, A. (2012) · Experimental and Therapeutic Medicine · doi:10.3892/etm.2012.452 · Cited by 37
Shimizu, K., Sakurai, F., Tomita, K., Nagamoto, Y., Nakamura, S., Katayama, K., Tachibana, M., Kawabata, K., & Mizuguchi, H. (2014) · Molecular Therapy — Methods & Clinical Development · doi:10.1038/mtm.2014.35 · Cited by 36
MiR‐142‐3p regulates synaptopathy‐driven disease progression in multiple sclerosis
Vito, F. D., Musella, A., Fresegna, D., Rizzo, F. R., Gentile, A., Bassi, M. S., Gilio, L., Buttari, F., Procaccini, C., Colamatteo, A., et al. (2021) · Neuropathology and Applied Neurobiology · doi:10.1111/nan.12765 · Cited by 38
Husted, S., Søkilde, R., Rask, L., Cirera, S., Busk, P. K., Eriksen, J., & Litman, T. (2011) · Molecular Pharmaceutics · doi:10.1021/mp200255d · Cited by 35
Kouhkan, F., Hafizi, M., Mobarra, N., Mohammadi, M. M., Mohammadi, S., Behmanesh, M., Zomorrod, M. S., Alizadeh, S., Lahmy, R., Daliri, M., et al. (2013) · Applied Biochemistry and Biotechnology · doi:10.1007/s12010-013-0633-0 · Cited by 35
Identification of miR-34a-target interactions by a combined network based and experimental approach
Hart, M., Rheinheimer, S., Leidinger, P., Backes, C., Menegatti, J., Fehlmann, T., Grässer, F. A., Keller, A., & Meese, E. U. (2016) · Oncotarget · doi:10.18632/oncotarget.9103 · Cited by 34
miR-142: A Master Regulator in Hematological Malignancies and Therapeutic Opportunities
Huang, W., Paul, D., Călin, G. A., & Bayraktar, R. (2023) · Cells · doi:10.3390/cells13010084 · Cited by 35
Tang, Q.-J., Lei, H., Wu, H., Chen, J., Deng, C., Sheng, W.-S., Fu, Y., Li, X., Lin, Y., Han, Y., et al. (2018) · Acta Pharmacologica Sinica · doi:10.1038/s41401-018-0041-7 · Cited by 33
Wei, L., Gong, X., Martinez, O. M., & Krams, S. M. (2013) · Transplant Immunology · doi:10.1016/j.trim.2013.08.005 · Cited by 32
Haralambieva, I. H., Kennedy, R. B., Simon, W. L., Goergen, K. M., Grill, D. E., Ovsyannikova, I. G., & Poland, G. A. (2018) · PLoS ONE · doi:10.1371/journal.pone.0191812 · Cited by 32
Chakrabarti, M., Garg, S., Ayana, R., Pati, S., & Singh, S. (2020) · Disease Models & Mechanisms · doi:10.1242/dmm.042820 · Cited by 32
Ricci, E. P., Limousin, T., Soto‐Rifo, R., Allison, R. J., Pöyry, T. A. A., Décimo, D., Jackson, R. J., & Ohlmann, T. (2011) · Nucleic Acids Research · doi:10.1093/nar/gkr086 · Cited by 32
Association of miR-34a, miR-130a, miR-150 and miR-155 polymorphisms with the risk of ischemic stroke
Choi, G. H., Ko, K. H., Kim, J. O., Kim, J., Oh, S. H., Han, I. B., Cho, K. G., Kim, O. J., Bae, J., & Kim, N. K. (2016) · International Journal of Molecular Medicine · doi:10.3892/ijmm.2016.2609 · Cited by 32
Zhou, L., Bu, Y., Liang, Y., Zhang, F., Zhang, H., & Li, S. (2016) · Medical Science Monitor · doi:10.12659/msm.897306 · Cited by 31
El‐Daly, S. M., Bayraktar, R., Anfossi, S., & Călin, G. A. (2020) · International Journal of Molecular Sciences · doi:10.3390/ijms21093387 · Cited by 31
Challenges and Opportunities of MicroRNAs in Lymphomas
Tullio, G. D., de Fazio, V., Sgherza, N., Minoia, C., Serratì, S., Merchionne, F., Loseto, G., Iacobazzi, A., Rana, A., Petrillo, P., et al. (2014) · Molecules · doi:10.3390/molecules190914723 · Cited by 30
Role of microRNAs in immunity and organ transplantation
Spiegel, J. C., Lorenzen, J. M., & Thum, T. (2011) · Expert Reviews in Molecular Medicine · doi:10.1017/s1462399411002080 · Cited by 29
Systems Studies Uncover miR-146a as a Target in Leishmania major Infection Model
Nimsarkar, P., Ingale, P., & Singh, S. (2020) · ACS Omega · doi:10.1021/acsomega.0c01502 · Cited by 30
Generation and Validation of miR-142 Knock Out Mice
Shrestha, A., Carraro, G., Agha, E. E., Талгатовна, М. Р., Chao, C., Rizvanov, A. A., Barreto, G., & Bellusci, S. (2015) · PLoS ONE · doi:10.1371/journal.pone.0136913 · Cited by 29
Expression and prognostic significance of hsa-miR-142-3p in acute leukemias
Dahlhaus, M., Roolf, C., Ruck, S., Lange, S., Freund, M., & Junghanß, C. (2013) · Neoplasma · doi:10.4149/neo_2013_056 · Cited by 29
MicroRNAs and Tumor Vasculature Normalization: Impact on Anti-Tumor Immune Response
Matejuk, A., Collet, G., Nadim, M., Grillon, C., & Kiéda, C. (2013) · Archivum Immunologiae et Therapiae Experimentalis · doi:10.1007/s00005-013-0231-4 · Cited by 30
Circulating microRNA-122 as Potential Biomarker for Detection of Testosterone Abuse
Salamin, O., Jaggi, L., Baume, N., Robinson, N., Saugy, M., & Leuenberger, N. (2016) · PLoS ONE · doi:10.1371/journal.pone.0155248 · Cited by 29
Giordano, M., Ciarambino, T., D’Amico, M., Trotta, M. C., Sette, A. D., Marfella, R., Malatino, L., Paolisso, G., & Adinolfi, L. E. (2019) · Journal of Clinical Medicine · doi:10.3390/jcm8020130 · Cited by 28
miR-146a and miR-150 promote the differentiation of CD133+ cells into T-lymphoid lineage
Fallah, P., Arefian, E., Naderi, M., Aghaee‐Bakhtiari, S. H., Atashi, A., Ahmadi, K., Shafiee, A., & Soleimani, M. (2013) · Molecular Biology Reports · doi:10.1007/s11033-013-2567-6 · Cited by 27
Sakurai, F., Narii, N., Tomita, K., Togo, S., Takahashi, K., Machitani, M., Tachibana, M., Ouchi, M., Katagiri, N., Urata, Y., et al. (2016) · Molecular Therapy — Methods & Clinical Development · doi:10.1038/mtm.2016.1 · Cited by 28
Platelet miRNAs and cardiovascular diseases
Eduardo Fuentes, Q., Palomo, I. F., & Alarcón, M. A. (2015) · Life Sciences · doi:10.1016/j.lfs.2015.04.016 · Cited by 29
Platelet-Enriched MicroRNAs and Cardiovascular Homeostasis
Elgheznawy, A., & Fleming, I. (2017) · Antioxidants and Redox Signaling · doi:10.1089/ars.2017.7289 · Cited by 26
Dou, L., Li, J., Zheng, D., Li, Y., Gao, X., Xu, C., Gao, L., Wang, L., & Yu, L. (2013) · Molecular Biology Reports · doi:10.1007/s11033-013-2798-6 · Cited by 26
The roles of miR-146a in the differentiation of Jurkat T-lymphoblasts
Saki, N., Abroun, S., Soleimani, M., Mortazavi, Y., Kaviani, S., & Arefian, E. (2013) · Hematology · doi:10.1179/1607845413y.0000000105 · Cited by 26
MiRNA as biomarker for uveitis - A systematic review of the literature
Počkar, S., Petrovič, M. G., Peterlin, B., & Valentinčič, N. V. (2019) · Gene · doi:10.1016/j.gene.2019.02.004 · Cited by 26
MicroRNAs as Regulators and Biomarkers of Platelet Function and Activity in Coronary Artery Disease
Stojković, S., Nossent, A. Y., Haller, P. M., Jäger, B., Vargas, K. G., Wojta, J., & Huber, K. (2019) · Thrombosis and Haemostasis · doi:10.1055/s-0039-1693702 · Cited by 26
Tay, J. W., JAMES, I. R., Hughes, Q., Tiao, J. Y.-H., & Baker, R. I. (2017) · BMC Research Notes · doi:10.1186/s13104-017-2636-3 · Cited by 25
Insight into microRNAs’ involvement in hematopoiesis: current standing point of findings
Nassiri, S. M., Afshar, N. A., & Almasi, P. (2023) · Stem Cell Research & Therapy · doi:10.1186/s13287-023-03504-3 · Cited by 25
Immunophenotype-related microRNA expression in canine chronic lymphocytic leukemia
Gioia, G., Mortarino, M., Gelain, M. E., Albonico, F., Ciusani, E., Forno, I., Marconato, L., Martini, V., & Comazzi, S. (2011) · Veterinary Immunology and Immunopathology · doi:10.1016/j.vetimm.2011.05.020 · Cited by 25
Standardization of Blood Collection and Processing for the Diagnostic Use of Extracellular Vesicles
Venturella, M., Carpi, F. M., & Zocco, D. (2019) · Current Pathobiology Reports · doi:10.1007/s40139-019-00189-3 · Cited by 24
Dabrowska, M. J., Dybkær, K., Johnsen, H. E., Wang, B., Wabl, M. R., & Pedersen, F. S. (2009) · Journal of Virology · doi:10.1128/jvi.00427-09 · Cited by 23
Clinical Applications of MicroRNAs in Acute Myeloid Leukemia: A Mini-Review
Bhatnagar, B., & Garzon, R. (2021) · Frontiers in Oncology · doi:10.3389/fonc.2021.679022 · Cited by 22
Hodge, L. S., Elsawa, S. F., Grote, D. M., Price-Troska, T. L., Asmann, Y. W., Fonseca, R., Gertz, M. A., Witzig, T. E., Novak, A. J., & Ansell, S. M. (2011) · Blood Cancer Journal · doi:10.1038/bcj.2011.25 · Cited by 24
Soltani, I., Douzi, K., Gharbi, H., Hassine, I. B., Teber, M., Amouri, H., Othmen, H. B. H., Farrah, A., Lakhal, R. B., Abbès, S., et al. (2016) · Hematology · doi:10.1080/10245332.2016.1252020 · Cited by 22
Kouhkan, F., Soleimani, M., Daliri, M., Behmanesh, M., Mobarra, N., Mohammadi, M. M., Mohammad, S., Mokhtari, M., & Lahmy, R. (2013) · Europe PMC (PubMed Central) · Cited by 22
Yu, L., Liao, Q., Zeng, X., Lv, Z., Zheng, H., Zhao, Y. C., Sun, X., & Wu, Z. (2014) · European Journal of Clinical Microbiology & Infectious Diseases · doi:10.1007/s10096-014-2087-x · Cited by 21
Complex role of microRNAs in HTLV-1 infections
Sampey, G. C., Duyne, R. V., Currer, R., Das, R., Narayanan, A., & Kashanchi, F. (2012) · Frontiers in Genetics · doi:10.3389/fgene.2012.00295 · Cited by 24
Gomez, J. C., Dang, H., Kanke, M., Hagan, R. S., Mock, J. R., Kelada, S. N. P., Sethupathy, P., & Doerschuk, C. M. (2017) · Scientific Reports · doi:10.1038/s41598-017-11638-7 · Cited by 21
microRNAs stimulate translation initiation mediated by HCV-like IRESes
Mengardi, C., Limousin, T., Ricci, E. P., Soto‐Rifo, R., Décimo, D., & Ohlmann, T. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkw1345 · Cited by 21
Megakaryocytic differentiation of CD133+ hematopoietic stem cells by down-regulation of microRNA-10a
Zarif, M. N., Soleimani, M., Abolghasemi, H., Amirizade, N., Arefian, E., & Rahimian, A. (2013) · Hematology · doi:10.1179/1607845412y.0000000047 · Cited by 20
Do microRNAs regulate bone marrow stem cell niche physiology?
Laine, S. K., Hentunen, T. A., & Laitala‐Leinonen, T. (2012) · Gene · doi:10.1016/j.gene.2012.01.045 · Cited by 20
Durán-Sanchón, S., Vila-Navarro, E., Marcuello, M., Lozano, J. J., Muñoz, J., Cubiella, J., Diez, M. S., Bujanda, L., Lanas, Á., Jover, R., et al. (2019) · Biomolecules · doi:10.3390/biom10010016 · Cited by 20
MicroRNAs in Kidney Transplantation: Living up to Their Expectations?
van den Akker, E. K., Dor, F. J. M. F., IJzermans, J. N. M., & de Bruin, R. W. F. (2015) · Journal of Transplantation · doi:10.1155/2015/354826 · Cited by 20
Differential Expression Analysis for RNA-Seq Data
Gupta, R., Dewan, I., Bharti, R., & Bhattacharya, A. (2012) · ISRN Bioinformatics · doi:10.5402/2012/817508 · Cited by 19
The expression ratio of miR-17-5p and miR-155 correlates with grading in canine splenic lymphoma
Albonico, F., Mortarino, M., Avallone, G., Gioia, G., Comazzi, S., & Roccabianca, P. (2013) · Veterinary Immunology and Immunopathology · doi:10.1016/j.vetimm.2013.06.018 · Cited by 19
Minhas, G., Mathur, D., Balakrishnan, R., Sharma, N. K., Paanu, V., & Anand, A. (2017) · Frontiers in Neuroscience · doi:10.3389/fnins.2017.00386 · Cited by 20
Hyperglycemia‐related FAS gene and hsa‐let‐7b‐5p as markers of poor outcomes for ischaemic stroke
Chi, N., Chiou, H., Chou, S., Hu, C., Chen, K., Chang, C. ‐., & Hsieh, Y. (2020) · European Journal of Neurology · doi:10.1111/ene.14288 · Cited by 19
Záveský, L., Jandáková, E., Turyna, R., Langmeierová, L., Weinberger, V., MINAR, L., & Kohoutová, M. (2015) · Neoplasma · doi:10.4149/neo_2015_062 · Cited by 19
The Role of miRNAs as Therapeutic Tools in Sickle Cell Disease
Cyrus, C. (2021) · Medicina · doi:10.3390/medicina57101106 · Cited by 18
Age-associated changes in miRNA expression profiles in thymopoiesis
Virts, E. L., & Thoman, M. L. (2010) · Mechanisms of Ageing and Development · doi:10.1016/j.mad.2010.09.008 · Cited by 17
Intra-individual variation of miRNA expression levels in human plasma samples
Wu, J., Cai, H., Xiang, Y., Matthews, C. E., Ye, F., Zheng, W., Cai, Q., & Shu, X. (2018) · Biomarkers · doi:10.1080/1354750x.2018.1427794 · Cited by 17
Domenico, T. D., Joelsons, G., Montenegro, R. M., & Manfro, R. C. (2017) · Brazilian Journal of Medical and Biological Research · doi:10.1590/1414-431x20175533 · Cited by 17
Hanif, Q., Farooq, M., Amin, I. U., Mansoor, S., Zhang, Y., & Khan, Q. M. (2018) · PLoS ONE · doi:10.1371/journal.pone.0206154 · Cited by 17
Molecular and Genetic Bases of Myeloproliferative Disorders: Questions and Perspectives
Plo, I., & Vainchenker, W. (2009) · Clinical Lymphoma & Myeloma · doi:10.3816/clm.2009.s.032 · Cited by 17
MicroRNA expression profiles in avian haemopoietic cells
Yao, Y., Charlesworth, J., Nair, V., & Watson, M. (2013) · Frontiers in Genetics · doi:10.3389/fgene.2013.00153 · Cited by 16
MicroRNA-181a* Targets Nanog in a Subpopulation of CD34+ Cells Isolated From Peripheral Blood
Mintz, P. J., Sætrom, P., Reebye, V., Lundbæk, M. B., Lao, K., Rossi, J. J., Gaensler, K. M. L., Kasahara, N., Nicholls, J. P., Jensen, S. L., et al. (2012) · Molecular Therapy — Nucleic Acids · doi:10.1038/mtna.2012.29 · Cited by 16
Erythrocyte miRNA regulators and malarial pathophysiology
Prabhu, S. R., Ware, A. P., & Saadi, A. V. (2021) · Infection Genetics and Evolution · doi:10.1016/j.meegid.2021.105000 · Cited by 17
Pirro, S., Matić, I., Colizzi, V., & Galgani, A. (2021) · Scientific Reports · doi:10.1038/s41598-021-88617-6 · Cited by 15
MicroRNA signature is indicative of long term prognosis in diffuse large B-cell lymphoma
Shepshelovich, D., Ram, R., Uziel, O., Kushnir, M., Lithwick‐Yanai, G., Hoshen, M., Feinmesser, M., Bairey, O., & Lahav, M. (2015) · Leukemia Research · doi:10.1016/j.leukres.2015.03.018 · Cited by 15
Circulating and urinary microRNAs as possible biomarkers in kidney transplantation
Janszky, N., & Süsal, C. (2017) · Transplantation Reviews · doi:10.1016/j.trre.2017.12.001 · Cited by 14
MicroRNA signatures and Foxp3+ cell count correlate with relapse occurrence in follicular lymphoma
Malpeli, G., Barbi, S., Greco, C., Zupo, S., Bertolaso, A., Scupoli, M. T., Krampera, M., Kamga, P. T., Croce, C. M., Scarpa, A., et al. (2018) · Oncotarget · doi:10.18632/oncotarget.24987 · Cited by 14
Lim, J., Byun, J., Guk, K., Hwang, S. G., Bae, P. K., Jung, J., Kang, T., & Lim, E. (2019) · ACS Omega · doi:10.1021/acsomega.9b01790 · Cited by 14
Krejčík, Z., Beličková, M., Hruštincová, A., Kléma, J., Zemanová, Z., Michalova, K., Čermák, J., Jonasova, A. T., & Merkerová, M. D. (2015) · Cancer Genetics · doi:10.1016/j.cancergen.2015.03.003 · Cited by 14
Voelz, C., Ebrahimy, N., Zhao, W., Habib, P., Zendedel, A., Pufe, T., Beyer, C., & Slowik, A. (2021) · International Journal of Molecular Sciences · doi:10.3390/ijms23010161 · Cited by 13
Tumor‐targeted fluorescence labeling systems for cancer diagnosis and treatment
Tazawa, H., Shigeyasu, K., Noma, K., Kagawa, S., Sakurai, F., Mizuguchi, H., Kobayashi, H., Imamura, T., & Fujiwara, T. (2022) · Cancer Science · doi:10.1111/cas.15369 · Cited by 13
Guha, D., Mancini, A. E., Sparks, J., & Ayyavoo, V. (2016) · Journal of Cellular Biochemistry · doi:10.1002/jcb.25489 · Cited by 13
Identification of miRNAs from stem cell derived microparticles in umbilical cord blood
Xagorari, A., Gerousi, M., Sioga, A., Bougiouklis, D., Argiriou, A., Anagnostopoulos, Α., & Sotiropoulos, D. (2019) · Experimental Hematology · doi:10.1016/j.exphem.2019.11.001 · Cited by 12
Identification of a New Target of miR-16, Vacuolar Protein Sorting 4a
Adhikari, N., Guan, W., Capaldo, B. J., Mackey, A. J., Carlson, M., Ramakrishnan, S., Walek, D., Gupta, M., Mitchell, A. J., Eckman, P., et al. (2014) · PLoS ONE · doi:10.1371/journal.pone.0101509 · Cited by 12
Genetic systems for a new approach to risk of progression of diabetic retinopathy
Pinazo-Duran, M. D., Zanón‐Moreno, V., Lleó-Pérez, A., García‐Medina, J. J., Galbis-Estrada, C., Roig-Revert, M. J., Marco-Ramírez, C., Gálvez, M. I. L., Dolz‐Marco, R., Duarte, L., et al. (2016) · Archivos de la Sociedad Española de Oftalmología (English Edition) · doi:10.1016/j.oftale.2016.01.016 · Cited by 12
MicroRNAs in Leukemias: Emerging Diagnostic Tools and Therapeutic Targets
Mian, Y. A., & Zeleznik‐Le, N. J. (2010) · Current Drug Targets · doi:10.2174/138945010791320872 · Cited by 12
Integrated micro/messenger RNA regulatory networks in essential thrombocytosis
Zhao, L. H., Wu, S., Huang, E., Gnatenko, D. V., Bahou, W. F., & Zhu, W. (2018) · PLoS ONE · doi:10.1371/journal.pone.0191932 · Cited by 11
Chen, Q. Y., Liu, N., Ma, J., Fang, Y., Cao, Y., Li, H., & Liu, Y. C. (2015) · Genetics and Molecular Research · doi:10.4238/2015.march.30.17 · Cited by 10
A Sensitive Switch for Visualizing Natural Gene Silencing in Single Cells
Haynes, K. A., Ceroni, F., Flicker, D., Younger, A. K. D., & Silver, P. A. (2012) · ACS Synthetic Biology · doi:10.1021/sb3000035 · Cited by 9
Sistemas genéticos para un nuevo abordaje del riesgo de progresión de la retinopatía diabética
Pinazo-Duran, M. D., Zanón‐Moreno, V., Lleó-Pérez, A., García‐Medina, J. J., Galbis-Estrada, C., Roig-Revert, M. J., Marco-Ramírez, C., Gálvez, M. I. L., Dolz‐Marco, R., Duarte, L., et al. (2016) · Archivos de la Sociedad Española de Oftalmología · doi:10.1016/j.oftal.2016.01.016 · Cited by 9
Quantitative RT-PCR for MicroRNAs in Biofluids
Thorsen, M. K., Blöndal, T., & Mouritzen, P. (2017) · Methods in molecular biology · doi:10.1007/978-1-4939-7172-5_21 · Cited by 9
Nimker, S., Sharma, K., Saraswathy, R., & Chandna, S. (2019) · Health Physics · doi:10.1097/hp.0000000000000975 · Cited by 9
MicroRNAs in erythropoiesis and red blood cell disorders
Mohammadi-Asl, J., Ramezani, A., Norozi, F., Malehi, A. S., Asnafi, A. A., Far, M. A. J., Mousavi, S. H., & Saki, N. (2015) · Frontiers in Biology · doi:10.1007/s11515-015-1365-z · Cited by 9
MicroRNAs in Platelet Production and Activation
Edelstein, L. C., Nagalla, S., & Bray, P. F. (2013) · Wiley eBooks · doi:10.1002/9781118300312.ch7 · Cited by 9
miR-181c regulates MCL1 and cell survival in GATA2 deficient cells
Wang, W., Chen, R., Droll, S. H., Barber, E., Saleh, L. M., Corrigan-Cummins, M., Trick, M., Anastas, V., Hawk, N. V., Zhao, Z., et al. (2021) · Journal of Leukocyte Biology · doi:10.1002/jlb.2a1220-824r · Cited by 8
The chicken miR-150 targets the avian orthologue of the functional zebrafish MYB 3'UTR target site
Guillon‐Munos, A., Dambrine, G., Richerioux, N., Coupeau, D., Muylkens, B., & Rasschaert, D. (2010) · BMC Molecular Biology · doi:10.1186/1471-2199-11-67 · Cited by 8
Platelet systems biology using integrated genetic and proteomic platforms
Bahou, W. F. (2012) · Thrombosis Research · doi:10.1016/s0049-3848(12)70014-2 · Cited by 7
The MicroRNA Regulatory Network in Normal- and HTLV-1-Transformed T Cells
D’Agostino, D. M., Zanovello, P., Watanabe, T., & Ciminale, V. (2012) · Advances in cancer research · doi:10.1016/b978-0-12-394280-7.00002-6 · Cited by 7
Exosomal microRNA following severe trauma: Role in bone marrow dysfunction
Munley, J. A., Willis, M. L., Gillies, G. S., Kannan, K. B., Polcz, V. E., Balch, J. A., Barrios, E. L., Wallet, S. M., Bible, L. E., Efron, P. A., et al. (2023) · The Journal of Trauma: Injury, Infection, and Critical Care · doi:10.1097/ta.0000000000004225 · Cited by 5
Provost, P. (2012) · Elsevier eBooks · doi:10.1016/b978-0-12-387837-3.00005-5 · Cited by 5
The Essential Role of Epigenetic Modifications in Neurodegenerative Diseases with Dyskinesia
Qi, Z., Li, J., Li, M., Du, X., Zhang, L., Wang, S., Xu, B., Liu, W., Xu, Z., & Deng, Y. L. (2021) · Cellular and Molecular Neurobiology · doi:10.1007/s10571-021-01133-z · Cited by 5
Metadata
- Authors
- Merkerova, M., Belickova, M., & Bruchova, H.
- Venue
- European Journal of Haematology
- Publisher
- Wiley
- Published
- 2008-09-15
- Volume
- 81
- Issue
- 4
- Pages
- 304-310
- ISSN
- 0902-4441 (ISSN-L)
- 1600-0609
- OpenAlex
- W2077066570
- Cited by
- 240
- References
- 17
- Citations by year
- 2026: 3 · 2025: 2 · 2024: 4 · 2023: 7 · 2022: 6 · 2021: 10 · 2020: 9 · 2019: 13 · 2018: 10 · 2017: 8 · 2016: 19 · 2015: 14 · 2014: 19 · 2013: 29 · 2012: 25
- FWCI
- 6.92
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- European Journal Of Haematology (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Ministerstvo Zdravotnictví Ceské Republiky
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › MicroRNA in disease regulation
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene expression and cancer classification
- Life Sciences › Agricultural and Biological Sciences › Plant Science › Plant Molecular Biology Research
- Keywords
- microRNA, hematopoietic lineage, miR-150, miR-155, miR-142-3p, miR-142-5p, miR-223, miR-451, miR-16, miR-15b, miR-15b-5p, miR-106b, miR-24, miR-30c, miR-342, miR-181, miR-30c-5p, reticulocytes, platelets, granulocytes, monocytes, B cells, T cells, hematopoietic cell lines, gene expression profiling
- MeSH terms
- Blood Platelets, Cell Differentiation, Gene Expression Regulation, HeLa Cells, Humans, Leukocytes, Reticulocytes, K562 Cells, Oligonucleotide Array Sequence Analysis, Gene Expression Profiling, MicroRNAs, Granulocyte Precursor Cells, Lymphoid Progenitor Cells
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
A language model drew the claims from the paper on 2026-11-10, under version 3 of the claim definition (model deepseek-v4.1-flash, prompt extract-v3).
A second model labelled each claim on 2026-11-10 (model jev-1.13-20260917, definition revision gold-guideline-v0.2).
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
