Evidence map›Paper›PMID 29458078›Full record

ArticleJournal of immunological methods2018

Isolation of intact RNA from murine CD4

Shajo Kunnath-Velayudhan, Steven A Porcelli

Abstract read
In one paragraph

Article in Journal of immunological methods, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.4field-weighted citation impact, top 42% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 5 citations in OpenAlex.

  1. Granzyme KScience translational medicine · 2022
    Article
  2. SKA-31, an activator of CaPharmacological research · 2020
    Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors at 1 institution in 1 country.

Shajo Kunnath-VelayudhanDepartment of Microbiology and Immunology, Albert Einstein College of Medicine, Bronx, New York 10461, USA.
Steven A PorcelliDepartment of Microbiology and Immunology, Albert Einstein College of Medicine, Bronx, New York 10461, USA. Electronic address: steven.porcelli@einstein.yu.edu.
Albert Einstein College of Medicine · US

Funding

WORD PROCESSORP30CA013330 · NCI · YESHIVA UNIVERSITY · PI STEVEN C. ALMO · 1985 to 2026
$111.2M
Precision Targeting of CD1-Restricted iNKT Cells for Cancer ImmunotherapyR01AI045889 · NIAID · YESHIVA UNIVERSITY · PI Steven A Porcelli · 1999 to 2026
$9.3M
NCI NIH HHS P30 CA013330NIAID NIH HHS R01 AI045889
6 · The paper itself

Abstract

Intracellular cytokine staining (ICS) is a powerful method for identifying functionally distinct lymphocyte subsets, and for isolating these by fluorescence activated cell sorting (FACS). Although transcriptomic analysis of cells sorted on the basis of ICS has many potential applications, this is rarely performed because of the difficulty in isolating intact RNA from cells processed using standard fixation and permeabilization buffers for ICS. To address this issue, we compared three buffers shown previously to preserve RNA in nonhematopoietic cells subjected to intracellular staining for their effects on RNA isolated from T lymphocytes processed for ICS. Our results showed that buffers containing the recombinant ribonuclease inhibitor RNasin or high molar concentrations of salt yielded intact RNA from fixed and permeabilized T cells. As proof of principle, we successfully used the buffer containing RNasin to isolate intact RNA from CD4

Indexed as

Cell SeparationFlow CytometryFluorescenceAnimalsCD4-Positive T-LymphocytesCytokinesFemaleMiceMice, Inbred C57BLRNASpleenCytokinesRNAFACSIntracellular cytokine stainingRNA isolationT cellsTranscriptomics

Identifiers

PMID29458078
PMCPMC5878738
OpenAlexW2789242880

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.