Evidence map›Paper›PMID 33918901›Full record

ReviewInternational journal of molecular sciences2021

RNA Flow Cytometry for the Study of T Cell Metabolism.

Alessandra Rossi, Ilenia Pacella, Silvia Piconese

Open access · goldAbstract readReview
In one paragraph

Review in International journal of molecular sciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.7field-weighted citation impact, top 35% 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

4 citing papers in PubMed, 9 citations in OpenAlex.

  1. Review
  2. Review
  3. Flow Cytometry and Its Applications to Molecular Biology and Diagnosis 2.0.International journal of molecular sciences · 2023
    Article
  4. 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

3 authors at 2 institutions in 1 country.

Alessandra RossiDepartment of Internal Clinical Sciences, Anaesthesiology and Cardiovascular Sciences, Sapienza University of Rome, 00161 Roma, Italy.ORCID 0000-0001-9042-3549
Ilenia PacellaDepartment of Internal Clinical Sciences, Anaesthesiology and Cardiovascular Sciences, Sapienza University of Rome, 00161 Roma, Italy.
Silvia PiconeseDepartment of Internal Clinical Sciences, Anaesthesiology and Cardiovascular Sciences, Sapienza University of Rome, 00161 Roma, Italy.ORCID 0000-0002-9685-5227
Sapienza University of Rome · ITIstituto Pasteur · IT

Funding

Associazione Italiana per la Ricerca sul Cancro IG-19784Italian Ministry of University and Research PRIN-2017K7FSYB
6 · The paper itself

Abstract

T cells undergo activation and differentiation programs along a continuum of states that can be tracked through flow cytometry using a combination of surface and intracellular markers. Such dynamic behavior is the result of transcriptional and post-transcriptional events, initiated and sustained by the activation of specific transcription factors and by epigenetic remodeling. These signaling pathways are tightly integrated with metabolic routes in a bidirectional manner: on the one hand, T cell receptors and costimulatory molecules activate metabolic reprogramming; on the other hand, metabolites modify T cell transcriptional programs and functions. Flow cytometry represents an invaluable tool to analyze the integration of phenotypical, functional, metabolic and transcriptional features, at the single cell level in heterogeneous T cell populations, and from complex microenvironments, with potential clinical application in monitoring the efficacy of cancer immunotherapy. Here, we review the most recent advances in flow cytometry-based analysis of gene expression, in combination with indicators of mitochondrial activity, with the aim of revealing and characterizing major metabolic pathways in T cells.

Indexed as

Energy MetabolismFlow CytometryAnimalsBiomarkersGene ExpressionHumansMitochondriaRNAT-LymphocytesT-Lymphocyte SubsetsBiomarkersRNAflow cytometrymetabolismmitochondriaRNAT cells

Identifiers

PMID33918901
PMCPMC8069477
OpenAlexW3154792632

What Socratic holds

Textmetadata
LicenceCC BY
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 Socratic graph.