Evidence map›Paper›PMID 24427535›Full record

ArticleInterface focus2013

The immune system as a biomonitor: explorations in innate and adaptive immunity.

Niclas Thomas, James Heather, Gabriel Pollara, Nandi Simpson, Theres Matjeka, John Shawe-Taylor, Mahdad Noursadeghi, Benjamin Chain

Abstract read
In one paragraph

Article in Interface focus, 2013. 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
–field-weighted citation impact
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.

  1. Article
  2. 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

8 authors.

Niclas ThomasCoMPLEX, University College London, Gower Street, London WC1E 6BT, UK.
James HeatherDivision of Infection and Immunity, University College London, Gower Street, London WC1E 6BT, UK.
Gabriel PollaraDivision of Infection and Immunity, University College London, Gower Street, London WC1E 6BT, UK.
Nandi SimpsonDivision of Infection and Immunity, University College London, Gower Street, London WC1E 6BT, UK.
Theres MatjekaDivision of Infection and Immunity, University College London, Gower Street, London WC1E 6BT, UK.
John Shawe-TaylorDepartment of Computer Science, University College London, Gower Street, London WC1E 6BT, UK.
Mahdad NoursadeghiDivision of Infection and Immunity, University College London, Gower Street, London WC1E 6BT, UK.
Benjamin ChainDivision of Infection and Immunity, University College London, Gower Street, London WC1E 6BT, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The human immune system has a highly complex, multi-layered structure which has evolved to detect and respond to changes in the internal microenvironment of the body. Recognition occurs at the molecular or submolecular scale, via classical reversible receptor-ligand interactions, and can lead to a response with great sensitivity and speed. Remarkably, recognition is coupled to memory, such that responses are modulated by events which occurred years or even decades before. Although the immune system in general responds differently and more vigorously to stimuli entering the body from the outside (e.g. infections), this is an emergent property of the system: many of the recognition molecules themselves have no inherent bias towards external stimuli (non-self) but also bind targets found within the body (self). It is quite clear that the immune response registers pathophysiological changes in general. Cancer, wounding and chronic tissue injury are some obvious examples. Against this background, the immune system 'state' tracks the internal processes of the body, and is likely to encode information regarding both current and past disease processes. Moreover, the distributed nature of most immune responses (e.g. typically involving lymphoid tissue, non-lymphoid tissue, bone marrow, blood, extracellular interstitial spaces, etc.) means that many of the changes associated with immune responses are manifested systemically, and specifically can be detected in blood. This provides a very convenient route to sampling immune cells. We consider two different and complementary ways of querying the human immune 'state' using high-dimensional genomic screening methodologies, and discuss the potentials of these approaches and some of the technological and computational challenges to be overcome.

Indexed as

microarraynext generation sequencingT-cell repertoiretranscriptomics

Identifiers

PMID24427535
PMCPMC3638490

What OpenQuestion holds

Textmetadata
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.