Evidence map›Paper›PMID 34663591›Full record

ArticleJournal of immunology (Baltimore, Md. : 1950)2021

SysInflam HuDB, a Web Resource for Mining Human Blood Cells Transcriptomic Data Associated with Systemic Inflammatory Responses to Sepsis.

Mohammed Toufiq, Susie Shih Yin Huang, Sabri Boughorbel, Mohamed Alfaki, Darawan Rinchai, Luis R Saraiva, Damien Chaussabel, Mathieu Garand

Abstract read
In one paragraph

Article in Journal of immunology (Baltimore, Md. : 1950), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. GIDISdb: a gene expression database for exploring human immune responses in infectious diseases.Database : the journal of biological databases and curation · 2026
    Article
  2. Article
  3. Abundance ofFrontiers in immunology · 2023
    Article
  4. Article
  5. 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.

Mohammed ToufiqSidra Medicine, Doha, Qatar.ORCID 0000-0002-6368-6746
Susie Shih Yin HuangSidra Medicine, Doha, Qatar.ORCID 0000-0001-9727-3213
Sabri BoughorbelSidra Medicine, Doha, Qatar.ORCID 0000-0003-2734-3356
Mohamed AlfakiSidra Medicine, Doha, Qatar.
Darawan RinchaiSidra Medicine, Doha, Qatar.ORCID 0000-0001-8851-7730
Luis R SaraivaSidra Medicine, Doha, Qatar.ORCID 0000-0003-4079-0396
Damien ChaussabelSidra Medicine, Doha, Qatar.
Mathieu GarandSidra Medicine, Doha, Qatar; mathieu.garand@gmail.com.ORCID 0000-0003-4243-853X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Sepsis develops after a dysregulated host inflammatory response to a systemic infection. Identification of sepsis biomarkers has been challenging because of the multifactorial causes of disease susceptibility and progression. Public transcriptomic data are a valuable resource for mechanistic discoveries and cross-studies concordance of heterogeneous diseases. Nonetheless, the approach requires structured methodologies and effective visualization tools for meaningful data interpretation. Currently, no such database exists for sepsis or systemic inflammatory diseases in human. Hence we curated SysInflam HuDB (http://sepsis.gxbsidra.org/dm3/geneBrowser/list), a unique collection of human blood transcriptomic datasets associated with systemic inflammatory responses to sepsis. The transcriptome collection and the associated clinical metadata are integrated onto a user-friendly and Web-based interface that allows the simultaneous exploration, visualization, and interpretation of multiple datasets stemming from different study designs. To date, the collection encompasses 62 datasets and 5719 individual profiles. Concordance of gene expression changes with the associated literature was assessed, and additional analyses are presented to showcase database utility. Combined with custom data visualization at the group and individual levels, SysInflam HuDB facilitates the identification of specific human blood gene signatures in response to infection (e.g., patients with sepsis versus healthy control subjects) and the delineation of major genetic drivers associated with inflammation onset and progression under various conditions.

Indexed as

Blood CellsDatabases as TopicData MiningDatasets as TopicGene Expression ProfilingHumansInflammationInternetSepsisSoftwareTranscriptomeUser-Computer Interface

Identifiers

PMID34663591
PMCPMC8525868

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.