Data · dataset · 2026
Processed serum and BALF metabolomics data for ARDS
Listed in ScienceDB
This dataset comprises processed metabolomics data generated using untargeted LC–MS analysis from serum and bronchoalveolar lavage fluid (BALF) samples collected from patients with pulmonary infection–induced acute respiratory distress syndrome (ARDS) and non-ARDS controls.
Description
Patient samples were collected between June 2023 and March 2024, during hospitalization and at a single time point per subject, representing a cross-sectional study design without longitudinal follow-up or geospatial information.The dataset is provided in Microsoft Excel (.xlsx) format and consists of multiple data sheets.
In each data table, rows correspond to annotated metabolite features, while columns represent individual biological samples. Sample grouping and naming conventions are described in the accompanying README file. All values represent normalized metabolite peak areas (arbitrary units, a.u.), reflecting relative abundances rather than absolute concentrations.In the original metabolomics data, some metabolite features were below the detection limit in individual samples and therefore contained missing values.
Read the rest (2 more)
During data processing, missing values were imputed using half of the minimum non-zero value for each metabolite across the dataset, resulting in complete data matrices for downstream statistical analyses. As untargeted metabolomics data, the measurements may be influenced by sample preparation, instrumental drift, and signal noise; however, analytical stability was monitored using quality control samples, and normalization procedures were applied to reduce systematic variability.This dataset does not include raw LC–MS files and is intended to support transparency, data reuse, and reproducibility of downstream statistical, differential metabolite, and pathway analyses.
The data files are stored in a standard Excel format and can be accessed and analyzed using commonly available software such as Microsoft Excel, R, or Python.
Links
Where it is published
- DOI doi.org/10.57760/sciencedb.35991 ↗
DOI / persistent id · from scidb cn
Catalogue records · 1
- OAI-PMH record scidb.cn/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=10.57760%2… ↗
metadata API · from scidb cn
Topics
- From keywords
- Earth & Environmental Science · Engineering · Humanities · Life Sciences · Social Science
- Inferred from text
- Bioinformatics and computational biology 73% · Longitudinal study 65% · Tabular 65%
Provenance · 1 source records, 13 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| ScienceDB | 10.57760/sciencedb.35991 | 8 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].anzsrc:group:3102 | enrichment · scidb cn | taxonomy-embedding@1.0.0 | title+keywords+description (73%) |
| concepts[field].local:field:earth-environmental | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:engineering | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:humanities | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:life-sciences | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:social-science | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[method].local:method:longitudinal-study | enrichment · scidb cn | keyword-concept-rules@1.0.0 | title+description (65%) |
| concepts[modality].local:modality:tabular | enrichment · scidb cn | keyword-concept-rules@1.0.0 | title+description (65%) |
| description | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/description |
| license | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/rights |
| publication_date | source · scidb cn | connector:scidb_cn@1.0.0 | |
| title | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/title |