Cytotoxicity of nanoparticles in normal and cancer cell lines¶

Original Data¶

Title: Cytotoxicity of nanoparticles in normal and cancer cell lines
Description: The dataset contains information on the toxicity of inorganic nanoparticles on various normal and cancer cell lines.
Total number of records: 5476
Number of features (columns): 34
Data type: Mixed
Application: Nanomaterials
Automatic validation: Yes

Data Scheme¶

Cytotoxicity Dataset – Column Descriptions¶

Column Name	Description
sn	Index of the sample (serial number).
material	Composition of the nanoparticle/material tested (e.g., SiO₂, Ag).
shape	Physical shape of the particle (e.g., Sphere, Rod).
coat_functional_group	Surface coating or functionalization (e.g., CTAB, PEG).
synthesis_method	Synthesis method (e.g., Precipitation, Commercial).
surface_charge	Reported surface charge (e.g., Negative, Positive).
size_in_medium_nm	Hydrodynamic size in biological medium (nm).
zeta_in_medium_mv	Zeta potential in medium (mV; blank if not measured).
potential_mv	Surface charge in solution (mV).
no_of_cells_cells_well	Cell density per well in the assay.
cell_type	Specific cell line name (e.g., PC12, A549).
human_animal	Origin of cells (A = Animal, H = Human).
cell_source	Species/organism (e.g., Rat, Human).
cell_tissue	Tissue origin of the cell line (e.g., Adrenal Gland, Lung).
cell_morphology	Cell shape (e.g., Irregular, Epithelial).
cell_age	Developmental stage of cells (e.g., Adult, Embryonic).
time_hr	Exposure duration in hours.
concentration	Tested concentration of the material (e.g., µg/mL).
test	Cytotoxicity assay type (e.g., MTT, LDH).
test_indicator	Reagent measured (e.g., TetrazoliumSalt for MTT).
viability_%	Cell viability percentage relative to control.
doi	Digital Object Identifier (DOI) of the article.
article_list	Identifier for the article in the dataset.
core_nm	Primary particle size (nm).
hydrodynamic_nm	Size in solution including coatings (nm).
journal_name	Name of the publishing journal.
publisher	Publisher of the article.
year	Year of publication.
title	Title of the article from which data was extracted.
journal_is_oa	Whether the journal is Open Access (TRUE/FALSE).
is_oa	Whether the specific article is Open Access (TRUE/FALSE).
oa_status	Open Access status (e.g., hybrid, gold, closed).
pdf	Filename of the corresponding PDF in the PDF archive.
access	Access status (1 = open, 0 = closed).

Metadata¶

All metadata is included in the main table and also used for source validation.

Column Name	Description
journal_name	Name of the publishing journal.
publisher	Publisher of the article.
year	Year of publication.
title	Title of the article.
journal_is_oa	Whether the journal is Open Access (TRUE/FALSE).
is_oa	Whether the specific article is Open Access (TRUE/FALSE).
oa_status	Open Access status at article level (e.g., hybrid, gold, closed).
pdf	File name of the article PDF in archive.
access	Access code (1 = open access, 0 = closed access).

Key Notes

human/animal: "A" for Animal, "H" for Human
viability (%): Values >100% may indicate proliferation stimulation
Blanks: Missing values (e.g., zeta in medium) imply unreported data

Dataset Description¶

The dataset contains experimental data on the effects of inorganic nanoparticles on human and animal cells. The main focus is on the assessment of cytotoxicity using standard tests (e.g., MTT) to understand how different nanoparticle characteristics (shape, size, charge, coating) affect cell survival.

Each entry includes:

Nanoparticle characteristics (material, shape, size, charge, etc.)
Cell line information (source, tissue, morphology, etc.)
Experimental conditions (exposure time, concentration, etc.)
Results of cell survival tests
Publication metadata (DOI, journal, year, etc.)

The aim of the dataset is to contribute to the investigation of the patterns between nanoparticle parameters and their cytotoxic effects.

Validation Results¶

In the Cytotox dataset, a total of 1,351 corrections were identified, nearly all of which (1,350) were pattern-based. These were mostly found in the cell_type, test, and test_indicator columns. The predominant problems involved terminology inconsistencies, abbreviation mismatches, and stylistic variation across sources. The high pattern consistency enabled efficient rule-based correction.