{"entity": "researcher", "timestamp": "2026-08-20T20:43:16.808Z", "family": "Breitholtz", "given": "Magnus", "initials": "M", "orcid": "0000-0002-4984-8323", "affiliations": ["Department of Environmental Science, Stockholm University, Svante Arrhenius v\u00e4g 8, 106 91 Stockholm, Sweden."], "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/researcher/1e2f3c4f62444d3c80f6bd1222c44ca5.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/researcher/1e2f3c4f62444d3c80f6bd1222c44ca5"}}, "publications": [{"entity": "publication", "iuid": "79f801e968034b6eaaabca2c416073c8", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/79f801e968034b6eaaabca2c416073c8.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/79f801e968034b6eaaabca2c416073c8"}}, "title": "An In Vivo Fluorescence Image Analysis Tool for Esterase Activity Quantification in Daphnia: Using Calcein AM in Ecotoxicological Studies.", "authors": [{"family": "Perez-Li\u00f1an", "given": "Amira", "initials": "A", "orcid": "0009-0000-1027-5938", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/0593a3f8eee14f168928a6e6d8773ddc.json"}}, {"family": "Abele", "given": "Cedric", "initials": "C", "orcid": "0009-0003-0101-1510", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/16de7d9fc2e74894a5d8518a52c52ac5.json"}}, {"family": "Pierozan", "given": "Paula", "initials": "P"}, {"family": "Breitholtz", "given": "Magnus", "initials": "M", "orcid": "0000-0002-4984-8323", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/1e2f3c4f62444d3c80f6bd1222c44ca5.json"}}, {"family": "Karlsson", "given": "Oskar", "initials": "O", "orcid": "0000-0001-8009-0015", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/9e8bc211d3eb432a877e1f32671e6aa8.json"}}], "type": "journal article", "published": "2025-09-02", "journal": {"title": "Environ. Sci. Technol.", "issn": "1520-5851", "volume": "59", "issue": "34", "pages": "18023-18032", "issn-l": "0013-936X"}, "abstract": "There is an increasing need for new approach methodologies (NAMs) to generate relevant ecotoxicological data. This study demonstrates the strengths of calcein AM, a highly sensitive fluorescent stain for esterase activity, in an automated image-based multiwell plate assay for detecting sublethal effects in Daphnia magna. Sample processing and feeding conditions were optimized to ensure a uniform dye distribution. The protocol was validated using two esterase inhibitors, triphenyl phosphate and netilmicin sulfate, and subsequently applied to test the environmental contaminants methoxychlor, lindane, tributyltin chloride, pentachlorophenol, diuron, and ethofumesate. The test organisms were imaged in vivo using automated confocal microscopy, and fluorescence intensity was quantified to generate concentration-response curves. The effects of triphenyl phosphate and netilmicin sulfate were observed at concentrations 3-fold and 6-fold lower, respectively, than in the OECD 202 immobilization test. All tested contaminants also inhibited esterase activity, with concentrations resulting in no esterase activity at 48 h, correlating with mortality observed at 48 h. This method provides a new sensitive fluorescent tool for detecting sublethal chemical effects in D. magna, with the added advantage of visualizing intracellular processes in vivo.", "doi": "10.1021/acs.est.5c03309", "pmid": "40841535", "labels": [], "xrefs": [{"db": "pmc", "key": "PMC12409896"}], "notes": [], "created": "2026-08-20T08:10:00.598Z", "modified": "2026-08-20T08:10:00.716Z"}, {"entity": "publication", "iuid": "ef521b9604144432b86f7338d1a4bba8", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/ef521b9604144432b86f7338d1a4bba8.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/ef521b9604144432b86f7338d1a4bba8"}}, "title": "Automated Image-Based Fluorescence Screening of Mitochondrial Membrane Potential in Daphnia magna: An Advanced Ecotoxicological Testing Tool.", "authors": [{"family": "Abele", "given": "Cedric", "initials": "C", "orcid": "0009-0003-0101-1510", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/16de7d9fc2e74894a5d8518a52c52ac5.json"}}, {"family": "Perez", "given": "Amira", "initials": "A"}, {"family": "H\u00f6glund", "given": "Andrey", "initials": "A", "orcid": "0000-0002-1130-374X", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/1d1b03b4ddcf4b618f8709fbcd29ebb2.json"}}, {"family": "Pierozan", "given": "Paula", "initials": "P"}, {"family": "Breitholtz", "given": "Magnus", "initials": "M", "orcid": "0000-0002-4984-8323", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/1e2f3c4f62444d3c80f6bd1222c44ca5.json"}}, {"family": "Karlsson", "given": "Oskar", "initials": "O", "orcid": "0000-0001-8009-0015", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/9e8bc211d3eb432a877e1f32671e6aa8.json"}}], "type": "journal article", "published": "2024-09-10", "journal": {"title": "Environ. Sci. Technol.", "issn": "1520-5851", "volume": "58", "issue": "36", "pages": "15926-15937", "issn-l": "0013-936X"}, "abstract": "This study demonstrated the strengths of in vivo molecular staining coupled with automated imaging analysis in Daphnia magna. A multiwell plate protocol was developed to assess mitochondrial membrane potential using the JC-1 dye. The suitability of five common anesthetics was initially tested, and 5% ethanol performed best in terms of anesthetic effects and healthy recovery. The staining conditions were optimized to 30 min staining with 2 \u03bcM JC-1 for best J-aggregate formation. The protocol was validated with the model compound carbonyl cyanide 3-chlorophenylhydrazone (CCCP) and used to measure the effect of four environmental contaminants, 2,4-dinitrophenol, triclosan, n-(1,3-dimethylbutyl)-N'-phenyl-p-phenylenediamine (6PPD), and ibuprofen, on mitochondrial health. Test organisms were imaged using an automated confocal microscope, and fluorescence intensities were automatically quantified. The effect concentrations for CCCP were lower by a factor of 30 compared with the traditional OECD 202 acute toxicity test. Mitochondrial effects were also detected at lower concentrations for all tested environmental contaminants compared to the OCED 202 test. For 2,4-dinitrophenol, mitochondria effects were detectable after 2 h exposure to environmentally relevant concentrations and predicted organism death was observed after 24 h. The high sensitivity and time efficiency of this novel automated imaging method make it a valuable tool for advancing ecotoxicological testing.", "doi": "10.1021/acs.est.4c02897", "pmid": "39190186", "labels": [], "xrefs": [{"db": "pmc", "key": "PMC11393999"}], "notes": [], "created": "2026-08-20T08:09:56.273Z", "modified": "2026-08-20T08:09:56.444Z"}, {"entity": "publication", "iuid": "1a46fdab0754486fba0ce7bfe33eb95a", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/1a46fdab0754486fba0ce7bfe33eb95a.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/1a46fdab0754486fba0ce7bfe33eb95a"}}, "title": "Bypassing the Identification: MS2Quant for Concentration Estimations of Chemicals Detected with Nontarget LC-HRMS from MS2 Data.", "authors": [{"family": "Sepman", "given": "Helen", "initials": "H"}, {"family": "Malm", "given": "Louise", "initials": "L"}, {"family": "Peets", "given": "Pilleriin", "initials": "P"}, {"family": "MacLeod", "given": "Matthew", "initials": "M", "orcid": "0000-0003-2562-7339", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/442bc3b108d848a0843e092a7582ca76.json"}}, {"family": "Martin", "given": "Jonathan", "initials": "J", "orcid": "0000-0001-6265-4294", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/02199c0d99674e2ea5e96e6589c07a00.json"}}, {"family": "Breitholtz", "given": "Magnus", "initials": "M", "orcid": "0000-0002-4984-8323", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/1e2f3c4f62444d3c80f6bd1222c44ca5.json"}}, {"family": "Kruve", "given": "Anneli", "initials": "A", "orcid": "0000-0001-9725-3351", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/09b2fdaf67e44efab3cf3fa747dfa992.json"}}], "type": "journal article", "published": "2023-08-22", "journal": {"title": "Anal. Chem.", "issn": "1520-6882", "volume": "95", "issue": "33", "pages": "12329-12338", "issn-l": "0003-2700"}, "abstract": "Nontarget analysis by liquid chromatography-high-resolution mass spectrometry (LC-HRMS) is now widely used to detect pollutants in the environment. Shifting away from targeted methods has led to detection of previously unseen chemicals, and assessing the risk posed by these newly detected chemicals is an important challenge. Assessing exposure and toxicity of chemicals detected with nontarget HRMS is highly dependent on the knowledge of the structure of the chemical. However, the majority of features detected in nontarget screening remain unidentified and therefore the risk assessment with conventional tools is hampered. Here, we developed MS2Quant, a machine learning model that enables prediction of concentration from fragmentation (MS2) spectra of detected, but unidentified chemicals. MS2Quant is an xgbTree algorithm-based regression model developed using ionization efficiency data for 1191 unique chemicals that spans 8 orders of magnitude. The ionization efficiency values are predicted from structural fingerprints that can be computed from the SMILES notation of the identified chemicals or from MS2 spectra of unidentified chemicals using SIRIUS+CSI:FingerID software. The root mean square errors of the training and test sets were 0.55 (3.5\u00d7) and 0.80 (6.3\u00d7) log-units, respectively. In comparison, ionization efficiency prediction approaches that depend on assigning an unequivocal structure typically yield errors from 2\u00d7 to 6\u00d7. The MS2Quant quantification model was validated on a set of 39 environmental pollutants and resulted in a mean prediction error of 7.4\u00d7, a geometric mean of 4.5\u00d7, and a median of 4.0\u00d7. For comparison, a model based on PaDEL descriptors that depends on unequivocal structural assignment was developed using the same dataset. The latter approach yielded a comparable mean prediction error of 9.5\u00d7, a geometric mean of 5.6\u00d7, and a median of 5.2\u00d7 on the validation set chemicals when the top structural assignment was used as input. This confirms that MS2Quant enables to extract exposure information for unidentified chemicals which, although detected, have thus far been disregarded due to lack of accurate tools for quantification. The MS2Quant model is available as an R-package in GitHub for improving discovery and monitoring of potentially hazardous environmental pollutants with nontarget screening.", "doi": "10.1021/acs.analchem.3c01744", "pmid": "37548594", "labels": [], "xrefs": [{"db": "pmc", "key": "PMC10448440"}], "notes": [], "created": "2026-08-20T08:08:37.794Z", "modified": "2026-08-20T08:08:37.935Z"}]}