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- Bulten, W, et al.
(författare)
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Artificial intelligence for diagnosis and Gleason grading of prostate cancer: the PANDA challenge
- 2022
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Ingår i: Nature medicine. - : Springer Science and Business Media LLC. - 1546-170X .- 1078-8956. ; 28:21, s. 154-
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Tidskriftsartikel (refereegranskat)abstract
- Artificial intelligence (AI) has shown promise for diagnosing prostate cancer in biopsies. However, results have been limited to individual studies, lacking validation in multinational settings. Competitions have been shown to be accelerators for medical imaging innovations, but their impact is hindered by lack of reproducibility and independent validation. With this in mind, we organized the PANDA challenge—the largest histopathology competition to date, joined by 1,290 developers—to catalyze development of reproducible AI algorithms for Gleason grading using 10,616 digitized prostate biopsies. We validated that a diverse set of submitted algorithms reached pathologist-level performance on independent cross-continental cohorts, fully blinded to the algorithm developers. On United States and European external validation sets, the algorithms achieved agreements of 0.862 (quadratically weighted κ, 95% confidence interval (CI), 0.840–0.884) and 0.868 (95% CI, 0.835–0.900) with expert uropathologists. Successful generalization across different patient populations, laboratories and reference standards, achieved by a variety of algorithmic approaches, warrants evaluating AI-based Gleason grading in prospective clinical trials.
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| 2. |
- Mohammed Taha, Hiba, et al.
(författare)
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The NORMAN Suspect List Exchange (NORMAN-SLE) : facilitating European and worldwide collaboration on suspect screening in high resolution mass spectrometry
- 2022
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Ingår i: Environmental Sciences Europe. - : Springer. - 2190-4707 .- 2190-4715. ; 34:1
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Tidskriftsartikel (refereegranskat)abstract
- Background: The NORMAN Association (https://www.norman-network.com/) initiated the NORMAN Suspect List Exchange (NORMAN-SLE; https://www.norman-network.com/nds/SLE/) in 2015, following the NORMAN collaborative trial on non-target screening of environmental water samples by mass spectrometry. Since then, this exchange of information on chemicals that are expected to occur in the environment, along with the accompanying expert knowledge and references, has become a valuable knowledge base for “suspect screening” lists. The NORMAN-SLE now serves as a FAIR (Findable, Accessible, Interoperable, Reusable) chemical information resource worldwide.Results: The NORMAN-SLE contains 99 separate suspect list collections (as of May 2022) from over 70 contributors around the world, totalling over 100,000 unique substances. The substance classes include per- and polyfluoroalkyl substances (PFAS), pharmaceuticals, pesticides, natural toxins, high production volume substances covered under the European REACH regulation (EC: 1272/2008), priority contaminants of emerging concern (CECs) and regulatory lists from NORMAN partners. Several lists focus on transformation products (TPs) and complex features detected in the environment with various levels of provenance and structural information. Each list is available for separate download. The merged, curated collection is also available as the NORMAN Substance Database (NORMAN SusDat). Both the NORMAN-SLE and NORMAN SusDat are integrated within the NORMAN Database System (NDS). The individual NORMAN-SLE lists receive digital object identifiers (DOIs) and traceable versioning via a Zenodo community (https://zenodo.org/communities/norman-sle), with a total of > 40,000 unique views, > 50,000 unique downloads and 40 citations (May 2022). NORMAN-SLE content is progressively integrated into large open chemical databases such as PubChem (https://pubchem.ncbi.nlm.nih.gov/) and the US EPA’s CompTox Chemicals Dashboard (https://comptox.epa.gov/dashboard/), enabling further access to these lists, along with the additional functionality and calculated properties these resources offer. PubChem has also integrated significant annotation content from the NORMAN-SLE, including a classification browser (https://pubchem.ncbi.nlm.nih.gov/classification/#hid=101).Conclusions: The NORMAN-SLE offers a specialized service for hosting suspect screening lists of relevance for the environmental community in an open, FAIR manner that allows integration with other major chemical resources. These efforts foster the exchange of information between scientists and regulators, supporting the paradigm shift to the “one substance, one assessment” approach. New submissions are welcome via the contacts provided on the NORMAN-SLE website (https://www.norman-network.com/nds/SLE/).
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| 4. |
- Hakkinen, E., et al.
(författare)
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Online measurement of highly oxygenated compounds from organic aerosol
- 2023
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Ingår i: Atmospheric Measurement Techniques. - : Copernicus GmbH. - 1867-1381 .- 1867-8548. ; 16:6, s. 1705-1721
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Tidskriftsartikel (refereegranskat)abstract
- Highly oxygenated compounds are important contributors to the formation and growth of atmospheric organic aerosol and thus have an impact on Earth's radiation balance and global climate. However, knowledge of the contribution of highly oxygenated compounds to organic aerosol and their fate after condensing into the particle phase has been limited by the lack of suitable detection techniques. Here, we present a new online method for measuring highly oxygenated compounds from organic aerosol. The method includes thermal evaporation of particles in a new inlet, the vaporization inlet for aerosols (VIA), followed by identification of the evaporated highly oxygenated compounds by a nitrate chemical ionization mass spectrometer (NO3-CIMS). The method does not require sample collection, enabling highly time-resolved measurements of particulate compounds. We evaluate the performance of the method by measuring the detection limit and performing background measurements. We estimate a detection limit of below 1 ng m(-3) for a single compound and below 1 mu g m(-3) for SOA with the sampling setup used here. These detection limits can be improved upon by optimizing the flow setup. Furthermore, we detect hundreds of particulate highly oxygenated compounds from organic aerosol generated from different precursors. Our results are consistent with previous studies showing that the volatility of organic compounds decreases with increasing m/z ratio and level of oxygenation and that organic aerosol consists of monomers and oligomeric compounds. By comparing the gas- and particle-phase compounds, we found indications of potential particle-phase reactions occurring in organic aerosol. Future work will focus both on further improving the sampling design and on better understanding the evaporation dynamics of the system, but already these initial tests show that the VIA coupled to the NO3-CIMS is a promising method for investigating the transformations and fate of the compounds after condensing into the particle phase.
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| 7. |
- Rajasilta, O, et al.
(författare)
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Maternal pre-pregnancy BMI associates with neonate local and distal functional connectivity of the left superior frontal gyrus
- 2021
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Ingår i: Scientific reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 11:1, s. 19182-
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Tidskriftsartikel (refereegranskat)abstract
- Maternal obesity/overweight during pregnancy has reached epidemic proportions and has been linked with adverse outcomes for the offspring, including cognitive impairment and increased risk for neuropsychiatric disorders. Prior neuroimaging investigations have reported widespread aberrant functional connectivity and white matter tract abnormalities in neonates born to obese mothers. Here we explored whether maternal pre-pregnancy adiposity is associated with alterations in local neuronal synchrony and distal connectivity in the neonate brain. 21 healthy mother-neonate dyads from uncomplicated pregnancies were included in this study (age at scanning 26.14 ± 6.28 days, 12 male). The neonates were scanned with a 6-min resting-state functional magnetic resonance imaging (rs-fMRI) during natural sleep. Regional homogeneity (ReHo) maps were computed from obtained rs-fMRI data. Multiple regression analysis was performed to assess the association of pre-pregnancy maternal body-mass-index (BMI) and ReHo. Seed-based connectivity analysis with multiple regression was subsequently performed with seed-ROI derived from ReHo analysis. Maternal adiposity measured by pre-pregnancy BMI was positively associated with neonate ReHo values within the left superior frontal gyrus (SFG) (FWE-corrected p < 0.005). Additionally, we found both positive and negative associations (p < 0.05, FWE-corrected) for maternal pre-pregnancy BMI and seed-based connectivity between left SFG and prefrontal, amygdalae, basal ganglia and insular regions. Our results imply that maternal pre-pregnancy BMI associates with local and distal functional connectivity within the neonate left superior frontal gyrus. These findings add to the evidence that increased maternal pre-pregnancy BMI has a programming influence on the developing neonate brain functional networks.
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