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Connection

Jerzy Leszczynski to Oxides

This is a "connection" page, showing publications Jerzy Leszczynski has written about Oxides.
Connection Strength

4.833
  1. Kar S, Pathakoti K, Leszczynska D, Tchounwou PB, Leszczynski J. In vitro and in silico study of mixtures cytotoxicity of metal oxide nanoparticles to Escherichia coli: a mechanistic approach. Nanotoxicology. 2022 06; 16(5):566-579.
    View in: PubMed
    Score: 0.791
  2. Kar S, Pathakoti K, Tchounwou PB, Leszczynska D, Leszczynski J. Evaluating the cytotoxicity of a large pool of metal oxide nanoparticles to Escherichia coli: Mechanistic understanding through In?Vitro and In Silico studies. Chemosphere. 2021 Feb; 264(Pt 1):128428.
    View in: PubMed
    Score: 0.689
  3. Toropova AP, Toropov AA, Leszczynska D, Leszczynski J. CORAL and Nano-QFAR: Quantitative feature - Activity relationships (QFAR) for bioavailability of nanoparticles (ZnO, CuO, Co3O4, and TiO2). Ecotoxicol Environ Saf. 2017 May; 139:404-407.
    View in: PubMed
    Score: 0.537
  4. Sizochenko N, Rasulev B, Gajewicz A, Kuz'min V, Puzyn T, Leszczynski J. From basic physics to mechanisms of toxicity: the "liquid drop" approach applied to develop predictive classification models for toxicity of metal oxide nanoparticles. Nanoscale. 2014 Nov 21; 6(22):13986-93.
    View in: PubMed
    Score: 0.459
  5. Toropova AP, Toropov AA, Rallo R, Leszczynska D, Leszczynski J. Optimal descriptor as a translator of eclectic data into prediction of cytotoxicity for metal oxide nanoparticles under different conditions. Ecotoxicol Environ Saf. 2015 Feb; 112:39-45.
    View in: PubMed
    Score: 0.458
  6. Gajewicz A, Schaeublin N, Rasulev B, Hussain S, Leszczynska D, Puzyn T, Leszczynski J. Towards understanding mechanisms governing cytotoxicity of metal oxides nanoparticles: hints from nano-QSAR studies. Nanotoxicology. 2015 May; 9(3):313-25.
    View in: PubMed
    Score: 0.447
  7. Puzyn T, Rasulev B, Gajewicz A, Hu X, Dasari TP, Michalkova A, Hwang HM, Toropov A, Leszczynska D, Leszczynski J. Using nano-QSAR to predict the cytotoxicity of metal oxide nanoparticles. Nat Nanotechnol. 2011 Mar; 6(3):175-8.
    View in: PubMed
    Score: 0.354
  8. Toropova AP, Toropov AA, Leszczynski J, Sizochenko N. Using quasi-SMILES for the predictive modeling of the safety of 574 metal oxide nanoparticles measured in different experimental conditions. Environ Toxicol Pharmacol. 2021 Aug; 86:103665.
    View in: PubMed
    Score: 0.179
  9. Sizochenko N, Mikolajczyk A, Syzochenko M, Puzyn T, Leszczynski J. Zeta potentials (?) of metal oxide nanoparticles: A meta-analysis of experimental data and a predictive neural networks modeling. NanoImpact. 2021 04; 22:100317.
    View in: PubMed
    Score: 0.179
  10. Sizochenko N, Syzochenko M, Fjodorova N, Rasulev B, Leszczynski J. Evaluating genotoxicity of metal oxide nanoparticles: Application of advanced supervised and unsupervised machine learning techniques. Ecotoxicol Environ Saf. 2019 Dec 15; 185:109733.
    View in: PubMed
    Score: 0.161
  11. Golbamaki A, Golbamaki N, Sizochenko N, Rasulev B, Leszczynski J, Benfenati E. Genotoxicity induced by metal oxide nanoparticles: a weight of evidence study and effect of particle surface and electronic properties. Nanotoxicology. 2018 12; 12(10):1113-1129.
    View in: PubMed
    Score: 0.147
  12. Golbamaki N, Rasulev B, Cassano A, Marchese Robinson RL, Benfenati E, Leszczynski J, Cronin MT. Genotoxicity of metal oxide nanomaterials: review of recent data and discussion of possible mechanisms. Nanoscale. 2015 Feb 14; 7(6):2154-98.
    View in: PubMed
    Score: 0.117
  13. Toropova AP, Toropov AA, Benfenati E, Korenstein R, Leszczynska D, Leszczynski J. Optimal nano-descriptors as translators of eclectic data into prediction of the cell membrane damage by means of nano metal-oxides. Environ Sci Pollut Res Int. 2015 Jan; 22(1):745-57.
    View in: PubMed
    Score: 0.113
  14. Kar S, Gajewicz A, Puzyn T, Roy K, Leszczynski J. Periodic table-based descriptors to encode cytotoxicity profile of metal oxide nanoparticles: a mechanistic QSTR approach. Ecotoxicol Environ Saf. 2014 Sep; 107:162-9.
    View in: PubMed
    Score: 0.111
  15. Sizochenko N, Gajewicz A, Leszczynski J, Puzyn T. Causation or only correlation? Application of causal inference graphs for evaluating causality in nano-QSAR models. Nanoscale. 2016 Apr 07; 8(13):7203-8.
    View in: PubMed
    Score: 0.032
  16. Kar S, Gajewicz A, Roy K, Leszczynski J, Puzyn T. Extrapolating between toxicity endpoints of metal oxide nanoparticles: Predicting toxicity to Escherichia coli and human keratinocyte cell line (HaCaT) with Nano-QTTR. Ecotoxicol Environ Saf. 2016 Apr; 126:238-244.
    View in: PubMed
    Score: 0.031
  17. Gajewicz A, Cronin MT, Rasulev B, Leszczynski J, Puzyn T. Novel approach for efficient predictions properties of large pool of nanomaterials based on limited set of species: nano-read-across. Nanotechnology. 2015 Jan 09; 26(1):015701.
    View in: PubMed
    Score: 0.029
Connection Strength

The connection strength for concepts is the sum of the scores for each matching publication.

Publication scores are based on many factors, including how long ago they were written and whether the person is a first or senior author.
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