{"id":"W4360849775","doi":"10.26434/chemrxiv-2023-0hzxw","title":"Therapeutic Copper-based Nanoparticles Release Labile Copper(II) and Trigger Cellular Responses in Glutathione and NRF2 Redox Pathways and Metal Homeostasis","year":2023,"lang":"en","type":"preprint","venue":"ChemRxiv","topic":"Trace Elements in Health","field":"Nursing","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Office of Science; European Research Council; National Institutes of Health; U.S. Department of Energy; Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina; Lawrence Berkeley National Laboratory; Canadian Institute for Advanced Research; Basic Energy Sciences; Universidad de Zaragoza","keywords":"Copper; Glutathione; Nanoparticle; Chemistry; Metal; Copper toxicity; Downregulation and upregulation; Biophysics; Nanomedicine; Homeostasis; Antioxidant; Biochemistry; Nanotechnology; Materials science; Cell biology; Biology; Enzyme; Organic chemistry","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001465908,0.0005268336,0.0007980681,0.0003900575,0.0003320464,0.000146156,0.0002014602,0.0004409865,0.00002590275],"category_scores_gemma":[0.0005014157,0.0005238812,0.00008381683,0.0003302983,0.0004305743,0.0001178777,0.0004324288,0.0008318779,0.00001125189],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002049613,"about_ca_system_score_gemma":0.0002075713,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002270087,"about_ca_topic_score_gemma":0.0001149167,"domain_scores_codex":[0.9964765,0.0005508923,0.0007449934,0.001152694,0.0003988962,0.0006760145],"domain_scores_gemma":[0.9977161,0.0009279982,0.0002781217,0.0007085018,0.00007707331,0.0002922254],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.006808384,0.001353222,0.05073855,0.005227432,0.0003334818,0.0005343484,0.01166691,0.0001609157,0.8554959,0.0002277388,0.002055258,0.06539788],"study_design_scores_gemma":[0.007985666,0.001322912,0.06916665,0.001860337,0.0006330181,0.00004343967,0.002463943,0.002347444,0.9033247,0.004674108,0.004295793,0.001882051],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9738636,0.01941613,0.000005454783,0.004704005,0.0005314249,0.001105315,0.0001111492,0.0002487476,0.00001415003],"genre_scores_gemma":[0.9970998,0.001258875,0.0006788711,0.0003931481,0.00008601549,0.0001978582,0.00005839074,0.0001316309,0.00009539726],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06351583,"threshold_uncertainty_score":0.9997213,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06055846887719221,"score_gpt":0.3045908462627159,"score_spread":0.2440323773855237,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}