{"id":"W4408858711","doi":"10.1021/acsnano.4c17080","title":"Leveraging Vitamin C to Augment Nanoenabled Photothermal Immunotherapy","year":2025,"lang":"en","type":"article","venue":"ACS Nano","topic":"Nanoplatforms for cancer theranostics","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Response Biomedical (Canada)","funders":"Anhui Provincial Key Research and Development Plan; National Key Research and Development Program of China; Natural Science Foundation of Anhui Province; Major Science and Technology Projects in Anhui Province; Chinese Academy of Sciences; National Natural Science Foundation of China","keywords":"Photothermal therapy; Immunotherapy; Immune system; Cancer research; T cell; Photosensitizer; Tumor microenvironment; Vitamin C; Immunology; Medicine; Chemistry; Materials science; Internal medicine; Nanotechnology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001164957,0.0002277429,0.0002291935,0.0002079405,0.00008772413,0.00006043096,0.0003064739,0.0000847841,0.0001333852],"category_scores_gemma":[0.00001026936,0.0002290623,0.0000683406,0.0004686433,0.00001342757,0.0001225353,0.00004556332,0.0001211077,0.0001526895],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004271177,"about_ca_system_score_gemma":0.00005201029,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005217502,"about_ca_topic_score_gemma":0.00001442976,"domain_scores_codex":[0.9989293,0.000008466053,0.0002642159,0.0002032873,0.000163702,0.0004310439],"domain_scores_gemma":[0.9994206,0.00004457761,0.00001973595,0.0004160976,0.00003482652,0.00006411245],"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":[0.0000410258,0.0000194367,0.0001504372,0.0000436445,0.0001292498,0.000005987558,0.0005353716,0.003828867,0.9663034,0.000163599,0.005019735,0.02375924],"study_design_scores_gemma":[0.001049259,0.00003824526,0.0003678938,0.0001065008,0.00001476762,0.000002251598,0.00005889794,0.0005190089,0.8413026,0.0003172267,0.1559388,0.0002845731],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9663364,0.001266579,0.01794717,0.0002421222,0.001770322,0.0005566173,0.00001239801,0.0006045692,0.01126379],"genre_scores_gemma":[0.9922257,0.0001713547,0.001225969,0.00107134,0.0000650375,0.00009107048,0.00000561172,0.00006953664,0.005074354],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.150919,"threshold_uncertainty_score":0.9340891,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005599586234313052,"score_gpt":0.2134950996372365,"score_spread":0.2078955134029234,"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."}}