{"id":"W4391447960","doi":"10.1002/adma.202307454","title":"Self‐Disassembling and Oxygen‐Generating Porphyrin‐Lipoprotein Nanoparticle for Targeted Glioblastoma Resection and Enhanced Photodynamic Therapy","year":2024,"lang":"en","type":"article","venue":"Advanced Materials","topic":"Nanoplatforms for cancer theranostics","field":"Engineering","cited_by":50,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Shanghai Rising-Star Program; National Natural Science Foundation of China; National Key Research and Development Program of China; Shanghai Science and Technology Development Foundation","keywords":"Photodynamic therapy; Porphyrin; Materials science; Glioblastoma; Nanoparticle; Reactive oxygen species; Cancer research; Nanotechnology; Photochemistry; Medicine; Organic chemistry; Biochemistry; Chemistry","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":[0.0002348485,0.0002367758,0.0002525739,0.00009969798,0.0001239881,0.0002115947,0.0000610897,0.00009066913,0.0000211387],"category_scores_gemma":[0.00003416101,0.0002268718,0.00003035615,0.0001647248,0.00002401512,0.0004506326,0.00002385908,0.00006520555,0.000004752322],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001038022,"about_ca_system_score_gemma":0.00001907127,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009208649,"about_ca_topic_score_gemma":0.00003328835,"domain_scores_codex":[0.9988812,0.00001452672,0.0003202287,0.0003153207,0.0001265615,0.0003422183],"domain_scores_gemma":[0.9996123,0.00007586932,0.00003897835,0.0001537455,0.00005015028,0.00006894077],"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":[0.0001945981,0.000007111678,3.024783e-7,0.0004377603,0.00006344564,0.000002953889,0.0003436143,0.001533141,0.9849597,0.0001509117,0.00001031301,0.01229612],"study_design_scores_gemma":[0.0008415477,0.0002668705,0.00001121138,0.0001260716,0.00001691009,0.00001133882,0.00005442628,0.01414933,0.9819474,0.001264547,0.001038284,0.0002721192],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9859353,0.004113507,0.007085325,0.00001481008,0.001134835,0.0008645302,0.00006478528,0.0007625236,0.00002440364],"genre_scores_gemma":[0.9886241,0.001037524,0.00960856,0.0000206789,0.0001950871,0.0003642978,0.00001399545,0.0001061042,0.00002966772],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01261619,"threshold_uncertainty_score":0.9251565,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006229674990870683,"score_gpt":0.2330954290661435,"score_spread":0.2268657540752728,"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."}}