{"id":"W2997049714","doi":"10.1093/neuonc/noz243","title":"Connexin43 peptide, TAT-Cx43266–283, selectively targets glioma cells, impairs malignant growth, and enhances survival in mouse models in vivo","year":2019,"lang":"en","type":"article","venue":"Neuro-Oncology","topic":"Connexins and lens biology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":52,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Canadian Institutes of Health Research; Junta de Castilla y León; Ministerio de Economía y Competitividad; Canada Research Chairs; Fundación Ramón Areces","keywords":"Glioma; SOX2; Cancer research; In vivo; Stem cell; Nestin; Biology; Cell culture; Pathology; Neural stem cell; Transcription factor; Medicine; Cell biology; Gene","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001941841,0.0006267429,0.0003445827,0.0003928004,0.0001705671,0.0002206966,0.0002164609,0.0004625388,0.001141708],"category_scores_gemma":[0.00007705957,0.0001931601,0.0002895998,0.0002159292,0.0003484443,0.0003168837,0.0001354076,0.0008352614,0.0003723194],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002345881,"about_ca_system_score_gemma":0.0002168081,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004834509,"about_ca_topic_score_gemma":0.0005865943,"domain_scores_codex":[0.9997943,0.0000290204,0.00002306275,0.0000491088,0.00005699796,0.00004754026],"domain_scores_gemma":[0.9998431,0.00001954526,0.0000592563,0.00001882485,0.00001112285,0.00004822155],"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":[0.0001266459,0.00006216871,0.00005229715,0.00003182627,0.000004231783,0.00003518784,0.00001431291,0.00005221762,0.9991074,0.00006179335,0.00004866994,0.0004032366],"study_design_scores_gemma":[0.00002032314,0.0009716951,0.001241571,0.000005192554,0.00001710517,0.0002129811,0.0000185958,0.0005629704,0.9959709,0.00003002007,0.0009450074,0.000003642105],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9951925,0.001050305,0.001883185,0.0001160109,0.0000472329,0.00003971435,0.0004967034,0.0001567486,0.001017693],"genre_scores_gemma":[0.9913112,0.001454371,0.002373938,0.00004985305,0.00001648975,0.00007670375,0.0008046043,0.00004651209,0.003866261],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001141708,"threshold_uncertainty_score":0.003819346,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00992218349736684,"score_gpt":0.2409914152566072,"score_spread":0.2310692317592404,"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."}}