{"id":"W2107955975","doi":"10.1093/intimm/dxp044","title":"Synthetic methylated CpG ODNs are potent in vivo adjuvants when delivered in liposomal nanoparticles","year":2009,"lang":"en","type":"article","venue":"International Immunology","topic":"Immune Response and Inflammation","field":"Immunology and Microbiology","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; Arbutus Biopharma (Canada)","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"TLR9; CpG Oligodeoxynucleotide; Toll-Like Receptor 9; CpG site; DNA methylation; Methylation; In vivo; Chemistry; Oligonucleotide; Innate immune system; Folate receptor; Immune system; Receptor; Guanine; Molecular biology; Cell biology; Biology; Biochemistry; DNA; Gene expression; Immunology; Gene; Genetics; Nucleotide","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":[0.0002642784,0.0003714157,0.000142353,0.0001567909,0.00005610214,0.0001858178,0.0001165609,0.0002705911,0.0008252906],"category_scores_gemma":[0.0001992846,0.0001395389,0.0001028564,0.00006857049,0.0001466523,0.0001713144,0.0001797674,0.0003052558,0.0002831106],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001285845,"about_ca_system_score_gemma":0.0001572601,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001218058,"about_ca_topic_score_gemma":0.0002159422,"domain_scores_codex":[0.9999,0.00002729536,0.00000677042,0.00001114215,0.00003442762,0.00002031691],"domain_scores_gemma":[0.9999084,0.00001754866,0.00003183512,0.000006159366,0.00001310214,0.00002288646],"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":[0.0000800303,0.00001396358,0.00005148198,0.00003765195,0.00000274533,0.00001305713,0.00000502319,0.0001058346,0.9981472,0.00009149708,0.00001550053,0.001436018],"study_design_scores_gemma":[0.000009075038,0.0003748204,0.0002795134,0.000004968833,0.000009045305,0.00006760489,0.000004227325,0.0004010008,0.9977143,0.00005214873,0.001081615,0.000001750228],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9761129,0.004014242,0.01693468,0.0001825108,0.00006559175,0.00008119625,0.0001920699,0.0001181157,0.002298712],"genre_scores_gemma":[0.9906557,0.001126523,0.005655535,0.00006732708,0.00001867411,0.00003363686,0.0001646626,0.0000178405,0.002260118],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0008252906,"threshold_uncertainty_score":0.002760828,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009537583772299808,"score_gpt":0.2364415463368946,"score_spread":0.2269039625645948,"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."}}