{"id":"W4407172316","doi":"10.1073/pnas.2406659122","title":"Rapid restoration of potent neutralization activity against the latest Omicron variant JN.1 via AI rational design and antibody engineering","year":2025,"lang":"en","type":"article","venue":"Proceedings of the National Academy of Sciences","topic":"SARS-CoV-2 and COVID-19 Research","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"HEC Montréal; Université de Montréal; Mila - Quebec Artificial Intelligence Institute","funders":"HEC Montréal; National Science and Technology Major Project; Henan Provincial People's Hospital; Université de Montréal; National Key New Drug Creation and Manufacturing Program, Ministry of Science and Technology; Shanghai Jiao Tong University; Zhengzhou University; National Natural Science Foundation of China; University of Pittsburgh","keywords":"Neutralization; Antibody; Neutralizing antibody; Virology; Antibody Repertoire; Potency; In vitro; Mutant; Rational design; Antigen; Biology; Chemistry; Virus; Gene; Immunology; Genetics","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":[0.0004881427,0.000606149,0.000486305,0.0004744048,0.0002445401,0.0004843363,0.000544949,0.0003395812,0.0004723188],"category_scores_gemma":[0.0003309462,0.0002759766,0.0004358974,0.0003911183,0.0003842882,0.0002610823,0.0004223772,0.0008548428,0.0002613657],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005439534,"about_ca_system_score_gemma":0.0005013308,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007442889,"about_ca_topic_score_gemma":0.00137306,"domain_scores_codex":[0.9997146,0.00004126009,0.00002501988,0.00004321638,0.00009819642,0.00007777991],"domain_scores_gemma":[0.9999063,0.00001515645,0.00002784246,0.000009579496,0.0000224497,0.00001869096],"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":[0.000153306,0.0002167064,0.0004446222,0.000243334,0.00003581954,0.0002953349,0.00008955361,0.005802977,0.9648268,0.003249787,0.000385207,0.02425666],"study_design_scores_gemma":[0.0001775349,0.001449663,0.001081304,0.00004239538,0.0001073648,0.0006442062,0.00006497515,0.02077449,0.9513198,0.001339621,0.02295044,0.00004827407],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.802078,0.005726263,0.1791011,0.0006284945,0.0001514766,0.0008447753,0.0005183305,0.0005349825,0.01041669],"genre_scores_gemma":[0.8796879,0.005834375,0.1098496,0.0003059649,0.0000292427,0.0004367986,0.0006808594,0.0001002381,0.003074991],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0007442889,"threshold_uncertainty_score":0.003946662,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04543392113376526,"score_gpt":0.3466158035167829,"score_spread":0.3011818823830177,"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."}}