{"id":"W3199941887","doi":"10.26685/urncst.278","title":"Resurrecting the Dead: Mitigating Efflux-Pump Inhibitor Toxicity using a Liposomal Delivery System to Recover Efficacy of Antimicrobial Drugs","year":2021,"lang":"en","type":"article","venue":"Undergraduate Research in Natural and Clinical Science and Technology (URNCST) Journal","topic":"Antibiotic Resistance in Bacteria","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Efflux; Antimicrobial; Pseudomonas aeruginosa; Microbiology; Antibiotics; Viability assay; Liposome; Ethidium bromide; Multiple drug resistance; Pharmacology; Minimum inhibitory concentration; Cytotoxicity; Bacteria; Toxicity; Antibiotic resistance; Chemistry; Biology; Biochemistry; Cell; In vitro; DNA","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002817951,0.0004479487,0.0003242067,0.0002836507,0.0001707894,0.00042657,0.0002874205,0.0005412326,0.001285625],"category_scores_gemma":[0.0002149584,0.0001703732,0.0003794602,0.0001173112,0.0002533073,0.0006079488,0.0003659235,0.0006073502,0.0005929043],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003176465,"about_ca_system_score_gemma":0.0002451992,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003367007,"about_ca_topic_score_gemma":0.0003508354,"domain_scores_codex":[0.9998599,0.00001846558,0.00001336381,0.00003705968,0.00004019055,0.00003102198],"domain_scores_gemma":[0.9998983,0.00001583702,0.00003474096,0.000009544111,0.00002456779,0.00001702022],"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":[0.000085605,0.0000545415,0.0000847039,0.0001474591,0.000007941143,0.00005857317,0.00001846283,0.0001274787,0.9939366,0.0001670127,0.0001471008,0.005164634],"study_design_scores_gemma":[0.0000212851,0.0006733061,0.000519668,0.0000192419,0.00002331157,0.0001525889,0.00001557704,0.001419966,0.9923839,0.00004387436,0.004715598,0.00001173189],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9153852,0.01350047,0.06323548,0.0009080099,0.0002698671,0.0007346229,0.0005649243,0.0007716589,0.004629861],"genre_scores_gemma":[0.9500307,0.006323184,0.03586601,0.0004911813,0.00004781667,0.0004819091,0.0005419301,0.0000749156,0.006142329],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001285625,"threshold_uncertainty_score":0.004300773,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03118298654328724,"score_gpt":0.3630764415827176,"score_spread":0.3318934550394304,"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."}}