{"id":"W2956420751","doi":"10.2147/idr.s215084","title":"<p>Synergism of cationic antimicrobial peptide WLBU2 with antibacterial agents against biofilms of multi-drug resistant <em>Acinetobacter baumannii</em> and <em>Klebsiella pneumoniae</em></p>","year":2019,"lang":"en","type":"article","venue":"Infection and Drug Resistance","topic":"Antimicrobial Peptides and Activities","field":"Immunology and Microbiology","cited_by":41,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Jordan University of Science and Technology","keywords":"Acinetobacter baumannii; Microbiology; Antimicrobial; Klebsiella pneumoniae; Minimum bactericidal concentration; Minimum inhibitory concentration; Biofilm; Antimicrobial peptides; MTT assay; Ciprofloxacin; Chemistry; Biology; Bacteria; In vitro; Antibiotics; Pseudomonas aeruginosa; Escherichia coli; Biochemistry","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001842483,0.0004556037,0.0003899457,0.0002129604,0.00009642157,0.0001949529,0.0001855172,0.0002894803,0.001320207],"category_scores_gemma":[0.0001717853,0.0001229494,0.0002206328,0.0001252395,0.0001458666,0.000289907,0.0002619522,0.0002272682,0.0002841162],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001001855,"about_ca_system_score_gemma":0.0001669239,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001810136,"about_ca_topic_score_gemma":0.0002812926,"domain_scores_codex":[0.9998477,0.00004233378,0.000016643,0.00002849581,0.0000362346,0.0000286182],"domain_scores_gemma":[0.9999073,0.00001788865,0.00002292724,0.000007012748,0.00001255008,0.00003238959],"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":[0.0009483927,0.0001655853,0.0001806282,0.0001769613,0.00001379615,0.00009188994,0.00001458914,0.0001309434,0.9926941,0.00003379714,0.0001199662,0.005429346],"study_design_scores_gemma":[0.0001179174,0.007750198,0.003175233,0.00002356077,0.00004950255,0.0004751381,0.00003477502,0.0007719769,0.9850695,0.00002163708,0.002498531,0.00001201408],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9954031,0.002355009,0.0006440409,0.00006791373,0.00005162757,0.00005408,0.0001319004,0.00003608285,0.001256279],"genre_scores_gemma":[0.9960496,0.000915275,0.001642399,0.00006358662,0.00002933531,0.00005262906,0.0001821251,0.000009147932,0.001055901],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001320207,"threshold_uncertainty_score":0.004416525,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007747853103074652,"score_gpt":0.213115602144159,"score_spread":0.2053677490410843,"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."}}