{"id":"W4416527614","doi":"10.1021/acs.nanolett.5c02487","title":"Polymer Blend Controls Nanoparticles’ Surface Charge for Improved Mucus Penetration and Epithelial Cell Adhesion","year":2025,"lang":"en","type":"article","venue":"Nano Letters","topic":"Advanced Drug Delivery Systems","field":"Pharmacology, Toxicology and Pharmaceutics","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; Deutscher Akademischer Austauschdienst; National Institute of General Medical Sciences; National Institute of Environmental Health Sciences; Canadian Institutes of Health Research; Grand Challenges in Global Health; National Institute of Diabetes and Digestive and Kidney Diseases; Bill and Melinda Gates Foundation","keywords":"Penetration (warfare); Mucus; Mucin; Methacrylate; Nanoparticle; Epithelium; Polymer; Drug delivery; Adhesion","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.0001101571,0.0003162834,0.00014604,0.0001542702,0.00008705191,0.0002625348,0.0001760451,0.0003327895,0.001447006],"category_scores_gemma":[0.0002003515,0.00014203,0.0001231617,0.000144903,0.0001404815,0.0002965734,0.0001668337,0.000297848,0.0002404523],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002461206,"about_ca_system_score_gemma":0.0001147859,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004071671,"about_ca_topic_score_gemma":0.0007002379,"domain_scores_codex":[0.9998914,0.000007314059,0.00001200423,0.00003736228,0.00002647882,0.00002539108],"domain_scores_gemma":[0.9999092,0.00002047418,0.00002771425,0.000007285625,0.00001565408,0.00001964359],"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":[0.00003111854,0.00001477797,0.00002604409,0.00001018184,0.000001422592,0.000008709421,0.000004626752,0.0000378992,0.9991513,0.00002382576,0.00001865508,0.0006714201],"study_design_scores_gemma":[0.000007983405,0.00008782907,0.0004378536,0.000001581011,0.0000044726,0.00001924714,0.000004740118,0.0007897636,0.9981369,0.000008674058,0.0004983324,0.000002589579],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9962507,0.0003598522,0.002062708,0.00005703912,0.00002011808,0.0000196451,0.00008575228,0.00009147132,0.001052805],"genre_scores_gemma":[0.9959059,0.0002331049,0.002446191,0.00003877027,0.000004693264,0.00003104788,0.00008487658,0.00003090148,0.001224432],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001447006,"threshold_uncertainty_score":0.004840672,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03335481271569253,"score_gpt":0.3565248151098875,"score_spread":0.323170002394195,"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."}}