Effect of RecA inactivation on quinolone susceptibility and the evolution of resistance in clinical isolates of Escherichia coli

This study was presented in part at the Twenty-Ninth European Congress of Clinical Microbiology and Infectious Diseases, Amsterdam, The Netherlands, 2019 (Poster Presentation P1339).[Background] SOS response suppression (by RecA inactivation) has been postulated as a therapeutic strategy for potentiating antimicrobials against Enterobacterales.[Objectives] To evaluate the impact of RecA inactivation on the reversion and evolution of quinolone resistance using a collection of Escherichia coli clinical isolates.[Methods] Twenty-three E. coli clinical isolates, including isolates belonging to the high-risk clone ST131, were included. SOS response was suppressed by recA inactivation. Susceptibility to fluoroquinolones was determined by broth microdilution, growth curves and killing curves. Evolution of quinolone resistance was evaluated by mutant frequency and mutant prevention concentration (MPC).[Results] RecA inactivation resulted in 2–16-fold reductions in fluoroquinolone MICs and modified EUCAST clinical category for several isolates, including ST131 clone isolates. Growth curves and time–kill curves showed a clear disadvantage (up to 10 log10 cfu/mL after 24 h) for survival in strains with an inactivated SOS system. For recA-deficient mutants, MPC values decreased 4–8-fold, with values below the maximum serum concentration of ciprofloxacin. RecA inactivation led to a decrease in mutant frequency (≥103-fold) compared with isolates with unmodified SOS responses at ciprofloxacin concentrations of 4×MIC and 1 mg/L. These effects were also observed in ST131 clone isolates.[Conclusions] While RecA inactivation does not reverse existing resistance, it is a promising strategy for increasing the effectiveness of fluoroquinolones against susceptible clinical isolates, including high-risk clone isolates.This study was funded by the Instituto de Salud Carlos III, Ministerio de Economía y Competitividad—co-financed by European Development Regional Fund ‘A way to achieve Europe’ ERDF, Spanish Network for Research in Infectious Diseases (REIPI RD12/0015 and RD16/0016). Supported by Plan Nacional de I+D+i 2013‐2016 and Instituto de Salud Carlos III, Subdirección General de Redes y Centros de InvestigaciónCooperativa, Ministerio de Economía, Industria y Competitividad, Spanish Network for Research in Infectious Diseases (PI14/00940, PI17/01501, AC16/00072, RD16/0016/0001 and REIPI RD16/0016/0009) ‐ co-financed by European Development Regional Fund ‘A way to achieve Europe’, Operative Programme Intelligent Growth 2014‐2020.Peer reviewe

Computational approaches to explainable artificial intelligence: Advances in theory, applications and trends

Deep Learning (DL), a groundbreaking branch of Machine Learning (ML), has emerged as a driving force in both theoretical and applied Artificial Intelligence (AI). DL algorithms, rooted in complex and non-linear artificial neural systems, excel at extracting high-level features from data. DL has demonstrated human-level performance in real-world tasks, including clinical diagnostics, and has unlocked solutions to previously intractable problems in virtual agent design, robotics, genomics, neuroimaging, computer vision, and industrial automation. In this paper, the most relevant advances from the last few years in Artificial Intelligence (AI) and several applications to neuroscience, neuroimaging, computer vision, and robotics are presented, reviewed and discussed. In this way, we summarize the state-of-the-art in AI methods, models and applications within a collection of works presented at the 9th International Conference on the Interplay between Natural and Artificial Computation (IWINAC). The works presented in this paper are excellent examples of new scientific discoveries made in laboratories that have successfully transitioned to real-life applications.MCIU - Nvidia(UMA18-FEDERJA-084

Computational Approaches to Explainable Artificial Intelligence:Advances in Theory, Applications and Trends

Deep Learning (DL), a groundbreaking branch of Machine Learning (ML), has emerged as a driving force in both theoretical and applied Artificial Intelligence (AI). DL algorithms, rooted in complex and non-linear artificial neural systems, excel at extracting high-level features from data. DL has demonstrated human-level performance in real-world tasks, including clinical diagnostics, and has unlocked solutions to previously intractable problems in virtual agent design, robotics, genomics, neuroimaging, computer vision, and industrial automation. In this paper, the most relevant advances from the last few years in Artificial Intelligence (AI) and several applications to neuroscience, neuroimaging, computer vision, and robotics are presented, reviewed and discussed. In this way, we summarize the state-of-the-art in AI methods, models and applications within a collection of works presented at the 9 International Conference on the Interplay between Natural and Artificial Computation (IWINAC). The works presented in this paper are excellent examples of new scientific discoveries made in laboratories that have successfully transitioned to real-life applications

Análisis crítico del tratamiento fibinolítico en la trombosis del bypass fermoropoplíteo

Objetivo. Evaluar el resultado de la terapia fibrinolítica en el tratamiento de la trombosis del injerto femoropoplíteo. Pacientes y métodos. Desde enero de 1998 a diciembre de 2005 se han tratado 50 casos de trombosis de bypass femoropoplíteo con fibrinólisis local con urocinasa. La muestra se compone de 30 pacientes con edad media de 67,7 años, portadores de bypass a primera (16%) o tercera porción (84%), con material protésico (88%) o vena (12%). La trombosis sucedió en el primer año de control clínico en el 73% de los casos. Presentaron una isquemia grado I y IIa (escala de Rutherford) el 58%. Se trató del primer episodio de trombosis en el 66% de la muestra. El tiempo de evolución de la isquemia fue menor de 14 días en el 58% de los casos. Resultados. La eficacia técnica fue del 80%. Se identificó lesión causante de la trombosis en el 90% de los casos, tratándose con terapia endovascular (69,4%) o cirugía (19,4%). La permeabilidad y el salvamento de extremidad al año fueron del 26,8 y 50,6%, respectivamente, y a los dos años del 22,3 y 47,2%, respectivamente. Los injertos que se fibrinolisaron por primera vez presentaron mayor permeabilidad (p = 0,008) y mayor salvamento de extremidad (p = 0,006), que los injertos que ya se habían tratado previamente. Conclusiones. La terapia trombolítica es una técnica útil para restablecer la permeabilidad de los injertos femoropoplíteos; no obstante, los resultados obtenidos en la segunda y tercera fibrinólisis de un mismo bypass hacen replantear la necesidad de un tratamiento alternativo

Disección y trombosis de arteria iliaca común secundaria a traumatismo abdominal cerrado: tratamiento endovascular

Introducción. Las lesiones traumáticas de las arterias iliacas son poco frecuentes, constituyen alrededor del 10% de todas las lesiones vasculares abdominales y se deben en su mayoría a traumatismos penetrantes. La mayoría de los casos documentados de lesiones iliacas por traumatismos contusos fueron tratados mediante técnicas convencionales. Presentamos un caso de lesión traumática cerrada de la arteria iliaca común resuelta mediante un abordaje mínimamente invasivo. Caso clínico. Varón de 38 años que presenta traumatismo abdominal cerrado tras accidente laboral, con lesiones óseas y abdominales asociadas a disección y trombosis de la arteria iliaca común derecha, que se trata mediante trombectomía e implantación de un stent autoexpandible de nitinol. El control realizado con eco-Doppler a los tres meses demostró la permeabilidad del stent y el eje iliaco tratado. Conclusión. El tratamiento endovascular de lesiones arteriales iliacas secundarias a traumatismos cerrados es una opción válida y debe considerarse particularmente en pacientes politraumatizados con múltiples lesiones, en los que la cirugía abierta se asocia a elevadas tasas de morbimortalidad