Results 191 to 200 of about 734,075 (399)

Computational and AI‐Driven Design of Hydrogels for Bioelectronic Applications

Advanced Electronic Materials, EarlyView.
This review highlights the role of AI in advancing hydrogel design for bioelectronics, exploring natural, and synthetic gels tailored for applications like wound healing, biosensing, and tissue engineering. It emphasizes the synergy between hydrogels, electronics, and AI in creating responsive, multifunctional systems, showcasing recent innovations ...
Rebekah Finster, Prashant Sankaran, Eloise Bihar   +2 more
wiley   +1 more source

An AI-directed analytical study on the optical transmission microscopic images of Pseudomonas aeruginosa in planktonic and biofilm states [PDF]

arXiv
Biofilms are resistant microbial cell aggregates that pose risks to health and food industries and produce environmental contamination. Accurate and efficient detection and prevention of biofilms are challenging and demand interdisciplinary approaches.
arxiv  

THE LYSIS OF PSEUDOMONAS AERUGINOSA BY LYSOZYME [PDF]

, 1955
George H. Warren, Jane Gray, Pasquale F. Bartell   +2 more
openalex   +1 more source

Comparison between olanexidine gluconate and conventional antiseptics for surgical site infection in gastroenterological surgery: A meta‐analysis

Annals of Gastroenterological Surgery, EarlyView.
This meta‐analysis compared olanexidine gluconate (OLG) with conventional antiseptics on surgical site infections (SSIs) in gastroenterological surgery. OLG significantly reduced overall SSIs without statistical heterogeneity. Abstract Aim To compare the preventative effect of the new antiseptic olanexidine gluconate (OLG) with conventional antiseptics
Akihisa Matsuda, Takeshi Yamada, Kay Uehara, Aya Yamagishi, Hiroshi Yoshida   +4 more
wiley   +1 more source

Pseudomonas aeruginosa and whirlpools [PDF]

BMJ, 1985
Judith Brett, A du Vivier
openaire   +7 more sources

Detection of bla-IMP-1 and bla-IMP-2 Genes Among Metallo-β-lactamase-Producing Pseudomonas Aeruginosa Isolated from Burn Patients in Isfahan

Bihdād, 2016
Background: Pseudomonas aeruginosa is a nosocomial pathogen which especially causes infections among burn patients. Carbapenems are extensively used for the treatment of infections caused by multidrug-resistant P. aeruginosa isolates.
M. Pourbabaee, F. Firoozeh, M. Saffari, M. Zibaei, M. Sehat, M. Radan   +5 more
doaj  

A Bacteriophage for Pseudomonas pyocyanea ( Pseudomonas aeruginosa ) [PDF]

, 1945
L.B. Fastier
openalex   +1 more source

Ultrafine‐Mn‐Loaded N,O‐Doped Nanocarbon via Mott‒Schottky Effect for Photo‐Enhanced Antibacterial Therapy and Wound Healing

Aggregate, EarlyView.
Herein, we used the Mott–Schottky effect to synthesize an ultrafine‐Mn‐loaded N,O‐doped porous nanocarbons (Mn‐PNCs) nanozyme. The fabricated Mn‐PNCs nanozyme using a sustainable and efficient heteroatom‐doped strategy exhibited excellent photothermal‐enhanced, peroxidase‐like activity, thereby contributing to effective antibacterial treatment for ...
Xueyu Jiang, Fanwei Zeng, Yan Li, Yang Yi, Xiaodong Tang, Ang Lu   +5 more
wiley   +1 more source

Complete genome sequence of Pseudomonas aeruginosa PAO1, an opportunistic pathogen

Nature, 2000
C. Stover, X. Pham, A. Erwin, S. Mizoguchi, P. Warrener, M. Hickey, F. Brinkman, W. O. Hufnagle, D. J. Kowalik, Lagrou Mj, R. Garber, L. Goltry, E. Tolentino, S. Westbrock-Wadman, Ying Yuan, L. L. Brody, S. Coulter, K. Folger, A. Kas, K. Larbig, R. Lim, Kelly D. Smith, D. Spencer, Gane Ka-Shu Wong, Z. Wu, I. Paulsen, J. Reizer, M. Saier, R. Hancock, S. Lory, M. Olson   +30 more
semanticscholar   +1 more source

Integrating Aggregate Materials and Machine Learning Algorithms: Advancing Detection of Pathogen‐Derived Extracellular Vesicles

Aggregate, EarlyView.
Pathogen‐derived extracellular vesicle detection: theoretical insights and advanced methodologies: This review explores the theoretical foundations and practical applications of pEV detection, emphasizing the challenges and innovative strategies involving novel aggregate materials and machine learning for enhanced diagnostic accuracy.
Lihan Lai, Yun Su, Cong Hu, Zehong Peng, Wei Xue, Liang Dong, Tony Y. Hu   +6 more
wiley   +1 more source