Unlabelled: Pseudomonas aeruginosa is a Gram-negative, opportunistic pathogen that causes chronic and acute infections in immunocompromised patients. Most P. aeruginosa strains encode an active type III secretion system (T3SS), utilized by the bacteria to deliver effector proteins from the bacterial cell directly into the cytoplasm of the host cell. Four T3SS effectors have been discovered and extensively studied in P. aeruginosa: ExoT, ExoS, ExoU, and ExoY. This is especially intriguing in light of P. aeruginosa's ability to infect a wide range of hosts. We therefore hypothesized that additional T3SS effectors that have not yet been discovered are encoded in the genome of P. aeruginosa. Here, we applied a machine learning classification algorithm to identify novel P. aeruginosa effectors. In this approach, various types of data are integrated to differentiate effectors from the rest of the open reading frames of the bacterial genome. Due to the lack of a sufficient learning set of positive effectors, our machine learning algorithm integrated genomic information from another Pseudomonas species and utilized dozens of features accounting for various aspects of the effector coding genes and their products. Twelve top-ranking predictions were experimentally tested for T3SS-specific translocation, leading to the discovery of two novel T3SS effectors. We demonstrate that these effectors are not part of the injection structural complex and report initial efforts toward their characterization.
Importance: Pseudomonas aeruginosa uses a type III secretion system (T3SS) to secrete toxic proteins, termed effectors, directly into the cytoplasm of the host cell. The activation of this secretion system is correlated with disease severity and patient death. Compared with many other T3SS-utilizing pathogenic bacteria, P. aeruginosa has a fairly limited arsenal of effectors that have been identified. This is in sharp contrast with the wide range of hosts that this bacterium can infect. The discovery of two novel effectors described here is an important step toward better understanding of the virulence and host evasion mechanisms adopted by this versatile pathogen and may provide novel approaches to treat P. aeruginosa infections.
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http://dx.doi.org/10.1128/mBio.00161-15 | DOI Listing |
Patient
January 2025
Division of Rheumatology, Allergy and Immunology, Department of Medicine, University of Cincinnati College of Medicine, Cincinnati, OH, USA.
Background: In the context of injectable biologic products approved or in development for chronic spontaneous urticaria (CSU), it is important to capture which treatment attributes matter most to patient and what trade-offs patients are willing to make.
Objectives: The CHOICE-CSU study aimed to quantify patient preferences toward injectable treatment attributes among patients with CSU, inadequately controlled by H1-antihistamines.
Methods: This was a two-phase cross-sectional patient preference study in adult patients with a diagnosis of CSU, inadequately controlled by H1-antihistamines.
Radiology
January 2025
From the Departments of Biomedical Systems Informatics (S.K., Jaewoong Kim, C.H., D.Y.) and Neurology (Joonho Kim, J.Y.), Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul 03722, Republic of Korea; Department of Radiology, Central Draft Physical Examination Office of Military Manpower Administration, Daegu, Republic of Korea (D.K.); Department of Radiology, Research Institute of Radiological Science and Center for Clinical Imaging Data Science (H.J.S. Y.K., S.J.), and Center for Digital Health (H.J.S., D.Y.), Yongin Severance Hospital, Yonsei University College of Medicine, Yongin, Republic of Korea; Department of Radiology, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea (S.H.L.); Departments of Radiology (M.H.) and Neurology (S.J.L.), Ajou University Hospital, Ajou University School of Medicine, Suwon, Republic of Korea; and Institute for Innovation in Digital Healthcare, Severance Hospital, Seoul, Republic of Korea (D.Y.).
Background The increasing workload of radiologists can lead to burnout and errors in radiology reports. Large language models, such as OpenAI's GPT-4, hold promise as error revision tools for radiology. Purpose To test the feasibility of GPT-4 use by determining its error detection, reasoning, and revision performance on head CT reports with varying error types and to validate its clinical utility by comparison with human readers.
View Article and Find Full Text PDFmBio
January 2025
Department of Biochemistry and Molecular Biology, University of Texas Medical Branch, Galveston, Texas, USA.
The chick embryo chorioallantoic membrane (CAM) tumor model is a valuable preclinical model for studying the tumor-colonizing process of serovar Typhimurium. It offers advantages such as cost-effectiveness, rapid turnaround, reduced engraftment issues, and ease of observation. In this study, we explored and validated the applicability of the partially immune-deficient CAM tumor model.
View Article and Find Full Text PDFJ Contemp Dent Pract
October 2024
College of Dentistry, Ajman University, Ajman P.O. Box 346, United Arab Emirates; Department of Endodontic, Faculty of Dentistry, Mansoura University, Egypt, Orcid: https://orcid.org/0000-0003-3391-5306.
Aim: This study aimed to investigate and compare the total and sectional bond strengths of three endodontic sealers when used with the single-cone obturation technique.
Materials And Methods: Forty-five human maxillary central incisors were prepared and divided into three groups according to the type of endodontic sealer: Group I (Gutta-percha/AH Plus Jet), group II (Gutta-percha/GuttaFlow 2), and group III (RealSeal/RealSeal SE). All canals were filled with the single-cone technique.
Int Angiol
December 2024
Department of Vascular Surgery, Beijing Tongren Hospital, Capital Medical University, Beijing, China -
Background: This study aimed to investigate the clinical outcomes of percutaneous transluminal angioplasty (PTA) in patients undergoing hemodialysis with different types of superior vena cava obstruction (SVCO) lesions.
Methods: This retrospective observational study recruited patients undergoing hemodialysis with SVCO and analyzed the clinical characteristics of SVCO. Patency rates were collected for patients treated with PTA and were assessed using the t-test, U-test, log-rank test and survival analyses such as the Kaplan-Meier method.
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