Functional analysis of quorum sensing-mediated pathogenicity in Burkholderia contaminans SK875 using transposon mutagenesis.

Burkholderia contaminans SK875, a member of Burkholderia cepacia complex (Bcc), are known to cause lung infections in cystic fibrosis patients. To gain deeper insights into its quorum sensing (QS)-mediated pathogenicity, we employed a transposon (Tn) insertion-based random mutagenesis approach. A Tn mutant library comprising of 15,000 transconjugants was generated through conjugation between wild-type (WT) recipient B.

Enhancing Radiation Therapy Response in Prostate Cancer Through Metabolic Modulation by Mito-Lonidamine: A H and P Magnetic Resonance Spectroscopy Study.

Radiation therapy (RT) is the cornerstone treatment for prostate cancer; however, it frequently induces gastrointestinal and genitourinary toxicities that substantially diminish the patients' quality of life. While many individuals experience transient side effects, a subset endures persistent, long-term complications. A promising strategy to mitigate these toxicities involves enhancing tumor radiosensitivity, potentially allowing for lower radiation doses.

Using artificial intelligence based language interpretation in non-urgent paediatric emergency consultations: a clinical performance test and legal evaluation.

Objective: To evaluate the accuracy of Google Translate (GT) in translating low-acuity paediatric emergency consultations involving respiratory symptoms and fever, and to examine legal and policy implications of using AI-based language interpretation in healthcare.

Methods: Based on the methodology used for conducting language performance testing routinely at the Interpreter Services Department of the Hospital for Sick Children, clinical performance testing was completed using a paediatric emergency scenario (child with respiratory illness and fever) on five languages: Spanish, French, Urdu, Arabic, and Mandarin. The study focused on GT's translation accuracy and a legal and policy evaluation regarding AI-based interpretation in healthcare was conducted by legal scholars.

HDNLS: Hybrid Deep-Learning and Non-Linear Least Squares-Based Method for Fast Multi-Component T1ρ Mapping in the Knee Joint.

Non-linear least squares (NLS) methods are commonly used for quantitative magnetic resonance imaging (MRI), especially for multi-exponential T1ρ mapping, which provides precise parameter estimation for different relaxation models in tissues, such as mono-exponential (ME), bi-exponential (BE), and stretched-exponential (SE) models. However, NLS may suffer from problems like sensitivity to initial guesses, slow convergence speed, and high computational cost. While deep learning (DL)-based T1ρ fitting methods offer faster alternatives, they often face challenges such as noise sensitivity and reliance on NLS-generated reference data for training.

Electrochemical immunosensor for PA toxin using a polypyrrole-gold nanoparticle/multiwall carbon nanotube sensing platform and cadmium sulphide nanocrystal signal tag.

A sandwich electrochemical immunosensor was proposed for the sensitive detection of protective antigen ( PA) toxin based on cadmium sulphide nanocrystals (CdS NCs) and polypyrrole-gold nanoparticle-modified multiwalled carbon nanotubes (PPy-AuNPs/MWCNTs). Herein, PPy-AuNPs/MWCNTs were used as a biocompatible and conducting matrix for immobilization of rabbit anti-PA antibody [RαPA antibody, capturing antibody (Ab1)] and to facilitate excellent electrical conductivity. PPy-AuNPs/MWCNTs were synthesized through a one-step chemical reaction of pyrrole and Au on the surface of MWCNTs.