Dual-mode-driven nanomotors targeting inflammatory macrophages for the MRI and synergistic treatment of atherosclerosis.

With the progress of atherosclerosis (AS), the arterial lumen stenosis and compact plaque structure, the thickening intima and the narrow gaps between endothelial cells significantly limit the penetration efficiency of nanoprobe to plaque, weakening the imaging sensitivity and therapy efficiency. Thus, in this study, a HO-NIR dual-mode nanomotor, Gd-doped mesoporous carbon nanoparticles/Pt with rapamycin (RAPA) loading and AntiCD36 modification (Gd-MCNs/Pt-RAPA-AC) was constructed. The asymmetric deposition of Pt on Gd-MCNs catalyzed HO at the inflammatory site to produce O, which could promote the self-motion of the nanomotor and ease inflammation microenvironment of AS plaque.

Validation of a Deep Learning Tool for Detection of Incidental Vertebral Compression Fractures.

Objective: This study evaluated the performance of a deep learning-based vertebral compression fracture (VCF) detection tool in patients with incidental VCF. The purpose of this study was to validate this tool across multiple sites and multiple vendors.

Methods: This was a retrospective, multicenter, multinational blinded study using anonymized chest and abdominal CT scans performed for indications other than VCF in patients ≥50 years old.

Tumour size is associated with growth rates of >0.5 cm/year and delayed intervention in small renal masses in patients on active surveillance.

Objective: To evaluate the association between tumour size and the growth rate (GR) of small renal masses (SRMs) in patients managed by active surveillance (AS).

Materials And Methods: We queried the prospective, multi-institutional Delayed Intervention and Surveillance for Small Renal Masses (DISSRM) registry for patients on AS with an imaging interval of ≥6 months, identifying 456 patients. We tracked tumour size over time; a GR >0.

identification through bronchoscope in intensive care unit - a retrospective, databased cohort study.

Introduction: Invasive pulmonary aspergillosis (IPA) increases the risk of mortality of critically ill patients. Diagnostic criteria specifically targeting patients in intensive care units(ICUs) have been developed to improve diagnostic sensitivity. This study investigated health outcomes among patients in ICUs with Aspergillus isolates identified using bronchoscopy.

Utilizing TP53 hotspot mutations as effective predictors of gemcitabine treatment outcome in non-small-cell lung cancer.

TP53 mutations are recognized to correlate with a worse prognosis in individuals with non-small cell lung cancer (NSCLC). There exists an immediate necessity to pinpoint selective treatment for patients carrying TP53 mutations. Potential drugs were identified by comparing drug sensitivity differences, represented by the half-maximal inhibitory concentration (IC50), between TP53 mutant and wild-type NSCLC cell lines using database analysis.