Orders of Magnitude Improved Cyclotron-Mode Cooling for Nondestructive Spin Quantum Transition Spectroscopy with Single Trapped Antiprotons.

We demonstrate efficient subthermal cooling of the modified cyclotron mode of a single trapped antiproton and reach particle temperatures T_{+}=E_{+}/k_{B} below 200 mK in preparation times shorter than 500 s. This corresponds to the fastest resistive single-particle cyclotron cooling to subthermal temperatures ever demonstrated. By cooling trapped particles to such low energies, we demonstrate the detection of antiproton spin transitions with an error rate <0.

Image-Current Mediated Sympathetic Laser Cooling of a Single Proton in a Penning Trap Down to 170 mK Axial Temperature.

We demonstrate a new temperature record for image-current mediated sympathetic cooling of a single proton in a cryogenic Penning trap by laser-cooled ^{9}Be^{+}. An axial mode temperature of 170 mK is reached, which is a 15-fold improvement compared to the previous best value. Our cooling technique is applicable to any charged particle, so that the measurements presented here constitute a milestone toward the next generation of high-precision Penning-trap measurements with exotic particles.

Unveiling the Significance of MRP 1 in Achieving Complete Remission Following Induction Therapy in Acute Myeloid Leukemia.

Background: Increased expression of MRP 1 in AML patients results in the efflux of drugs from the cells, preventing the patient from achieving remission or potentially leading to relapse. Several studies have demonstrated that early identification of ABC transporter may yield favorable outcomes.

Aims And Objectives: The objectives of the study were to investigate the correlation between MRP 1 gene expression and MRP 1 protein levels and the response to remission induction in AML patients.

Risk factors affecting patients survival with colorectal cancer in Morocco: survival analysis using an interpretable machine learning approach.

The aim of our study was to assess the overall survival rates for colorectal cancer at 3 years and to identify associated strong prognostic factors among patients in Morocco through an interpretable machine learning approach. This approach is based on a fully non-parametric survival random forest (RSF), incorporating variable importance and partial dependence effects. The data was povided from a retrospective study of 343 patients diagnosed and followed at Hassan II University Hospital.