Dressed-State Spectroscopy and Magic Trapping of Microwave-Shielded NaCs Molecules.

We report on the optical polarizability of microwave-shielded ultracold NaCs molecules in an optical dipole trap. While dressing a pair of rotational states with a microwave field, we observe a marked dependence of the optical polarizability on the intensity and detuning of the dressing field. To precisely characterize differential energy shifts between dressed rotational states, we establish dressed-state spectroscopy.

Three-Body Recombination of Ultracold Microwave-Shielded Polar Molecules.

A combined experimental and theoretical study is carried out on the three-body recombination process in a gas of microwave-shielded polar molecules. For ground-state polar molecules dressed with a strong microwave field, field-linked bound states can appear in the intermolecular potential. We model three-body recombination into such bound states using classical trajectory calculations.

Developing a novel model for predicting overall survival in late-onset colon adenocarcinoma patients based on LODDS: a study based on the SEER database and external validation.

Aim: To construct a predictive model based on the LODDS stage established for patients with late-onset colon adenocarcinoma to enhance survival stratification.

Methods: Late-onset colon adenocarcinoma data were obtained from the public database. After determining the optimal LODDS truncation value for the training set via X-tile software, we created a new staging system by integrating the T stage and M stage.

Safety and efficacy of selective RIPK1 inhibitor SIR1-365 in hospitalized patients with severe COVID-19: A multicenter, randomized, double-blind, phase 1b trial.

Background: Receptor-interacting protein kinase 1 (RIPK1), a serine/threonine protein kinase, is mainly activated by pro-inflammatory cytokines and pathogens, including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and its activation could result in apoptosis, necroptosis, or inflammation. This study was conducted to evaluate the safety and efficacy of a potent and selective inhibitor of RIPK1, SIR1-365, in hospitalized patients with severe coronavirus disease 2019 (COVID-19).

Methods: This multicenter, randomized, double-blind, phase 1b study screened patients from December 18, 2020 until November 27, 2021.

Machine learning based models for predicting presentation delay risk among gastric cancer patients.

Objective: Presentation delay of cancer patients prevents the patient from timely diagnosis and treatment leading to poor prognosis. Predicting the risk of presentation delay is crucial to improve the treatment outcomes. This study aimed to develop and validate prediction models of presentation delay risk in gastric cancer patients by using various machine learning models.