Precise Measurement of the e^{+}e^{-}→D_{s}^{+}D_{s}^{-} Cross Section at Center-of-Mass Energies from Threshold to 4.95 GeV.

Using the e^{+}e^{-} collision data collected with the BESIII detector operating at the BEPCII collider, at center-of-mass energies from the threshold to 4.95 GeV, we present precise measurements of the cross section for the process e^{+}e^{-}→D_{s}^{+}D_{s}^{-} using a single-tag method. The resulting cross section line shape exhibits several new structures, thereby offering an input for a future coupled-channel analysis and model tests, which are critical to understand vector charmonium-like states with masses between 4 and 5 GeV.

Measurement of Λ_{b}^{0}, Λ_{c}^{+}, and Λ Decay Parameters Using Λ_{b}^{0}→Λ_{c}^{+}h^{-} Decays.

A comprehensive study of the angular distributions in the bottom-baryon decays Λ_{b}^{0}→Λ_{c}^{+}h^{-}(h=π,K), followed by Λ_{c}^{+}→Λh^{+} with Λ→pπ^{-} or Λ_{c}^{+}→pK_{S}^{0} decays, is performed using a data sample of proton-proton collisions corresponding to an integrated luminosity of 9  fb^{-1} collected by the LHCb experiment at center-of-mass energies of 7, 8, and 13 TeV. The decay parameters and the associated charge-parity (CP) asymmetries are measured, with no significant CP violation observed. For the first time, the Λ_{b}^{0}→Λ_{c}^{+}h^{-} decay parameters are measured.

Sensitivity to Environmental Stress and Adversity and Lung Cancer.

Importance: Sensitivity to environmental stress and adversity may influence lung cancer risk, highlighting a critical link between psychosocial factors and cancer etiology.

Objective: To evaluate whether genetically estimated sensitivity to environmental stress and adversity is associated with lung cancer risk.

Design, Setting, And Participants: Data were obtained from a genome-wide association study identifying 37 independent genetic variants strongly associated with sensitivity to environmental stress and adversity and a cross-ancestry genome-wide meta-analysis from the International Lung Cancer Consortium.

CD155 promotes the advancement of hepatocellular carcinoma by suppressing the p53-mediated ferroptosis via interacting with CD96.

This work researched the influence and mechanism of CD155 on hepatocellular carcinoma advancement. CD155 expression and its effect on survival of hepatocellular carcinoma patients were analyzed based on the GEPIA2 database. String software predicted the interacting between CD155 and CD96, which was further verified by co-immunoprecipitation experiment.

Generative artificial intelligence enables the generation of bone scintigraphy images and improves generalization of deep learning models in data-constrained environments.

Purpose: Advancements of deep learning in medical imaging are often constrained by the limited availability of large, annotated datasets, resulting in underperforming models when deployed under real-world conditions. This study investigated a generative artificial intelligence (AI) approach to create synthetic medical images taking the example of bone scintigraphy scans, to increase the data diversity of small-scale datasets for more effective model training and improved generalization.

Methods: We trained a generative model on Tc-bone scintigraphy scans from 9,170 patients in one center to generate high-quality and fully anonymized annotated scans of patients representing two distinct disease patterns: abnormal uptake indicative of (i) bone metastases and (ii) cardiac uptake indicative of cardiac amyloidosis.