Development of a deep-learning model tailored for HER2 detection in breast cancer to aid pathologists in interpreting HER2-low cases.

Aims: Over 50% of breast cancer cases are "Human epidermal growth factor receptor 2 (HER2) low breast cancer (BC)", characterized by HER2 immunohistochemistry (IHC) scores of 1+ or 2+ alongside no amplification on fluorescence in situ hybridization (FISH) testing. The development of new anti-HER2 antibody-drug conjugates (ADCs) for treating HER2-low breast cancers illustrates the importance of accurately assessing HER2 status, particularly HER2-low breast cancer. In this study we evaluated the performance of a deep-learning (DL) model for the assessment of HER2, including an assessment of the causes of discordances of HER2-Null between a pathologist and the DL model.

Rare-Earth-Mediated Optomechanical System in the Reversed Dissipation Regime.

Strain-mediated interaction between phonons and telecom photons is demonstrated using excited states of erbium ions embedded in a mechanical resonator. Owing to the extremely long-lived nature of rare-earth ions, the dissipation rate of the optical resonance falls below that of the mechanical one. Thus, a "reversed dissipation regime" is achieved in the optical frequency region.

When LC-HRMS metabolomics gets ISO17025 accredited and ready for official controls - application to the screening of forbidden compounds in livestock.

Within the particular context of controlling chemical residues in food, an alternative to targeted approaches has emerged; it consists in the characterisation of physiological perturbations induced upon exposure of animals to a given chemical substance/class of substances to highlight suitable biomarkers addressing safety and/or regulatory issues. Metabolomics in particular has been investigated in the hope of identifying such biomarkers, and a range of studies have demonstrated the efficiency of the strategy. Until very recently, steps remained to be taken towards official or commercial implementation of corresponding tools.