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https://www.selleckchem.com/products/trastuzumab-emtansine-t-dm1-.html Currently, due to the special functions and potential application values, rare sugars become the hot topic in carbohydrate fields. L-Ribulose, an isomer of L-ribose, is an expensive rare ketopentose. As an important precursor for other rare sugars and L-nucleoside analogue synthesis, L-ribulose attracts more and more attention in recent days. Compared with complicated chemical synthesis, the bioconversion method becomes a good alternative approach to L-ribulose production. Generally, the bioconversion of L-ribulose was linked with ribitol, L-arabinose, L-ribose, L-xylulose, and L-arabitol. Herein, an overview of recent advances in the metabolic pathway, chemical synthesis, bioproduction of L-ribulose, and the potential application of L-ribulose is reviewed in detail in this paper. KEY POINTS 1. L-Ribulose is a rare sugar and the key precursor for L-ribose production. 2. L-Ribulose is the starting material for L-nucleoside derivative synthesis. 3. Chemical synthesis, bioproduction, and applications of L-ribulose are reviewed.Machine learning (ML) and deep learning (DL) systems, currently employed in medical image analysis, are data-driven models often considered as black boxes. However, improved transparency is needed to translate automated decision-making to clinical practice. To this aim, we propose a strategy to open the black box by presenting to the radiologist the annotated cases (ACs) proximal to the current case (CC), making decision rationale and uncertainty more explicit. The ACs, used for training, validation, and testing in supervised methods and for validation and testing in the unsupervised ones, could be provided as support of the ML/DL tool. If the CC is localised in a classification space and proximal ACs are selected by proper metrics, the latter ones could be shown in their original form of images, enriched with annotation to radiologists, thus allowing immediate interpretation

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