The Cellular Thermal Shift Assay (CETSA) enables the study of protein-ligand interactions in a cellular context. It provides valuable information on the binding affinity and specificity of both small and large molecule ligands in a relevant physiological context, hence forming a unique tool in drug discovery. Though high-throughput lab protocols exist for scaling up CETSA, subsequent data analysis and quality control remain laborious and limit experimental throughput. Here, we introduce a scalable and robust data analysis workflow which allows integration of CETSA into routine high throughput screening (HT-CETSA). This new workflow automates data analysis and incorporates quality control (QC), including outlier detection, sample and plate QC, and result triage. We describe the workflow and show its robustness against typical experimental artifacts, show scaling effects, and discuss the impact of data analysis automation by eliminating manual data processing steps.

The progression of type II diabetes (T2D) is characterized by a complex and highly variable loss of beta-cell mass, resulting in impaired insulin secretion. Many T2D drug discovery efforts aimed at discovering molecules that can protect or restore beta-cell mass and function have been developed using limited beta-cell lines and primary rodent/human pancreatic islets. Various high-throughput screening methods have been used in the context of drug discovery, including luciferase-based reporter assays, glucose-stimulated insulin secretion, and high-content screening. In this context, a cornerstone of small molecule discovery has been the use of immortalized rodent beta-cell lines. Although insightful, this usage has led to a more comprehensive understanding of rodent beta-cell proliferation pathways rather than their human counterparts. Advantages gained in enhanced physiological relevance are offered by three-dimensional (3D) primary islets and pseudoislets in contrast to monolayer cultures, but these approaches have been limited to use in low-throughput experiments. Emerging methods, such as high-throughput 3D islet imaging coupled with machine learning, aim to increase the feasibility of integrating 3D microtissue structures into high-throughput screening. This review explores the current methods used in high-throughput screening for small molecule modulators of beta-cell mass and function, a potentially pivotal strategy for diabetes drug discovery.

This chapter attempts to provide an all-round picture of a dynamic and major branch of modern endocrinology, i.e. the gastrointestinal endocrinology. The advances during the last half century in our understanding of the dimensions and diversity of gut hormone biology - inside as well as outside the digestive tract - are astounding. Among major milestones are the dual brain-gut relationship, i.e. the comprehensive expression of gastrointestinal hormones as potent transmitters in central and peripheral neurons; the hormonal signaling from the enteroendocrine cells to the brain and other extraintestinal targets; the role of gut hormones as growth and fertility factors; and the new era of gut hormone-derived drugs. Accordingly, gastrointestinal hormones have pathogenetic roles in major metabolic disorders (diabetes mellitus and obesity); in tumor development (common cancers, sarcomas, and neuroendocrine tumors); and in cerebral diseases (anxiety, panic attacks, and probably eating disorders). Such clinical aspects require accurate pathogenetic and diagnostic measurements of gastrointestinal hormones - an obvious responsibility for clinical chemistry/biochemistry. In order to obtain a necessary insight into today\'s gastrointestinal endocrinology, the chapter will first describe the advances in gastrointestinal endocrinology in a historical context. The history provides a background for the subsequent description of the present biology of gastrointestinal hormones, and its biomedical consequences - not least for clinical chemistry/biochemistry with its specific responsibility for selection of appropriate assays and reliable measurements.

Thrombin is the pivotal enzyme in the biochemistry of secondary hemostasis crucial to maintaining homeostasis of hemostasis. In contrast to routine coagulation tests (PT or aPTT) or procoagulant or anticoagulant factor assays (e.g. fibrinogen, factor VIII, antithrombin or protein C), the thrombin generation assay (TGA), also named thrombin generation test (TGT) is a so-called \"global assay\" that provides a picture of the hemostasis balance though a continuous and simultaneous measurement of thrombin formation and inhibition. First described in the early 1950s, as a manual assay, efforts have been made in order to standardize and automate the assay to offer researchers, clinical laboratories and the pharmaceutical industry a versatile tool covering a wide range of clinical and non-clinical applications. This review describes technical options offered to properly run TGA, including a review of preanalytical and analytical items, performance, interpretation, and applications in physiology research and pharmacy.