Serial X-ray liquidography: multi-dimensional assay framework for exploring biomolecular structural dynamics with microgram quantities

Abstract Understanding protein structure and kinetics under physiological conditions is crucial for elucidating complex biological processes. While time-resolved (TR) techniques have advanced to track molecular actions, their practical application in biological reactions is often confined to reversible photoreactions within limited experimental parameters due to inefficient sample utilization and inflexibility of experimental setups. Here, we introduce serial X-ray liquidography (SXL), a technique that combines time-resolved X-ray liquidography with a fixed target of serially arranged microchambers. SXL breaks through the previously mentioned barriers, enabling microgram-scale TR studies of both irreversible and reversible reactions of even a non-photoactive protein. We demonstrate its versatility in studying a wide range of biological reactions, highlighting its potential as a flexible and multi-dimensional assay framework for kinetic and structural characterization. Leveraging X-ray free-electron lasers and micro-focused X-ray pulses promises further enhancements in both temporal resolution and minimizing sample quantity. SXL offers unprecedented insights into the structural and kinetic landscapes of molecular actions, paving the way for a deeper understanding of complex biological processes

Random Sets Unify, Explain, And Aid Known Uncertainty Methods In Expert Systems

. Numerous formalisms have been proposed for representing and processing uncertainty in expert systems. Several of these formalisms are somewhat ad hoc, in the sense that some of their formulas seem to have been chosen rather arbitrarily. In this paper, we show that random sets provide a natural general framework for describing uncertainty, a framework in which many existing formalisms appear as particular cases. This interpretation of known formalisms (e.g., of fuzzy logic) in terms of random sets enables us to justify many "ad hoc" formulas. In some cases, when several alternative formulas have been proposed, random sets help to choose the best ones (in some reasonable sense). One of the main objectives of expert systems is not only to describe the current state of the world, but also to provide us with reasonable actions. The simplest case is when we have the exact objective function. In this case, random sets can help in choosing the proper method of "fuzzy optimization." As a t..