Success Criteria Analysis using Deep Neural Network and Monte Carlo Dropout for Dynamic Probabilistic Safety Assessment

Dynamic probabilistic safety assessment (PSA) performs analysis and simulation of a large number of scenario sequences, unlike legacy PSA. When performing safety assessments that reflect dynamic characteristics, success criteria such as allowable time are of great importance. However, numerous scenarios have different success criteria. When a lot of variables that affect the state of a power plant change, success criteria can also change significantly. Therefore, when performing dynamic PSA and interpreting the results, if we try to assign meaning to each scenario (simulation calculation), we must find success criteria for each scenario. On the other hand, if we try to assign meaning by merging scenarios, we need to derive the range (bound) of allowable time. Therefore, we must find success criteria for a large number of scenarios that are affected by numerous variables. Thus, our research team proposes a study to explore success criteria for dynamic PSA. This study utilizes an optimization algorithm called Deep-SAILs. By using Monte-Carlo dropout and deep-learning, this algorithm efficiently finds the limit surface to determine success criteria for numerous scenarios. To do this, we need to perform scenario analysis that is suitable for the purpose of conducting dynamic PSA. During this process, we extract variables that require analysis and have a significant impact, set their bounds, and find the limit surface called success criteria. Moreover, the criteria can be any parameter in the simulation system code such like peak cladding temperature, pressurizer pressure. To efficiently find the limit surface, we connect system codes like MAAP with Deep-SAILs to perform simulation and inference model calculations. This research aims to perform more complete safety assessments by deriving scenario-specific success criteria that sufficiently reflect dynamic meaning, thereby reducing the number of simulations needed to interpret the results of dynamic P

A competitive and reversible deactivation approach to catalysis-based quantitative assays

Catalysis-based signal amplification makes optical assays highly sensitive and widely useful in chemical and biochemical research. However, assays must be fine-tuned to avoid signal saturation, substrate depletion and nonlinear performance. Furthermore, once stopped, such assays cannot be restarted, limiting the dynamic range to two orders of magnitude with respect to analyte concentrations. In addition, abundant analytes are difficult to quantify under catalytic conditions due to rapid signal saturation. Herein, we report an approach in which a catalytic reaction competes with a concomitant inactivation of the catalyst or consumption of a reagent required for signal generation. As such, signal generation proceeds for a limited time, then autonomously and reversibly stalls. In two catalysis-based assays, we demonstrate restarting autonomously stalled reactions, enabling accurate measurement over five orders of magnitude, including analyte levels above substrate concentration. This indicates that the dynamic range of catalysis-based assays can be significantly broadened through competitive and reversible deactivation

Rapid-Response Nitrite Probes: Intramolecular Griess Reaction for Nitrite Detection at Picogram Level

Nitrite is abundantly used not only in the food industry but also in various chemical reactions such as diazotization to furnish azo-dye compounds and the Sandmeyer reaction. When a secondary amine is in the presence of nitrite, residual levels of nitrite ions can potentially form corresponding N-nitrosamines, many of which are known to be carcinogenic. The carcinogenicity concerns with N-nitrosamines resulted in worldwide recalls of numerous marketed pharmaceutical products since 2018. Therefore, the residual nitrite assay is a critical part of N-nitrosamine risk assessment, as many components present in drug products including not only the drug substance but also excipients can be a potential source of nitrite ions. While ion chromatography serves as a primary analytical tool for the nitrite ion assay, leveraging the Griess reaction shows several benefits over ion chromatography, which includes rapid and visible responses as well as flexibility of sample preparations in organic solvent. In order to simplify the Griess reaction method and enhance reactivity toward the nitrite ion, a series of probe molecules was designed and synthesized. Upon exposure to the nitrite ion, molecular probes undergo diazotization followed by intramolecular cyclization to form benzo[c]cinnoline, which elicits dramatic absorption and emission changes as a signal readout for the nitrite assay. The reactivity toward the nitrite ion depends on nucleophilicity as well as electron-withdrawing/donating properties of substituents on probe molecules. Among a series of probe molecules, comparative kinetic studies revealed that the para-sulfonamide-substituted molecule (probe 1) has the highest reactivity with no-detectable side reaction. With probe 1, method validation was performed with two representative excipients, microcrystalline cellulose and dicalcium phosphate dihydrate, which demonstrated excellent accuracy, linearity, precision, and multilevel spike/recovery as well as very low detection limit (sub-parts-per-billion level) when coupled with a fluorescence detector. This new probe molecule offers low detection limits and wide flexibility in terms of sample preparation in a higher composition of organic solvent. Such flexibility of solvent choice enables a broader application of the method to any components in drug products including API, process intermediates, and excipients

Turn-On Fluorescence Detection of Cyanide in Water: Activation of Latent Fluorophores through Remote Hydrogen Bonds That Mimic Peptide β-Turn Motif

A molecular probe was prepared that selectively responds to cyanide in aqueous solutions by fluorescence enhancement. Using the peptide β-turn as a structural template, we designed a series of diphenylacetylene derivatives in which the π-conjugated backbone was functionalized with an aldehyde group to render the molecule nonfluorescent. The N−H···O hydrogen bond across the 2,2′-functionalized diphenylacetylene turn motif activates the carbonyl group toward nucleophilic attack, and chemical transformation of this internal quencher site by reaction with CN− elicits a rapid (k = 72 M−1 s−1) enhancement in the emission at λmax = 375 nm. Tethering of an ammonium group to the hydrogen bond donor fragment significantly increased both the response kinetics and the intensity of the fluorescence signal. In addition to providing electrostatic attraction toward the CN− ion, this positively charged R-NH3+ fragment can engage in a secondary hydrogen bond to facilitate the formation of the cyanohydrin adduct responsible for the signaling event. The structurally optimized molecular probe 3 responds exclusively to μM-level cyanide in neutral aqueous solutions, with no interference from other common anions including F− and AcO−