Interatomic potentials for mixed oxide (MOX) nuclear fuels

We extend our recently developed interatomic potentials for UO_{2} to the mixed oxide fuel system (U,Pu,Np)O_{2}. We do so by fitting against an extensive database of ab initio results as well as to experimental measurements. The applicability of these interactions to a variety of mixed environments beyond the fitting domain is also assessed. The employed formalism makes these potentials applicable across all interatomic distances without the need for any ambiguous splining to the well-established short-range Ziegler-Biersack-Littmark universal pair potential. We therefore expect these to be reliable potentials for carrying out damage simulations (and Molecular Dynamics simulations in general) in nuclear fuels of varying compositions for all relevant atomic collision energies

Inferring phase transitions and critical exponents from limited observations with Thermodynamic Maps

Phase transitions are ubiquitous across life, yet hard to quantify and describe accurately. In this work, we develop an approach for characterizing generic attributes of phase transitions from very limited observations made deep within different phases' domains of stability. Our approach is called Thermodynamic Maps, which combines statistical mechanics and molecular simulations with score-based generative models. Thermodynamic Maps enable learning the temperature dependence of arbitrary thermodynamic observables across a wide range of temperatures. We show its usefulness by calculating phase transition attributes such as melting temperature, temperature-dependent heat capacities, and critical exponents. For instance, we demonstrate the ability of thermodynamic maps to infer the ferromagnetic phase transition of the Ising model, including temperature-dependent heat capacity and critical exponents, despite never having seen samples from the transition region. In addition, we efficiently characterize the temperature-dependent conformational ensemble and compute melting curves of the two RNA systems GCAA tetraloop and HIV-TAR, which are notoriously hard to sample due to glassy-like landscapes

Spontaneous Polarization in an Ultrathin Improper-Ferroelectric/Dielectric Bilayer in a Capacitor Structure at Cryogenic Temperatures

To determine the effect of depolarization and the critical thickness in improper-ferroelectric hexagonal-ferrite thin films, we investigate the polarization switching of a ferroelectric/dielectric bilayer in capacitor structures at 20 K. Experimentally, we show that the spontaneous polarization persists throughout the studied thickness range (3 to 80 unit cell), even with a thick (10-nm) dielectric layer, suggesting no practical thickness limit for applications. By fitting the effect of depolarization using the phenomenological theory, we show that the spontaneous polarization remains finite when the thickness of the ferroelectric layer approaches zero, providing a hint for the absence of critical thickness. We also find that the interfacial effects limit the multidomain formation and govern the polarization switching mechanisms

Generation of a Compendium of Transcription Factor Cascades and Identification of Potential Therapeutic Targets using Graph Machine Learning

Transcription factors (TFs) play a vital role in the regulation of gene expression thereby making them critical to many cellular processes. In this study, we used graph machine learning methods to create a compendium of TF cascades using data extracted from the STRING database. A TF cascade is a sequence of TFs that regulate each other, forming a directed path in the TF network. We constructed a knowledge graph of 81,488 unique TF cascades, with the longest cascade consisting of 62 TFs. Our results highlight the complex and intricate nature of TF interactions, where multiple TFs work together to regulate gene expression. We also identified 10 TFs with the highest regulatory influence based on centrality measurements, providing valuable information for researchers interested in studying specific TFs. Furthermore, our pathway enrichment analysis revealed significant enrichment of various pathways and functional categories, including those involved in cancer and other diseases, as well as those involved in development, differentiation, and cell signaling. The enriched pathways identified in this study may have potential as targets for therapeutic intervention in diseases associated with dysregulation of transcription factors. We have released the dataset, knowledge graph, and graphML methods for the TF cascades, and created a website to display the results, which can be accessed by researchers interested in using this dataset. Our study provides a valuable resource for understanding the complex network of interactions between TFs and their regulatory roles in cellular processes

Chikungunya virus infectivity, RNA replication and non-structural polyprotein processing depend on the nsP2 protease's active site cysteine residue

Chikungunya virus (CHIKV), genus Alphavirus, family Togaviridae, has a positive-stand RNA genome approximately 12 kb in length. In infected cells, the genome is translated into non-structural polyprotein P1234, an inactive precursor of the viral replicase, which is activated by cleavages carried out by the non-structural protease, nsP2. We have characterized CHIKV nsP2 using both cell-free and cell-based assays. First, we show that Cys478 residue in the active site of CHIKV nsP2 is indispensable for P1234 processing. Second, the substrate requirements of CHIKV nsP2 are quite similar to those of nsP2 of related Semliki Forest virus (SFV). Third, substitution of Ser482 residue, recently reported to contribute to the protease activity of nsP2, with Ala has almost no negative effect on the protease activity of CHIKV nsP2. Fourth, Cys478 to Ala as well as Trp479 to Ala mutations in nsP2 completely abolished RNA replication in CHIKV and SFV trans-replication systems. In contrast, trans-replicases with Ser482 to Ala mutation were similar to wild type counterparts. Fifth, Cys478 to Ala as well as Trp479 to Ala mutations in nsP2 abolished the rescue of infectious virus from CHIKV RNA transcripts while Ser482 to Ala mutation had no effect. Thus, CHIKV nsP2 is a cysteine protease.Peer reviewe

Circulating Tumor DNA Monitoring on Chemo-immunotherapy for Risk Stratification in Advanced Non-Small Cell Lung Cancer

PURPOSE: Chemoimmunotherapy (chemoIO) is a prevalent first-line treatment for advanced driver-negative non-small cell lung cancer (NSCLC), with maintenance therapy given after induction. However, there is significant clinical variability in the duration, dosing, and timing of maintenance therapy after induction chemoIO. We used circulating tumor DNA (ctDNA) monitoring to inform outcomes in patients with advanced NSCLC receiving chemoIO. EXPERIMENTAL DESIGN: This retrospective study included 221 patients from a phase III trial of atezolizumab+carboplatin+nab-paclitaxel versus carboplatin+nab-paclitaxel in squamous NSCLC (IMpower131). ctDNA monitoring used the FoundationOne Tracker involving comprehensive genomic profiling of pretreatment tumor tissue, variant selection using an algorithm to exclude nontumor variants, and multiplex PCR of up to 16 variants to detect and quantify ctDNA. RESULTS: ctDNA was detected (ctDNA+) in 96% of pretreatment samples (median, 93 mean tumor molecules/mL), and similar ctDNA dynamics were noted across treatment arms during chemoIO. ctDNA decrease from baseline to C4D1 was associated with improved outcomes across multiple cutoffs for patients treated with chemoIO. When including patients with missing plasma or ctDNA- at baseline, patients with ctDNA- at C4D1 (clearance), had more favorable progression-free survival (median 8.8 vs. 3.5 months; HR, 0.32;0.20-0.52) and OS (median not reached vs. 8.9 months; HR, 0.22; 0.12-0.39) from C4D1 than ctDNA+ patients. CONCLUSIONS: ctDNA monitoring during induction chemoIO can inform treatment outcomes in patients with advanced NSCLC. Importantly, monitoring remains feasible and informative for patients missing baseline ctDNA. ctDNA testing during induction chemoIO identifies patients at higher risk for disease progression and may inform patient selection for novel personalized maintenance or second-line treatment strategies

Design and Validation of Novel Chikungunya Virus Protease Inhibitors

Chikungunya virus (CHIKV; genus Alphavirus) is the causative agent of chikungunya fever. CHIKV replication can be inhibited by some broad-spectrum antiviral compounds; in contrast, there is very little information about compounds specifically inhibiting the enzymatic activities of CHIKV replication proteins. These proteins are translated in the form of a nonstructural (ns) P1234 polyprotein precursor from the CHIKV positive-strand RNA genome. Active forms of replicase enzymes are generated using the autoproteolytic activity of nsP2. The available three-dimensional (3D) structure of nsP2 protease has made it a target for in silico drug design; however, there is thus far little evidence that the designed compounds indeed inhibit the protease activity of nsP2 and/or suppress CHIKV replication. In this study, a set of 12 compounds, predicted to interact with the active center of nsP2 protease, was designed using target-based modeling. The majority of these compounds were shown to inhibit the ability of nsP2 to process recombinant protein and synthetic peptide substrates. Furthermore, all compounds found to be active in these cell-free assays also suppressed CHIKV replication in cell culture, the 50% effective concentration (EC50) of the most potent inhibitor being similar to 1.5 mu M. Analysis of stereoisomers of one compound revealed that inhibition of both the nsP2 protease activity and CHIKV replication depended on the conformation of the inhibitor. Combining the data obtained from different assays also indicates that some of the analyzed compounds may suppress CHIKV replication using more than one mechanism.Peer reviewe