Accurate, Uncertainty-Aware Classification of Molecular Chemical Motifs from Multimodal X-ray Absorption Spectroscopy.

Accurate classification of molecular chemical motifs from experimental measurement is an important problem in molecular physics, chemistry, and biology. In this work, we present neural network ensemble classifiers for predicting the presence (or lack thereof) of 41 different chemical motifs on small molecules from simulated C, N, and O K-edge X-ray absorption near-edge structure (XANES) spectra. Our classifiers not only achieve class-balanced accuracies of more than 0.95 but also accurately quantify uncertainty. We also show that including multiple XANES modalities improves predictions notably on average, demonstrating a "multimodal advantage" over any single modality. In addition to structure refinement, our approach can be generalized to broad applications with molecular design pipelines.

In Situ Insights into Cathode Calcination for Predictive Synthesis: Kinetic Crystallization of LiNiO2 from Hydroxides.

Calcination is a solid-state synthesis process widely deployed in battery cathode manufacturing. However, its inherent complexity associated with elusive intermediates hinders the predictive synthesis of high-performance cathode materials. Here, correlative in situ X-ray absorption/scattering spectroscopy is used to investigate the calcination of nickel-based cathodes, focusing specifically on the archetypal LiNiO2 from Ni(OH)2. Combining in situ observation with data-driven analysis reveals concurrent lithiation and dehydration of Ni(OH)2 and consequently, the low-temperature crystallization of layered LiNiO2 alongside lithiated rocksalts. Following early nucleation, LiNiO2 undergoes sluggish crystallization and structural ordering while depleting rocksalts; ultimately, it turns into a structurally-ordered layered phase upon full lithiation but remains small in size. Subsequent high-temperature sintering induces rapid crystal growth, accompanied by undesired delithiation and structural degradation. These observations are further corroborated by mesoscale modeling, emphasizing that, even though calcination is thermally driven and favors transformation towards thermodynamically equilibrium phases, the actual phase propagation and crystallization can be kinetically tuned via lithiation, providing freedom for structural and morphological control during cathode calcination.

Probing Oxidation-Driven Amorphized Surfaces in a Ta(110) Film for Superconducting Qubit.

Recent advances in superconducting qubit technology have led to significant progress in quantum computing, but the challenge of achieving a long coherence time remains. Despite the excellent lifetime performance that tantalum (Ta) based qubits have demonstrated to date, the majority of superconducting qubit systems, including Ta-based qubits, are generally believed to have uncontrolled surface oxidation as the primary source of the two-level system loss in two-dimensional transmon qubits. Therefore, atomic-scale insight into the surface oxidation process is needed to make progress toward a practical quantum processor. In this study, the surface oxidation mechanism of native Ta films and its potential impact on the lifetime of superconducting qubits were investigated using advanced scanning transmission electron microscopy (STEM) techniques combined with density functional theory calculations. The results suggest an atomistic model of the oxidized Ta(110) surface, showing that oxygen atoms tend to penetrate the Ta surface and accumulate between the two outermost Ta atomic planes; oxygen accumulation at the level exceeding a 1:1 O/Ta ratio drives disordering and, eventually, the formation of an amorphous Ta2O5 phase. In addition, we discuss how the formation of a noninsulating ordered TaO1-δ (δ < 0.1) suboxide layer could further contribute to the losses of superconducting qubits. Subsurface oxidation leads to charge redistribution and electric polarization, potentially causing quasiparticle loss and decreased current-carrying capacity, thus affecting superconducting qubit coherence. The findings enhance the comprehension of the realistic factors that might influence the performance of superconducting qubits, thus providing valuable guidance for the development of future quantum computing hardware.

Effect of stem cell conditional medium-loading adhesive hydrogel on TGF-ß1-induced endometrial stromal cell fibrosis.

Introduction: Uterine adhesion (IUA) is a severe complication that results from uterine operations or uterine infections. Hysteroscopy is considered the gold standard for the diagnosis and treatment of uterine adhesions. Yet, this invasive procedure leads to re-adhesions after hysteroscopic treatment. Hydrogels loading functional additives (e.g., placental mesenchymal stem cells (PC-MSCs)) that can act as physical barriers and promote endometrium regeneration are a good solution. However, traditional hydrogels lack tissue adhesion which makes them unstable under a rapid turnover of the uterus, and PC-MSCs have biosafety risks when used as functional additives. Methods: In this study, we coupled an adhesive hydrogel with a PC-MSCs conditioned medium (CM) to form a hybrid of gel and functional additives (CM/Gel-MA). Results and Discussion: Our experiments show that CM/Gel-MA enhances the activity of endometrial stromal cells (ESCs), promotes cell proliferation, and reduces the expression of α-SMA, collagen I, CTGF, E-cadherin, and IL-6, which helps to reduce the inflammatory response and inhibit fibrosis. We conclude that CM/Gel-MA can more potentially prevent IUA by combining the physical barriers from adhesive hydrogel and functional promotion from CM.

Deciphering phase evolution in complex metal oxide thin films via high-throughput materials synthesis and characterization.

Discovery of structure-property relationships in thin film alloys of complex metal oxides enabled by high-throughput materials synthesis and characterization facilities is demonstrated here with a case-study. Thin films of binary transition metal oxides (Ti-Zn) are prepared by pulsed laser deposition with continuously varying Ti:Zn ratio, creating combinatorial samples for exploration of the properties of this material family. The atomic structure and electronic properties are probed by spatially resolved techniques including x-ray absorption near edge structures (XANES) and x-ray fluorescence (XRF) at the Ti and Zn K-edge, x-ray diffraction, and spectroscopic ellipsometry. The observed properties as a function of Ti:Zn ratio are resolved into mixtures of five distinguishable phases by deploying multivariate curve resolution analysis on the XANES spectral series, under constraints set by results from the other characterization techniques. First-principles computations based on density function theory connect the observed properties of each distinct phase with structural and spectral characteristics of crystalline polymorphs of Ti-Zn oxide. Continuous tuning of the optical absorption edge as a function of Ti:Zn ratio, including the unusual observation of negative optical bowing, exemplifies a functional property of the film correlated to the phase evolution.

PolyODENet: Deriving mass-action rate equations from incomplete transient kinetics data.

Kinetics of a reaction network that follows mass-action rate laws can be described with a system of ordinary differential equations (ODEs) with polynomial right-hand side. However, it is challenging to derive such kinetic differential equations from transient kinetic data without knowing the reaction network, especially when the data are incomplete due to experimental limitations. We introduce a program, PolyODENet, toward this goal. Based on the machine-learning method Neural ODE, PolyODENet defines a generative model and predicts concentrations at arbitrary time. As such, it is possible to include unmeasurable intermediate species in the kinetic equations. Importantly, we have implemented various measures to apply physical constraints and chemical knowledge in the training to regularize the solution space. Using simple catalytic reaction models, we demonstrate that PolyODENet can predict reaction profiles of unknown species and doing so even reveal hidden parts of reaction mechanisms.

Smart-ORF: a single-molecule method for accessing ribosome dynamics in both upstream and main open reading frames.

Upstream open reading frame (uORF) translation disrupts scanning 43S flux on mRNA and modulates main open reading frame (mORF) translation efficiency. Current tools, however, have limited access to ribosome dynamics in both upstream and main ORFs of an mRNA. Here, we develop a new two-color in vitro fluorescence assay, Smart-ORF, that monitors individual uORF and mORF translation events in real-time with single-molecule resolution. We demonstrate the utility of Smart-ORF by applying it to uORF-encoded arginine attenuator peptide (AAP)-mediated translational regulation. The method enabled quantification of uORF and mORF initiation efficiencies, 80S dwell time, polysome formation, and the correlation between uORF and mORF translation dynamics. Smart-ORF revealed that AAP-mediated 80S stalling in the uORF stimulates the uORF initiation efficiency and promotes clustering of slower uORF-translating ribosomes. This technology provides a new tool that can reveal previously uncharacterized dynamics of uORF-containing mRNA translation.

An In Vitro Single-Molecule Imaging Assay for the Analysis of Cap-Dependent Translation Kinetics.

Cap-dependent protein synthesis is the predominant translation pathway in eukaryotic cells. While various biochemical and genetic approaches have allowed extensive studies of cap-dependent translation and its regulation, high resolution kinetic characterization of this translation pathway is still lacking. Recently, we developed an in vitro assay to measure cap-dependent translation kinetics with single-molecule resolution. The assay is based on fluorescently labeled antibody binding to nascent epitope-tagged polypeptide. By imaging the binding and dissociation of antibodies to and from nascent peptide-ribosome-mRNA complexes, the translation progression on individual mRNAs can be tracked. Here, we present a protocol for establishing this assay, including mRNA and PEGylated slide preparations, real-time imaging of translation, and analysis of single molecule trajectories. This assay enables tracking of individual cap-dependent translation events and resolves key translation kinetics, such as initiation and elongation rates. The assay can be widely applied to distinct translation systems and should broadly benefit in vitro studies of cap-dependent translation kinetics and translational control mechanisms.

LncRNA SNHG8 accelerates proliferation and inhibits apoptosis in HPV-induced cervical cancer through recruiting EZH2 to epigenetically silence RECK expression.

Infection of human papillomaviruses (HPVs), such as subtypes HPV16 and HPV18 is carcinogenic to human and is prominent cause of HPV-positive cervical carcinoma (CC). A closer investigation into the mechanism of HPV-induced CC may stimulate the generation of an improved therapy treating cervical cancer. Our study herein interrogated the function of a small nucleolar RNA host gene 8 (SNHG8) in HPV-induced CC. As a result, a notable increase of SNHG8 in HPV-induced CC cells was found compared with HPV-negative CC cells. Functionally, it identified that SNHG8 aggravated the cell proliferation and migration in Cell Counting Kit-8 and transwell assays. Besides, flow cytometry apoptosis assay displayed that blockade of SNHG8 exacerbated apoptosis of HPV-positive CC cells. As detected by fluorescence in situ hybridization analysis and subcellular fractionation assay, SNHG8 was primarily expressed in the nucleus and exerted suppressive role on reversion inducing cysteine-rich protein with kazal motifs (RECK) expression, which implied a potential transcriptional regulation of SNHG8 on RECK level. Mechanically, SNHG8 was disclosed to interact with enhancer of zeste homolog 2 (EZH2) based on RNA immunoprecipitation assay. ChIP assay further unveiled the occupancy of EZH2 in the promoter region of RECK. An additional chromatin immunoprecipitation assay highlighted that SNHG8 intensified the enrichment of EZH2 and H3K27me3 in RECK promoter region. Altogether, it reflected that SNHG8 recruited EZH2 to downregulate RECK expression, leading to HPV-induced CC aggravation.

An in vitro single-molecule assay for eukaryotic cap-dependent translation initiation kinetics.

Eukaryotic mRNAs are predominantly translated via the cap-dependent pathway. Initiation is a rate-limiting step in cap-dependent translation and is the main target of translational control mechanisms. There is a lack of high-resolution techniques for characterizing the cap-dependent initiation kinetics. Here, we report an in vitro single-molecule assay that allows characterization of both initiation and peptide chain elongation kinetics for cap-dependent translation. Surprisingly, the histogram of the first-round initiation time is highly asymmetrical and spans a large time range that is several-fold greater than the average peptide synthesis time in translation reactions with a firefly luciferase-encoding mRNA. Both the histogram and single-molecule trajectories reveal an unexpected high-degree of asynchrony in translation activity between mRNA molecules. Furthermore, by inserting a small stem-loop (ΔG = -4.8 kcal/mol) in the middle of the mRNA 5' untranslated region (UTR), our assay robustly detects small changes in budding yeast initiation kinetics, which could not be resolved by bulk luminescence kinetics. Lastly, we demonstrate the general applicability of this assay to distinct cell-free translation systems by using extracts prepared from budding yeast, wheat germ, and rabbit reticulocyte lysates. This assay should facilitate mechanistic studies of eukaryotic cap-dependent translation initiation and translational control.

C-S Bonds in Sulfur-Embedded Graphene, Carbon Nanotubes, and Flake Graphite Cathodes for Lithium-Sulfur Batteries.

Lithium-sulfur (Li-S) batteries are excellent rechargeable battery candidates which are extraordinarily promising as they exhibit superior specific capacity and well-known energy density; they are cost-effective and environmentally benign. Nevertheless, a few technical issues pose a significant challenge on the path to industrial applications, namely, capacity fade and Coulombic efficiency decay, which are inherent in the soluble polysulfide shuttle effect during charge/discharge cycling. Carbon materials which have excellent conductive scaffold and flexible structure with a variety of morphologies can serve as a remedy to this issue. Herein, with a well-designed melt-diffusion procedure, we prepared three carbon-based sulfur-embedded cathodes with diverse structures [graphene, carbon nanotubes (CNTs), and flake graphite]. Sulfur loading varies between 60 and 73 wt %. Among these three carbon/S cathodes, beyond 100 cycles, the graphene/S cathode showed a discharge capacity of 840 mA h g-1 at 0.2 A g-1 current density and its average Coulombic efficiency was above 99.4%, demonstrating the best cycle stability and reversibility. While at a higher current rate, 1 A g-1, CNT/S reaches the best capacity of 518 mA h g-1 among these three cathodes, revealing excellent sulfur utilization under high rate conditions. The X-ray photo spectroscopy shows evidence for chemical bonding between graphene/CNTs surfaces and carbonyl, hydroxyl, and ether groups, resulting in well-confined polysulfides in the cathode side, which significantly restrain the movement of soluble polysulfide in the charging process and efficiently decreases the capacity fading of sulfur. This unique structure is a potential explanation for the outstanding electrochemical performance.

Suppressing serum response factor inhibits invasion in cervical cancer cell lines via regulating Egr­1 and epithelial-mesenchymal transition.

Serum response factor (SRF) is a transcription factor that has important roles in tumor progression. However, its role in cervical cancer cell proliferation and invasion remains unclear. The present study revealed that SRF silencing constrained cervical cancer cell proliferation and invasion via controlling early growth response­1 (Egr­1). The results demonstrated that SRF was significantly increased in cervical cancer tissues and cell lines, compared with normal. Suppressing SRF, by using a loss­of­function experiment, constrained cervical cancer cell proliferation, invasion, and epithelial­mesenchymal transition. Furthermore, SRF knockdown significantly downregulated Egr­1 expression in cervical cancer cell lines, and overexpression of Egr­1 reversed the effect of SRF on cell proliferation, invasion, and epithelial­mesenchymal transition. Therefore, SRF may control cell proliferation and invasion by regulating Egr­1 in cervical cancer.

Elucidating Solvation Structures for Rational Design of Multivalent Electrolytes-A Review.

Fundamental molecular-level understanding of functional properties of liquid solutions provides an important basis for designing optimized electrolytes for numerous applications. In particular, exhaustive knowledge of solvation structure, stability, and transport properties is critical for developing stable electrolytes for fast-charging and high-energy-density next-generation energy storage systems. Accordingly, there is growing interest in the rational design of electrolytes for beyond lithium-ion systems by tuning the molecular-level interactions of solvate species present in the electrolytes. Here we present a review of the solvation structure of multivalent electrolytes and its impact on the electrochemical performance of these batteries. A direct correlation between solvate species present in the solution and macroscopic properties of electrolytes is sparse for multivalent electrolytes and contradictory results have been reported in the literature. This review aims to illustrate the current understanding, compare results, and highlight future needs and directions to enable the deep understanding needed for the rational design of improved multivalent electrolytes.

Materials Genomics Screens for Adaptive Ion Transport Behavior by Redox-Switchable Microporous Polymer Membranes in Lithium-Sulfur Batteries.

Selective ion transport across membranes is critical to the performance of many electrochemical energy storage devices. While design strategies enabling ion-selective transport are well-established, enhancements in membrane selectivity are made at the expense of ionic conductivity. To design membranes with both high selectivity and high ionic conductivity, there are cues to follow from biological systems, where regulated transport of ions across membranes is achieved by transmembrane proteins. The transport functions of these proteins are sensitive to their environment: physical or chemical perturbations to that environment are met with an adaptive response. Here we advance an analogous strategy for achieving adaptive ion transport in microporous polymer membranes. Along the polymer backbone are placed redox-active switches that are activated in situ, at a prescribed electrochemical potential, by the device's active materials when they enter the membrane's pore. This transformation has little influence on the membrane's ionic conductivity; however, the active-material blocking ability of the membrane is enhanced. We show that when used in lithium-sulfur batteries, these membranes offer markedly improved capacity, efficiency, and cycle-life by sequestering polysulfides in the cathode. The origins and implications of this behavior are explored in detail and point to new opportunities for responsive membranes in battery technology development.

Group additivity-Pourbaix diagrams advocate thermodynamically stable nanoscale clusters in aqueous environments.

The characterization of water-based corrosion, geochemical, environmental and catalytic processes rely on the accurate depiction of stable phases in a water environment. The process is aided by Pourbaix diagrams, which map the equilibrium solid and solution phases under varying conditions of pH and electrochemical potential. Recently, metastable or possibly stable nanometric aqueous clusters have been proposed as intermediate species in non-classical nucleation processes. Herein, we describe a Group Additivity approach to obtain Pourbaix diagrams with full consideration of multimeric cluster speciation from computations. Comparisons with existing titration results from experiments yield excellent agreement. Applying this Group Additivity-Pourbaix approach to Group 13 elements, we arrive at a quantitative evaluation of cluster stability, as a function of pH and concentration, and present compelling support for not only metastable but also thermodynamically stable multimeric clusters in aqueous solutions.

Machine Learning Estimation of Atom Condensed Fukui Functions.

To enable the fast estimation of atom condensed Fukui functions, machine learning algorithms were trained with databases of DFT pre-calculated values for ca. 23,000 atoms in organic molecules. The problem was approached as the ranking of atom types with the Bradley-Terry (BT) model, and as the regression of the Fukui function. Random Forests (RF) were trained to predict the condensed Fukui function, to rank atoms in a molecule, and to classify atoms as high/low Fukui function. Atomic descriptors were based on counts of atom types in spheres around the kernel atom. The BT coefficients assigned to atom types enabled the identification (93-94 % accuracy) of the atom with the highest Fukui function in pairs of atoms in the same molecule with differences ≥0.1. In whole molecules, the atom with the top Fukui function could be recognized in ca. 50 % of the cases and, on the average, about 3 of the top 4 atoms could be recognized in a shortlist of 4. Regression RF yielded predictions for test sets with R(2) =0.68-0.69, improving the ability of BT coefficients to rank atoms in a molecule. Atom classification (as high/low Fukui function) was obtained with RF with sensitivity of 55-61 % and specificity of 94-95 %.

Toward Accurate Modeling of the Effect of Ion-Pair Formation on Solute Redox Potential.

A scheme to model the dependence of a solute redox potential on the supporting electrolyte is proposed, and the results are compared to experimental observations and other reported theoretical models. An improved agreement with experiment is exhibited if the effect of the supporting electrolyte on the redox potential is modeled through a concentration change induced via ion pair formation with the salt, rather than by only considering the direct impact on the redox potential of the solute itself. To exemplify the approach, the scheme is applied to the concentration-dependent redox potential of select molecules proposed for nonaqueous flow batteries. However, the methodology is general and enables rational computational electrolyte design through tuning of the operating window of electrochemical systems by shifting the redox potential of its solutes; including potentially both salts as well as redox active molecules.

Proximal disruptor aided ligation (ProDAL) of kilobase-long RNAs.

RNA with site-specific modification is a useful tool for RNA biology studies. However, generating kilobase (kb) -long RNA with internal modification at a site distant from RNA termini remains challenging. Here we report an enhanced splint ligation technique, proximal disruptor aided ligation (ProDAL), which allows adequate efficiency toward this purpose. The key to our approach is using multiple DNA oligonucleotides, 'proximal disruptors', to target the RNA substrate sequence next to the ligation site. The binding of disruptors helps to free the ligation site from intramolecular RNA basepairing, and consequently promotes more efficient formation of the pre-ligation complex and a higher overall ligation yield. We used naturally occurring 1.0 kb renilla and 1.9 kb firefly luciferase mRNA sequences to test the efficacy of our approach. ProDAL yielded 9-14% efficiency for the ligation between two RNA substrates, both of which were between 414 and 1313 nucleotides (nt) long. ProDAL also allowed similarly high efficiency for generating kb-long RNA with site-specific internal modification by a simple three-part ligation between two long RNA substrates and a modification-carrying RNA oligonucleotide. In comparison, classical splint ligation yielded a significantly lower efficiency of 0-2% in all cases. We expect that ProDAL will benefit studies involving kb-long RNAs, including translation, long non-coding RNAs, RNA splicing and modification, and large ribonucleoprotein complexes.