Unraveling the Hydration Shell Structure and Dynamics of Group 10 Aqua Ions.

We present ab initio simulations based on subsystem DFT of group 10 aqua ions accurately compared against experimental data on hydration structure. Our simulations provide insights into the molecular structures and dynamics of hydration shells, offering recalibrated interpretations of experimental results. We observe a soft, but distinct second hydration shell in Palladium (Pd) due to a balance between thermal fluctuations, metal-water interactions, and hydrogen bonding. Nickel (Ni) and platinum (Pt) exhibit more rigid hydration shells. Notably, our simulations align with experimental findings for Pd, showing axial hydration marked by a broad peak at about 3 Å in the Pd-O radial distribution function, revising the previously sharp "mesoshell" prediction. We introduce the "hydrogen bond dome" concept to describe a resilient network of hydrogen-bonded water molecules around the metal, which plays a critical role in the axial hydration dynamics.

Accelerating Structural Optimization through Fingerprinting Space Integration on the Potential Energy Surface.

Structural optimization has been a crucial component in computational materials research, and structure predictions have relied heavily on this technique, in particular. In this study, we introduce a novel method that enhances the efficiency of local optimization by integrating extra fingerprint space into the optimization process. Our approach utilizes a mixed energy concept in the hyper potential energy surface (PES), combining real energy and a newly introduced fingerprint energy derived from the symmetry of the local atomic environment. This method strategically guides the optimization process toward high-symmetry, low-energy structures by leveraging the intrinsic symmetry of the atomic configurations. The effectiveness of our approach was demonstrated through structural optimizations of silicon, silicon carbide, and Lennard-Jones cluster systems. Our results show that the fingerprint space biasing technique significantly enhances the performance and probability of discovering energetically favorable, high-symmetry structures as compared to conventional optimizations. The proposed method is anticipated to streamline the search for new materials and facilitate the discovery of novel energetically favorable configurations.

Mesenchymal Stem Cells-Derived Exosomes Alleviate Acute Lung Injury by Inhibiting Alveolar Macrophage Pyroptosis.

Acute lung injury (ALI) is an important pathological process of acute respiratory distress syndrome, yet there are limited therapies for its treatment. Mesenchymal stem cells-derived exosomes (MSCs-Exo) have been shown to be effective in suppressing inflammation. However, the effects of MSCs-Exo on ALI and the underlying mechanisms have not been well elucidated. Our data showed that MSCs-Exo, but not exosomes derived from MRC-5 cells (MRC-5-Exo), which are human fetal lung fibroblast cells, significantly improved chest imaging, histological observations, alveolocapillary membrane permeability, and reduced inflammatory response in ALI mice model. According to miRNA sequencing and proteomic analysis of MSCs-Exo and MRC-5-Exo, MSCs-Exo may inhibit pyroptosis by miRNAs targeting caspase-1-mediated pathway, and by proteins with immunoregulation functions. Taken together, our study demonstrated that MSCs-Exo were effective in treating ALI by inhibiting the pyroptosis of alveolar macrophages and reducing inflammation response. Its mechanism may be through pyroptosis-targeting miRNAs and immunoregulating proteins delivered by MSCs-Exo. Therefore, MSCs-Exo may be a new treatment option in the early stage of ALI.

Bound-State Breaking and the Importance of Thermal Exchange-Correlation Effects in Warm Dense Hydrogen.

Hydrogen at extreme temperatures and pressures is of key relevance for cutting-edge technological applications, with inertial confinement fusion research being a prime example. In addition, it is ubiquitous throughout our universe and naturally occurs in a variety of astrophysical objects. In the present work, we present exact ab initio path integral Monte Carlo (PIMC) results for the electronic density of warm dense hydrogen along a line of constant degeneracy across a broad range of densities. Using the well-known concept of reduced density gradients, we develop a new framework to identify the breaking of bound states due to pressure ionization in bulk hydrogen. Moreover, we use our PIMC results as a reference to rigorously assess the accuracy of a variety of exchange-correlation (XC) functionals in density functional theory calculations for different density regions. Here, a key finding is the importance of thermal XC effects for the accurate description of density gradients in high-energy-density systems. Our exact PIMC test set is freely available online and can be used to guide the development of new methodologies for the simulation of warm dense matter and beyond.

Entropy is a good approximation to the electronic (static) correlation energy.

For an electronic system, given a mean field method and a distribution of orbital occupation numbers that are close to the natural occupations of the correlated system, we provide formal evidence and computational support to the hypothesis that the entropy (or more precisely -σS, where σ is a parameter and S is the entropy) of such a distribution is a good approximation to the correlation energy. Underpinning the formal evidence are mild assumptions: the correlation energy is strictly a functional of the occupation numbers, and the occupation numbers derive from an invertible distribution. Computational support centers around employing different mean field methods and occupation number distributions (Fermi-Dirac, Gaussian, and linear), for which our claims are verified for a series of pilot calculations involving bond breaking and chemical reactions. This work establishes a formal footing for those methods employing entropy as a measure of electronic correlation energy (e.g., i-DMFT [Wang and Baerends, Phys. Rev. Lett. 128, 013001 (2022)] and TAO-DFT [J.-D. Chai, J. Chem. Phys. 136, 154104 (2012)]) and sets the stage for the widespread use of entropy functionals for approximating the (static) electronic correlation.

Machine learning electronic structure methods based on the one-electron reduced density matrix.

The theorems of density functional theory (DFT) establish bijective maps between the local external potential of a many-body system and its electron density, wavefunction and, therefore, one-particle reduced density matrix. Building on this foundation, we show that machine learning models based on the one-electron reduced density matrix can be used to generate surrogate electronic structure methods. We generate surrogates of local and hybrid DFT, Hartree-Fock and full configuration interaction theories for systems ranging from small molecules such as water to more complex compounds like benzene and propanol. The surrogate models use the one-electron reduced density matrix as the central quantity to be learned. From the predicted density matrices, we show that either standard quantum chemistry or a second machine-learning model can be used to compute molecular observables, energies, and atomic forces. The surrogate models can generate essentially anything that a standard electronic structure method can, ranging from band gaps and Kohn-Sham orbitals to energy-conserving ab-initio molecular dynamics simulations and infrared spectra, which account for anharmonicity and thermal effects, without the need to employ computationally expensive algorithms such as self-consistent field theory. The algorithms are packaged in an efficient and easy to use Python code, QMLearn, accessible on popular platforms.

Which Physical Phenomena Determine the Ionization Potential of Liquid Water?

Understanding and predicting the properties of molecular liquids from the corresponding properties of the individual molecules is notoriously difficult because there is cooperative behavior among the molecules in the liquid. This is particularly relevant for water, where even the most fundamental molecular properties, such as the dipole moment, are radically different in the liquid compared to the gas phase. In this work, we focus on the ionization potential (IP) of liquid water by dissecting its individual contributions from the individual molecules making up the liquid. This is achieved by using periodic subsystem DFT, a state-of-the-art electronic structure method based on density embedding. We identify and evaluate four important electronic contributions to the IP of water: (1) mean-field, evaluated at the Hartree-Fock level; (2) electronic correlation, incorporated via DFT and wave function-based methods; (3) interaction with and (4) polarization of the environment, both evaluated ab initio with density embedding. Furthermore, we analyze their impact on the IP relative to the structural fluctuation of liquid water, revealing unexpected, hidden correlations, confirming that the broadening of the photoelectron spectra is mostly caused by intermolecular interactions confined in the first solvation shell.

Adaptive Subsystem Density Functional Theory.

Subsystem density functional theory (DFT) is emerging as a powerful electronic structure method for large-scale simulations of molecular condensed phases and interfaces. Key to its computational efficiency is the use of approximate nonadditive noninteracting kinetic energy functionals. Unfortunately, currently available nonadditive functionals lead to inaccurate results when the subsystems interact strongly such as when they engage in chemical reactions. This work disrupts the status quo by devising a workflow that extends subsystem DFT's applicability also to strongly interacting subsystems. This is achieved by implementing a fully automated adaptive definition of subsystems which is realized during geometry optimizations or ab initio molecular dynamics simulations. The new method prescribes subsystem merging and splitting events redistributing the resources (both for work and data) in an efficient way making use of modern parallelization strategies and object-oriented programming. We showcase the method with examples probing from moderate-to-strong inter-subsystem interactions, opening the door to using subsystem DFT for modeling chemical reactions in molecular condensed phases with a black box computational tool.

Circ_0039569 contributes to the paclitaxel resistance of endometrial cancer via targeting miR-1271-5p/PHF6 pathway.

Circular RNA (circRNA) has been confirmed to be involved in the chemoresistance process of cancers. However, whether circ_0039569 mediates the chemoresistance of endometrial cancer (EC) remains unclear. Quantitative real-time PCR was performed to analyze circ_0039569, microRNA (miR)-1271-5p and PHD finger protein 6 (PHF6) expression. Cell counting kit-8 assay was used to assess the paclitaxel (PTX) resistance of cells. Cell proliferation, apoptosis and invasion were determined using EdU assay, colony formation assay, flow cytometry and transwell assay. Protein expression was examined by western blot analysis. RNA interaction was verified by dual-luciferase reporter assay and RNA pull-down assay. Xenograft tumor models were constructed to explore the effect of circ_0039569 knockdown on the PTX sensitivity of EC tumors. Circ_0039569 was upregulated in PTX-resistant EC tissues and cells. Knockdown of circ_0039569 enhanced the PTX sensitivity of EC cells by inhibiting cell growth and invasion. MiR-1271-5p could be sponged by circ_0039569, and its inhibitor abolished the regulation of circ_0039569 knockdown on the PTX sensitivity of EC cells. PHF6 was targeted by miR-1271-5p, and its overexpression eliminated the promotion effect of miR-1271-5p on the PTX sensitivity of EC cells. Also, interference of circ_0036569 enhanced the PTX sensitivity of EC tumors by regulating the miR-1271-5p/PHF6 pathway. Collectively, circ_0039569 might contribute to the PTX resistance of EC through the regulation of the miR-1271-5p/PHF6 axis.

Density Embedding Method for Nanoscale Molecule-Metal Interfaces.

In this work, we extend the applicability of standard Kohn-Sham DFT (KS-DFT) to model realistically sized molecule-metal interfaces where the metal slabs venture into the tens of nanometers in size. Employing state-of-the-art noninteracting kinetic energy functionals, we describe metallic subsystems with orbital-free DFT and combine their electronic structure with molecular subsystems computed at the KS-DFT level resulting in a multiscale subsystem DFT method. The method reproduces within a few millielectronvolts the binding energy difference of water and carbon dioxide molecules adsorbed on the top and hollow sites of an Al(111) surface compared to KS-DFT of the combined supersystem. It is also robust for Born-Oppenheimer molecular dynamics simulations. Very large system sizes are approached with standard computing resources thanks to a parallelization scheme that avoids accumulation of memory at the gather-scatter stage. The results as presented are encouraging and open the door to ab initio simulations of realistically sized, mesoscopic molecule-metal interfaces.

A symmetry-orientated divide-and-conquer method for crystal structure prediction.

Crystal structure prediction has been a subject of topical interest but remains a substantial challenge especially for complex structures as it deals with the global minimization of the extremely rugged high-dimensional potential energy surface. In this paper, a symmetry-orientated divide-and-conquer scheme was proposed to construct a symmetry tree graph, where the entire search space is decomposed into a finite number of symmetry dependent subspaces. An artificial intelligence-based symmetry selection strategy was subsequently devised to select the low-lying subspaces with high symmetries for global exploration and in-depth exploitation. Our approach can significantly simplify the problem of crystal structure prediction by avoiding exploration of the most complex P1 subspace on the entire search space and has the advantage of preserving the crystal symmetry during structure evolution, making it well suitable for predicting the complex crystal structures. The effectiveness of the method has been validated by successful prediction of the candidate structures of binary Lennard-Jones mixtures and the high-pressure phase of ice, containing more than 100 atoms in the simulation cell. The work therefore opens up an opportunity toward achieving the long-sought goal of crystal structure prediction of complex systems.

GGA-Level Subsystem DFT Achieves Sub-kcal/mol Accuracy Intermolecular Interactions by Mimicking Nonlocal Functionals.

The key feature of nonlocal kinetic energy functionals is their ability to reduce to the Thomas-Fermi functional in the regions of high density and to the von Weizsäcker functional in the region of low-density/high reduced density gradient. This behavior is crucial when these functionals are employed in subsystem DFT simulations to approximate the nonadditive kinetic energy. We propose a GGA nonadditive kinetic energy functional which mimics the good behavior of nonlocal functionals, retaining the computational complexity of typical semilocal functionals. Crucially, this functional depends on the inter-subsystem density overlap. The new functional reproduces Kohn-Sham DFT and benchmark CCSD(T) interaction energies of weakly interacting dimers in the S22-5 and S66 test sets with a mean absolute deviation well below 1 kcal/mol.

Efficient DFT Solver for Nanoscale Simulations and Beyond.

We present the one-orbital ensemble self-consistent field (OE-SCF), an alternative orbital-free DFT solver that extends the applicability of DFT to beyond nanoscale system sizes, retaining the accuracy required to be predictive. OE-SCF treats the Pauli potential as an external potential updating it iteratively, dramatically outperforming current solvers because only few iterations are needed to reach convergence. OE-SCF enabled us to carry out the largest ab initio simulations for silicon-based materials to date by employing only 1 CPU. We computed the energy of bulk-cut Si nanoparticles as a function of their diameter up to 16 nm, and the polarization and interface charge transfer when a Si slab is sandwiched between two metal slabs where lattice matching mandated a large contact area. Additionally, OE-SCF opens the door to adopting even more accurate functionals in orbital-free DFT simulations while still tackling large system sizes.

Inhibition of lncRNA-NEAT1 sensitizes 5-Fu resistant cervical cancer cells through de-repressing the microRNA-34a/LDHA axis.

Cervical cancer is one of the most diagnosed malignancies among females. The 5-fluorouracil (5-Fu) is a widely used chemotherapeutic agent against diverse cancers. Despite the initially encouraging progresses, a fraction of cervical cancer patients developed 5-Fu resistance. We detected that nuclear-rich transcripts 1 (NEAT1) was significantly up-regulated in cervical cancer tissues and cell lines. Moreover, NEAT1 was positively associated with 5-Fu resistance. Furthermore, expression of NEAT1 was significantly up-regulated in 5-Fu resistant CaSki cervical cancer cells. Knocking down NEAT1 by shRNA dramatically promoted the sensitivity of 5-Fu resistant CaSki cells. We observed a negative correlation between long noncoding RNA (lncRNA)-NEAT1 and miR-34a in cervical cancer patient tissues. Overexpression of miR-34a significantly sensitized 5-Fu resistant cells. Bioinformatics analysis uncovered that NEAT1 functions as a competitive endogenous RNA (ceRNA) of miR-34a in cervical cancer cells via sponging it at multiple sites to suppress expression of miR-34a. This negative association between NEAT1 and miR-34a was further verified in cervical cancer tissues. We found the 5-Fu resistant cells displayed significantly increased glycolysis rate. Overexpression of miR-34a suppressed cellular glycolysis rate and sensitized 5-Fu resistant cells through direct targeting the 3'-untranslated region (UTR) of LDHA, a glycolysis key enzyme. Importantly, knocking down NEAT1 successfully down-regulated LDHA expressions and glycolysis rate of cervical cancer cells by up-regulating miR-34a, a process could be further rescued by miR-34a inhibition. Finally, we demonstrated inhibition of NEAT1 significantly sensitized cervical cancer cells to 5-Fu through the miR-34a/LDHA pathway. In summary, the present study suggests a new molecular mechanism for the NEAT1-mediated 5-Fu resistance via the miR-34a/LDHA-glycolysis axis.

Immediate versus delayed induction of labour in hypertensive disorders of pregnancy: a systematic review and meta-analysis.

BACKGROUND: Mothers with hypertensive disorder of pregnancy can be managed with either immediate or delayed induction of labour with expectant monitoring of both mother and baby. There are risks and benefits associated with both the type of interventions. Hence, this review was conducted to compare outcomes of immediate and delayed induction of labour among women with hypertensive disorder of pregnancy based on disease severity and gestational age. METHODS: We conducted systematic searches in various databases including Medline, Cochrane Controlled Register of Trials (CENTRAL), Scopus, and Embase from inception until October 2019.Cochrane risk of bias tool was used to assess the quality of published trials. A meta-analysis was performed with random-effects model and reported pooled Risk ratios (RR) with 95% confidence intervals (CIs). RESULTS: Fourteen randomized controlled trials with 4244 participants were included. Majority of the studies had low or unclear bias risks. Amongst late onset mild pre-eclampsia patients, the risk of renal failure was significantly lower with immediate induction of labour (pooled RR: 0.36; 95%CI: 0.14 to 0.92). In severe pre-eclampsia patients, immediate induction of labour significantly reduced the risk of having small-for-gestational age babies compared to delayed induction of labour (pooled RR: 0.49; 95%CI: 0.29-0.84).Delayed induction was found to significantly reduce the risk of neonatal respiratory distress syndrome risk among late onset mild pre-eclampsia patients (pooled RR: 2.15; 95%CI: 1.14 to 4.06) None of the other outcomes demonstrated statistically significant difference between the two interventions. CONCLUSION: Delayed induction of labour with expectant monitoring may not be inferior to immediate induction of labour in terms of neonatal and maternal outcomes. Expectant approach of management for late onset mild pre-eclampsia patients may be associated with decreased risk of neonatal respiratory distress syndrome, while immediate induction of labour among severe pre-eclampsia patients is associated with reduced risk of small-for-gestational age babies and among mild pre-eclampsia patients, it is associated with reduced risk of severe renal impairment.

Pressure-stabilized divalent ozonide CaO3 and its impact on Earth's oxygen cycles.

High pressure can drastically alter chemical bonding and produce exotic compounds that defy conventional wisdom. Especially significant are compounds pertaining to oxygen cycles inside Earth, which hold key to understanding major geological events that impact the environment essential to life on Earth. Here we report the discovery of pressure-stabilized divalent ozonide CaO3 crystal that exhibits intriguing bonding and oxidation states with profound geological implications. Our computational study identifies a crystalline phase of CaO3 by reaction of CaO and O2 at high pressure and high temperature conditions; ensuing experiments synthesize this rare compound under compression in a diamond anvil cell with laser heating. High-pressure x-ray diffraction data show that CaO3 crystal forms at 35 GPa and persists down to 20 GPa on decompression. Analysis of charge states reveals a formal oxidation state of -2 for ozone anions in CaO3. These findings unravel the ozonide chemistry at high pressure and offer insights for elucidating prominent seismic anomalies and oxygen cycles in Earth's interior. We further predict multiple reactions producing CaO3 by geologically abundant mineral precursors at various depths in Earth's mantle.

Efficient potential-tuning strategy through p-type doping for designing cathodes with ultrahigh energy density.

Designing new cathodes with high capacity and moderate potential is the key to breaking the energy density ceiling imposed by current intercalation chemistry on rechargeable batteries. The carbonaceous materials provide high capacities but their low potentials limit their application to anodes. Here, we show that Fermi level tuning by p-type doping can be an effective way of dramatically raising electrode potential. We demonstrate that Li(Na)BCF2/Li(Na)B2C2F2 exhibit such change in Fermi level, enabling them to accommodate Li+(Na+) with capacities of 290-400 (250-320) mAh g-1 at potentials of 3.4-3.7 (2.7-2.9) V, delivering ultrahigh energy densities of 1000-1500 Wh kg-1. This work presents a new strategy in tuning electrode potential through electronic band structure engineering.

Polyethylene Glycol-Na+ Interface of Vanadium Hexacyanoferrate Cathode for Highly Stable Rechargeable Aqueous Sodium-Ion Battery.

Vanadium hexacyanoferrate (VHCF) with an open-framework crystal structure is a promising cathode material for rechargeable aqueous metal-ion batteries owing to its high electrochemical performance and easy synthesis. In this paper, vanadium hexacyanoferrate cathodes were first used for constructing rechargeable aqueous sodium-ion batteries (VHCF/WO3) and tested in the new-type electrolyte (NaP-4.6) consisting of a polyethylene glycol (PEG)/H2O/NaClO4 electrolyte with a low H+ concentration (molar ratio of [H2O]/[Na+] is 4.6), which has high stability at a high current density as high as 1000 mA g-1 with a capacity retention of 90.3% after 2000 cycles at high coulombic efficiency (above 97.8%). To understand their outstanding performance, the proton-assisted sodium-ion storage mechanism and interphase chemistry of VHCF are investigated by solid-state NMR (ssNMR) technology. It is suggested that the H+ storage reaction is accompanied by the redox of vanadium atoms and Na+ intercalation is accompanied by the redox of iron atoms. It is also observed that the complex of polyethylene glycol (PEG) with Na+ (PEG-Na+) exists on the VHCF surface, which facilitates the stability of VHCF and promotes the alkali-ion transfer at a high current density. The results of the ssNMR study offer new insights into the intercalation chemistry of Prussian blue analogues with open-framework-structured compounds, which can greatly broaden our horizons for battery research.

Ab initio electronic structure calculations using a real-space Chebyshev-filtered subspace iteration method.

Ab initio electronic structure calculations within Kohn-Sham density functional theory requires a solution for the Kohn-Sham equation. However, the traditional self-consistent field (SCF) approach of solving the equation using iterative diagonalization exhibits an inherent cubic scaling behavior and becomes prohibitive for large systems. The Chebyshev-filtered subspace iteration (CheFSI) method holds considerable promise for large-system calculations by substantially accelerating the SCF procedure. Here, we employed a combination of the real space finite-difference formulation and CheFSI to solve the Kohn-Sham equation, and implemented this approach in ab initio Real-space Electronic Structure (ARES) software in a multi-processor, parallel environment. An improved scheme was proposed to generate the initial subspace of Chebyshev filtering in ARES efficiently, making it suitable for large-scale simulations. The accuracy, stability, and efficiency of the ARES software were illustrated by simulations of large-scale crystalline systems containing thousands of atoms.

Structure evolution of chromium-doped boron clusters: toward the formation of endohedral boron cages.

The electron-deficient nature of boron endows isolated boron clusters with a variety of interesting structural and bonding properties that can be further enriched through metal doping. In the current work, we report the structural and electronic properties of a series of chromium-doped boron clusters. The global minimum structures for CrB n clusters with an even number of n ranging from 8 to 22 are proposed through extensive first-principles swarm-intelligence structure searches. Half-sandwich structures are found to be preferred for CrB8, CrB10, CrB12 and CrB14 clusters and to transform to a drum-like structure at CrB16 cluster. Endohedral cage structures with the Cr atom located at the center are energetically most favorable for CrB20 and CrB22 clusters. Notably, the endohedral CrB20 cage has a high symmetry of D 2d and a large HOMO-LUMO gap of 4.38 eV, whose stability is attributed to geometric fit and formation of an 18-electron closed-shell configuration. The current results advance our understanding of the structure and bonding of metal-doped boron clusters.