STELLA provides a drug design framework enabling extensive fragment-level chemical space exploration and balanced multi-parameter optimization.

In drug discovery, identifying molecules with desired pharmacological properties remains challenging, as conventional methods often rely on exhaustive trial-and-error and limited exploration of chemical space. Here, we present STELLA, a metaheuristics-based generative molecular design framework that combines an evolutionary algorithm for fragment-based chemical space exploration with a clustering-based conformational space annealing method for efficient multi-parameter optimization. Additionally, it leverages deep learning models for accurate prediction of pharmacological properties.

Medial Joint Opening in the Operated Knee After Unilateral High Tibial Osteotomy: Risk of Osteoarthritis and Future Surgery in the Operated and Nonoperated Knee.

Background: High tibial osteotomy (HTO) modifies the mechanics of the affected knee but can also affect the nonoperated knee. However, no research has reported on the prognosis and risk factors related to the nonoperated knee after unilateral HTO.

Purpose: To assess the radiological parameters associated with osteoarthritis (OA) progression and the need for surgery in the nonoperated knee after unilateral HTO, with concurrent assessment of the operated knee.

Quantum-Informed Molecular Representation Learning Enhancing ADMET Property Prediction.

We examined pretraining tasks leveraging abundant labeled data to effectively enhance molecular representation learning in downstream tasks, specifically emphasizing graph transformers to improve the prediction of ADMET properties. Our investigation revealed limitations in previous pretraining tasks and identified more meaningful training targets, ranging from 2D molecular descriptors to extensive quantum chemistry simulations. These data were seamlessly integrated into supervised pretraining tasks.

Software for the frontiers of quantum chemistry: An overview of developments in the Q-Chem 5 package.

This article summarizes technical advances contained in the fifth major release of the Q-Chem quantum chemistry program package, covering developments since 2015. A comprehensive library of exchange-correlation functionals, along with a suite of correlated many-body methods, continues to be a hallmark of the Q-Chem software. The many-body methods include novel variants of both coupled-cluster and configuration-interaction approaches along with methods based on the algebraic diagrammatic construction and variational reduced density-matrix methods.

A local environment descriptor for machine-learned density functional theory at the generalized gradient approximation level.

We propose a grid-based local representation of electronic quantities that can be used in machine learning applications for molecules, which is compact, fixed in size, and able to distinguish different chemical environments. We apply the proposed approach to represent the external potential in density functional theory with modified pseudopotentials and demonstrate its proof of concept by predicting the Perdew-Burke-Ernzerhof and local density approximation electronic density and exchange-correlation potentials by kernel ridge regression. For 16 small molecules consisting of C, H, N, and O, the mean absolute error of exchange-correlation energy was 0.

Origin of unusual spinel-to-layered phase transformation by crystal water.

It is well known that many layered transition metal oxides can transform into a spinel structure upon repeated battery cycling, but a phase transition in the opposite direction is rare. Recently, the transformation from spinel MnO to layered MnO was observed during the operation of a Mg battery in aqueous conditions, resulting in high performance Mg batteries. We hereby use calculations to unveil the mechanism by which crystal water plays a critical role in this unique transformation.

Artificial neural network for the configuration problem in solids.

A machine learning approach based on the artificial neural network (ANN) is applied for the configuration problem in solids. The proposed method provides a direct mapping from configuration vectors to energies. The benchmark conducted for the M1 phase of Mo-V-Te-Nb oxide showed that only a fraction of configurations needs to be calculated, thus the computational burden significantly decreased, by a factor of 20-50, with R = 0.

A soft damping function for dispersion corrections with less overfitting.

The use of damping functions in empirical dispersion correction schemes is common and widespread. These damping functions contain scaling and damping parameters, and they are usually optimized for the best performance in practical systems. In this study, it is shown that the overfitting problem can be present in current damping functions, which can sometimes yield erroneous results for real applications beyond the nature of training sets.

Exploring the possibilities of two-dimensional transition metal carbides as anode materials for sodium batteries.

Recently a group of two-dimensional materials called MXenes have been discovered and they have demonstrated their potential in Li rechargeable batteries. Herein, the Na storage and ion migration properties of M2C-type MXenes (M = Ti, V, Cr, Mn, Fe, Co, Ni, Nb, Mo) were investigated using density functional theory (DFT) calculations, and were compared to the Li case. Based on the average voltage and migration barrier of surface ions, we suggest that M = Ti, V, Cr, Mn, and Mo are suitable for sodium ion battery (SIB) anodes.

Assessments of semilocal density functionals and corrections for carbon dioxide adsorption on metal-organic frameworks.

The significant amount of attention that has been directed toward metal-organic frameworks (MOFs) for a wide spectrum of applications can be attributed to their variety and tunability, which are precisely the aspects that computational modeling can offer by systematically exploring the chemical space. In this minireview, we describe density functional theory calculations for gas adsorption on MOFs, mainly focusing on the interaction of CO2 with MOF-74. The generalized gradient approximation (GGA) level of density functional studies seems suited to treat MOFs, owing to the balance between its practical applicability and its useful accuracy, although this method is not without deficiencies such as the lack of nonlocal correlations and self-interactions.

Diffusion and perfusion MRI prediction of progression-free survival in patients with hepatocellular carcinoma treated with concurrent chemoradiotherapy.

Purpose: To assess whether MR perfusion and diffusion parameters taken before concurrent chemoradiotherapy (CCRT) are useful imaging biomarkers for predicting progression-free survival (PFS) in patients with hepatocellular carcinoma (HCC).

Materials And Methods: Twenty patients with locally advanced HCC who had no treatment before CCRT underwent dynamic contrast-enhanced (DCE) and diffusion-weighted MRI. Mean values of the volume transfer constant (K(trans) ), reflex constant (Kep ), extravascular extracellular volume fraction (Ve ) and the apparent diffusion coefficient (ADC) were estimated on a region of interest.

On the structure of Si(100) surface: importance of higher order correlations for buckled dimer.

We revisit a dangling theoretical question of whether the surface reconstruction of the Si(100) surface would energetically favor the symmetric or buckled dimers on the intrinsic potential energy surfaces at 0 K. This seemingly simple question is still unanswered definitively since all existing density functional based calculations predict the dimers to be buckled, while most wavefunction based correlated treatments prefer the symmetric configurations. Here, we use the doubly hybrid density functional (DHDF) geometry optimizations, in particular, XYGJ-OS, complete active space self-consistent field theory, multi-reference perturbation theory, multi-reference configuration interaction (MRCI), MRCI with the Davidson correction (MRCI + Q), multi-reference average quadratic CC (MRAQCC), and multi-reference average coupled pair functional (MRACPF) methods to address this question.

Analytic Derivatives of Quartic-Scaling Doubly Hybrid XYGJ-OS Functional: Theory, Implementation, and Benchmark Comparison with M06-2X and MP2 Geometries for Nonbonded Compelexes.

Analytic first derivative expression of opposite-spin (OS) ansatz adapted quartic scaling doubly hybrid XYGJ-OS functional is derived and implemented into Q-Chem. The resulting algorithm scales quartically with system size as in OS-MP2 gradient, by utilizing the combination of Laplace transformation and density fitting technique. The performance of XYGJ-OS geometry optimization is assessed by comparing the bond lengths and the intermolecular properties in reference coupled cluster methods.

Free-breathing dynamic contrast-enhanced MRI of the abdomen and chest using a radial gradient echo sequence with K-space weighted image contrast (KWIC).

Objectives: To evaluate the feasibility of free-breathing, dynamic contrast-enhanced (DCE) MRI of the abdomen and thorax using the radial-gradient-echo sequence with k-space weighted image contrast (KWIC) reconstruction.

Methods: Institutional review board approval was obtained. Fourteen patients underwent free-breathing radial DCE-MRI.