Photochemistry-Enabled Nitrogen-Assisted Organostibines as an Efficient Alkyl Radical Precursor: Mechanistic Insights and Synthetic Applications.

Organostibines exhibit significant potential as functional handles for the construction of C─C-rich scaffolds owing to their orthogonal and robust reactivity features. At present, the transformation of C(sp)/C(sp)─Sb bonds into C─C bonds has established a mature methodology. However, breakthroughs in the C(sp)─Sb system still require systematic investigations into reaction mechanisms, catalyst design, and other aspects.

Non-Invasive Composition Identification in Organic Solar Cells via Deep Learning.

Accurate identification of active-layer compositions in organic photovoltaic (OPV) devices often relies on invasive techniques such as electrical measurements or material extraction, which risk damaging the device. In this study, we propose a non-invasive classification approach based on simulated full-device absorption spectra. To account for fabrication-related variability, the active-layer thickness varied by over ±15% around the optimal value, creating a realistic and diverse training dataset.

A 54.6 GHz Clock Transition in Ho Electron Spin Qubits Assembled into a Metal-Organic Framework.

A high-symmetry assembly of molecular spin qubits has been achieved in the metal-organic framework (MOF) [Ho(pzdo)](ClO) (), where the eight-coordinate Ho nodes are bridged by pyrazine-1,4-dioxide (pzdo) ligands. The approximate square-antiprismatic () coordination of the Ho ion leads to the stabilization of the = ±4 ground-state doublet due to crystal-field splitting of the = 8 total angular momentum state. Mixing of the = +4 and = -4 projection states opens a zero-field energy gap (Δ) resulting in the spin clock transition (SCT) evident in the EPR spectra of .

General Quantum Alchemical Free Energy Simulations via Hamiltonian Interpolation.

We present an implementation of alchemical free energy simulations at the quantum mechanical level by directly interpolating the electronic Hamiltonian. The method is compatible with any level of electronic structure theory and requires only one quantum calculation for each molecular dynamics step in contrast to multiple energy evaluations that would be needed when interpolating the ground-state energies. We demonstrate the correctness and applicability of the technique by computing alchemical free energy changes of gas-phase molecules, with both nuclear and electron creation/annihilation.

Physics-informed CNN convolution for emulating scattering in quantum-dot color conversion displays.

We propose a physics-informed convolutional framework for simulating optical scattering in quantum-dot color conversion films (QDCFs). Scattering intensity distributions, computed using LightTools (LT), are spatially discretized into 3 × 3, 5 × 5, 7 × 7, and 9 × 9 grids. The integrated energy within each region is normalized to construct convolution kernels, where each element represents the proportion of scattered energy from a central source to neighboring positions.

Image super-resolution inspired electron density prediction.

Predicting ground-state electron densities of chemical systems has recently received growing attention in machine learning quantum chemistry, given their fundamental importance as highlighted by the Hohenberg-Kohn theorem. Drawing inspiration from the domain of image super-resolution, we view the electron density as a 3D grayscale image and use a convolutional residual network to transform a crude and trivially generated guess of the molecular density into an accurate ground-state quantum mechanical density. Here we show that this model produces more accurate predictions than all prior density prediction approaches.

Depression in left-behind adolescents from single-parent families: a nomogram based on multidimensional risk factors.

Background: Depression is a significant issue affecting adolescents' mental health. While depression research is relatively extensive, studies focusing on left-behind adolescents from single-parent families remain limited. Due to their unique family structure, this group is more susceptible to multiple stressors, increasing their risk of depression.

Age-related changes in depression symptom networks in children in China with parental absence: A comparative analysis of youth aged nine to 18.

Background: The network perspective on psychopathology views depression as a system of interacting symptoms. Research shows that mental health problems change with age. Children with parental absence are at risk for depression, but it's unclear how their depressive symptom networks evolve across developmental stages.

Shadow Molecular Dynamics with a Machine Learned Flexible Charge Potential.

We present an extended Lagrangian shadow molecular dynamics scheme with an interatomic Born-Oppenheimer potential determined by the relaxed atomic charges of a second-order charge equilibration model. To parametrize the charge equilibration model, we use machine learning with neural networks to determine the environment-dependent electronegativities and chemical hardness parameters for each atom, in addition to the charge-independent energy and force terms. The approximate shadow molecular dynamics potential in combination with the extended Lagrangian formulation improves the numerical stability and reduces the number of Coulomb potential calculations required to evaluate accurate conservative forces.

Sleep patterns and smartphone use among left-behind children: a latent class analysis and its association with depressive symptoms.

Background: Left-behind children in China face challenges in sleep patterns, technology use, and mental health. This study uses an individual-centered approach to derive behavioral profiles associated with depressive symptoms.

Methods: Data from 131,586 left-behind children aged 8 to 18 years from the Chinese Psychological Health Guard for Children and Adolescents Project were analyzed.

Accurate QM/MM Molecular Dynamics for Periodic Systems in GPU4PySCF with Applications to Enzyme Catalysis.

We present an implementation of the quantum mechanics/molecular mechanics (QM/MM) method for periodic systems using GPU accelerated QM methods, a distributed multipole formulation of the electrostatics, and a pseudobond treatment of the QM/MM boundary. We demonstrate that our method has well-controlled errors, stable self-consistent QM convergence, and energy-conserving dynamics. We further describe an application to the catalytic kinetics of chorismate mutase.

Reprogrammed Lung Metastasis Immunodeficiency via Targeted Penetrated Delivery of M1 Macrophage-Wrapped NanoCubes-Mediated T Cell Infiltration.

The infiltration of cytotoxic T lymphocytes holds promise for suppressing even the most resilient metastatic tumors in immunotherapy. Polarizing tumor-associated macrophages (TAMs) and remodeling the immune-deficient tumor microenvironment (TME) can enhance T lymphocyte recruitment and infiltration. However, the immune privilege and low immunogenic responses of these aggressive tumor clusters often limit lymphocyte recruitment.

Variations of phosphorus in sediments and suspended particulate matter of a typical mesotrophic plateau lake and their contribution to eutrophication.

Internal phosphorus loading (IPL), as an important part of lake phosphorus cycle and the key to solve the eutrophication problem, is still an important cause of regional and seasonal algal blooms for some mesotrophic lakes located in plateau areas. We investigated the composition, distribution of P fractions in sediments and suspended particulate matter (SPM) of Erhai Lake, southwest China, and explored the relationships between environmental variables and spatial-temporal variations of P fractions. The total P (TP) in surface sediments ranged from 817 to 1216 mg/kg, with inert Ca-P (32%) and Res-P (24%) predominating, at a moderate level.

Quantitative insights into the mechanism of proton conduction and selectivity for the human voltage-gated proton channel Hv1.

Human voltage-gated proton (hHv1) channels are crucial for regulating essential biological processes such as immune cell respiratory burst, sperm capacitation, and cancer cell migration. Despite the significant concentration difference between protons and other ions in physiological conditions, hHv1 demonstrates remarkable proton selectivity. Our calculations of single-proton, cation, and anion permeation free energy profiles quantitatively demonstrate that the proton selectivity of the wild-type channel originates from its strong proton affinity via the titration of the key residues D112 and D174, although the channel imposes similar kinetic blocking effects for protons compared to other ions.

Early-Life Exposure to 4-Hydroxy-4'-Isopropoxydiphenylsulfone Induces Behavioral Deficits Associated with Autism Spectrum Disorders in Mice.

Exposure to bisphenol A (BPA) during gestation and lactation is considered to be a potential risk factor for autism spectrum disorder (ASD) in both humans and animals. As a novel alternative to BPA, 4-hydroxy-4'-isopropoxydiphenylsulfone (BPSIP) is frequently detected in breast milk and placental barrier systems, suggesting potential transmission from the mother to offspring and increased risk of exposure. Gestation and lactation are critical periods for central nervous system development, which are vulnerable to certain environmental pollutants.

Base-Promoted Annulated Aromatization of Aryl Acetylenes with Dimethyl Sulfoxide to Access Symmetrical/Unsymmetric -Terphenyl.

A protocol for selective and efficient synthesis of symmetrical and unsymmetrical -terphenyls is presented among aryl acetylene and DMSO in the presence of KOH and methanol. In this reaction, two molecules of aryl acetylene contribute four carbons, and DMSO, as a dual carbon donor, provides two carbons to a new aromatic ring. This protocol can be tolerated for the electron-donating or disubstituted phenylacetylenes as well as the heterocyclic acetylene derivatives.

Performant automatic differentiation of local coupled cluster theories: Response properties and ab initio molecular dynamics.

In this work, we introduce a differentiable implementation of the local natural orbital coupled cluster (LNO-CC) method within the automatic differentiation framework of the PySCFAD package. The implementation is comprehensively tuned for enhanced performance, which enables the calculation of first-order static response properties on medium-sized molecular systems using coupled cluster theory with single, double, and perturbative triple excitations [CCSD(T)]. We evaluate the accuracy of our method by benchmarking it against the canonical CCSD(T) reference for nuclear gradients, dipole moments, and geometry optimizations.

Structural, Ionic, and Electronic Properties of Solid-State Phthalimide-Containing Polymers for All-Organic Batteries.

Redox-active polymers serving as the active materials in solid-state electrodes offer a promising path toward realizing all-organic batteries. While both cathodic and anodic redox-active polymers are needed, the diversity of the available anodic materials is limited. Here, we predict solid-state structural, ionic, and electronic properties of anodic, phthalimide-containing polymers using a multiscale approach that combines atomistic molecular dynamics, electronic structure calculations, and machine learning surrogate models.

Combined effects of cadmium and sulfamethoxazole on Eisenia fetida: Insights into accumulation, subcellular partitioning, biomarkers and toxicological responses.

Cadmium (Cd) and sulfamethoxazole (SMX) frequently coexist in farmlands, yet their synergistic toxicological impacts on terrestrial invertebrates remain unexplored. In this study, earthworms were exposed to artificial soils percolated with Cd (5 mg/kg), SMX (5 mg/kg) or combination of them for 7 days, followed by a 12-day elimination phase in uncontaminated soil. The uptake of Cd and SMX by the earthworms, along with their subcellular distribution, was meticulously analyzed.

Zero Voltage-Degradation of LiMnO with Ultrathin Amorphous Li─Mn─O Coating.

Manganese-based lithium-rich layered oxides (Mn-LLOs) are promising candidate cathode materials for lithium-ion batteries, however, the severe voltage decay during cycling is the most concern for their practical applications. Herein, an Mn-based composite nanostructure constructed LiMnO (LMO@LiMnO) is developed via an ultrathin amorphous functional oxide LiMnO coating at the grain surface. Due to the thin and universal LMO amorphous surface layer etched from the lithiation process by the high-concentration alkaline solution, the structural and interfacial stability of LiMnO are enhanced apparently, showing the significantly improved voltage maintenance, cycle stability, and energy density.