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CBX2 promoted oral squamous cell carcinoma via increasing CEP55/NF-κB/METTL3/SHP2 signaling induced metastasis/proliferation and angiogenesis

Analytical nuclear gradients for second-order Møller–Plesset perturbation theory using pair-natural orbitals based on localized virtual molecular orbitals

Accelerating analytical nuclear energy gradient calculations within wavefunction-based quantum chemical frameworks and extending their applicability to large systems remain significantly challenging. Recently, Pinski and Neese developed fully analytical nuclear energy gradients for second-order Møller–Plesset perturbation theory (MP2) using pair natural orbitals (PNOs) based on projected atomic orbitals (PAOs) [P. Pinski and F. Neese, J. Chem. Phys. 148, 031101 (2018); P. Pinski and F. Neese, J. Chem. Phys. 150, 164102 (2019)]. Here, we present an analytical nuclear gradient method based on the PNO-MP2 theory using orthonormal and non-redundant localized virtual molecular orbitals (LVMOs) instead of conventional PAOs. Compared to PAO-based approaches, our method exhibits two main differences. First, constraints from the construction of LVMOs are incorporated into the Lagrangian, requiring the solution of an additional Z-vector equation—the coupled-perturbed virtual localization (CP-VL) equation. Second, owing to the orthonormality of the LVMOs, the derivatives of the PNO coefficients with respect to both the MO coefficients and the nuclear coordinates vanish. The latter property significantly simplifies the formulation of analytical energy gradients. In addition, to mitigate the technical complexity of deriving gradient formulas with the PNO treatment, we used an extended scheme implemented in our automatic derivation program. Benchmark calculations on phenylalkane chains, docetaxel, and a host–guest complex demonstrated high computational scalability of our nuclear gradient implementations, additionally confirming that the computational effort required to solve the CP-VL equation is relatively minor. We illustrated that the energy gradients as functions of nuclear coordinates are smooth and that the errors in the predicted structures are small.

Genome-wide variation reveal that goats were introduced into Asia via multiple migrations

Unlocking the optoelectronic potential of AGeX3 (A = Ca, Sr, Ba; X = S, Se): A sustainable alternative in chalcogenide perovskites

The quest for environmentally benign and stable optoelectronic materials has intensified, and chalcogenide perovskites (CPs) have emerged as promising candidates owing to their non-toxic composition, stability, small bandgaps, and large absorption coefficients. However, a detailed theoretical study of excitonic and polaronic properties of these materials remains underexplored due to the high computational demands. Herein, we present a comprehensive theoretical investigation of germanium-based CPs, AGeX3 (A = Ca, Sr, Ba; X = S, Se), which adopt distorted perovskite structures (β-phase) with an orthorhombic crystal structure (space group: pnma) by utilizing state-of-the-art density functional theory, density functional perturbation theory (DFPT), and many-body perturbation theory [GW, Bethe–Salpeter Equation (BSE)]. Our calculations reveal that these materials are mechanically stable, having potential thermodynamic accessibility under suitable conditions. The G0W0@PBE bandgaps range from 0.65 to 2.00 eV, suitable for optoelectronics. We analyze the ionic and electronic contributions to dielectric screening using DFPT and BSE methods, finding that the electronic component dominates. The exciton binding energies range from 6.38 to 73.63 meV, indicating efficient exciton dissociation under ambient conditions. In addition, these perovskites exhibit low to high polaronic mobilities (1.67–167.65 cm2 V−1 s−1), exceeding many lead-free CPs and halide perovskites due to reduced carrier-phonon interactions. Among the studied systems, BaGeSe3 exhibits the most robust combination of thermodynamic stability and high carrier mobility, while SrGeSe3 shows a balanced interplay between electronic and optical performance. On the other hand, BaGeS3 and other sulfide members demonstrate noteworthy variations in excitonic and polaronic behavior, offering additional directions for property tuning. The combination of tunable bandgaps, low exciton binding energies, and high carrier mobility underscores the scientific promise of these materials in the context of future optoelectronic applications.

Cellular heterogeneity and therapeutic response profiling of human IDH + glioma stem cell cultures

Real-space Hubbard-corrected density functional theory

We present an accurate and efficient framework for real-space Hubbard-corrected density functional theory. In particular, we obtain expressions for the energy, atomic forces, and stress tensor suitable for real-space finite-difference discretization and develop a large-scale parallel implementation. We verify the accuracy of the formalism through comparisons with established plane-wave results. We demonstrate that the implementation is highly efficient and scalable, outperforming established plane-wave codes by more than an order of magnitude in minimum time to solution, with increasing advantages as the system size and/or the number of processors is increased. We apply this framework to examine the impact of exchange–correlation inconsistency in local atomic orbital generation and introduce a scheme for optimizing the Hubbard parameter based on hybrid functionals, both while studying TiO2 polymorphs.

Factors influencing complete abstinence during Thailand’s temporary alcohol abstinence campaign

Two-photon dissociation dynamics of N2O: The N(2P <i>J</i> ) and N(2D <i>J</i> ) atom channels

Two-photon dissociation dynamics of N2O were investigated by means of the time-sliced velocity map ion imaging technique. The N(2PJ) + NO(X2Π) and N(2DJ) + NO(X2Π) channels were accessed via two-photon excitation in the wavelength range of 218–236 nm. The four lobes in the angular distributions were clearly observed in both N-atom product channels, implying that the coherence between the two sequential transitions in the overall two-photon photodissociation process at the energies investigated has a significant influence on the angular distribution of the products. In addition, the translational energy distributions have been determined from the recorded images, revealing highly inverted vibrational populations of both NO products. In the N(2PJ) channel, initial vibrational excitation has a significant impact on the photodissociation dynamics of N2O via 3pσ1Π states. According to experimental results, the N(2PJ) channel may proceed via a bent configuration dissociation pathway involving coupling to an A′ symmetry potential energy surface that has not yet been theoretically reported. While the N(2DJ) channel may be preferentially formed via triplet and singlet Rydberg states that couple to the 43A′ and 51A′ states, followed by dissociation in a bent geometry.

Quality evaluation of Capitatae Fructus from different geographical regions in China

Recombination of HCO+ ions with electrons in the temperature range of 80–200 K

The recombination of HCO+ ions with electrons was studied in the temperature range of 80–200 K using a combination of stationary afterglow with CRDS and microwave diagnostic techniques. The determined recombination rate coefficient is αHCO+=(1.32±0.14)(300K/T)(0.52±0.14)×10−7 cm3 s−1. The pressure broadening coefficients for the P(4) transition of the 2000 ← 0000 vibrational band of HCO+ and the upper estimates for the reaction rate coefficient for the (HCO)+·CO cluster formation assisted by helium were also obtained.

Decoding the relationships among miRNA, HPV infection, and tumor suppressor gene expression in breast cancer patients

Selective excitation of molecular vibrations via a two-mode cavity Raman scheme

The experimental realization of strong light–matter coupling with molecules initiated the rapidly evolving field of molecular polaritonics. Most studies focus on how exciton polaritons, which combine electronic excitations with confined light modes, alter photochemistry. In this paper, we investigate their use in selectively exciting molecular vibrational states in the ground state. Selectively exciting molecules to high vibrational states with infrared lasers to catalyze ground-state chemical reactions is a challenging task. Here, we propose a two-cavity mode setup in the electronic strong coupling regime inspired by the process of stimulated Raman adiabatic passage to selectively populate excited vibrational states. One cavity mode actively pumps the molecular system, while the other provides a highly effective and tunable decay channel via photon leakage. We demonstrate the ability to selectively populate vibrational states for coherent and incoherent light sources using a molecular model system. Our initial findings show high efficiency and suggest a possible route to steering and controlling chemical reactions in the electronic ground state based on electronic strong coupling.

Baseline and early changes in eosinophil count and neutrophil-to-eosinophil ratio predict outcomes in metastatic renal cell carcinoma treated with nivolumab

Enhanced molecular diffusion near a soft fluctuating membrane

Particles diffusing near interfaces face anisotropic resistance to motion due to hydrodynamic interactions. While this has been extensively studied near hard interfaces since the works of Lorentz and Brenner, our understanding of diffusion near soft, thermally fluctuating interfaces remains limited. Previous studies have predominantly focused on particles much larger than the molecular scale at which thermal fluctuations become important. In this work, we numerically investigate the dynamics of individual solvent molecules near a thermally fluctuating lipid membrane, a canonical soft interface in biology. We observe that the diffusive motion of solvent molecules near the fluctuating membrane is slightly enhanced compared to a flat rigid interface and significantly more so than near an undulated rigid interface. This enhancement in diffusive motion arises from spontaneous momentum exchanges between the moving membrane and adjacent molecules, promoting mixing. Notably, this dispersion effect overcomes geometric trapping that slows diffusion near the rigid undulated interface. Our analysis reveals that the momentum transfer near the fluctuating membrane is so efficient that it resembles an effective slip boundary condition over a length scale equal to the fluctuation height. These molecular-scale mechanisms differ from those of larger particles, where hydrodynamic memory and elasticity effects can be at play as they relax over timescales comparable to significant diffusive motion. Our findings advance understanding of enhanced diffusive motion and promoted mixing near soft fluctuating membranes involved in diverse biological processes and soft-matter technologies containing natural and model cell membranes.

A novel deep transformer based CvT model for sign language recognition in visual communication

Abstract Sign language serves as a crucial mode of communication for the deaf and hard-of-hearing communities, enabling effective interaction in daily life. With the growing advancements in Artificial Intelligence (AI) and computer vision, there has been a significant shift toward automating SLR, making communication more accessible and inclusive. Traditional AI-based approaches, such as rule-based and statistical models, struggle to handle complex hand gestures, varying lighting conditions, and occlusions. Deep learning-based methods, particularly Convolutional Neural Networks (CNNs), have improved recognition capabilities, but they often fail to capture intricate spatial and temporal dependencies that are essential for accurate classification. To address these limitations, vision transformers (ViTs) have emerged as a breakthrough technology, offering superior feature extraction through self-attention mechanisms. Unlike conventional CNNs, ViTs efficiently model long-range dependencies, enabling robust sign recognition. This study proposes a Convolutional Vision Transformer (CvT)-based model that integrates hierarchical convolutional tokenization with transformer-based attention mechanisms, optimizing both local and global feature extraction. The proposed CvT model was evaluated on a publicly available sign language digits dataset, consisting of 1,712 images across 10 different classes along with alphabet and symbol dataset with 87,000 images of 29 classes. Empirical results indicate that with both datasets, the proposed model analysis CvT outperforms baseline models, achieving the highest accuracy of 99%, surpassing traditional CNN and transformer-based BeIT models. The findings demonstrate that CvT effectively reduces misclassifications, improves predictive confidence, and enhances generalization across training, validation, and test sets.

Ultrafast dissociation dynamics of nitromethane: Enhanced efficiency under near-infrared vs ultraviolet excitation

Nitromethane is an essential energetic material with diverse technological applications. While numerous studies have independently investigated its dissociation dynamics under ultraviolet (UV) or near-infrared (NIR) excitation, comparative analyses between these spectral regimes at ultrafast temporal and microscopic spatial resolutions are limited. Here, employing real-time time-dependent density functional theory molecular dynamics simulations, we represent the first detailed microscopic comparison of nitromethane dissociation induced by NIR (1.55 eV) and UV (6.8 eV) laser excitations. Both excitation wavelengths initially drive C–N bond elongation during irradiation, followed by relaxation post-illumination. However, at sufficiently strong laser fields, immediate bond cleavage occurs within the irradiation period, underscoring the critical role of wavelength and intensity in reaction dynamics. Our simulations notably reveal significantly enhanced dissociation rates and efficiencies under NIR excitation compared to UV at equivalent intensities. This improved efficiency arises from distinct nonlinear multiphoton excitation pathways and pronounced thermal effects, promoting substantial molecular distortions and rapid energy transfer. These findings elucidate wavelength-dependent dissociation mechanisms, offering valuable insights to develop safer and more efficient laser-driven initiation strategies for nitroalkyl energetic materials.

Research on cross-dataset cardiac signal domain generalization and feature interpretability

Connections between Richardson–Gaudin states, perfect-pairing, and pair coupled-cluster theory

Slater determinants underpin most electronic structure methods, but orbital-based approaches often struggle to describe strong correlation efficiently. Geminal-based theories, by contrast, naturally capture static correlation in bond-breaking and multi-reference problems, though at the expense of implementation complexity and limited treatment of dynamic effects. In this work, we examine the interplay between orbital and geminal frameworks, focusing on perfect-pairing (PP) wavefunctions and their relation to pair coupled-cluster doubles (pCCD) and Richardson-Gaudin states. We show that PP arises as an eigenvector of a simplified, reduced Bardeen–Cooper–Schrieffer Hamiltonian expressed in bonding/antibonding orbital pairs, with the complementary eigenvectors enabling a systematic treatment of weak correlation. Second-order Epstein–Nesbet perturbation theory on top of PP is found to yield energies nearly equivalent to pCCD. These results clarify the role of pair-based ansätze and open avenues for hybrid approaches that combine the strengths of orbital- and geminal-based methods.

Hypoxic BMSC-derived exosomes-induced mitophagy quenches intestinal inflammation via HIF-1α/BNIP3 pathway

AlScN-based ferroelectric memristor for electrical synapse emulation and light-stimulated reservoir computing

In this study, we present a multifunctional indium tin oxide (ITO)/aluminum scandium nitride (AlScN)/n+ Si ferroelectric memristor for integrated electrical–optical neuromorphic computing. The device, fabricated using radio frequency sputtering, exhibits robust ferroelectricity with an average remanent polarization of 48.46 μC/cm2 and stable endurance over 105 cycles. Electrical measurements confirm core synaptic behaviors, including potentiation and depression, with improved linearity and recognition accuracy using incremental pulse schemes. Spike-dependent plasticity modulated by pulse number, amplitude, and width is also demonstrated. In addition, the device exhibits a volatile photoresponse under 405 nm illumination conditions, enabling optically induced potentiation and depression depending on light intensity, mimicking short-term synaptic plasticity. Leveraging this dual electrical–optical modulation, we implemented a physical reservoir computing system using optically stimulated devices to process 4-bit encoded Modified National Institute of Standards and Technology inputs, achieving a classification accuracy of 96.35%. These results highlight the potential of the ITO/AlScN/n+ Si memristor as a compact, energy-efficient platform for next-generation optoelectronic neuromorphic systems.