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Irisin activates the AMPK-Beclin1 signaling pathway to regulate pulmonary autophagy induced by CSE + LPS
Structural, mechanical, and thermodynamic properties of solid BeF <b>2</b> at finite temperatures based on machine learning force field simulations
As a primary component of molten salt reactor (MSR) fuel and coolant mixtures, BeF2 exhibits critical mechanical and thermodynamic behaviors at high temperatures that are essential for MSR design. This study systematically investigates the structural, mechanical, and thermodynamic properties of solid BeF2 at finite temperatures using first-principles calculations and machine learning force field molecular dynamics simulations. BeF2 is a wide-bandgap transparent compound with a bandgap of 10.4 eV, slightly lower than that of LiF. At low temperatures, BeF2 exhibits anisotropic and brittle elastic properties, with lower resistance to external pressure and shear compared to LiF, attributed to its lower symmetry and weaker bonding strength. As the temperature rises, the elastic moduli show enhanced isotropy and ductility. The Be–F bond demonstrates strong stability at high temperatures, revealed by the atomic vibration displacement distribution and the pair correlation function, while the Be–Be and F–F distributions become more dynamically averaged. Due to the tetrahedral structure and covalent bonding characteristics, BeF2 displays a significantly higher thermal expansion coefficient than the ionic crystal LiF. Furthermore, BeF2 has a broader phonon vibration frequency distribution compared to LiF, with a notable density of states peak in the high-frequency region of 20–28 THz. This provides additional contributions to the heat capacity in the elevated temperature range, making the isobaric heat capacity of BeF2 much higher than that of LiF. These findings deepen the understanding of the fundamental properties of BeF2 and provide theoretical insights for the design and optimization of MSR fuel mixtures.
Application of machine learning-based exosome-related gene profiles in precision diagnosis and treatment of osteoarthritis
Anapole enhanced deep-ultraviolet third harmonic generation in a TiO2 metasurface
The deep ultraviolet (DUV) radiation source serves as a critical component in lithography systems, where its energy conversion performance significantly impacts applications in nanoscale photonics and quantum physics. This study presents a theoretical framework achieving exceptional third-harmonic generation with an efficiency higher than 10−2% in the DUV spectrum under optimal conditions and power scaling. Through carefully designed TiO2 nanostructures deposited on metal films, we observe pronounced anapole mode excitation that dramatically amplifies localized field intensities while facilitating nonlinear optical interactions. These findings provide crucial insights into how dielectric nanostructures with moderate refractive indices can manipulate DUV frequency conversion via anapole states, offering new possibilities for developing compact nonlinear optical devices and subwavelength light sources.
Hybrid wavelet transform, K-means singular value decomposition and Spatial memory guided cat swarm optimization technique for watermark embedding
Stability of hydrogen-filled hexagonal ice under high pressure
Hydrogen hydrates, composed of a water (H2O) host framework enclosing hydrogen (H2) molecules, exhibit diverse crystal structures. The stability of their high-pressure phases provides fundamental insight into the constituents of giant planets—rich in both H2O and H2—as well as their potential for energy storage on Earth. While H2-filled ice Ic (C2 hydrate) is known to be stable above 2 GPa, the possible existence of H2-filled ice Ih (named CIh hydrate) has remained largely unexplored. Here, we employ hybrid grand-canonical Monte Carlo and isothermal–isobaric molecular dynamics simulations to demonstrate that ice Ih can absorb H2 up to an H2-to-H2O ratio of 0.5 upon compression. Moreover, free energy calculations reveal that CIh hydrate becomes thermodynamically stable under a few gigapascals, thereby occupying the stability conditions previously attributed to C1 hydrate.
Artificial intelligence CNN for information system optimization and decision support model
Comparative studies of optimizer performance in a variational quantum eigensolver
Quantum computation holds the seminal key to overcoming inherent limitations of classical computing, potentially unlocking profound advancements across every scientific and industrial frontier. Currently and in the near future, variational quantum eigensolver (VQE) is one of the most promising algorithms in solving multi-body problems. Under the VQE framework, the classical optimizer plays a critical role in estimating expectation values. However, it is not well studied how different optimizers perform in a quantum circuit. The answer to this question helps make VQE applicable to larger systems. In this work, we scrutinize 12 optimizers on their convergence performances in VQE calculations by varying the number of qubits, depths of the quantum circuit, initial guesses, and number of measurements. It is found that gradient-based methods generally outperform the derivative-free methods. The optimizers involving stochastic processes usually fail to locate the minimum. The step length is far from trivial to reach the convergence. In addition, the Powell method is the most promising to alleviate the barren plateau problem.
Comparative molecular profiling of Helicobacter pylori infection and antibiotic genotypic resistance in paired gastric mucosa, gastric juice, and stool samples
Architecting hybrid chromophores for enhanced two photon absorption response: Synergistic integration of BODIPY–squaraine–benzimidazole
We propose a unique fusion of three two-photon (TP) active chromophores, namely BODIPY, squaraine, and benzimidazole, for engineering an efficient non-linear optical material. Furthermore, to fine-tune their TP activity, we functionalized the fused molecule with six different polar substitutions and studied the said property using the stat-of-the-art RI-CC2 method and the (aug-)cc-pVDZ basis set. Our calculations reveal that the said fusion indeed gives rise to systems with tenfold enhanced TP activity in the near-IR region than their constituent chromophores.
Characterization of glucose transporter-targeted lipid nanoparticles for enhancing n-3 PUFA utilization in slow-growing Korat chickens
Abstract The aim of this research was to investigate the synthesis of suitable carriers of nanoparticles for improving the utilization of n-3 polyunsaturated fatty acids (n-3 PUFAs) source in chicken diets. Lipid nanoparticles were successfully prepared with two different n-3 oil sources, tuna and algal oils using hot and high-pressure homogenization methods. Four preparations were defined as follows: non-targeting lipid nanoparticles containing tuna oil (TO_NPs), non-targeting lipid nanoparticles containing algal oil (AO_NPs), targeting lipid nanoparticles containing tuna oil (TO_TNPs) and targeting lipid nanoparticles containing algal oil (AO_TNPs). A second study was conducted for the targeting procedure, the treatments as follows: Control, TO_NPs and TO_TNPs. Thirty-three slow-growing chickens were examined during the post-administration kinetic at 2, 4, 8, 12 and 24 h. The physicochemical characteristics of lipid nanoparticles, storage stability and in vivo biodistribution were evaluated. The results showed that the particle diameters of TO_NPs and AO_NPs were 223.7 and 294.4 nm, whereas the particle diameters of TO_TNPs and AO_TNPs were 134.7 and 184.0 nm, respectively. The polydispersity index (PDI) and zeta-potential of nanoparticles showed a good distribution and stability in colloid dispersions, respectively. Moreover, the nanoparticles of the TNPs groups were less susceptible to lipid oxidation than that of the NPs groups during a storage at 4 °C. Biodistribution analysis based on Nile Red intensity indicated superior cellular uptake of TNPs. Fatty-acid profiling further confirmed this enhanced delivery, with TNPs increasing EPA and DHA deposition in breast muscle by approximately 26% and 35%, respectively, at 24 h post-administration compared with NPs. These results demonstrate the effectiveness of targeted lipid-based nanoparticles in facilitating direct transport of fatty acids into skeletal muscle cells.
Multiple Davydov <i>Ansätze</i> as solutions to Lindblad master equations
Lindblad master equations describing driven quantum systems coupled to multiple bosonic modes are central to modeling cavity quantum electrodynamics and pseudomode models. In this work, we employ the density-operator-based Dirac–Frenkel time-dependent variational principle combined with the multiple Davydov D2Ansatz to provide optimal solutions for Lindblad master equations in both multimode and driven scenarios. Our approach is benchmarked against numerically “exact” methods in two representative models. The first describes a driven qubit subject to spontaneous emission and coupled to a lossy cavity, while the second corresponds to the pseudomode Lindblad master equation derived from the driven spin-boson model, incorporating seven discrete pseudomodes. The proposed variational approach achieves excellent agreement with numerically “exact” results. Furthermore, we analyze the accuracy of the variational solutions using an error metric based on the Frobenius norm, confirming their reliability. Overall, the present method offers an accurate and computationally efficient framework for simulating Lindblad master equations in complex open quantum systems.
Conveyor belt speed detection via the synergistic fusion of optical flow and feature matching
Stochastic resolution of identity to CC2 for large systems: Excited-state gradients and derivative couplings
Excited-state gradients and derivative couplings are critical for simulating excited-state dynamics. However, their calculations are very expensive within the coupled-cluster framework due to the steep scaling. In this work, we present two implementations of stochastic resolution of identity to CC2 (sRI-CC2) for excited-state analytical gradients and derivative couplings. The first method employs sRI for both Coulomb and exchange terms, reducing the formal scaling to cubic. However, this method has significant stochastic noise. Consequently, we introduce a substitute, termed partial sRI-CC2, which applies sRI selectively to the exchange terms only. The partial sRI-CC2 shows a quartic scaling with a modest prefactor, rendering it a practical alternative. This work is an extension of our previous implementation of the sRI-CC2 method and provides essential ingredients for large-scale nonadiabatic dynamics.
Schottky-gated transistors using chitosan extracted from marine crab
Diagonal Born–Oppenheimer corrections in condensed-phase ring polymer surface hopping
Ring polymer surface hopping (RPSH) is a mixed quantum–classical dynamics method for incorporating nuclear quantum effects into nonadiabatic dynamics simulations via the extended phase-space of a classical ring polymer. Here, we systematically investigate several variants of RPSH in the frameworks of centroid and bead approximations (RPSH-CA and RPSH-BA) in modeling the dynamics of the spin-boson system across different reaction regimes, reorganization energies, and temperatures. Moreover, the effects of including the diagonal Born–Oppenheimer correction (DBOC) on the performance of the RPSH-CA and RPSH-BA methods are investigated. Our simulations of symmetric potentials, i.e., without energy bias, show that the RPSH-CA method, where nonadiabatic transitions are handled at the centroid level, is satisfactorily accurate and robust across different reaction regimes. Adding DBOC improves the method’s accuracy in specific intermediate and nonadiabatic reaction regimes at low temperature. Overall, the effect of DBOC in RPSH-CA is in moderation compared to the conventional fewest-switches surface hopping method where DBOC over-damps the dynamics significantly and reduces accuracy considerably, especially at low temperatures. However, the RPSH-CA and its DBOC variant struggle in simulations of asymmetric potentials especially at low temperatures. On the other hand, RPSH-BA results, where nonadiabatic transitions are handled at the level of individual beads of the ring polymers, are generally unreliable unless in the high temperature adiabatic reaction regimes with symmetric potentials. The inclusion of DBOC is not particularly helpful in remedying this erratic behavior. Our findings clarify when geometric corrections are beneficial or detrimental to nonadiabatic simulations using RPSH, providing practical guidance for atomistic condensed-phase applications.
Targeting cell surface GRP78-CD44v interaction suppresses cell migration in triple-negative breast cancer cells
Abstract Triple-negative breast cancer (TNBC) is characterized by the absence of estrogen receptor (ER), progesterone receptor (PR), and HER-2 amplification, rendering it unresponsive to endocrine and HER2-targeted therapies. GRP78 (78 kDa glucose-regulated protein), a key endoplasmic reticulum (ER)-resident chaperone involved in protein folding and stress response, has been observed atypically localized on the cell surface of various cancer and stressed cell types, where it engages in non-canonical signaling and cellular functions. Cell surface GRP78 (csGRP78) is preferentially expressed in malignant cells relative to normal tissue, making it an attractive therapeutic target. In this study, we report that over 70% of MDA-MB-231 TNBC cells express csGRP78. Interestingly, MDA-MB-231 cells predominantly exhibit a distinct unipolar morphology, with csGRP78 prominently co-localizing with the variant isoform of CD44 (CD44v, containing variable exon 3) at the anterior region of the cell. Co-localizations of csGRP78 and CD44v were also observed in MDA-MB-231 tumor xenografts, supporting its relevance in vivo . Importantly, targeting csGRP78 with the monoclonal antibody 76-E6 downregulated CD44v expression, inhibited Src kinase signaling, disrupted cell morphology, and suppressed cell motility. We further mapped the epitope of GRP78 targeted by 76-E6. Together, our findings identify csGRP78 as a functional regulator of cell morphology and migration at least in part via a csGRP78-CD44v axis and underscore its potential as a therapeutic target in TNBC.
Effects of bacillus on continuous cropping of sugar beets and their rhizosphere microbial community
Abstract Sugar beet is a vital sugar-producing crop, and continuous cropping poses a significant threat to its growth, leading to a decline in yield and quality. This study aimed to investigate the effects of two bacterial agents, Bacillus subtilis and Bacillus mucilaginosus , on the growth, soil physicochemical properties, and rhizosphere microbial community of sugar beet seedlings. We employed pot experiments and amplicon sequencing to analyze the impact of applying two different Bacillus agents on the microbial community structure in the rhizosphere soil of continuously cropped sugar beet and explore the microbial composition, environmental driving factors, and potential functions present within the microbial communities. The results showed that both Bacillus agents and their combination significantly promoted the growth of continuous cropping sugar beet seedlings, reaching or even surpassing the levels observed in crop rotation, improved soil pH, and enhanced soil environment. High-throughput sequencing analysis of the rhizosphere soil revealed that all Bacillus treatments induced changes in the diversity and structural composition of the rhizosphere microbial community, and significantly increased the relative abundance of Proteobacteria, thereby enriching beneficial microorganisms such as Pseudomonas , Novosphingobium , and Sphingomonas compared with that in the control group. Additionally, the application of Bacillus inoculants significantly enhanced the nitrate respiration, nitrogen respiration, and chitinolytic functions. These two bacterial agents optimized soil physicochemical properties and improved the rhizosphere soil microbial community structure, promoting sugar beet seedling growth and effectively mitigating the negative effects of continuous cropping.