Browse Articles

Electro-optical nonlinearity and Kerr effect engineering in SnO2-doped nematic liquid crystal for advanced photonic applications

Programmable SHG switching enabled by sliding ferroelectricity in bilayer MoS2

Achieving programmable second-harmonic generation (SHG) switching in two-dimensional materials is highly desirable for optical switching, communication, and information storage in next-generation integrated photonic technologies. In this work, we reveal that sliding ferroelectricity can programmably and reversibly modulate the SHG response, thereby enabling SHG switching in bilayer MoS2 based on compelling first-principles calculations. Interlayer sliding induces interfacial charge redistribution, giving rise to ferroelectric polarization reversal, accompanied by systematic modulation of interlayer coupling and electronic structure. Correspondingly, the SHG tensor is reconstructed in a symmetry-dependent manner, while the out-of-plane components exhibit a one-to-one correspondence with ferroelectric polarization reversal, realizing robust and programmable SHG switching with broad amplitude tunability. The underlying SHG polarity reversal originates from sign-inverted momentum-resolved susceptibility distributions and two-photon transitions between mirror-symmetric electronic states. The switching behavior is further manifested in polarization-resolved SHG patterns, which evolve from a threefold distribution to a sixfold pattern and recover with a rigid π/3 rotation. Building on these characteristics, we propose a sliding-ferroelectric nonlinear optical device enabling high-contrast optical readout in a compact footprint. Our work establishes sliding ferroelectricity as an effective paradigm for programmable SHG switching, shedding light on the intrinsic coupling of sliding ferroelectricity with SHG and guiding the design of ultrathin, integrated nonlinear photonic devices.

SLC27A1 overexpression correlates with lactylation and poor colorectal cancer progression

Parity violation effects in helical osmocene: Theoretical analysis and experimental prospects

We present a computational investigation of the parity-violating contributions to the vibrational transitions and nuclear magnetic resonance shieldings of helical osmocene. A number of promising transitions within the spectral window of currently available sub-Hz metrology-grade lasers are identified, exhibiting high intensities and parity violation shifts of up to 7 Hz. We discuss the prospects for the synthesis of this compound and for subsequent ultra-precise mid-IR spectroscopy toward the first detection of parity violation in a chiral molecule.

Enhanced proteolytic stability and distinct mechanisms of a D-amino acid-modified antimicrobial peptide against Pseudomonas aeruginosa

Electron transfer, diabatic couplings, and vibronic energy gaps in a phase space electronic structure framework

We investigate the well-known Shin–Metiu model for an electronic crossing, using both a standard Born–Huang (BH) framework and a novel phase space (PS) electronic Hamiltonian framework. We show that as long as we are not in the strongly nonadiabatic region, a PS framework can obtain a relative error in vibrational energy gap and other vibronic matrix elements that are consistently one order of magnitude smaller than what is found within a BH framework. In line with recent results showing that dynamics on one PS surface can outperform dynamics on one Born–Oppenheimer surface, our results indicate that the same advantages should largely hold for curve crossings and dynamics on two or a handful of electronic surfaces, from which several implications can be surmised as far as the possibility of spin-dependent electron transfer dynamics.

Trifluridine/tipiracil enhances radiation-induced abscopal effects and augments PD-1 blockade in gastric cancer

Abstract Gastric cancer (GC) often exhibits resistance to anti-programmed death-1 (PD-1) immunotherapy. Immunogenic cell death (ICD) enhances antitumor immunity, and trifluridine/tipiracil (FTD/TPI) induces ICD and modulates immunity. Radiation therapy (RT) may trigger abscopal effects. We investigated whether FTD/TPI combined with RT enhances tumor immunity in GC and its impact with PD-1 blockade. ICD induction by FTD and RT in YTN16 mouse GC cells was assessed by calreticulin, high-mobility group box 1 (HMGB1), and ATP evaluation. A dual subcutaneous YTN16 tumor model was established in C57BL/6J mice; mice were treated with FTD/TPI and RT (with irradiation of the first tumor). ICD was induced in vitro by FTD or RT and enhanced by the combination, as indicated by increased calreticulin surface expression and HMGB1 and ATP release. ICD induction in the first tumor was confirmed by HMGB1 release. FTD/TPI + RT suppressed growth of the second tumor and enhanced antitumor immunity by increasing CD8⁺ T-cell infiltration and depleting M2 macrophages. PD-1 expression on CD8⁺ T cells increased after FTD/TPI + RT; adding anti-PD-1 further suppressed the second tumor growth. Our findings support clinical trials of this triple-combination strategy in advanced GC, particularly in subgroups refractory to immune checkpoint blockade.

Chain-length-dependent partitioning of 1-alkanols in raft-like lipid membranes

Although 1-alkanols are widely used as anesthetics and membrane-active agents, the molecular basis of their chain-length-dependent cutoff behavior remains unclear. Here, we perform extensive atomistic molecular dynamics simulations to investigate the partitioning of 1-alkanols with varying chain lengths in a raft-like lipid bilayer composed of dipalmitoylphosphatidylcholine (DPPC), dioleoylphosphatidylcholine (DOPC), and cholesterol (Chol), which exhibits coexistence of liquid-ordered (lo) and liquid-disordered (ld) domains. We observe pronounced lateral heterogeneity in alkanol distribution, membrane thickness, number density, and lateral pressure profiles across coexisting phases. A distinct cutoff chain length, ncutoff = 12, is identified: alkanols with n < ncutoff preferentially partition into DOPC-rich ld domains, whereas alkanols with n ≥ ncutoff preferentially localize within DPPC- and cholesterol-rich lo domains. Our results indicate a reduction in the magnitude of the lateral pressure profile and the associated elastic moments upon incorporation of 1-alkanols relative to the alkanol-free membrane, within statistical uncertainty. The results provide a detailed molecular characterization of how alkanol chain length modulates the membrane structure and mechanical response in laterally heterogeneous lipid membranes.

Meet the academics refusing to use generative AI

Dose-dependent doxycycline local drug delivery using T-PRF: preliminary in vitro study

Abstract T-PRF is an autologous platelet concentrate widely used in medicine and dentistry. Its potential as a local drug delivery system remains an area of growing interest. This study aimed to evaluate the characteristics and performance of T-PRF membranes loaded with different doses of doxycycline (0.5 mL, 1 mL, and 2 mL). T-PRF membranes were prepared from 15 healthy individuals without bleeding disorders. Each membrane was injected with one of the three doxycycline doses, and outcomes were compared with non–drug-loaded controls. Fibrin network patterns, antibacterial activity against Staphylococcus aureus and Pseudomonas aeruginosa , doxycycline release over time, and membrane degradation rates were assessed using light microscopy and standard microbiological methods. In this preliminary in vitro study, doxycycline-loaded T-PRF membranes exhibited lower degradation rates than unloaded controls, with the 2 mL group showing the slowest degradation ( p  ≤ 0.001), suggesting that higher drug loading may enhance membrane stability. Fibrin network scores were higher in all drug-loaded groups ( p  ≤ 0.001), indicating a denser matrix that could support sustained drug retention. All membranes demonstrated antibacterial activity against S. aureus, whereas no activity was observed against P. aeruginosa, highlighting the selective antimicrobial potential of doxycycline-loaded T-PRF membranes. Among the tested groups, the 2 mL dose produced the largest inhibition zone, reflecting the most pronounced antibacterial effect within the studied range. While these results are encouraging, they should be interpreted as preliminary observations given the in vitro design, the use of the disk diffusion method, and the semi-quantitative nature of the release data. Overall, these in vitro findings indicate that doxycycline-loaded T-PRF membranes provide selective antibacterial activity and enhanced membrane stability, suggesting that autologous T-PRF may be a promising platform for local antimicrobial delivery. Further studies are needed to confirm their effectiveness and explore controlled release under more comprehensive conditions.

Molecular design of electrolyte additives for aqueous zinc-ion batteries via reinforcement learning and quantum chemistry calculations

The use of electrolyte additives is regarded as a cost-effective strategy to regulate the components of aqueous zinc-ion batteries (AZIBs) and to improve their overall electrochemical performance. Here, we demonstrate an artificial-intelligence-guided framework that integrates machine learning and quantum chemistry calculations to accelerate the rational design of electrolyte additives for AZIBs. Using a molecular generator based on a recurrent neural network and the Monte Carlo tree search method, we efficiently identified seven top-ranked candidate molecules, including imidazole, heptane, and dihydropyrimidinone derivatives. These molecules bind Zn2+ ions more strongly than H2O does, due to their higher highest-occupied molecular orbital (HOMO) energies. Furthermore, their binding strengths surpass those of established electrolyte additives such as pyridine, 1,2-dimethoxyethane, and tetrahydrofuran. High-level quantum chemistry calculations reveal that the spatial localization of the HOMO-1 orbital plays a critical role in determining the preferred coordination site for Zn2+. Force-field molecular dynamics simulations provide direct evidence that these molecules preferentially appear in the first solvation sheath structure of Zn2+ ions, effectively modifying the conventional hydration structure of [Zn(H2O)6]2+. This study substantially shortens the screening cycle of functional molecules and provides new insights into the molecular design of electrolyte additives for AZIBs.

FC-FTCP: a lightweight fault-tolerant clustering protocol for secure IoT data transmission

Conductivity in Li-ion gel polymer electrolytes: Role of ultrafast solution dynamics and agreement between Onsager predictions and measurements

In this paper, we studied the role of ultrafast medium dynamics in determining the conductivity of a representative gel polymer electrolyte system composed of propylene carbonate, lithium perchlorate (LiClO4), and polypropylene glycol (PPG), with a fixed PC:LiClO4 ratio of 10.7, and explored the possible reasons behind the breakdown of Onsager theory in successfully predicting the composition-dependent measured conductivities at different temperatures. For this purpose, we measured the solution dynamical response by employing frequency dependent dielectric relaxation (DR) experiments and a streak camera-based fluorescence dynamics setup. These measurements indicated fast solution dynamics facilitated ion transport, while the slow diffusive dynamics offered frictional resistance. These opposite roles for the fast and the slow dynamics led to viscosity decoupling of conductivity and suggested the presence of non-hydrodynamic modes for ion transport. Our dynamic light scattering measurements suggested the presence of polymer-induced aggregated structures (∼2000–5000 nm) in these solutions, hinting at a negligible contribution from the center-of-mass motions of these nanoaggregates to the measured conductivities. Raman spectroscopic measurements indicated PC–PPG interaction and suppression of ion-pair formation upon addition of PPG. Comparison of experimental conductivities to Hubbard–Onsager (HO) predictions reveals a strong sensitivity to the high-frequency dielectric constant (ε∞) and average DR times τDR. Use of a relatively faster τDR in the HO theory significantly improves the predictions, emphasizing the importance of the ultrafast medium dynamics. This demonstrates the overwhelming dominance of the long-wavelength collective medium polarization modes in governing ion transport and suggests a possible route for optimization of solution composition for battery applications.

Editorial Expression of Concern: Nociceptive neurons promote gastric tumour progression via a CGRP–RAMP1 axis

A hybrid evolutionary framework for efficient IoT task scheduling in fog computing

How back reaction, hydrogen transport, and capillarity control the performance of hydrogen release from liquid organic carriers

We derive a theoretical model to elucidate the inhibition of catalytic activity during the dehydrogenation of Liquid Organic Hydrogen Carriers (LOHCs). Within our model, we account for the reversible nature of the hydrogenation–dehydrogenation reaction as well as the transport of both LOHC and produced hydrogen. Our analysis reveals that the main limiting factor for the performance of porous catalysts is the transport of dissolved hydrogen, which has been overlooked so far. In particular, we show that two distinct kinetic regimes can arise depending on whether hydrogen leaves the pellet in the form of bubbles or via diffusion. Moreover, we derive the conditions for the onset of bubbling depending on hydrogen supersaturation and capillarity. Beyond LOHC systems, our findings are applicable to a broader class of reversible reactions, particularly those involving volatile products that can leave the liquid reaction medium in the form of bubbles.

The role of temporomandibular joint mobilization in the management of benign paroxysmal positional vertigo: randomized controlled trial

Flocking as a continuous phase transition in self-aligning active crystals

We study a two-dimensional crystal composed of active units governed by self-alignment. This mechanism induces a torque that aligns a particle’s orientation with its velocity and leads to a phase transition from a disordered to a flocking crystal. Here, we provide the first microscopic theory that analytically maps the crystal dynamics onto a Landau–Ginzburg model, in which the velocity-dependent effective free energy undergoes a transition from a single-well shape to a Mexican-hat profile. As confirmed by simulations, our theory quantitatively predicts the transition point and characteristic spatial velocity correlations. The continuous variation of the order parameter and the divergence of the analytically predicted correlation length imply that flocking in self-aligning active crystals corresponds to a continuous phase transition of the Berezinskii–Kosterlitz–Thouless type in two dimensions and to a second-order phase transition in three dimensions. These findings provide a theoretical foundation for the flocking phenomenon observed experimentally in active granular particles and migrating cells.

A two-stream network with global-local feature fusion for bone age assessment

Abstract Bone age assessment (BAA) is a widely used clinical technique that can accurately reflect an individual’s growth and development level, as well as maturity. In recent years, although deep learning has advanced the field of bone age assessment, existing methods face challenges in efficiently balancing global features and local skeletal details. This study aims to develop an automated bone age assessment system based on a two-stream deep learning architecture to achieve higher accuracy in bone age assessment. We propose the BoNet+ model incorporating global and local feature extraction channels. A Transformer module is introduced into the global feature extraction channel to enhance the ability in extracting global features through multi-head self-attention mechanism. A RFAConv module is incorporated into the local feature extraction channel to generate adaptive attention maps within multiscale receptive fields, enhancing local feature extraction capabilities. Global and local features are concatenated along the channel dimension and optimized by an Inception-V3 network. The proposed method has been validated on the Radiological Society of North America (RSNA) and Radiological Hand Pose Estimation (RHPE) test datasets, achieving mean absolute errors (MAEs) of 3.81 and 5.65 months, respectively. These results are comparable to the state-of-the-art. The BoNet+ model reduces the clinical workload and achieves automatic, high-precision, and more objective bone age assessment.

Exact factorization of unitary transformations with spin-adapted generators

Preserving spin symmetry in variational quantum algorithms is essential for producing physically meaningful electronic wave functions. Implementing spin-adapted transformations on quantum hardware, however, is challenging because the corresponding fermionic generators translate into noncommuting Pauli operators. In this study, we introduce an exact and computationally efficient factorization of spin-adapted unitaries derived from fermionic double excitation and deexcitation rotations. These unitaries are expressed as ordered products of exponentials of Pauli operators. Our method exploits the fact that the elementary operators in these generators form small Lie algebras. By working in the adjoint representation of these algebras, we reformulate the factorization problem as a low-dimensional nonlinear optimization over matrix exponentials. This approach enables precise numerical reparametrization of the unitaries without relying on symbolic manipulations. The proposed factorization provides a practical strategy for constructing symmetry-conserving quantum circuits within variational algorithms. It preserves spin symmetry by design, reduces implementation cost, and ensures the accurate representation of electronic states in quantum simulations of molecular systems.