Search Results (2,472)

This paper presents a theoretical analysis of frequency shifts in broadband acoustic field interference structures caused by an internal soliton wave in shallow water. It analyzes the spectral signature of interference-maxima frequency shifts within a coupled-mode framework that describes the scattering of acoustic normal modes under soliton-induced perturbations. Using the weak coupling approximation, analytical expressions are obtained for modal phase variations and the spectral peak frequency associated with the temporal evolution of frequency shifts induced by internal soliton waves. The analytical estimates obtained in the weak coupling approximation are extensively validated using numerical simulations under realistic ocean conditions without invoking it. This paper’s theoretical analysis demonstrates that internal soliton wave-induced mode coupling produces frequency shift spectrum signatures that strongly depend on soliton parameters. These results suggest that it is potentially feasible to estimate key soliton parameters, such as propagation direction, velocity, and effective amplitude, from measured frequency shifts. Numerical simulations demonstrate the feasibility of solving this inverse problem. These findings highlight the potential of frequency shift analysis as a practical, robust tool for remote sensing of internal wave dynamics in ocean acoustics. Full article

Achieving low hydration heat without sacrificing strength is essential for early-age temperature-crack control in concrete. This study designed a low-heat Portland cement (LHPC)–fly ash (FA)–ground-granulated blast-furnace slag (GGBS)–silica fume (SF) binder system with LHPC fixed at 80 wt.% and total supplementary cementitious materials (SCMs) fixed at 20 wt.%. Compressive strength at 3, 7, and 28 d, 7 d isothermal calorimetry combined with Krstulović–Dabić (K–D) modeling, X-ray diffraction (XRD), thermogravimetric analysis (TGA), and scanning electron microscopy (SEM) were used to identify a low-heat/high-strength pathway. The mixture containing 20 wt.% FA (F20) reduced the 7 d cumulative heat to 194.060 J·g⁻¹ but lowered the 28 d compressive strength to 44.2 MPa. Replacing FA with GGBS under the same replacement level restored the strength baseline, and the mixture containing 20 wt.% GGBS (G20) reached 56.7 MPa. Introducing SF created an optimum compositional window, and the mixture containing 10 wt.% FA, 3 wt.% GGBS, and 7 wt.% SF (F10G3S7) achieved the highest 28 d strength of 58.2 MPa. Notably, the mixture containing 10 wt.% FA, 9 wt.% GGBS, and 1 wt.% SF (F10G9S1) combined relatively low 7 d heat (203.545 J·g⁻¹) with high 28 d strength (54.2 MPa). K–D fitting showed that FA lowered the heat potential (Qmax = 217.98 J·g⁻¹) relative to LHPC (236.19 J·g⁻¹), whereas GGBS/SF blends increased Qmax to 268.77–271.55 J·g⁻¹, indicating composition-dependent hydration efficiency. TGA revealed higher bound water per unit LHPC at 28 d (21.46–22.97%) than in LHPC alone (17.17%), and bound water correlated more strongly with compressive strength (R² = 0.75–0.78) than calcium hydroxide (CH) content (R² = 0.66–0.67). SEM confirmed a more continuous gel-rich matrix in F10G9S1, suggesting that the low-heat/high-strength route is governed by efficient heat-to-hydrate conversion and microstructural densification rather than heat output alone. These findings provide both mechanistic insight and practical guidance for proportioning low-heat, high-strength binders for concrete applications requiring early-age temperature-crack control. Full article

Safety-oriented UAV motion planning relies on distance-to-obstacle fields and their gradients, yet onboard mapping is typically limited to bounded local distance updates. Consequently, optimization may stall outside the updated band due to missing gradients, while enlarging the update range substantially increases computational cost. Our key insight is that motion-planning locality implies only a small subset of obstacles governs local trajectory refinement. We term this subset points of interest (POIs). Motivated by this observation, we develop a locality-aware sequential motion planning framework with a POI-driven feedback mechanism that continuously identifies and augments these trajectory-relevant obstacles during search and optimization. The mechanism tightly couples mapping, search, and optimization and enables safe trajectory refinement without requiring global distance updates. The framework adopts a heuristic mapping strategy that combines a long-term occupancy grid with bounded incremental distance updates and a POI-based short-term k-d tree, enabling efficient nearest-neighbor queries and gradient proxies beyond the update band. The search process generates a dynamically feasible initial trajectory in the long-term map while collecting POIs, which are then used to construct the short-term component. The trajectory is subsequently refined through iterative optimization loops, where newly exposed closest obstacles are incorporated into the POI set and the short-term map is updated until convergence. Safety is enforced through conservative collision checking against the inflated long-term occupancy map. Simulations in building and forest environments show that 99.7% of trials converge within two refinements in sparse scenes and none exceed four overall. Compared with FastPlanner and EgoPlanner, the proposed method achieves consistently larger obstacle clearances. Onboard experiments further validate its practicality under real sensing and computational constraints. Full article

This article examines the integrability of the combined KdV-mKdV equation, which provides an effective framework for modeling coherent structures in turbulent flows. We generate the explicit Darboux solutions for the combined KdV-mKdV equation using Wronskians. These results are further generalized to the K-th order and supplemented as the logarithmic derivative of the K-th order Wronskian that provides us with the multi-soliton solutions. We generate the exact explicit solution for one-, two-, and three-solitons. Graphical depictions of the soliton formations’ interactions, dynamical characteristics, and temporal evolution are used to support these conclusions. Furthermore, we generate the multi-wave and periodic cross-kink wave solutions by employing bilinear formulism. The graphical representations of these nonlinear excitations highlight their extensive dynamical activity and structural complexity. Full article

Background: Arginine and related amino acids are widely used to suppress protein aggregation, thereby affecting stability, manufacturability, and therapeutic performance. However, their effectiveness remains limited, necessitating the exploration of alternative strategies. Previous studies have shown that N-acetyl-L-arginine (NA-Arg) can improve protein stability; however, the potential of other N-acetylated amino acids has not been fully explored. Methods: This study aimed to investigate the effects of multiple N-acetylated amino acids as alternative excipients on aggregation, colloidal stability, and viscosity in intravenous immunoglobulin (IVIG) formulations. Dynamic light scattering (DLS) was used to evaluate diffusion behavior and aggregation tendencies, while complementary analyses were performed using size-exclusion chromatography (SEC) and flow-imaging microscopy (FI). Results: Overall, N-acetylation of amino acids improved colloidal stability, shifting the kD values from −5.87 to 6.83 mL/g for arginine and from −8.17 to 16.22 mL/g for histidine, and increased the aggregation onset temperature (Tagg) to above 60 °C. Among the tested compounds, N-acetyl-L-histidine (NA-His) showed the most favorable results, increasing the monomer proportion by approximately 4%, reducing high-molecular-weight species to below 2%, and producing a greater than 10-fold decrease in subvisible particles relative to histidine hydrochloride after 5 days of agitation. At 50 mM, both NA-His and NA-Arg reduced the viscosity of highly concentrated 200 mg/mL IVIG formulations, with NA-His exhibiting the lowest viscosity (7.24 ± 0.12 mPa·s). Protein–protein interaction and surface charge analyses indicated improved colloidal stability relative to parent amino acids, attributable to the presence of the acetyl group. Conclusions: These findings support the potential of N-acetylation as a strategy to modulate interaction-driven instability and suggest NA-His as a promising candidate excipient for stabilizing highly concentrated therapeutic proteins at acidic pH. Full article

Galectins are a functionally diverse family of β-galactosyl-binding lectins that are ubiquitously present in animal species, with key roles in development and immune regulation. Recently, galectins have been found to recognize microbial glycosylated moieties, but the detailed mechanisms of their innate immune functions in mucosal epithelia have remained elusive. The zebrafish (Danio rerio) represents an ideal genetically tractable model to address these questions, as the skin, gills, and gut display mucosal surfaces exposed to the environment. In this study, we investigated the range of endogenous and microbial glycans that are recognized by zebrafish galectin Drgal1 present in epidermal mucus, which would be consistent with defense functions against a bacterial challenge. Results revealed that zebrafish galectin isoform Drgal1-L2 can recognize selected bacterial glycans, as well as zebrafish mucus glycans and cell-surface receptors for bacterial adhesins such as fibronectin (K_D = 1.593 × 10⁻⁶ M) and CD147 (K_D = 1.115 × 10⁻⁶ M). Furthermore, preliminary experiments revealed that Drgal1-L2 may hinder bacterial adhesion to epidermal mucus in about 50% at 2.5 μg/mL. Our results suggest that Drgal1-L2 present in epidermal mucus can prevent access of pathogenic bacteria to the epithelial cell surface by alternate or synergic binding to bacterial glycans and to zebrafish mucus components and epithelial receptors for bacterial adhesins. Thus, the present study provides key information for the testing of the abovementioned hypothesis by implementing gene-silencing approaches targeting both zebrafish Drgal1-L2 and its ligands. Full article

Background/Objectives: PDE4 is a key regulator of cAMP signaling and a clinically validated anti-inflammatory target; however, the use of PDE4 inhibitors is often limited by adverse effects such as nausea, vomiting, and diarrhea. The natural compound braylin was previously identified as a novel PDE4 inhibitor scaffold, exhibiting an IC₅₀ of 0.96 µM. Using the PDE4–braylin co-crystal structure, we conducted structure-based design and optimization to enhance its potency. Methods: A series of novel braylin derivatives was synthesized and characterized. Their inhibitory activities against PDE4D were evaluated via enzymatic assays, and binding thermodynamics were analyzed by isothermal titration calorimetry (ITC). Molecular modeling was used to predict binding modes, and anti-inflammatory effects were assessed in LPS-stimulated macrophages. Results: Structure-guided optimization yielded lead compound L27, which showed significantly improved PDE4D inhibition (IC₅₀ = 67 nM) and high-affinity binding (K_d = 45 nM) as confirmed by ITC. L27 also exhibited remarkable selectivity against PDE isoforms. Molecular simulations highlighted key interactions with Gln369 and hydrophobic residues in the PDE4 active site. In cellular assays, L27 dose-dependently suppressed LPS-induced inflammation in macrophages at non-cytotoxic concentrations with efficacy comparable to roflumilast. Conclusions: We developed L27, a potent and selective PDE4 inhibitor derived from natural braylin. It demonstrated promising in vitro anti-inflammatory activity and represents a valuable lead for further therapeutic development. Full article

Background/Objectives: The most abundant flavonoid, quercetin, which is mostly found as glycosides, is widely distributed in plants. Quercetin is rapidly metabolized, having a short half-life in the blood circulation, and forms its conjugates by undergoing ring cleavage of the benzopyranone ring system. Despite its fast clearance in the body, quercetin was demonstrated to have clinically anti-inflammatory, cardioprotective, antidiabetic, and anti-obesity activities. This study aimed to determine whether quercetin itself or its metabolites are responsible for these activities. Methods: We performed molecular docking of 27 metabolites, including quercetin itself, against ten inflammation-related proteins in silico. We then conducted microscale thermophoresis (MST) of selected metabolites towards the NLRP3 inflammasome. Results: Overall, Phase II metabolites yielded better binding energies compared to the metabolites formed by degradation. MST results revealed that isorhamnetin, the 4-O-methylated metabolite of quercetin, gave the best results, with a binding affinity (K_D value) of 16.12 ± 5.16 µM, even better than quercetin itself, which has a binding affinity of 44.84 ± 4.21 µM. Glucuronide metabolites of quercetin (isorhamnetin 3-O-glucuronide, quercetin 7-O-glucuronide, and quercetin 3-O-glucuronide) were found to bind to the inflammasome protein with low binding affinities, whereas small degradation products (hippuric acid and 3,4-dihydroxytoluene) did not bind at all. Conclusions: These results suggest that Phase II metabolites, specifically isorhamnetin, may contribute more significantly to the biological activity of quercetin than the parent compound, however, degradation products appear inactive. Full article

Trastuzumab is the first humanised monoclonal antibody (Mab) developed for breast cancer (BC) therapy. The high affinity of Trastuzumab Fab-domain binding to the human epidermal growth factor receptor 2 (HER2) receptor, with a K_d value of <1 nM, is also accompanied by Fc domain interaction with Fc-receptors in natural killer cells and leukocytes, enabling the killing of tumour cells through antibody-directed cellular cytotoxicity (ADCC). Trastuzumab blocks the over-expressed HER2 receptor-mediated dimerization and consequent intracellular signalling, leading to cancerous growth. However, the trastuzumab resistance (TR) became the major problem within 1 year of treatment. The mutation in phosphatidylinositol 3′-kinase (PI3K) pathway, cross-talk with estrogen receptors, over-expression of Mucin 1 (MUC1) protein, insulin-like growth factor I receptor, etc., are key pathways involved in TR. In this review, we have provided a molecular view of TR and the possible remedies for overcoming TR using BC stem cell (BCSC)-based therapy, PI3K pathway inhibitors, MUC1-based treatment, etc. We have also analysed the patents and clinical trials from the pre-TR and post-TR era to rationalise the possible steps to overcome TR. Our analysis implies that Trastuzumab monotherapy no longer applies to HER2+ BC treatment. Further, combination therapy using other antibodies like pertuzumab and protein kinase inhibitors and targeting pathways like the ubiquitin proteasome pathway will be the future option for BC Treatment. Overall, this review provides a detailed summary of the molecular mechanisms involving TR and its potential ways of evasion, based on updated information from published research articles, clinical trial outcomes, and patent data. Full article

Understanding dry-out-induced weakening of reservoir and caprock rocks driven by gas displacement is critical for ensuring the operational safety and efficiency of underground gas storage (UGS). Using core samples from the Xiangguosi UGS collected from different regions and stratigraphic intervals, we quantify the evolution of dynamic elastic parameters during simulated downhole dry-out with a joint ultrasonic and nuclear magnetic resonance (NMR) monitoring system. The results show that as water saturation (S_w) decreases, the dynamic bulk modulus (K_d) and P-wave velocity (V_p) decline by varying degrees across specimens, with reductions ranging from 3.0% to 50.48% and from 1.34% to 17.56%, respectively, whereas the dynamic shear modulus (G_d) and S-wave velocity (V_s) show only minor variations throughout the process. These findings demonstrate that the sensitivity of dynamic parameters to dry-out is strongly specimen-dependent. Further analysis indicates that the dry-out response is highly variable and depends on a combination of petrophysical properties. Among these, the heterogeneity of the initial pore structure acts as an important factor, with its influence shaped by mineralogy and bulk frame rigidity. Cores with multimodal pore size distributions and well-developed macropores (long T₂ components) respond more strongly to dry-out, whereas higher clay mineral contents tend to mitigate modulus degradation by retaining water under stronger capillary confinement. Based on these observations, we propose a conceptual model of pore support and skeleton constraint. The model suggests that dry-out weakening arises from a progressive loss of pore fluid volumetric support to the rock skeleton as free water is preferentially displaced from meso- and macropores. These findings provide key experimental evidence and mechanistic insights for using geophysical methods to monitor dry-out zone expansion and to assess long-term formation stability in UGS. Full article

Background and Clinical Significance: Multiligamentous knee injuries (MLKIs) are uncommon but severe injuries associated with instability, neurovascular compromise, and long-term functional impairment. Irreducible knee dislocations are a distinct subgroup requiring urgent intervention because soft-tissue interposition may prevent closed reduction and place the limb at risk of skin necrosis and vascular compromise. This report reviews current concepts in MLKI management and presents a complex KD-IV irreducible knee dislocation treated with a staged surgical strategy. Case Presentation: A 56-year-old woman presented 24 h after a skiing injury with a grossly deformed knee, multidirectional instability, and an anteromedial “pucker sign”. Magnetic resonance imaging demonstrated a KD-IV injury with complete rupture of the anterior cruciate ligament, posterior cruciate ligament, and medial collateral ligament, associated with capsular disruption and intra-articular soft-tissue interposition causing irreducibility. Urgent open reduction was performed. The first stage included reduction of the incarcerated capsule, capsular repair, and reconstruction of the posteromedial corner and medial collateral ligament using a semitendinosus autograft. Delayed reassessment at 6 months demonstrated satisfactory stability, minimal residual anterior laxity, and no subjective instability; therefore, anterior cruciate ligament reconstruction was not performed. At final follow-up, the patient had near-full range of motion, no significant valgus instability, and no arthrofibrosis or vascular complications. Conclusions: Management of MLKIs should be individualized according to reducibility, soft-tissue condition, neurovascular status, and functional demands. Irreducible KD-IV dislocations with a pucker sign require urgent open reduction. In selected patients, staged reconstruction may reduce postoperative stiffness and allow selective omission of cruciate ligament reconstruction when satisfactory functional stability is achieved. Full article

Wearable neurotechnology depends critically on continuous movement monitoring to characterize motor impairment and recovery in real-world settings. While joint torque serves as a clinically essential kinetic marker, estimating it directly on-device from inertial signals remains challenging due to stringent computational, memory, and energy constraints. Lightweight pipelines typically omit computationally expensive time–frequency processing; however, this omission degrades the observability of dynamics encoded in 1D IMU signals and diminishes the effectiveness of standard knowledge distillation strategies. To enable reliable on-device torque inference, we propose a Physically Guided Dual-Consistency Knowledge Distillation (PDC-KD) framework that explicitly integrates biomechanical priors into the learning process through two collaborative pathways: parameter-manifold alignment and physics-guided compensation. The student network receives guidance through Fisher-information-weighted parameter transfer, ensuring robust knowledge distillation despite significant model capacity mismatch. Furthermore, the framework incorporates a physics-guided regularization term that enforces dynamically consistent torque trajectories via a numerically stable Cholesky-parameterized constraint. Experiments demonstrate that the student model preserves teacher-level predictive accuracy while operating within the stringent resource constraints of edge devices (achieving a 98% parameter reduction, ∼2× faster inference, and ∼1 ms latency). Moreover, the proposed method yields torque estimates with enhanced dynamical consistency, providing an efficient biosignal-processing solution for wearable neurotechnology platforms demanding real-time movement analytics. Full article

Various neuromodulatory benefits of the ketogenic diet (KD) have been demonstrated, yet its influence on reward learning and underlying mechanisms remain poorly defined. This study combined proteomics and metabolomics to identify key molecular changes in the hippocampus of KD-fed mice. Our analysis revealed significant upregulation of the “dopaminergic synapse” pathway, with CAMK2A emerging as a central regulator. In vitro, treatment of the hippocampal neuronal cell line HT22 with β-hydroxybutyrate (BHB), a primary KD metabolite, increased the protein expression of CAMK2A and increased the phosphorylation of its downstream target, GluA1. Crucially, Camk2a knockdown completely blocked BHB-induced p-GluA1 enhancement. To determine the behavioral relevance, we stereotaxically delivered AAV-shCamk2a into the hippocampus of KD-fed mice. Knockdown of Camk2a reversed the pro-reward effects of KD, as measured by the sucrose preference test and conditioned place preference test, without impairing general locomotor activity in the open field test. Together, these results suggest a novel BHB–CAMK2A–dopaminergic signaling axis through which KD enhances reward learning, thus bridging systemic metabolism with cognitive function and expanding our understanding of KD-mediated neuromodulation. Full article

Background/Objectives: Lung cancer (LC) remains the leading cause of cancer-related death worldwide, despite advances in systemic and targeted therapies. A mechanism of survival of tumor cells is metabolic reprogramming, characterized by increased glucose uptake, aerobic glycolysis, and alterations in mitochondrial function. These adaptations seem to support tumor growth, immune evasion, and therapeutic resistance. In parallel, supportive care and specifically nutritional interventions have become essential components of modern oncology. The interplay between metabolic reprogramming and targeted nutritional strategies represents a promising area of investigation that bridges tumor biology with supportive care, aiming to enhance both therapeutic efficacy and patient quality of life. Methods: This narrative review explores the biological and pathophysiological rationale for the ketogenic diet (KD) as a possible complementary intervention in LC management and summarizes the published preclinical and clinical data supporting this rationale. Results: We discuss key aspects of tumor metabolism, including the Warburg effect, glucose dependency, oxidative stress regulation, fatty acid metabolism, lactate cycling and tumor microenvironment interactions, with particular emphasis on how carbohydrate restriction and ketosis may exacerbate mitochondrial dysfunction in cancer cells and modulate inflammatory pathways. Furthermore, we summarize available preclinical and clinical evidence evaluating the KD in oncology and, more specifically, in LC, focusing on feasibility, safety, metabolic effects, and potential synergy with chemotherapy, radiotherapy, and immunotherapy. Conclusions: While preclinical models suggest enhanced treatment efficacy, clinical data remain limited and heterogeneous, with patient adherence representing a major challenge. Further well-designed longitudinal studies are required to clarify the therapeutic role of the ketogenic diet in lung cancer. Full article

Knowledge distillation (KD) transfers knowledge from large language models (LLMs) to smaller or similarly sized models in order to obtain efficient yet capable systems. However, performing distillation over all tokens is computationally expensive and may weaken the transfer signal. To address this limitation, Knowledge-Filtered Distillation (KFD) is introduced as a selective distillation approach in which tokens are filtered according to the divergence $KL({\mathcal{M}}_2\mid {\mathcal{M}}_0)$ between a teacher model (${\mathcal{M}}_2$) and a base model (${\mathcal{M}}_0$), while the student model (${\mathcal{M}}_1$) is also derived from the same base model. Only tokens whose divergence exceeds a predefined threshold are distilled. For the selected tokens, the teacher distribution is normalized over the Top-5 predictions, whereas tokens outside this case receive a label-ranking bonus. The proposed conditional Top-5/bonus target design is shown theoretically to yield a lower label-focused target error than using only Top-5 normalization or only the bonus across all tokens. In addition, the KL and cross-entropy (CE) losses are balanced through a dynamically computed batch-level coefficient $\alpha$. Experiments on multiple Turkish text datasets show that KFD consistently outperforms CE-only training, achieving higher accuracy with less data and shorter training time. KFD also outperforms entropy-based token selection methods and highlights the role of student initialization in effective knowledge transfer, thereby providing an efficient and scalable distillation framework for teacher–student models of equal size. Full article