Search Results (300)

Background: Global aging has led to a rise in neurodegenerative diseases. Neuroinflammation constitutes a core pathological mechanism in these disorders. The Kongsheng Zhenzhong Pill (KSZZP), a modern preparation derived from a classical Chinese herbal formula, are reputed for their sedative and cognition-enhancing effects. However, the molecular mechanism underlying its modulation of microglia-mediated neuroinflammation remains unclear. The present study was designed to assess the intervention effects of KSZZP on LPS-induced neuroinflammation in BV-2 microglial cells and to preliminarily explore the potential molecular mechanisms involved. Methods: An in vitro neuroinflammation model was established in LPS-induced BV-2 microglial cells. The chemical components of KSZZP were identified using UPLC-Q-Exactive HFX technology. The pharmacological effects of KSZZP were evaluated by assessing cell activation, inflammatory response, oxidative stress, and apoptosis. Molecular docking and Western blotting were used to explore the specific mechanism of its action on the cGAS-STING pathway. Results: Chemical analysis identified 67 components in KSZZP, primarily flavonoids, prenyl lipids, and isoflavones. KSZZP treatment dose-dependently inhibited LPS-induced BV-2 microglial activation and significantly reduced pro-inflammatory factor release. Furthermore, it alleviated oxidative stress, mitigated mitochondrial ultrastructural damage, and inhibited apoptosis induced by LPS. Molecular docking revealed that key active components of KSZZP exhibit strong binding potential to cGAS and STING proteins. Western blotting further confirmed that KSZZP dose-dependently suppressed the expression of key cGAS-STING pathway proteins (cGAS, STING) and downstream proteins associated with M1 polarization (iNOS, TNF-α, COX-2). Conclusions: This study indicates that KSZZP alleviates LPS-induced microglial activation, neuroinflammation, oxidative stress, mitochondrial damage, and apoptosis, and these effects may involve the modulation of the cGAS-STING signaling pathway. Collectively, these findings provide a preliminary experimental basis for understanding the anti-neuroinflammatory mechanism of KSZZP and support its potential application in the prevention and treatment of neurodegenerative diseases. Full article

Ziziphi Spinosae Semen (ZSS) is a traditional East Asian sedative–hypnotic herb with over 2000 years of clinical application. Spinosin (SPI), a characteristic flavone-C-glycoside, is the official quality marker and principal bioactive constituent of ZSS. Despite extensive research on SPI in recent years, a timely, comprehensive review integrating its pharmacological mechanisms, pharmacokinetic barriers, and translational strategies remains absent. Herein, a systematic literature search was conducted up to 31 May 2026, and we synthesize all available evidence on SPI’s chemical properties, natural sources, pharmacology, pharmacokinetics, toxicology, structural derivatives, and advanced drug delivery systems. Our analysis reveals that SPI exerts broad-spectrum pharmacological activities via multi-target modulation of serotonergic/GABAergic neurotransmission, the ERK/CREB/BDNF axis, and the Nrf2/HO-1 pathway. However, its clinical translation is severely hindered by extremely low oral bioavailability (<1%) and limited blood–brain barrier penetration due to poor aqueous solubility and P-glycoprotein-mediated efflux. Novel formulations have achieved up to 5-fold enhancement in oral bioavailability in preclinical models. While toxicological studies support a favorable safety profile, long-term toxicity and human pharmacokinetic data are lacking. This review critically discusses key translational bottlenecks and proposes evidence-based future directions to advance SPI as a natural neurotherapeutic agent. Full article

The Upper Blue Nile Basin contributes about 60% of the Nile River’s annual streamflow but faces severe sediment-related challenges driven by intense monsoonal erosion and reservoir siltation. Accurate estimation of suspended sediment concentration (SSC) and sediment load in large, data-scarce watersheds remains difficult due to sparse monitoring and complex supply-limited transport dynamics. This study develops a hybrid machine learning (ML) and process-based approach for the Kessie watershed (65,784 km²), a major sediment source upstream of the GERD. The approach combines Random Forest (RF) based SSC reconstruction from 251 intermittent samples spanning 1995–2011, approximately 70% collected during the wet season (June–October) and 94% concentrated in 2008–2011, covering a wide range of observed streamflow conditions at the time of sampling (120–5897 m³/s), with a two-stage calibration of the WASA-SED model. Using hydrologically informed predictors, the RF algorithm substantially outperformed the bias-corrected traditional sediment rating curve and other ML algorithms, increasing the validation coefficient of determination (R²) from 0.274 to 0.693. The reconstructed daily SSC yielded a mean annual sediment load of 180.7 Mt/yr. The model performed well, particularly at monthly scales for 1995–2011, achieving good to very good performance (NSE up to 0.83/0.71 for streamflow and 0.86/0.63 for sediment load, calibration/validation, respectively) and reproducing dominant hydrological and sediment regimes using duration curves. Mann–Kendall trend analysis (α = 0.05) indicated no statistically significant monotonic trends in annual rainfall (p = 0.90), mean annual streamflow (p = 0.24 observed; p = 0.84 simulated), or mean annual sediment load (p = 0.66 simulated); the reconstructed sediment load series showed a near-significant increasing tendency (p = 0.06) that falls below the accepted significance threshold and should be interpreted with caution given the short 17-year record. This hybrid approach effectively captures monsoon-driven sediment fluxes and provides model-based daily-to-monthly sediment load estimates with quantified uncertainty. It supports improved reservoir sedimentation assessment, erosion-risk evaluation, and transboundary water-resources planning in data-scarce tropical highlands. Full article

Lake eutrophication and water quality deterioration are increasingly jeopardizing both ecological integrity and human health. As a typical eutrophic shallow lake on plateaus, Yilong Lake currently faces the primary issue of excessive COD_Cr levels. Through systematic sampling and analysis, as well as static release of COD_Cr from sediment experiments, we have categorized the release process of COD_Cr and identified factors that are highly correlated with COD by using RDA and random forest analyses. The aim is to investigate the release patterns of COD_Cr in Yilong Lake, explore the primary factors influencing COD_Cr, and understand the causes of water quality pollution in the lake. The principal findings of this study are as follows: the static release of COD_Cr from sediment experiments was conducted to estimate the COD_Cr release flux from the sediments of Yilong Lake using Fick’s first law, and the release process was divided into three stages: initial release, intermediate adsorption, and late equilibrium. The RDA results indicate that SedpH and SedTP are positively correlated with both COD_Cr and COD_Mn; COD_Mn is statistically most closely related to SedAP; and COD_Cr exhibits the strongest synergy with SedpH. The random forest model output demonstrates that BOD₅ is the factor most highly correlated with COD_Cr, followed by SedAP. The results of the submerged plant humic degradation experiments show that the organic matter released during the humic degradation process of submerged plants has a significant impact on COD_Cr in water bodies, and that algal activity also affects COD_Cr. These findings provide a scientific basis for environmental protection and pollution control in Yilong Lake and similar lakes. Full article

Reliable star formation rates (SFRs) are essential for studying the connection between black hole growth and quasar host galaxies. We study the far-infrared (FIR) SFRs and the host galaxy properties of 202 SDSS and PG quasars at $0.02<z\lesssim 0.8$, spanning $log({\mathrm{SFR}}_{\mathrm{FIR}}/M_{\odot }{\mathrm{yr}}^{-1})\simeq -0.45$–$2.76$, using multiwavelength spectral energy distribution (SED) decomposition. The photometry covers wavelengths from the optical to the FIR and is supplemented by JCMT/SCUBA-2 observations at 450 and 850 $\mathsf{\mu }$m. We model the SEDs with CIGALE and AGNfitter and adopt multiple cold dust templates to quantify systematic uncertainties. The median model-dependent scatter among the five FIR SFR estimates is $0.14$ dex, and AGNfitter gives FIR SFRs lower than the mean CIGALE estimate by a median of $0.09$ dex. For the 58 quasars with SCUBA-2 coverage, including SCUBA-2 data changes the adopted FIR SFR by only ∼0.01 dex on average but can affect individual sources with limited Herschel coverage or radio-loud emission. Within our FIR-constrained sample, many quasar hosts lie on or above the star-forming main sequence, but the redshift-dependent FIR selection of the SDSS subsample limits conclusions about the full quasar-host population. We find no clear correlation between the main-sequence (MS) offset and the direct Eddington ratio, while the offset is positively related to the infrared-based $L_{\mathrm{tor}}/L_{\mathrm{Edd}}$ proxy. The minimum radiation field intensity in the dust model, $U_{\min }$, increases with bolometric luminosity and dust temperature. WISE W2 (4.6 $\mathsf{\mu }$m) and W3 (12 $\mathsf{\mu }$m) combined with Herschel bands can also provide useful empirical indicators of $f_{\mathrm{AGN}}$. Full article

Sediment transport beneath subsea pipelines is essentially a highly complex multiphase flow problem, involving strong coupling between hydrodynamics, structural response, and sediment transfer. Accurately capturing this process is of significant scientific and engineering importance for predicting seabed evolution and ensuring the structural safety and stability of subsea pipelines. In this study, the coupled vortex-induced vibration (VIV) and scour behaviour of subsea pipelines under steady current conditions is investigated using a computational fluid dynamics (CFD)-based numerical approach. The solver is developed within SedFoam by incorporating dynamic mesh motion to account for pipeline vibration. The pipeline is modelled as a single-degree-of-freedom system with a vertically mounted spring and a concentrated mass. The numerical results reveal a strong interaction between pipeline VIV and the evolving seabed morphology. Repeated pipeline motion toward the seabed significantly modifies the local scour profile and promotes the formation of a sand dune beneath the pipeline. The presence of the sand dune alters the near-bed flow field and suppresses vortex shedding beneath the pipeline. As the scour process develops and the fluid–structure–seabed interaction intensifies, the VIV response of the pipeline is progressively reduced. The present study highlights the important coupling mechanisms between pipeline vibration and seabed scour and provides insights into the dynamic evolution of pipeline–seabed interaction. Full article

Xylazole is a sedative and analgesic agent widely used in Chinese veterinary practice, valued for its convenient administration and effectiveness. This study aimed to clarify its mechanism of action by investigating the effects on cAMP and monoamine neurotransmitters using both in vitro and in vivo rat models. In rat cortical neurons, Xylazole increased cAMP levels in a concentration- and time-dependent manner, transiently increased extracellular DA levels, which subsequently declined, consistently reduced extracellular NE levels, and enhanced extracellular 5-HT along with its metabolite 5-HIAA. In contrast, in vivo administration in adult rats reduced cAMP, DA, and NE levels across multiple brain regions, including the cerebrum, hippocampus, and brainstem, while increasing 5-HT and 5-HIAA. Notably, in the cerebellum group, cAMP was elevated after drug washout, a pattern not observed in the other brain regions. These findings reveal a striking divergence: in P7 cortical neurons, Xylazole triggers an α₂-adrenoceptor-dependent cAMP elevation, whereas in adult brain regions, a high concentration of locally delivered Xylazole leads to predominantly inhibitory cAMP changes, with a notable delayed increase in the cerebellum. Because of the non-physiological concentration used in reverse microdialysis, the in vivo neurochemical patterns should be regarded as exploratory regional responses, not as evidence of specific receptor-mediated mechanisms. Full article

Physical activity is a key lifestyle factor for mental health prevention, yet the influence of accelerometer placement on mood prediction remains unclear. We merged high-resolution acceleration data and Ecological Momentary Assessment (EMA) mood reports from 259 healthy participants across three ambulatory studies (SedMood, 24 hrCog, HO). Additionally, 15 min pre-assessment movement windows consisting of raw triaxial acceleration (64 Hz) from hip, thigh, chest, and wrist sensors were paired with six-item mood EMA queries. Features (e.g., mean, entropy, spectral power) were extracted and fed into gradient-boosted decision tree models (XGBoost), trained separately for energetic arousal, valence, and calmness. Performance was measured using the metrics MAE, RMSE and R². Within individual studies, chest and hip sensors achieved the highest performance, followed by wrist and thigh. In the combined dataset, hip sensors again outperformed thigh (R² 0.38 vs. 0.20). Multi-sensor models rarely surpassed the best single-sensor configuration and sometimes reduced accuracy. These results suggest that sensor location modestly impacts mood-prediction performance, with hip and chest offering the most reliable signals, while adding sensors does not reliably enhance predictive power. Future work should explore larger, homogenous datasets and location-specific feature engineering to refine wearable-based mental health monitoring. Full article

Background/Objectives: Sedation is a fundamental component of gastrointestinal endoscopy, improving patient comfort, procedural quality, and overall satisfaction. However, traditional drug-centered sedation models are increasingly challenged by rising procedural volumes, aging populations, and limited anesthesiology resources. The aim of this narrative review is to provide an integrated overview of evolving pharmacological agents, monitoring strategies, organizational models, and future directions toward personalized, technology-supported sedation pathways. Methods: A structured literature search was conducted across PubMed/MEDLINE, Scopus, and Web of Science for studies published between January 2010 and December 2025. Relevant guidelines, randomized controlled trials, meta-analyses, and large observational studies were included. Evidence was synthesized qualitatively, emphasizing clinical applicability and real-world relevance. Results: Propofol remains the most widely used sedative agent due to its rapid onset and recovery profile, although its narrow therapeutic window and lack of antagonist limit its safety in high-risk patients. Emerging agents such as remimazolam and ciprofol demonstrate comparable efficacy with improved respiratory and hemodynamic safety profiles, particularly in elderly populations. Adjunctive strategies, including procedure-specific approaches such as spinal anesthesia, may further optimize sedation. Advanced monitoring tools, such as capnography, bispectral index, and high-flow nasal cannula, show potential in enhancing safety, especially in selected high-risk groups. Structured training programs and standardized discharge criteria are essential for ensuring quality and safety. Conclusions: Sedation in gastrointestinal endoscopy is transitioning from a standardized, drug-centered approach to a personalized, risk-adapted, and technology-supported model. Integration of novel pharmacological agents, advanced monitoring, and structured training will be key to improving patient safety, procedural efficiency, and healthcare sustainability. Full article

Background/Objectives: Insomnia is a prevalent clinical sleep disorder, with existing hypnotic therapies limited by safety concerns. There is an urgent clinical need for new safe, effective sleep-promoting candidates derived from natural products. Spinosin is one of the main active components of Semen Ziziphi Spinosae that exerts sedative and hypnotic effects. The adenosine receptor (AR) has been reported as a potential therapeutic target for insomnia; however, the hypnotic effect of spinosin through the A_2AR remains to be elucidated. Methods: In the study, the involvement of A_2ARs in spinosin’s hypnotic effect was investigated using caffeine and further elucidated in A_2AR-knockout (KO) mice. Diazepam was used as a positive control drug to validate the experimental model and evaluate the hypnotic effect of spinosin. Molecular docking and molecular dynamics (MDs) simulations were performed to validate the interaction of spinosin with the A_2AR. Results: The hypnotic effects of spinosin were effectively antagonized by caffeine. Compared with A_2AR-wild-type (WT) mice, spinosin-induced non-rapid eye movement (NREM) sleep and locomotor activity diminution were significantly reduced in A_2AR-KO mice. Spinosin significantly increased the activity of γ-aminobutyric acid (GABA)ergic medium spiny neurons (MSNs) in the nucleus accumbens (NAc) and significantly decreased the activity of orexin neurons in the lateral hypothalamus (LH), as revealed by c-Fos immunostaining. These effects were significantly reversed by caffeine pretreatment or in A_2AR-KO mice. Finally, the results of molecular docking showed that spinosin had a good binding potential with the A_2AR. MD simulations further demonstrated that spinosin had strong binding stability with the A_2AR. Conclusions: Our findings strongly suggest that spinosin exerts the hypnotic effects through the A_2AR, and thus may have therapeutic potential for insomnia. Our identification of spinosin’s direct molecular target supports its translational potential as a novel natural-origin candidate for clinical insomnia drug development. Full article

Sound Event Localization and Detection (SELD) integrates Sound Event Detection (SED) and Direction-of-Arrival Estimation (DOAE) to recognize and localize sound events in various applications, including urban sound sensing, wildlife monitoring, and home surveillance. Recently, advancements in machine learning, particularly deep learning techniques, have demonstrated remarkable success in improving SELD performance. However, training deep learning models for SELD is challenged by the limited availability of high-quality spatial audio data, which is essential for accurate model generalization. This paper explores the effectiveness of data augmentation techniques in overcoming this limitation. We evaluate the impact of Frequency Shift (FS), Random Cutout (RC), and Channel Swapping (CS) on SELD performance using a comprehensive set of experiments. Our findings indicate that all tested augmentation combinations except FS alone significantly improve SELD performance, reducing the SELD error by approximately 8% compared to no augmentation. The differences among effective combinations are not statistically significant, suggesting that the decision to augment is more impactful than the specific combination chosen. This work highlights the critical role of data augmentation in enhancing SELD systems and suggests future research directions, including testing these techniques with different model architectures and exploring additional augmentation methods. Full article

This study develops an end-to-end workflow, from laboratory measurements to Eulerian–Eulerian two-phase simulations with SedFoam, to investigate bed erosion in free-surface open-channel flow over a deformable granular bed. Experiments were conducted with a calibrated non-cohesive deposit of epoxy-coated spherical beads under steady, fully turbulent, subcritical conditions. Particle Image Velocimetry provided mean-flow and turbulence data, while a 3D camera workflow supplied bed-elevation fields and time-resolved maps of sediment rearrangement. These datasets were used to constrain a staged numerical strategy in which single-phase hydrodynamics were first reproduced and then extended to live-bed morphodynamics. Validation over a rigid bed showed that the 2006 k–$\omega$ closure, combined with a rough-wall treatment, reproduced the measured mean-velocity profiles and provided acceptable turbulent kinetic energy levels, yielding dynamically consistent near-bed shear conditions. In live-bed conditions, the simulations reproduced the streamwise organization of scour and deposition, predicted cumulative erosion rates of the correct order of magnitude, and captured bedform migration consistent with time-resolved bed reconstructions. The numerical results were compared with repeated experiments while accounting for run-to-run variability and the metrological limits of the 3D camera. This work proposes a transferable experimental–numerical methodology for assessing the predictive capability of live-bed morphodynamic simulations, in which hydraulic characterization, three-dimensional bed monitoring, erosion/deposition metrics, and repeated experiments are combined within a common comparison procedure. Full article

Background/Objective: Childhood obesity induces physiological changes that alter drug distribution and clearance; however, these patients are often excluded from clinical trials, creating a critical safety gap for high-alert medications (HAM). The Objective was to evaluate HAM dosing strategies and pharmacokinetic (PK) alterations in overweight and obese pediatric patients. Methods: A systematic review was conducted and registered in PROSPERO (CRD42023452126). A search of MEDLINE, EMBASE, Web of Science, and Cochrane CENTRAL (1990–March 2026) identified studies reporting dosing strategies or PK of HAM in obese or overweight pediatric patients. Studies were included if they reported dosing recommendations or PK parameters. Eligible designs comprised prospective and retrospective, randomized and non-randomized, observational (cohort, case-control, and cross-sectional), case series, case reports, and narrative and systematic reviews. Study selection, data extraction, and quality assessment were conducted independently by two reviewers. Methodological quality was assessed using validated tools, and results were synthesized qualitatively. Results: Of 5801 records, 91 studies were included, providing evidence for only 27% of the evaluated HAM. Total body weight (TBW) appeared to be appropriate for insulin and vancomycin, although close monitoring was required. TBW-based dosing was associated with approximately 20% overexposure for enoxaparin, supporting the use of fat-free mass (FFM) or reduced dosing strategies. Increased clearance may justify higher doses for amlodipine and consideration of adult-equivalent dosing for metformin in adolescents. For gentamicin, FFM appeared to be the most appropriate descriptor, while adjusted body weight was used for valproic acid. In anesthetics and sedatives, reduced TBW-based dosing may be considered for propofol, whereas ideal body weight (IBW) or FFM were generally preferred for ketamine and dexmedetomidine. Analgesics such as fentanyl and morphine may require IBW- or FFM-based dosing, and maintenance dosing of paracetamol may require adjustment. Conclusions: Evidence remains limited and heterogeneous, with no standardized dosing approach. Model-informed strategies—such as population PK (PopPK) and physiologically based PK model (PBPK) approaches—may be useful for hypothesis generation and exploring PK variability; however, their clinical applicability is constrained by the limited and heterogeneous evidence base, and they should be considered exploratory. Full article

Nearby ($z<0.1$) TeV-detected, high-energy-peaked BL Lacertae objects (HBLs) are among the most prominent extragalactic sources of the highest-energy photons, sometimes detected at energies of ∼10 TeV or beyond. These objects show a strong and complex flux variability, with strong flares and exceptional outbursts, as well as very rapid and large-amplitude TeV-band variations on timescales down to a few minutes during such instances. The higher-energy component of broadband spectral energy distribution (SED) is stretched over the MeV–TeV domain and, generally peaking beyond 100 GeV, has a controversial origin, and different emission scenarios (one- or multi-zone synchrotron self-Compton, hadronic cascades, etc.) are proposed. This paper presents a review of the TeV-band timing and spectral results obtained in the framework of different observational campaigns for nearby HBLs, their implications for different emission scenarios, and basic results from the corresponding SED modelings. Finally, the prospect of filling the observational gaps above some threshold energy by means of the planned projects for the dedicated $\gamma$-ray observations and, consequently, solving the different persisting problems related to the innermost structure, particle acceleration, and emission mechanisms are also presented. Full article

Background/Objectives: Strain energy density-based algorithms are widely applied in modelling bone healing, yet their use under patient-specific geometry-based conditions remains underdeveloped. This study proposes a patient-specific geometry-based framework for fracture healing simulation and investigates how different postoperative loading conditions influence the mechanical environment of callus remodeling. Methods: Using postoperative radiographic data of a 63-year-old male patient with a distal diaphyseal tibial fracture and concomitant proximal and distal fibular fractures, a three-dimensional finite element model of the tibia was reconstructed, imported into a multiphysics simulation environment, and coupled with an iterative numerical algorithm. A uniform initial callus density of 750 kg/m³ was assumed as a simplified and homogenized representation of the healing tissue. The effects of different mechanical loading conditions (partial weight-bearing, physiological loading, and supraphysiological loading) on the mechanical response and density evolution of the callus were evaluated. Results: Partial weight-bearing resulted in insufficient mechanical stimulation and progressive density loss within the callus. Physiological loading generated strain energy density levels consistent with known osteogenic ranges and contributed to continuous cortical shell formation and overall density increase. Supraphysiological loading was associated with overload-related resorption and spatial heterogeneity, which may reduce callus stability. Conclusions: The findings suggest that loading magnitude may influence the simulated remodeling response of the callus under the assumptions of the present model. These results indicate that intermediate loading conditions were associated with a more pronounced remodeling response compared to reduced or excessive loading for the investigated case. The comparison with postoperative clinical imaging showed qualitative agreement in the spatial distribution of mineralized and less mineralized regions, supporting the feasibility of the proposed patient-specific geometry-based SED-based framework. Full article