Automated weed detection is essential for site-specific herbicide application, that can result into the reduced environmental footprint of conventional agriculture. However, for field deployment of automated weeding devices, occlusion remains a critical challenge that can weaken the precision of weed identification. Here, we compare the performance of Vision Transformers (ViT-B16 & PvTv2) and Convolutional Neural Networks (EfficientNet-B0 & ResNet-50) in accurate weed detection, using controlled synthetic occlusion levels (0%, 25%, and 50%). We found that ViT-B16 has superior occlusion resilience, with image testing accuracy increasing from 80% to 86% under 50% occlusion. In contrast, the testing accuracy of PvTv2, EfficientNet-B0 and ResNet-50 dropped from 45 to 76% under similar conditions. Multivariable regression confirmed architecture type as the dominant testing accuracy driver (p ≤ 0.001), with ViTs outperforming CNNs by an average of 14.56% points. These results suggest that occlusion resilience is not uniform across architectural variants but depends critically on attention-based design. Consequently, for real time deployable automatic weed detection systems, hybrid architectures that balance ViT global context with CNN computational efficiency represent a critical future direction. Such approaches can support precise herbicide application, reduce chemical inputs, and enable more sustainable crop protection through reliable AI-driven automation.
The purpose of this review is to describe the intersection between pediatric hypertension and advancing stages of cardiovascular, kidney metabolic syndrome in children and adolescents. Cardiovascular-kidney-metabolic syndrome is highly prevalent in the pediatric population. The onset of CKM in childhood is influenced by the presence of antenatal risk factors such as maternal hypertensive disorders of pregnancy. Advancing stages of CKM in children and adolescents are strongly influenced by food insecurity and social determinants of health that impact the risk for childhood obesity. Activation of the renin-angiotensin-aldosterone system is a key mediator in the relationship between antenatal risk, early life course exposure and hypertension in children and adolescents. Effective strategies for slowing the rate of advancement of CKM staging in children and adolescents require attention to early course factors that influence the development of hypertension and obesity. Likewise, management strategies and therapeutic interventions that address these factors are critical to mitigating CKM stage advancement. Although hypertension is a component of the CKM framework, the presence of hypertension in children and adolescents drives higher CKM staging. Together, hypertension and higher CKM staging are associated with increased atherosclerotic cardiovascular disease risk. Social factors, including access to healthy foods and attention to early life course nutrition are critical strategies to improving CKM and hypertension related outcomes in children and adolescents.
Accurate placement of the endotracheal tube (ETT) is critical for ensuring optimal care for patients requiring mechanical ventilation and preventing potential complications. ETT positioning can be assessed using several methods, with chest X-ray (CXR) being the most precise. Radiologists evaluate whether the ETT requires adjustment by measuring the distance between the distal tip of the ETT and the tracheal carina. This study presents the development of a machine learning model to detect and measure ETT position on adult CXRs and evaluates its performance. Six physicians annotated ETT and trachea locations on a dataset of 3856 CXRs. The U-Net-based model was then trained to generate trachea and ETT segmentations. After post-processing steps, an estimate of the distance between the distal tip of the ETT and the tracheal carina was found. It was demonstrated that the trained model is capable of estimating the position of the ETT and calculating the distance from the tube tip to the tracheal carina. The Dice index for the segmentations on the external validation subset for the trachea and ETT was 89.2% ± 9.0% and 87.8% ± 16.9%, respectively. The estimated absolute error on the external validation subset was 4.72 mm. This model represents a promising tool to support clinicians, particularly in Intensive Care Units, where correct intubation and effective ventilation are critical. It may also be integrated into clinical workflows to facilitate patient management and enhance patient safety.
As urban rail transit networks become increasingly dense, new tunnels frequently undercross existing operational lines. The cyclic loads from existing double-track trains pose a threat to the structural safety of the underlying sections. This paper proposes a computationally efficient analytical model for the 'double-track train-soil layer-underpass tunnel section' system. In this model, the double-track train is represented as a moving two-degree-of-freedom (2-DOF) sprung mass system, the soil is modeled as a spring-damper system, and the underpass tunnel roof structure is treated as an Euler-Bernoulli simply supported beam. The system response is solved using the modal superposition method. Key parameters are calibrated via displacement back analysis, and the model's predictive capability is validated against FLAC3D simulations and independent field measurement data. A systematic parametric study investigates the influence of train speed, tunnel beam length, overburden thickness, equivalent stiffness, and soil mechanical parameters. The analysis reveals the underlying mechanisms of system resonance and critical design parameters. For the specific case study, resonance peaks were observed at speeds around 48 km/h and 72 km/h, a dual-peak resonance phenomenon emerged at beam lengths of approximately 25 m and 45 m, and a vibration amplification effect was identified at a soil cover thickness near 5 m. These findings highlight the resonance mechanisms that should be avoided in design, while the specific critical parameter values are case-dependent and should be re-calibrated for other projects. Increasing the equivalent beam stiffness can effectively suppress the vibration response, while grouting reinforcement modulated the system's dynamic response. This study provides a theoretical framework and an efficient preliminary assessment tool for understanding vibration mechanisms and aiding early-stage design in similar projects.
Drought perturbs water potential in the plants, causing oxidants accumulation and impairing cellular functions. The mineral nutrients are critical for adjusting water potential and modulating antioxidant activity and photosynthesis. This work investigated the impact of sodium nitroprusside (SNP) and chitosan (CS) on six key nutrients (Na, K, P, Ca, Mg, Fe) in leaves of spinach under polyethylene glycol (PEG)-induced drought. The 3-leaved seedlings were irrigated with PEG (5%, 10%, and 15%) and one-day later treated by foliar spray of SNP (25 and 50 µM) and CS (15 and 30 mg/L). The physiological responses were studied by measuring the concentrations of hydrogen peroxide, malondialdehyde, chlorophylls, carotenoids, phenols, flavonoids, anthocyanins, and nutrients using UV/Vis spectrophotometry and inductively coupled plasma optical emission spectrometry. Increasing drought intensity enhanced hydrogen peroxide and malondialdehyde contents. Drought stress increased Na, K, and Mg and decreased Ca and P. Iron remained constant due to its dual function in catalyzing oxidants and in activating antioxidant enzymes and photosynthesis. The SNP and CS applications enhanced photosynthesis and alleviated oxidative stress by enhanced production of phenolics and carotenoids. The elicitors caused higher Ca, P and Fe, and lower Na, K and Mg than those of non-elicited controls. Co-application of both elicitors caused the highest Fe, accompanied by the highest chlorophylls. The intricate interplay between six nutrients were critical to minimize oxidative damage and to improve photosynthetic performance. Overall, the Fe, Mg and Ca interplay were important for photosynthetic performance and antioxidant activity. Moreover, the Na, K and P interplay is essential for osmotic adjustment.
Glucose-regulated protein 78 (GRP78), a core molecular chaperone governing the endoplasmic reticulum (ER) stress response, exerts dual regulatory effects during the pathogenesis of viral pneumonia. Beyond serving as a critical cofactor that promotes viral invasion and replication, GRP78 functions as an indispensable protective chaperone that preserves pulmonary cellular homeostasis and attenuates lung injury. This review characterizes two distinct subcellular localizations of GRP78 in viral pneumonia, namely ER-resident GRP78 and cell surface GRP78 (csGRP78), and systematically summarizes its dual regulatory mechanisms. Specifically, csGRP78 mediates viral adhesion and internalization, whereas ER-GRP78 promotes viral replication and aggravates pulmonary inflammation by modulating ER stress and the unfolded protein response. Meanwhile, GRP78 alleviates pulmonary tissue damage via suppressing lung cell apoptosis and restraining excessive ERS activation. Moreover, this review provides a comprehensive overview of advances in GRP78-targeted therapeutic strategies. The covered therapeutic modalities include small-molecule inhibitors, biological macromolecular drugs, indirect regulatory compounds, and natural products. This review also elaborates their specific molecular targets, core mechanisms, and preclinical findings. Additionally, the current research trends, existing limitations, and future perspectives of GRP78-related investigations are critically discussed. This review aims to clarify the central regulatory role of GRP78 in viral pneumonia, providing theoretical basis and innovative research directions for the precision targeted therapy of viral pneumonia.
Global climate crisis and waste disposal costs drive the need for circular industrial models. This study investigates whether industrial symbiosis through co-disposal of papermaking waste and blast furnace slag can convert these materials from waste to resources. Using a system expansion Life Cycle Assessment framework, we assessed alkali-activated mortars based on global warming potential, water footprint, and toxic impacts. Results indicate that high-volume waste substitution significantly improves the material's environmental profile, achieving a net-negative Global Warming Potential of - 7.9 kg CO2 eq/m³ and a 129% net environmental benefit for human health damage compared to the baseline. These results occur because the avoidance of landfill-related greenhouse gas emissions and primary material production outweigh the impacts of chemical activation. This study outlines a structured approach to decarbonizing construction materials. It shows how technological innovation can strengthen competitiveness within circular economic systems. This work verifies the technical feasibility of regenerative material strategies and identifies activator optimization as a critical factor for advancing next-generation sustainable materials, thereby offering practical guidance to help industrial sectors meet global sustainability requirements.
Glioblastoma (GBM) is the most common and aggressive primary malignant brain tumor in adults, characterized by rapid progression and exceptionally poor prognosis. Identifying novel molecular drivers and therapeutic targets is urgently needed. This study reports a previously unrecognized MET-YANK2 signaling axis that drives glioma progression. Analysis of glioma patient samples reveals that high co‑expression of MET and YANK2 is positively correlated and significantly associated with poor survival outcomes. Mechanistically, MET directly phosphorylates YANK2 at tyrosine 282 (Y282), a conserved residue critical for maintaining YANK2 protein stability. This phosphorylation event prevents SUMOylation mediated proteasomal degradation of YANK2, thereby enhancing its oncogenic function. Functional assays demonstrate that YANK2 phosphorylation promotes GBM cell proliferation and tumor growth both in vitro and in vivo. Conversely, loss of this phosphorylation or enhanced SUMOylation at lysine residues K8 and K148 markedly suppresses YANK2 oncogenic activity. Through structure based screening, rutin, a natural flavonoid compound, is identified as a potent direct binder of YANK2. Rutin treatment effectively inhibits YANK2 kinase activity, reduces downstream p70S6K phosphorylation, and selectively suppresses proliferation of YANK2 high GBM cells. Importantly, rutin exhibits synergistic effects with temozolomide (TMZ), significantly inhibiting tumor growth and prolonging survival in YANK2 overexpressing orthotopic glioma models. Collectively, these findings establish YANK2 as a novel prognostic biomarker and a promising therapeutic target, and highlight rutin as a potential chemosensitizer for biomarker driven combination therapy in glioma.
Cloud detection algorithms in remote sensing imagery exploit spectral and spatial characteristics, either independently or synergistically, to facilitate the discrimination between cloud and underlying surfaces. Individual cloud detection methods manifest unique operational advantages but suffer from inherent limitations, such as bright surface misclassification and thin cloud omission, leading to unstable performance across heterogeneous landscapes. A critical research gap exists in how to systematically integrate complementary strengths of multiple deep learning models while mitigating their individual weaknesses. To address this gap, this paper proposes a novel ensemble framework based on multiple deep learning models, using an F1-score-weighted fusion strategy. The framework first evaluates three representative deep learning-based detection algorithms (CD-SLCNN, SRMF-CD, CNN-TransNet) on Landsat-8 imagery, then derives algorithm-specific weights from their F1-scores on a validation set to produce a weighted probabilistic fusion. Quantitative comparisons on a hold-out test set show that the proposed method outperforms standard ensemble baselines: it improves F1-score by 4.7% points over majority voting and by 1.9% points over bayesian model averaging, while also reducing misclassification and omission errors across heterogeneous landscapes. The proposed F1-weighted ensemble thus provides a robust and accurate solution for large-scale cloud detection.
The road safety and traffic efficiency is enhanced by providing communication between Vehicles in Vehicle Ad hoc networks (VANETs). Position falsification attacks represent a significant threat in VANETs, where the accuracy and integrity of location-based information are critical for safe and efficient transportation. The misbehavior detection frameworks can effectively identify position falsification attacks. The frameworks employ machine learning classifiers trained on features derived from inter-vehicular communication data. Optimization can enhance a stacked ensemble model for misbehaviour detection by hyperparameter tuning of classifiers. The proposed methodology involves constructing a stacked ensemble model composed of five diverse base classifiers, such as K Nearest Neighbours Classifier (KNN), Ada Boost Classifier (ADA), Extra Trees Classifier (ETC), Random Forest (RF), and Extreme Gradient Boosting Classifier (XGBC). Meta Classifier is used to combine predictions from the individual classifiers with logistic regression. To achieve the highest accuracy, Artificial Bee Colony (ABC) optimization is used to enhance the hyperparameters for the base classifiers. The optimized stacked ensemble model shows that our model provides the best results when compared with the existing methods.
The gut microbiota acts as a critical driver influencing the pathogenesis, therapeutic response, and clinical outcomes across various cancer types. This study aimed to investigate the prognostic value of human gut microbes and microbial metabolites related genes (HGMMMRGs) in head and neck squamous cell carcinoma (HNSCC). We constructed a prognostic risk model comprising 19 core HGMMMRGs using LASSO penalized regression and a multivariate Cox proportional hazards model. The predictive performance of the model was evaluated through Kaplan-Meier analysis, receiver operating characteristic (ROC) curves, nomograms, and concordance index. In addition, functional enrichment analysis was performed on the differentially expressed risk genes. Furthermore, the relationship between the immune microenvironment of HNSCC and the risk diagnostic model was examined. Western blot analysis was used to assess the expression levels of IL10 in both HNSCC tissues and adjacent normal tissues. Finally, the correlation between IL10 and the gut microbiota was explored. This study developed a risk score model integrating 19 HGMMMRG genes, which can serve as a tool to guide prognosis and immune microenvironment assessment in HNSCC patients. Survival analysis showed that patients in the high-risk group had significantly worse outcomes (P < 0.05). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed significant enrichment of differentially expressed genes (DRLs) and immune-related pathways. Western blot analysis further confirmed that IL10 was highly expressed in HNSCC, and the abundance of Faecalibacterium prausnitzii and Enterococcus durans colonies was correlated with IL10 expression. We developed a prognostic model for HGMMMRGs that can be effectively used to predict OS in patients with HNSCC. Second, Faecalibacterium prausnitzii and Enterococcus durans can influence the prognosis of patients with HNSCC by mediating the expression IL10 and thereby affecting the prognosis of HNSCC patients. Thus, human gut microbes and microbial metabolite-related genes may be another promising strategy for the treatment of patients with HNSCC.
Waning immunity and reinfection are critical features of many infectious diseases, but epidemiological models often fail to capture the interaction between an individual's immunity history and their current infection status, or do so only simplistically. We develop a dual-age structured model tracking immunity age (time since last recovery) and infection age (time since infection) to analyze epidemic dynamics under waning immunity and reinfection. The model is formulated as a system of age-structured partial differential equations describing susceptible and infected populations stratified by both age variables. The contact rate, mortality and recovery rates, susceptibility, and pathogen load are all treated as parameter functions depending on both immunity and infection age. We derive basic reproduction numbers and numerically solve the system using a second-order Runge-Kutta scheme along characteristic lines. We further extend the model to treat vaccination interventions, specifically booster vaccination strategies targeting individuals by immunity age - interventions that cannot be formulated in standard models. Numerical results reveal that higher contact rates produce larger oscillation amplitudes with longer inter-epidemic periods. However, long-term oscillation amplitude and cumulative infections depend non-monotonically on the initial infected population size, indicating that the relationship between initial infection levels and long-term epidemic outcomes is not straightforward. Vaccination efficiency depends critically on the pathogen load profile, with more concentrated distributions requiring higher vaccination rates for elimination. Most efficient strategies target intermediate immunity ages rather than only fully waned individuals.
The management of postoperative pain is a critical ethical concern and a challenge in laboratory animal research, particularly for mice. Surgical procedures are routinely conducted in mice, but the use of analgesic drugs is underreported and the assessment of their efficacy is limited. This systematic review assesses the efficacy of analgesic drugs for postoperative pain in mice, addressing the influence of various factors, including sex, surgical invasiveness, pain modalities and analgesic classes. A systematic literature search resulted in 48 eligible studies included in the qualitative analysis and 43 in the quantitative analysis. The overall pooled standardized mean difference (SMD) for analgesic drugs was 0.46 (95% confidence interval 0.31 to 0.60), indicating a positive pain-reducing effect. Subgroup analysis revealed that analgesic treatment was significantly more effective in male (SMD 0.84; 0.60 to 1.08) than in female mice, in mild (SMD 0.57; 0.38 to 0.75) than in severe surgical procedures and in reducing evoked pain (SMD 1.12; 0.83 to 1.41) than in reducing spontaneous pain. In addition, almost all analgesic drug classes tested, including opioids, nonsteroidal anti-inflammatory drugs, acetaminophen and local anesthetics were effective in reducing evoked pain but not spontaneous pain (SMD 0.12; -0.03 to 0.27). However, most studies present limitations that could produce a high risk of bias. Taken together, our results indicate that, although analgesic drugs can reduce postoperative pain in mice, their efficacy is reduced in females, severely invasive surgeries and spontaneous pain. Thus, high-quality studies are still needed to answer ethical concerns and to guarantee full analgesia in laboratory mice submitted to surgical procedures.
The present work explores corrosion response of Selective Laser Melting (SLM) prepared NiTi shape memory alloys with an aim to study processing-induced defects and surface-specific microstructural features inherent to SLM, influence on alloy corrosion response. The study systematically investigated corrosion behavior within the defect-minimized region of established SLM printability maps by comparing representative low- and high-power/scan speed conditions (P-80: 80 W, 330 mm s⁻¹; P-200: 200 W, 1080 mm s⁻¹) and by varying hatch spacing (64 μm and 80 μm) under constant laser power and scan speed. Corrosion behavior analysis was carried out on four distinct surfaces following a 72-h immersion in Hank's Balanced Salt Solution (HBSS): the internal and external surface of P-80 and P-200 specimens sectioned parallel to build direction (BD), and top and bottom surface of h-64 and h-80 specimens sectioned perpendicular to BD. Unlike prior studies that compared SLM NiTi against wrought material or varied parameters broadly, this work systematically isolates surface-specific defect populations within the defect-minimized region of an established printability map at matched volumetric energy density. The parallel to BD, P-80 specimens, showed the highest porosity of 5.4% and a corrosion current density of 140 nA/cm², with localized pits reaching up to 110 μm in depth, initiating primarily at porosity defects thereby disrupting the passive film formation. In contrast, perpendicular to BD specimens, particularly h-80 with larger hatch spacings, showed enhanced corrosion resistance on a single-specimen basis, attributed to a more effective passive film formation. Surfaces with higher defect density developed effective thicker but defect-rich passive films with poor protective performance, whereas Ti-enriched, low-defect surfaces formed effective thinner yet compact and highly resistive films. These results indicate that within the defect-minimized region of the printability map, surface-specific defect populations and surface chemistry are the dominant factors governing corrosion response, rather than nominal process parameters. The findings imply that build-orientation selection and surface-specific post-processing-beyond bulk-density optimization-are required for corrosion-critical SLM NiTi components. Direct passive-film characterization, replicate testing, and Ni-ion-release quantification are identified as essential follow-on work.
Adipocyte death is a key event in the development of white adipose tissue (WAT) inflammation, a major driver of obesity-associated metabolic dysfunction. Receptor-interacting protein kinase 3 (RIPK3) mediates necroptosis, a recently discovered mode of regulated necrosis. Necroptosis has been implicated in several inflammatory pathologies; however, the role of adipocyte necroptosis in obesity remains unclear. In the present study, we sought to investigate the role of adipocyte RIPK3 in obesity and glucose homeostasis. We demonstrated that necroptotic signalling was upregulated in WAT of mice with diet-induced obesity and was associated with body-mass index in human WAT. We also demonstrated that caspase-8, a central regulator of apoptosis, suppresses adipocyte necroptosis both in vitro and in vivo. Adipocyte-specific deletion of caspase-8 in mice reduced adiposity compared to control mice. This difference was not observed with concomitant global deletion of RIPK3. Furthermore, adipocyte-specific deletion of the RIPK3 receptor-interacting protein homotypic interaction motif (RHIM), which is required for necroptotic induction, did not influence weight gain, adiposity, or glucose homeostasis in mice with diet-induced obesity. Caspase-8 knockdown by siRNA or pharmacological inhibition in 3T3-L1 adipocytes suppressed adipogenesis, which may be independent of adipocyte Ripk3. Collectively, our findings suggest that adipocyte RIPK3 RHIM does not play a critical role in obesity and glucose homeostasis. Alternatively, we provide further evidence that caspase-8 plays an essential role in adipocyte differentiation, offering insight into the molecular mechanisms underlying obesity and metabolic dysfunction.
Reliable, painless glucose surveillance is critical during the early neonatal fall in plasma glucose levels. However, existing continuous glucose monitors are invasive and expensive. We evaluated a non-invasive method for estimating blood glucose levels from the phase delay (Δθ) between oxy- and deoxyhemoglobin waveforms, expressed as a metabolic index (MI). Thirty-eight term neonates were enrolled on postnatal day 2, and 30 recordings satisfied the predefined signal quality criteria. Neonatal pulse oximetry probes captured 5-min photoplethysmography traces, from which stable 15-60-s epochs were extracted. The α-corrected MI for each infant was correlated with plasma glucose measured on an ABL90 FLEX analyzer. Glycemic slopes were compared with published adult data using ANCOVA. The α-corrected MI showed a significant positive correlation with plasma glucose (R2 = 0.51, r = 0.71; p < 0.01). Linear regression for neonates was MI = 0.17 × glucose - 6.78. Both slope and intercept differed from adult values (p < 0.05), indicating age-dependent modulation of the Δθ-glucose relationship. Phase-delay analysis using standard pulse oximetry provides a promising approach for continuous glucose estimation in term neonates. Age-specific calibration is required before clinical deployment; however, the technique's low cost and noninvasiveness potentiate universal bedside hypoglycemia surveillance. Key message: Non-invasive glucose monitoring using the phase delay between oxy- and deoxyhemoglobin waveforms obtained from a pulse oximetry probe shows a significant correlation with blood glucose levels in term neonates. Literature contribution: This study demonstrates that the metabolic index derived from hemoglobin phase delays differs between neonates and adults, suggesting the need for age-specific calibration. This low-cost technique may enable continuous bedside glucose surveillance in neonates without repeated blood sampling.
Lodging is a major constraint in wheat production, often resulting in substantial yield losses. Resistance to lodging is influenced by various morphological, biochemical, and anatomical traits of the stem, and the relative contribution of different stem parts, particularly individual internodes, to lodging tolerance remains unclear. In this study, key culm-related morphological internode length (IL), internode weight (IW), stem diameter (SD), culm wall thickness (CWT), pith diameter (PD), the stem diameter to culm wall thickness ratio (SD/CWT) and the internode length to internode weight ratio (IL/IW), biochemical (cellulose), and anatomical traits were evaluated across the first three internodes in diverse wheat genotypes. The results revealed that the second internode played the most critical role in lodging tolerance. Lodging-resistant genotypes presented higher PD, CWT, IW, and cellulose content in the second internode, whereas susceptible genotypes presented increased IL and IL/IW ratios. Anatomical analyses revealed that resistant genotypes possessed more vascular bundles, thicker sclerenchyma, well-developed parenchyma, and enhanced lignin deposition in the second internode, collectively contributing to superior mechanical stability. Furthermore, single-marker analysis using SSR markers revealed 12 significant loci associated with 16 culm strength traits, with Gwm337 and Wmc273 explaining the greatest percentage of the phenotypic variance (24.40% and 23.01%, respectively). These findings underscore the pivotal role of the second internode in lodging tolerance and provide valuable molecular markers to support marker-assisted breeding for enhanced culm strength in wheat.
Urban agglomerations serve as a critical vehicle for advancing high-quality regional urbanization, with the Lanzhou-Xining (Lanxi) urban agglomeration representing an advanced stage of urbanization in western China. As a nationally significant urban agglomeration in the western region, the Lanxi urban agglomeration also functions as a vital ecological barrier. Studying the supply and demand dynamics of ecotourism in this area is therefore important for the development of ecotourism and for promoting sustainable regional tourism practices. Based on this premise, this study focuses on the supply and demand conditions of new urbanization and ecotourism across 19 cities (districts and counties) within the Lanxi urban agglomeration. An evaluation index system is developed to assess the development of regional new-type urbanization and ecotourism supply and demand. The study employs methods including the coupling coordination model, the obstacle degree model, and the geographical detector to examine the comprehensive development levels of the regional systems, their spatial and temporal distribution characteristics, and the associated obstacle factors. The results indicate the following: (1) During the study period, the average comprehensive development level of the three major systems within the Lanxi urban agglomeration exhibited a steady upward trend overall. (2) Over the study period, the degree of coupling coordination among the three systems shifted from moderate imbalance (with coordination values between 0.2 and 0.3) to mild imbalance (with coordination values between 0.3 and 0.4). Significant regional differences and spatial clustering were observed in the coupling coordination levels. The overall spatial distribution of new-type urbanization and ecotourism supply and demand in the Lanxi urban agglomeration generally presented a pattern characterized by higher values in the central area (Lanzhou and Xining) and lower values in the peripheral areas. (3) The four dimensions represented by eight influencing factors-namely tourism scale, tourism benefits, tourism resources, and infrastructure-are identified as key determinants influencing the coupled and coordinated development of regional new urbanization and ecotourism supply and demand.
Organic solvents are routinely used to dissolve poorly water-soluble chemicals in zebrafish-based assays. However, their intrinsic biological activity may confound behavioural endpoints and compromise data interpretation. This study systematically evaluated the effects of seven commonly used laboratory solvents, dimethyl sulfoxide (DMSO), ethanol (EtOH), methanol (MeOH), acetone (Ace), acetonitrile (ACN), isopropanol (IPA), and ethyl acetate (EtOAc), at four concentrations (1, 0.5, 0.1, 0.05%; v/v), on locomotor behaviour of zebrafish Danio rerio larvae at 120 h post fertilization. Larval activity was quantified using automated video tracking under alternating light-dark conditions, assessing distance moved, velocity, acceleration, mobility states, and turning behaviour. Behavioural responses were strongly solvent- and concentration-dependent. EtOH, MeOH, Ace, and IPA induced hyperactivity at ≥ 0.5%, while DMSO showed biphasic effects, stimulating activity at 0.5% but suppressing it at 1%. ACN demonstrated a significant inhibitory response even at 0.5%, while EtOAc was tolerated only at ≤ 0.1%. Principal component analysis (PCA) and hierarchical clustering on principal components (HCPC) further revealed coherent behavioural signatures shaped not only by solvent identity and concentration but also strongly by light-dark transitions, underscoring the critical importance of consistent illumination conditions in zebrafish behavioural assays. Overall, ≤ 0.1% of Ace and EtOAc, and ≤ 0.05% of DMSO, EtOH, MeOH, ACN, and IPA did not significantly alter locomotion, suggesting their suitability for zebrafish behavioural assays. These findings establish reference points for solvent selection and concentration thresholds in zebrafish behavioural assays under the specific experimental conditions tested, thereby supporting reproducibility and reliability in scientific research.
Drebrin modulates F-actin networks and links them to other intracellular components, regulating crucial processes including neuritogenesis, synaptic plasticity, virus internalisation and cancer invasion. Using single-particle cryo-EM we characterise drebrin's interaction with F-actin through two separate conserved actin binding domains (ABD1 and ABD2), revealing structural bases for its F-actin-modulating properties. We describe a multimodal interaction where drebrin's ABD1 can adopt two conformations and a long flexible loop connecting to ABD2 allows the two ABDs to occupy multiple relative positions along F-actin. The flexible loop connecting the two ABDs also confers some propensity to loosely bundle F-actin. Drebrin's ABDs bind across multiple actin protomers and their subdomains and modify the longitudinal inter-protomer interface, explaining its F-actin stabilising properties. Furthermore, we show drebrin's binding site on F-actin is shared with other critical actin-binding and regulatory proteins, explaining their competitive displacement.