Search Results (273)

The venom of Bothrops jararaca (BjV) induces intense and prolonged pain, which is not alleviated by antivenom, along with hemorrhage and inflammation. In this study, we investigated the effects of the specialized pro-resolving lipid mediator (SPM) maresin 2 (MaR2) in a murine model of BjV-evoked pain and inflammation. Mice received a single intraperitoneal (i.p.) injection of MaR2 30 min before the intraplantar BjV injection. MaR2 treatment significantly attenuated mechanical (electronic aesthesiometer) and thermal (hot plate) hyperalgesia in a dose-dependent manner. Additionally, MaR2 restored the balance for the hind-paw static weight distribution. When BjV (0.01, 0.1, and 1 μg) stimulus was administered intraperitoneally, pre-treatment with MaR2 (0.3, 1, or 3 ng) ameliorated mechanical and thermal hyperalgesia in a dose-dependent manner. Moreover, MaR2 (3 ng) effectively reduced the levels of myeloperoxidase activity and cytokines (TNF-α, IL-1β, and IL-6) and superoxide anion (O₂^•−) production induced by intraplantar injection of BjV while enhancing total antioxidant levels (ABTS scavenging). For the peritonitis model induced by BjV, MaR2 pretreatment decreased leukocyte recruitment, hemorrhage, nitric oxide (NO), and O₂^•− generation and gp91phox and inducible nitric oxide synthase (iNOS) mRNA expression. In conclusion, this study presents the first evidence that MaR2 effectively mitigated BjV-induced pain, hemorrhage, and inflammation. Full article

As a type of distinctive pit on Mars, skylights are entrances to subsurface lava caves. They are very important for studying volcanic activity and potential preserved water ice, and are also considered as potential sites for human extraterrestrial bases in the future. Most skylights are manually identified, which has low efficiency and is highly subjective. Although deep learning methods have recently been used to identify skylights, they face challenges of few effective samples and low identification accuracy. In this article, 151 positive samples and 920 negative samples based on the MRO-HiRISE image data was used to create an initial skylight dataset, which contained few positive samples. To augment the initial dataset, StyleGAN2-ADA was selected to synthesize some positive samples and generated an augmented dataset with 896 samples. On the basis of the augmented skylight dataset, we proposed YOLOv9-Skylight for skylight identification by incorporating Inner-EIoU loss and DySample to enhance localization accuracy and feature extracting ability. Compared with YOLOv9, the P, R, and the F1 of YOLOv9-Skylight were improved by about 9.1%, 2.8%, and 5.6%, respectively. Compared with other mainstream models such as YOLOv5, YOLOv10, Faster R-CNN, Mask R-CNN, and DETR, YOLOv9-Skylight achieved the highest accuracy (F1 = 92.5%), which shows a strong performance in skylight identification. Full article

The Zhurong rover of the Tianwen-1 mission has detected sulfates in its landing area. The analysis of these sulfates provides scientific evidence for exploring past hydration conditions and atmospheric evolution on Mars. As a non-contact technique with long-range detection capability, Laser-Induced Breakdown Spectroscopy (LIBS) is widely used for elemental identification on Mars. However, quantitative analysis of anionic elements using LIBS remains challenging due to the weak characteristic spectral lines of evaporite salt elements, such as sulfur, in LIBS spectra, which provide limited quantitative information. This study proposes a quantitative analysis method for sulfur in sulfate-containing Martian analogs by leveraging spectral line correlations, full-spectrum information, and prior knowledge, aiming to address the challenges of sulfur identification and quantification in Martian exploration. To enhance the accuracy of sulfur quantification, two analytical models for high and low sulfur concentrations were developed. Samples were classified using infrared spectroscopy based on sulfur content levels. Subsequently, multimodal deep learning models were developed for quantitative analysis by integrating LIBS and infrared spectra, based on varying concentrations. Compared to traditional unimodal models, the multimodal method simultaneously utilizes elemental chemical information from LIBS spectra and molecular structural and vibrational characteristics from infrared spectroscopy. Considering that sulfur exhibits distinct absorption bands in infrared spectra but demonstrates weak characteristic lines in LIBS spectra due to its low ionization energy, the combination of both spectral techniques enables the model to capture complementary sample features, thereby effectively improving prediction accuracy and robustness. To validate the advantages of the multimodal approach, comparative analyses were conducted against unimodal methods. Furthermore, to optimize model performance, different feature selection algorithms were evaluated. Ultimately, an XGBoost-based feature selection method incorporating prior knowledge was employed to identify optimal LIBS spectral features, and the selected feature subsets were utilized in multimodal modeling to enhance stability. Experimental results demonstrate that, compared to the BPNN, SVR, and Inception unimodal methods, the proposed multimodal approach achieves at least a 92.36% reduction in RMSE and a 46.3% improvement in R². Full article

Background and Objectives: This study aimed to investigate the relationship between Maresin-1 (MaR1), Chitinase-3-like protein 1 (CHI3L1), and inflammatory as well as hematological markers in patients with type 2 diabetes mellitus (T2DM) and diabetic nephropathy (DN). Materials and Methods: This cross-sectional study included 90 participants divided into three groups: healthy controls (n = 30), patients with T2DM (n = 30), and patients with diabetic nephropathy (n = 30). The serum levels of MaR1 and CHI3L1 were measured using ELISA. Biochemical and hematological parameters were also assessed. Statistical comparisons were conducted using non-parametric tests, and correlations were analyzed via Spearman correlation. Results: Serum MaR1 levels were significantly higher in DN patients compared to both T2DM patients and controls (p < 0.01), while CHI3L1 levels were significantly lower in the DN group compared to controls (p = 0.007). MaR1 showed a positive correlation with CRP, BUN, and creatinine, and a negative correlation with GFR. CHI3L1 levels were positively correlated with GFR and negatively with BUN. Inflammatory markers such as CRP were elevated in the diabetic groups, while no significant differences were found in NLR values. Conclusions: Elevated MaR1 levels in DN patients and their correlation with renal dysfunction markers suggest that MaR1 may serve as a potential prognostic biomarker in diabetic nephropathy. The unexpected decrease in CHI3L1 levels in DN patients indicates the need for further research to clarify their role. These findings indicated that MaR1 and CHI3L1 should be further investigated in future studies as indicators for the early detection and monitoring of diabetic complications. Full article

With the rapid expansion of railway networks and increasing operational complexity, intelligent rail damage detection has become crucial for ensuring safety and improving maintenance efficiency. Traditional physical inspection methods (e.g., ultrasonic testing, magnetic flux leakage) are limited in terms of efficiency and environmental adaptability. This study proposes a machine vision-based approach leveraging deep learning to identify four primary types of rail damages: corrugations, spalls, cracks, and scratches. A self-developed acquisition device collected 298 field images from the Chongqing Metro system, which were expanded into 1556 samples through data augmentation techniques (including rotation, translation, shearing, and mirroring). This study systematically evaluated three object detection models—YOLOv8, SSD, and Faster R-CNN—in terms of detection accuracy (mAP), missed detection rate (mAR), and training efficiency. The results indicate that YOLOv8 outperformed the other models, achieving an mAP of 0.79, an mAR of 0.69, and a shortest training time of 0.28 h. To further enhance performance, this study integrated the Multi-Head Self-Attention (MHSA) module into YOLO, creating MHSA-YOLOv8. The optimized model achieved a significant improvement in mAP by 10% (to 0.89), increased mAR by 20%, and reduced training time by 50% (to 0.14 h). These findings demonstrate the effectiveness of MHSA-YOLO for accurate and efficient rail damage detection in complex environments, offering a robust solution for intelligent railway maintenance. Full article

Background: Lung ischemia reperfusion injury (LIRI) is a severe complication after lung transplantation (LT). Ferroptosis contributes to the pathogenesis of LIRI. Maresin1 (MaR1) is an endogenous pro-resolving lipid mediator that exerts protective effects against multiorgan diseases. However, the role and mechanism of MaR1 in the ferroptosis of LIRI after LT need to be further investigated. Methods: A mouse LT model and a pulmonary vascular endothelial cell line after hypoxia reoxygenation (H/R) culture were established in our study. Histological morphology and inflammatory cytokine levels predicted the severity of LIRI. Cell viability and cell injury were determined by CCK-8 and LDH assays. Ferroptosis biomarkers, including Fe²⁺, MDA, 4-HNE, and GSH, were assessed by relevant assay kits. Transferrin receptor (TFRC) and Acyl-CoA Synthetase Long Chain Family Member 4 (ACSL4) protein levels were examined by western blotting. In vitro, lipid peroxide levels were detected by DCFH-DA staining and flow cytometry analysis. The ultrastructure of mitochondria was imaged using transmission electron microscopy. Furthermore, the potential mechanism by which MaR1 regulates ferroptosis was explored and verified with signaling pathway inhibitors using Western blotting. Results: MaR1 protected mice from LIRI after LTx, which was reversed by the ferroptosis agonist Sorafenib in vivo. MaR1 administration decreased Fe²⁺, MDA, 4-HNE, TFRC, and ACSL4 contents, increased GSH levels, and ameliorated mitochondrial ultrastructural injury after LTx. In vitro, Sorafenib resulted in lower cell viability and worsened cell injury and enhanced the hallmarks of ferroptosis after H/R culture, which was rescued by MaR1 treatment. Mechanistically, the protein kinase A and YAP inhibitors partly blocked the effects of MaR1 on ferroptosis inhibition and LIRI protection. Conclusions: This study revealed that MaR1 alleviates LIRI and represses ischemia reperfusion-induced ferroptosis via the PKA-Hippo-YAP signaling pathway, which may offer a promising theoretical basis for the clinical application of organ protection after LTx. Full article

Accurate real-time icing grid fields are critical for preventing ice-related disasters during winter and protecting property. These fields are essential for both mapping ice distribution and predicting icing using physical models combined with numerical weather prediction systems. However, developing precise real-time icing grids is challenging due to the uneven distribution of monitoring stations, data confidentiality restrictions, and the limitations of existing interpolation methods. In this study, we propose a new approach for constructing real-time icing grid fields using 1339 online terminal monitoring datasets provided by the China Southern Power Grid Research Institute Co., Ltd. (CSPGRI) during the winter of 2023. Our method integrates static geographic information, dynamic meteorological factors, and ice_kriging values derived from parameter-optimized Empirical Bayesian Kriging Interpolation (EBKI) to create a spatiotemporally matched, multi-source fused icing thickness grid dataset. We applied five machine learning algorithms—Random Forest, XGBoost, LightGBM, Stacking, and Convolutional Neural Network Transformers (CNNT)—and evaluated their performance using six metrics: R, RMSE, CSI, MAR, FAR, and fbias, on both validation and testing sets. The stacking model performed best, achieving an R-value of 0.634 (0.893), RMSE of 3.424 mm (2.834 mm), CSI of 0.514 (0.774), MAR of 0.309 (0.091), FAR of 0.332 (0.161), and fbias of 1.034 (1.084), respectively, when comparing predicted icing values with actual measurements on pylons. Additionally, we employed the SHAP model to provide a physical interpretation of the stacking model, confirming the independence of selected features. Meteorological factors such as relative humidity (RH), 10 m wind speed (WS₁₀), 2 m temperature (T₂), and precipitation (PRE) demonstrated a range of positive and negative contributions consistent with the observed growth of icing. Thus, our multi-source remote-sensing data-fusion approach, combined with the stacking model, offers a highly accurate and interpretable solution for generating real-time icing grid fields. Full article

This study aimed to investigate the relationship between visual system parameters (visual acuity and refractive error) and postural balance under controlled conditions in elite football players. Visual acuity (monocular and binocular) and refractive errors were assessed in 34 male athletes using retinoscopy and subjective refraction. Postural stability was assessed with the Cyber-Sabots™ platform, recording the center of pressure (CoP) metrics, including sway amplitude, velocity, and distribution area. Visual and postural parameter correlations were assessed using Pearson’s test (p < 0.05). Athletes demonstrated good binocular visual acuity (−0.03 ± 0.09 logMAR) and were predominantly emmetropic. Visual acuity and postural parameters showed significant negative correlations, whereby visual acuity was associated with reduced CoP displacement (r = −0.352) and sway area (r = −0.367), indicating enhanced stability. Hyperopia and oblique astigmatism were moderately correlated with increased sway (r = 0.343) and antero-posterior sway amplitude in the sagittal plane (r = 0.324). Anisometropia showed moderately negative correlations with antero-posterior control (r = −0.421), suggesting a disruptive effect on postural stability. The postural analysis showed adaptations characteristic of football players, including anterior body inclination, increased forefoot loading, and medio-lateral sway. Romberg’s quotients highlighted significant visual input reliance for maintaining postural balance. Visual acuity, refractive errors, and interocular refractive asymmetries significantly influence postural stability in elite football players. These results support incorporating visual function assessment into training and injury prevention in elite sports. Full article

Forest aboveground biomass (AGB) serves as a crucial quantitative indicator that reflects the carbon sequestration capacity of forests, and accurately mapping AGB is pivotal for assessing forest ecosystem stability. However, mapping AGB in subtropical evergreen broadleaf forests in southern China presents challenges due to their complex canopy structure, stand heterogeneity, and spectral signal saturation. The phenological features reflecting seasonal vegetation dynamics are conducive to over-coming these challenges. By analyzing differential spectral reflectance patterns during the non-growing (Jan–Mar, Nov–Dec) versus growing (Apr–Oct) seasons, this study established a phenological feature-based methodology for improving AGB estimation in subtropical evergreen broadleaf forests. Subsequently, four time series vegetation indices (VI), namely NDVI, EVI2, NDPI, and IRECI were employed to extract phenological features (PFs) for mapping forest AGB using a multiple linear regression model (MLR), K-nearest neighbor model (KNN), support vector machine model (SVM), and random forest model (RF). The results demonstrated significant differences in Sentinel-2 spectral reflectance (740–1610 nm bands) between the growing and non-growing seasons. The PFs demonstrated the highest distance correlation coefficient (0.57), significantly outperforming other baseline feature types (0.44). Furthermore, seasonal changes in NDVI and NDPI were found to better reflect AGB accumulation in evergreen broadleaf forests compared to EVI2 and IRECI. Incorporating diverse PFs derived from all four VI significantly enhanced the accuracy of AGB mapping by yielding rRMSE values ranging from 21.01% to 25.06% and R² values ranging from 0.40 to 0.58. The results inferred that PFs can be considered a key factor for alleviating spectral signal saturation problems while effectively improving the accuracy of AGB estimation. Full article

Chromobacterium spp. use a density-dependent cell-to-cell communication mechanism (quorum sensing, QS) to control various traits, including the pigment violacein biosynthesis. Recently, one of the type strains of this genus, previously deposited in the American Type Culture Collection under accession number C. violaceum 31532, was reclassified as C. subtsugae, making the QS data obtained for the first species irrelevant to the second. The goal of this study is to conduct transcriptomic and genomic analyses of the C. subtsugae ATCC 31532 (formerly C. violaceum ATCC 31532) strain to identify density-dependent regulated genes and the mechanisms of their QS control. Whole transcriptome dataset analysis comparing QS-negative mid-log phase and QS-positive early stationary phase samples revealed 35 down-regulated and 261 up-regulated genes, including 44 genes that increased transcription activity the most (log2 (fold change) > 4.0). In addition to the violacein biosynthesis, QS-controlled traits in C. subtsugae ATCC 31532 included the following: (i) cdeAB-oprM efflux pump; (ii) RND efflux transporter; (iii) chuPRSTUV iron acquisition system; (iv) polyamine transport system; (v) carbohydrate (semialdehydes) metabolic pathways; (vi) SAM/SPASM maturase system XYE (predicted); (vii) prophage proteins; and (viii) fucose-binding lectin II. Subsequent screening of the promoter regions of the up-regulated genes and operons in most cases showed the presence of CsuR AHL-receptor/transcriptional regulator binding sites with 56.25–68.75% similarity to the ideal 16-base-pair palindrome 5′-CTGTCCGATAGGACAG-3′ sequence, supporting the concept of QS control in C. subtsugae ATCC 31532 by the csuI-csuR gene pair. Notably, several transcriptional regulators (MarR, TetR/AcrR, HU family DNA-binding protein, helix-turn-helix domain-containing protein) were found to be under QS control. Based on these data, a hierarchical QS regulatory network in C. subtsugae ATCC 31532 was hypothesized that provides direct control of the target genes via a canonical autoinduction mechanism and further dissemination of the effect via the activity of QS-controlled transcriptional regulators. Full article

Genotype by environment (G × E) interaction is a magnitude change in the performance of a genotype when grown in contrasting environments. The sensitivity of a genotype to different environmental conditions is an important determinant of its suitability for cultivation in a specific environment or across multiple environments. In many nations of the world, where the drive to achieve a net-zero CO₂ emission by 2030 has spurred significant investments in clean energy sources such as photovoltaics with a resultant conversion of some agricultural lands to photovoltaic facilities, there is a need to find the right balance between addressing the food and energy crises. Agri-photovoltaics (APV) offer a sustainable solution by allowing crops to grow underneath photovoltaic panels. However, selection efficiency and repeatability of APV experimental results could be marred by the presence of G × E interaction. The study objective was to identify mungbean genotype(s) with a high yield potential and broad adaptability across APV environments. Five mungbean (Vigna radiata L.) genotypes, Tvr18, Tvr28, Tvr65, Tvr79, and Tvr 83, were assessed under six contrasting APV environments, EPV-R, EPV-D, NPV-R, NPV-D, WPV-R, and WPV-D, at the Agri-PV Food and Energy Training Center, University of Nigeria, Nsukka. The experiment was a split-plot design, with the environment as the whole-plot factor while genotype was the sub-plot factor with five replications. The additive main effects and multiplicative interaction (AMMI) and the Finlay and Wilkinson joint regression analysis confirmed significant genotype, environment, and G × E interaction effects for mungbean seed yield. Two genotypes, Tvr28 and Tvr83 expressed broad adaptability to the APV environments with higher yields (2.60 and 2.50 t ha⁻¹), ranking first and second, respectively. In contrast, the Tvr79 genotype displayed the highest sensitivity (2.95) to environmental variation and was unstable across the environments with higher IPCA1 and ASV scores of −1.17 and 1.39, respectively. The EPV-R recorded the highest yield (2.61) with low interaction effect (0.38), whereas the WPV-D environment had the least yield (1.71) and was the most unstable (−0.48). Conclusively, the Tvr28 and Tvr83 genotypes and the EPV-R environment were the ideal genotypes and environment, respectively, and are therefore recommended for use in APV facilities. Full article

Dust storms, as an important extreme weather event on Mars, have significant impacts on the Martian atmosphere and climate and the activities of Martian probes. Therefore, it is necessary to analyze and predict the activity trends of Martian dust storms. This study uses historical data on global Column Dust Optical Depth (CDOD) from the Martian years (MYs) 24–36 (1998–2022) to develop a CDOD prediction method based on deep learning and predicts the spatiotemporal trends of dust storms in the landing areas of Martian rovers at high latitudes, the tropics, and the equatorial region. Firstly, based on a trained Particle Swarm Optimization (PSO) Long Short-Term Memory (LTSM)-CDOD network, the rolling predictions of CDOD average values for several sols in the future are performed. Then, an evaluation method based on the accuracy of the test set gives the maximum predictable number of sols and categorizes the predictions into four accuracy intervals. The effective prediction time of the model is about 100 sols, and the accuracy is higher in the tropics and equatorial region compared to at high latitudes. Notably, the accuracy of the Zhurong landing area in the north subtropical region is the highest, with a coefficient of determination (R²) and relative mean error (RME) of 0.98 and 0.035, respectively. Additionally, a Convolutional LSTM (ConvLSTM) network is used to predict the spatial distribution of CDOD intensity for different latitude landing areas of the future sol. The results are similar to the time predictions. This study shows that the LSTM-based prediction model for the intensity of Martian dust storms is effective. The prediction of Martian dust storm activity is of great significance to understanding changes in the Martian atmospheric environment and can also provide a scientific basis for assessing the impact on Martian rovers’ landing and operations during dust storms. Full article

A 10-month-old pygmy goat was examined at the Royal (Dick) School of Veterinary Studies at the University of Edinburgh in January 2022, having been referred with a suspected diagnosis of a disorder of sexual development (DSD). The animal displayed a predominantly female phenotype (vulva with enlarged clitoris and vagina) but some male external characteristics such as a beard, larger body size, and larger horns. It also typically exhibits male behaviours such as mounting, aggression, and flehmen response. Computed tomography (CT) detected a bicornuated tubular fluid-filled structure connected to bulbous soft tissue masses. Subsequent exploratory laparotomy and reproductive tract removal identified underdeveloped uterine horns connected to ductus deferens and gonads, which were confirmed as testicles by histological examination. No spermatogenesis was detected, and no ovarian tissue was apparent. Blood levels of testosterone showed a marked decrease post-surgery (2.10 nmol/L to <0.03 nmol/L). Whole genome sequencing suggested that the patient may have an XY male karyotype, although cytological analysis was not possible to confirm the XY karyotype. Full article

Background: Specialized pro-resolving lipid mediators (SPMs), such as maresins and resolvins, play a key role in resolving inflammation and repairing tissues. This study aimed to evaluate whether maresin-1 (MaR1) and resolvin-D1 (RvD1) could serve as serum non-invasive biomarkers for monitoring disease activity in ulcerative colitis (UC). Methods: This cross-sectional study included 60 UC patients (30 active, 30 remission) and 30 healthy controls. Disease activity was assessed using the Mayo Endoscopic Subscore (MES). Inflammatory indices, including the neutrophil–lymphocyte ratio (NLR), monocyte–HDL cholesterol ratio (MHR), platelet–lymphocyte ratio (PLR), CRP–lymphocyte ratio (CLR), CRP–albumin ratio (CAR), systemic inflammation response index (SIRI), and systemic immune-inflammation index (SII), were calculated. Plasma MaR1 and RvD1 levels were measured via enzyme-linked immunosorbent assay (ELISA). Receiver operating characteristic (ROC) analysis was performed to evaluate biomarker accuracy. Results: CRP, NLR, PLR, CLR, CAR, SIRI, and SII were significantly elevated in active UC, whereas MaR1 and RvD1 were lower compared to remission and controls (p < 0.05). MaR1 levels were lower in the remission group than in controls. ROC analysis demonstrated high area under the curve (AUC) values for RvD1 (0.906), CAR (0.872), CLR (0.861), and CRP (0.858) in distinguishing active UC from remission, and for CRP (0.944), CAR (0.939), CLR (0.939), RvD1 (0.928), and MaR1 (0.889) in distinguishing active UC from controls. The specificity for detecting active UC was 60% for MaR1 and 80% for RvD1. Both RvD1 and MaR1 showed a negative correlation with the MES, with RvD1 demonstrating a stronger correlation (r = −0.754, p < 0.001). Conclusions: RvD1 shows a strong negative correlation with disease severity in ulcerative colitis, while low MaR1 levels in remission may indicate subclinical inflammation. Although MaR1 and RvD1 are not disease-specific, their role in inflammation resolution suggests they may complement conventional inflammatory markers for more comprehensive UC monitoring. Full article

Objectives: This study aimed to translate, cross-culturally adapt, and evaluate the psychometric properties of the Persian version of the Measure of Audiologic Rehabilitation Self-Efficacy for Hearing Aids (MARS-HA) in elderly Iranian adults. Methods and Materials: This cross-sectional study was conducted in Tehran, 2021. Following translation and cross-cultural adaptation, the face validity, content validity, and reliability of the questionnaire were assessed. The Satisfaction with Amplification in Daily Life (SADL) questionnaire was used to assess concurrent validity. Study participants included 300 hearing-aid users aged 60 years and older who completed the research instruments. Data were analyzed using Confirmatory Factor Analysis (CFA), Cronbach’s alpha coefficient, Pearson correlation coefficient, independent t-tests, and analysis of variance (ANOVA) in SPSS and AMOS version 24. The significance level was set at p ≤ 0.05 for all tests. Results: The mean (SD) age of the participants was 71.38 (8.05) years. The face and content validity of the questionnaire were confirmed by ten experts (CVI > 0.91). The CFA supported the four-factor structure of the questionnaire, and the goodness-of-fit indices indicated that the final model had a good fit. The Cronbach’s alpha for the total questionnaire was 0.93, and for the subscales, it ranged between 0.83 and 0.93. The Pearson’s correlation analysis results showed a positive and significant correlation between MARS-HA and SADL scores (r = 0.61, p < 0.05), supporting criterion validity. Conclusions: The P-MARS-HA questionnaire demonstrates good validity and reliability and can be used as an appropriate tool for assessing self-efficacy in hearing-aid use among elderly Iranian adults. Full article