Search Results (249)

Introduction: Fish skin is the first line of defense against the aquatic environment, acting as a physical, chemical, and immunological barrier. In addition to preventing pathogen entry, the skin and its mucus contribute to osmoregulation, innate immunity, and redox balance. Skin lesions—caused by mechanical damage, parasites, environmental stress, or handling—disrupt this barrier, increasing susceptibility to infections, inflammation, and production losses. Thus, efficient skin regeneration is essential for fish welfare and performance. Nutrition plays a key role in this process by providing substrates for epithelial repair, immune function, and antioxidant defense. Among dietary factors, zinc (Zn) is particularly important due to its involvement in cell proliferation, enzymatic activity, and maintenance of skin integrity. Objective: Our objective is to assess the effectiveness of image-based analysis in quantifying the skin healing process in Atlantic salmon fed diets supplemented with zinc. Methodology: The trial comprised three dietary treatments: a control diet with 42 mg Zn per kg (D1), and two diets supplemented up to 120 mg/kg of zinc, derived from inorganic (D2) or organic (D3) forms. Pit-tagged fish with an initial body weight (78 ± 0.1 g) were fed the diets for 75 days. After 15 days of experimental feeding, a standardized wound lesion (2.5 mm diameter × 0.5 mm depth) was inflicted in deeply anesthetized fish, with a disposable biopsy punch, in the dorsal area. After wound infliction, the fish resumed their normal feeding regime for the rest of the trial days. The progression of skin wound healing was assessed using standardized digital image analysis. High-resolution photographs of individual wounds were collected 8, 16, 24 and 32 days post-wounding. All images were acquired under standardized conditions with the inclusion of ArUco identifiers to enable a subsequent computer-assisted comparison. Morphometric parameters (wound width, diameter, perimeter and area) were used to assess wound contraction and closure over time. In parallel, a semi-quantitative visual scoring system was applied to each wound image to capture qualitative aspects of healing that are not fully described by morphometric data alone. Results: Full data analysis is currently underway, but the first results show beneficial effects of dietary zinc supplementation on the skin regenerative process. Conclusions: The combined use of objective digital measurements and standardized visual scoring enabled a comprehensive evaluation of wound healing progress, bridging quantitative tissue remodeling with biologically relevant phenotypic outcomes. This image-based framework provides a sensitive and reproducible approach for assessing dietary interventions targeting skin regeneration and barrier restoration in Atlantic salmon. Full article

Background/Objectives: The Al Haouz earthquake that struck Morocco on 8 September 2023, resulted in substantial material, human, and psychological impacts. Children are at increased risk of psychological disorders, notably post-traumatic stress disorder (PTSD). This study aims to assess probable PTSD and its associated factors among children exposed to the Al Haouz earthquake. Methods: This cross-sectional study, conducted between December 2024 and January 2025, included 536 children from the affected areas. Probable PTSD was assessed using the 20 item Child and Adolescent Trauma Screen (CATS). Sociodemographic and exposure-related data, including post-earthquake conditions, were collected using a structured questionnaire. Data analysis was performed using SPSS software, version 25. Results: Analysis revealed that 47.6% of the children presented with probable PTSD. Multivariable analysis identified several factors independently associated with probable PTSD among children exposed to the earthquake, including age between 11 and 15 years (AOR = 2.02; p < 0.001), female gender (AOR = 1.82; p = 0.001), advanced level of education (AOR = 1.87; p = 0.006), housing damage (AOR = 2.08; p = 0.015), physical injury (AOR = 1.86; p = 0.012), proximity to the epicenter (AOR = 2.22; p = 0.006), temporary shelter in tents (AOR = 1.75; p = 0.02), difficulty of evacuation (OR = 1.97; p = 0.01), and loss of a family member (AOR = 1.98; p = 0.013). Conclusions: This study revealed a high frequency of probable PTSD in children exposed to the Al Haouz earthquake and identifies several associated factors, highlighting the need to targeted, multidimensional interventions. Full article

Invertebrates rely exclusively on innate immunity but exhibit memory-like responses termed immune priming or trained immunity. In the commercially vital whiteleg shrimp (Litopenaeus vannamei), infection by Vibrio parahaemolyticus causes severe economic losses, yet the molecular networks driving secondary immune recall remain poorly understood. In this study, we established a two-step immune challenge model in L. vannamei using formaldehyde-inactivated V. parahaemolyticus and performed transcriptomic analysis on hemocytes to compare primary and secondary immune responses. Differentially expressed gene (DEG) screening and enrichment analyses (GO, KEGG, and GSEA) suggest that shrimp hemocytes undergo a broad and coordinated transcriptional reprogramming rather than uniform upregulation of immune genes. Transcriptomic data show potential associations between secondary immune priming and the modulation of cell fate processes: genes related to cell cycle progression (e.g., CDK1, CCNB3) and spindle assembly (e.g., MPS1) were significantly upregulated alongside apoptosis inhibition (CASP6 downregulation). Concurrently, metabolic remodeling was observed through the upregulation of lipid synthesis (SREBF1, FASN) and carbohydrate uptake pathways, potentially providing anabolic support for hemocyte growth and immune activation. Furthermore, the humoral effector responses appear to be strengthened, characterized by upregulated antimicrobial peptides (PEN, ALF) and the proPO melanization cascade (PPAF3, PPO3), whereas the expression of intracellular NLR was relatively suppressed, which might help mitigate excessive immune inflammation and immunopathological damage. Collectively, these transcriptomic findings identify a putative coordinated transcriptional signature of hemocyte recall responses in L. vannamei. This study expands our understanding of innate immune memory in invertebrates and provides candidate molecular markers for further study in disease-resistant breeding research in shrimp aquaculture. Full article

Soluble solids content (SSC) is one of the most important indicators of sweetness, ripeness, and market quality in sweet cherries. However, conventional SSC determination is destructive, labor-intensive, and unsuitable for rapid or large-scale quality assessment. Therefore, there is a need for fast, non-destructive, and data-driven sensing approaches that can estimate internal fruit quality without damaging the sample. This study aimed to develop a non-destructive approach for SSC prediction in sweet cherries by combining open-ended coaxial probe dielectric spectroscopy with deep learning models. An open-ended coaxial probe measurement system was designed and developed to determine the dielectric properties of sweet cherries and was coupled with an Agilent E4991A impedance analyzer operating over a frequency range of 5–3005 MHz. A total of 10,080 dielectric measurements and 2100 reference SSC measurements were collected over 26 experimental days. The dielectric constant (ε′), loss factor (ε″), and loss tangent (tan δ) were extracted and used to construct separate ε′, ε″, tan δ, and integrated combined datasets. Six deep learning architectures, namely convolutional neural network (CNN), long short-term memory (LSTM), bidirectional long short-term memory (BiLSTM), gated recurrent unit (GRU), CNN-LSTM, and convolutional long short-term memory (ConvLSTM), were trained and optimized using Bayesian optimization and early stopping. CNN achieved the best performance on the tan δ dataset (test R² = 0.9099, RMSE = 0.8354 °Brix, MAE = 0.6599 °Brix), whereas GRU yielded the highest accuracy on the integrated combined dataset (test R² = 0.8622, RMSE = 1.0331 °Brix, MAE = 0.7958 °Brix). ConvLSTM provided the most consistent performance across all four datasets (test R² = 0.8081–0.8651), demonstrating strong predictive capability and practical computational efficiency. These findings confirm the potential of reduced-range dielectric spectroscopy combined with deep learning for rapid, non-destructive SSC assessment in sweet cherries. Full article

In the context of the influx of about 1 million displaced Rohingya people from Myanmar into the Cox’s Bazar District of Bangladesh in 2017, it is critical to examine their impacts on the sustainability of the social–ecological system in host Bangladesh. The specific objectives of the study are to assess the nature of intergroup conflicts between the resettled and host communities, the emerging threats posed by resettlement to social–ecological sustainability, and the adaptation and resilience of both communities. A Case Study approach was adopted in the Rohingya resettlement area of Ukhia Upazila of Cox’s Bazar District, Bangladesh. Primary data were collected through Key Informant Interviews, Focus Group Discussions, and oral history conversations. The findings reveal that the average population density in the Rohingya refugee camps is 20 m² per person, whereas the international guideline for refugee camp population density is 30–45 m²/person. The sudden Rohingya population influx has resulted in considerable land cover change, livelihood competition, and deteriorated security conditions. Between 2015 and 2023, a rapid decline in the extent of dense forest was observed—from 93 sq km to 63 sq km. The sense of land loss among the host community created a resentment towards the resettled Rohingyas that turned into social conflicts and unrest. Despite these damages, socioeconomic evolution, the implementation of adaptive measures, and successful restoration programs by the relevant institutions have revealed some degree of community resilience. An inclusive development planning strategy is recommended to sustain livelihood opportunities for both communities and local social–ecological systems. Full article

Phytochrome-interacting factors (PIFs) were initially recognized as pivotal regulators of plant light signaling pathways. However, mounting evidence suggests that PIFs also exert significant influences on plant development and responses to stress. Here, we identified seven PIF genes in the potato genome and conducted comprehensive characterizations through phylogenetics, gene structure, conserved motif, synteny, chromosomal location analyses and cis-regulatory element. Transcriptome data and gene expression analysis showed that the StPIF4 gene was markedly induced by mannitol-induced water deficit. Additionally, the StPIF4 protein was primarily localized in the nucleus and plasma membrane. In order to explore the function of the StPIF4 gene under mannitol-induced water deficit, the StPIF4 gene was cloned, and several StPIF4 overexpression (OE) lines (OE-8, OE-10, and OE-11) and three RNA interference (RNAi) transgenic lines (RNAi-5, RNAi-9, and RNAi-11) were obtained. The OE lines displayed notable enhancements in various growth parameters such as plant height, leaf number, branch number, fresh weight, dry weight, total root length, root surface area, number of root forks, and number of root tips under mannitol-induced water deficit compared to the wild-type (WT) lines, whereas these parameters were significantly decreased in the RNAi lines. The activities of antioxidant enzymes (SOD, POD, CAT) and the accumulation of proline and soluble sugars were also significantly increased under mannitol-induced water deficit, whereas the levels of thiobarbituric acid reactive substances (TBARSs) and reactive oxygen species (ROS), including hydrogen peroxide (H₂O₂) and O₂⁻, were significantly reduced in the OE lines compared to WT plants under mannitol-induced water deficit. Moreover, the stomatal aperture of the leaves and the water loss rate in the leaves of the OE lines were significantly reduced under mannitol-induced water deficit compared to the WT plants, whereas for the RNAi lines they were significantly increased. In addition, the overexpression of StPIF4 also upregulated expression of drought-responsive genes and ABA content under mannitol-induced water deficit. Collectively, these results highlight the positive role of the StPIF4 gene in enhancing potato tolerance to mannitol-induced water deficit by decreasing stomatal aperture, enhancing ROS scavenging and mitigating oxidative damage. Full article

Background: Minimally invasive aesthetic procedures using atmospheric plasma devices are increasingly applied to improve skin laxity and age-related loss of firmness. These systems generate a localized plasma arc at the tissue surface, enabling controlled and spatially confined tissue interaction; however, quantitative histological data on the extent of plasma-induced tissue effects remain limited. Materials and Methods: This ex vivo study evaluated freshly collected porcine kidney, liver, and skeletal muscle tissues (n = 3 per tissue type). Tissue sublimation defects were produced using the Plasma IQ device under conditions representative of standard clinical use, applying two predefined settings (“LOW” and “HIGH”). Immediately after treatment, specimens were fixed in 10% neutral buffered formalin and processed into formalin-fixed paraffin-embedded (FFPE) blocks. Sections were stained with hematoxylin and eosin (H&E), and the diameter and depth of the sublimation zones were measured by light microscopy. Results: Plasma IQ exposure consistently produced well-demarcated superficial sublimation defects in all tissues. The HIGH setting increased the diameter of the sublimation zones compared with the LOW setting across all tissue types, whereas the depth differences were smaller and tissue-dependent. Lesions exhibited a characteristic flattened, cone-shaped morphology, with diameter exceeding depth. No histologically detectable collateral damage was observed beyond the immediate sublimation zone. Conclusions: Atmospheric plasma treatment induces controlled and spatially confined tissue sublimation with clearly defined histological boundaries and limited penetration depth. These findings provide quantitative histological support for the localized tissue effects of plasma-based devices and their rationale in aesthetic procedures. Full article

National and provincial surveillance of pine wood-boring pests in China is designed to detect damaging taxa, map occurrence, assess risk and loss, and support early warning, zoning and control decisions. Province-scale comparisons of alternative monitoring devices remain rare, especially under the operational conditions required by such programs in climatically and topographically heterogeneous forests. Using data from the 2025–2026 systematic survey of pine wood-boring pests in Yunnan Province, China, we integrated several monitoring datasets to compare baited logs, lure traps, and flight-intercept traps. The harmonized database comprised 2603 standard monitoring subcompartments and 3519 installed sites, including 4080 baited-log piles, 4807 lure-trap units, and 373 flight-intercept traps. Main performance analyses focused on active sites with at least one collection event (570 baited-log sites, 63 flight-intercept sites, and 496 lure-trap sites), whereas installed site summaries were retained to characterize operational coverage. Because the study was observational and the three devices have different sampling mechanisms, we interpreted detection probability as the primary early warning metric, and catch, operational taxon richness, standardized yield, and cost metrics as supporting indicators of diagnostic and operational return. Site-level comparisons were complemented with paired analyses of 21 co-located subcompartments, a more comparable subset defined within county × elevation band × host group strata represented by all three methods, county-clustered regression, and a taxonomic-resolution sensitivity analysis. Lure traps consistently had the highest detection probability (0.73), the greatest cumulative catch (8617 individuals), and the broadest operational taxonomic coverage (45 operational taxa). In county-clustered models, lure traps had higher odds of detection (odds ratio = 11.25, 95% CI: 5.64–22.43) and higher catch rates (incidence rate ratio = 5.97, 95% CI: 2.26–15.76) than baited logs after adjustment for elevation band, host group, and collection effort. The same ranking persisted in the more comparable subset and after exclusion of unresolved family-, subfamily-, genus-, and unknown-level records. Standardized yield peaked at 1500–2200 m. Scenario-based costing showed that lure traps had the lowest cost per captured and resolved captured individual, whereas detection cost estimates were interpreted together with absolute detections and operational taxonomic output. Overall, the results support a tiered surveillance architecture in which lure traps serve as the primary routine early warning tool, baited logs provide targeted complementary information, and flight-intercept traps are reserved mainly for exploratory or faunistic surveys. Full article

Data collected by sensors plays a critical role in system decision-making. Microphone arrays enable distance measurement and fault localization, which is particularly critical in the radiation environments of nuclear facilities. Acoustic localization based on microphone arrays can effectively fulfill this requirement. This study experimentally evaluates the Total Ionizing Dose (TID) effects of ⁶⁰Co γ-ray radiation on commercial MEMS (micro-electro-mechanical systems) silicon microphones. Five identical microphone units were simultaneously irradiated at a dose rate of 0.0342 Gy(Si)/s while continuously monitoring operating current and spectral response. Experimental results show that the commercial MEMS silicon microphones exhibit an average TID failure threshold of 932.6 ± 62.8 Gy(Si), with a 95% confidence interval of [875.5, 989.7] Gy(Si). Three degradation/failure levels are clearly defined: channel degradation, channel failure, and full system failure. Radiation exposure causes a progressive increase in operating current (up to 6.7 times the initial value), severe spectral distortion, and ultimately complete loss of localization function. This indicated that standard commercial MEMS silicon microphones possess a certain degree of tolerance to TID radiation. Subsequently, an annealing test was performed. However, Post-irradiation annealing restored the operating current but not the acoustic performance, indicating irreversible radiation-induced damage. Full article

Improved conservation efforts in China have contributed to the recovery and range expansion of the Asian elephant, increasing spatial overlap between humans and elephants and intensifying the pressure of human–elephant coexistence. Understanding human tolerance toward Asian elephants has therefore become an important pathway for promoting conservation and coexistence. Using survey data from 873 farm households collected in Xishuangbanna Prefecture and Pu’er City in Yunnan Province, this study measures tolerance toward Asian elephants across five dimensions: types of elephant-related damage, economic loss, population size, spatial distance, and activity frequency. Independent-sample t-tests, one-way ANOVA and ANCOVA were used to examine differences in tolerance among different groups of farm households. The results show that: (1) the overall tolerance toward Asian elephants among farm households is relatively low (mean = 2.40); (2) within types of elephant-related damage, tolerance is lowest for crop loss and cash crop loss, followed by loss of working time and risk of human injury, while tolerance is relatively higher for damage to houses and property, loss of stored food, and damage to vehicles; (3) farm households showed low levels of tolerance across the dimensions of economic loss, population size, spatial distance, and activity frequency; (4) higher tolerance is observed among male respondents, Dai farm households, those engaged in wildlife protection-related occupations, and households located in Pu’er City, and tolerance increased as cultivated land area decreased, household income increased, and agricultural dependence declined. These findings provide empirical evidence for understanding farm households’ tolerance toward Asian elephants and offer policy insights for improving tolerance, optimizing human–elephant conflict (HEC) management, and promoting the social sustainability of human–elephant coexistence. The study also contributes China-based evidence to discussions on flagship species conservation and community coexistence under the SDG 15 and CBD frameworks. Full article

The impact of environmental disturbances and sensor deployment variations on damage identification represents a critical bottleneck that constrains the practical effectiveness of structural health monitoring. Existing methods addressing these challenges often suffer from poor interpretability due to information loss during feature extraction or exhibit insufficient sensitivity in identifying early-stage minor damage. This paper proposes a damage identification method based on the Shapelet Transform and Random Forest classifier, which extracts highly interpretable local shape features from vibration response signals to achieve robust identification of structural state changes. The study utilizes measured random vibration response data from a timber truss bridge. The dataset comprises four reference states collected on different dates and five damage states simulated by additional masses ranging from +23.5 g to +193.7 g, with sensors deployed in both vertical and horizontal directions. The Shapelet Transform selects local subsequences with high information gain from the original time series as features, which are subsequently classified using the Random Forest algorithm. The experimental design systematically investigates the influence of different damage severities, sensor locations, and environmental variations on method performance. The results demonstrate that with a Shapelet extraction time of 10 min, the method achieves 100% identification accuracy across multiple operating conditions comprehensively considering environmental variations, sensor location differences, and varying damage severities. When the extraction time is reduced to 5 min, 3 min, and 1 min, the average accuracies are 93.98%, 89.51%, and 58.48%, respectively. The method effectively identifies the minimum simulated damage (+23.5 g), which represents only 0.07% of the total structural mass, while maintaining stable performance under varying sensor locations and environmental conditions. Compared to traditional methods based on global frequency-domain features or statistical characteristics, the proposed method extracts physically meaningful local Shapelet features, offering significant advantages in interpretability. In contrast to deep learning approaches, this method demonstrates greater robustness under limited sample conditions. This study confirms that the combined framework of the Shapelet Transform and Random Forest can effectively address multiple real-world challenges in structural health monitoring, delivering high accuracy, strong robustness, and excellent interpretability, thereby providing a novel approach for developing practical real-time damage identification systems. Full article

Heavy and overloaded freight traffic strongly affects pavement performance, yet short-term weigh-in-motion (WIM) measurements are not easily converted into design-oriented traffic inputs. Using the Nairobi Southern Bypass in Kenya as a case study, this study develops axle load spectrum (ALS) and equivalent single axle load (ESAL) indicators from more than 1.5 million axle group records collected between June and December 2025 and proposes an XGBoost-based conditional axle load spectrum (CA-ALS) framework. The data revealed strongly right-skewed load distributions, with a limited number of heavily loaded axle groups dominating pavement damage. Compared with the static ALS by axle group type baseline, the CA-ALS reduced log loss from 2.7563 to 2.6709 in conditional spectrum prediction. In the December 2025 tandem axle benchmark, the CA-ALS increased the ESAL-based verification input by 6.0% at b = 4 and 11.1% at b = 5 relative to the stronger static reference. A legal-load-capped counterfactual analysis further showed that, for all heavy vehicles, observed overloading increased ESAL by 161.0% at b = 4 and 239.4% at b = 5. These results indicate that the CA-ALS provides condition-sensitive traffic inputs for design traffic verification, scenario-based pavement checks, and overload-sensitive evaluation based on short-term WIM observations. Full article

As one of the world’s leading cotton-producing countries, China frequently experiences severe yield reductions due to crop diseases and pest infestations, with losses often exceeding 20%. Although computer vision models can identify diseased plants, they currently fail to connect visual symptoms to the diagnostic reasoning process used by agronomists. This leads to text descriptions that ignore the biological causes of the damage. To fix this, we built Multimodal Knowledge Graph-Enhanced Cross Vision Transformer-18-Dagger-408 and Text-to-Text Transfer Transformer for Cotton Disease and Pest Image Captioning (MKG-CottonCapT6), a model that uses a local knowledge database to generate professional diagnostic reports from field images. The technical core consists of a Multimodal Knowledge Graph (MMKG) containing 14 types of entities (such as Pathogens and Control Agents) and 12 types of relations. We use a Cross Vision-Transformer-18-Dagger-408 (CrossViT) encoder to capture both the overall leaf shape and microscopic details of pests. Through a Visual Entity Grounding (VEG) module, the model maps visual features directly to specific triplets in the graph. These triplets are then turned into text sequences and fused with image data in a Text-to-Text-Transfer-Transformer (T5) decoder. To train the model, we collected a dataset of cotton images paired with expert descriptions of lesions, colors, and affected plant parts. Tests show that MKG-CottonCapT6 performs better than standard models, reaching an Information-based Metric for Image Captioning (InfoMetIC) score of 72.6%. Results prove that by using a specific alignment loss (${\mathcal{L}}_{align}$), the model generates reports that correctly name the disease stage and recommend specific chemicals, such as Carbendazim or Triadimefon. This framework provides a practical tool for farmers to record and treat cotton diseases with high precision. Full article

This study investigates the performance and microstructure evolution of high-ferrite Portland cement (HFC) concrete under the coupled action of abrasion and freeze–thaw cycles (CAA-FTC). The 3D surface morphology of deteriorated concrete was studied; abrasion depth and volume loss evolution data were collected, while analyzing the abrasion depth fractal dimension. The characteristics of hydration products were determined using mercury intrusion porosimetry and ²⁹Si nuclear magnetic resonance method. The ITZ’s micromechanical properties and thickness were investigated via nanoindentation and SEM-EDS. The results show that under the CAA-FTC conditions, concrete deterioration is significantly exacerbated, leading to increased abrasion depth and volume loss compared to single-factor abrasion. A significant inverse relationship between the abrasion depth fractal dimension and abrasion resistance was revealed. Under CAA-FTC conditions, CG1 and CD1 exhibit increased total porosity with enlarged large pore proportions and reduced medium pores, whereas HFC1 outperforms HFC2-based concrete, showing 8.2–26.4% higher abrasion resistance and 6.5–12.0% greater nanoindentation elastic modulus in the ITZ. Regarding the deterioration factors’ influence weight, abrasion time exhibits a deterioration weight 4.8 times to 10.0 times greater than freeze–thaw cycling, making the former a dominant factor and the latter a secondary contributor. Mechanistically, freeze–thaw cycles reduce the average molecular chain length of C-S-H gel, increase harmful pores and total porosity, and degrade the ITZ’s microstructure, while abrasion causes surface-to-core physical damage and freeze–thaw cycling induces core-to-surface expansive damage. This interaction results in surface scaling, mortar spalling, and structural loosening, significantly reducing physical and mechanical properties of the concrete under study. Full article

This narrative review summarizes current evidence on the molecular and cellular effects of low-dose methotrexate (LD-MTX) on bone tissue. In addition, it critically examines the limited and heterogeneous data on LD-MTX-associated osteopathy, a rare and incompletely understood condition that may be underrecognized in clinical practice. Finally, the review highlights key knowledge gaps and outlines future research directions aimed at improving diagnosis, management, and prevention. In total, 451 relevant articles were retrieved, and 71 studies were included in our review. Methotrexate (MTX) has been shown to prevent bone loss associated with inflammatory rheumatic diseases, primarily through its anti-inflammatory properties. However, current evidence highlights a variety of negative effects on bone associated with LD-MTX therapy, including osteoblast dysfunction, increased osteoclastogenesis, and endothelial damage. Collectively, these effects may result in deterioration of microarchitecture, impaired bone healing and insufficiency fractures. Despite the long and successful use of MTX in rheumatology, our knowledge of its effects on bone and awareness of LD-MTX osteopathy remain limited, potentially leading to delayed or missed diagnoses. Recent clinical studies highlight the potential underestimation of this condition and emphasize the need for further research to establish clear diagnostic criteria and treatment guidelines, as well as to achieve a more comprehensive understanding of the complex pathophysiology underlying LD-MTX osteopathy. Full article