Search Results (14,629)

Digestive tract structure is a key indicator of fish health and environmental adaptation, while seasonal dynamics of the gut microbiota reflect host responses to environmental changes. In this study, the digestive tract microstructure of Hypomesus nipponensis from Bosten Lake was characterized using H&E staining and scanning electron microscopy, followed by 16S rDNA gene V3-V4 region sequencing and analysis of the gut microbiota in spring, summer, and autumn. The results showed that the esophageal mucosa of H. nipponensis is a stratified columnar epithelium, with abundant gastric glands, and the circular muscle layer of the stomach caeca is significantly thickened (244.84 ± 49.01 μm). The pyloric caeca resemble the gut in structure; both are covered with dense microvilli on the luminal surface. Collectively, these features constitute the structural basis for its carnivorous diet. Microbiota analysis revealed that the diversity of gut microbiota fluctuated significantly with season: the Chao, Ace, and Sob indices in spring (144.63 ± 30.27) were significantly higher than in summer (82.13 ± 21.45) and autumn (83.25 ± 15.30) (p < 0.001), with no significant difference between summer and autumn (p > 0.05). The dominant marker genera of H. nipponensis in spring, summer, and autumn were Bacillus (31.60%), Clostridium (32.20%), and Sarcina (29.32%), respectively. This study describes the adaptive characteristics of the digestive tract structure and feeding habits of H. nipponensis and reveals the seasonal changes in its gut microbiota. Importantly, since the digestive tract structure data were collected only in summer, the direct relationship between the structure and seasonal microbial dynamics cannot be determined, and multi-season histological sampling is needed for further investigation. Nevertheless, these findings provide preliminary morphological and microbiological references for the ecological adaptation of this species in Bosten Lake and offer a scientific basis for water resource management in this area. Full article

Cabbage (Brassica oleracea var. capitata), a member of the Brassicaceae family, is an important vegetable crop grown worldwide. Self-incompatibility (SI) in cabbage is a key trait that prevents self-fertilization and inbreeding, thereby maintaining genetic diversity within populations. Although several genes related to SI have been reported, its genetic control remains unclear. In this study, we developed an F₂ population from the highly self-compatible (SC) cabbage line 87-534 and the highly self-incompatible (SI) line 01-20, both of which exhibit the S5 haplotype. The segregation analysis of the F₂ population revealed the possible control of SI by a major gene with additional modifying genetic factors. Bulk segregant analysis sequencing (BSA-Seq) and RNA sequencing (RNA-Seq) were performed on SI and SC samples selected from the F₂ population. BSA-Seq revealed a candidate region on chromosome 7 (C07: 7.45 Mb to 8.93 Mb), including 32 differentially expressed genes (DEGs). RNA-Seq identified a total of 2400 DEGs between the two pools, and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses suggested that plant hormone biosynthesis and signaling, plant immune response were significantly enriched and may be involved in SI. The combined analysis of BSA-Seq and RNA-Seq identified six candidate genes associated with SI, and their expression was confirmed using quantitative real-time PCR (qRT-PCR). Among them, Bol023956 encodes fructokinase, Bol023986 is involved in plant defense response, Bol024018 is related to pollen development, Bol024012 encodes a transport protein for phytohormones, Bol023943 encodes chorismate mutase 3, and Bol012515 is an important regulatory gene for chloroplast synthesis. These six genes, potentially linked to SI, should be targets for further validation. These findings provide insights into the molecular mechanisms of SI in cabbage and the selection of superior cabbage varieties. Full article

Two new species of the flesh fly subgenus Sarcophaga Meigen, 1826 (Diptera: Sarcophagidae), Sarcophaga (S.) karai sp. nov. and Sarcophaga (S.) hayati sp. nov., are described from Türkiye. For each new taxon, detailed morphological descriptions, differential diagnoses, and high-resolution illustrations of the male terminalia are provided. The genital structures of the newly recognized taxa were further examined using scanning electron microscopy (SEM), allowing detailed characterization of surface morphology and fine ultrastructural features not discernible with conventional optical methods. The diagnostic value of key morphological structures of the male terminalia is discussed in the context of species delimitation within the subgenus. Each new species is compared with those most similar in terminalia morphology, and an updated identification key to the males of Turkish representatives of the subgenus is provided to facilitate future faunistic studies in the region. These findings contribute to a more comprehensive understanding of sarcophagid diversity across the Anatolian Peninsula and highlight the substantial species richness that remains to be documented within this group. Full article

Poplar (Populus) trees are indispensable to various industries and environmental sustainability efforts. They are widely utilized for paper production, timber, and windbreaks, while also playing a significant role in carbon sequestration. Given their economic and ecological importance, the effective management of diseases is crucial. Convolutional Neural Networks (CNNs), renowned for their ability to process visual data, are pivotal in accurately detecting and classifying plant diseases. This study presents a domain-specific dataset of manually collected images of diseased poplar leaves from Uzbekistan and South Korea, ensuring geographic diversity and broader applicability. The dataset includes four disease classes, i.e., “Parsha (Scab),” “Brown spotting,” “White-Gray spotting,” and “Rust,” which represent common afflictions in these regions. To advance research efforts, this dataset will be made publicly accessible, providing a valuable resource for the scientific community. Leveraging the cutting-edge YOLOv9c model, a state-of-the-art CNN architecture, we applied the Histogram Equalization technique as a preprocessing step to enhance the image quality to increase the accuracy of disease detection. This method not only improves the diagnostic performance of the model but also provides a scalable solution for monitoring and managing poplar diseases. By ensuring the health of poplar trees, this approach supports the sustainability of these critical resources. To our knowledge, this is the first publicly available dataset specifically focused on diseased poplar leaves, making it a significant contribution to global research efforts. It offers an invaluable resource for researchers and practitioners, enabling further advancements in early disease detection and sustainable forestry management. Full article

Nature-based solutions (NBSs) involving tree-based interventions deliver multiple community benefits, yet evidence linking these benefits to underlying socio-ecological vulnerabilities remains limited. This study synthesised metadata from 131 European treescape NBS case studies spanning eight biogeographical regions using reverse-logic, thematic qualitative analysis. Case studies were identified via adapted PRISMA guidelines from open-access repositories, with community benefit themes categorised and mapped spatially across bioregions. The analysis revealed eleven principal community benefit categories and distinct region-specific patterns: Mediterranean interventions primarily mitigated extreme heat and drought vulnerabilities, whilst Alpine projects addressed slope stability and hazard reduction. The Continental and Atlantic regions emphasised social cohesion, recreational access, and the preservation of cultural heritage. The reverse-logic methodology successfully identified underlying socio-ecological vulnerabilities through systematic analysis of observed benefit profiles across diverse European contexts. This approach provides evidence-based guidance for designing location-sensitive treescape NBS that advance environmental research and public health objectives. The findings establish a methodological foundation for future assessments of NBS effectiveness and for refining location-specific treescape interventions that address community vulnerabilities and enhance adaptive capacity. Full article

Cadmium (Cd), a highly mobile and phytotoxic heavy metal, threatens plant growth and food safety and has increased interest in woody plant-based phytoremediation. However, the genome-wide characteristics of the NAC transcription factor family and its role in Cd tolerance remain largely unknown in pomegranate (Punica granatum L.), a stress-tolerant woody plant. In this study, 121 PgNAC genes were identified from the chromosome-level genome of the pomegranate cultivar ‘Tunisia’. Phylogenetic analysis classified these genes into two major groups and 16 subgroups. PgNAC genes were unevenly distributed across the eight chromosomes and showed evident clustered distribution patterns. Synteny and Ka/Ks analyses further revealed that segmental and tandem duplication jointly shaped the expansion of the PgNAC family, while the duplicated pairs have largely evolved under strong purifying selection. Conserved motif and gene structure analyses showed that PgNAC proteins possessed a highly conserved N-terminal NAM domain, whereas their C-terminal regions were relatively divergent. Promoter analysis further identified abundant hormone- and stress-responsive cis-elements, suggesting diverse regulatory roles of the PgNAC family. Transcriptome profiling identified PgNAC87, a member of the NAP subfamily, as a Cd-responsive candidate gene that was consistently upregulated in both roots and leaves under Cd stress. Heterologous overexpression of PgNAC87 in tobacco significantly enhanced Cd tolerance, as reflected by alleviated growth inhibition, increased antioxidant enzyme activities and osmotic adjustment substances, and reduced oxidative damage. Collectively, our results clarify the evolutionary features of the PgNAC family and its involvement in Cd-induced transcriptional regulation, while highlighting PgNAC87 as a potential genetic target for enhancing Cd tolerance in pomegranate and related woody species. Full article

In most metaheuristic approaches, particles are handled based on their fitness values without considering the distribution of solutions within the search space. Although this approach is simple, it causes particles to prematurely converge into a limited region of the search space due to the loss of diversity within the population. To address this limitation, this study proposes a metaheuristic approach in which particles are assigned to different search behaviors based on their Euclidean distance to the best solution. At each iteration, the population is divided into three groups: an exploitation set composed of the closest particles, an exploration set composed of the farthest particles, and a reference set composed of intermediate-distance particles. Two dedicated operators manage these groups: exploitation particles perform fine-grained refinement around the current best, whereas exploration particles search for new regions guided by randomly selected reference particles. In addition, an elitist acceptance mechanism ensures that only improved positions are retained, thereby promoting monotonic progress. This distance-based framework provides a distributed population of particles, where each particle is driven by its relevance to the optimal solution in the search space. This ensures a good diversity of solutions and prevents premature convergence and redundant search efforts. Experimental results on benchmark functions show that the method outperforms several State-of-the-Art metaheuristic algorithms in both solution quality and convergence behavior. Full article

To elucidate the mammalian community structure and interspecific relationships within the alpine ecosystem of the Qinghai–Tibet Plateau, this study was conducted in the Selin co National Nature Reserve for Black-necked Cranes, Tibet. Based on infrared camera monitoring data collected from June 2023 to July 2024, we analyzed mammalian species diversity and their spatial association patterns. A total of 150 infrared cameras were deployed, of which 128 were effectively retrieved, yielding 13,301 effective camera-trap days and 31,170 photographs of mammals. In total, 21 mammal species were recorded, belonging to 5 orders, 9 families, and 17 genera. The species accumulation curve approached an asymptote, indicating adequate sampling effort. Relative abundance analysis showed that Bharal (Pseudois nayaur) was the dominant species (RAI = 13.72), followed by Plateau Pika (Ochotona curzoniae) (RAI = 8.44), Moupin Pika (Ochotona thibetana) (RAI = 5.93), and Red Fox (Vulpes vulpes) (RAI = 5.50), while Snow Leopard (Panthera uncia) exhibited a moderate abundance level (RAI = 3.69). Significant differences in species diversity were observed among habitat types. Alpine meadow and meadow–desert ecotone exhibited higher diversity indices, whereas alpine desert and alpine bare rock habitats showed lower diversity. Interspecific association analysis identified 30 significant species pairs (p < 0.05), among which positive associations accounted for 93.3% and negative associations for 6.7%. The constructed association network comprised 16 nodes and 30 edges, with Chiru (Pantholops hodgsonii), Snow Leopard, and Red Fox serving as key hub species. Predator–prey pairs exhibited clear spatial coupling, while positive associations among herbivores mainly reflected shared utilization of similar habitat resources. The association structure varied across habitats, being most complex in alpine meadow, whereas no significant associations were detected in alpine desert. Overall, the mammalian community in this region is characterized by “low species richness and high endemism,” with interspecific relationships dominated by positive associations. Habitat heterogeneity plays a critical role in shaping the structure of the association network. These findings provide a scientific basis for biodiversity conservation and alpine ecosystem management on the Qinghai–Tibet Plateau. Full article

The optimization of new cropland allocation is crucial for promoting the efficient use of cropland resources and safeguarding food security. However, existing studies primarily take suitability as the optimization objective and lack the consideration of stable utilization potential, which may lead to subsequent unstable use. To address this gap, this study quantified the stable utilization potential of new cropland using a machine learning model and integrated it with the ant colony optimization (ACO) model to develop a spatial allocation framework. This framework was validated in Guangdong Province, China, a region characterized by diverse resource endowments and pronounced regional heterogeneity. The results indicated that, under the specified objective-weighting scheme and compared with the business-as-usual (BAU) scenario, the optimized scenario achieved regional cropland quantity balance. It also increased the average stable utilization potential of new cropland and overall utility by 34.84% and 12.74%, respectively, while reducing the mean cost and mean ecological benefit loss per unit area by 10.22% and 41.36%, respectively. Overall, under the specified constraints, the proposed framework offers a promising approach for new cropland planning and provides a basis for governments and land management authorities to improve future allocation practice. Full article

Digital camera sensors are designed to capture a wide range of incident illuminants, enabling the creation of high-quality images. However, these sensors lack the capability to differentiate between the color of the source illuminant and the actual color (or original color) of the object being captured. For this reason, the computational color constancy (CCC) was introduced and has been developed over decades. The CCC is an approach to modeling the color perception of the human visual system (HVS) by ensuring accurate object color determination under varying source illuminant conditions. At the core of human visual perception (HVP)-based CCC is attaining higher accuracy in scene illuminant estimation. The emergence of deep convolutional neural networks (DCNNs) was a recent innovation in accurate illuminant estimation, fundamentally transforming the CCC research landscape. Nevertheless, accurate illuminant estimation still remains a huge challenge for both traditional and state-of-the-art (SOTA) approaches. To further advance precision in illuminant estimation, this article presents a novel learning-based illumination color cast estimation approach to HVP-based CCC. Most importantly, the proposed approach is intended to integrate informative features into both channel and spatial regions while preserving long-term dependency feature information with the use of dense skip connections. To achieve these objectives, the proposed Dense Dual Connection Aggregated Transform Network (DDCATNet) architecture is designed to comprise several modules: shallow feature extraction, channel-wise and spatial feature-based Dense Dual Connection (DDC), fusion of the dense channel-wise attention (CA) and spatial attention (SA) branches through a gate mechanism (GM) unit, and aggregate transform. It is worth noting that both the CA blocks and the SA blocks in the DDC module are characterized by dense and cascading connections, meant to preserve long-term feature information and modulate different-level feature information at both global and local scales. The densely connected CA branch (DCA) and the densely connected SA branch (DSA) are also highly effective in securing high-contribution information while suppressing redundant data. The GM unit is integrated at the back of the DDC module, fusing the two DCA and DSA branches to ensure the adaptive merging of useful hierarchical feature information and the extraction of more valuable feature information. As a result, the proposed DDCATNet architecture significantly enhanced precision in illuminant estimation, thereby improving performance. In rigorous experiments on a wide range of datasets, the proposed DDCATNet approach outperformed its SOTA counterparts, validating the efficacy and generalization capabilities, as well as robust camera-invariance, across diverse, single- and multi-illuminant datasets and model architectures. Full article

ATP-binding cassette (ABC) transporters are one of the largest superfamilies of membrane proteins, but little is known about the structural and evolutionary features of their non-domain regions. To clarify the diversity of these non-canonical regions across evolutionary lineages, we performed an analysis of intrinsically disordered regions, site-specific selection and predicted post-translational modification (PTM) sites among five architectural classes involving 1581 prokaryotic and eukaryotic sequences. Linker and flanking regions were more disordered than transmembrane and nucleotide-binding domains in all architectures. Disorder fraction was significantly different between region types after phylogenetic correction (Pagel’s λ ≈ 0.97). Predicted PTM sites are enriched in disordered non-domain segments, with N-linked glycosylation and phosphoserine showing the strongest positive enrichment. A total of 140 sites satisfied a tiered conservation criterion (MusiteDeep score ≥ 0.5; cross-species conservancy ≥ 30%), including 40 high-confidence or moderate-confidence sites (conservancy ≥ 50%) as well as novel phosphotyrosine candidates in half transporters and NBD-only proteins. Site-specific selection analyses showed pervasive purifying selection across domain cores and architecture-dependent enrichment of episodic positive selection in non-domain regions, with significant non-domain enrichment in full reverse and half forward transporters (Fisher’s exact, BH-adjusted p < 0.05). In summary, these findings establish that non-canonical regions of ABC transporters are evolutionarily dynamic and contain conserved predicted modification sites, supporting the idea that these regions are evolutionary dynamic segments that deserve experimental characterization as candidate regulatory interfaces. Full article

Thalassemia is one of the most common inherited diseases in Guangxi, China. Early identification of thalassemia by neonatal screening is beneficial for effective clinical management and treatment. A total of 3671 newborns from multiple centers of Guangxi were prospectively recruited and screened for thalassemia using single molecule real-time (SMRT) sequencing technology. A total of 36 types of variants of globin genes were identified, including 16 common variants and 20 rare variants in the Chinese population. In total, 956 (26.04%) newborns were identified to carry thalassemia variants, including 672 (18.31%) α-thalassemia, 228 (6.21%) β-thalassemia, 55 (1.50%) combined α/β-thalassemia and 1 (0.03%) δ-thalassemia. In addition, this study showed that the carrier rates of structural variants of α-globin genes and abnormal hemoglobin variants were 1.28% and 0.93% respectively. Phenotypically, 12 newborns with hemoglobin H disease and 2 cases with intermedia β-thalassemia were found, two of whom would be misdiagnosed by conventional genetic analysis methods. Collectively, this study characterized the complexity and diversity of thalassemia gene variants in newborns of Guangxi, and further achieved early identification of newborns with intermedia thalassemia, which facilitated precision prevention of thalassemia in this region. Also, SMRT provided a powerful tool for neonatal thalassemia screening, especially in prevalent regions. Full article

Image generation of plant disease in the natural environment has always been a challenging task. Traditional methods applied in the image generation of plant disease are without sufficient diversity and detailed lesions. Thus, this paper applies an image harmonization method to generate diverse combinations of disease images by integrating different backgrounds and target regions to enhance diversity. To construct the dataset, we captured real disease images of soybean and rice in natural environments. Next, the Squeeze-and-Excitation (SE) attention mechanism was integrated into the domain verification network (DoveNet), together with a mask guide generator, to focus more attention on lesions. Two discriminators worked together to capture global and local features, ensuring the preservation of critical contextual information. Finally, the improved DoveNet achieved a MSE of 43.77, a PSNR of 33.02, and an SSIM of 0.9806, showing a reduction of 3.61 in the MSE, an increase of 0.50 in the PSNR, and a 2.49% improvement in the SSIM compared with the original DoveNet. Meanwhile, through visual Turing tests we confirmed that images generated using the improved DoveNet were of much better quality and more convincing. Full article

Theta oscillations, neural activity within the 4–8 Hz range, are implicated in a wide range of cognitive functions, including oculomotor and sensory processing, attention, memory, and motor planning and execution across diverse brain regions. Saccadic eye movements (SEMs), which are integral to visual perception and cognition, occur within a similar frequency range. This review explores how theta oscillations contribute to oculomotor and cognitive processing, emphasizing their role in coordinated motor and sensory functions. We synthesize foundational and contemporary studies into a working model describing neural synchronization across cognitive networks. We discuss the complex interplay between theta oscillations, SEMs, and cognition, summarizing the current state of our knowledge. Full article

Background: Vascular adverse events (VAEs) related to facial filler injections are rare but potentially severe complications. Doppler ultrasound has emerged as an adjunct imaging tool for evaluating vascular compromise; however, Doppler findings in facial VAEs remain insufficiently characterized. Objectives: To characterize Doppler ultrasound findings associated with filler-related facial VAEs and to assess whether Doppler patterns differ according to prior hyaluronidase administration. Methods: This international multicenter retrospective observational study included 100 patients with clinically diagnosed facial VAEs following filler injections between May 2022 and April 2025. Doppler ultrasound findings were analyzed, including absent flow in perforators and major arteries, compensatory flow, abnormal waveforms, increased peak systolic velocity (PSV), and absence of Doppler abnormalities. Patients were categorized according to hyaluronidase administration prior to ultrasound evaluation. Descriptive statistics and comparative analyses were performed. Results: One hundred patients (median age, 38 years; IQR: 30–50; 88 women) were evaluated. The most frequent Doppler ultrasound findings were absent flow in perforators (42%) and major arteries (35%), followed by compensatory flow (26%), string sign (18%), flow diversion (16%), and increased peak systolic velocity (16%). No Doppler abnormalities were observed in 12% of cases, while tardus–parvus (9%) and staccato waveform (8%) were less frequent. Doppler ultrasound findings did not differ significantly between patients who received hyaluronidase before imaging and those who did not (all p > 0.05). The dose of hyaluronidase varied substantially. Livedo reticularis, blanching, and pain were the most common clinical findings. Central facial arterial territories, particularly the perioral, nasolabial fold, nasal, and glabellar regions, were most commonly involved. Conclusions: Filler-related facial VAEs show recognizable Doppler ultrasound patterns, and the identification of these patterns may improve localization of vascular occlusion and support ultrasound-guided hyaluronidase administration, potentially enabling more targeted delivery with lower doses. Full article