Search Results (286)

Introduction: Myxoid liposarcoma (MLPS) is a rare soft tissue sarcoma comprising 5–10% of adult cases, most often in the thigh. Diagnosis is challenging due to nonspecific imaging findings and resemblance to benign lesions. Case Report: A 42-year-old male presented with a painless, enlarging upper right medial thigh mass. CT and ultrasound suggested a complex solid lesion, possibly benign. Outpatient surgical excision revealed a red, gelatinous, non-encapsulated mass. Frozen section suggested a myxomatous spindle cell tumor. Final pathology confirmed MLPS FNCLCC grade 2 (intermediate grade) with DDIT3 rearrangement on fluorescence in situ hybridization (FISH). Margins were negative but close. Postoperative PET scan and Signatera MRD assay were negative for metastasis. Given the tumor’s size (>10 cm) and known radiosensitivity, adjuvant radiotherapy (60–66 Gy) was initiated. Discussion: MLPS features myxoid stroma, plexiform vasculature, and, in high-grade tumors, a round cell component. The FUS::DDIT3 fusion gene is diagnostic. While MRI offers superior soft tissue characterization, definitive diagnosis requires pathology and molecular testing. Surgical excision with negative margins remains standard, with radiotherapy recommended for large tumors or close margins to reduce recurrence. This case highlights the limitations of preoperative imaging and the value of intraoperative pathology in guiding management. Conclusions: Early recognition, accurate diagnosis, and tailored multimodal treatment are essential for MLPS. Given the potential for recurrence, late extrapulmonary metastases, long-term surveillance with imaging, and molecular assays are critical for optimizing outcomes. Full article

Marine lectins function as pattern recognition receptors in innate immunity through carbohydrate-binding mechanisms. However, mechanistic evidence detailing intracellular signaling cascades (e.g., MAPK/NF-κB/JAK-STAT activation linked to defined cytokine outputs) remains taxonomically uneven. Bivalve mollusks—particularly the Mytilectin family—represent the most extensively characterized group, whereas lectins from other marine phyla (echinoderms, cnidarians, fish, algae) have been studied primarily for structural and glycan-binding properties alongside phenotypic antimicrobial outcomes. Signaling-level resolution in native immune-cell contexts, while present in some cases, remains comparatively limited. This review synthesizes mechanistic insights dominated by bivalve-derived lectins, while integrating cross-taxa comparisons at evidence-supported levels. Specific bivalve lectins induce macrophage activation and pro-inflammatory cytokine production through reactive oxygen species-dependent activation of key signaling pathways including MAPK, NF-κB, and JAK-STAT cascades. These lectins exhibit context-dependent properties, promoting inflammatory responses in resting cells while inducing endotoxin tolerance in pre-activated macrophages through epigenetic reprogramming. Functional outcomes include broad-spectrum antiviral activity through viral envelope glycoprotein binding, anti-inflammatory effects in pain models, and cancer-associated immune responses through tumor glycan recognition and macrophage polarization. Critical gaps include uncharacterized effects on adaptive immunity, limited understanding of dendritic cell and natural killer cell interactions, and incomplete evaluation of cancer immunotherapy potential. Future research should prioritize mechanistic characterization of marine lectin-based immunotherapeutics. Full article

Recent genomic phylogenies have generated new robust classifications of actinopterygian fishes, making possible greater nomenclatural stability, but genus-level classifications of groups like the diverse catfish subfamily Trichomycterinae are still unclear, containing ill-defined paraphyletic taxa. The focus of the present study is the Trichomycterus Lineage (TL), a clade with great morphological diversity, containing about 170 species widely distributed in South America, occurring in the most important biodiversity hotspots of the world, such as the Atlantic Forest, Cerrado, and the Tropical Andes. Most species are small, but at least one reaches about 400 mm of total length, being used as food and depicted in pre-Hispanic Andean ceramics. Based on a comparative morphological analysis, mainly using osteological characters, supported by concordant genomic phylogenies, a new classification at the genus level is here provided. Many morphological features delimiting TL genera seem to be related to ecological adaptations. Nine genera are here recognised of which five are new. Recognition of the new genera will allow easier descriptions of new species and consequently better biodiversity estimates. Full article

China possesses abundant marine fishery resources, which play a vital role in the national economy. Achieving rapid and high-precision classification of underwater targets in complex aquatic environments is of significant importance for enhancing aquaculture intelligence and operational efficiency. To address the challenges of insufficient feature extraction and inefficient classifier parameter optimization in underwater image classification, this study proposes a classification method integrating local binary patterns (LBP), kernel principal component analysis (KPCA), and an improved sparrow search algorithm (SSA). The method first extracts image texture features using LBP and then applies KPCA for nonlinear dimensionality reduction. Subsequently, three optimization strategies—dynamic weighting, boundary contraction, and adaptive mutation—are introduced to enhance SSA, which is then employed to optimize the core parameters of the Support Vector Machine (SVM). Experiments were conducted on an underwater image dataset containing four types of targets: sea urchins, fish, rocks, and scallops. The results demonstrate that, compared with the traditional KPCA-SVM method, the integration of LBP features and the improved SSA increases classification accuracy from 55% to 94.37%, validating the effectiveness of the proposed approach in extracting underwater image features and optimizing classifier parameters. This provides technical support for improving the feasibility of automatic underwater target recognition in aquaculture applications. Full article

Background and Clinical Significance: Plasmablastic lymphoma (PBL) is a rare and highly aggressive B-cell neoplasm most often associated with immunodeficiency. Transformation of chronic lymphocytic leukemia/small lymphocytic lymphoma (CLL/SLL) into PBL is exceptionally uncommon, particularly in immunocompetent individuals. This paper describes a rare synchronous SLL-to-PBL transformation and summarizes current knowledge on synchronous and metachronous cases reported in the literature. Case Presentation A midle-aged immunocompetent patent presented with generalized lymphadenopathy and lumbar pain. Concurrent biopsies of an axillary lymph node and a retroperitoneal mass were obtained. Diagnostic evaluation included immunohistochemistry; fluorescent in situ hybridization (FISH); PCR-based assessment of IGH, IGK, and IGL loci; and next-generation sequencing (NGS) of IGHV to assess clonal relatedness. The patient was treated with six cycles of Dara-CHOP, followed by autologous stem cell transplantation and maintenance therapy with daratumumab and ibrutinib. The axillary node showed SLL (CD20+, CD5+, CD23+), while the retroperitoneal mass demonstrated classic features of PBL (CD138+, MUM1+, MYC+, Ki-67 ~100%, CD20−). FISH detected MYC rearrangement in the PBL component. PCR and NGS confirmed identical IGHV1-69 rearrangements, establishing clonal relatedness and Richter transformation. A review of published cases shows that both synchronous and metachronous CLL/SLL-to-PBL transformations are exceedingly rare. The patient achieved partial metabolic remission after treatment and remains in sustained metabolic response 24 months after diagnosis. Conclusions: This case highlights a rare example of synchronous CLL/SLL-to-PBL transformation in an immunocompetent patient. Integration of detailed molecular diagnostics enabled early recognition and guided a personalized treatment approach incorporating CD38-targeted therapy and BTK inhibition, resulting in an excellent long-term clinical outcome. Full article

Accurate feeding-state monitoring is essential for improving feeding management, reducing feed waste, and supporting water quality and fish welfare in aquaculture. However, existing vision-based methods often rely on subjective labels or computationally expensive temporal models, which limits practical on-farm deployment. Here, we propose an objective, edge-deployable framework for motion-driven feeding-state quantification and binary feeding/non-feeding recognition from top-view videos. The framework integrates frame-pair dense optical-flow encoding with a lightweight network (EfficientFeedingNet) to enable real-time deployment. Using an optical-flow-derived motion-intensity signal (V-Value), we automatically delineate feeding-response intervals and construct a perception-based dataset (Perceptual Dataset) with reproducible binary labels, alongside an observer-labeled Intuitive Dataset. Across representative backbones, models trained on the Perceptual Dataset achieve >90% test accuracy and improve over the Intuitive Dataset by 13.13–18.46 percentage points. The proposed EfficientFeedingNet attains 96.53% test accuracy while remaining lightweight for edge deployment; on a Jetson Orin NX, it runs at 7.0 ms per image (143.24 fps). Overall, the proposed framework provides a practical basis for timely, data-driven feeding decisions in precision aquaculture. Full article

Reproductive dysfunction in captive-bred Senegalese sole (Solea senegalensis) limits aquaculture production consolidation, particularly due to reduced fertility and poor sperm quality in F1 males. To elucidate the molecular mechanisms underlying this problem, a quantitative proteomic analysis was conducted using LC–MS/MS on gonadal tissues from wild and F1 males and females. A total of 2221 proteins were identified, of which 1797 were retained after quality filtering. Comparative analyses revealed clear segregation by origin (F1 [cultivated] and wild) and sex (male and female), and 86 proteins were differentially expressed between F1 and wild males. Functional enrichment showed significant downregulation of key reproductive processes in F1 males, including sperm–egg recognition, binding of sperm to zona pellucida, and acrosome reaction, suggesting impaired gamete interaction and fertilization ability. Conversely, F1 males displayed metabolic and proteolytic pathway enrichment, which is indicative of compensatory energy demands. Protein–protein interaction network analysis identified a reproductive subnetwork dominated by zona pellucida sperm-binding proteins, which exhibited reduced connectivity in F1 males. These results demonstrate a coordinated suppression of molecular components essential for sperm–egg communication and acrosomal exocytosis, providing proteomic evidence for the systemic deregulation of the reproductive machinery in F1 fish. This study identifies potential protein biomarkers linked to reproductive performance, offering molecular targets to improve broodstock management and fertilization success in S. senegalensis aquaculture. Full article

In response to the challenges of target recognition and misjudgment caused by varying target scales, diverse shapes, and interference such as lake surface reflections in river and lake scenarios, this paper proposes the YOLO v11n-DDH model for fast and detection of spatial targets in river and lake environments. The model builds upon YOLO v11n by introducing the Dynamic Snake Convolution (DySnakeConv) to enhance the ability to extract detailed features. It integrates the Deformable Attention Mechanism (DAttention) to strengthen key features and suppress noise, while combining the improved High-Level Screening Feature Pyramid Network (HSFPN) structure for multi-level feature fusion, thus improving the semantic representation of targets at different scales. Experiments on a self-constructed dataset show that the precision, recall, and mAP of the YOLO v11n-DDH model reached 88.4%, 78.9%, and 83.9%, respectively, with improvements of 3.4, 2.9, and 2.5 percentage points over the original model. Specifically, DySnakeConv increased mAP@50 by 0.6 percentage points, DAttention improved mAP@50 by 0.3 percentage points, and HSFPN contributed to a 0.9 percentage point rise in mAP@50. This patrol system can effectively identify and visualize various pollutants in river and lake areas, such as underwater waste, water quality pollution, illegal swimming and fishing, and the “Four Chaos” issues, providing technical support for intelligent river and lake management. Full article

Food waste remains a global challenge, particularly among younger generations. This study examines the attitudes and behaviours of 330 Generation Z individuals (aged 18–24 years) from Italy, Estonia, Croatia, Romania, and Serbia using an extended Theory of Planned Behaviour (TPB). The TPB model was expanded to include moral social values, awareness of health risks, and good provider identity. A mixed-methods approach was applied, combining 7-day food waste diaries, visual plate-waste analysis, and self-administered questionnaires. Food recognition analysis showed that Estonian participants wasted less food per meal (3.43%) than those from Italy, Serbia, Croatia, and Romania (12.53%, 12.57%, 14.53%, and 17.18%). Nationality-specific patterns emerged: Romanians mainly discarded meat and potatoes, while participants from Estonia, Croatia, and Serbia wasted fruit and vegetables; Italians most frequently wasted fish and dairy. The extended TPB effectively predicted intentions to reduce food waste, identifying key behavioural determinants that can inform targeted interventions for young consumers. Full article

This study presents SEAF-Net, a lightweight and efficient detection network designed for low-contrast and highly dynamic underwater environments. Built upon YOLOv11n, SEAF-Net introduces three complementary structural enhancements: (1) Omni-Dimensional Dynamic Convolution (ODConv) to improve adaptive modeling of multi-scale and directional texture variations; (2) SimA-SPPF, which embeds the SimAM attention mechanism into the SPPF module to enable neuron-level saliency reweighting and effective suppression of complex background interference; and (3) GhostC3k2 to reduce redundant computation while preserving sufficient representational capacity. Evaluated on a standardized 13-class underwater fish dataset under a unified training and evaluation protocol, SEAF-Net achieves 6.1 GFLOPs, 92.683% Precision, 88.459% Recall, 93.333% mAP50, 73.445% mAP, and a 90.522% F1-score. Compared with the YOLOv11n baseline, SEAF-Net improves F1-score and Recall by 0.510% and 0.575%, respectively, while reducing computational cost by approximately 6%, demonstrating a favorable accuracy–efficiency trade-off under lightweight constraints. Ablation results further confirm that SimA-SPPF plays a dominant role in background suppression, ODConv consistently enhances deformation and directional texture modeling, and GhostC3k2 effectively controls computational overhead without degrading detection accuracy. To assess deployment feasibility, additional test set evaluations were conducted under deployment-oriented conditions using resource-limited hardware, yielding an F1-score of 88.54%. This result confirms that the proposed model maintains stable detection performance and robustness beyond training and validation stages. Overall, SEAF-Net provides an effective balance of accuracy, efficiency, and robustness, offering practical support for low-carbon, scalable, and sustainable intelligent aquaculture monitoring and underwater ecological assessment in real-world environments. Full article

This study investigates the genomic basis of immune adaptation in the transparent glass catfish (Kv: Kryptopterus vitreolus), focusing on the loss of the Toll-like receptor 21 (TLR21) gene. Comparative genomic analysis with closely related non-transparent North African catfish (Cg: Clarias gariepinus) revealed 11 TLR genes in the latter, while only 8 TLR genes (KvTLR1, 2, 3, 5, 7, 9, 13, and 20) were retained in the glass catfish, with TLR21 specifically absent. Collinearity analysis confirmed that the genomic region containing TLR21 is conserved across eight siluriform species, with loss exclusively in the glass catfish, supporting its lineage-specific absence. Structural expansion was notable in KvTLR5, KvTLR7, and KvTLR20. Molecular docking indicated that binding stability between CpG oligonucleotides and TLR21 varies significantly, with CpG-B 1681 showing the strongest interaction, which highlights sequence-dependent ligand recognition. Interestingly, absence of the TLR1 gene in another transparent teleost, the X-ray tetra (Pristella maxillaris), suggests that transparent fishes may share an evolutionary trend of lineage-specific TLR gene loss. Together, these findings reveal a distinctive evolutionary trajectory in the innate immune receptor family of transparent fishes and provide new molecular insights into their adaptive immune strategies. These insights will benefit the academic community by improving comparative frameworks for fish innate immunity, and they may inform disease prevention and health management strategies in aquaculture and the ornamental fish trade. Full article

In aquaculture production, manual or fixed-schedule feeding often fails to match the real-time feeding level of fish schools, and overfeeding can lead to feed wastage and water-quality deterioration, which has become a major bottleneck for both large-scale farming efficiency and environmental sustainability. During feeding, intense competition and jumping behaviors generate splashes of varying magnitudes, which can serve as an indirect visual proxy for hunger intensity. In this study, we constructed a frame-level splash-annotated dataset and performed data preprocessing. Building upon YOLO11 pretrained weights, we introduced a P2–P5 four-scale detection head to enhance small-splash recognition, injected EGMA into the backbone C3k2 blocks, and replaced stride-2 downsampling convolutions with a three-branch ADown operator. On the validation set, the proposed YOLO11-PEGA achieved a precision of 0.86 and a recall of 0.80, with mAP@0.5 exceeding 0.80 and mAP@0.5–0.95 exceeding 0.30. Compared with the baseline model, the parameter count was reduced by 72.3%. The results demonstrate that the proposed model maintains stable detection and evaluation performance under complex environmental conditions, providing actionable decision support for feeding-threshold setting, feeding-time determination, and feed-amount adjustment. Full article

Several studies have demonstrated that methionine supplementation in fish diets enhances immune status, inflammatory response, and resistance to bacterial infections by modulating for DNA methylation, aminopropylation, and transsulfuration pathways. However, the immunomodulatory effects of methionine in viral infections remain unexplored. This study aimed to evaluate the effect of methionine supplementation on immune modulation and resistance to the viral haemorrhagic septicaemia virus (VHSV) in rainbow trout (Oncorhynchus mykiss). Two diets were formulated and fed to juvenile rainbow trout for four weeks: a control diet (CTRL) with all nutritional requirements, including the amino acid profile required for the species, and a methionine-supplemented diet (MET), containing twice the normal requirement of DL-methionine. After feeding, fish were bath-infected with VHSV, while control fish were exposed to a virus-free bath. Samples were collected at 0 (after feeding trial), 24, 72, and 120 h post-infection for the haematological profile, humoral immune response, oxidative stress, viral load, RNAseq, and gene expression analysis. In both diets, results showed a peak in viral activity at 72 h, followed by a reduction in viral load at 120 h, indicating immune recovery. During the peak of infection, leukocytes, thrombocytes, and monocytes migrated to the infection site, while oxidative stress biomarkers (superoxide dismutase glutathione S-transferase, and glutathione redox ratio) suggested a compromised ability to manage cellular imbalance due to intense viral activity. At 120 h, immune recovery and homeostasis were observed due to an increase in the amount of nitric oxide, GSH/GSSG levels, leukocyte replacement, monocyte influx, and a reduction in the viral load. When focusing on the infection peak, gene ontology (GO) analysis showed several exclusively enriched pathways in the skin and gills of MET-fed fish, driven by the upregulation of several key genes. Genes involved in recognition/signalling, inflammatory response, and other genes with direct antiviral activity, such as TLR3, MYD88, TRAF2, NF-κB, STING, IRF3, -7, VIG1, caspases, cathepsins, and TNF, were observed. Notably, VIG1 (viperin), a key antiviral protein, was significantly upregulated in gills, confirming the modulatory role of methionine in inducing its transcription. Viperin, which harbours an S-adenosyl-L-methionine (SAM) radical domain, is directly related to methionine biosynthesis and plays a critical role in the innate immune response to VHSV infection in rainbow trout. In summary, this study suggests that dietary methionine supplementation can enhance a more robust fish immune response to viral infections, with viperin as a crucial mediator. The improved antiviral readiness observed in MET-fed fish underscores the potential of targeted nutritional adjustments to sustain fish health and welfare in aquaculture. Full article

AI enhances aquatic resource management by automating species detection, optimizing feed, forecasting water quality, protecting species interactions, and strengthening the detection of illegal, unreported, and unregulated fishing activities. However, these advancements are inconsistently employed, subject to domain shifts, limited by the availability of labeled data, and poorly benchmarked across operational contexts. Recent developments in technology and applications in fisheries genetics and monitoring, precision aquaculture, management, and sensing infrastructure are summarized in this paper. We studied automated species recognition, genomic trait inference, environmental DNA metabarcoding, acoustic analysis, and trait-based population modeling in fisheries genetics and monitoring. We used digital-twin frameworks for supervised learning in feed optimization, reinforcement learning for water quality control, vision-based welfare monitoring, and harvest forecasting in aquaculture. We explored automatic identification system trajectory analysis for illicit fishing detection, global effort mapping, electronic bycatch monitoring, protected species tracking, and multi-sensor vessel surveillance in fisheries management. Acoustic echogram automation, convolutional neural network-based fish detection, edge-computing architectures, and marine-domain foundation models are foundational developments in sensing infrastructure. Implementation challenges include performance degradation across habitat and seasonal transitions, insufficient standardized multi-region datasets for rare and protected taxa, inadequate incorporation of model uncertainty into management decisions, and structural inequalities in data access and technology adoption among smallholder producers. Standardized multi-region benchmarks with rare-taxa coverage, calibrated uncertainty quantification in assessment and control systems, domain-robust energy-efficient algorithms, and privacy-preserving data partnerships are our priorities. These integrated priorities enable transition from experimental prototypes to a reliable, collaborative infrastructure for sustainable wild capture and farmed aquatic systems. Full article

Fishes are frequently exposed to hypoxic stress, yet their tolerance to hypoxia varies significantly among species. The association between this variation and alterations in the hypoxia-inducible factor (HIF) pathway remains unclear. We discovered that otomorphs generally retain two Hif-1α paralogs (Hif-1αa and Hif-1αb), resulting from the teleost-specific genome duplication (TGD), whereas most euteleosts possess only a single Hif-1αa copy. In otomorphs, key mutations disrupt one conserved Leu-X-X-Leu-Ala-Pro (LXXLAP) motif in the oxygen-dependent degradation (ODD) domain of the Hif-1αa proteins. Molecular dynamics simulations revealed that these mutations impede the recognition of the critical proline residue by prolyl hydroxylase domain protein 2 (PHD2), suggesting enhanced normoxic stability of Hif-1αa. We also investigated the expression profiles of hif-1α and downstream genes in four fish species (two otomorphs and two euteleosts). In otomorphs, the hif-1αa genes were highly expressed specifically in the heart; concomitantly, two critical downstream genes, ldha and mct4, exhibited relatively high expression levels in vital tissues such as the heart, brain, and muscle. This coordinated expression pattern promotes a heightened glycolytic capacity and facilitates lactate shuttling in these tissues, thereby ensuring energy supply during hypoxic stress. Our integrated computational analyses indicate that otomorphs achieve enhanced hypoxia tolerance through the subfunctionalization of Hif-1α paralogs. Full article