Search Results (572)

In this study, pathogenic bacteria were isolated from diseased Pelteobagrus fulvidraco collected from a yellow catfish farm in northern China. The recovered isolate was subjected to Gram staining, transmission electron microscopy observation, 16S rRNA gene sequencing and whole-genome sequencing, followed by systematic analyses of its antimicrobial resistance, pathogenicity and genomic characteristics. Combined with artificial infection assays and multiple comparative verifications, the pathogen was identified as Vibrio mimicus. Clinical observation of naturally infected fish revealed that superficial skin ulcers of varying severity constituted the hallmark clinical sign of this disease. Genomic analysis uncovered major virulence-related genes, including tlh, vmh and tdh, as well as key antimicrobial resistance genes such as crp and ugd. Artificial infection trials confirmed the strong virulence of this isolate against P. fulvidraco, with distinct clinical manifestations triggered by injections of bacterial suspensions at different concentrations. Mortality was first observed in the high-dose group at 2–3 days post-injection, yet no cutaneous ulceration was detected at this stage. The peak incidence and mortality occurred between 3 and 7 days post-challenge, with diseased fish exhibiting lesions identical to those seen in naturally infected individuals. The median lethal dose (LD₅₀) of the isolate was determined to be 1.72 × 10⁵ CFU/mL. Growth gradient assays across varying temperatures and pH values identified the optimal culture conditions for this strain: 33 °C and pH 8.5. Antimicrobial susceptibility testing demonstrated that the isolate was highly susceptible to piperacillin, norfloxacin, roxithromycin, azithromycin, furazolidone, ceftriaxone and tetracycline, whereas it displayed high-level resistance to compound sulfamethoxazole and clindamycin. Collectively, this work lays a scientific foundation for the isolation, identification and comprehensive research of Vibrio mimicus-induced ulcerative disease in yellow catfish. Full article

Background: Skin cancer encompasses a diverse range of malignancies and remains a significant global health challenge. Accurate machine-learning-assisted diagnosis can substantially improve patient outcomes through early detection and timely clinical intervention. Federated Learning (FL) enables privacy-preserving collaborative model training across multiple healthcare institutions while ensuring that sensitive patient data remain decentralized. However, deploying advanced architectures such as Vision Transformers (ViTs) in clinical environments is challenging due to the high computational demands of self-attention mechanisms. Methods: This work proposes FedSwin-LHTP, an efficient federated learning framework for skin lesion classification that integrates a Swin Transformer backbone with a Lightweight Hessian-Inspired Token Pruning (LHTP) mechanism. LHTP estimates token importance using a second-order Taylor approximation around converged local model parameters to identify less informative patch tokens, enabling the early pruning of redundant representations without explicitly computing the Hessian matrix. Furthermore, the framework incorporates the FedProx optimization objective to mitigate client drift under heterogeneous non-IID data distributions. The proposed framework is evaluated on the HAM10000 and ISIC datasets under realistic non-IID federated settings. Results: Experimental results demonstrate stable convergence, effective knowledge aggregation, and robust diagnostic discrimination across distributed clients. By adaptively pruning approximately 60% of Stage-1 tokens, the proposed framework substantially reduces the computational burden of local transformer processing while maintaining high multiclass classification performance, achieving an accuracy of up to 96.1% on the evaluated datasets. Conclusions: These results highlight the potential of FedSwin-LHTP as a practical, privacy-preserving, and resource-efficient solution for collaborative healthcare intelligence. Full article

This case report describes the investigation of two cases of cutaneous vasculitis in sows following vaccination. The herd was porcine reproductive and respiratory syndrome virus (PRRSV)-stable, with routine PRRSV-1 and porcine circovirus type 2 (PCV2) sows’ vaccination. Two sows developed red-to-purple macules on the udder, flanks, and hind limbs, occurring two and three days after vaccination, respectively. Diagnostic investigations included biochemistry, complete blood count, PCR, immunohistochemistry (IHC), serology, histopathology, Gram staining, and immunofluorescence (IF) to assess the involvement of type III hypersensitivity. Clinical examination and herd evaluation revealed no significant abnormalities. Both sows showed biochemistry results within the reference intervals. One sow had lymphocytosis. All PCR PCV2, PCV3 and PRRSV-1/2 on serum and IHC PCV2 conducted on skin biopsies were negative, although both animals were seropositive for PCV2. Histopathology revealed necrotizing leukocytoclastic vasculitis, and Gram staining detected no bacteria. IF failed to identify immune complex or complement deposition. However, type III hypersensitivity could not be excluded, as immune complexes are transient and biopsies were collected about 48 h after lesion onset. Overall, the findings support a vaccine-related adverse reaction. Vaccine adverse effects should therefore be considered in the differential diagnosis of cutaneous vasculitis in swine. Full article

Incontinentia pigmenti (IP) is a rare, X-linked dominant genodermatosis caused by mutations in the IKBKG gene and characterized by sequential cutaneous stages following the lines of Blaschko. The highly inflammatory initial vesiculobullous stage frequently mimics severe neonatal infections, such as herpes simplex or bullous impetigo, leading to potentially dangerous diagnostic delays and unnecessary antimicrobial therapies. The objective of this report is to highlight the utility of multimodal medical imaging and clinico-pathologic correlation in the rapid diagnosis of early-stage IP. We present the case of a full-term female neonate presenting on the third day of life with a rapidly disseminating blistering eruption, initially treated as a widespread infectious process. A multimodal diagnostic approach was applied, incorporating bedside clinico-dermoscopic evaluation of the infant and her mother (who reported a history of early miscarriages), followed by neonatal skin biopsy, immunohistochemistry (S-100, MART-1), and subsequent genetic testing. Dermoscopy of the neonate’s transitional lesions revealed early dermal melanophage accumulation, while maternal evaluation exposed pathognomonic residual Blaschko-linear dyspigmentation featuring a distinct “pepper-like” dermoscopic pattern. Histopathology demonstrated classic eosinophilic spongiosis, intraepidermal vesicles, and early pigment incontinence. Genetic testing confirmed recurrent IKBKG exon 4–10 deletion. Crucially, this rapid diagnosis facilitated immediate targeted ophthalmologic screening, detecting asymptomatic stage 2B retinal vasculopathy. Integrating noninvasive dermoscopy with precise histopathologic correlation offers a rapid, highly effective framework to distinguish early IP from neonatal blistering infections. Timely multimodal imaging is crucial for triggering immediate multidisciplinary screening, effectively preventing severe, irreversible vision-threatening complications. Full article

In traditional Chinese medicine, frankincense is widely recognized for its anti-inflammatory and immunomodulatory capacities and has been conventionally applied to manage multiple chronic inflammatory skin disorders. Nevertheless, its therapeutic potency and molecular mechanisms against atopic dermatitis (AD) remain poorly clarified. This study aimed to explore the protective efficacy of frankincense oil extract (FOE) and its active constituents in AD mouse models, thereby clarifying underlying regulatory mechanisms. Two classic AD models induced by 2,4-dinitrochlorobenzene (DNCB) and carvacrol were established to evaluate the therapeutic performance of FOE and its bioactive components. Hematoxylin–eosin and toluidine blue staining were applied to characterize lesional histopathological alterations, immunohistochemistry was used to detect expression profiles of TRPV3, β-catenin, and COX-2 in skin lesions, and calcium fluorescence imaging was applied to monitor TRPV3-mediated intracellular calcium dynamics. The results showed that FOE markedly alleviated typical AD-like manifestations, reducing inflammatory injury, ear edema and splenomegaly in DNCB- and carvacrol-challenged mice. Histological evaluation confirmed that FOE improved pathological lesions, mitigated epidermal hyperplasia, and reduced mast cell infiltration. Meanwhile, FOE remodeled the abnormal expression patterns of TRPV3, β-catenin, and COX-2 triggered by AD stimulation. Additionally, FOE effectively regulated carvacrol-evoked calcium influx mediated by TRPV3 activation. Collectively, FOE and its active components exert anti-inflammatory effects, restraining epidermal over-proliferation and ameliorating epidermal structural disorders, thereby supporting the restoration of epidermal tissue morphology. Such benefits are attributed to modulating TRPV3 activity and remodeling the cutaneous inflammatory microenvironment. This work highlights FOE as a promising novel candidate for atopic dermatitis intervention. Full article

Background/Objectives: Cutaneous squamous cell carcinoma (cSCC) is the second most common non-melanoma skin cancer (NMSC) and represents the leading cause of NMSC-related deaths. Despite its growing global burden, comprehensive epidemiological and clinicopathological data from Easter Europe remains limited. This study aimed to evaluate the epidemiological, clinical, histopathological, and surgical characteristics of cSCC diagnosed before, during and after the COVID-19 pandemic. Methods: We conducted a retrospective, descriptive observational study including 332 lesions diagnosed between January 2017 and December 2025 at the Clinical Pathology Department of the Mureș Clinical County Hospital. Demographic, epidemiological, topographic, histopathologic, surgical, and volumetric parameters were analyzed. Tumours were stratified into low-, high-, and very-high-risk categories according to the National Comprehensive Cancer Network (NCCN) criteria. Results: The cohort demonstrated a significant male predominance (n = 193 vs. n = 139; p = 0.0355), with females presenting a higher median age (77 vs. 75; p = 0.0489). Lesions were predominantly located in the head and neck region (n = 216; p < 0.0001), which was significantly associated with very-high-risk tumours (p = 0.0051). Low-risk tumours accounted for 62.35% of cases, while high-risk and very-high-risk lesions comprised 19.88% and 17.77%, respectively (p < 0.0001). Ulcerations were strongly associated with very-high-risk tumours (p < 0.0001). Poor differentiation was more frequent outside the head and neck region (p < 0.0001) and varied significantly across the pandemic periods (p = 0.0349). Tumoral and excision volumes were higher in very-high-risk (p = 0.0070; p = 0.0004) and ulcerated tumours (p < 0.001), with a peak in volume during the COVID-19 period (p < 0.0001). A decrease through the years of diagnosis was observed in tumoral volumes (r = −0.2295; p < 0.0001) and patients showed a weak positive correlation with diagnosis year (r = +0.13; p = 0.019). Conclusions: The study provides an epidemiological and clinicopathological characterization of cSCC within one of the largest Romanian cohorts to date. Tumour aggressiveness was primarily driven by histopathological and topographical features rather than demographic factors. While the COVID-19 pandemic did not induce persistent changes in tumour risk profiles or surgical outcomes, it influenced diagnosis timing and tumour burden. These findings highlight the importance of incorporating temporal and emerging systemic factors, such as pandemics, and infectious events, into future epidemiological models to improve preparedness, early detection, future treatment schemes, and risk stratification in cSCC. Full article

Citrobacter freundii, an opportunistic Gram-negative bacterium belonging to the Enterobacteriaceae family, is emerging as a significant pathogen in diverse aquatic species, often associated with environmental stress and poor husbandry conditions. This study describes four distinct cases of fatal C. freundii-associated lesions in captive freshwater species in South Korea, including an Ocellate river stingray (Potamotrygon motoro), a Royal peacock bass (Cichla intermedia), a Japanese eel (Anguilla japonica), and a Poison dart frog (Dendrobates leucomelas). Bacterial DNA was analyzed using 16S rRNA PCR and sequence analysis, and FFPE tissues were additionally examined by PCR for molecular identification. Tissues were examined using routine hematoxylin and eosin (H&E) staining for detailed histopathology. Results: Molecular analysis detected C. freundii-associated DNA in the liver, kidney, and intestine of all samples. Histopathology consistently revealed severe bacterial enteritis with epithelial necrosis and abundant intraluminal bacterial aggregates (stingray, frog). Systemic manifestations included severe ulcerative skin lesions (peacock bass), hepatic fatty degeneration (peacock bass, eel), renal tubular degeneration (peacock bass), and prominent hepatic melanomacrophage center activation (frog); however, these findings should be interpreted as lesions observed in association with C. freundii detection, as several of these changes are not specific to bacterial infection. To our knowledge, this study provides one of the first comparative histopathological descriptions of naturally occurring C. freundii-associated cases across multiple captive freshwater vertebrate species in South Korea. Although bacterial culture, biochemical identification, and experimental infection were not performed, this retrospective investigation identified an association between molecular detection of C. freundii and histopathological lesions. Therefore, these findings should be interpreted as supportive diagnostic evidence rather than proof of a definitive causal relationship. These observations highlight the complementary value of histopathological examination alongside molecular detection in the diagnostic evaluation of aquatic animal diseases. Full article

Ectoparasites cause skin lesions, anemia, and mortality in wild animals and act as vectors of zoonotic pathogens. This study reports ectoparasites detected during an opportunistic survey on wild mammals admitted to the Van Yuzuncu Yil University Wildlife Protection and Rehabilitation Center in eastern Türkiye during 2024–2025. Due to the opportunistic nature of sampling, the findings primarily reflect parasite burdens in injured or debilitated individuals and may not be representative of healthy free-ranging populations. Of the 28 animals examined, 20 (71.4%) were infested. A total of 449 ectoparasites were collected: 370 fleas (82.4%), 58 ticks (12.9%), and 21 lice (4.7%). Identified species included four fleas (Paraceras melis, Chaetopsylla globiceps, Pulex irritans, Archaeopsylla erinacei), four ticks (Ixodes kaiseri, Rhipicephalus turanicus, Haemaphysalis parva, Haemaphysalis erinacei), and one louse (Trichodectes melis). This study provides new host–ectoparasite association records for Türkiye: I. kaiseri and R. turanicus on beech marten (Martes foina); I. kaiseri and C. globiceps on Eurasian badger (Meles meles); and P. irritans on Eurasian lynx (Lynx lynx) and brown bear (Ursus arctos). Bipartite network analysis revealed moderate specialization (H2’ = 0.52) and marked variation in host specificity, with T. melis, A. erinacei, and P. melis showing high host specificity (d’ > 0.85), whereas Chaetopsylla globiceps and Pulex irritans acted as generalists (d’ < 0.30). Some identified ectoparasites are known or suspected vectors of zoonotic pathogens. These findings provide baseline data for future research on wildlife health and disease transmission risks in the region. Full article

Background/Objectives: Automated dermoscopic image analysis can assist research on early skin cancer detection, but deep learning models may learn acquisition-related shortcuts, including terminal hairs, illumination gradients, gel bubbles, shadows and measurement markings. This study evaluates a causal uncertainty-decomposed ensemble (CUDE) for confounding-aware skin-lesion classification within the ISIC 2019 benchmark setting. Methods: CUDE uses a structured variational autoencoder (SVAE) to impose separate lesion-relevant and acquisition-related nuisance latent heads. Three stochastic latent-space experts are trained on complementary streams and are integrated by a Dirichlet-based fusion module trained with nuisance sampling. The causal graph is used as a modeling prior rather than proof of causal identification. Results: Using a stratified internal split of the labeled ISIC 2019 training collection, CUDE achieved a balanced accuracy of 89.7% and an AUROC of 0.972. Under the predefined synthetic artifact protocol, CUDE showed a relative performance drop of 5.0%, compared with 9.6% for the deep ensemble. Deferring the 10% most uncertain cases increased non-deferred accuracy from 89.7% to 93.2% and reduced false-negative rates for melanoma, BCC and SCC in the non-deferred subset. Conclusions: Within the evaluated ISIC 2019 split and controlled synthetic corruption protocol, structured latent separation, stochastic expert diversity and Dirichlet fusion were associated with improved benchmark robustness and calibration. These results should not be interpreted as evidence of broad real-world robustness or clinical deployment readiness; external multi-center, device-diverse and skin-tone-diverse validation remains required. Full article

Timely and accurate identification of fish diseases, along with the provision of corresponding treatment plans, is crucial for improving fish welfare and reducing economic losses in aquaculture facilities. To address issues such as low detection efficiency and excessive reliance on manual experience in aquaculture, this paper proposes an innovative diagnostic and treatment method based on the Octopus framework for model optimization. The CBAM (Convolutional Block Attention Module) attention mechanism is introduced into the YOLOv11n backbone to enhance feature extraction, while the Focus-CIoU (Focus-Complete Intersection over Union) loss function is adopted to improve the detection performance for small-target lesions and dense fish schools. Additionally, by integrating wireless sensor networks and the OTDA (Octopus-inspired Therapeutic Decision Agent) bionic agent, an integrated ‘detection-identification-perception-recommendation’ framework is constructed. The results showed that the optimized YOLOv11n model achieved a detection precision of 98.00%, a recall of 94.86%, and an F1 score of 96.40% in detecting ulcer disease, tail rot disease, and red skin disease. Furthermore, the mAP@50 was 97.58%, and the mAP@50–95 was 85.68%. Compared with the traditional YOLOv11n model, the optimized model achieved improvements of 1.39%, 1.48%, 1.43%, 1.4%, and 2.74% in precision, recall, F1 score, mAP@50, and mAP@50–95, respectively. The treatment recommendations produced by means of the Octopus bionic intelligent agent resulted in an average system response time of no more than 53 s, with the maximum observed response time not exceeding 60 s. The identification accuracy of OTDA remained above 87.1%. Full article

Members of the Genus Avipoxvirus have been reported in more than 374 avian species worldwide. Generally, poxviruses are considered to have a limited host range; however, canarypox-like viruses appear to infect a broader host range. In 2024, four juvenile common swifts in an age of 30 to 35 days from three different breeding sites of Lower Saxony, Germany, showed nodular, verrucous and crusted skin lesions of the wings, especially of the dorsal surface of the elbow and forearm region and the skin between the outer primary flight feathers. The skin on the head or the feet as well as the mucous membrane of the oral cavity was not affected. Two swifts of these cases had to be euthanized due to pox-related alterations of feather follicles of the primary flight feathers and associated feather growth disorders and loos. The other two swifts were released into the wild after recovery and successful hand-rearing. The diagnosis of a poxvirus infection is based in our cases on a combination of clinical examination, histology, transmission electron microscopy, and molecular biological investigations. The histological examination of skin lesions displayed severe heterophilic and histiocytic dermatitis with severe epithelial hyperplasia, mild orthokeratotic hyperkeratosis and cytoplasmic eosinophilic inclusion bodies (Bollinger’s inclusion bodies) within frequently swollen keratinocytes (ballooning degeneration). Using transmission electron microscopy, virions showing typical brick-shaped poxvirus morphology were visualized. Avipoxvirus-specific DNA was detected by PCR. The sequence analysis of the 176 bp amplicon revealed 100% identity to a canarypox virus and a shearwaterpox virus 2 strain. Herpesvirus- or papillomavirus-specific DNA was not detected by PCR. To our knowledge, this is the first report of an avipoxvirus infection in a swift species. Notably, in all swift cases, the disease was limited to the skin of the wings. The origin of the virus and its transmission to swifts are unknown. However, transmission from other wild birds via biting insects appears to be possible, as has been described for canarypox-like viruses. Full article

Detection of skin cancer has become an increasingly prevalent health issue for which there is a need for reliable methods of detection to improve patient outcomes, minimize delays in diagnosis, and ensure clinical referral. Advances in computer vision and artificial intelligence have allowed automatic analyses of dermoscopic, clinical, and smartphone imaging of skin lesions. While numerous models have been found to perform very well on the basis of curated benchmark datasets, their accuracy in practical settings still needs to be evaluated. This review critically evaluates the literature from 2015 to 2025. Rather than considering the Dice, Jaccard, AUC, sensitivity, and specificity metrics on an absolute basis, this review evaluates them relative to dataset quality, validation process, external testing, statistical analysis, and risk of bias. Key areas of focus include dataset imbalance, lack of coverage of darker skin, poor external validation, explainability, uncertainty quantification, and barriers to clinical adoption. This review provides valuable insights for researchers, practitioners, dataset producers, and healthcare providers involved in developing AI-enabled dermatology tools. Full article

Background/Objectives: Melanoma is a life-threatening skin cancer characterized by aggressive progression and high metastatic potential, making early diagnosis essential for improving patient survival and treatment outcomes. However, accurate automated skin lesion classification remains challenging due to variations in lesion appearance, illumination, image quality, and the presence of artifacts. This study proposes a unified framework for robust multi-class skin cancer classification by integrating preprocessing, lesion segmentation, feature extraction, optimization, and classification within a single end-to-end architecture. Methods: The proposed framework employs an iterative hair artifact removal strategy based on the fusion of Frangi vesselness filtering, Gabor texture filtering, morphological refinement, and Telea inpainting to preserve lesion integrity. A novel dermoscopic lesion segmentation network (CutisNet) is introduced to accurately delineate lesion boundaries. Hybrid representation learning combines deep features extracted using MobileNetV2 with uniquely selected handcrafted descriptors to capture complementary texture, structural, and contextual information. Gray Wolf Optimization is utilized for feature fusion and refinement, while a hybrid GNN–CNN classifier performs robust multi-class skin lesion classification. Results: Extensive experiments conducted on multiple benchmark dermoscopic datasets demonstrate the effectiveness and generalization capability of the proposed framework. The proposed model consistently outperformed existing state-of-the-art methods, achieving a maximum classification accuracy of 96.7% on the PH² dataset while maintaining competitive performance across other benchmark datasets. Conclusions: The proposed framework effectively integrates novel preprocessing, segmentation, hybrid feature representation, feature optimization, and classification strategies to improve the robustness and accuracy of automated skin cancer classification. These results demonstrate its potential to support reliable computer-aided diagnosis and assist clinicians in the early detection of skin cancer. Full article

Early detection of skin cancer significantly improves patient outcomes yet remains challenging due to the visual similarity of lesions and the need for clinical context. This paper proposes a novel Image-driven multimodal deep learning framework for automated skin cancer diagnosis integrating dermoscopic imaging sensors’ clinical metadata and biomedical knowledge graphs. Dermoscopic images acquired from optical skin imaging sensors undergo advanced signal processing including multi-scale CLAHE enhancement and artifact suppression. A YOLOv8-nano sensor-based lesion detector achieves 97.2% mAP@0.5 for region-of-interest extraction. The biomedical knowledge graph (26 nodes 86 edges) encodes dermatological domain knowledge into 32-dimensional disease embeddings. Clinical metadata (age gender anatomical site) is encoded via learned feature vectors. A cross-attention fusion mechanism integrates these multimodal sensor-derived signals. Evaluated on the HAM10000 dataset (10,015 images 7 classes), our full multimodal model achieves 91.35% accuracy outperforming image-only (86.96%) and image+metadata (88.45%) baselines. An ensemble reaches 92.78% state-of-the-art accuracy with significant improvements on challenging classes (BCC +6.0% melanoma +3.8%). Statistical significance is confirmed (p < 0.01 95% CI [90.7% 92.0%]). This work demonstrates that Image-based multimodal signal fusion with structured medical knowledge enhances both diagnostic accuracy and clinical interpretability. Full article

Background: Aorto–atrial fistula is a rare pathological communication associated with diagnostic difficulties, progressive hemodynamic consequences, and potential infective complications. Methods and Results: We present a 53-year-old woman with a long-standing congenital non-coronary sinus of Valsalva–to–right atrial fistula that had been followed for nine years under the working diagnosis of a Gerbode defect. The communication was first detected at the age of 44 years during pregnancy and was managed conservatively while the patient remained largely asymptomatic. At the age of 53 years, recurrent exertional dyspnea prompted definitive reassessment. Right heart catheterization demonstrated a hemodynamically significant left-to-right shunt at the right atrial level, with a pulmonary-to-systemic blood flow (Qp/Qs) ratio of 2.1. Intraoperatively, the communication was shown to originate immediately above the non-coronary cusp and drain into the right atrium, establishing the diagnosis of a congenital aorto–right atrial fistula. A granulomatous, windsock-like endocardial lesion was identified at its right atrial opening, and Staphylococcus capitis was isolated from surgically obtained tissue. Histopathology showed nonspecific regressive changes without specific features of active infective endocarditis. The fistula was closed with an autologous pericardial patch, and intravenous flucloxacillin was administered because of probable localized infective involvement. Conclusions: This case illustrates the diagnostic difficulty of distinguishing an aorto–atrial fistula from a Gerbode defect and supports careful multimodality evaluation of the anatomical origin and flow characteristics of intracardiac shunts. Persistent high-velocity flow may contribute to endocardial injury and create a substrate for subsequent bacterial colonization, although causality cannot be established from a single case. Isolation of a low-virulence skin commensal from pathological cardiac tissue should be interpreted in the complete clinical, operative, microbiological, and histopathological context rather than automatically classified as contamination. Full article