Swept-source OCT characterization of dengue retinopathy: Novel grading system and laminar linear retinal hyperreflectivity.

Differential distribution characteristics of heavy metal resistance genes and driving mechanisms of heavy metal speciation in river-lake system sediments.

Differential deformation characteristics and evolution of ultra-deep strike-slip faults in the Tarim craton, China

Hysteretic dissociation of methane hydrate and differential cationic response characteristics under alternating oscillating electric fields: A molecular dynamics study

Spectrum-efficacy and pharmacodynamics-pharmacokinetics correlation of multi-index constituents in Liangfu Dripping Pills in ethanol-induced acute gastric ulcer rats.

Metagenomic analysis of the gut microbiota in Cryptosporidium-infected Tibetan sheep.

Beijing’s urban development has moved from the era of expansion to renewal. The exploration of industrial spatial evolution laws aims to tackle the major theoretical and practical problems in Beijing’s high-quality urban development. Few studies have analyzed the spatial and temporal patterns of industrial spatial aggregation based on long time-series data and fine-grained spatial scale industrial data sets. Based on the multitype industry data set from 2006 to 2020, this study uses a spatial similarity model and a circle analysis method to deeply analyze the rule and circle differentiation characteristics of Beijing’s industrial dominant types and aggregation levels. The results show that (1) the spatial similarity index of Beijing industry increases, showing the general characteristics of the continuous enhancement of the degree of aggregation. There exists a high aggregation degree and an obvious aggregation trend within the service industry and a low aggregation degree between the service and manufacturing industries. (2) The spatial aggregation of producer and living services is always high, and the aggregation of public services or cultural and creative industries with other services increases significantly. (3) The differential distribution of spatial circles and the slow process of aggregation are the main reasons for the spatial separation of the service and manufacturing industries. (4) Beijing’s industrial spatial aggregation shows a significant ring pattern, and the dominant types and aggregation levels of industrial evolution vary in different circles. The research conclusions scientifically support the optimization of the capital’s spatial structure and its high-quality spatial development.

Dermatophytosis is an infectious skin disease caused by fungal organisms collectively known as dermatophytes. In cats, the most commonly isolated dermatophyte is Microsporum canis. Known predisposing factors include young age, long hair coat, lifestyle, warm geographical locations and Persian breed. The aim of this retrospective study was to evaluate the prevalence of dermatophytosis in cats of different breeds in a dermatological referral practice in Italy over a 9 year period, highlighting clinical and breed-related differential features. 1457 cats of different breeds, 54 of which were affected by dermatophytosis. Cases of feline dermatophytosis diagnosed between 1 January 2016 and 31 December 2024 were searched. Cases were included based on availability of signalment, clinical presentation and confirmation of diagnosis with positive microscopic examination of hair shafts and/or Wood's lamp examination and positive fungal culture. The prevalence of feline dermatophytosis in our sample was 3.7%, with M. canis identified in all cases. Dermatophytosis was more frequently diagnosed in Persian cats (14 of 66, 21.2%) and Persian-related breeds, including British shorthair (10 of 39, 25.6%), exotic shorthair (two of 22, 9.1%) and Scottish fold (two of 20, 10%). Among Domestic short hair (DSH) cats, the prevalence was 2.1%. Young age was a predisposing factor and in pure-bred kittens contagion most likely occurred at the breeder's facility. Pruritus was reported in 63% of the cats. The disease was frequently diagnosed in Persian cats and Persian-related breeds. Cats aged < 1 year are predisposed. Pruritus is common, regardless of the breed.

Major depressive disorder (MDD) is highly prevalent among adolescents, but its neurobiological mechanisms remain unclear. Neuroimaging studies have shown cortical abnormalities in MDD, and emerging evidence suggests that trace elements may impact brain structure. This study aimed to investigate the association between urinary element concentrations and cortical alterations in adolescent MDD. Structural magnetic resonance imaging (sMRI) was conducted on 190 adolescents with MDD and 123 healthy controls (HCs), measuring cortical volume, cortical thickness, and urinary metal concentrations. Partial correlation analyses examined the associations between differential elements and cortical features, while mediation analyses tested whether cortical changes mediated the effects of elements on symptom severity. Furthermore, nine supervised machine learning models were trained using differential cortical and element features, and model performance was evaluated using cross-validation and stacking ensembles. The results revealed significant reductions in cortical volume in the left lateral orbitofrontal cortex (LLOF), left medial orbitofrontal cortex (LMOF), left rostral middle frontal gyrus (LRMFG), and left frontal pole (LFP), as well as reduced cortical thickness in the right pars triangularis (RPTRI), right pars orbitalis (RPORB), and right medial orbitofrontal cortex (RMOF) in adolescents with MDD compared with HCs. Urinary copper (Cu) levels were negatively correlated with LFP volume and positively associated with both depressive and anxiety symptom severity. In machine learning classification, the stacking ensemble demonstrated the best overall performance, indicating the discriminative value of combined cortical and urinary element features in distinguishing adolescents with MDD from HCs. This study suggests that trace elements, particularly Cu, are linked to structural brain alterations and symptom severity in adolescent MDD. The integration of neuroimaging and element data enhances predictive modeling and offers new insights into the pathophysiology of MDD.

Macrophage reprogramming nodes for bone repair identified by single-cell and spatial omics.

Rhizosphere metabolites play a pivotal role in plant-soil-microbe interactions, yet the absence of standardised sampling method presents challenges for data comparability and a unified understanding of rhizochemistry dynamics. In this study, the rhizosphere metabolites of spring wheat (Triticum aestivum L.) were systematically evaluated using three commonly used sampling methods - rhizosphere soil extraction, hydroponic collection, and in situsampling. We assessed the differences in metabolite abundance, diversity, composition, and metabolic pathways among the three methods. The results revealed that rhizosphere soil extraction method is simple and repeatable, but it tends to underestimate the rare metabolic features compared to the other two methods. The hydroponic collection method offered a more comprehensive rhizochemical profile, however, it may not reflect the actual soil environment in which plants grow. The in situ method mostly captured the rhizochemical dynamics under natural conditions but was technically complex and less reproducible. Pathway enrichment of differential metabolic features showed a distinct pattern, with hydroponic emphasising plant-centric primary metabolism, and rhizosphere soil extraction and in situ methods reflecting pathways more associated with environmental interaction and ecological adaptation. Overall, our results highlight that the sampling methods significantly influences the abundance and composition of the detected rhizochemical profile, thus the rhizosphere metabolites sampling methods should be considered according to the experimental objectives of future research.

Inverted sinonasal papilloma (ISP) and respiratory epithelial adenomatoid hamartoma (REAH) are sinonasal lesions with overlapping clinical, radiographic, and histologic features, making accurate diagnosis challenging. ISP is a benign but aggressive tumor with a propensity for local destruction, recurrence, and malignant transformation, whereas REAH is a hamartomatous lesion often arising in the olfactory cleft. We present four patients with lesions initially suspected to be ISP based on intraoperative frozen section but ultimately diagnosed as REAH on permanent pathology. All patients had polypoid sinonasal masses, frequently involving or adjacent to the olfactory cleft. Intraoperative frozen sections were often inconclusive or favored ISP, reflecting the difficulty of distinguishing these entities. Histologic analysis revealed that epithelial thickness served as a key morphologic feature differentiating ISP from REAH, with REAH exhibiting ciliated glandular proliferation and ISP characterized by hyperplastic epithelium with features of columnar and squamous differentiation. These patients underscore the diagnostic pitfalls of small biopsies and frozen sections, and highlight the importance of permanent specimens and collaboration with experienced pathologists. Accurate differentiation is critical, as management strategies differ substantially: ISP requires aggressive resection and long-term surveillance, while REAH may be treated with limited excision and minimal follow-up.

Distinguishing erosions from non-inflammatory lesions in hand MRI: A quantitative morphological approach.

CSFeatures improves the identification of cell-type-specific differential features in single-cell and spatial omics data.

BackgroundLipedema is a chronic and progressive disorder of subcutaneous adipose tissue that predominantly affects women and is frequently misdiagnosed as obesity, lymphedema, or venous disease. Increasing evidence indicates that lipedema represents a systemic vascular-lymphatic-inflammatory disorder rather than a cosmetic or metabolic condition. Delayed diagnosis often results in progressive fibrosis, lymphatic dysfunction, chronic pain, and functional impairment.ObjectiveThis review aims to present a structured, clinically applicable framework for the diagnosis and multimodal management of lipedema within phlebology practice, with an emphasis on stage-specific assessment and integrated therapeutic strategies.MethodsA narrative clinical review of peer-reviewed literature in phlebology, vascular medicine, lymphatic disorders, and adipose tissue pathology was conducted. Diagnostic criteria, clinical staging, and differential diagnostic features were synthesized into a practical, stage-based framework. A multilayer therapeutic approach targeting inflammation, lymphatic function, adipose tissue pathology, extracellular matrix remodeling, and post-treatment rehabilitation is proposed.ResultsAccurate diagnosis of lipedema relies primarily on clinical evaluation, including pain assessment, tissue palpation, characteristic fat distribution, and exclusion of lymphedema and simple obesity. Early-stage identification enables effective intervention focused on inflammation control and lymphatic unloading, potentially preventing irreversible fibrosis. Advanced stages require targeted adipose tissue interventions, fibrosis management, and structured rehabilitation to preserve mobility and quality of life.ConclusionLipedema should be recognized as a systemic vascular-lymphatic-inflammatory disorder within phlebology practice. Early diagnosis and implementation of a structured, stage-specific multimodal treatment framework may significantly alter disease progression and reduce the risk of long-term disability.

Melanoma is a highly aggressive form of skin cancer with a significant mortality rate. Over the past two decades, its incidence has been on the rise and is projected to increase further in the future. Early treatment has a higher survival rate. Currently, dermatologists rely on visual inspection followed by biopsy to diagnose melanoma, but there is considerable variability in diagnostic accuracy among different dermatologists. Therefore, developing a convenient, universal, and reliable early diagnostic technology for melanoma is crucial for early diagnosis and treatment.This study aims to develop a deep learning model for identifying melanoma from images captured by mobile phones. To enhance the generalization and robustness of the model, we implemented data augmentation and multiscale and multibranch learning strategies and optimized the model architecture. Finally, we designed a new network architecture: DEFA-Net, and we trained a melanoma recognition model based on this architecture. Experiments show that our proposed model achieves a validation accuracy of 92.5% and a test accuracy of 91.0% on a dataset of melanoma images captured by mobile phones, which is comparable to the diagnostic performance of experienced dermatologists. Based on the results of this study, a smartphone platform for melanoma prediagnosis was developed to assist in the early diagnosis of melanoma. We anticipate that this technology will serve as an effective tool for global skin cancer screening and prevention efforts.

DNA methylation profiling is a predictor of meningioma behavior and outcomes. We aimed to identify qualitative and quantitative MRI features to distinguish between three meningioma methylation groups: Merlin-intact, Immune-enriched, and Hypermitotic, each with distinct clinical outcomes, biologic features, and therapeutic vulnerabilities. Preoperative MRIs were retrospectively analyzed in meningiomas with previous DNA methylation profiling. Pearson's Chi-square, Fisher exact, and ANOVA tests were used to compare features between the three groups. ROC AUCs were used to assess the accuracy in discriminating between groups. 165 patients (54 years ± 14 SD; 58 men) were analyzed. 60 meningiomas were Merlin-intact, 55 Immune-enriched, and 50 Hypermitotic. Qualitative reduced diffusion (p< .001), nADC (p< .001), T2WI signal intensity (p= .02), T1 CE volume (p<.005), and tumor site (p<.001) varied between the groups. Merlin-intact meningiomas had higher T2WI signal intensity than Immune-enriched tumors (1.97 ± 0.98 vs 1.63 ± 0.45, p= .04). Hypermitotic meningiomas had the highest proportion of tumors with qualitative reduced diffusion (67%) and lowest nADC values (1.07 ± 0.14) compared to Merlin-intact (18%, p< .001; 1.41 ± 0.30, p< .001) and Immune-enriched (31%, p= .02; 1.29 ± 0.29, p= .002) meningiomas. The presence of qualitative reduced diffusion (AUC 0.71, p= .001) and lower nADC (AUC 0.82, p< .001) were able to predict Hypermitotic meningiomas. Merlin-intact tumors were predicted by the absence of qualitative reduced diffusion (AUC 0.66, p= 0.01), higher nADC (AUC 0.74, p< .001), and higher T2WI signal intensity (AUC 0.64, p= .047). Hypermitotic tumors (64.3 cm3 ± 49.1) had larger T1CE volumes than Merlin-intact (42.5 cm3 ± 37.9, p= .02) and Immune-enriched (38.2 cm3 ± 37.7, p=<.002) tumors, with tumor size a predictor of Hypermitotic (AUC 0.65, p=.003) and Immune-enriched (AUC 0.62, p=.02) meningiomas. Merlin-intact tumors were predicted by presence at the skull base (AUC 0.67, p<.001) while Immune-enriched tumors were predicted by location outside of the skull base (AUC 0.61; 95% CI 0.70, 0.52, p= .02). MR imaging has the potential to discriminate between different molecular groups of meningioma and to serve as a surrogate non-invasive marker of tumor behavior.

Numerous proteins display pleiotropic functions in different clinical contexts. However, the molecular mechanism underlying such effects is rarely understood. Speckle-type POZ protein (SPOP) is a typical example, exhibiting tumor-suppressing or tumor-promoting effects in different tumor types in accordance with different amino acid changes; specifically, two distinct sets of variants in SPOP are commonly found in subsets of prostate cancer and endometrial cancer patients. To comprehensively characterize the functional landscape of SPOP alteration, we performed a deep mutational screening (DMS), elucidating the functionality of 7,933 out of 8,228 possible single amino acid changes (96.4% coverage). Leveraging the observation that overexpression of human SPOP leads to yeast growth arrest, we assessed the functionality of each variant using a yeast proliferation assay. In addition, our approach combined long-read and short-read sequencing. Finally, our DMS model enables a clear distinction of likely-loss-of-function variants that are enriched in prostate cancers and reveals their differential characteristics in both protein structure and genetic assessments. These results demonstrate the utility of our approach in high-resolution mapping and amino acid-level interpretation of protein function.

New pulmonary lesions after prior cancer present a diagnostic challenge, potentially representing malignancy relapse or new primary lung cancer due to shared risk factors and/or impact of prior oncological therapies. This study evaluated radiologist-defined semantic features for differentiation of second primary lung cancer (SPLC) versus lung metastasis (LM). 651 single-timepoint, pre-treatment CT thorax scans from the multicentre retrospective AI-SONAR biomarker study (IRAS 331656 REC 23/NE/0151) were divided for review by nine thoracic oncology radiologists to evaluate eight semantic features. Logistic regression analysis was undertaken to identify significant features and a developed 'Second Malignancy Aetiology Recognition Tool' model (SMART) was compared to real-world clinical reader performance using McNemar's test. 649 scans were technically usable, 299 SPLC and 350 LM. Emphysema (p < 0.0001, OR 0.20 [95% CI 0.14-0.29]), irregular contour (p < 0.0001, OR 0.31 [95% CI 0.20-0.48]) and spiculation (p = 0.013, OR 0.51 [95% CI 0.30-0.89]) were more prevalent in SPLC (OR < 1 indicates association with SPLC). Peripheral lung distribution (p = 0.003, OR 1.80 [95% CI 1.20-2.68]) was more common in LM (OR > 1 indicates metastasis). SMART model AUC was 0.81 (95% CI 0.78-0.84), LM classification accuracy 75% vs 69% by radiology reader and McNemar p-value < 0.01 for comparative accuracy. 550/649 cases were predicted SPLC or LM by radiologists, in which the SMART model LM classification accuracy was 74% vs 77% by reader and McNemar p-value 0.20. In new lesions after prior treated cancer, radiologist readers called SPLC more often than LM. The SMART model performed comparably with expert thoracic radiologists in the diagnosis of LM. Question Differentiating the malignant aetiology of indeterminate lung lesions after prior cancer presents a growing diagnostic challenge. The literature and nodule guidelines are sparse for this setting. Findings A SMART model derived from semantic CT imaging features correctly classified malignant lung lesions as metastasis or lung cancer, more often than thoracic radiologists. Clinical relevance The SMART model could improve the stratification of malignant new lung lesions after prior cancer. This may lead to earlier diagnosis and optimise patient management, treatment selection and downstream outcomes.

To reveal the mechanism underlying the effects of dominant spoilage fungi on wheat quality during storage and provide a theoretical basis for targeted microbial control in wheat storage, this study characterized the structural features of fungal communities on the surface of stored wheat and at different depths of the grain bulk via high-throughput sequencing. Additionally, screening was performed for stably existing dominant spoilage fungi in a wheat storage environment. Subsequently, four isolated dominant spoilage fungal strains, Fusarium lateritium, Aspergillus niger, Penicillium citrinum and Talaromyces islandicus, were back-inoculated onto wheat kernels sterilized by 60Co gamma irradiation. Simulated storage trials were conducted at 28 °C and 80% relative humidity to investigate their impacts on wheat quality. The results show that F. lateritium and A. niger exhibited faster growth rates and were able to colonize the entire surface of wheat kernels within 8 days. After infection by these two fungi, wheat superoxide dismutase (SOD) activity decreased by 33.83 U/g and 21.90 U/g, peroxidase (POD) activity decreased by 1408 U/(g·min) and 745 U/(g·min), and electrical conductivity (EC) increased by 11.17 μS/(cm·g) and 7.74 μS/(cm·g), respectively. After 10 days of storage, A. niger significantly reduced the water absorption of wheat gluten to 175.91% and elevated the fatty acid value to 74.20 mg/100g, rendering the wheat unsuitable for storage. P. citrinum exerted the most significant effect on the solvent retention capacity (SRC) of wheat flour in water, sucrose, sodium carbonate, and lactic acid solutions. This study clarified the screening criteria for dominant spoilage fungi in stored wheat, as well as the threshold values and differential characteristics of the impacts of different dominant spoilage fungi on wheat quality, providing critical theoretical support for targeted microbial control during wheat storage.