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This study developed an effective combination of and (SNE) and evaluated its anti-inflammatory and anti-hyperuricemic effects under conditions. First, the effect of SNE was tested on xanthine oxidase (XOD) activity. To investigate the anti-inflammatory effect of SNE, nitric oxide (NO) production was detected by Griess assay, and proinflammatory cytokines were measured by enzyme-linked immunosorbent assay in RAW264.7 cells. Next, we examined the effect of SNE on inducible nitric oxide synthase (iNOS) and cyclooxygenase-2 (COX-2) production using Western blot analysis. NF-κB transcriptional activity was measured using the NF-κB-SEAP reporter plasmid. To confirm the anti-hyperuricemia effect of SNE, potassium oxonate (PO)-induced mouse model was established, and the serum was used to measure glutamic pyruvic transaminase, glutamic oxaloacetic transaminase, blood urea nitrogen, creatinine, and XOD levels. Through extensive screening for a herbal medicine library, we found that SNE exhibited a potent inhibitory effect on XOD activity. In addition, SNE remarkably inhibited the production of proinflammatory cytokines [e.g., NO, interleukin (IL)-1β, and IL-6] in lipopolysaccharide-induced RAW264.7 cells and suppressed the promoter activity of NF-κB. SNE also inhibited iNOS and COX-2 expression. Finally, SNE showed anti-hyperuricemic effects in a mouse model of PO-induced hyperuricemia and did not exhibit any toxicity to liver and kidney functions. SNE, a water extract from a mixture of and at a ratio of 1:1 (w/w), is a good herbal combination that possesses dual therapeutic activities on inflammation and hyperuricemia.
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http://dx.doi.org/10.3746/pnf.2025.30.4.340 | DOI Listing |
PLoS One
September 2025
Department of Zoology, University of British Columbia, Vancouver, British Columbia, Canada.
Computer vision has increasingly shown potential to improve data processing efficiency in ecological research. However, training computer vision models requires large amounts of high-quality, annotated training data. This poses a significant challenge for researchers looking to create bespoke computer vision models, as substantial human resources and biological replicates are often needed to adequately train these models.
View Article and Find Full Text PDFPrev Nutr Food Sci
August 2025
College of Pharmacy and Research Institute of Drug Development, Chonnam National University, Gwangju 61186, Korea.
This study developed an effective combination of and (SNE) and evaluated its anti-inflammatory and anti-hyperuricemic effects under conditions. First, the effect of SNE was tested on xanthine oxidase (XOD) activity. To investigate the anti-inflammatory effect of SNE, nitric oxide (NO) production was detected by Griess assay, and proinflammatory cytokines were measured by enzyme-linked immunosorbent assay in RAW264.
View Article and Find Full Text PDFFront Oncol
August 2025
Department of Obstetrics and Gynecology, Shanxi Medical University Second Hospital, Taiyuan, China.
Objective: Cervical cancer screening through cytology remains the gold standard for early detection, but manual analysis is time-consuming, labor-intensive, and prone to inter-observer variability. This study proposes an automated deep learning-based framework that integrates lesion detection, feature extraction, and classification to enhance the accuracy and efficiency of cytological diagnosis.
Materials And Methods: A dataset of 4,236 cervical cytology samples was collected from six medical centers, with lesion annotations categorized into six diagnostic classes (NILM, ASC-US, ASC-H, LSIL, HSIL, SCC).
NPJ Precis Oncol
September 2025
Shapingba Hospital affiliated to Chongqing University (Shapingba District People's Hospital of Chongqing), Shapingba District, Chongqing, China.
Hepatocellular carcinoma (HCC) is an aggressive and heterogeneous liver cancer with restricted therapy selections and poor diagnosis. Although there have been great advances in genomics, the molecular mechanisms essential to HCC progression are not yet fully implicit, particularly at the single-cell stage. This research utilized single-cell RNA sequencing technology to evaluate transcriptional heterogeneity, immune cell infiltration, and potential therapeutic targets in HCC.
View Article and Find Full Text PDFSci Rep
September 2025
School of Computing, Mathematics and Engineering, Charles Sturt University, Bathurst, NSW, 2795, Australia.
The increasing frequency of ransomware attacks necessitates the development of more effective detection methods. Existing image-based ransomware detection approaches have largely focused on static analysis, overlooking specialized ransomware behaviors such as encryption, privilege escalation, and system recovery disruption. Although dynamic and memory forensics-based visualization methods exist in the broader malware domain, they primarily target generic malware families and often rely on memory dumps or system snapshots without transforming behavioral features into spatially meaningful representations.
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