Two new spirotetronate class compounds designated wychimicins E (1) and F (2) were isolated from the culture extract of an actinomycete Cryptosporangium sp. RD061707. Their structures were determined through extensive NMR analysis in comparison with wychimicin C. Both compounds lack one hydroxy group in the decalin moiety, and the relative configuration of the remaining hydroxy group was assigned by NMR analysis of triacetylwychimicin E (3). Compounds 1 and 2 showed potent antimicrobial activity against Kocuria rhizophila and Staphylococcus aureus. These compounds were also modestly cytotoxic against P388 murine leukemia cells.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1038/s41429-024-00770-y | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Refining MR-guided thermal ablation for HCC within the Milan criteria: a decade of clinical outcomes and predictive modeling at a single institution.
BMC Cancer
January 2025
Department of Interventional Radiology, First Affiliated Hospital of Fujian Medical University, Fuzhou, 350000, China.
Background: The appropriateness of ablation for liver cancer patients meeting the Milan criteria remains controversial.
Purpose: This study aims to evaluate the long-term outcomes of MR-guided thermal ablation for HCC patients meeting the Milan criteria and develop a nomogram for predicting survival rates.
Methods: A retrospective analysis was conducted from January 2009 to December 2021 at a single institution.
Network dynamics in post-stroke cognitive impairment: insights from effective connectivity analysis.
Brain Imaging Behav
January 2025
Department of Radiology, Zhongnan Hospital of Wuhan University, Wuchang, Wuhan, Hubei, 430071, China.
This study investigates post-stroke cognitive impairment (PSCI) by utilizing spectral dynamic causal modeling (spDCM) to examine changes in effective connectivity (EC) within the default mode, executive control, dorsal attention, and salience networks. Forty-one PSCI patients and 41 demographically matched healthy controls underwent 3D-T1WI and resting-state functional magnetic resonance imaging on a 3.0T MRI.
View Article and Find Full Text PDFUsing partially shared radiomics features to simultaneously identify isocitrate dehydrogenase mutation status and epilepsy in glioma patients from MRI images.
Sci Rep
January 2025
Shanghai Key Laboratory of Magnetic Resonance, School of Physics and Electronic Science, East China Normal University, Shanghai, China.
Prediction of isocitrate dehydrogenase (IDH) mutation status and epilepsy occurrence are important to glioma patients. Although machine learning models have been constructed for both issues, the correlation between them has not been explored. Our study aimed to exploit this correlation to improve the performance of both of the IDH mutation status identification and epilepsy diagnosis models in patients with glioma II-IV.
View Article and Find Full Text PDFPrediction of subsequent vertebral fracture after percutaneous vertebral augmentation using MRI-based vertebral bone quality and CT-based Hounsfield units: a retrospective cross-sectional study.
Sci Rep
January 2025
Department of Orthopaedics, Xuzhou Central Hospital, Xuzhou Clinical School of Xuzhou Medical University, #199 Jiefang South Road, Xuzhou, 221009, JiangSu Province, China.
Subsequent vertebral fracture (SVF) is a common and refractory complication after percutaneous vertebral augmentation (PVA) for osteoporotic vertebral compression fracture (OVCF). Computed tomography (CT)-based Hounsfeld units (HU) and magnetic resonance imaging (MRI)-based vertebral bone quality (VBQ) score can evaluate osteoporosis quantitatively, hyperlipidemia(HLP) might affect measurement result of VBQ score. The primary objective of this study is to compare the predictive capabilities of HU and VBQ for SVF, and to clarify the impact of hyperlipidemia on the predictive abilities.
View Article and Find Full Text PDFDilated SE-DenseNet for brain tumor MRI classification.
Sci Rep
January 2025
Department of Applied Mathematics, University of Waterloo, Waterloo, ON, N2L 3G1, Canada.
In the field of medical imaging, particularly MRI-based brain tumor classification, we propose an advanced convolutional neural network (CNN) leveraging the DenseNet-121 architecture, enhanced with dilated convolutional layers and Squeeze-and-Excitation (SE) networks' attention mechanisms. This novel approach aims to improve upon state-of-the-art methods of tumor identification. Our model, trained and evaluated on a comprehensive Kaggle brain tumor dataset, demonstrated superior performance over established convolution-based and transformer-based models: ResNet-101, VGG-19, original DenseNet-121, MobileNet-V2, ViT-L/16, and Swin-B across key metrics: F1-score, accuracy, precision, and recall.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!