Cross-modality Guidance-aided Multi-modal Learning with Dual Attention for MRI Brain Tumor Grading

Brain tumor represents one of the most fatal cancers around the world, and is very common in children and the elderly. Accurate identification of the type and grade of tumor in the early stages plays an important role in choosing a precise treatment plan. The Magnetic Resonance Imaging (MRI) protocols of different sequences provide clinicians with important contradictory information to identify tumor regions. However, manual assessment is time-consuming and error-prone due to big amount of data and the diversity of brain tumor types. Hence, there is an unmet need for MRI automated brain tumor diagnosis. We observe that the predictive capability of uni-modality models is limited and their performance varies widely across modalities, and the commonly used modality fusion methods would introduce potential noise, which results in significant performance degradation. To overcome these challenges, we propose a novel cross-modality guidance-aided multi-modal learning with dual attention for addressing the task of MRI brain tumor grading. To balance the tradeoff between model efficiency and efficacy, we employ ResNet Mix Convolution as the backbone network for feature extraction. Besides, dual attention is applied to capture the semantic interdependencies in spatial and slice dimensions respectively. To facilitate information interaction among modalities, we design a cross-modality guidance-aided module where the primary modality guides the other secondary modalities during the process of training, which can effectively leverage the complementary information of different MRI modalities and meanwhile alleviate the impact of the possible noise

Attenuating effect of Polygala tenuifolia Willd. seed oil on progression of MAFLD

Introduction: Metabolic-associated fatty liver disease (MAFLD) is a common chronic metabolic disease that seriously threatens human health. The pharmacological activity of unsaturated fatty acid-rich vegetable oil interventions in the treatment of MAFLD has been demonstrated. This study evaluated the pharmacological activity of Polygala tenuifolia Willd, which contains high levels of 2-acetyl-1,3-diacyl-sn-glycerols (sn-2-acTAGs).Methods: In this study, a mouse model was established by feeding a high-fat diet (HFD, 31% lard oil diet), and the treatment group was fed a P. tenuifolia seed oil (PWSO) treatment diet (17% lard oil and 14% PWSO diet). The pharmacological activity and mechanism of PWSO were investigated by total cho-lesterol (TC) measurement, triglyceride (TG) measurement and histopathological observation, and the sterol regulatory element-binding protein-1 (SREBP1), SREBP2 and NF-κB signaling pathways were evaluated by immunofluorescence and Western blot analyses.Results: PWSO attenuated the increases in plasma TC and TG levels. Furthermore, PWSO reduced the hepatic levels of TC and TG, ameliorating hepatic lipid accumulation. PWSO treatment effectively improves the level of hepatitic inflammation, such as reducing IL-6 levels and TNF-α level.Discussion: PWSO treatment inactivated SREBP1 and SREBP2, which are involved in lipogenesis, to attenuate hepatic lipid accumulation and mitigate the inflammatory response induced via the NF-κB signaling pathway. This study demonstrated that PWSO can be used as a relatively potent dietary supplement to inhibit the occurrence and development of MAFLD

Additional file 1 of Mutation spectrum of chinese amyotrophic lateral sclerosis patients with frontotemporal dementia

Supplementary Material