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Cardiovascular diseases (CVDs) are the leading causes of death globally that seriously threaten human health. Although novel western medicines have continued to be discovered over the past few decades to inhibit the progression of CVDs, new drug research and development for treating CVDs with less side effects and adverse reactions are continuously being desired. Puerarin is a natural product found in a variety of medicinal plants belonging to the flavonoid family with potent biological and pharmacological activities. Abundant research findings in the literature have suggested that puerarin possesses a promising prospect in treating CVDs. In recent years, numerous new molecular mechanisms of puerarin have been explored in experimental and clinical studies, providing new evidence for this plant metabolite to protect against CVDs. This article systematically introduces the history of use, bioavailability, and various dosage forms of puerarin and further summarizes recently published data on the major research advances and their underlying therapeutic mechanisms in treating CVDs. It may provide references for researchers in the fields of pharmacology, natural products, and internal medicine.
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Language bias stands as a noteworthy concern in visual question answering (VQA), wherein models tend to rely on spurious correlations between questions and answers for prediction. This prevents the models from effectively generalizing, leading to a decrease in performance. In order to address this bias, we propose a novel modality fusion collaborative de-biasing algorithm (CoD). In our approach, bias is considered as the model's neglect of information from a particular modality during prediction. We employ a collaborative training approach to facilitate mutual modeling between different modalities, achieving efficient feature fusion and enabling the model to fully leverage multimodal knowledge for prediction. Our experiments on various datasets, including VQA-CP v2, VQA v2, and VQA-VS, using different validation strategies, demonstrate the effectiveness of our approach. Notably, employing a basic baseline model resulted in an accuracy of 60.14% on VQA-CP v2.
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BACKGROUND: Colorectal cancer (CRC) is a major global health burden. The current diagnostic tests have shortcomings of being invasive and low accuracy. AIM: To explore the combination of intestinal microbiome composition and multi-target stool DNA (MT-sDNA) test in the diagnosis of CRC. METHODS: We assessed the performance of the MT-sDNA test based on a hospital clinical trial. The intestinal microbiota was tested using 16S rRNA gene sequencing. This case-control study enrolled 54 CRC patients and 51 healthy controls. We identified biomarkers of bacterial structure, analyzed the relationship between different tumor markers and the relative abundance of related flora components, and distinguished CRC patients from healthy subjects by the linear discriminant analysis effect size, redundancy analysis, and random forest analysis. RESULTS: MT-sDNA was associated with Bacteroides. MT-sDNA and carcinoembryonic antigen (CEA) were positively correlated with the existence of Parabacteroides, and alpha-fetoprotein (AFP) was positively associated with Faecalibacterium and Megamonas. In the random forest model, the existence of Streptococcus, Escherichia, Chitinophaga, Parasutterella, Lachnospira, and Romboutsia can distinguish CRC from health controls. The diagnostic accuracy of MT-sDNA combined with the six genera and CEA in the diagnosis of CRC was 97.1%, with a sensitivity and specificity of 98.1% and 92.3%, respectively. CONCLUSION: There is a positive correlation of MT-sDNA, CEA, and AFP with intestinal microbiome. Eight biomarkers including six genera of gut microbiota, MT-sDNA, and CEA showed a prominent sensitivity and specificity for CRC prediction, which could be used as a non-invasive method for improving the diagnostic accuracy for this malignancy.
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BACKGROUND: The multi-target stool DNA test (MT-sDNA) has potential utility in the detection of colorectal cancer (CRC), but validation of its clinical accuracy has been limited in China. AIM: To evaluate the diagnostic performance of MT-sDNA and investigate the combined diagnostic value of alpha-fetoprotein (AFP), carcinoembryonic antigen (CEA), and carbohydrate antigen 199 (CA199) with MT-sDNA in CRC and adenomas. METHODS: We evaluated the performance of the MT-sDNA kit based on a hospital clinical trial. In this case-control study, 135 participants from the Affiliated Hospital of Medical School of Ningbo University, including 51 CRC patients, 23 patients with adenomas, and 61 healthy controls were enrolled. We used a risk scoring system to determine the positivity of tests with histological diagnosis or colonoscopy as the reference standard. RESULTS: The main indices of sensitivity, specificity and accuracy were evaluated. The sensitivity and specificity for CRC detection were 90.2% and 83.3%, respectively, with an accuracy of 89.8%. For adenoma, the sensitivity and specificity were 56.5% and 68.9%, respectively, with an accuracy of 73.1%. The sensitivity and specificity of MT-sDNA combined with CEA in the diagnosis of adenoma were 78.3% and 60.7%, respectively. CONCLUSION: The MT-sDNA test showed better performance in the detection of CRC, which was superior to AFP, CEA, and CA199 separately, but not for predicting adenomas. The combination of MT-sDNA with CEA further improved the sensitivity for adenoma diagnosis.
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A new method was used for treating the natural bone. A series of natural bone materials were treated mainly by Supercritical Carbon Dioxide Fluid Technology (SC-CO2-FT) and chemical ultrasound marination. The treated bone materials were determined by scanning electron microscopy, X-ray diffraction and thermo gravimetric analyses. The results showed that the sizes of bone, the sequence of processes as well as the time effected the treated bone. The treated bone material still maintained its natural porous structure, and its wall was quite clear; moreover, the hydroxyapatite crystals kept good crystalline structure. Compared to traditional treatments, the new treatments were beneficial to delipidation and proteic extraction and were not in need of organic solvent. The results demonstrated that this new method is promising in the treatment of natural bone.