Institution
Chengdu University of Traditional Chinese Medicine
Education•Chengdu, China•
About: Chengdu University of Traditional Chinese Medicine is a education organization based out in Chengdu, China. It is known for research contribution in the topics: Randomized controlled trial & Cochrane Library. The organization has 6815 authors who have published 4569 publications receiving 43947 citations. The organization is also known as: Chengdu University of Traditional Chinese Medicine & Chéngdū zhōng yīyào Dàxué.
Papers published on a yearly basis
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TL;DR: A conceptual models for the COVID-19 outbreak in Wuhan with the consideration of individual behavioural reaction and governmental actions is proposed, and it successfully captures the course of the COIDs, and thus sheds light on understanding the trends of the outbreak.
925 citations
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TL;DR: It is suggested that patients with COVID‐19 should receive Kaletra early and should be treated by a combination of Western and Chinese medicines, andKaletra and TCM played an important role in the treatment of the viral pneumonia.
Abstract: The outbreak of the novel coronavirus in China (SARS-CoV-2) that began in December 2019 presents a significant and urgent threat to global health. This study was conducted to provide the international community with a deeper understanding of this new infectious disease. Epidemiological, clinical features, laboratory findings, radiological characteristics, treatment, and clinical outcomes of 135 patients in northeast Chongqing were collected and analyzed in this study. A total of 135 hospitalized patients with COVID-19 were enrolled. The median age was 47 years (interquartile range, 36-55), and there was no significant gender difference (53.3% men). The majority of patients had contact with people from the Wuhan area. Forty-three (31.9%) patients had underlying disease, primarily hypertension (13 [9.6%]), diabetes (12 [8.9%]), cardiovascular disease (7 [5.2%]), and malignancy (4 [3.0%]). Common symptoms included fever (120 [88.9%]), cough (102 [76.5%]), and fatigue (44 [32.5%]). Chest computed tomography scans showed bilateral patchy shadows or ground glass opacity in the lungs of all the patients. All patients received antiviral therapy (135 [100%]) (Kaletra and interferon were both used), antibacterial therapy (59 [43.7%]), and corticosteroids (36 [26.7%]). In addition, many patients received traditional Chinese medicine (TCM) (124 [91.8%]). It is suggested that patients should receive Kaletra early and should be treated by a combination of Western and Chinese medicines. Compared to the mild cases, the severe ones had lower lymphocyte counts and higher plasma levels of Pt, APTT, d-dimer, lactate dehydrogenase, PCT, ALB, C-reactive protein, and aspartate aminotransferase. This study demonstrates the clinic features and therapies of 135 COVID-19 patients. Kaletra and TCM played an important role in the treatment of the viral pneumonia. Further studies are required to explore the role of Kaletra and TCM in the treatment of COVID-19.
788 citations
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TL;DR: Recent advances in exploring mTOR signaling and the development of mTOR inhibitors for cancer therapy are updated and the mechanisms underlying the resistance to mTOR inhibitor in cancer cells are discussed.
Abstract: Mechanistic target of rapamycin (mTOR) is a protein kinase regulating cell growth, survival, metabolism, and immunity. mTOR is usually assembled into several complexes such as mTOR complex 1/2 (mTORC1/2). In cooperation with raptor, rictor, LST8, and mSin1, key components in mTORC1 or mTORC2, mTOR catalyzes the phosphorylation of multiple targets such as ribosomal protein S6 kinase β-1 (S6K1), eukaryotic translation initiation factor 4E binding protein 1 (4E-BP1), Akt, protein kinase C (PKC), and type-I insulin-like growth factor receptor (IGF-IR), thereby regulating protein synthesis, nutrients metabolism, growth factor signaling, cell growth, and migration. Activation of mTOR promotes tumor growth and metastasis. Many mTOR inhibitors have been developed to treat cancer. While some of the mTOR inhibitors have been approved to treat human cancer, more mTOR inhibitors are being evaluated in clinical trials. Here, we update recent advances in exploring mTOR signaling and the development of mTOR inhibitors for cancer therapy. In addition, we discuss the mechanisms underlying the resistance to mTOR inhibitors in cancer cells.
467 citations
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TL;DR: The beneficial effects of puerarin on the various medicinal purposes may be due to its wide spectrum of pharmacological properties such as vasodilation, cardioprotection, neuroprotection, antioxidant, anticancer, antiinflammation, alleviating pain, promoting bone formation, inhibiting alcohol intake, and attenuating insulin resistance.
Abstract: Puerarin is the major bioactive ingredient isolated from the root of the Pueraria lobata (Willd.) Ohwi, which is well known as Gegen (Chinese name) in traditional Chinese medicine. As the most abundant secondary metabolite, puerarin was isolated from Gegen in the late 1950s. Since then, its pharmacological properties have been extensively investigated. It is available in common foods and is used in alternative medicine. It has been widely used in the treatment of cardiovascular and cerebrovascular diseases, diabetes and diabetic complications, osteonecrosis, Parkinson's disease, Alzheimer's disease, endometriosis, and cancer. The beneficial effects of puerarin on the various medicinal purposes may be due to its wide spectrum of pharmacological properties such as vasodilation, cardioprotection, neuroprotection, antioxidant, anticancer, antiinflammation, alleviating pain, promoting bone formation, inhibiting alcohol intake, and attenuating insulin resistance. However, the direct molecular mechanisms and targets remain unclear. This review provides a comprehensive summary of the pharmacological effects of puerarin.
403 citations
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TL;DR: The results suggested that long-term internet addiction would result in brain structural alterations, which probably contributed to chronic dysfunction in subjects with IAD.
Abstract: Background: Recent studies suggest that internet addiction disorder (IAD) is associated with structural abnormalities in brain gray matter. However, few studies have investigated the effects of internet addiction on the microstructural integrity of major neuronal fiber pathways, and almost no studies have assessed the microstructural changes with the duration of internet addiction. Methodology/Principal Findings: We investigated the morphology of the brain in adolescents with IAD (N=18) using an optimized voxel-based morphometry (VBM) technique, and studied the white matter fractional anisotropy (FA) changes using the diffusion tensor imaging (DTI) method, linking these brain structural measures to the duration of IAD. We provided evidences demonstrating the multiple structural changes of the brain in IAD subjects. VBM results indicated the decreased gray matter volume in the bilateral dorsolateral prefrontal cortex (DLPFC), the supplementary motor area (SMA), the orbitofrontal cortex (OFC), the cerebellum and the left rostral ACC (rACC). DTI analysis revealed the enhanced FA value of the left posterior limb of the internal capsule (PLIC) and reduced FA value in the white matter within the right parahippocampal gyrus (PHG). Gray matter volumes of the DLPFC, rACC, SMA, and white matter FA changes of the PLIC were significantly correlated with the duration of internet addiction in the adolescents with IAD. Conclusions: Our results suggested that long-term internet addiction would result in brain structural alterations, which probably contributed to chronic dysfunction in subjects with IAD. The current study may shed further light on the potential brain effects of IAD.
324 citations
Authors
Showing all 6873 results
Name | H-index | Papers | Citations |
---|---|---|---|
Yang Yang | 164 | 2704 | 144071 |
Jun Lu | 135 | 1526 | 99767 |
Andrew H. Paterson | 119 | 496 | 59373 |
Alexei Verkhratsky | 89 | 450 | 29788 |
Peter Illes | 62 | 306 | 13229 |
Jian Kong | 60 | 329 | 12055 |
Wei Chen | 58 | 157 | 11456 |
Qianqian Li | 53 | 193 | 8647 |
Lijuan Chen | 50 | 337 | 7924 |
Canhua Huang | 48 | 167 | 15456 |
Hong Zhang | 45 | 334 | 8088 |
Zhenglin Yang | 44 | 169 | 8139 |
Hui Zhou | 43 | 341 | 6841 |
Jin-Jian Lu | 41 | 188 | 5892 |
Jian-Bo Wan | 41 | 193 | 5130 |