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1.
J Transl Med ; 18(1): 382, 2020 10 09.
Artigo em Inglês | MEDLINE | ID: mdl-33036625

RESUMO

BACKGROUND: The gut microbiota was shown to play a crucial role in the development of vascular dysfunction, and the bacterial composition differed between healthy controls and coronary artery disease patients. The goal of this study was to investigate how the gut microbiota affects host metabolic homeostasis at the organism scale. METHODS: We colonized germ-free C57BL/6 J mice with faeces from healthy control donors (Con) and coronary artery disease (CAD) patients and fed both groups a high fat diet for 12 weeks. We monitored cholesterol and vascular function in the transplanted mice. We analysed bile acids profiles and gut microbiota composition. Transcriptome sequencing and flow cytometry were performed to evaluate inflammatory and immune response. RESULTS: CAD mice showed increased reactive oxygen species generation and intensive arterial stiffness. Microbiota profiles in recipient mice clustered according to the microbiota structure of the human donors. Clostridium symbiosum and Eggerthella colonization from CAD patients modulated the secondary bile acids pool, leading to an increase in lithocholic acid and keto-derivatives. Subsequently, bile acids imbalance in the CAD mice inhibited hepatic bile acids synthesis and resulted in elevated circulatory cholesterol. Moreover, the faecal microbiota from the CAD patients caused a significant induction of abnormal immune responses at both the transcriptome level and through the enhanced secretion of cytokines. In addition, microbes belonging to CAD promoted intestinal inflammation by contributing to lamina propria Th17/Treg imbalance and worsened gut barrier permeability. CONCLUSIONS: In summary, our findings elucidated that the gut microbiota impacts cholesterol homeostasis by modulating bile acids. In addition, the CAD-associated bacterial community was shown to function as an important regulator of systemic inflammation and to influence arterial stiffness.

2.
Infect Genet Evol ; 85: 104419, 2020 11.
Artigo em Inglês | MEDLINE | ID: mdl-32540428

RESUMO

The COVID-19 pandemic, caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), is a current global threat for which there is an urgent need to search for an effective therapy. The transmembrane spike (S) glycoprotein of SARS-CoV-2 directly binds to the host angiotensin-converting enzyme 2 (ACE2) and mediates viral entrance, which is therefore considered as a promising drug target. Considering that new drug development is a time-consuming process, drug repositioning may facilitate rapid drug discovery dealing with sudden infectious diseases. Here, we compared the differences between the virtual structural proteins of SARS-CoV-2 and SARS-CoV, and selected a pocket mainly localizing in the fusion cores of S2 domain for drug screening. A virtual drug design algorithm screened the Food and Drug Administration-approved drug library of 1234 compounds, and 13 top scored compounds were obtained through manual screening. Through in vitro molecular interaction experiments, eltrombopag was further verified to possess a high binding affinity to S protein plus human ACE2 and could potentially affect the stability of the ACE2-S protein complex. Hence, it is worth further exploring eltrombopag as a potential drug for the treatment of SARS-CoV-2 infection.

3.
Comput Intell Neurosci ; 2019: 3679203, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31814818

RESUMO

The performance of convolutional neural network- (CNN-) based object detection has achieved incredible success. Howbeit, existing CNN-based algorithms suffer from a problem that small-scale objects are difficult to detect because it may have lost its response when the feature map has reached a certain depth, and it is common that the scale of objects (such as cars, buses, and pedestrians) contained in traffic images and videos varies greatly. In this paper, we present a 32-layer multibranch convolutional neural network named MBNet for fast detecting objects in traffic scenes. Our model utilizes three detection branches, in which feature maps with a size of 16 × 16, 32 × 32, and 64 × 64 are used, respectively, to optimize the detection for large-, medium-, and small-scale objects. By means of a multitask loss function, our model can be trained end-to-end. The experimental results show that our model achieves state-of-the-art performance in terms of precision and recall rate, and the detection speed (up to 33 fps) is fast, which can meet the real-time requirements of industry.


Assuntos
Veículos Automotores , Redes Neurais de Computação , Reconhecimento Automatizado de Padrão/métodos , Ciclismo , Cidades , Humanos , Luz , Fatores de Tempo
4.
Microbiome ; 7(1): 68, 2019 04 26.
Artigo em Inglês | MEDLINE | ID: mdl-31027508

RESUMO

BACKGROUND: Coronary artery disease (CAD) is associated with gut microbiota alterations in different populations. Gut microbe-derived metabolites have been proposed as markers of major adverse cardiac events. However, the relationship between the gut microbiome and the different stages of CAD pathophysiology remains to be established by a systematic study. RESULTS: Based on multi-omic analyses (sequencing of the V3-V4 regions of the 16S rRNA gene and metabolomics) of 161 CAD patients and 40 healthy controls, we found that the composition of both the gut microbiota and metabolites changed significantly with CAD severity. We identified 29 metabolite modules that were separately classified as being positively or negatively correlated with CAD phenotypes, and the bacterial co-abundance group (CAG) with characteristic changes at different stages of CAD was represented by Roseburia, Klebsiella, Clostridium IV and Ruminococcaceae. The result revealed that certain bacteria might affect atherosclerosis by modulating the metabolic pathways of the host, such as taurine, sphingolipid and ceramide, and benzene metabolism. Moreover, a disease classifier based on differential levels of microbes and metabolites was constructed to discriminate cases from controls and was even able to distinguish stable coronary artery disease from acute coronary syndrome accurately. CONCLUSION: Overall, the composition and functions of the gut microbial community differed from healthy controls to diverse coronary artery disease subtypes. Our study identified the relationships between the features of the gut microbiota and circulating metabolites, providing a new direction for future studies aiming to understand the host-gut microbiota interplay in atherosclerotic pathogenesis.


Assuntos
Doença da Artéria Coronariana/metabolismo , Doença da Artéria Coronariana/microbiologia , Microbioma Gastrointestinal , Metabolômica , Adulto , Idoso , Bactérias/classificação , Biomarcadores/metabolismo , Doença da Artéria Coronariana/fisiopatologia , Fezes/microbiologia , Feminino , Genômica , Humanos , Masculino , Pessoa de Meia-Idade , RNA Ribossômico 16S/genética , Índice de Gravidade de Doença
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