RESUMEN
BACKGROUND AND AIMS: Therapeutic arteriogenesis is a promising direction for the treatment of ischemic disease caused by atherosclerosis. However, pharmacological or biological approaches to stimulate functional collateral vessels are not yet available. Identifying new drug targets to promote and explore the underlying mechanisms for therapeutic arteriogenesis is necessary. METHODS: Peptide OM-LV20 (20 ng/kg) was administered for 7 consecutive days on rat hindlimb ischemia model, collateral vessel growth was assessed by H&E staining, liquid latex perfusion, and specific immunofluorescence. In vitro, we detected the effect of OM-LV20 on human umbilical vein endothelial cells (HUVEC) proliferation and migration. After transfection, we performed quantitative real-time polymerase chain reaction, in situ-hybridization and dual luciferase reporters to assessed effective miRNAs and target genes. The proteins related to downstream signaling pathways were detected by Western blot. RESULTS: OM-LV20 significantly increased visible collateral vessels and endothelial nitric oxide synthase (eNOS), together with enhanced inflammation cytokine and monocytes/macrophage infiltration in collateral vessels. In vitro, we defined a novel microRNA (miR-29b-3p), and its inhibition enhanced proliferation and migration of HUVEC, as well as the expression of vascular endothelial growth factor A (VEGFA). OM-LV20 also promoted migration and proliferation of HUVEC, and VEGFA expression was mediated via inhibition of miR-29b-3p. Furthermore, OM-LV20 influenced the protein levels of VEGFR2 and phosphatidylinositol3-kinase (PI3K)/AKT and eNOS in vitro and invivo. CONCLUSIONS: Our data indicated that OM-LV20 enhanced arteriogenesis via the miR-29b-3p/VEGFA/VEGFR2-PI3K/AKT/eNOS axis, and highlighte the application potential of exogenous peptide molecular probes through miRNA, which could promote effective therapeutic arteriogenesis in ischemic conditions.
Asunto(s)
MicroARNs , Péptidos , Factor A de Crecimiento Endotelial Vascular , Humanos , Ratas , Animales , Arteria Femoral/metabolismo , Proteínas Proto-Oncogénicas c-akt/metabolismo , Fosfatidilinositol 3-Quinasas/metabolismo , MicroARNs/genética , MicroARNs/metabolismo , Células Endoteliales de la Vena Umbilical Humana/metabolismo , Isquemia/genética , Proliferación CelularRESUMEN
Machine learning (ML) has been widely used in microbiome research for biomarker selection and disease prediction. By training microbial profiles of samples from patients and healthy controls, ML classifiers constructs data models by community features that highly correlated with the target diseases, so as to determine the status of new samples. To clearly understand the host-microbe interaction of specific diseases, previous studies always focused on well-designed cohorts, in which each sample was exactly labeled by a single status type. However, in fact an individual may be associated with multiple diseases simultaneously, which introduce additional variations on microbial patterns that interferes the status detection. More importantly, comorbidities or complications can be missed by regular ML models, limiting the practical application of microbiome techniques. In this review, we summarize the typical ML approaches of single-label classification for microbiome research, and demonstrate their limitations in multi-label disease detection using a real dataset. Then we prospect a further step of ML towards multi-label classification that potentially solves the aforementioned problem, including a series of promising strategies and key technical issues for applying multi-label classification in microbiome-based studies.
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SSRI antidepressant fluoxetine is widely used to treat psychological stress related disorders, however the underlying working mechanisms is not fully understood, as SSRIs can rapidly increase the extracellular serotonin levels but it normally takes weeks to reveal their therapeutic effect in the stress-related psychological disorders. Our previous study demonstrated that purely psychological stress without any physic stimuli induces a biphasic change in the expression of brain-derived neurotrophic factor (BDNF), which immediately decrease and then gradually increase after the stress; and that the latter BDNF increase in response to the psychological stress involves the activation of serotonin system. To investigate the role of BDNF in the fluoxetine treatment for stress-related psychological disorders, we examined the mRNA and protein levels of BDNF in the brain of Sprague-Dawley (SD) rats, which were pretreated with fluoxetine at 10 mg/kg or vehicle solution for 14 days, over 24 hour after an acute psychological stress exposure. In situ hybridization and immunohistochemistry were performed to detect the expression of BDNF at different time points in various brain regions after the psychological stress. We found that fluoxetine treatment completely blocked the BDNF decrease induced by the psychological stress, and also enhanced the gradual increase in the expression of BDNF in most of the brain regions except VTA after the psychological stress. The results suggest that the enhancement in BDNF levels induced by chronic fluoxetine treatment mediates the therapeutic effect against psychological stress.
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Previous studies suggest that serotonin (5-HT) might interact with brain-derived neurotrophic factor (BDNF) during the stress response. However, the relationship between 5-HT and BDNF expression under purely psychological stress is unclear. In this study, one hour before psychological stress exposure, the 5-HT1A receptor agonist 8-OH-DPAT or antagonist MDL73005, or the 5-HT2A receptor agonist DOI or antagonist ketanserin were administered to rats exposed to psychological stress. Immunohistochemistry and in situ hybridization revealed that after psychological stress, with the exception of the ventral tegmental area, BDNF protein and mRNA expression levels were higher in the 5-HT1A and the 5-HT2A receptor agonist groups compared with the solvent control no-stress or psychological stress group in the CA1 and CA3 of the hippocampus, prefrontal cortex, central amygdaloid nucleus, dorsomedial hypothalamic nucleus, dentate gyrus, shell of the nucleus accumbens and the midbrain periaqueductal gray. There was no significant difference between the two agonist groups. In contrast, after stress exposure, BDNF protein and mRNA expression levels were lower in the 5-HT1A and 5-HT2A receptor antagonist groups than in the solvent control non-stress group, with the exception of the ventral tegmental area. Our findings suggest that 5-HT regulates BDNF expression in a rat model of acute psychological stress.