Hepatocyte growth factor (HGF) exclusively stimulates the growth of endothelial cells without replication of vascular smooth muscle cells, and acts as a survival factor against endothelial cell death. Recently, a novel therapeutic strategy for ischemic diseases using angiogenic growth factors to expedite and/or augment collateral artery development has been proposed. We have previously reported that intraarterial administration of recombinant HGF induced angiogenesis in a rabbit hindlimb ischemia model. In this study, we examined the feasibility of gene therapy using HGF to treat peripheral arterial disease rather than recombinant therapy, due to its disadvantages. Initially, we examined the transfection of 'naked' human HGF plasmid into a rat hindlimb ischemia model. Intramuscular injection of human HGF plasmid resulted in a significant increase in blood flow as assessed by laser Doppler imaging, accompanied by the detection of human HGF protein. A significant increase in capillary density was found in rats transfected with human HGF as compared with control vector, in a dose-dependent manner (P Ͻ 0.01). Importantly, at 5 weeks after transfection, the degree of angiogenesis induced by transfection of HGF plasmid was significantly greater than that caused by
Effects of 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) on local circulation and apoptosis in the midbrain were investigated in zebrafish (Danio rerio) embryos during early development. Embryos were exposed to TCDD from 24 h post fertilization (hpf) until observation, in water maintained at 28.5 degrees C. TCDD decreased blood flow in the mesencephalic vein, the only vessel perfusing the dorsal midbrain of the embryo. At 50 hpf, blood flow was maximally reduced in this vessel and gradually returned to the control level at 60 hpf. In contrast, blood flows in the trunk and in other vessels of the head of the embryo did not significantly change until 72 hpf. Furthermore, TCDD exposure caused apoptosis in the midbrain at 60 hpf, and the TCDD dose response relationship for this effect was similar to that for reduced blood flow in the mesencephalic vein at 50 hpf. The effects of TCDD on apoptosis in the midbrain, but not on blood flow, were abolished by Z-VAD-FMK, a general caspase inhibitor. TCDD effects on both endpoints were mimicked by beta-naphthoflavone (BNF), an aryl hydrocarbon receptor (AHR) agonist, and almost abolished by concomitant exposure to TCDD and alpha-naphthoflavone (ANF), an AHR antagonist. Concomitant exposure to TCDD and either an inhibitor of cytochrome P450 (CYP) (SKF525A or miconazole) or an antioxidant (N-acetylcysteine or ascorbic acid) inhibited these effects of TCDD. The incidence of apoptosis in the midbrain was inversely related to blood flow in this brain region following these various treatments and graded TCDD exposure concentrations (r = -0.91). The same range of TCDD exposure concentrations that reduced blood flow and increased apoptosis in the midbrain greatly enhanced CYP1A mRNA expression and immunoreactivity at 50 hpf in endothelial cells of blood vessels including the mesencephalic vein and the heart, but not the brain parenchyma. Taken together, these results suggest that TCDD induces apoptosis in the midbrain of the zebrafish embryo secondary to local circulation failure, which could be related to AHR activation, induction of CYP1A, and oxidative stress.
Lung cancer is one of the major causes of cancer-related deaths in many countries around the world, and its histopathological diagnosis is crucial for deciding on optimum treatment strategies. Recently, Artificial Intelligence (AI) deep learning models have been widely shown to be useful in various medical fields, particularly image and pathological diagnoses; however, AI models for the pathological diagnosis of pulmonary lesions that have been validated on large-scale test sets are yet to be seen. We trained a Convolution Neural Network (CNN) based on the EfficientNet-B3 architecture, using transfer learning and weakly-supervised learning, to predict carcinoma in Whole Slide Images (WSIs) using a training dataset of 3,554 WSIs. We obtained highly promising results for differentiating between lung carcinoma and non-neoplastic with high Receiver Operator Curve (ROC) area under the curves (AUCs) on four independent test sets (ROC AUCs of 0.975, 0.974, 0.988, and 0.981, respectively). Development and validation of algorithms such as ours are important initial steps in the development of software suites that could be adopted in routine pathological practices and potentially help reduce the burden on pathologists.
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