RESUMO
Pyrazinoindole-based Lewis-acid/base assemblies are prepared through the use of regioselective formal [3 + 3] cycloaddition reactions, and their intriguing photophysical properties are described. The assemblies exhibit strong emissions in THF solution, which are attributed to through-space intramolecular charge-transfer (ICT) transitions between the branched Lewis-acid/base moieties. Furthermore, these show ratiometric color-change responses in PL titration experiments, which give rise to new colors through turn-on emissions ascribable to ICT transitions that alternate between the pyrazinoindole units and each triarylboryl or amino moiety, a consequence of the binding of the fluoride or acid. Pieces of filter paper covered by these assemblies exhibited blue-shifted color changes when immersed in aqueous acidic solutions, suggesting that these are promising candidate indicators that detect acid through emissive color. Computational data for these assemblies and their corresponding adducts verify the existence of ICT transitions that alternate through fluoride or acid binding.
RESUMO
To train an automatic brain tumor segmentation model, a large amount of data is required. In this paper, we proposed a strategy to overcome the limited amount of clinically collected magnetic resonance image (MRI) data regarding meningiomas by pre-training a model using a larger public dataset of MRIs of gliomas and augmenting our meningioma training set with normal brain MRIs. Pre-operative MRIs of 91 meningioma patients (171 MRIs) and 10 non-meningioma patients (normal brains) were collected between 2016 and 2019. Three-dimensional (3D) U-Net was used as the base architecture. The model was pre-trained with BraTS 2019 data, then fine-tuned with our datasets consisting of 154 meningioma MRIs and 10 normal brain MRIs. To increase the utility of the normal brain MRIs, a novel balanced Dice loss (BDL) function was used instead of the conventional soft Dice loss function. The model performance was evaluated using the Dice scores across the remaining 17 meningioma MRIs. The segmentation performance of the model was sequentially improved via the pre-training and inclusion of normal brain images. The Dice scores improved from 0.72 to 0.76 when the model was pre-trained. The inclusion of normal brain MRIs to fine-tune the model improved the Dice score; it increased to 0.79. When employing BDL as the loss function, the Dice score reached 0.84. The proposed learning strategy for U-net showed potential for use in segmenting meningioma lesions.
RESUMO
Prominin-1 (PROM1), also known as CD133, is expressed in hepatic progenitor cells (HPCs) and cholangiocytes of the fibrotic liver. In this study, we show that PROM1 is upregulated in the plasma membrane of fibrotic hepatocytes. Hepatocellular expression of PROM1 was also demonstrated in mice (Prom1CreER; R26TdTom) in which cells expressed TdTom under control of the Prom1 promoter. To understand the role of hepatocellular PROM1 in liver fibrosis, global and liver-specific Prom1-deficient mice were analyzed after bile duct ligation (BDL). BDL-induced liver fibrosis was aggravated with increased phosphorylation of SMAD2/3 and decreased levels of SMAD7 by global or liver-specific Prom1 deficiency but not by cholangiocyte-specific Prom1 deficiency. Indeed, PROM1 prevented SMURF2-induced SMAD7 ubiquitination and degradation by interfering with the molecular association of SMAD7 with SMURF2. We also demonstrated that hepatocyte-specific overexpression of SMAD7 ameliorated BDL-induced liver fibrosis in liver-specific Prom1-deficient mice. Thus, we conclude that PROM1 is necessary for the negative regulation of TGFß signaling during liver fibrosis.