Purpose: To compare corneal endothelial damage associated with 2 techniques for preloaded Descemet membrane endothelial keratoplasty (DMEK): a tri-folded graft stored in a plastic cartridge designed for DMEK and a scrolled graft stored in a modified Jones Tube, at the time of preparation and after shipping. Methods: DMEK grafts were prepared at the Rocky Mountain Lions Eye Bank. The grafts were either tri-folded and loaded in a plastic cartridge or scrolled and loaded into a modified Jones Tube. In each group, the grafts were then either immediately removed from the cartridges or shipped for 48 hours. The grafts were then stained with Calcein AM and imaged using a fluorescent microscope. Endothelial cell loss (ECL) was determined using trainable segmentation in Fiji by 2 graders. At each time point, rates of ECL loss were compared across the 2 groups. To explore the role of donor characteristics, a multivariable regression model was produced to account for method (tri-folding vs. scroll), donor age, donor gender, death-to-preservation time, death-to-preparation time, and shipping. Results: A total of 40 grafts were prepared, processed, imaged, and analyzed. No significant difference in cell loss was seen between groups at either time point alone. In the multivariate model, no significant increase in cell loss was associated with either tri-folding (3.7% less ECL; P = 0.051) or shipping (4.3% less ECL; P = 0.049). Conclusions: All techniques used resulted in clinically acceptable levels of ECL. Tri-folded tissue in a plastic cartridge did not result in ECL inferior to a scroll when prepared either immediately or preloaded for 48 hours.
There is an urgent need to identify vulnerabilities in pancreatic ductal adenocarcinoma (PDAC). PDAC cells acquire metabolic changes that augment NADPH production and cytosolic redox homeostasis. Here, we show that high NADPH levels drive activity of NADPH oxidase 4 (NOX4) expressed in the endoplasmic reticulum (ER) membrane. NOX4 produces H2O2 metabolized by peroxiredoxin 4 (PRDX4) in the ER lumen. Using functional genomics and subsequent in vitro and in vivo validations, we find that PDAC cell lines with high NADPH levels are dependent on PRDX4 for their growth and survival. PRDX4 addiction is associated with increased reactive oxygen species, a DNA-PKcs–governed DNA damage response and radiosensitivity, which can be rescued by depletion of NOX4 or NADPH. Hence, this study has identified NOX4 as a protein that paradoxically converts the reducing power of the cytosol to an ER-specific oxidative stress vulnerability in PDAC that may be therapeutically exploited by targeting PRDX4.
With the large-scale penetration of social media into our daily lives, it has become a platform for individuals to share and express their views, feelings, opinions, and thoughts. Identifying emotions has many applications ranging from personalized marketing to behavior study. Individuals express their feelings in a language that is frequently accompanied by ambiguity and figure of speech, which makes it difficult even for humans to comprehend. In this paper, we propose a new approach to classify text into emotion categories. We use Twitter data as labeled input, this data is labeled using hashtags and addresses features like emoticons, emoji, apostrophes, Twitter slang and spelling variations which are a part of informal language on social media. Our model uses word vectors generated by architecture like Word2vec, Glove, and Fasttext to generate word representations of the text. We then investigate the utility of these models on random forest classifier. Ultimately we compare the results to find the best model for text classification based on emotions. We achieve an overall 91% precision for four emotional classes on a mined dataset of more than 100,000 tweets. This is a very useful tool to understand human behavior and a natural step beyond the positive/negative polarity.
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