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Medicopsis romeroi is a dematiaceous fungus that rarely causes subcutaneous phaeohyphomycosis. Here, we report a subcutaneous phaeohyphomycosis caused by a rare dematiaceous fungus, M. romeroi, in a 56-year-old male renal transplant patient. The patient was admitted for graft dysfunction and was found to have painless swelling over the anterior aspect of the right knee, which was aspirated twice within 40 days. Broad septate hyphae (determined by microscopy) and growth of phaeoid in a culture were observed in both the specimens. No sporulation was observed in the slide culture. Swelling recurred even after treatment with voriconazole, so the lesion was surgically excised. Genotypically, the isolate was identified as M. romeroi in both specimens. He was discharged on voriconazole. During a 6-month follow-up, no relapse was noticed. Phaeohyphomycosis caused by M. romeroi is rare, with only a few cases reported in India. Laboratory diagnosis of Medicopsis by conventional methods is challenging. Medicopsis species should be considered one of the etiological agents for subcutaneous phaeohyphomycosis. Molecular methods should be used for the identification of unusual pathogens.

Organophosphate nerve agent (OPNA) exposure induces acute and long-term neurological deficits. OPNA exposure at sub-lethal concentrations induces irreversible inhibition of acetylcholinesterase and cholinergic toxidrome and develops status epilepticus (SE). Persistent seizures have been associated with increased production of ROS/RNS, neuroinflammation, and neurodegeneration. A total of 1400W is a novel small molecule, which irreversibly inhibits inducible nitric oxide synthase (iNOS) and has been shown to effectively reduce ROS/RNS generation. In this study, we investigated the effects of 1400W treatment for a week or two weeks at 10 mg/kg or 15 mg/kg per day in the rat diisopropylfluorophosphate (DFP) model. 1400W significantly reduced the number of microglia, astroglia, and NeuN+FJB positive cells compared to the vehicle in different regions of the brain. 1400W also significantly reduced nitrooxidative stress markers and proinflammatory cytokines in the serum. However, neither of the two concentrations of 1400W for two weeks of treatment had any significant effect on epileptiform spike rate and spontaneous seizures during the treatment period in mixed sex cohorts, males, or females. No significant sex differences were found in response to DFP exposure or 1400W treatment. In conclusion, 1400W treatment at 15 mg/kg per day for two weeks was more effective in significantly reducing DFP-induced nitrooxidative stress, neuroinflammatory and neurodegenerative changes.

Portal vein thrombosis (PVT) is an important cause of extrahepatic portal hypertension in children. A majority of children with PVT of unknown etiology have functional protein C deficiency or abnormally elevated levels of anti-cardiolipin antibodies. We present an 8-year-old boy with portal hypertension with protein C deficiency, who underwent mesocaval shunt surgery due to recurrent episodes of bleeding esophageal varices and subsequently developed a block in the mesocaval shunt due to a thrombotic tendency.

Abstract Choosing which recipe to eat and which recipe to avoid isn’t that simple for anyone. It takes strenuous efforts and a lot of time for people to calculate the number of calories and P.H level of the dish. In this paper, we propose an ensemble neural network architecture that suggests recipes based on the taste of the person, P.H level and calorie content of the recipes. We also propose a bi-directional LSTMs-based variational autoencoder for generating new recipes. We have ensembled three bi-directional LSTM-based recurrent neural networks which can classify the recipes based on the taste of the person, P.H level of the recipe and calorie content of the recipe. The proposed model also predicts the taste ratings of the recipes for which we proposed a custom loss function which gave better results than the standard loss functions and the model also predicts the calorie content of the recipes. The bi-directional LSTMs-based variational autoencoder after being trained with the recipes which are fit for the person generates new recipes from the existing recipes. After training and testing the recurrent neural networks and the variational autoencoder, we have tested the model with 20 new recipes and got overwhelming results in the experimentation, the variational autoencoders generated a couple of new recipes, which are healthy to the specific person and will be liked by the specific person.