The harmful by-product of paracetamol is known as N-Acetyl-p-benzoquinoneimine, (NAPQI). When paracetamol is given at therapeutic dosages or in excess, it undergoes Phase I metabolism in the liver via Cytochrome P-450 2E1 (CYP2E1), and then it produces NAPQI. Previous studies reported that a non-ionic surfactant known as Brij 35 (Polyoxyethylene lauryl ether) has been shown to be an effective inhibitor of CYP2E1 and P-glycoprotein (P-gp).
View Article and Find Full Text PDFThe image retrieval is the process of retrieving the relevant images to the query image with minimal searching time in internet. The problem of the conventional Content-Based Image Retrieval (CBIR) system is that they produce retrieval results for either colour images or grey scale images alone. Moreover, the CBIR system is more complex which consumes more time period for producing the significant retrieval results.
View Article and Find Full Text PDFMyelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD) and neuromyelitis optica spectrum disorders (NMOSD) are two rare autoimmune inflammatory demyelinating diseases involving the central nervous system, which are often seen with combined involvement of the optic nerve and spinal cord. MOGAD can be confused with multiple sclerosis or NMOSD, due to its clinical presentation that may be similar and its characteristic to progress with habitual attacks. Although the clinical course of the above-mentioned three diseases is similar, their diagnosis and management are different.
View Article and Find Full Text PDFIntroduction: Organ donation refers to the collection of a human organ from a living or deceased donor and its transplantation into a recipient. An organ transplant recipient is a patient with organ failure who will not survive unless he receives a new organ. Although the benefits of organ transplantation are undeniable, there is a significant gap between the number of donors and recipients, as the demand for organs greatly surpasses the available supply.
View Article and Find Full Text PDFThis study aimed to develop an advanced ensemble approach for automated classification of mental health disorders in social media posts. The research question was: can an ensemble of fine-tuned transformer models (XLNet, RoBERTa, and ELECTRA) with Bayesian hyperparameter optimization improve the accuracy of mental health disorder classification in social media text. Three transformer models (XLNet, RoBERTa, and ELECTRA) were fine-tuned on a dataset of social media posts labelled with 15 distinct mental health disorders.
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