Recent advancements in machine vision methods for product code recognition: A systematic review.

Manufacturing markings printed on products play an important role in the handling and use of pharmaceuticals and perishable foods. Currently, optical character recognition, neural networks, deep learning-based methods, and combinations of these methods are used to recognize these codes. This systematic review was performed to find papers that can answer the following research questions: How have machine vision methods that can recognize product texts evolved over the past eight years? What are the most common difficulties in recognizing product texts? Articles published between 2012 and 2020 were systematically searched from Science Direct/SCOPUS, and Google Scholar in November-December 2020.

Chlorpromazine and apigenin reduce adenovirus replication and decrease replication associated toxicity.

Background: Adenoviruses can cause severe toxicity in immunocompromised individuals. Although clinical trials have confirmed the potency and safety of selectively oncolytic adenoviruses for treatment of advanced cancers, increasingly effective agents could result in more toxicity and therefore it would be useful if replication could be abrogated if necessary.

Methods: We analyzed the effect of chlorpromazine, an inhibitor of clathrin-dependent endocytosis and apigenin, a cell cycle regulator, on adenovirus replication and toxicity.