Allopurinol to Prevent Mercaptopurine Adverse Effects in Children and Young Adults With Acute Lymphoblastic Leukemia.

Mercaptopurine (6MP) is used to treat acute lymphoblastic leukemia (ALL) and is metabolized by hypoxanthine guanine phosphoribosal transferase to form 6-thioguanine nucleotide (6TGN). It is also metabolized by thiopurine methyl-transferase to produce 6-methylmercaptopurine (6MMP). Elevated levels of 6MMP have been associated with toxic effects that may interfere with therapy. Allopurinol is known to inhibit thiopurine methyl-transferase which reduces red cell 6MMP and increases 6TGN. Allopurinol has been utilized successfully in adult and pediatric patients with inflammatory bowel disease who have experienced 6MMP related gastrointestinal toxicity. Between August 2015 and August 2018 we started 25 patients with ALL in maintenance on allopurinol in combination with a reduced dose of 6MP. They all had unacceptable side-effects from elevated 6MMP, including abdominal pain, nausea, vomiting, decreased appetite, hypoglycemia, fatigue, and liver toxicity. In addition many had a facial rash. All patients showed resolution of symptoms within a few weeks after starting allopurinol. The red cell levels of 6MMP rapidly declined in the first month. The red cell levels of 6TGN transiently increased in spite of the lower 6MP dose. There was no decrease in absolute neutrophil count or hemoglobin. Platelets decreased slightly not requiring therapy modification. Elevated bilirubin normalized, and alanine aminotransferase decreased significantly with most normalizing. All patients continued on allopurinol with reduced dose 6MP until completing therapy. Allopurinol, in conjunction with a reduced dose of 6MP, effectively resolves 6MMP related side-effects in ALL patients on maintenance chemotherapy. This approach may lead to increased adherence to oral 6MP during ALL maintenance in patients with 6MMP induced side-effects.

EmoCodes: a Standardized Coding System for Socio-emotional Content in Complex Video Stimuli.

Social information processing is vital for inferring emotional states in others, yet affective neuroscience has only begun to scratch the surface of how we represent emotional information in the brain. Most previous affective neuroscience work has used isolated stimuli such as static images of affective faces or scenes to probe affective processing. While this work has provided rich insight to the initial stages of emotion processing (encoding cues), activation to isolated stimuli provides limited insight into later phases of emotion processing such as interpretation of cues or interactions between cues and established cognitive schemas. Recent work has highlighted the potential value of using complex video stimuli to probe socio-emotional processing, highlighting the need to develop standardized video coding schemas as this exciting field expands. Toward that end, we present a standardized and open-source coding system for complex videos, two fully coded videos, and a video and code processing Python library. The EmoCodes manual coding system provides an externally validated and replicable system for coding complex cartoon stimuli, with future plans to validate the system for other video types. The emocodes Python library provides automated tools for extracting low-level features from video files as well as tools for summarizing and analyzing the manual codes for suitability of use in neuroimaging analysis. Materials can be freely accessed at https://emocodes.org/. These tools represent an important step toward replicable and standardized study of socio-emotional processing using complex video stimuli. Supplementary Information: The online version contains supplementary material available at 10.1007/s42761-021-00100-7.