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Manish Thapar,1 Akash Singh,2 Kevin M Robinson,3 Herbert L Bonkovsky4 1Division of Hepatology, Jefferson- Einstein Medical Center, Philadelphia, PA, USA; 2Department of Medicine, Jefferson- Einstein Medical Center Montgomery, East Norriton, PA, USA; 3Department of Medicine Jefferson- Einstein Medical Center, Philadelphia, PA, USA; 4Division of Gastroenterology and Hepatology, Wake Forest University School of Medicine/NC Baptist Hospital, Winston-Salem, NC, USACorrespondence: Manish Thapar, Division of Hepatology, Jefferson-Einstein Medical Center, 5401 Old York Road, Philadelphia, PA, USA, Email manish.thapar@Jefferson.eduAbstract: Porphyrias are, for the most part, inherited disorders of the heme biosynthetic pathway which lead to accumulation of specific intermediates responsible for most of the symptoms and signs of biochemically active disease. Acute hepatic porphyrias usually come to clinical attention primarily in women in their reproductive years who present with episodic, severe, generalized abdominal pain. Such acute attacks may also be associated with tachycardia, systemic arterial hypertension, hyponatremia, recent history of dark reddish to brownish urine, and anxiety, delirium, and sensory or motor neuropathies. Diagnosing AHPs is often challenging, requiring a high index of suspicion and the appropriate testing showing elevated ALA and/or PBG in a random urine specimen. Obstacles to diagnosis include inappropriate testing for porphyrins only, inadequate sample handling, and ordering genetic testing as the initial diagnostic test. While some of these pitfalls in diagnosis are surmountable with current knowledge, others are in need of more research.Keywords: porphyria, diagnosis, porphyrins, ALA, PBG, misdiagnosis, obstacle to diagnosis, acute intermittent porphyria, secondary coproporphyrinuria

Misgendering is the act of referring to someone in a way that does not reflect their gender identity. Translation systems, including foundation models capable of translation, can produce errors that result in misgendering harms. To measure the extent of such potential harms when translating into and out of English, we introduce a dataset, MiTTenS, covering 26 languages from a variety of language families and scripts, including several traditionally underpresented in digital resources. The dataset is constructed with handcrafted passages that target known failure patterns, longer synthetically generated passages, and natural passages sourced from multiple domains. We demonstrate the usefulness of the dataset by evaluating both dedicated neural machine translation systems and foundation models, and show that all systems exhibit errors resulting in misgendering harms, even in high resource languages., Comment: GitHub repository https://github.com/google-research-datasets/mittens