The intracellular pathogen, Legionella pneumophila (L.p.), secretes approximately 300 effector proteins to modulate the host environment. Given the intimate interaction between L.p. and the endoplasmic reticulum, we investigated the role of the host Unfolded Protein Response (UPR) during L.p. infection. Interestingly, we show that the host identifies L.p. infection as a form of endoplasmic reticulum stress and the sensor pATF6 is processed to generate pATF6(N), a transcriptional activator of downstream UPR genes. However, L.p. is able to suppress the UPR and block the translation of prototypical UPR genes, BiP and CHOP. Furthermore, biochemical studies reveal that L.p. uses two effectors (Lgt1 and Lgt2) to inhibit the splicing of XBP1u mRNA to XBP1s, an UPR response regulator. Thus, we demonstrate that L.p. is able to inhibit the UPR by multiple mechanisms including blocking XBP1u splicing and causing translational repression. This observation highlights the utility of L.p. as a powerful tool for studying a critical protein homeostasis regulator.

Background Effective healthcare disparities curricula seek to train physicians who are well equipped to address the health needs of an increasingly diverse society. Current literature on healthcare disparities curricula and implementation focuses on courses created independent of existing educational materials. Our aim was to develop and implement a novel resource-conserving healthcare disparities curriculum to enhance existing medical school lectures without the need for additional lectures. Methods This non-randomized intervention was conducted at the University of California Los Angeles. The curriculum was offered to all first-year medical students in the class of 2021 (n=188). With institutional approval, a new healthcare disparities curriculum was created based on the Society of General Internal Medicine’s core learning objectives for effective healthcare disparities curricula (J General Internal Med 25:S160–163, 2010). Implementation of the curriculum made use of “teachable moments” within existing medical school lectures. Teachable moments were broad lecture topics identified by the research team as suitable for introducing relevant healthcare disparities content. The new lecture-enhancing healthcare disparities curriculum was delivered with the related lecture via integrated PDF documents uploaded to an online learning management system. Students were encouraged to complete pre- and post- course assessments to examine changes in disparities knowledge and self-rated confidence in addressing disparities. Matched χ2 tests were used for statistical analysis. Results Participating students (n=92) completed both pre- and post-course assessments and were retrospectively stratified, based on self-reported use of the new lecture enhancing curriculum, into the “high utilizer” group (use of materials “sometimes” or “very often,” n=52) and the comparison “low utilizer” group (use of the materials “rarely” or “very rarely,” n=40). Students who self-identified as underrepresented racial and ethnic minorities in medicine were more likely to utilize the material (41% of the high utilizers vs. 17% of the low utilizer group, p<.01). Post-course knowledge assessment scores and self-reported confidence in addressing healthcare disparities improved only in the high utilizer group. Conclusions Integrating new guideline based curricula content simultaneously into pre-existing lectures by identifying and harnessing teachable moments may be an effective and resource-conserving strategy for enhancing healthcare disparities education among first year medical students.

outcomes including disrupted neurodevelopment, increased risk of SE recurrence, and increased long term mortality. SE is "refractory" if seizures continue after firstand second-line therapy. Refractory status epilepticus (RSE) is associated with mortality rates as high as 32%. Expedient treatment of SE is essential for achieving good outcomes, however the average time to first-, second-, and third-line treatments are longer than guidelines recommend at US tertiary care hospitals. To address this issue, the American Academy of Neurology proposed as a quality measure, the proportion of pediatric patients receiving third-line treatment for convulsive RSE within 60 minutes. We field-tested this quality measure with the goal of determining whether it is feasible to measure and whether it actually reflects quality of care.Methods: Using the statistical programming language R, we developed a tool to automatically identify patients in RSE and calculate time to third-line treatment using data from electronic medical records. We tested the fidelity of our tool on a large cohort of patients using manual chart review as a gold standard. The cohort included all pediatric patients (age 0-21) admitted to both the pediatric ED and pediatric ICU at New York Presbyterian Cornell Hospital between 2012 and 2017 with ICD-9 and ICD-10 codes corresponding to epilepsy and recurrent seizures as well as convulsions not elsewhere specified and general symptoms. The tool identifies cases by searching for the term "status epilepticus" in radiation reports, EEG notes, and discharge summaries, as well as checking for ICD codes that correspond to status epilepticus. Any case that meets at least one of those conditions is next checked to see if a 2nd or 3rd line medication for SE, generally an IV antiepileptic drug (AED), was given while in the ED or within 3 hours of being transferred to the pediatric ICU.Results: By manual chart review, we identified 62 episodes of convulsive SE out of a total of 665 patient visits. Of the 62 episodes of convulsive SE, 25 responded to first line treatment with benzodiazepines and 16 responded to second line treatment with an IV AED. In 6 cases, the patient was intubated and given paralytics after second line treatment -2 were subsequently given a third line medication. Finally, there were 14 cases of convulsive RSE that required third line treatment for continued seizures. Our tool identified 15 of the 16 cases that received a 3rd line medication giving a sensitivity of 93.8% and a specificity of 94.9% for detection of convulsive RSE.Conclusions: We have designed a computable phenotype that identifies cases of convulsive RSE with a high degree of sensitivity and specificity. We've demonstrated that it is feasible to automate case detection for the quality measure: proportion of pediatric patients receiving third line treatment for convulsive RSE within 60 minutes. This will allow informed quality improvement as well as research into factors that influence quality care for convulsive RSE. Future directions of t...

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