Citations

Abstract Genome sequencing of the heterogeneous primary mitochondrial disorders (PMD) frequently reveals variants of uncertain significance that require functional tests for diagnosis, and does not identify variants in all patients. We analyzed mitochondrial enzyme assays, blue native polyacrylamide gel electrophoresis (BN-PAGE) with in-gel activity staining, complex I assembly blot, and select protein abundances in fibroblasts of a case series of 204 PMD patients divided into functional classes, in comparison to 51 controls and 53 differential diagnostic conditions. Overall, sensitivity and specificity for respiratory chain enzyme assays were 46% and 93% respectively, for BN-PAGE 40% and 98%, for complex I assembly assay 49% and 99%. The overall sensitivity of all tests was 76%, specificity 93%, with positive predictive value 96% and negative predictive value 67%. Categories with high sensitivity were isolated complex deficiencies, nuclear DNA-encoded mitochondrial protein synthesis defects, co-factor defects, and mitochondrial amino-acyl-tRNA synthetase conditions when aided by protein abundance. Mitochondrial DNA mutations and maintenance disorders showed poor sensitivities. Secondary dysfunctions were rare. A complete battery of functional tests showed strong diagnostic clinical utility in fibroblasts. One sentence summary A combination of four mitochondrial functional tests to identify or confirm suspected primary mitochondrial disease in fibroblasts had good sensitivity and excellent specificity, well beyond what was perceived using enzyme assays only.

ABSTRACT C3 glomerulonephritis (C3GN) is a rare kidney disease driven by dysregulation of the alternative complement pathway. We report two challenging cases of patients with C3GN in whom various immunosuppressant therapies have failed to achieve complete remission, prompting treatment with eculizumab, an anti-C5 humanized monoclonal antibody that inhibits the terminal complement pathway. Although transient improvement in kidney function was observed, both patients eventually experienced worsening renal parameters, with increasing proteinuria and hematuria, culminating in progression to end-stage kidney disease. Repeated kidney biopsies following eculizumab therapy demonstrated persistent, granular mesangial and capillary wall C3 (3+) staining on immunofluorescence studies, indicating ongoing complement activation upstream of the C5 blockade and the perpetuation of C3 deposits in the glomeruli. These cases underscore the limited efficacy of terminal complement inhibition in halting disease progression in C3GN.

ABSTRACT Enteroendocrine cells (EECs) are specialized sensors of the gastrointestinal (GI) epithelium that regulate gut function and systemic metabolism through hormone secretion. The molecular pathways directing intestinal stem cell (ISC) differentiation into EECs are incompletely understood due, in part, to their rarity. We sought to identify novel regulators of human EEC differentiation using a high-throughput screen of FDA-approved drugs and human duodenal organoids. Two epidermal growth factor receptor inhibitors (EGFRi) commonly used in cancer therapy and known to cause GI side effects, erlotinib and lapatinib, emerged as strong inducers of EEC differentiation, dramatically increasing chromogranin A (CHGA) expression compared to controls, while maintaining ISC function and organoid growth. EGFRi-treated organoids revealed robust and broad upregulation of EEC hormones, including serotonin (5HT), motilin (MLN), and somatostatin (SST), among others. In agreement with these findings, analysis of a patient cohort with lung cancer revealed an association with erlotinib use and increased circulating levels of the above EEC hormones compared to matched controls. Supporting a direct effect of EGFRi on EEC differentiation, mice treated with erlotinib demonstrated increased EEC numbers and hormones and showed EGFRi-associated diarrhea (EAD), a limiting side effect of these medications. Mechanistically, EGFRi induced upregulation of interferon (IFN) signaling targets during early ISC-to-EEC differentiation. Consistent with this, inhibition of Signal Transducer and Activator of Transcription 1 (STAT1) attenuated EGFRi-induced EEC differentiation. These findings provide important insight into EEC differentiation that could inform treatment strategies for EAD, metabolic diseases, and GI diseases. Brief Summary Inhibition of EGFR signaling promotes human ISC-to-EEC differentiation through activation of STAT1 signaling.

As machine learning (ML)-based decision support tools proliferate in clinical practice, understanding how clinicians integrate personalized ML predictions alongside randomized controlled trial (RCT) evidence is critical. We designed a web-based clinical decision support system (CDSS) presenting survival and adverse event data from a simulated RCT and ML model across 12 synthetic multiple myeloma scenarios. In a within-subjects study with 32 physicians, we evaluated how clinicians synthesize competing evidence sources to make treatment decisions. When ML and RCT outputs were concordant, physicians reported greater confidence than with RCT data alone. When results were discordant, most physicians shifted toward the ML-supported treatment, often before reviewing any information about model training or validation, suggesting a tendency toward automation bias rather than algorithm avoidance. Despite reporting higher perceived reliability after viewing model quality disclosures, physicians were largely unable to describe the validation procedures they had reviewed. Taken together, these findings reveal that clinicians may over-rely on ML recommendations even when equipped with tools designed to support critical appraisal. We discuss implications for CDSS design, clinician training, and the institutional safeguards needed before ML-based systems are deployed in high-stakes oncology settings.

ABSTRACT Incomplete aneurysm occlusion after flow disruption treatment strongly depends on the persistence of strong flow into the aneurysm, which in turn depends on the aneurysm and parent artery geometry as well as the device placement. However, at the time of treatment it remains challenging to predict future outcomes (complete or incomplete occlusion). This paper describes a strategy to evaluate the local hemodynamic environment created immediately after flow‐modifying device deployment to treat cerebral aneurysms and connect it to the subsequent long‐term outcomes. The approach is based on the concept of angiographic signatures that can be extracted from DSA sequences or computational models and represented as images that can be used to compare different aneurysmal environments. The methodology is demonstrated on two small series of four experimental rabbit aneurysms each, treated with either intrasaccular flow disruptors or endoluminal flow diverters. Noticeable differences in the angiographic signatures of completely and incompletely occluded aneurysms at follow‐up were observed. Specifically, larger values of mean transit times and longer time‐to‐peaks were observed deeper into the aneurysms that remained incompletely occluded in both series. The findings suggest that angiographic signatures can be used to assess the underlying hemodynamic environment immediately after device implantation and prognosticate the likelihood of future complete or incomplete occlusion.