RESUMEN
BACKGROUND: Diagnostic decision support systems (DDSS) are computer programs aimed to improve health care by supporting clinicians in the process of diagnostic decision-making. Previous studies on DDSS demonstrated their ability to enhance clinicians' diagnostic skills, prevent diagnostic errors, and reduce hospitalization costs. Despite the potential benefits, their utilization in clinical practice is limited, emphasizing the need for new and improved products. OBJECTIVE: The aim of this study was to conduct a preliminary analysis of the diagnostic performance of "Kahun," a new artificial intelligence-driven diagnostic tool. METHODS: Diagnostic performance was evaluated based on the program's ability to "solve" clinical cases from the United States Medical Licensing Examination Step 2 Clinical Skills board exam simulations that were drawn from the case banks of 3 leading preparation companies. Each case included 3 expected differential diagnoses. The cases were entered into the Kahun platform by 3 blinded junior physicians. For each case, the presence and the rank of the correct diagnoses within the generated differential diagnoses list were recorded. Each diagnostic performance was measured in two ways: first, as diagnostic sensitivity, and second, as case-specific success rates that represent diagnostic comprehensiveness. RESULTS: The study included 91 clinical cases with 78 different chief complaints and a mean number of 38 (SD 8) findings for each case. The total number of expected diagnoses was 272, of which 174 were different (some appeared more than once). Of the 272 expected diagnoses, 231 (87.5%; 95% CI 76-99) diagnoses were suggested within the top 20 listed diagnoses, 209 (76.8%; 95% CI 66-87) were suggested within the top 10, and 168 (61.8%; 95% CI 52-71) within the top 5. The median rank of correct diagnoses was 3 (IQR 2-6). Of the 91 expected diagnoses, 62 (68%; 95% CI 59-78) of the cases were suggested within the top 20 listed diagnoses, 44 (48%; 95% CI 38-59) within the top 10, and 24 (26%; 95% CI 17-35) within the top 5. Of the 91 expected diagnoses, in 87 (96%; 95% CI 91-100), at least 2 out of 3 of the cases' expected diagnoses were suggested within the top 20 listed diagnoses; 78 (86%; 95% CI 79-93) were suggested within the top 10; and 61 (67%; 95% CI 57-77) within the top 5. CONCLUSIONS: The diagnostic support tool evaluated in this study demonstrated good diagnostic accuracy and comprehensiveness; it also had the ability to manage a wide range of clinical findings.
RESUMEN
Inflammatory bowel disease (IBD) is a multifactorial disease characterized by the dysregulated activity of many pro-inflammatory factors. Thus, bi-specific inhibitors for the simultaneous inhibition of two pro-inflammatory factors can exhibit high therapeutic potential. Here, we developed a novel bi-specific inhibitor targeting the TL1A cytokine and ADAM17/TACE metalloprotease. Biochemical analysis of the bi-specific inhibitor revealed high TL1A binding and TACE inhibition that is similar to the two respective mono-specific inhibitors. Interestingly, cell based assays for TL1A inhibition revealed strong synergism between the inhibitory domains showing an up to 80-fold increase in potency of the bi-specific inhibitor. The dramatic increase in potency is associated with binding to cell membranes through the TACE inhibitory domain leading to increased concentration of the inhibitor on the cell surface. Our study highlights the high potential of the simultaneous targeting of cell surface metalloprotease (TACE) and soluble pro-inflammatory cytokine (TL1A) as a potential therapeutic approach in IBD.
RESUMEN
Asymmetric messenger RNA (mRNA) localization facilitates efficient translation in cells such as neurons and fibroblasts. However, the extent and importance of mRNA polarization in epithelial tissues are unclear. Here, we used single-molecule transcript imaging and subcellular transcriptomics to uncover global apical-basal intracellular polarization of mRNA in the mouse intestinal epithelium. The localization of mRNAs did not generally overlap protein localization. Instead, ribosomes were more abundant on the apical sides, and apical transcripts were consequently more efficiently translated. Refeeding of fasted mice elicited a basal-to-apical shift in polarization of mRNAs encoding ribosomal proteins, which was associated with a specific boost in their translation. This led to increased protein production, required for efficient nutrient absorption. These findings reveal a posttranscriptional regulatory mechanism involving dynamic polarization of mRNA and polarized translation.