ABSTRACT
BACKGROUND/OBJECTIVES: Artificial intelligence can assist with ocular image analysis for screening and diagnosis, but it is not yet capable of autonomous full-spectrum screening. Hypothetically, false-positive results may have unrealized screening potential arising from signals persisting despite training and/or ambiguous signals such as from biomarker overlap or high comorbidity. The study aimed to explore the potential to detect clinically useful incidental ocular biomarkers by screening fundus photographs of hypertensive adults using diabetic deep learning algorithms. SUBJECTS/METHODS: Patients referred for treatment-resistant hypertension were imaged at a hospital unit in Perth, Australia, between 2016 and 2022. The same 45° colour fundus photograph selected for each of the 433 participants imaged was processed by three deep learning algorithms. Two expert retinal specialists graded all false-positive results for diabetic retinopathy in non-diabetic participants. RESULTS: Of the 29 non-diabetic participants misclassified as positive for diabetic retinopathy, 28 (97%) had clinically useful retinal biomarkers. The models designed to screen for fewer diseases captured more incidental disease. All three algorithms showed a positive correlation between severity of hypertensive retinopathy and misclassified diabetic retinopathy. CONCLUSIONS: The results suggest that diabetic deep learning models may be responsive to hypertensive and other clinically useful retinal biomarkers within an at-risk, hypertensive cohort. Observing that models trained for fewer diseases captured more incidental pathology increases confidence in signalling hypotheses aligned with using self-supervised learning to develop autonomous comprehensive screening. Meanwhile, non-referable and false-positive outputs of other deep learning screening models could be explored for immediate clinical use in other populations.
ABSTRACT
Since mucosal surfaces represent major portals of entry for pathogens, its associated immune system is important to protect the organism. In this paper, we compared at the cellular and molecular levels intestinal leukocyte suspensions with their head kidney (HK) or peripheral blood (PBL) counterparts to highlight characteristics of intestinal immune functions in healthy rainbow trout. These studies show that intestinal phagocytes are less activated by yeast cells but when they are activated they can ingest as many yeast cells as their HK counterparts. A natural cytotoxic activity could be detected which is twice higher in intestinal than in HK leukocyte preparations. This natural cytotoxic activity is correlated with the expression of transcripts encoding the natural killer enhancement factor (NKEF). Intestinal leukocytes did not respond to an in vitro mitogenic stimulation performed under classical culture conditions. And finally, a high expression of CD8α transcripts was observed in gut leukocyte preparations, suggesting that the intestine could contain a high proportion of T cells expressing the αα homodimeric form of CD8. This kind of comparison on nonimmunized fish provides better knowledge on basal immune functions in the intestine to, analyze later on, immune responses induced by an antigenic stimulation.
