Yen, Y.-H. | Search bioRxiv

bioRxiv2023

The cytokine genes of Oncorhynchus masou formosanus include a defective interleukin-4A gene.

Oncorhynchus masou formosanus (Formosa land-locked salmon) is a critically endangered salmonid fish endemic to Taiwan. To begin to understand how its drastic change in lifestyle from anadromous to exclusively river-dwelling is reflected in its immune genes, we characterized the genes encoding six cytokines (IL-2A, IL-2B, IL-4A, IL-4B1, IL-4B2, and IL-17A/F2a) important for T cell responses as no genomic data is available for this fish. Interestingly, all genes appeared homozygous indicative of a genetic bottleneck. The IL2 and IL17A/F2a genes and their products are highly similar to their characterized homologs in Oncorhynchus mykiss (rainbow trout) and other salmonid fish. Two notable differences were observed in IL4 family important for type 2 immune responses. First, O. m. formosanus carries not only one but two genes encoding IL-4B1 proteins and expansions of these genes are present in other salmonid fish. Second, the OmfoIL4A gene carries a 228 bp deletion that results in a premature stop codon and hence a non-functional IL-4A cytokine. This suggests a reduced ability for T cell responses against parasitic infections in this species.

immunology↗

bioRxiv2023

Identification of Pain-Associated Effusion-Synovitis from Knee Magnetic Resonance Imaging by Deep Generative Networks

ObjectivesTo identify the source and location of osteoarthritis-induced pain symptoms, we used deep learning techniques to identify imaging abnormalities associated with pain from magnetic resonance imaging (MRI) of knees with symptoms of symptoms of osteoarthritis pain. MethodsPain-associated areas were detected from the difference between the MRI images of symptomatic knees and their respective counterfactual asymptomatic images generated by a Generative adversarial network. A total of 2,225 pairs of 3D MRI images were extracted from patients with unilateral pain symptoms in the baseline and follow-up cohorts of the Osteoarthritis Initiative. Subsequently, pain-associated effusion-synovitis were characterized into subregions (patellar, central, and posterior) using an anatomical segmentation model. ResultsWe found that the volumes of pain-associated effusion-synovitis were more sensitive and reliable indicators of pain symptoms than the overall volumes in the central and posterior subregions (odds ratio [OR]:3.23 versus 1.77 in the central region, and 3.18 versus 2.66 in the posterior region for severe effusion-synovitis). For mild effusion-synovitis, only pain-associated volume was found to be associated with pain symptoms, but not with overall volume. Patients with significant pain-associated effusion-synovitis in the patellar subregion had the highest increased odds of pain symptoms (OR=4.86). ConclusionTo the best of our knowledge, this is the first study to utilize deep-learning-based models for the detection and characterization of pain-associated imaging abnormalities. The developed algorithm can help identifying the source and location of pain symptoms and in designing targeted and individualized treatment regimens.

bioinformatics↗