Anti-CIQC monoclonal antibody, clone A243H4

Amur sturgeon Acipenser schrenckii, an economically important freshwater fish cultured in China, is now facing numerous bacterial diseases during aquaculture. Infection by Yersina ruckeri causes high mortality and great economic loss in sturgeon culture. To better understand the immune response of Amur sturgeon to Y. ruckeri infection, we performed the transcriptome analysis using livers from Y. ruckeri-infected fish and a control group through RNA-Seq technology. Totally 119 300 unigenes with high quality were obtained. Moreover, 1112 differently expressed genes (DEGs) including 468 up-regulated genes and 644 down-regulated genes were identified based on the expression patterns. 63 immune-related DEGs, such as TLR5, IL-8, NALP3, CCL19/21, C1qC, Hsp70/90 and MHCI, were identified and further divided into 15 KEGG pathways via enrichment analysis using KEGG database. The expression patterns of DEGs were validated by qRT-PCR. In addition, 55 990 potential SSRs were identified from 34 580 transcripts, and 1 696 286 candidate SNPs were identified in the A. schrenckii liver transcriptome. This study will provide the first and crucial information on the immune mechanism of Amur sturgeon against bacterial infection.

Study Design: Basic science animal research study. Objectives: Using T10 spinal contused rats, we sought to identify molecular and circulating, metabolic and immune biomarkers during the subchronic and chronic recovery periods that may inform us concerning neurorehabilitation. Methods: Gene expression of the cord and ELISA were performed in 28 and 100 days in T10 injured rats and compared to sham-injured rats. Hundred-day injured rats were placed on either a low-fat or high-fat diet following the recovery phase. Linear regression analysis was performed between markers and locomotor score, body weight, body composition, and blood cholesterol and triglycerides. Results: Gene expression in the thoracic cord for complement marker, C1QC, dendritic cell marker, ITGAX, and cholesterol biosynthesis genes, FDFT1, HMCGR, LDLR, and SREBP1, were significantly associated with BBB score, body weight, composition, and other metabolic parameters. Circulating levels of these proteins, however, did not vary by injury or predict the level of locomotor recovery. Conclusions: Identification of reliable circulating biomarkers that are durable and based on level of spinal injury are complicated by immune and metabolic comorbidities. Continued work is necessary to identify stable markers of disease progression.