Age-, season- and gender-specific reference intervals of serum 25-hydroxyvitamin D3 for healthy children (0 ~ 18 years old) in Nanning area of China.

Establishing specific reference intervals (RIs) of serum 25-hydroxyvitamin D3 [25(OH)D] for children is essential for improving the accuracy of diagnosis and prognosis monitoring of diseases such as rickets and growth retardation. The study including 6,627 healthy children was conducted to establish specific RIs of 25(OH)D for children in Nanning area of China. The results showed that there were statistically significant differences among age, season, and gender of serum 25(OH)D levels, and the age-specific RIs of serum 25(OH)D were 20.3 ~ 53.6 ng/mL for 0 ~ ≤ 1 year and 18.9 ~ 49.6 ng/mL for 2 ~ ≤ 3 years. The age-, season-specific RIs of serum 25(OH)D for 4 ~ ≤ 6 years in spring-summer and autumn-winter were 15.8 ~ 42.6 ng/mL and 15.2 ~ 37.7 ng/mL, respectively. The age-, gender-specific RIs of serum 25(OH)D for 7 ~ ≤ 18 years for males and females were 12.1 ~ 36.1 ng/mL and 10.8 ~ 35.3 ng/mL, respectively. This study successfully established the RIs of serum 25(OH)D, which may help to improve disease diagnosis and monitoring for children in the Nanning area of China.

CDC20 May Serve as a Potential Biomarker-Based Risk Score System in Predicting the Prognosis of Patients with Hepatocellular Carcinoma.

Background: The specificity and sensitivity of hepatocellular carcinoma (HCC) diagnostic markers are limited, hindering the early diagnosis and treatment of HCC patients. Therefore, improving prognostic biomarkers for patients with HCC is urgently needed. Methods: HCC-related datasets were downloaded from the public databases. Differentially expressed genes (DEGs) between HCC and adjacent nontumor liver tissues were then identified. Moreover, the intersection of DEGs in four datasets (GSE138178, GSE77509, GSE84006, and TCGA) was used in the functional enrichment, and module genes were obtained by a coexpression network. Cox and Kaplan-Meier analyses were used to identify overall survival- (OS-) related genes from module genes. Area under the curve (AUC) > 0.9 of OS-related genes was then carried out in order to perform the protein-protein interaction network. The feature genes were identified by least absolute shrinkage and selection operator (LASSO). Furthermore, the hub gene was identified through the univariate Cox model, after which the correlation analysis between the hub gene and pathways was explored. Finally, infiltration in immune cell types in HCC was analyzed. Results: A total of 2,227 upregulated genes and 1,501 downregulated DEGs were obtained in all four datasets, which were mainly found to be involved in the cell cycle and retinol metabolism. Accordingly, 998 OS-related genes were screened to construct the LASSO model. Finally, 8 feature genes (BUB1, CCNB1, CCNB2, CCNA2, AURKB, CDC20, OIP5, and TTK) were obtained. CDC20 was shown to serve as a poor prognostic gene in HCC and was mainly involved in the cell cycle. Moreover, a positive correlation was noted between the high degree of infiltration with Th2 and CDC20. Conclusion: High expression of CDC20 predicted poor survival, as potential target in the treatment for HCC.

ABIN1 inhibits HDAC1 ubiquitination and protects it from both proteasome- and lysozyme-dependent degradation.

ABIN1, an important immune regulator, has been shown to be involved in various cellular functions, such as immunity, development, tissue homeostasis, and tumor progression. It inhibits TNF- and TLR-induced NF-κB signaling activation and the consequent gene expression. Despite its functional significance, the mechanism of ABIN1 in the regulation of various cellular functions remains unclear. In this study, we identified HDAC1, a key regulator of eukaryotic gene expression and many important cellular events, including cell proliferation, differentiation, cancer and immunity, as an interacting partner of ABIN1. The results showed that ABIN1 acted as a modulator to down-regulate HDAC1 ubiquitination via three different linkages, thereby stabilizing HDAC1 by inhibiting its lysosomal and proteasomal degradation. Interestingly, the inhibitory function of ABIN1 required direct binding with HDAC1. Moreover, the level of p53, which was a tumor suppressor and a well-studied substrate of HDAC1, was under the regulation of ABIN1 via the modulation of HDAC1 levels, suggesting that ABIN1 was physiologically significant in tumor progression. This study has revealed a new function of ABIN1 in mediating HDAC1 modification and stability.