Cinnamic aldehyde, an anti-inflammatory component in Du-Huo-Ji-Sheng-Tang, ameliorates arthritis in II collagenase and monosodium iodoacetate induced osteoarthritis rat models.

Background and aim: Du-Huo-Ji-Sheng-Tang (DHJST) is a Chinese herbal formula used for arthralgia and arthritis treatment clinically. This study aims to evaluate the joint-protecting efficacy of DHJST and to identify the active constituents as the evaluation marker. Experimental procedure: DHJST can be categorized into three recipes: Blood-tonifying-herbs Si-Wu-Tang (SWT), Wind-dampness-dispelling-herbs (WDH) and Qi-tonifying-herbs (TH). All formulas were used to explore the joint-protecting efficacies. Results and conclusion: s: Firstly, DHJST could decrease the arthritis progression in the monosodium-iodoacetate-induced rat and cure arthritis in the type II collagenase-induced rat. Further, in lipopolysaccharide-stimulated RAW 264.7 cells, DHJST, TH and Cinnamomum cassia (CC), an ingredient in TH, were the most potent nitric oxide (NO) and prostaglandin E2 (PGE2) inhibitors. The major components, cinnamic aldehyde, showed the strongest NO and PGE2 inhibition. Up-regulated inducible NO synthase (iNOS) and cyclooxygenase-2 were inhibited by DHJST, TH, CC, and cinnamic aldehyde. In interleukin-1ß-stimulated primary chondrocytes, upregulated iNOS was inhibited by DHJST, TH, Cinnamomum cassia, and cinnamic aldehyde. Upregulated matrix metalloprotease-13 was only inhibited by DHJST and TH and Eucommia ulmoides (EU) extract. Results suggest that DHJST presented joint-protective and cure arthritis effects. TH presented equal joint-protective effects as DHJST. The major anti-inflammatory ingredient in TH was Cinnamomum cassia in TH. And cinnamic aldehyde was the potent anti-inflammatory active compound in Cinnamomum cassia. Therefore, this study may facilitate the modern use of DHJST with TH as a simplified version but equally effective anti-osteoarthritic agents with cinnamic aldehyde as a quality control marker of DHJST and TH in osteoarthritis prevention or treatment.

Top-ranked expressed gene transcripts of human protein-coding genes investigated with GTEx dataset.

With considerable accumulation of RNA-Seq transcriptome data, we have extended our understanding about protein-coding gene transcript compositions. However, alternatively compounded patterns of human protein-coding gene transcripts would complicate gene expression data processing and interpretation. It is essential to exhaustively interrogate complex mRNA isoforms of protein-coding genes with an unified data resource. In order to investigate representative mRNA transcript isoforms to be utilized as transcriptome analysis references, we utilized GTEx data to establish a top-ranked transcript isoform expression data resource for human protein-coding genes. Distinctive tissue specific expression profiles and modulations could be observed for individual top-ranked transcripts of protein-coding genes. Protein-coding transcripts or genes do occupy much higher expression fraction in transcriptome data. In addition, top-ranked transcripts are the dominantly expressed ones in various normal tissues. Intriguingly, some of the top-ranked transcripts are noncoding splicing isoforms, which imply diverse gene regulation mechanisms. Comprehensive investigation on the tissue expression patterns of top-ranked transcript isoforms is crucial. Thus, we established a web tool to examine top-ranked transcript isoforms in various human normal tissue types, which provides concise transcript information and easy-to-use graphical user interfaces. Investigation of top-ranked transcript isoforms would contribute understanding on the functional significance of distinctive alternatively spliced transcript isoforms.

Overlapping protein-coding genes in human genome and their coincidental expression in tissues.

The completion of human genome sequences and the advancement of next-generation sequencing technologies have engendered a clear understanding of all human genes. Overlapping genes are usually observed in compact genomes, such as those of bacteria and viruses. Notably, overlapping protein-coding genes do exist in human genome sequences. Accordingly, we used the current Ensembl gene annotations to identify overlapping human protein-coding genes. We analysed 19,200 well-annotated protein-coding genes and determined that 4,951 protein-coding genes overlapped with their adjacent genes. Approximately a quarter of all human protein-coding genes were overlapping genes. We observed different clusters of overlapping protein-coding genes, ranging from two genes (paired overlapping genes) to 22 genes. We also divided the paired overlapping protein-coding gene groups into four subtypes. We found that the divergent overlapping gene subtype had a stronger expression association than did the subtypes of 5'-tandem overlapping and 3'-tandem overlapping genes. The majority of paired overlapping genes exhibited comparable coincidental tissue expression profiles; however, a few overlapping gene pairs displayed distinctive tissue expression association patterns. In summary, we have carefully examined the genomic features and distributions about human overlapping protein-coding genes and found coincidental expression in tissues for most overlapping protein-coding genes.