Pulmonary arterial hypertension (PAH) is a rare cardiovascular disease with very high mortality rate. The currently available therapeutic strategies, which improve symptoms, cannot fundamentally reverse the condition. Thus, new therapeutic strategies need to be established. Our research analyzed three microarray datasets of lung tissues from human PAH samples retrieved from the Gene Expression Omnibus (GEO) database. We combined two datasets for subsequent analyses, with the batch effects removed. In the merged dataset, 542 DEGs were identified and the key module relevant to PAH was selected using WGCNA. GO and KEGG analyses of DEGs and the key module indicated that the pre-ribosome, ribosome biogenesis, centriole, ATPase activity, helicase activity, hypertrophic cardiomyopathy, melanoma, and dilated cardiomyopathy pathways are involved in PAH. With the filtering standard (|MM| > 0.95 and |GS| > 0.90), 70 hub genes were identified. Subsequently, five candidate marker genes (CDC5L, AP3B1, ZFYVE16, DDX46, and PHAX) in the key module were found through overlapping with the top thirty genes calculated by two different methods in CytoHubb. Two of them (CDC5L and DDX46) were found to be significantly upregulated both in the merged dataset and the validating dataset in PAH patients. Meanwhile, expression of the selected genes in lung from PAH chicken measured by qRT-PCR and the ROC curve analyses further verified the potential marker genes’ predictive value for PAH. In conclusion, CDC5L and DDX46 may be marker genes and potential therapeutic targets for PAH.

The newly identified liver-enriched gene 1 (LEG1) encodes a protein with a characteristic domain of unknown function 781 (DUF781/LEG1), constituting a protein family with only one member in mammals. A functional study in zebrafish suggested that LEG1 genes are involved in liver development, while the platypus LEG1 homolog, Monotreme Lactation Protein (MLP), which is enriched in the mammary gland and milk, acts as an antibacterial substance. However, no functional studies on eutherian LEG1s have been published to date. Thus, we here report the first functional prediction study at the cellular level. As previously reported, eutherian LEG1s can be classified into three paralogous groups. Pigs have all three LEG1 genes (pLEG1s), while humans and mice have retained only LEG1a. Hence, pLEG1s might represent an ideal model for studying LEG1 gene functions. RNA-seq was performed by the overexpression of pLEG1s and platypus MLP in HepG2 cells. Enrichment analysis showed that pLEG1a and pLEG1b might exhibit little function in liver cells; however, pLEG1c is probably involved in the endoplasmic reticulum (ER) stress response and protein folding. Additionally, gene set enrichment analysis revealed that platypus MLP shows antibacterial activity, confirming the functional study in platypus. Therefore, our study showed from the transcriptomic perspective that mammalian LEG1s have different functions in liver cells due to the subfunctionalization of paralogous genes.

Ischemic cardiomyopathy (ICM) caused by coronary artery disease always leads to myocardial infarction and heart failure. Identification of novel transcriptional regulators in ICM is an effective method to establish new diagnostic and therapeutic strategies. In this study, we used two RNA-seq datasets and one microarray dataset from different studies, including 25 ICM and 21 non-failing control (NF) samples of human left ventricle tissues for further analysis. In total, 208 differentially expressed genes (DEGs) were found by combining two RNA-seq datasets with batch effects removed. GO and KEGG analyses of DEGs indicated that the response to wounding, positive regulation of smooth muscle contraction, chromatin, PI3K-Akt signaling pathway, and transporters pathways are involved in ICM. Simple Enrichment Analysis found that NFIC-binding motifs are enriched in promoter regions of downregulated genes. The Gene Importance Calculator further proved that NFIC is vital. NFIC and its downstream genes were verified in the validating microarray dataset. Meanwhile, in rat cardiomyocyte cell line H9C2 cells, two genes (Tspan1 and Hopx) were confirmed, which decreased significantly along with knocking down Nfic expression. In conclusion, NFIC participates in the ICM process by regulating TSPAN1 and HOPX. NFIC and its downstream genes may be marker genes and potential diagnostic and therapeutic targets for ICM.

Meat consumption is increasing globally. The safety and quality of meat are considered important issues for human health. During evaluations of meat quality and freshness, microbiological parameters are often analyzed. Counts of indicator cells can provide important references for meat quality. In order to eliminate the error of manual operation and improve detection efficiency, this paper proposed a Convolutional Neural Network (CNN) with a backbone called Detect-Cells-Rapidly-Net (DCRNet), which can identify and count stained cells automatically. The DCRNet replaces the single channel of residual blocks with the aggregated residual blocks to learn more features with fewer parameters. The DCRNet combines the deformable convolution network to fit flexible shapes of stained animal cells. The proposed CNN with DCRNet is self-adaptive to different resolutions of images. The experimental results indicate that the proposed CNN with DCRNet achieves an Average Precision of 81.2% and is better than traditional neural networks for this task. The difference between the results of the proposed method and manual counting is less than 0.5% of the total number of cells. The results indicate that DCRNet is a promising solution for cell detection and can be equipped in future meat quality monitoring systems.

Androgen-inducible genes (AIGs), which can be regulated by androgen level, constitute a group of genes characterized by the presence of the AIG/FAR-17a domain in its protein sequence. Previous studies on AIGs demonstrated that one member of the gene family, AIG1, is involved in many biological processes in cancer cell lines and that ADTRP is associated with cardiovascular diseases. It has been shown that the numbers of AIG paralogs in humans, mice, and zebrafish are 2, 2, and 3, respectively, indicating possible gene duplication events during vertebrate evolution. Therefore, classifying subgroups of AIGs and identifying the homologs of each AIG member are important to characterize this novel gene family further. In this study, vertebrate AIGs were phylogenetically grouped into three major clades, ADTRP, AIG1, and AIG-L, with AIG-L also evident in an outgroup consisting of invertebrsate species. In this case, AIG-L, as the ancestral AIG, gave rise to ADTRP and AIG1 after two rounds of whole-genome duplications during vertebrate evolution. Then, the AIG family, which was exposed to purifying forces during evolution, lost or gained some of its members in some species. For example, in eutherians, Neognathae, and Percomorphaceae, AIG-L was lost; in contrast, Salmonidae and Cyprinidae acquired additional AIG copies. In conclusion, this study provides a comprehensive molecular phylogenetic analysis of vertebrate AIGs, which can be employed for future functional characterization of AIGs.