In recent decades, with the continuous development of high‐throughput sequencing technology, data volume in medical research has increased, at the same time, almost all clinical researchers have their own independent omics data, which provided a better condition for data mining and a deeper understanding of gene functions. However, for these large amounts of data, many common and cutting‐edge effective bioinformatics research methods still cannot be widely used. This has encouraged the establishment of many analytical platforms, a portion of databases or platforms were designed to solve the special analysis needs of users, for instance, MG RAST, IMG/M, Qiita, BIGSdb, and TRAPR were developed for specific omics research, and some databases or servers provide solutions for special problems solutions. Metascape was designed to only provide functional annotations of genes as well as function enrichment analysis; BioNumerics and RidomSeqSphere+ perform multilocus sequence typing; CARD provides only antimicrobial resistance annotations. Additionally, some web services are outdated, and inefficient interaction often fails to meet the needs of researchers, such as our previous versions of the platform. Therefore, the demand to complete massive data processing tasks urgently requires a comprehensive bioinformatics analysis platform. Hence, we have developed a website platform, Sangerbox 3.0 (http://vip.sangerbox.com/), a web‐based tool platform. On a user‐friendly interface that also supports differential analysis, the platform provides interactive customizable analysis tools, including various kinds of correlation analyses, pathway enrichment analysis, weighted correlation network analysis, and other common tools and functions, users only need to upload their own corresponding data into Sangerbox 3.0, select required parameters, submit, and wait for the results after the task has been completed. We have also established a new interactive plotting system that allows users to adjust the parameters in the image; moreover, optimized plotting performance enables users to adjust large‐capacity vector maps on the web site. At the same time, we have integrated GEO, TCGA, ICGC, and other databases and processed data in batches, greatly reducing the difficulty to obtain data and improving the efficiency of bioimformatics study for users. Finally, we also provide users with rich sources of bioinformatics analysis courses, offering a platform for researchers to share and exchange knowledge.

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Protein kinase C (PKC) and galectin-3 are two important mediators that play a key pathogenic role in cardiac hypertrophy and heart failure (HF). However, the molecular mechanisms and signaling pathways are not fully understood. In this study, we explored the relationship between and roles of PKC-α and galectin-3 in the development of HF. We found that activation of PKC by phorbol dibutyrate (PDB) increased galectin-3 expression by ~180%, as well as collagen I and fibronection accumulation in cultured HL-1 cardiomyocytes. Over-expression of galectin-3 in HL-1 cells increased collagen I protein production. Inhibition of galectin-3 by β-lactose blocked PDB-induced galectin-3 and collagen production, indicating that galectin-3 mediates PKC-induced cardiac fibrosis. In rats subjected to pulmonary artery banding (PAB) to induce right ventricular HF, galectin-3 was increased by ~140% in the right ventricle and also by ~240% in left ventricle compared to control. The elevated galectin-3 is consistent with an increase of total and activated (phosphorylated) PKC-α, α-SMA and collagen I. Finally, we extended our findings to examine the role of angiotensin II (Ang II), which activates the PKC pathway and contributes to cardiac fibrosis and the development of HF. We found that Ang II activated the PKC-α pathway and increased galectin-3 expression and collagen production. This study provides a new insight into the molecular mechanisms of HF mediated by PKC-α and galectin-3. PKC-α promotes cardiac fibrosis and HF by stimulation of galectin-3 expression.