Since 1992 PredictProtein (https://predictprotein.org) is a one-stop online resource for protein sequence analysis with its main site hosted at the Luxembourg Centre for Systems Biomedicine (LCSB) and queried monthly by over 3,000 users in 2020. PredictProtein was the first Internet server for protein predictions. It pioneered combining evolutionary information and machine learning. Given a protein sequence as input, the server outputs multiple sequence alignments, predictions of protein structure in 1D and 2D (secondary structure, solvent accessibility, transmembrane segments, disordered regions, protein flexibility, and disulfide bridges) and predictions of protein function (functional effects of sequence variation or point mutations, Gene Ontology (GO) terms, subcellular localization, and protein-, RNA-, and DNA binding). PredictProtein's infrastructure has moved to the LCSB increasing throughput; the use of MMseqs2 sequence search reduced runtime five-fold (apparently without lowering performance of prediction methods); user interface elements improved usability, and new prediction methods were added. PredictProtein recently included predictions from deep learning embeddings (GO and secondary structure) and a method for the prediction of proteins and residues binding DNA, RNA, or other proteins. PredictProtein.org aspires to provide reliable predictions to computational and experimental biologists alike. All scripts and methods are freely available for offline execution in high-throughput settings.

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Graphene oxide has attracted widespread attention in the biomedical fields due to its excellent biocompatibility. Herein we investigated the layer-number dependent antibacterial and osteogenic behaviors of graphene oxide in biointerfaces. Graphene oxide with different layer numbers was deposited on the titanium surfaces by cathodal electrophoretic deposition with varied deposition voltages. The initial cell adhesion and spreading, cell proliferation, and osteogenic differentiation were observed from all the samples using rat bone mesenchymal stem cells. Both Gram-negative Escherichia coli and Gram-positive Staphylococcus aureus were used to investigate the antibacterial effect of the modified titanium surfaces. Cocultures of human gingival fibroblasts (HGF) cells with Escherichia coli and Staphylococcus aureus were conducted to simulate the conditions of the clinical practice. The results show that the titanium surfaces with graphene oxide exhibited excellent antibacterial and osteogenic effects. Increasing the layer-number of graphene oxide resulted in the augment of reactive oxygen species levels and the wrinkling, which led to the antibacterial and osteogenic effects, respectively. Compared to pure titanium surface in the cells-bacteria coculture process, the modified titanium surfaces with graphene oxide exhibited higher surface coverage percentage of cells.

Colorectal cancer (CRC), one of the most malignant cancers, is currently the fourth leading cause of cancer deaths worldwide. Recent studies indicated that long non-coding RNAs (lncRNAs) could be robust molecular prognostic biomarkers that can refine the conventional tumor-node-metastasis staging system to predict the outcomes of CRC patients. In this study, the lncRNA expression profiles were analyzed in five datasets (GSE24549, GSE24550, GSE35834, GSE50421, and GSE31737) by probe set reannotation and an lncRNA classification pipeline. Twenty-five lncRNAs were differentially expressed between CRC tissue and tumor-adjacent normal tissue samples. In these 25 lncRNAs, patients with higher expression of LINC01296, LINC00152, and FIRRE showed significantly better overall survival than those with lower expression (P < 0.05), suggesting that these lncRNAs might be associated with prognosis. Multivariate analysis indicated that LINC01296 overexpression was an independent predictor for patients' prognosis in the test datasets (GSE24549, GSE24550) (P = 0.001) and an independent validation series (GSE39582) (P = 0.027). Our results suggest that LINC01296 could be a novel prognosis biomarker for the diagnosis of CRC.

Since 1992 PredictProtein (https://predictprotein.org) is a one-stop online resource for protein sequence analysis with its main site hosted at the Luxembourg Centre for Systems Biomedicine (LCSB) and queried monthly by over 3,000 users in 2020. PredictProtein was the first Internet server for protein predictions. It pioneered combining evolutionary information and machine learning. Given a protein sequence as input, the server outputs multiple sequence alignments, predictions of protein structure in 1D and 2D (secondary structure, solvent accessibility, transmembrane segments, disordered regions, protein flexibility, and disulfide bridges) and predictions of protein function (functional effects of sequence variation or point mutations, Gene Ontology (GO) terms, subcellular localization, and protein-, RNA-, and DNA binding). PredictProtein's infrastructure has moved to the LCSB increasing throughput; the use of MMseqs2 sequence search reduced runtime five-fold; user interface elements improved usability, and new prediction methods were added. PredictProtein recently included predictions from deep learning embeddings (GO and second-ary structure) and a method for the prediction of proteins and residues binding DNA, RNA, or other proteins. Pre-dictProtein.org aspires to provide reliable predictions to computational and experimental biologists alike. All scripts and methods are freely available for offline execution in high-throughput settings.

BackgroundBronchopulmonary dysplasia (BPD) is a neonatal chronic lung disease characterized by impaired pulmonary alveolar development in preterm infants. Until now, little is known about the molecular and cellular basis of BPD. There is increasing evidence that lncRNAs regulate cell proliferation and apoptosis during lung organogenesis. The potential role of lncRNAs in the pathogenesis of BPD is unclear. This study aims to clarify the role of MALAT1 during the process of BPD in preterm infants and illustrate the protective effect of MALAT1 involved in preterm infants.MethodsWe assessed the expression of MALAT1 in BPD mice lung tissues by reanalyzing dataset GSE25286 (Mouse GEO Genome 4302 Array) from gene expression database gene expression omnibus (GEO), and verified MALAT1 expression in BPD patients by realtime q-PCR. Then the role of MALAT1 in regulating cell biology was examined by profiling dataset GSE43830. The expression of CDC6, a known antiapoptopic gene was verified in BPD patients and the alveolar epithelial cell line A549 cells in which MALAT1 was knocked down. Cell apoptosis was determined by FACS using PI/Annexin-V staining.ResultsThe expression of MALAT1 was significantly evaluated in lung tissues of BPD mice at day 14 and day 29 compared to WT (P < 0.05). In consistent with mRNA array profiling analysis, MALAT1 expression level in blood samples from preterm infants with BPD was significantly increased. Bioinformative data analysis of MALAT1 knockdown in WI-38 cells showed various differentially expressed genes were found enriched in apoptosis related pathway. Down-regulation of antiapoptopic gene, CDC6 expression was further verified by q-PCR result. PI/Annexin-V apoptisis assay results showed that MALAT1 knocked down in the alveolar epithelial cell line (A549) promotes cell apoptosis.ConclusionsIn our study, we found that up-regulation of lncRNA MALAT1 could protect preterm infants with BPD by inhibiting cell apoptosis. These data provide novel insights into MALAT1 regulation which may be relevant to cell fate and shed light on BPD prevention and treatment.Electronic supplementary materialThe online version of this article (10.1186/s12890-017-0524-1) contains supplementary material, which is available to authorized users.

Titanium and its alloys have been widely used in orthopedic and dental implants because of their excellent properties. However, implant failures still occur due to implant-associated bacterial infections. Therefore, proper surface modification of titanium and its alloys is necessary. In this work, commercial pure titanium plates were modified with graphene oxide (GO) which was used to load minocycline hydrochloride. Gram-positive Staphylococcus aureus (S. aureus) and Streptococcus mutans (S. mutans) and Gram-negative Escherichia coli (E. coli) were used to investigate the antibacterial activity of the samples. Human gingival fibroblast (HGF) cells were applied to assess the cytocompatibility of the various samples. To investigate cell adhesion and cell surface coverage in the presence of bacteria, the coculture of HGF cells and S. aureus was performed. The results indicated that the GO-modified titanium surface could inhibit the growth of the bacteria which had direct contact with GO, while it could not affect the bacteria without direct contact of GO. Minocycline hydrochloride on the GO-modified titanium surface (M@GO-Ti) showed a slow release behavior and exhibited excellent antibacterial activity with the synergistic effect of contact-killing and release-killing by GO and minocycline hydrochloride, respectively. In the coculture process with the presence of S. aureus, HGF cells on M@GO-Ti demonstrated the best cell viability and cell surface coverage among all the samples.

Ds-block elements have been gaining increasing attention in the field of biomaterials modification, owing to their excellent biological properties, such as antibiosis, osteogenesis, etc. However, their function mechanisms are not well understood and conflicting conclusions were drawn by previous studies on this issue, which are mainly resulted from the inconsistent experimental conditions. In this work, three most widely used ds-block elements, copper, zinc, and silver were introduced on titanium substrate by plasma immersion ion implantation method to investigate the rule of ds-block elements in the immune responses. Results showed that the implanted samples could decrease the inflammatory responses compared with Ti sample. The trend of anti-inflammatory effects of macrophages on samples was in correlation with cellular ROS levels, which was induced by the implanted biomaterials and positively correlated with the number of valence electrons of ds-block elements. The co-culture experiments of macrophages and bone marrow mesenchymal stem cells showed that these two kinds of cells could enhance the anti-inflammation and osteogenesis of samples by the paracrine manner of PGE2. In general, in their steady states on titanium substrate (Cu 2+ , Zn 2+ , Ag), the ds-block elements with more valence electrons exhibit better anti-inflammatory and osteogenic effects. Moreover, molecular biology experiments indicate that the PGE2-related signaling pathway may contribute to the desired immunoregulation and osteoinduction capability of ds-block elements. These findings suggest a correlation between the number of valence electrons of ds-block elements and the relevant biological responses, which provides new insight into the selection of implanted ions and surface design of biomaterials.