EC number prediction of protein sequences based on combination of hierarchical and global features.

The identification of enzyme functions plays a crucial role in understanding the mechanisms of biological activities and advancing the development of life sciences. However, existing enzyme EC number prediction methods did not fully utilize protein sequence information and still had shortcomings in identification accuracy. To address this issue, we proposed an EC number prediction network using hierarchical features and global features (ECPN-HFGF). This method first utilized residual networks to extract generic features from protein sequences, and then employed hierarchical feature extraction modules and global feature extraction modules to further extract hierarchical and global features of protein sequences. Subsequently, the prediction results of both feature types were combined, and a multitask learning framework was utilized to achieve accurate prediction of enzyme EC numbers. Experimental results indicated that the ECPN-HFGF method performed best in the task of predicting EC numbers for protein sequences, achieving macro F1 and micro F1 scores of 95.5% and 99.0%, respectively. The ECPN-HFGF method effectively combined hierarchical and global features of protein sequences, allowing for rapid and accurate EC number prediction. Compared to current commonly used methods, this method offers significantly higher prediction accuracy, providing an efficient approach for the advancement of enzymology research and enzyme engineering applications.

Hedgehog signaling pathway mediates invasion and metastasis of hepatocellular carcinoma via ERK pathway.

AIM: To investigate the role of Hedgehog (Hh) signaling pathway in the invasion and metastasis of human hepatocellular carcinoma (HCC). METHODS: Eighty six HCC tissues samples and HCC cell line Bel-7402 were examined. The protein expression of sonic hedgehog (Shh), nuclear glioma-associated oncogene-1 (Gli1), MMP-9 and p-ERK1/2 in HCC was analyzed using immunohistochemistry and Western blot analysis. Boyden chamber assay and wound-healing assay were used to quantify the invasion and metastasis of Bel-7402 cells. RESULTS: In 86 HCC tissue samples, the positive ratio of Shh and nucleus Gli1 was 67.44% (58/86) and 60.47% (52/86), respectively; the expression of nucleus Gli1 was correlated with the tumor pathological grade (P=0.034), and with the ability of the tumor to invade and metastasize (P=0.001); the expression of nucleus Gli1 was also correlated with p-ERK1/2 (P=0.031) and with MMP-9 (P=0.034). Neither Shh, nor nucleus Gli1 was observed in normal liver tissue. KAAD-cyclopamine (KAAD-cyc), a specific inhibitor of the Hh pathway, at the concentrations of 1 and 4 µmol/L inhibited the invasion and migration of Bel-7402 cells and decreased the expression of Gli1 in nucleus and MMP-9, p-ERK1/2 proteins in Bel-7402 cells. On the other hand, Shh, a ligand of the Hh pathway, at the concentration of 0.5 µg/mL produced opposite effects. The MAPK pathway inhibitors U0126 and PD98059 at the concentrations of 5 and 10 µmol/L inhibited invasion and metastasis of Bel-7402 cells induced by Shh, and decreased the expression of p-ERK1/2 and MMP-9. However, U0126 and PD98059 had no effect on the expression of Gli1. CONCLUSION: Hh signaling pathway mediates invasion and metastasis of human HCC by up-regulating the protein expression of MMP-9 via ERK pathway.

Biased Random Walk With Restart on Multilayer Heterogeneous Networks for MiRNA-Disease Association Prediction.

Numerous experiments have proved that microRNAs (miRNAs) could be used as diagnostic biomarkers for many complex diseases. Thus, it is conceivable that predicting the unobserved associations between miRNAs and diseases is extremely significant for the medical field. Here, based on heterogeneous networks built on the information of known miRNA-disease associations, miRNA function similarity, disease semantic similarity, and Gaussian interaction profile kernel similarity for miRNAs and diseases, we developed a computing model of biased random walk with restart on multilayer heterogeneous networks for miRNA-disease association prediction (BRWRMHMDA) through enforcing degree-based biased random walk with restart (BRWR). Assessment results reflected that an AUC of 0.8310 was gained in local leave-one-out cross-validation (LOOCV), which proved the calculation algorithm's good performance. Besides, we carried out BRWRMHMDA to prioritize candidate miRNAs for esophageal neoplasms based on HMDD v2.0. We further prioritize candidate miRNAs for breast neoplasms based on HMDD v1.0. The local LOOCV results and performance analysis of the case study all showed that the proposed model has good and stable performance.

[Recent progress of robots in stomatology].

With the development of industrial robot technology, robotics has entered the medical field, and the research and development of new robots for many medical applications have become a significant research direction in global robotics. Robots are widely used in various aspects of dentistry, such as prosthodontics, orthodontics, implants, endodontics, and oral surgery. This article mainly introduces the application of robots in stomatology from the above five aspects.

Sarcoidosis in gastric cancer at the time of diagnosis: A case report.

Sarcoidosis is a multisystemic inflammatory disease that commonly affects the lungs and lymphatic system and is characterized by the formation of non-caseating granulomas. Although the association between sarcoidosis and malignant diseases has been well described, it remains controversial whether this association is merely a coincidence or the consequence of a common pathophysiological mechanism. The present study reports a rare case of sarcoidosis that was present in a patient with gastric cancer at the time of diagnosis. A 64-year-old female diagnosed with stage I gastric cancer underwent curative surgery, and the postoperative pathology of the lymph nodes revealed non-caseating granulomas. At the 4-year follow-up, the sarcoidosis remained stable, and no recurrence of cancer was identified. The present case revealed that sarcoidosis and gastric cancer may coexist simultaneously and focused on the potential advantages of histological confirmation in patients with cancer and sarcoidosis.

BAFF/BAFF-R involved in antibodies production of rats with collagen-induced arthritis via PI3K-Akt-mTOR signaling and the regulation of paeoniflorin.

ETHNOPHARMACOLOGICAL RELEVANCE: Paeoniflorin (Pae) is extracted from the root of paeonia lactiflora which have attracted attention for anti-rheumatic and immune modulating properties. AIM OF THE STUDY: To investigate the role of PI3K/Akt/mTOR signaling mediated by BAFF/BAFF-R in antibodies production and the regulation of Pae on the signaling pathway in rats with collagen-induced arthritis (CIA). MATERIALS AND METHODS: CIA rats were randomly separated into different groups and treated with Pae (25, 100mg/kg) from day 18 to day 38 after immunization. The effects of Pae on B lymphocytes of CIA rats were evaluated by the levels of BAFF, anti-CII antibody, IgA, IgG and IgM, and the expressions of BAFF-R, PI3K, p-Akt and mTOR. RESULTS: In CIA rats, the levels of anti-CII antibody, IgA, IgG and IgM in serum enhanced, BAFF, BAFF-R, PI3K, p-Akt and mTOR were highly expressed. Pae (100mg/kg) obviously decreased arthritis score, relieved ankle and paw swelling, improved spleen histopathology in CIA rats, decreased the levels of IgA, IgM, IgG and anti-CII antibody, and significantly decreased the expressions of BAFF, BAFF-R, PI3K, p-Akt and mTOR. CONCLUSION: PI3K/Akt/mTOR signaling mediated by BAFF/BAFF-R participates in antibodies production by B lymphocytes of CIA rats. Pae had therapeutic effects on rats with CIA. These effects might be relative to regulating PI3K/Akt/mTOR signal mediated by BAFF/BAFF-R, and down regulate the antibodies production further.