An increase in SNHG5 expression is associated with poor cancer prognosis, according to a meta-analysis.

BACKGROUND: He long noncoding RNA small nucleolar host RNA 5 (SNHG5) is highly expressed in many cancers, and there is a notable correlation between the elevated expression of SNHG5 and survival outcome in cancer patients. The objective of this study was to conduct a meta-analysis to evaluate the correlation between SNHG5 expression and the clinical outcome of cancer patients. METHODS: Six relevant electronic databases were exhaustively searched, and, depending on the inclusion and exclusion criteria, appropriate literature was obtained. The Newcastle-Ottawa Scale (NOS) score was utilized to evaluate the quality of the research for every article included, and pertinent data from each study were carefully extracted. Hazard ratios (HRs), odds ratios (ORs) and 95% confidence intervals (CIs) were combined to explore the association of SNHG5 expression levels with cancer prognosis, and sensitivity analyses and assessments of publication bias were also conducted to investigate any possibility in the publication of the studies. RESULTS: Eleven studies encompassing 721 patients were ultimately collected. When combined, the hazard ratios (HRs) revealed a substantial direct correlation between elevated SNHG5 expression and an unfavourable prognosis for cancer patients (HR = 1.90, 95% CI 0.87-4.15); however, the correlation did not reach statistical significance. Furthermore, high SNHG5 expression was predictive of advanced TNM stage (OR: 1.988, 95% CI 1.205-3.278) and larger tumour size (OR: 1.571, 95% CI 1.090-2.264); moreover, there were nonsignificant relationships between SNHG5 expression and DM (OR: 0.449, 95% CI 0.077-2.630), lymph node metastasis (OR: 1.443, 95% CI 0.709-2.939), histological grade (OR: 2.098, 95% CI 0.910-4.838), depth of invasion (OR: 1.106, 95% CI 0.376-3.248), age (OR: 0.946, 95% CI 0.718-1.247) and sex (OR: 0.762, 95% CI 0.521-1.115). CONCLUSION: SNHG5 expression is typically increased in the majority of tumour tissues. Elevated SNHG5 expression may indicate poor prognosis in cancer patients. Therefore, SNHG5 is a promising potential therapeutic target for tumours and a reliable prognostic biomarker.

Non-invasive dual attention TCN for electromyography and motion data fusion in lower limb ambulation prediction.

Objective.Recent technological advances show the feasibility of fusing surface electromyography (sEMG) signals and movement data to predict lower limb ambulation intentions. However, since the invasive fusion of different signals is a major impediment to improving predictive performance, searching for a non-invasive (NI) fusion mechanism for lower limb ambulation pattern recognition based on different modal features is crucial.Approach. We propose an end-to-end sequence prediction model with NI dual attention temporal convolutional networks (NIDA-TCNs) as a core to elegantly address the essential deficiencies of traditional decision models with heterogeneous signal fusion. Notably, the NIDA-TCN is a weighted fusion of sEMG and inertial measurement units with time-dependent effective hidden information in the temporal and channel dimensions using TCN and self-attentive mechanisms. The new model can better discriminate between walking, jumping, downstairs, and upstairs four lower limb activities of daily living.Main results. The results of this study show that the NIDA-TCN models produce predictions that significantly outperform both frame-wise and TCN models in terms of accuracy, sensitivity, precision, F1 score, and stability. Particularly, the NIDA-TCN with sequence decision fusion (NIDA-TCN-SDF) models, have maximum accuracy and stability increments of 3.37% and 4.95% relative to the frame-wise model, respectively, without manual feature-encoding and complex model parameters.Significance. It is concluded that the results demonstrate the validity and feasibility of the NIDA-TCN-SDF models to ensure the prediction of daily lower limb ambulation activities, paving the way to the development of fused heterogeneous signal decoding with better prediction performance.

PCDHB15 as a potential tumor suppressor and epigenetic biomarker for breast cancer.

Breast cancer is among the most frequently diagnosed cancer types and the leading cause of cancer-related death in women. The mortality rate of patients with breast cancer is currently increasing, perhaps due to a lack of early screening tools. In the present study, using The Cancer Genome Atlas (TCGA) breast cancer dataset (n=883), it was determined that methylation of the protocadherin ß15 (PCDHB15) promoter was higher in breast cancer samples than that in normal tissues. A negative association between promoter methylation and expression of PCDHB15 was observed in the TCGA dataset and breast cancer cell lines. In TCGA cohort, lower PCDHB15 expression was associated with shorter relapse-free survival times. Treatment with the DNA methyltransferase inhibitor restored PCDHB15 expression in a breast cancer cell line; however, overexpression of PCDHB15 was shown to suppress colony formation. PCDHB15 methylation detected in circulating cell-free DNA (cfDNA) isolated from serum samples was higher in patients with breast cancer (40.8%) compared with that in patients with benign tumors (22.4%). PCDHB15 methylation was not correlated with any clinical parameters. Taken together, PCDHB15 is a potential tumor suppressor in cases of breast cancer, which can be epigenetically silenced via promoter methylation. PCDHB15 methylation using cfDNA is a novel minimally invasive epigenetic biomarker for the diagnosis and prognosis of breast cancer.