A coordinated adaptive multiscale enhanced spatio-temporal fusion network for multi-lead electrocardiogram arrhythmia detection.

The multi-lead electrocardiogram (ECG) is widely utilized in clinical diagnosis and monitoring of cardiac conditions. The advancement of deep learning has led to the emergence of automated multi-lead ECG diagnostic networks, which have become essential in the fields of biomedical engineering and clinical cardiac disease diagnosis. Intelligent ECG diagnosis techniques encompass Recurrent Neural Networks (RNN), Transformers, and Convolutional Neural Networks (CNN). While CNN is capable of extracting local spatial information from images, it lacks the ability to learn global spatial features and temporal memory features. Conversely, RNN relies on time and can retain significant sequential features. However, they are not proficient in extracting lengthy dependencies of sequence data in practical scenarios. The self-attention mechanism in the Transformer model has the capability of global feature extraction, but it does not adequately prioritize local features and cannot extract spatial and channel features. This paper proposes STFAC-ECGNet, a model that incorporates CAMV-RNN block, CBMV-CNN block, and TSEF block to enhance the performance of the model by integrating the strengths of CNN, RNN, and Transformer. The CAMV-RNN block incorporates a coordinated adaptive simplified self-attention module that adaptively carries out global sequence feature retention and enhances spatial-temporal information. The CBMV-CNN block integrates spatial and channel attentional mechanism modules in a skip connection, enabling the fusion of spatial and channel information. The TSEF block implements enhanced multi-scale fusion of image spatial and sequence temporal features. In this study, comprehensive experiments were conducted using the PTB-XL large publicly available ECG dataset and the China Physiological Signal Challenge 2018 (CPSC2018) database. The results indicate that STFAC-ECGNet surpasses other cutting-edge techniques in multiple tasks, showcasing robustness and generalization.

SLUG is activated by nuclear factor kappa B and confers human alveolar epithelial A549 cells resistance to tumor necrosis factor-alpha-induced apoptosis.

BACKGROUND: The role of tumor necrosis factor alpha (TNF-α) in cancer is complex with both apoptotic and anti-apoptotic roles proposed. However the mechanism is not clear. In the study, we designed to investigate the effect of TNF-α on the activation and expression of nuclear factor kappa B (NF-κB)/p65/SLUG/PUMA/Bcl-2 levels in human lung cancer A549 cell line, and in conditions of TNF-α-induced apoptosis. METHODS: We have engineered three A549 cell lines that were transiently transfected with PUMA siRNA, SLUG siRNA and Bcl-2 siRNA, respectively. We have measured the in vitro effects of siRNA on apoptosis, and sensitivity to 20 ng/ml of TNF-α treatment for 24-48 h. RESULTS: We found the NF-κB activity and PUMA mRNA/protein was significantly increased after treatment of TNF-α for 24 h in untreated A549 cells, and led to a significant increase in TNF-α-induced apoptosis, no significant increase of SLUG and Bcl-2 level was shown. However, after treatment of TNF-α for 48 h in untreated A549 cells, SLUG and Bcl-2 level was significant increased, and PUMA level was significant decreased, and TNF-α-induced apoptosis was significantly decreased compared to the apoptosis level after treatment of TNF-α for 24 h. Inhibition of the NF-κB activity could effectively decrease the PUMA level and increase the SLUG and Bcl-2 level. PUMA silencing by siRNA led to a significant decrease in TNF-α-induced apoptosis after treatment of TNF-α for 24 h. Bcl-2 and SLUG silencing by siRNA led to a significant increase in TNF-α-induced apoptosis for 48 h. Furthermore, SLUG silencing increased PUMA level and decreased Bcl-2 level. CONCLUSIONS: The findings suggested that TNF-α treatment promoted apoptosis via the NF-κB-dependent PUMA pathway. The anti-apoptotic role of TNF-α was via NF-κB-dependent SLUG and Bcl-2 pathway at a later time.

Clinical significance of zoledronic acid and strontium-89 in patients with asymptomatic bone metastases from non-small-cell lung cancer.

BACKGROUND: The purpose of this study was to clarify the treatment value of zoledronic acid (ZA) and/or strontium-89 (Sr-89) in patients with non-small-cell lung cancer (NSCLC) with asymptomatic bone metastases (BMs). PATIENTS AND METHODS: Eligible patients were those with resectable NSCLC and asymptomatic BMs. These candidates were randomized into 4 groups: group A was treated with ZA and Sr-89 simultaneously, group B was treated with ZA, group C was treated with Sr-89, and group D was untreated. Patients were monitored and analyzed for the first skeletal-related event (SRE), overall survival (OS), and annual incidence of SREs. RESULTS: One hundred eighty patients were enrolled. Time to first SRE in group A was 15 months (95% confidence interval [CI], 14.0-16.0 months), in group B it was 12 months (95% CI, 11.1-13.0 months), in group C it was 9 months (95% CI, 8.5-9.5 months), and in group D it was 8 months (95% CI, 7.1-8.9 months) (P = .000). The overall survival (OS) in group A was 17 months (95% CI, 16.0-18.1 months); in group B, it was 16 months (95% CI, 14.2-17.8 months); in group C, it was 12 months (95% CI, 11.1-12.9 months); and in group D, it was 12 months (95% CI, 10.8-13.2 months). The annual incidence of SREs in group A was 24.4%; in group B, it was 55.6%; in group C, it was 75.6%; in group D, it was 91.1% (P = .000). CONCLUSIONS: Treatment with ZA and/or Sr-89 significantly extended the time to first SRE as well as survival time and reduced the annual incidence of SREs. Treatment with the combined use of ZA and Sr-89 was safe and well tolerated and achieved the best effect on asymptomatic BMs of NSCLC.

Coffee and tea consumption and risk of lung cancer: a dose-response analysis of observational studies.

Results from the recent meta-analysis suggested a favorable effect of green tea consumption and risk of lung cancer, while no significant association was found between black tea consumption and risk of lung cancer. Besides, a significantly positive association was found between coffee consumption and risk of lung cancer. However, the relationship of green tea and coffee consumption is unclear. Thus the dose-response relationship was assessed by restricted cubic spline model and multivariate random-effect meta-regression. Results suggested that a linear dose-response relationship exists between coffee consumption and risk of lung cancer, while the dose-response relationship is nonlinear between green tea consumption and risk of lung cancer.