Overexpressed Gαi1 exerts pro-tumorigenic activity in nasopharyngeal carcinoma.

The current study tested the expression and potential functions of Gαi1 in nasopharyngeal carcinoma (NPC). The Cancer Genome Atlas (TCGA) database results demonstrate that Gαi1 transcripts' number in NPC tissues is significantly higher than that in the normal nasal epithelial tissues. Its overexpression correlates with poor survival in certain NPC patients.

Hypoxic nasopharyngeal carcinoma-derived exosomal miR-455 increases vascular permeability by targeting ZO-1 to promote metastasis.

Nasopharyngeal carcinoma (NPC), the most frequent reason for treatment failure in head and neck tumors, has the greatest incidence of distant metastases. Increased vascular permeability facilitates metastasis. Exosomal microRNAs (miRNAs) have been implicated in the development of the premetastatic niche and are emerging as prospective biomarkers in cancer patients.

The pro-tumorigenic activity of p38γ overexpression in nasopharyngeal carcinoma.

It is urgent to identify and validate biomarkers for early diagnosis and efficient treatment of nasopharyngeal carcinoma (NPC). Recent studies have proposed p38 gamma (p38γ) as a cyclin-dependent kinase (CDK)-like kinase that phosphorylates retinoblastoma (Rb) to promote cyclins expression and tumorigenesis. Here the Gene Expression Profiling Interactive Analysis (GEPIA) database and results from the local NPC tissues demonstrate that p38γ is significantly upregulated in NPC tissues, correlating with poor overall survival.

HIF-1α downregulation of miR-433-3p in adipocyte-derived exosomes contributes to NPC progression via targeting SCD1.

Resident adipocytes under a hypoxic tumor microenvironment exert an increasingly important role in cell growth, proliferation, and invasion in cancers. However, the communication between adipocytes and cancer cells during nasopharyngeal carcinoma (NPC) progression is poorly understood. Here, we demonstrate that hypoxic adipocyte-derived exosomes are key information carriers that transfer low expression of miR-433-3p into NPC cells.

Transductive Joint-Knowledge-Transfer TSK FS for Recognition of Epileptic EEG Signals.

Intelligent recognition of electroencephalogram (EEG) signals is an important means to detect seizure. Traditional methods for recognizing epileptic EEG signals are usually based on two assumptions: 1) adequate training examples are available for model training and 2) the training set and the test set are sampled from data sets with the same distribution. Since seizures occur sporadically, training examples of seizures could be limited.

Generalized Hidden-Mapping Transductive Transfer Learning for Recognition of Epileptic Electroencephalogram Signals.

Electroencephalogram (EEG) signal identification based on intelligent models is an important means in epilepsy detection. In the recognition of epileptic EEG signals, traditional intelligent methods usually assume that the training dataset and testing dataset have the same distribution, and the data available for training are adequate. However, these two conditions cannot always be met in practice, which reduces the ability of the intelligent recognition model obtained in detecting epileptic EEG signals.

TGF-β1 Promotes Hepatocellular Carcinoma Invasion and Metastasis via ERK Pathway-Mediated FGFR4 Expression.

Background/aims: TGF-β1 is beneficial during early liver disease but is tumor-progressive during late stages especially for hepatocellular carcinoma (HCC). Thus, exploring the underlying mechanisms may provide information about a potentially therapeutic role of TGF-β1 in HCC.

Methods: Western blot and real-time quantitative PCR were used to quantify FGFR4 expression in HCC cell lines and a normal liver cell line.