IMH-Net: a convolutional neural network for end-to-end EEG motor imagery classification.

As the main component of Brain-computer interface (BCI) technology, the classification algorithm based on EEG has developed rapidly. The previous algorithms were often based on subject-dependent settings, resulting in BCI needing to be calibrated for new users. In this work, we propose IMH-Net, an end-to-end subject-independent model. The model first uses Inception blocks extracts the frequency domain features of the data, then further compresses the feature vectors to extract the spatial domain features, and finally learns the global information and classification through Multi-Head Attention mechanism. On the OpenBMI dataset, IMH-Net obtained 73.90 ± 13.10% accuracy and 73.09 ± 14.99% F1-score in subject-independent manner, which improved the accuracy by 1.96% compared with the comparison model. On the BCI competition IV dataset 2a, this model also achieved the highest accuracy and F1-score in subject-dependent manner. The IMH-Net model we proposed can improve the accuracy of subject-independent Motor Imagery (MI), and the robustness of the algorithm is high, which has strong practical value in the field of BCI.

Optimal whole blood dilution protocol for preprocessing samples prior to circulating tumor cell capture by size-based isolation.

BACKGROUND: This study compared whole blood dilution versus density gradient centrifugation for pre-processing blood samples prior to circulating tumor cell (CTC) capture on the efficiency of CTC separation by size-based isolation. MATERIALS AND METHODS: Whole blood from a healthy volunteer spiked with SKBR3 cells was used to optimize the whole blood dilution protocol for sample volume, dilution ratio, and paraformaldehyde (PFA) concentration. Whole blood from healthy volunteers spiked with SKBR3, A549, or PC3 cells, and whole blood from patients with advanced gastric, esophageal, or liver cancer, was used to compare pre-processing by the optimal whole blood dilution protocol with density-gradient centrifugation. All statistical evaluations were performed using Student t test of the Statistical Package for Social Sciences (SPSS version 17.0). RESULTS: In blood samples from healthy volunteers, spiked SKBR3 cell recovery rates were highest in 5 ml of whole blood, diluted with 2.5 ml buffer, and fixed with 0.2% PFA, and spiked SKBR3, A549, and PC3 cell recovery rates from 5 ml whole blood were significantly greater when using the optimized whole blood dilution protocol (87.67% ± 1.76%, 79.50% ± 0.50% and 71.83% ± 1.04%, respectively) compared to density-gradient centrifugation (46.83 ± 1.76%, 37.00 ± 1.50% and 41.00 ± 1.50%, respectively).

Application of ß-Cyclodextrin metal-organic framework/titanium dioxide hybrid nanocomposite as dispersive solid-phase extraction adsorbent to organochlorine pesticide residues in honey samples.

A simple and efficient dispersive solid-phase extraction (D-SPE) method combined with gas chromatography tandem mass spectrometry (GC-MS/MS) was developed to determine organochlorine pesticides (OCP) in honey. Firstly, a type of hybrid nanocomposite (CD-MOF/TiO2) was prepared by grafting a metal-organic framework material synthesized with cyclodextrin as an organic ligand onto titanium dioxide. Then, the CD-MOF/TiO2 was used as a D-SPE adsorbent to extract the OCP, and the effects of the amount of adsorbent, ultrasonic time, vortex time, pH, and salinity on the extraction were investigated using Plackett-Burman design and Box-Behnken Design. Under the optimized adsorption and desorption conditions, an analysis method that combined D-SPE with GC-MS/MS was established. The linear ranges of 14 OCP are 1-500 µg kg-1 and the correlation coefficients are between 0.9991 and 1.000. The limits of detection and quantification vary from 0.01 to 0.04 µg kg-1 and 0.04 to 0.12 µg kg-1, respectively. The intra-day and inter-day precision of this method are suitable (RSDs% less than 11.3%). The established CD-MOF/TiO2 / D-SPE method was used for the extraction of OCP in honey samples with recovery in the range of 76.4 to 114.3%. The results demonstrate that the CD-MOF/TiO2 has a good selective enrichment ability for OCP and is suitable for the D-SPE pretreat of honey sample analysis.

CYP2C8 Suppress Proliferation, Migration, Invasion and Sorafenib Resistance of Hepatocellular Carcinoma via PI3K/Akt/p27kip1 Axis.

BACKGROUND: Cytochrome P450 2C8 (CYP2C8) gene is one of the members of the cytochrome P450 enzymes (CYPs) gene family. The aim of this study was to reveal the function of CYP2C8 in hepatocellular carcinoma (HCC) and its effect on the sorafenib resistance. METHODS: Differential expression analysis in multiple HCC datasets all suggested that CYP2C8 expression was significantly decreased in HCC tissues, compared with para-carcinoma liver tissues. The expression level of CYP2C8 was subsequently compared between HCC tissues and para-carcinoma liver tissues of 70 patients form Guangxi, China, with the result consistent with the above. Survival analysis and ROC analysis indicated that CYP2C8 was equipped with satisfactory diagnostic and prognostic value in HCC. To examine the effect of CYP2C8 on the malignant phenotype of HCC cells, stable transcriptional cell lines with CYP2C8 over-expression were established, and then Cell Counting Kit-8 (CCK8) assay, colony formation assay, cell cycle assay, cell invasion assay and wound healing assay were performed. RESULTS: The results of aforementioned assays suggested that CYP2C8 over-expression restricted the proliferation, clonality, migration, invasion and cell cycle of HCC cells but had no significant effect on cell apoptosis. The enrichment analysis in terms of sequencing data of HCC cell lines with stable CYP2C8 over-expression suggested that CYP2C8 might be related to PI3K/Akt/p27Kip1 axis. The inhibition of CYP2C8 over-expression on PI3K/Akt/p27Kip1 axis was subsequently demonstrated with Western blot assay. In the rescue experiment, it was observed that both P27 inhibitor and PI3K agonist counteracted the repressed malignant phenotype caused by CYP2C8 over-expression, which further demonstrated that CYP2C8 played a role in HCC cells via PI3K/Akt/p27Kip1 axis. DISCUSSION: The results demonstrated that CYP2C8 enhances the anticancer activity of sorafenib in vitro assays and in tumor xenograft model, with Ki-67 down-regulation and PI3K/Akt/p27Kip1 axis inhibition. In conclusion, these findings hinted that CYP2C8 restricted malignant phenotype and sorafenib resistance in HCC via PI3K/Akt/p27kip1 axis.

Prognostic value of Glypican family genes in early-stage pancreatic ductal adenocarcinoma after pancreaticoduodenectomy and possible mechanisms.

BACKGROUND: This study explored the prognostic significance of Glypican (GPC) family genes in patients with pancreatic ductal adenocarcinoma (PDAC) after pancreaticoduodenectomy using data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). METHODS: A total of 112 PDAC patients from TCGA and 48 patients from GEO were included in the analysis. The relationship between overall survival and the expression of GPC family genes as well as basic clinical characteristics was analyzed using the Kaplan-Meier method with the log-rank test. Joint effects survival analysis was performed to further examine the relationship between GPC genes and prognosis. A prognosis nomogram was established based on clinical characteristics and prognosis-related genes. Prognosis-related genes were investigated by genome-wide co-expression analysis and gene set enrichment analysis (GSEA) was carried out to identify potential mechanisms of these genes affecting prognosis. RESULTS: In TCGA database, high expression of GPC2, GPC3, and GPC5 was significantly associated with favorable survival (log-rank P = 0.031, 0.021, and 0.028, respectively; adjusted P value = 0.005, 0.022, and 0.020, respectively), and joint effects analysis of these genes was effective for prognosis prediction. The prognosis nomogram was applied to predict the survival probability using the total scores calculated. Genome-wide co-expression and GSEA analysis suggested that the GPC2 may affect prognosis through sequence-specific DNA binding, protein transport, cell differentiation and oncogenic signatures (KRAS, RAF, STK33, and VEGFA). GPC3 may be related to cell adhesion, angiogenesis, inflammatory response, signaling pathways like Ras, Rap1, PI3K-Akt, chemokine, GPCR, and signatures like cyclin D1, p53, PTEN. GPC5 may be involved in transcription factor complex, TFRC1, oncogenic signatures (HOXA9 and BMI1), gene methylation, phospholipid metabolic process, glycerophospholipid metabolism, cell cycle, and EGFR pathway. CONCLUSION: GPC2, GPC3, and GPC5 expression may serve as prognostic indicators in PDAC, and combination of these genes showed a higher efficiency for prognosis prediction.