Colorectal Cancer Prediction Based on Weighted Gene Co-Expression Network Analysis and Variational Auto-Encoder.

An effective feature extraction method is key to improving the accuracy of a prediction model. From the Gene Expression Omnibus (GEO) database, which includes 13,487 genes, we obtained microarray gene expression data for 238 samples from colorectal cancer (CRC) samples and normal samples. Twelve gene modules were obtained by weighted gene co-expression network analysis (WGCNA) on 173 samples. By calculating the Pearson correlation coefficient (PCC) between the characteristic genes of each module and colorectal cancer, we obtained a key module that was highly correlated with CRC. We screened hub genes from the key module by considering module membership, gene significance, and intramodular connectivity. We selected 10 hub genes as a type of feature for the classifier. We used the variational autoencoder (VAE) for 1159 genes with significantly different expressions and mapped the data into a 10-dimensional representation, as another type of feature for the cancer classifier. The two types of features were applied to the support vector machines (SVM) classifier for CRC. The accuracy was 0.9692 with an AUC of 0.9981. The result shows a high accuracy of the two-step feature extraction method, which includes obtaining hub genes by WGCNA and a 10-dimensional representation by variational autoencoder (VAE).

Calculation of immune cell proportion from batch tumor gene expression profile based on support vector regression.

In addition to tumor cells, a large number of immune cells are found in the tumor microenvironment (TME) of cancer patients. Tumor-infiltrating immune cells play an important role in tumor progression and patient outcome. We improved the relative proportion estimation algorithm of immune cells based on RNA-seq gene expression profiling and solved the multiple linear regression model by support vector regression ([Formula: see text]-SVR). These steps resulted in increased robustness of the algorithm and more accurate calculation of the relative proportion of different immune cells in cancer tissues. This method was applied to the analysis of infiltrating immune cells based on 41 pairs of colorectal cancer tissues and normal solid tissues. Specifically, we compared the relative fractions of six types of immune cells in colorectal cancer tissues to those found in normal solid tissue samples. We found that tumor tissues contained a higher proportion of CD8 T cells and neutrophils, while B cells and monocytes were relatively low. Our pipeline for calculating immune cell proportion using gene expression profile data can be freely accessed from GitHub at https://github.com/gutmicrobes/EICS.git.

Induction of cell cycle arrest by increasing GTP­RhoA levels via Taxol­induced microtubule polymerization in renal cell carcinoma.

Renal cell carcinoma (RCC) is the most common neoplasm of the kidney in adults, accounting for ~3% of adult malignancies. Understanding the underlying mechanism of RCC tumorigenesis is necessary to improve patient survival. The present study revealed that Taxol­induced microtubule (MT) polymerization causes cell cycle arrest and an increase in guanosine triphosphate­Ras homology gene family, member A (GTP­RhoA) protein expression. Disruption of Taxol­induced MT polymerization reversed GTP­RhoA expression and cell cycle arrest. The localization and redistribution of MTs and RhoA were consistent in cells with MT bundles and those without. Decreased GTP­RhoA had no marked effect on Taxol­induced MT bundling, however, it reduced the proportion of cells in G2/M phase. Taken together, Taxol­induced MT polymerization regulated the protein expression levels of GTP­RhoA and cell cycle arrest. However, the alteration in GTP­RhoA expression did not influence MT arrangement, suggesting that GTP­RhoA serves a pivotal role in Taxol­induced MT polymerization and cell cycle arrest in RCC.

Dosimetry of electromagnetic field exposure of an active armlet and its electromagnetic interference to the cardiac pacemakers using adult, child and infant models.

Wearable devices have been popularly used with people from different age groups. As a consequence, the concerns of their electromagnetic field (EMF) exposure to the human body and their electromagnetic interference (EMI) to the implanted medical devices have attracted many studies. The aim of this study was to evaluate the human exposure to the EMF of an active radiofrequency identification (RFID) armlet as well as its EMI to the cardiac pacemaker (CP). Different human models from various age groups were applied to assess the result variability. The scalar potential finite element method was utilized in the simulation. Local EMF exposure and the exposure to the central nerve system tissues were evaluated using different metrics. EMI to the CP was assessed in terms of the conducted voltage to the CP. The results from all the models revealed that the studied RFID armlet would not produce the EMF exposure exceeding the safety limits. The calculated interference voltage was highly dependent on the distance between the RFID armlet and the CP (i.e. the physical dimension of the individual model). The results proposed to evaluate the appropriateness of the current EMI measurement protocol for this kind of devices used by the infants.

Evaluation of different classification methods for the diagnosis of schizophrenia based on functional near-infrared spectroscopy.

BACKGROUND: Based on near-infrared spectroscopy (NIRS), recent converging evidence has been observed that patients with schizophrenia exhibit abnormal functional activities in the prefrontal cortex during a verbal fluency task (VFT). Therefore, some studies have attempted to employ NIRS measurements to differentiate schizophrenia patients from healthy controls with different classification methods. However, no systematic evaluation was conducted to compare their respective classification performances on the same study population. NEW METHOD: In this study, we evaluated the classification performance of four classification methods (including linear discriminant analysis, k-nearest neighbors, Gaussian process classifier, and support vector machines) on an NIRS-aided schizophrenia diagnosis. We recruited a large sample of 120 schizophrenia patients and 120 healthy controls and measured the hemoglobin response in the prefrontal cortex during the VFT using a multichannel NIRS system. Features for classification were extracted from three types of NIRS data in each channel. We subsequently performed a principal component analysis (PCA) for feature selection prior to comparison of the different classification methods. RESULTS: We achieved a maximum accuracy of 85.83% and an overall mean accuracy of 83.37% using a PCA-based feature selection on oxygenated hemoglobin signals and support vector machine classifier. COMPARISON WITH EXISTING METHODS: This is the first comprehensive evaluation of different classification methods for the diagnosis of schizophrenia based on different types of NIRS signals. CONCLUSIONS: Our results suggested that, using the appropriate classification method, NIRS has the potential capacity to be an effective objective biomarker for the diagnosis of schizophrenia.

Transcription factor CREB is involved in CaSR-mediated cytoskeleton gene expression.

Our previous studies illustrated that a steady increase of intracellular calcium concentration ([Ca2+]i) was important for maintaining microtubules (MTs) rearrangement in apoptotic cells. However, little is known about the effect of calcium sensing receptor (CaSR)-mediated increase in [Ca2+]i on cytoskeleton gene expression. We examined the impact of taxol or CaSR agonist/antagonist on the regulation of [Ca2+]i concentration, cytoskeleton arrangement, phosphorylated CREB and cytoskeleton gene expressions in HeLa cells with dominant negative plasmid of CREB (PM). This study demonstrated that Gdcl3 (a specific CaSR agonist) evoked a rapid increase of [Ca2+]i, formed a rigid bundle of MTs which surrounded the nucleus and decreased the cytoskeleton gene expressions in HeLa cells. These effects were rescued by addition of NPS2390 (a specific CaSR antagonist). Moreover, CaSR activity affected cytoskeleton gene expression through transcription factor CREB. Histoscores of pCREB immunoreactivity in tissues of cervical adenocarcinoma, renal clear cell carcinoma, and diffuse large B-cell lymphoma were markedly increased compared with non malignant tissue. These data demonstrate, for the first time, that CaSR-mediated increase in [Ca2+]i probably modulate cytoskeleton organization and gene expression via transcription factor.

Reduced prefrontal activation during a verbal fluency task in Chinese-speaking patients with schizophrenia as measured by near-infrared spectroscopy.

Near-infrared spectroscopy (NIRS) has been applied to examine the possible functional alternations during the performance of cognitive tasks in schizophrenia. With this technique, previous studies have observed that patients with schizophrenia are often associated with reduced brain activation in the prefrontal cortex during the verbal fluency task (VFT) of the English version or the Japanese version. However, it remains unclear whether there is a brain functional impairment in Chinese-speaking patients with schizophrenia. In this study, we designed a Chinese version of the VFT and performed a multichannel NIRS study in a large group of patients with schizophrenia and healthy controls. We investigated brain activation during the task period of the Chinese version of the VFT within a schizophrenia group and a healthy group, respectively, and compared the relative changes between the two groups. Our results confirmed that Chinese-speaking patients with schizophrenia had significantly lower brain activation in the prefrontal cortex and superior temporal cortex when compared with healthy controls. Such findings based on the NIRS data provided us reliable evidences about brain functional deficits in the Chinese-speaking patients with schizophrenia.

Generation of a head phantom according to the 95th percentile Chinese population data for evaluating the specific absorption rate by wireless communication devices.

A Chinese head phantom (CHP) is constructed for evaluating the specific absorption rate (SAR) by the wireless transceivers. The dimensions of the head phantom are within 4 % difference compared with the 95th percentile data from the China's standard. The shell's thickness and the configuration of the pinna are the same as those of the specific anthropomorphic mannequin (SAM). Three computable models for the mobile phones are generated and used in the SAR simulations with the SAM and the CHP. The results show that the simulated SAR from the SAM head is similar. Its morphological reason has been analysed. The authors discuss the conservativeness of the two head phantoms as well. The CHP can be used in the inter-laboratory evaluation for the SAR uncertainty. It can also provide the information for the SAR variability due to physical difference, which will benefit the maintenance and the harmonisation of the standards.