OCIAD2 suppressed tumor growth and invasion via AKT pathway in Hepatocelluar carcinoma.

Hepatocellular carcinoma (HCC) is an aggressive tumor and the third leading cause of cancer-related death worldwide. Ovarian carcinoma immunoreactive antigen-like protein 2 (OCIAD2) has been found frequently methylated in various cancers, including HCC. The aim of the present study was to investigate the role of OCIAD2 in HCC progression. We analyzed liver hepatocellular carcinoma patients' data from the Cancer Genome Atlas (TCGA), including data extracted from 371 HCC tissues and 50 adjacent normal liver tissues. The RNA sequencing and DNA methylation data revealed that OCIAD2 were significantly hypermethylated and its expression level in the tumor tissues was much lower than that in the corresponding adjacent normal tissues. The methylation level in the promoter was negatively correlated with the expression level of OCAID2. Treatment of HCC cell lines with the DNA methylation inhibitor 5-aza-2'-deoxycitydine (5-Aza) induced a significant increase in the OCIAD2 mRNA and protein. Knocking-down OCIAD2 led to an increased colony formation, migration and invasion dramatically, accompanying with an enhanced expression of MMP9 and activation of AKT and FAK. Inhibition of AKT signaling restored OCIAD2-mediated changes in HCC cell clonogenic growth, migration and invasion. Survival analysis of HCC patient's data indicated patients with a higher expression ratio of OCIAD2/MMP9 had a shorter overall survival than those with a lower expression ratio of OCIAD2/MMP9. Overall, our data indicate that reduced expression of OCIAD2 by DNA hypermethylation plays an important role in HCC tumor growth and invasion. Hypermethylation of OCIAD2 may contribute to HCC treatment development.

Systemic treatment with GnRH agonist produces antidepressant-like effects in LPS induced depression male mouse model.

Gonadotropin-releasing hormone (GnRH) is at the head of the neuroendocrine reproductive axis. However, the non-reproductive functions of GnRH expressed in various tissues, including hippocampus, are still not known. Here, we unveil a previously unknown effect of GnRH, which mediates depression-like behaviors through the modulation of microglia function during immune challenge. Specifically, we found that either systemic treatment with GnRH agonist or over-expression of endogenous hippocampal GnRH via viral tool abolished the depression-like behavior after LPS challenges in mice. And the anti-depressant of GnRH was dependent on the hippocampal GnRHR signaling, since antagonizing GnRHR by drug treatment or by hippocampal GnRHR knockdown could block the antidepressant-effect of GnRH agonist. Interestingly, we found that the peripheral GnRH treatment prevented the microglia activation mediated inflammation in the hippocampus of mice. In light of the research findings presented here, we propose that, at least in the hippocampus, GnRH appears to act on GnRHR to regulate higher order non-reproductive functions associated with the microglia mediated neuroinflammation. These findings also provide insights into the function and cross-talk of GnRH, a known neuropeptide hormone, in neuro-immune response.

LSCC SNP variant regulates SOX2 modulation of VDAC3.

Lung squamous cell carcinoma (LSCC) is a genomically complex malignancy with no effective treatments. Recent studies have found a large number of DNA alterations such as SOX2 amplification in LSCC patients. As a stem cell transcription factor, SOX2 is important for the maintenance of pluripotent cells and may play a role in cancer. To study the downstream mechanisms of SOX2, we employed expression quantitative trait loci (eQTLs) technology to investigate how the presence of SOX2 affects the expression of target genes. We discovered unique eQTLs, such as rs798827-VDAC3 (FDR p-value = 0.0034), that are only found in SOX2-active patients but not in SOX2-inactive patients. SNP rs798827 is within strong linkage disequilibrium (r2 = 1) to rs58163073, where rs58163073 [T] allele increases the binding affinity of SOX2 and allele [TA] decreases it. In our analysis, SOX2 silencing downregulates VDAC3 in two LSCC cell lines. Chromatin conformation capturing data indicates that this SNP is located within the same Topologically Associating Domain (TAD) of VDAC3, further suggesting SOX2's role in the regulation of VDAC3 through the binding of rs58163073. By first subgrouping patients based on SOX2 activity, we made more relevant eQTL discoveries and our analysis can be applied to other diseases.

FGF21 protects human umbilical vein endothelial cells against high glucose-induced apoptosis via PI3K/Akt/Fox3a signaling pathway.

AIMS: Diabetic macroangiopathy is the main cause of morbidity and mortality in patients with diabetes. Endothelial cell injury is a pathological precondition for diabetic macroangiopathy. Fibroblast growth factor 21 (FGF21) is a key metabolic regulator which has recently been suggested to protect cardiac myocytes and vascular cells against oxidative stress-induced injury in vitro and vivo. In this study, we aimed to investigate the protective capacity of FGF21 in human umbilical vein endothelial cells (HUVECs) against high glucose (HG)-induced apoptosis via phosphatidylinositol-3-kinase/protein kinase B (PI3K/Akt)/FoxO3a pathway. METHODS: The cell viability was examined by CCK-8 assay, Intracellular ROS levels were measured by the detection of the fluorescent product formed by the oxidation of DCFH-DA, Apoptosis was analyzed using Hoechst 33258 nuclear staining and Flow Cytometry Analysis (FCA), the expression of protein were detected by Western blot. RESULTS: Results show that pretreating HUVECs with FGF21 before exposure to HG increases cell viability, while decreasing apoptosis and the generation of reactive oxygen species. Western blot analysis shows that HG reduces the phosphorylation of Akt and FoxO3a, and induces nuclear localization of FoxO3a. The effects were significantly reversed by FGF21 pre-treatment. Furthermore, the protective effects of FGF21 were prevented by PI3K/Akt inhibitor LY294002. CONCLUSIONS: Our data demonstrates that FGF21 protects HUVECs from HG-induced oxidative stress and apoptosis via the activation of PI3K/Akt/FoxO3a signaling pathway.

Multi-scale modeling for the transmission of influenza and the evaluation of interventions toward it.

Mathematical modeling of influenza epidemic is important for analyzing the main cause of the epidemic and finding effective interventions towards it. The epidemic is a dynamic process. In this process, daily infections are caused by people's contacts, and the frequency of contacts can be mainly influenced by their cognition to the disease. The cognition is in turn influenced by daily illness attack rate, climate, and other environment factors. Few existing methods considered the dynamic process in their models. Therefore, their prediction results can hardly be explained by the mechanisms of epidemic spreading. In this paper, we developed a heterogeneous graph modeling approach (HGM) to describe the dynamic process of influenza virus transmission by taking advantage of our unique clinical data. We built social network of studied region and embedded an Agent-Based Model (ABM) in the HGM to describe the dynamic change of an epidemic. Our simulations have a good agreement with clinical data. Parameter sensitivity analysis showed that temperature influences the dynamic of epidemic significantly and system behavior analysis showed social network degree is a critical factor determining the size of an epidemic. Finally, multiple scenarios for vaccination and school closure strategies were simulated and their performance was analyzed.

Red blood cell tracking using optical flow methods.

The investigation of microcirculation is an important task in biomedical and physiological research because the microcirculation information, such as flow velocity and vessel density, is critical to monitor human conditions and develop effective therapies of some diseases. As one of the tasks of the microcirculation study, red blood cell (RBC) tracking presents an effective approach to estimate some parameters in microcirculation. The common method for RBC tracking is based on spatiotemporal image analysis, which requires the image to have high qualification and cells should have fixed velocity. Besides, for in vivo cell tracking, cells may disappear in some frames, image series may have spatial and temporal distortions, and vessel distribution can be complex, which increase the difficulties of RBC tracking. In this paper, we propose an optical flow method to track RBCs. It attempts to describe the local motion for each visible point in the frames using a local displacement vector field. We utilize it to calculate the displacement of a cell in two adjacent frames. Additionally, another optical flow-based method, scale invariant feature transform (SIFT) flow, is also presented. The experimental results show that optical flow is quite robust to the case where the velocity of cell is unstable, while SIFT flow works well when there is a large displacement of the cell between two adjacent frames. Our proposed methods outperform other methods when doing in vivo cell tracking, which can be used to estimate the blood flow directly and help to evaluate other parameters in microcirculation.

Computational modeling of 3D tumor growth and angiogenesis for chemotherapy evaluation.

Solid tumors develop abnormally at spatial and temporal scales, giving rise to biophysical barriers that impact anti-tumor chemotherapy. This may increase the expenditure and time for conventional drug pharmacokinetic and pharmacodynamic studies. In order to facilitate drug discovery, we propose a mathematical model that couples three-dimensional tumor growth and angiogenesis to simulate tumor progression for chemotherapy evaluation. This application-oriented model incorporates complex dynamical processes including cell- and vascular-mediated interstitial pressure, mass transport, angiogenesis, cell proliferation, and vessel maturation to model tumor progression through multiple stages including tumor initiation, avascular growth, and transition from avascular to vascular growth. Compared to pure mechanistic models, the proposed empirical methods are not only easy to conduct but can provide realistic predictions and calculations. A series of computational simulations were conducted to demonstrate the advantages of the proposed comprehensive model. The computational simulation results suggest that solid tumor geometry is related to the interstitial pressure, such that tumors with high interstitial pressure are more likely to develop dendritic structures than those with low interstitial pressure.

A novel breath analysis system based on electronic olfaction.

Certain gases in the breath are known to be indicators of the presence of diseases and clinical conditions. These gases have been identified as biomarkers using equipments such as gas chromatography (GC) and electronic nose (e-nose). GC is very accurate but is expensive, time consuming, and non-portable. E-nose has the advantages of low-cost and easy operation, but is not particular for analyzing breath odor and hence has a limited application in diseases diagnosis. This article proposes a novel system that is special for breath analysis. We selected chemical sensors that are sensitive to the biomarkers and compositions in human breath, developed the system, and introduced the odor signal preprocessing and classification method. To evaluate the system performance, we captured breath samples from healthy persons and patients known to be afflicted with diabetes, renal disease, and airway inflammation repectively and conducted experiments on medical treatment evaluation and disease identification. The results show that the system is not only able to distinguish between breath samples from subjects suffering from various diseases or conditions (diabetes, renal disease, and airway inflammation) and breath samples from healthy subjects, but in the case of renal failure is also helpful in evaluating the efficacy of hemodialysis (treatment for renal failure).