Clinical significance of heparin-binding epidermal growth factor-like growth factor in peritoneal fluid of ovarian cancer

Epidermal growth factor receptor (EGFR) has been implicated in tumour growth and extension of ovarian cancer. Peritoneal fluid in ovarian cancer patients contains various growth factors that can promote tumour growth and extension. In order to investigate the clinical significance of EGFR ligands as activating factors of ovarian cancer, we examined the cell proliferation-promoting activity and the level of EGFR ligands in peritoneal fluid obtained from 99 patients. Proliferation-promoting activity in peritoneal fluid from 63 ovarian cancer patients (OVCA) was much higher than peritoneal fluid from 18 ovarian cyst patients (OVC) and 18 normal ovary patients (NO), and the activity was suppressed only by antibodies against EGFR or heparin-binding epidermal growth factor (HB-EGF). A large difference was observed in the level of EGFR ligands between HB-EGF and TGF-α or amphiregulin. The concentration of HB-EGF in OVCA significantly increased compared to that in OVC or NO (P<0.01). No significant difference in the concentration of TGF-α and amphiregulin was found between the OVCA and NO or OVC groups. In peritoneal fluid, HB-EGF is sufficiently elevated to activate cancer cells even at an early stage of OVCA. These results suggested that HB-EGF in peritoneal fluid might play a key role in cell survival and in the proliferation of OVCA

Activation of Type I and III Interferon Signalling Pathways Occurs in Lung Epithelial Cells Infected with Low Pathogenic Avian Influenza Viruses

The host response to the low pathogenic avian influenza (LPAI) H5N2, H5N3 and H9N2 viruses were examined in A549, MDCK, and CEF cells using a systems-based approach. The H5N2 and H5N3 viruses replicated efficiently in A549 and MDCK cells, while the H9N2 virus replicated least efficiently in these cell types. However, all LPAI viruses exhibited similar and higher replication efficiencies in CEF cells. A comparison of the host responses of these viruses and the H1N1/WSN virus and low passage pH1N1 clinical isolates was performed in A549 cells. The H9N2 and H5N2 virus subtypes exhibited a robust induction of Type I and Type III interferon (IFN) expression, sustained STAT1 activation from between 3 and 6 hpi, which correlated with large increases in IFN-stimulated gene (ISG) expression by 10 hpi. In contrast, cells infected with the pH1N1 or H1N1/WSN virus showed only small increases in Type III IFN signalling, low levels of ISG expression, and down-regulated expression of the IFN type I receptor. JNK activation and increased expression of the pro-apoptotic XAF1 protein was observed in A549 cells infected with all viruses except the H1N1/WSN virus, while MAPK p38 activation was only observed in cells infected with the pH1N1 and the H5 virus subtypes. No IFN expression and low ISG expression levels were generally observed in CEF cells infected with either AIV, while increased IFN and ISG expression was observed in response to the H1N1/WSN infection. These data suggest differences in the replication characteristics and antivirus signalling responses both among the different LPAI viruses, and between these viruses and the H1N1 viruses examined. These virus-specific differences in host cell signalling highlight the importance of examining the host response to avian influenza viruses that have not been extensively adapted to mammalian tissue culture

Economic and Environmental Impacts of Harmful Non-Indigenous Species in Southeast Asia

10.1371/journal.pone.0071255PLoS ONE88-POLN

The Connectome Visualization Utility: Software for Visualization of Human Brain Networks

In analysis of the human connectome, the connectivity of the human brain is collected from multiple imaging modalities and analyzed using graph theoretical techniques. The dimensionality of human connectivity data is high, and making sense of the complex networks in connectomics requires sophisticated visualization and analysis software. The current availability of software packages to analyze the human connectome is limited. The Connectome Visualization Utility (CVU) is a new software package designed for the visualization and network analysis of human brain networks. CVU complements existing software packages by offering expanded interactive analysis and advanced visualization features, including the automated visualization of networks in three different complementary styles and features the special visualization of scalar graph theoretical properties and modular structure. By decoupling the process of network creation from network visualization and analysis, we ensure that CVU can visualize networks from any imaging modality. CVU offers a graphical user interface, interactive scripting, and represents data uses transparent neuroimaging and matrix-based file types rather than opaque application-specific file formats

ATP-Sensitive Potassium Channels Exhibit Variance in the Number of Open Channels below the Limit Predicted for Identical and Independent Gating

In small cells containing small numbers of ion channels, noise due to stochastic channel opening and closing can introduce a substantial level of variability into the cell's membrane potential. Negatively cooperative interactions that couple a channel's gating conformational change to the conformation of its neighbor(s) provide a potential mechanism for mitigating this variability, but such interactions have not previously been directly observed. Here we show that heterologously expressed ATP-sensitive potassium channels generate noise (i.e., variance in the number of open channels) below the level possible for identical and independent channels. Kinetic analysis with single-molecule resolution supports the interpretation that interchannel negative cooperativity (specifically, the presence of an open channel making a closed channel less likely to open) contributes to the decrease in noise. Functional coupling between channels may be important in modulating stochastic fluctuations in cellular signaling pathways

Local Signal Time-Series during Rest Used for Areal Boundary Mapping in Individual Human Brains

It is widely thought that resting state functional connectivity likely reflects functional interaction among brain areas and that different functional areas interact with different sets of brain areas. A method for mapping areal boundaries has been formulated based on the large-scale spatial characteristics of regional interaction revealed by resting state functional connectivity. In the present study, we present a novel analysis for areal boundary mapping that requires only the signal timecourses within a region of interest, without reference to the information from outside the region. The areal boundaries were generated by the novel analysis and were compared with those generated by the previously-established standard analysis. The boundaries were robust and reproducible across the two analyses, in two regions of interest tested. These results suggest that the information for areal boundaries is readily available inside the region of interest

Combinations of Host Biomarkers Predict Mortality among Ugandan Children with Severe Malaria: A Retrospective Case-Control Study

Background: Severe malaria is a leading cause of childhood mortality in Africa. However, at presentation, it is difficult to predict which children with severe malaria are at greatest risk of death. Dysregulated host inflammatory responses and endothelial activation play central roles in severe malaria pathogenesis. We hypothesized that biomarkers of these processes would accurately predict outcome among children with severe malaria. Methodology/Findings: Plasma was obtained from children with uncomplicated malaria (n = 53), cerebral malaria (n = 44) and severe malarial anemia (n = 59) at time of presentation to hospital in Kampala, Uganda. Levels of angiopoietin-2, von Willebrand Factor (vWF), vWF propeptide, soluble P-selectin, soluble intercellular adhesion molecule-1 (ICAM-1), soluble endoglin, soluble FMS-like tyrosine kinase-1 (Flt-1), soluble Tie-2, C-reactive protein, procalcitonin, 10 kDa interferon gamma-induced protein (IP-10), and soluble triggering receptor expressed on myeloid cells-1 (TREM-1) were determined by ELISA. Receiver operating characteristic (ROC) curve analysis was used to assess predictive accuracy of individual biomarkers. Six biomarkers (angiopoietin-2, soluble ICAM-1, soluble Flt-1, procalcitonin, IP-10, soluble TREM-1) discriminated well between children who survived severe malaria infection and those who subsequently died (area under ROC curve&gt;0.7). Combinational approaches were applied in an attempt to improve accuracy. A biomarker score was developed based on dichotomization and summation of the six biomarkers, resulting in 95.7% (95% CI: 78.1-99.9) sensitivity and 88.8% (79.7-94.7) specificity for predicting death. Similar predictive accuracy was achieved with models comprised of 3 biomarkers. Classification tree analysis generated a 3-marker model with 100% sensitivity and 92.5% specificity (cross-validated misclassification rate: 15.4%, standard error 4.9%). Conclusions: We identified novel host biomarkers of pediatric severe and fatal malaria (soluble TREM-1 and soluble Flt-1) and generated simple biomarker combinations that accurately predicted death in an African pediatric population. While requiring validation in further studies, these results suggest the utility of combinatorial biomarker strategies as prognostic tests for severe malaria

An Observational Cohort Study of the Kynurenine to Tryptophan Ratio in Sepsis: Association with Impaired Immune and Microvascular Function

Both endothelial and immune dysfunction contribute to the high mortality rate in human sepsis, but the underlying mechanisms are unclear. In response to infection, interferon-γ activates indoleamine 2,3-dioxygenase (IDO) which metabolizes the essential amino acid tryptophan to the toxic metabolite kynurenine. IDO can be expressed in endothelial cells, hepatocytes and mononuclear leukocytes, all of which contribute to sepsis pathophysiology. Increased IDO activity (measured by the kynurenine to tryptophan [KT] ratio in plasma) causes T-cell apoptosis, vasodilation and nitric oxide synthase inhibition. We hypothesized that IDO activity in sepsis would be related to plasma interferon-γ, interleukin-10, T cell lymphopenia and impairment of microvascular reactivity, a measure of endothelial nitric oxide bioavailability. In an observational cohort study of 80 sepsis patients (50 severe and 30 non-severe) and 40 hospital controls, we determined the relationship between IDO activity (plasma KT ratio) and selected plasma cytokines, sepsis severity, nitric oxide-dependent microvascular reactivity and lymphocyte subsets in sepsis. Plasma amino acids were measured by high performance liquid chromatography and microvascular reactivity by peripheral arterial tonometry. The plasma KT ratio was increased in sepsis (median 141 [IQR 64–235]) compared to controls (36 [28–52]); p<0.0001), and correlated with plasma interferon-γ and interleukin-10, and inversely with total lymphocyte count, CD8+ and CD4+ T-lymphocytes, systolic blood pressure and microvascular reactivity. In response to treatment of severe sepsis, the median KT ratio decreased from 162 [IQR 100–286] on day 0 to 89 [65–139] by day 7; p = 0.0006) and this decrease in KT ratio correlated with a decrease in the Sequential Organ Failure Assessment score (p<0.0001). IDO-mediated tryptophan catabolism is associated with dysregulated immune responses and impaired microvascular reactivity in sepsis and may link these two fundamental processes in sepsis pathophysiology

Identification of MicroRNA-21 as a Biomarker for Chemoresistance and Clinical Outcome Following Adjuvant Therapy in Resectable Pancreatic Cancer

Pancreatic ductal adenocarcinoma (PDAC) has a dismal prognosis. The high risk of recurrence following surgical resection provides the rationale for adjuvant therapy. However, only a subset of patients benefit from adjuvant therapy. Identification of molecular markers to predict treatment outcome is therefore warranted. The aim of the present study was to evaluate whether expression of novel candidate biomarkers, including microRNAs, can predict clinical outcome in PDAC patients treated with adjuvant therapy.Formalin-fixed paraffin embedded specimens from a cohort of 82 resected Korean PDAC cases were analyzed for protein expression by immunohistochemistry and for microRNA expression using quantitative Real-Time PCR. Cox proportional hazards model analysis in the subgroup of patients treated with adjuvant therapy (N = 52) showed that lower than median miR-21 expression was associated with a significantly lower hazard ratio (HR) for death (HR = 0.316; 95%CI = 0.166–0.600; P = 0.0004) and recurrence (HR = 0.521; 95%CI = 0.280–0.967; P = 0.04). MiR-21 expression status emerged as the single most predictive biomarker for treatment outcome among all 27 biological and 9 clinicopathological factors evaluated. No significant association was detected in patients not treated with adjuvant therapy. In an independent validation cohort of 45 frozen PDAC tissues from Italian cases, all treated with adjuvant therapy, lower than median miR-21 expression was confirmed to be correlated with longer overall as well as disease-free survival. Furthermore, transfection with anti-miR-21 enhanced the chemosensitivity of PDAC cells.. These data provide evidence that miR-21 may allow stratification for adjuvant therapy, and represents a new potential target for therapy in PDAC

Measuring macroscopic brain connections in vivo

Decades of detailed anatomical tracer studies in non-human animals point to a rich and complex organization of long-range white matter connections in the brain. State-of-the art in vivo imaging techniques are striving to achieve a similar level of detail in humans, but multiple technical factors can limit their sensitivity and fidelity. In this review, we mostly focus on magnetic resonance imaging of the brain. We highlight some of the key challenges in analyzing and interpreting in vivo connectomics data, particularly in relation to what is known from classical neuroanatomy in laboratory animals. We further illustrate that, despite the challenges, in vivo imaging methods can be very powerful and provide information on connections that is not available by any other means