Potential role of PC-1 expression and pyrophosphate elaboration in the molecular etiology of the FGFR-associated craniosynostosis syndromes

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/73652/1/j.1601-6343.2007.00387.x.pd

Bivariate random-effects meta-analysis and the estimation of between-study correlation

BACKGROUND: When multiple endpoints are of interest in evidence synthesis, a multivariate meta-analysis can jointly synthesise those endpoints and utilise their correlation. A multivariate random-effects meta-analysis must incorporate and estimate the between-study correlation (ρ(B)). METHODS: In this paper we assess maximum likelihood estimation of a general normal model and a generalised model for bivariate random-effects meta-analysis (BRMA). We consider two applied examples, one involving a diagnostic marker and the other a surrogate outcome. These motivate a simulation study where estimation properties from BRMA are compared with those from two separate univariate random-effects meta-analyses (URMAs), the traditional approach. RESULTS: The normal BRMA model estimates ρ(B )as -1 in both applied examples. Analytically we show this is due to the maximum likelihood estimator sensibly truncating the between-study covariance matrix on the boundary of its parameter space. Our simulations reveal this commonly occurs when the number of studies is small or the within-study variation is relatively large; it also causes upwardly biased between-study variance estimates, which are inflated to compensate for the restriction on [Formula: see text] (B). Importantly, this does not induce any systematic bias in the pooled estimates and produces conservative standard errors and mean-square errors. Furthermore, the normal BRMA is preferable to two normal URMAs; the mean-square error and standard error of pooled estimates is generally smaller in the BRMA, especially given data missing at random. For meta-analysis of proportions we then show that a generalised BRMA model is better still. This correctly uses a binomial rather than normal distribution, and produces better estimates than the normal BRMA and also two generalised URMAs; however the model may sometimes not converge due to difficulties estimating ρ(B). CONCLUSION: A BRMA model offers numerous advantages over separate univariate synthesises; this paper highlights some of these benefits in both a normal and generalised modelling framework, and examines the estimation of between-study correlation to aid practitioners

Seasonality in depressive and anxiety symptoms among primary care patients and in patients with depressive and anxiety disorders; results from the Netherlands Study of Depression and Anxiety

<p>Abstract</p> <p>Background</p> <p>Little is known about seasonality of specific depressive symptoms and anxiety symptoms in different patient populations. This study aims to assess seasonal variation of depressive and anxiety symptoms in a primary care population and across participants who were classified in diagnostic groups 1) healthy controls 2) patients with a major depressive disorder, 3) patients with any anxiety disorder and 4) patients with a major depression and any anxiety disorder.</p> <p>Methods</p> <p>Data were used from the Netherlands Study of Depression and Anxiety (NESDA). First, in 5549 patients from the NESDA primary care recruitment population the Kessler-10 screening questionnaire was used and data were analyzed across season in a multilevel linear model. Second, in 1090 subjects classified into four groups according to psychiatric status according to the Composite International Diagnostic Interview, overall depressive symptoms and atypical versus melancholic features were assessed with the Inventory of Depressive Symptoms. Anxiety and fear were assessed with the Beck Anxiety Inventory and the Fear questionnaire. Symptom levels across season were analyzed in a linear regression model.</p> <p>Results</p> <p>In the primary care population the severity of depressive and anxiety symptoms did not show a seasonal pattern. In the diagnostic groups healthy controls and patients with any anxiety disorder, but not patients with a major depressive disorder, showed a small rise in depressive symptoms in winter. Atypical and melancholic symptoms were both elevated in winter. No seasonal pattern for anxiety symptoms was found. There was a small gender related seasonal effect for fear symptoms.</p> <p>Conclusions</p> <p>Seasonal differences in severity or type of depressive and anxiety symptoms, as measured with a general screening instrument and symptom questionnaires, were absent or small in effect size in a primary care population and in patient populations with a major depressive disorder and anxiety disorders.</p

Metastatic lymph node in gastric cancer; Is it a real distant metastasis?

<p>Abstract</p> <p>Background</p> <p>Currently, the TNM staging system is a widely accepted method for assessing the prognosis of the disease and planning therapeutic strategies for cancer. Of the TNM system, the extent of lymph node involvement is the most important independent prognostic factor for gastric cancer. The aim of our study is to evaluate the survival and prognosis of gastric cancer patients with LN#12 or #13 involvement only and to assess the impact of anatomic regions of primary gastric tumor on survival in this particular subset of patients.</p> <p>Methods</p> <p>Among data of 1,008 stage IV gastric cancer patients who received curative R0 gastrectomy, a total of 79 patients with LN#12 (n = 68) and/or #13 (n = 11) were identified. All patients performed gastrectomy with D2 or D3 lymph node dissection.</p> <p>Results</p> <p>In 79 patients with LN#12/13 involvement, the estimated one-, three- and five-year survival rate was 77.2%, 41.8% and 26.6% respectively. When we compared the patients with LN#12/13 involvement to those without involvement, there was no significant difference in OS (21.0 months vs. 25.0 months, respectively; P = 0.140). However, OS was significantly longer in patients with LN#12/13 involvement only than in those with M1 lymph node involvement (14.3 months; P = 0.001). There was a significant difference in survival according to anatomic locations of the primary tumor (lower to mid-body vs. high body or whole stomach): 26.5 vs. 9.2 months (P = 0.009). In Cox proportional hazard analysis, only N stage (p = 0.002) had significance to predict poor survival.</p> <p>Conclusion</p> <p>In this study we found that curatively resected gastric cancer patients with pathologic involvement of LN #12 and/or LN #13 had favorable survival outcome, especially those with primary tumor location of mid-body to antrum. Prospective analysis of survival in gastric cancer patients with L N#12 or #13 metastasis is warranted especially with regards to primary tumor location.</p

Phosphorylation State-Dependent Interactions of Hepadnavirus Core Protein with Host Factors

Dynamic phosphorylation and dephosphorylation of the hepadnavirus core protein C-terminal domain (CTD) are required for multiple steps of the viral life cycle. It remains unknown how the CTD phosphorylation state may modulate core protein functions but phosphorylation state-dependent viral or host interactions may play a role. In an attempt to identify host factors that may interact differentially with the core protein depending on its CTD phosphorylation state, pulldown assays were performed using the CTD of the duck hepatitis B virus (DHBV) and human hepatitis B virus (HBV) core protein, either with wild type (WT) sequences or with alanine or aspartic acid substitutions at the phosphorylation sites. Two host proteins, B23 and I2PP2A, were found to interact preferentially with the alanine-substituted CTD. Furthermore, the WT CTD became competent to interact with the host proteins upon dephosphorylation. Intriguingly, the binding site on the DHBV CTD for both B23 and I2PP2A was mapped to a region upstream of the phosphorylation sites even though B23 or I2PP2A binding to this site was clearly modulated by the phosphorylation state of the downstream and non-overlapping sequences. Together, these results demonstrate a novel mode of phosphorylation-regulated protein-protein interaction and provide new insights into virus-host interactions

Secretome-Based Identification of ULBP2 as a Novel Serum Marker for Pancreatic Cancer Detection

BACKGROUND: To discover novel markers for improving the efficacy of pancreatic cancer (PC) diagnosis, the secretome of two PC cell lines (BxPC-3 and MIA PaCa-2) was profiled. UL16 binding protein 2 (ULBP2), one of the proteins identified in the PC cell secretome, was selected for evaluation as a biomarker for PC detection because its mRNA level was also found to be significantly elevated in PC tissues. METHODS: ULBP2 expression in PC tissues from 67 patients was studied by immunohistochemistry. ULBP2 serum levels in 154 PC patients and 142 healthy controls were measured by bead-based immunoassay, and the efficacy of serum ULBP2 for PC detection was compared with the widely used serological PC marker carbohydrate antigen 19-9 (CA 19-9). RESULTS: Immunohistochemical analyses revealed an elevated expression of ULPB2 in PC tissues compared with adjacent non-cancerous tissues. Meanwhile, the serum levels of ULBP2 among all PC patients (n = 154) and in early-stage cancer patients were significantly higher than those in healthy controls (p<0.0001). The combination of ULBP2 and CA 19-9 outperformed each marker alone in distinguishing PC patients from healthy individuals. Importantly, an analysis of the area under receiver operating characteristic curves showed that ULBP2 was superior to CA 19-9 in discriminating patients with early-stage PC from healthy controls. CONCLUSIONS: Collectively, our results indicate that ULBP2 may represent a novel and useful serum biomarker for pancreatic cancer primary screening

Predicting sulfotyrosine sites using the random forest algorithm with significantly improved prediction accuracy

addresses: School of Biosciences, University of Exeter, Exeter EX4 5DE, UK. [email protected]: PMCID: PMC2777180types: Journal Article; Research Support, Non-U.S. Gov't© 2009 Yang; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Tyrosine sulfation is one of the most important posttranslational modifications. Due to its relevance to various disease developments, tyrosine sulfation has become the target for drug design. In order to facilitate efficient drug design, accurate prediction of sulfotyrosine sites is desirable. A predictor published seven years ago has been very successful with claimed prediction accuracy of 98%. However, it has a particularly low sensitivity when predicting sulfotyrosine sites in some newly sequenced proteins

Impacts of excision repair cross-complementing gene 1 (ERCC1), dihydropyrimidine dehydrogenase, and epidermal growth factor receptor on the outcomes of patients with advanced gastric cancer

Using laser-captured microdissection and a real-time RT–PCR assay, we quantitatively evaluated mRNA levels of the following biomarkers in paraffin-embedded gastric cancer (GC) specimens obtained by surgical resection or biopsy: excision repair cross-complementing gene 1 (ERCC1), dihydropyrimidine dehydrogenase (DPD), methylenetetrahydrofolate reductase (MTHFR), epidermal growth factor receptor (EGFR), and five other biomarkers related to anticancer drug sensitivity. The study group comprised 140 patients who received first-line chemotherapy for advanced GC. All cancer specimens were obtained before chemotherapy. In patients who received first-line S-1 monotherapy (69 patients), low MTHFR expression correlated with a higher response rate (low: 44.9% vs high: 6.3%; P=0.006). In patients given first-line cisplatin-based regimens (combined with S-1 or irinotecan) (43 patients), low ERCC1 correlated with a higher response rate (low: 55.6% vs high: 18.8%; P=0.008). Multivariate survival analysis of all patients demonstrated that high ERCC1 (hazard ratio (HR): 2.38 (95% CI: 1.55–3.67)), high DPD (HR: 2.04 (1.37–3.02)), low EGFR (HR: 0.34 (0.20–0.56)), and an elevated serum alkaline phosphatase level (HR: 1.00 (1.001–1.002)) were significant predictors of poor survival. Our results suggest that these biomarkers are useful predictors of clinical outcomes in patients with advanced GC