Forced decadal changes in the East Asian summer monsoon: the roles of greenhouse gases and anthropogenic aerosols

Since the mid-1990s precipitation trends over eastern China display a dipole pattern, characterized by positive anomalies in the south and negative anomalies in the north, named as the Southern-Flood-Northern-Drought (SFND) pattern. This work investigates the drivers of decadal changes of the East Asian summer monsoon (EASM), and the dynamical mechanisms involved, by using a coupled climate model (specifically an atmospheric general circulation model coupled to an ocean mixed layer model) forced by changes in (1) anthropogenic greenhouse gases (GHG), (2) anthropogenic aerosol (AA) and (3) the combined effects of both GHG and AA (All Forcing) between two periods across the mid-1990s. The model experiment forced by changes in All Forcing shows a dipole pattern of response in precipitation over China that is similar to the observed SFND pattern across the mid-1990s, which suggests that anthropogenic forcing changes played an important role in the observed decadal changes. Furthermore, the experiments with separate forcings indicate that GHG and AA forcing dominate different parts of the SFND pattern. In particular, changes in GHG increase precipitation over southern China, whilst changes in AA dominate in the drought conditions over northern China. Increases in GHG cause increased moisture transport convergence over eastern China, which leads to increased precipitation. The AA forcing changes weaken the EASM, which lead to divergent wind anomalies over northern China and reduced precipitation

Estimation of progression of multi-state chronic disease using the Markov model and prevalence pool concept

<p>Abstract</p> <p>Background</p> <p>We propose a simple new method for estimating progression of a chronic disease with multi-state properties by unifying the prevalence pool concept with the Markov process model.</p> <p>Methods</p> <p>Estimation of progression rates in the multi-state model is performed using the E-M algorithm. This approach is applied to data on Type 2 diabetes screening.</p> <p>Results</p> <p>Good convergence of estimations is demonstrated. In contrast to previous Markov models, the major advantage of our proposed method is that integrating the prevalence pool equation (that the numbers entering the prevalence pool is equal to the number leaving it) into the likelihood function not only simplifies the likelihood function but makes estimation of parameters stable.</p> <p>Conclusion</p> <p>This approach may be useful in quantifying the progression of a variety of chronic diseases.</p

Fifteen new risk loci for coronary artery disease highlight arterial-wall-specific mechanisms

Coronary artery disease (CAD) is a leading cause of morbidity and mortality worldwide. Although 58 genomic regions have been associated with CAD thus far, most of the heritability is unexplained, indicating that additional susceptibility loci await identification. An efficient discovery strategy may be larger-scale evaluation of promising associations suggested by genome-wide association studies (GWAS). Hence, we genotyped 56,309 participants using a targeted gene array derived from earlier GWAS results and performed meta-analysis of results with 194,427 participants previously genotyped, totaling 88,192 CAD cases and 162,544 controls. We identified 25 new SNP-CAD associations (P &lt; 5 × 10(-8), in fixed-effects meta-analysis) from 15 genomic regions, including SNPs in or near genes involved in cellular adhesion, leukocyte migration and atherosclerosis (PECAM1, rs1867624), coagulation and inflammation (PROCR, rs867186 (p.Ser219Gly)) and vascular smooth muscle cell differentiation (LMOD1, rs2820315). Correlation of these regions with cell-type-specific gene expression and plasma protein levels sheds light on potential disease mechanisms

MetNetAPI: A flexible method to access and manipulate biological network data from MetNet

<p>Abstract</p> <p>Background</p> <p>Convenient programmatic access to different biological databases allows automated integration of scientific knowledge. Many databases support a function to download files or data snapshots, or a webservice that offers "live" data. However, the functionality that a database offers cannot be represented in a static data download file, and webservices may consume considerable computational resources from the host server.</p> <p>Results</p> <p>MetNetAPI is a versatile Application Programming Interface (API) to the MetNetDB database. It abstracts, captures and retains operations away from a biological network repository and website. A range of database functions, previously only available online, can be immediately (and independently from the website) applied to a dataset of interest. Data is available in four layers: molecular entities, localized entities (linked to a specific organelle), interactions, and pathways. Navigation between these layers is intuitive (e.g. one can request the molecular entities in a pathway, as well as request in what pathways a specific entity participates). Data retrieval can be customized: Network objects allow the construction of new and integration of existing pathways and interactions, which can be uploaded back to our server. In contrast to webservices, the computational demand on the host server is limited to processing data-related queries only.</p> <p>Conclusions</p> <p>An API provides several advantages to a systems biology software platform. MetNetAPI illustrates an interface with a central repository of data that represents the complex interrelationships of a metabolic and regulatory network. As an alternative to data-dumps and webservices, it allows access to a current and "live" database and exposes analytical functions to application developers. Yet it only requires limited resources on the server-side (thin server/fat client setup). The API is available for Java, Microsoft.NET and R programming environments and offers flexible query and broad data- retrieval methods. Data retrieval can be customized to client needs and the API offers a framework to construct and manipulate user-defined networks. The design principles can be used as a template to build programmable interfaces for other biological databases. The API software and tutorials are available at <url>http://www.metnetonline.org/api</url>.</p

Tailoring Adjuvant Endocrine Therapy for Postmenopausal Breast Cancer: A CYP2D6 Multiple-Genotype-Based Modeling Analysis and Validation

Purpose: Previous studies have suggested that postmenopausal women with breast cancer who present with wild-type CYP2D6 may actually have similar or superior recurrence-free survival outcomes when given tamoxifen in place of aromatase inhibitors (AIs). The present study established a CYP2D6 multiple-genotype-based model to determine the optimal endocrine therapy for patients harboring wild-type CYP2D6. Methods: We created a Markov model to determine whether tamoxifen or AIs maximized 5-year disease-free survival (DFS) for extensive metabolizer (EM) patients using annual hazard ratio (HR) data from the BIG 1-98 trial. We then replicated the model by evaluating 9-year event-free survival (EFS) using HR data from the ATAC trial. In addition, we employed two-way sensitivity analyses to explore the impact of HR of decreased-metabolizer (DM) and its frequency on survival by studying a range of estimates. Results: The 5-year DFS of tamoxifen-treated EM patients was 83.3%, which is similar to that of genotypically unselected patients who received an AI (83.7%). In the validation study, we further demonstrated that the 9-year EFS of tamoxifentreated EM patients was 81.4%, which is higher than that of genotypically unselected patients receiving tamoxifen (78.4%) and similar to that of patients receiving an AI (83.2%). Two-way sensitivity analyses demonstrated the robustness of the results

Mild Joint Symptoms Are Associated with Lower Risk of Falls than Asymptomatic Individuals with Radiological Evidence of Osteoarthritis

Osteoarthritis (OA) exacerbates skeletal muscle functioning, leading to postural instability and increased falls risk. However, the link between impaired physical function, OA and falls have not been elucidated. We investigated the role of impaired physical function as a potential mediator in the association between OA and falls. This study included 389 participants [229 fallers (≥2 falls or one injurious fall in the past 12 months), 160 non-fallers (no history of falls)], age (≥65 years) from a randomized controlled trial, the Malaysian Falls Assessment and Intervention Trial (MyFAIT). Physical function was assessed using Timed Up and Go (TUG) and Functional Reach (FR) tests. Knee and hip OA were diagnosed using three methods: Clinical, Radiological and Self-report. OA symptom severity was assessed using the Western Ontario and McMaster Universities Arthritis Index (WOMAC). The total WOMAC score was categorized to asymptomatic, mild, moderate and severe symptoms. Individuals with radiological OA and ‘mild’ overall symptoms on the WOMAC score had reduced risk of falls compared to asymptomatic OA [OR: 0.402(0.172–0.940), p = 0.042]. Individuals with clinical OA and ‘severe’ overall symptoms had increased risk of falls compared to those with ‘mild’ OA [OR: 4.487(1.883–10.693), p = 0.005]. In individuals with radiological OA, mild symptoms appear protective of falls while those with clinical OA and severe symptoms have increased falls risk compared to those with mild symptoms. Both relationships between OA and falls were not mediated by physical limitations. Larger prospective studies are needed for further evaluation

Correlation of microarray-based breast cancer molecular subtypes and clinical outcomes: implications for treatment optimization

<p>Abstract</p> <p>Background</p> <p>Optimizing treatment through microarray-based molecular subtyping is a promising method to address the problem of heterogeneity in breast cancer; however, current application is restricted to prediction of distant recurrence risk. This study investigated whether breast cancer molecular subtyping according to its global intrinsic biology could be used for treatment customization.</p> <p>Methods</p> <p>Gene expression profiling was conducted on fresh frozen breast cancer tissue collected from 327 patients in conjunction with thoroughly documented clinical data. A method of molecular subtyping based on 783 probe-sets was established and validated. Statistical analysis was performed to correlate molecular subtypes with survival outcome and adjuvant chemotherapy regimens. Heterogeneity of molecular subtypes within groups sharing the same distant recurrence risk predicted by genes of the Oncotype and MammaPrint predictors was studied.</p> <p>Results</p> <p>We identified six molecular subtypes of breast cancer demonstrating distinctive molecular and clinical characteristics. These six subtypes showed similarities and significant differences from the Perou-Sørlie intrinsic types. Subtype I breast cancer was in concordance with chemosensitive basal-like intrinsic type. Adjuvant chemotherapy of lower intensity with CMF yielded survival outcome similar to those of CAF in this subtype. Subtype IV breast cancer was positive for ER with a full-range expression of HER2, responding poorly to CMF; however, this subtype showed excellent survival when treated with CAF. Reduced expression of a gene associated with methotrexate sensitivity in subtype IV was the likely reason for poor response to methotrexate. All subtype V breast cancer was positive for ER and had excellent long-term survival with hormonal therapy alone following surgery and/or radiation therapy. Adjuvant chemotherapy did not provide any survival benefit in early stages of subtype V patients. Subtype V was consistent with a unique subset of luminal A intrinsic type. When molecular subtypes were correlated with recurrence risk predicted by genes of Oncotype and MammaPrint predictors, a significant degree of heterogeneity within the same risk group was noted. This heterogeneity was distributed over several subtypes, suggesting that patients in the same risk groups require different treatment approaches.</p> <p>Conclusions</p> <p>Our results indicate that the molecular subtypes established in this study can be utilized for customization of breast cancer treatment.</p