Revised standards for reporting interventions in clinical trials of acupuncture (STRICTA) : Extending the CONSORT statement

The Standards for Reporting Interventions in Clinical Trials of Acupuncture (STRICTA) were published in five journals in 2001 and 2002. These guidelines, in the form of a checklist and explanations for use by authors and journal editors, were designed to improve reporting of acupuncture trials, particularly the interventions, thereby facilitating their interpretation and replication. Subsequent reviews of the application and impact of STRICTA have highlighted the value of STRICTA as well as scope for improvements and revision

State Space Model with hidden variables for reconstruction of gene regulatory networks

<p>Abstract</p> <p>Background</p> <p>State Space Model (SSM) is a relatively new approach to inferring gene regulatory networks. It requires less computational time than Dynamic Bayesian Networks (DBN). There are two types of variables in the linear SSM, observed variables and hidden variables. SSM uses an iterative method, namely Expectation-Maximization, to infer regulatory relationships from microarray datasets. The hidden variables cannot be directly observed from experiments. How to determine the number of hidden variables has a significant impact on the accuracy of network inference. In this study, we used SSM to infer Gene regulatory networks (GRNs) from synthetic time series datasets, investigated Bayesian Information Criterion (BIC) and Principle Component Analysis (PCA) approaches to determining the number of hidden variables in SSM, and evaluated the performance of SSM in comparison with DBN.</p> <p>Method</p> <p>True GRNs and synthetic gene expression datasets were generated by using GeneNetWeaver. Both DBN and linear SSM were used to infer GRNs from the synthetic datasets. The inferred networks were compared with the true networks.</p> <p>Results</p> <p>Our results show that inference precision varied with the number of hidden variables. For some regulatory networks, the inference precision of DBN was higher but SSM performed better in other cases. Although the overall performance of the two approaches is compatible, SSM is much faster and capable of inferring much larger networks than DBN.</p> <p>Conclusion</p> <p>This study provides useful information in handling the hidden variables and improving the inference precision.</p

A new approach to construct pathway connected networks and its application in dose responsive gene expression profiles of rat liver regulated by 2,4DNT

<p>Abstract</p> <p>Background</p> <p>Military and industrial activities have lead to reported release of 2,4-dinitrotoluene (2,4DNT) into soil, groundwater or surface water. It has been reported that 2,4DNT can induce toxic effects on humans and other organisms. However the mechanism of 2,4DNT induced toxicity is still unclear. Although a series of methods for gene network construction have been developed, few instances of applying such technology to generate pathway connected networks have been reported.</p> <p>Results</p> <p>Microarray analyses were conducted using liver tissue of rats collected 24h after exposure to a single oral gavage with one of five concentrations of 2,4DNT. We observed a strong dose response of differentially expressed genes after 2,4DNT treatment. The most affected pathways included: long term depression, breast cancer regulation by stathmin1, WNT Signaling; and PI3K signaling pathways. In addition, we propose a new approach to construct pathway connected networks regulated by 2,4DNT. We also observed clear dose response pathway networks regulated by 2,4DNT.</p> <p>Conclusions</p> <p>We developed a new method for constructing pathway connected networks. This new method was successfully applied to microarray data from liver tissue of 2,4DNT exposed animals and resulted in the identification of unique dose responsive biomarkers in regards to affected pathways.</p

Fund for Shared Insight: Media Analysis

Fund for Shared Insight ("Shared Insight") is a collaborative effort among fundersthat pools financial and other resources to make grants to improve philanthropy. Shared Insight believes philanthropy can have a greater social and environmental impact if foundations and nonprofits listen to the people they seek to help, act on what they hear, and openly share what they learn.Related to feedback loops, Shared Insight's work is focused on increasingthe extent to which foundations listen to others—especially the people they seek to help—and respond to their expressed interests. When Shared Insight talks about "the people they seek to help," they are referring to the individuals who receive programs and services from nonprofit organizations; for example, the students served by charter schools, the recently released prisoners benefiting from job-training services, and the low-income first-time mothers participating in prenatal through birth programs.Over the next three years, Shared Insight would hope to see changes in the amount and kind of discourse in the field related tobeneficiary feedback loops. In the summer of 2015, one year since the launch of the collaborative, ORS Impact repeated a media analysis of relevant blogs, periodicals, and reports. The following memo outlines changes in the amount and kind of discourse in the field around feedback loops compared to the year before Shared Insight launched. We raise a few observations and considerations. More detailed methodological notes follow

Antihypertensive treatment among inpatients with hypertension at Anhui Provincial Hospital in China: a cross-sectional study

The aim of this study was to assess the prescribing pattern of antihypertensive treatment among inpatients with uncomplicated and complicated hypertension at Anhui Provincial Hospital (First Class Public Hospital) in the central region of China in accordance with the recommendations of current international guidelines. A retrospective cross-sectional study was performed from 1 January to 31 December, 2009. A total of 2010 hypertensive inpatients were included. Among 683 inpatients receiving monotherapy, calcium channel blockers (CCBs) were the most frequently drugs used in uncomplicated hypertensive patients (57.41 %) and those with stroke (61.73 %). Beta-blockers (BBs) (27.90 %) and angiotensin-converting enzyme inhibitors (ACEIs, 26.17 %) were the preferred agents in hypertensive patients with coronary heart disease (CHD). Among 1327 inpatients with combination therapy, two-drug regimen was the most popular, except for the hypertensive patients with stroke. The pattern of antihypertensive utilization appears to be partly in accordance with the recommendations of international guidelines. There was a tendency to use CCBs in hypertensive patients with stroke, whereas BBs and ACEI were the most prescribed in those with CHD.Colegio de Farmacéuticos de la Provincia de Buenos Aire

Sinteza backstepping regulatora za praćenje maksimalne proizvodnje energije u fotonaponskim sustavima

This work presents a new control method to track the maximum power point of a grid-connected photovoltaic (PV) system. A backstepping controller is designed to be applied to a buck-boost DC-DC converter in order to achieve an optimal PV array output voltage. This nonlinear control is based on Lyapunov functions assuring the local stability of the system. Control reference voltages are initially estimated by a regression plane, avoiding local maximum and adjusted with a modified perturb and observe method (P&O). Thus, the maximum power extraction of the generating system is guaranteed. Finally, a DC-AC converter is controlled to supply AC current in the point of common coupling (PCC) of the electrical network. The performance of the developed system has been analyzed by means a simulation platform in Matlab/Simulink helped by SymPowerSystem Blockset. Results testify the validity of the designed control method.Ovaj rad predstavlja novu metodu upravljanja za slije.enje točke maksimalne snage fotonaponskog (PV) sustava. Dana je sinteza backstepping regulatora za primjenu u silazno-uzlaznom DC-DC pretvaraču za postizanje optimalnog izlaznog napona PV-a. Ova je nelinearna metoda upravljanja zasnovana na Ljapunovim funkcijama osiguravajući tako lokalnu stabilnost sustava. Upravljačke reference napona prvo su estimirane korištenjem regresijske ravnine izbjegavajući lokalne maksimume, a zatim podešene tzv. modificiranom perturbiraj i uoči metodom (P&O). Prema tome, zagarantirano je maksimalno izvlačenje energije iz sustava proizvodnje. Naposlijetku, DC-AC pretvaračem upravlja se na način da osigurava željena izmjenična struja u točki zajedničkog spoja (PCC) elektroenergetske mreže. Ponašanje razvijenog sustava analizirano je kroz simulacije provedene u Matlab/Simulink okruženju uz korištenje SymPowerSystem biblioteke

Developing discriminate model and comparative analysis of differentially expressed genes and pathways for bloodstream samples of diabetes mellitus type 2

Background: Diabetes mellitus of type 2 (T2D), also known as noninsulin-dependent diabetes mellitus (NIDDM) or adult-onset diabetes, is a common disease. It is estimated that more than 300 million people worldwide suffer from T2D. In this study, we investigated the T2D, pre-diabetic and healthy human (no diabetes) bloodstream samples using genomic, genealogical, and phonemic information. We identified differentially expressed genes and pathways. The study has provided deeper insights into the development of T2D, and provided useful information for further effective prevention and treatment of the disease. Results: A total of 142 bloodstream samples were collected, including 47 healthy humans, 22 pre-diabetic and 73 T2D patients. Whole genome scale gene expression profiles were obtained using the Agilent Oligo chips that contain over 20,000 human genes. We identified 79 significantly differentially expressed genes that have fold change ≥ 2. We mapped those genes and pinpointed locations of those genes on human chromosomes. Amongst them, 3 genes were not mapped well on the human genome, but the rest of 76 differentially expressed genes were well mapped on the human genome. We found that most abundant differentially expressed genes are on chromosome one, which contains 9 of those genes, followed by chromosome two that contains 7 of the 76 differentially expressed genes. We performed gene ontology (GO) functional analysis of those 79 differentially expressed genes and found that genes involve in the regulation of cell proliferation were among most common pathways related to T2D. The expression of the 79 genes was combined with clinical information that includes age, sex, and race to construct an optimal discriminant model. The overall performance of the model reached 95.1% accuracy, with 91.5% accuracy on identifying healthy humans, 100% accuracy on pre-diabetic patients and 95.9% accuract on T2D patients. The higher performance on identifying pre-diabetic patients was resulted from more significant changes of gene expressions among this particular group of humans, which implicated that patients were having profound genetic changes towards disease development. Conclusion: Differentially expressed genes were distributed across chromosomes, and are more abundant on chromosomes 1 and 2 than the rest of the human genome. We found that regulation of cell proliferation actually plays an important role in the T2D disease development. The predictive model developed in this study has utilized the 79 significant genes in combination with age, sex, and racial information to distinguish pre-diabetic, T2D, and healthy humans. The study not only has provided deeper understanding of the disease molecular mechanisms but also useful information for pathway analysis and effective drug target identification

Community-Based Measures for Mitigating the 2009 H1N1 Pandemic in China

Since the emergence of influenza A/H1N1 pandemic virus in March–April 2009, very stringent interventions including Fengxiao were implemented to prevent importation of infected cases and decelerate the disease spread in mainland China. The extent to which these measures have been effective remains elusive. We sought to investigate the effectiveness of Fengxiao that may inform policy decisions on improving community-based interventions for management of on-going outbreaks in China, in particular during the Spring Festival in mid-February 2010 when nationwide traveling will be substantially increased. We obtained data on initial laboratory-confirmed cases of H1N1 in the province of Shaanxi and used Markov-chain Monte-Carlo (MCMC) simulations to estimate the reproduction number. Given the estimates for the exposed and infectious periods of the novel H1N1 virus, we estimated a mean reproduction number of 1.68 (95% CI 1.45–1.92) and other A/H1N1 epidemiological parameters. Our results based on a spatially stratified population dynamical model show that the early implementation of Fengxiao can delay the epidemic peak significantly and prevent the disease spread to the general population but may also, if not implemented appropriately, cause more severe outbreak within universities/colleges, while late implementation of Fengxiao can achieve nothing more than no implementation. Strengthening local control strategies (quarantine and hygiene precaution) is much more effective in mitigating outbreaks and inhibiting the successive waves than implementing Fengxiao. Either strong mobility or high transport-related transmission rate during the Spring Festival holiday will not reverse the ongoing outbreak, but both will result in a large new wave. The findings suggest that Fengxiao and travel precautions should not be relaxed unless strict measures of quarantine, isolation, and hygiene precaution practices are put in place. Integration and prompt implementation of these interventions can significantly reduce the overall attack rate of pandemic outbreaks