ENUMERATING ALTERNATE OPTIMAL FLUX DISTRIBUTIONS FOR METABOLIC RECONSTRUCTIONS

Metabolites consumed and produced by microorganisms for mass and energy conservation may cause changes in a microorganism’s environment. The microorganisms are unable to tolerate a particular environment for a long period. They may leave their old existence to find a new environment to sustain life. Essentially, organisms need to maintain their metabolic processes to survive in the new environment. Limitations of experimental studies to explore cell functions and regulations in detail result in insufficient information to explain processes of metabolic expressions under environments of organisms. Consequently, mathematical modeling and computer simulations have been conducted to combine all possible cellular metabolic fluxes into single or multiple connected networks. Metabolic modeling based on linear programming (LP) subjected to constraints with an optimization approach is often applied metabolic reconstruction. The LP objective function is maximized to obtain an optimal value of biomass flux. Optimal solutions in LP problems can be used to explain how metabolites function in metabolic reactions. As an LP problem may have many optimal solutions, this study proposes a method for enumerating all alternate optimal solutions to evaluate important reactions of metabolic pathways in microorganisms. The algorithm for generating alternate optimal solutions is implemented in MetModelGUI, a Java-based software for creating and analyzing metabolic reconstructions. The algorithm is applied to models of five microorganisms: Trypanosoma cruzi, Thermobifida fusca, Helicobacter pylori, Cryptococcus neoformans and Clostridium thermocellum. The results are analyzed using principal component analysis, and insight into the essential and non-essential pathways for each organism is derive

Evaluation of the Performance of Smoothing Functions in Generalized Additive Models for Spatial Variation in Disease

Generalized additive models (GAMs) with bivariate smoothing functions have been applied to estimate spatial variation in risk for many types of cancers. Only a handful of studies have evaluated the performance of smoothing functions applied in GAMs with regard to different geographical areas of elevated risk and different risk levels. This study evaluates the ability of different smoothing functions to detect overall spatial variation of risk and elevated risk in diverse geographical areas at various risk levels using a simulation study. We created five scenarios with different true risk area shapes (circle, triangle, linear) in a square study region. We applied four different smoothing functions in the GAMs, including two types of thin plate regression splines (TPRS) and two versions of locally weighted scatterplot smoothing (loess). We tested the null hypothesis of constant risk and detected areas of elevated risk using analysis of deviance with permutation methods and assessed the performance of the smoothing methods based on the spatial detection rate, sensitivity, accuracy, precision, power, and false-positive rate. The results showed that all methods had a higher sensitivity and a consistently moderate-to-high accuracy rate when the true disease risk was higher. The models generally performed better in detecting elevated risk areas than detecting overall spatial variation. One of the loess methods had the highest precision in detecting overall spatial variation across scenarios and outperformed the other methods in detecting a linear elevated risk area. The TPRS methods outperformed loess in detecting elevated risk in two circular areas

Polypectomy Techniques, Endoscopist Characteristics, and Serious Gastrointestinal Adverse Events

Background: A use of polypectomy techniques by endoscopist specialty (primary care, surgery, and gastroenterology) and experience (volume), and associations with serious gastrointestinal adverse events, were examined. Methods: A retrospective follow-up study with ambulatory surgery and hospital discharge datasets from Florida, 1999-2001, was used. Thirty-day hospitalizations due to colonic perforations and gastrointestinal bleeding were investigated for 323,585 patients. Results: Primary care endoscopists and surgeons used hot biopsy forceps/ablation, while gastroenterologists provided snare polypectomy or complex colonoscopy. Low-volume endoscopists were more likely to use simpler rather than complex procedures. For hot forceps/ablation and snare polypectomy, low- and medium-volume endoscopists reported higher odds of adverse events. For complex colonoscopy, higher odds of adverse events were reported for primary care endoscopists (1.74 [95%CI, 1.18 to 2.56]) relative to gastroenterologists Conclusions: Endoscopists regardless of specialty and experience can safely use cold biopsy forceps. For hot biopsy and snare polypectomy, low volume, but not specialty, contributed to increased odds of adverse events. For complex colonoscopy, primary care specialty, but not low volume, added to the odds of adverse events. Comparable outcomes were reported for surgeons and gastroenterologists. Cross-training and continuing medical education of primary care endoscopists in high-volume endoscopy settings are recommended for complex colonoscopy procedures

Development of HIV with Drug Resistance after CD4 Cell Count—Guided Structured Treatment Interruptions in Patients Treated with Highly Active Antiretroviral Therapy after Dual—Nucleoside Analogue Treatment

Background. For patients with human immunodeficiency virus (HIV) infection, structured treatment interruption (STI) is an attractive alternative strategy to continuous treatment, particularly in resource-restrained settings, because it reduces both side effects and costs. One major concern, however, is the development of resistance to antiretroviral drugs that can occur during multiple cycles of starting and stopping therapy. Methods. HIV genotypic drug resistance was investigated in 20 HIV-infected Thai patients treated with highly active antiretroviral therapy (HAART) and CD4 cell count—guided STI after dual nucleoside reverse-transcriptase inhibitor (NRTI) treatment. Resistance was tested at the time of the switch from dual-NRTI treatment to HAART and when HAART was stopped during the last interruption. Results. After STI, one major drug-resistance mutation occurred (T215Y), and, in the 4 samples with preexisting major mutations (D67N [n = 2], K70R [n = 2], T215Y [n = 2], and T215I [n = 1]), the mutations disappeared. All mutations in the HIV protease gene were minor mutations already present, in most cases, before STI was started, and their frequency was not increased through STI, whereas the frequency of reverse-transcriptase gene mutations significantly decreased after the interruptions. After the 48-week study period, no patients had virological failure. Long-term follow-up (108 weeks) showed 1 case of virological failure in the STI arm and 1 in the continuous arm. No virological failure was seen in patients with major mutations. Conclusions. Major HIV drug-resistance mutations were not induced through CD4 cell count—guided treatment interruptions in HIV-infected patients successfully treated with HAART after dual-NRTI therap

A feasibility study of immediate versus deferred antiretroviral therapy in children with HIV infection

<p>Abstract</p> <p>Objective</p> <p>To evaluate the feasibility of a large immediate versus deferred antiretroviral therapy (ART) study in children.</p> <p>Methods</p> <p>We conducted an open-label pilot randomized clinical trial study in 43 Thai children with CD4 15 to 24% of starting generic AZT/3TC/NVP immediately (Arm 1) or deferring until CD4 < 15% or CDC C (Arm 2). Primary endpoints were recruitment rate, adherence to randomized treatment and retention in trial. Secondary endpoints were % with CDC C or CD4 < 15%. Children were in the trial until the last child reached 108 weeks. Intention to treat and on treatment analyses were performed.</p> <p>Results</p> <p>Recruitment took 15 months. Twenty-six of 69 (37.7%) were not eligible due mainly to low CD4%. Twenty four and 19 were randomized to arms 1 and 2 respectively. All accepted the randomized arm; however, 3 in arm 1 stopped ART and 1 in arm 2 refused to start ART. Ten/19 (53%) in arm 2 started ART. At baseline, median age was 4.8 yrs, CDC A:B were 36:7, median CD4 was 19% and viral load was 4.8 log. All in arm 1 and 17/19 in arm 2 completed the study (median of 134 weeks). No one had AIDS or death. Four in immediate arm had tuberculosis. Once started on ART, deferred arm children achieved similar CD4 and viral load response as the immediate arm. Adverse events were similar between arms. The deferred arm had a 26% ART saving.</p> <p>Conclusion</p> <p>Almost 40% of children were not eligible due mainly to low CD4% but adherence to randomized treatment and retention in trial were excellent. A larger study to evaluate when to start ART is feasible.</p

Directly Observed Therapy and Improved Tuberculosis Treatment Outcomes in Thailand

BACKGROUND: The World Health Organization (WHO) recommends that tuberculosis (TB) patients receive directly observed therapy (DOT). Randomized controlled trials have not consistently shown that this practice improves TB treatment success rates. In Thailand, one of 22 WHO-designated high burden TB countries, patients may have TB treatment observed by a health care worker (HCW), family member, or no one. We studied whether DOT improved TB treatment outcomes in a prospective, observational cohort. METHODS AND FINDINGS: We prospectively collected epidemiologic data about TB patients treated at public and private facilities in four provinces in Thailand and the national infectious diseases hospital from 2004-2006. Public health staff recorded the type of observed therapy that patients received during the first two months of TB treatment. We limited our analysis to pulmonary TB patients never previously treated for TB and not known to have multidrug-resistant TB. We analyzed the proportion of patients still on treatment at the end of two months and with treatment success at the end of treatment according to DOT type. We used propensity score analysis to control for factors associated with DOT and treatment outcome. Of 8,031 patients eligible for analysis, 24% received HCW DOT, 59% family DOT, and 18% self-administered therapy (SAT). Smear-positive TB was diagnosed in 63%, and 21% were HIV-infected. Of patients either on treatment or that defaulted at two months, 1601/1636 (98%) patients that received HCW DOT remained on treatment at two months compared with 1096/1268 (86%) patients that received SAT (adjusted OR [aOR] 3.8; 95% confidence interval [CI] 2.4-6.0) and 3782/3987 (95%) patients that received family DOT (aOR 2.1; CI, 1.4-3.1). Of patients that had treatment success or that defaulted at the end of treatment, 1369/1477 (93%) patients that received HCW DOT completed treatment compared with 744/1074 (69%) patients that received SAT (aOR 3.3; CI, 2.4-4.5) and 3130/3529 (89%) patients that received family DOT (aOR 1.5; 1.2-1.9). The benefit of HCW DOT compared with SAT was similar, but smaller, when comparing patients with treatment success to those with death, default, or failure. CONCLUSIONS: In Thailand, two months of DOT was associated with lower odds of default during treatment. The magnitude of benefit was greater for DOT provided by a HCW compared with a family member. Thailand should consider increasing its use of HCW DOT during TB treatment

META-ANALYSIS OF GENE EXPRESSION STUDIES

Combining effect sizes from individual studies using random-effects models are commonly applied in high-dimensional gene expression data. However, unknown study heterogeneity can arise from inconsistency of sample qualities and experimental conditions. High heterogeneity of effect sizes can reduce statistical power of the models. We proposed two new methods for random effects estimation and measurements for model variation and strength of the study heterogeneity. We then developed a statistical technique to test for significance of random effects and identify heterogeneous genes. We also proposed another meta-analytic approach that incorporates informative weights in the random effects meta-analysis models. We compared the proposed methods with the standard and existing meta-analytic techniques in the classical and Bayesian frameworks. We demonstrate our results through a series of simulations and application in gene expression neurodegenerative diseases