Recent examples of α-ketoglutarate-dependent mononuclear non-haem iron enzymes in natural product biosyntheses

Covering: up to 2018 α-Ketoglutarate (αKG, also known as 2-oxoglutarate)-dependent mononuclear non-haem iron (αKG-NHFe) enzymes catalyze a wide range of biochemical reactions, including hydroxylation, ring fragmentation, C-C bond cleavage, epimerization, desaturation, endoperoxidation and heterocycle formation. These enzymes utilize iron(ii) as the metallo-cofactor and αKG as the co-substrate. Herein, we summarize several novel αKG-NHFe enzymes involved in natural product biosyntheses discovered in recent years, including halogenation reactions, amino acid modifications and tailoring reactions in the biosynthesis of terpenes, lipids, fatty acids and phosphonates. We also conducted a survey of the currently available structures of αKG-NHFe enzymes, in which αKG binds to the metallo-centre bidentately through either a proximal- or distal-type binding mode. Future structure-function and structure-reactivity relationship investigations will provide crucial information regarding how activities in this large class of enzymes have been fine-tuned in nature.R01 GM093903 - NIGMS NIH HHSAccepted manuscrip

Integrating Randomized Placebo-Controlled Trial Data with External Controls: A Semiparametric Approach with Selective Borrowing

In recent years, real-world external controls (ECs) have grown in popularity as a tool to empower randomized placebo-controlled trials (RPCTs), particularly in rare diseases or cases where balanced randomization is unethical or impractical. However, as ECs are not always comparable to the RPCTs, direct borrowing ECs without scrutiny may heavily bias the treatment effect estimator. Our paper proposes a data-adaptive integrative framework capable of preventing unknown biases of ECs. The adaptive nature is achieved by dynamically sorting out a set of comparable ECs via bias penalization. Our proposed method can simultaneously achieve (a) the semiparametric efficiency bound when the ECs are comparable and (b) selective borrowing that mitigates the impact of the existence of incomparable ECs. Furthermore, we establish statistical guarantees, including consistency, asymptotic distribution, and inference, providing type-I error control and good power. Extensive simulations and two real-data applications show that the proposed method leads to improved performance over the RPCT-only estimator across various bias-generating scenarios

Tractable Algorithm for Robust Time-Optimal Trajectory Planning of Robotic Manipulators under Confined Torque

In this paper, the problem of time optimal trajectory planning under confined torque and uncertain dynamics and torque parameters along a predefined geometric path is considered. It is shown that the robust optimal solution to such a problem can be obtained by solving a linear program. Thus a tractable algorithm is given for robust time-optimal path-tracking control under confined torque

Real Effect or Bias? Best Practices for Evaluating the Robustness of Real-World Evidence through Quantitative Sensitivity Analysis for Unmeasured Confounding

The assumption of no unmeasured confounders is a critical but unverifiable assumption required for causal inference yet quantitative sensitivity analyses to assess robustness of real-world evidence remains underutilized. The lack of use is likely in part due to complexity of implementation and often specific and restrictive data requirements required for application of each method. With the advent of sensitivity analyses methods that are broadly applicable in that they do not require identification of a specific unmeasured confounder, along with publicly available code for implementation, roadblocks toward broader use are decreasing. To spur greater application, here we present a best practice guidance to address the potential for unmeasured confounding at both the design and analysis stages, including a set of framing questions and an analytic toolbox for researchers. The questions at the design stage guide the research through steps evaluating the potential robustness of the design while encouraging gathering of additional data to reduce uncertainty due to potential confounding. At the analysis stage, the questions guide researchers to quantifying the robustness of the observed result and providing researchers with a clearer indication of the robustness of their conclusions. We demonstrate the application of the guidance using simulated data based on a real-world fibromyalgia study, applying multiple methods from our analytic toolbox for illustration purposes.Comment: 16 pages which includes 5 figure

Marital Status and Mortality among Middle Age and Elderly Men and Women in Urban Shanghai

Previous studies have suggested that marital status is associated with mortality, but few studies have been conducted in China where increasing aging population and divorce rates may have major impact on health and total mortality.We examined the association of marital status with mortality using data from the Shanghai Women's Health Study (1996–2009) and Shanghai Men's Health Study (2002–2009), two population-based cohort studies of 74,942 women aged 40–70 years and 61,500 men aged 40–74 years at the study enrollment. Deaths were identified by biennial home visits and record linkage with the vital statistics registry. Marital status was categorized as married, never married, divorced, widowed, and all unmarried categories combined. Cox regression models were used to derive hazard ratios (HR) and 95% confidence interval (CI).Unmarried and widowed women had an increased all-cause HR = 1.11, 95% CI: 1.03, 1.21 and HR = 1.10, 95% CI: 1.02, 1.20 respectively) and cancer (HR = 1.17, 95% CI: 1.04, 1.32 and HR = 1.18, 95% CI: 1.04, 1.34 respectively) mortality. Never married women had excess all-cause mortality (HR = 1.46, 95% CI: 1.03, 2.09). Divorce was associated with elevated cardiovascular disease (CVD) mortality in women (HR = 1.47, 95% CI: 1.01, 2.13) and elevated all-cause mortality (HR = 2.45, 95% CI: 1.55, 3.86) in men. Amongst men, not being married was associated with excess all-cause (HR = 1.45, 95% CI: 1.12, 1.88) and CVD (HR = 1.65, 95% CI: 1.07, 2.54) mortality.Marriage is associated with decreased all cause mortality and CVD mortality, in particular, among both Chinese men and women