Large-scale 13C-flux analysis reveals distinct transcriptional control of respiratory and fermentative metabolism in Escherichia coli

The authors analyze the role transcription plays in regulating bacterial metabolic flux. Of 91 transcriptional regulators studied, 2/3 affect absolute fluxes, but only a small number of regulators control the partitioning of flux between different metabolic pathways

Cyclic Hypervalent Iodine Reagents for Azidation: Safer Reagents and Photoredox-Catalyzed Ring Expansion

Azides are building blocks of increasing importance in synthetic chemistry, chemical biology, and materials science. Azidobenziodoxolone (ABX, Zhdankin reagent) is a valuable azide source, but its safety profile has not been thoroughly established. Herein, we report a safety study of ABX, which shows its hazardous nature. We introduce two derivatives, tBu-ABX and ABZ (azidobenziodazolone), with a better safety profile, and use them in established photoredox- and metal-mediated azidations, and in a new ring-expansion of silylated cyclobutanols to give azidated cyclopentanones

Predictive Models for Thermal Behavior of Chemicals with Quantitative Structure-Property Relationships

Most processes in the chemical industry involve potentially hazardous steps. It is thus of critical importance to perform risk assessments and to know the thermal behavior of the chemicals at stake. A widely used thermal analysis, differential scanning calorimetry, allows verifying if the compounds are stable towards heat or if they decompose above certain temperatures. This information helps setting the appropriate handling and storage conditions for safe operations. The time and resources needed for these experimental investigations would be reduced if the testing phase could be better targeted and guided using reliable predictive methods. This work helps to answer these needs by proposing predictive models for thermal stability based on the quantitative structure-property relationships method

Quantitative Structure-Property Relationships for Thermal Stability and Explosive Properties of Chemicals

Handling and storing chemicals in the industrial world require a conscientious hazards assessment and the implementation of appropriate measures to ensure safety for the workers, the company, the environment and the society. Reliable evaluations and predictions based solely on the molecular structure would represent a valuable tool in the preliminary hazard assessment process as it would reduce the necessary time and resources for extensive testing. This work presents how Quantitative Structure-Property Relationships (QSPR) of various hazardous chemical properties (i.e. thermal decomposition enthalpy or Minimal Ignition Energy) can be built to meet these needs. Results are to be illustrated with some examples. Two sets of chemicals were studied and the corresponding experimental results were correlated to 90 molecular descriptors. The models were built following a regression analysis. The best multi-linear regressions presenting 6 parameters or less with high determination and cross-validation coefficients are withheld as predictive models

Thermal Stability Predictions for Inherently Safe Process Design Using Molecular-Based Modelling Approaches

For efficient inherently safe design, awareness of all available options at the appropriate decision-making moment is key. Simulations offer both timely availability and large screening possibilities. Therefore computer-aided product design gained in popularity during the recent years and models of various physico-chemical properties were developed. Yet, predictions of safety related data are still limited. Hence, thermal stability derived from Differential Scanning Calorimetry (DSC) is analysed and simulated with two molecular-based modelling approaches: Group Contribution Method (GCM) and Quantitative Structure-Property Relationships (QSPR). Predictive models are developed and evaluated over fitting and predictive abilities for five properties extracted from the DSC curves