Prediction of Chameleonic Efficiency

Chameleonic properties, i. e., the capacity of a molecule to hide polarity in non-polar environments and expose it in water, help achieving sufficient permeability and solubility for drug molecules with high MW. We present models of experimental measures of polarity for a set of 24 FDA approved drugs (MW 405-1113) and one PROTAC (MW 1034). Conformational ensembles in aqueous and non-polar environments were generated using molecular dynamics. A linear regression model that predicts chromatographic apparent polarity (EPSA) with a mean unsigned error of 10 Ų was derived based on separate terms for donor, acceptor, and total molecular SASA. A good correlation (R²=0.92) with an experimental measure of hydrogen bond donor potential, Δlog P_oct-tol, was found for the mean hydrogen bond donor SASA of the conformational ensemble scaled with Abraham's A hydrogen bond acidity. Two quantitative measures of chameleonic behaviour, the chameleonic efficiency indices, are introduced. We envision that the methods presented herein will be useful to triage designed molecules and prioritize those with the best chance of achieving acceptable permeability and solubility.     

Corrosion behaviors of carbon steel induced by life activities of Phaeodactylum tricornutum in a marine environment

Microbiologically influenced corrosion induced by bacteria has been studied for many years. Corrosion is known to be sensitive to the presence of microalgae, such as Phaeodactylum tricornutum. However, the life activity of P. tricornutum that influences the general and localized corrosion of carbon steel is not fully understood. The current study uses a combination of immersion tests and electrochemical experiments with a detailed surface characterization to reveal the naturally formed corrosion products with/without the presence of P. tricornutum. The results show that samples suffer from pitting corrosion and the averaged pit depths are approximately 15 μm under a light–dark cycle condition or a 24-h constant light condition. Meanwhile, the corrosion products are mainly comprised of γ-FeOOH and Fe₃O₄ in a constant light condition. However, γ-FeOOH, Fe₃O₄, and FeCO₃ are found in a light–dark cycle. This study proposes the fundamental mechanisms of the effect of P. tricornutum life activities on the corrosion performance of Q235 carbon steel, to fulfill the knowledge gaps of the presence of microalgae inducing the general and pitting corrosion of carbon steel.     

Dual effect synergistically triggered Ce:(Y,Tb)3(Al,Mn)5O12 transparent ceramics enabling a high color-rendering index and excellent thermal stability for white LEDs

Ce:Y₃Al₅O₁₂ transparent ceramics (TCs) with appropriate emission light proportion and high thermal stability are significant to construct white light emitting diode devices with excellent chromaticity parameters. In this work, strategies of controlling crystal-field splitting around Ce³⁺ ion and doping orange-red emitting ion, were adopted to fabricate Ce:(Y,Tb)₃(Al,Mn)₅O₁₂ TCs via vacuum sintering technique. Notably, 85.4 % of the room-temperature luminescence intensity of the TC was retained at 150 °C, and the color rendering index was as high as 79.8. Furthermore, a 12 nm red shift and a 16.2 % increase of full width at half maximum were achieved owing to the synergistic effects of Tb³⁺ and Mn²⁺ ions. By combining TCs with a 460 nm blue chip, a warm white light with a low correlated color temperature of 4155 K was acquired. Meanwhile, the action mechanism of Tb³⁺ ion and the energy transfer between Ce³⁺ and Mn²⁺ ions were verified in prepared TCs.     

Enhancement of process modelling and simulation evaluation by deploying a test for assessment and feedback individualisation

This paper demonstrates a novel approach for a computer-based course assessment. A test is introduced in which computers are deployed. This significantly contributes to the enhancement of the marking consistency, individual performance distinction and feedbacks, and widen the questions range for computer-based modules. The proposed test method, for the first time, uses the simulation files marking for individualised evaluation purposes. The methodology has successfully been implemented in practice for three modules including Process Simulation (CE2105), Advanced Process Simulation (CE4023), and Process Computation (CE3021) at Aston University (UK) over three academic years, from 2016 to 2019. The effectiveness of the proposed approach has been evaluated using several factors, including final marks, consistency multiple academic years, and mark distribution. In contrast to the common teamwork assessments, individualised feedback became possible. While ASPEN has been used for CE4023 and CE2105 tests, MATLAB has been applied as the computation platform for CE3021 module. This reveals the applicability of different software in proposed methodology. The number of students in the cohorts studied was from 52 to 204, demonstrating the applicability of the method for various cohort sizes. Even though the methodology has been demonstrated based on the chemical engineering discipline modules, it allows digitalising the delivery and assessment of a wide range of simulation techniques in many disciplines.     

Public perceptions on artificial intelligence driven disaster management: Evidence from Sydney,Melbourne and Brisbane

In recent years, artificial intelligence (AI) is being increasingly utilised in disaster management activities. The public is engaged with AI in various ways in these activities. For instance, crowdsourcing applications developed for disaster management to handle the tasks of collecting data through social media platforms, and increasing disaster awareness through serious gaming applications. Nonetheless, there are limited empirical investigations and understanding on public perceptions concerning AI for disaster management. Bridging this knowledge gap is the justification for this paper. The methodological approach adopted involved: Initially, collecting data through an online survey from residents (n = 605) of three major Australian cities; Then, analysis of the data using statistical modelling. The analysis results revealed that: (a) Younger generations have a greater appreciation of opportunities created by AI-driven applications for disaster management; (b) People with tertiary education have a greater understanding of the benefits of AI in managing the pre- and post-disaster phases, and; (c) Public sector administrative and safety workers, who play a vital role in managing disasters, place a greater value on the contributions by AI in disaster management. The study advocates relevant authorities to consider public perceptions in their efforts in integrating AI in disaster management.     

Patient-Derived Organoids as a Model for Cancer Drug Discovery

In the search for the ideal model of tumours, the use of three-dimensional in vitro models is advancing rapidly. These are intended to mimic the in vivo properties of the tumours which affect cancer development, progression and drug sensitivity, and take into account cell–cell interactions, adhesion and invasiveness. Importantly, it is hoped that successful recapitulation of the structure and function of the tissue will predict patient response, permitting the development of personalized therapy in a timely manner applicable to the clinic. Furthermore, the use of co-culture systems will allow the role of the tumour microenvironment and tissue–tissue interactions to be taken into account and should lead to more accurate predictions of tumour development and responses to drugs. In this review, the relative merits and limitations of patient-derived organoids will be discussed compared to other in vitro and ex vivo cancer models. We will focus on their use as models for drug testing and personalized therapy and how these may be improved. Developments in technology will also be considered, including the use of microfluidics, 3D bioprinting, cryopreservation and circulating tumour cell-derived organoids. These have the potential to enhance the consistency, accessibility and availability of these models.     

Acquisition and Spread of Antimicrobial Resistance: A tet(X) Case Study

Understanding the mechanisms leading to the rise and dissemination of antimicrobial resistance (AMR) is crucially important for the preservation of power of antimicrobials and controlling infectious diseases. Measures to monitor and detect AMR, however, have been significantly delayed and introduced much later after the beginning of industrial production and consumption of antimicrobials. However, monitoring and detection of AMR is largely focused on bacterial pathogens, thus missing multiple key events which take place before the emergence and spread of AMR among the pathogens. In this regard, careful analysis of AMR development towards recently introduced antimicrobials may serve as a valuable example for the better understanding of mechanisms driving AMR evolution. Here, the example of evolution of tet(X), which confers resistance to the next-generation tetracyclines, is summarised and discussed. Initial mechanisms of resistance to these antimicrobials among pathogens were mostly via chromosomal mutations leading to the overexpression of efflux pumps. High-level resistance was achieved only after the acquisition of flavin-dependent monooxygenase-encoding genes from the environmental microbiota. These genes confer resistance to all tetracyclines, including the next-generation tetracyclines, and thus were termed tet(X). ISCR2 and IS26, as well as a variety of conjugative and mobilizable plasmids of different incompatibility groups, played an essential role in the acquisition of tet(X) genes from natural reservoirs and in further dissemination among bacterial commensals and pathogens. This process, which took place within the last decade, demonstrates how rapidly AMR evolution may progress, taking away some drugs of last resort from our arsenal.     

Structure-Activity Relationship Explorations and Discovery of a Potent Antagonist for the Free Fatty Acid Receptor 2

Free fatty acid receptor 2 (FFA2) is a sensor for short-chain fatty acids that has been identified as an interesting potential drug target for treatment of metabolic and inflammatory diseases. Although several ligand series are known for the receptor, there is still a need for improved compounds. One of the most potent and frequently used antagonists is the amide-substituted phenylbutanoic acid known as CATPB ( 1 ). We here report the structure-activity relationship exploration of this compound, leading to the identification of homologues with increased potency. The preferred compound 37 (TUG-1958) was found, besides improved potency, to have high solubility and favorable pharmacokinetic properties.