Commencement Program, May (1997)

https://red.mnstate.edu/commencement/1166/thumbnail.jp

Biosynthesis of providencin: understanding photochemical cyclobutane formation with density functional theory

The unique structure of furanocembranoid natural product providencin has stimulated biosynthetic hypotheses, especially concerning the formation of its cyclobutanol ring. One such hypothesis involves a photochemically induced Norrish–Yang cyclization in bipinnatin E. We have used computations to assess the feasibility and the stereochemical outcome of this proposed biosynthetic transformation. Density functional theory calculations reveal that the proposed Norrish–Yang cyclization in bipinnatin E is possible and that the stereoselectivity of this step is consistent with that of the natural product

Thermal and photochemical mechanisms for cyclobutane formation in bielschowskysin biosynthesis

The unique structure of furanocembranoid natural product bielschowskysin has provoked a number of biosynthetic hypotheses: quantum chemical calculations provide a means to assess the feasibility of postulated mechanisms in the construction of this unusual carbon skeleton. Calculations reveal that thermal closure is possible in water via an unusual concerted cyclobutane-forming transition state without the intervention of an enzyme. Photocycloaddition is computed to be extremely efficient, provided enol ether triplet sensitization can be achieved by an appropriate light source. The possible existence of a stable dicarbonyl intermediate presents a challenge for the thermal route, implicating a photochemical pathway in bielschowskysin biosynthesis

AQME: Automated quantum mechanical environments for researchers and educators

AQME, automated quantum mechanical environments, is a free and open-source Python package for the rapid deployment of automated workflows using cheminformatics and quantum chemistry. AQME workflows integrate tasks performed across multiple computational chemistry packages and data formats, preserving all computational protocols, data, and metadata for machine and human users to access and reuse. AQME has a modular structure of independent modules that can be implemented in any sequence, allowing the users to use all or only the desired parts of the program. The code has been developed for researchers with basic familiarity with the Python programming language. The CSEARCH module interfaces to molecular mechanics and semi-empirical QM (SQM) conformer generation tools (e.g., RDKit and Conformer–Rotamer Ensemble Sampling Tool, CREST) starting from various initial structure formats. The CMIN module enables geometry refinement with SQM and neural network potentials, such as ANI. The QPREP module interfaces with multiple QM programs, such as Gaussian, ORCA, and PySCF. The QCORR module processes QM results, storing structural, energetic, and property data while also enabling automated error handling (i.e., convergence errors, wrong number of imaginary frequencies, isomerization, etc.) and job resubmission. The QDESCP module provides easy access to QM ensemble-averaged molecular descriptors and computed properties, such as NMR spectra. Overall, AQME provides automated, transparent, and reproducible workflows to produce, analyze and archive computational chemistry results. SMILES inputs can be used, and many aspects of tedious human manipulation can be avoided. Installation and execution on Windows, macOS, and Linux platforms have been tested, and the code has been developed to support access through Jupyter Notebooks, the command line, and job submission (e.g., Slurm) scripts. Examples of pre-configured workflows are available in various formats, and hands-on video tutorials illustrate their use

Strategic toolkits: seniority, usage and performance in the German SME machinery and equipment sector

This paper examines the strategic tool kit, from a human resource management (HRM) perspective, in terms of usage and impact. Research to date has tended to consider usage, assuming to a certain extent that knowledge and understanding of particular tools suggest that practitioners value them. The research on which this paper is based builds upon the idea that usage indicates satisfaction, but develops the usage theme to investigate which decision-makers are actually engaged in both tool appliance and the strategic process. Of particular interest to the researchers are the educational background, age and seniority of the decision-makers. In addition, potential links with HRM and organizational performance are also explored. The context of the research, the German machinery and equipment sector, provides an insight into the industry's ability to sustain growth in face of increasing international competition. The paper calls for a greater awareness, from a human resource perspective, and utilization of strategic management practice and associated decision-making aids

Influenza Hospitalisations in England during the 2022/23 Season: do different data sources drive divergence in modelled waves? A comparison of surveillance and administrative data

Accurate and representative data is vital for precisely reporting the impact of influenza in healthcare systems. Northern hemisphere winter 2022/23 experienced the most substantial influenza wave since the COVID-19 pandemic began in 2020. Simultaneously, new data streams become available within health services because of the pandemic. Comparing these data, surveillance and administrative, supports the accurate monitoring of population level disease trends. We analysed admissions rates per capita from four different collection mechanisms covering National Health Service hospital Trusts in England over the winter 2022/23 wave. We adjust for difference in reporting and extracted key epidemic characteristics including the maximum admission rate, peak timing, cumulative season admissions and growth rates by fitting generalised additive models at national and regional levels. By modelling the admission rates per capita across surveillance and administrative data systems we show that different data measuring the epidemic produce different estimates of key quantities. Nationally and in most regions the data correspond well for the maximum admission rate, date of peak and growth rate, however, in subnational analysis discrepancies in estimates arose, particularly for the cumulative admission rate. This research shows that the choice of data used to measure seasonal influenza epidemics can influence analysis substantially at sub-national levels. For the admission rate per capita there is comparability in the sentinel surveillance approach (which has other important functions), rapid situational reports, operational databases and time lagged administrative data giving assurance in their combined value. Utilising multiple sources of data aids understanding of the impact of seasonal influenza epidemics in the population

Real-time COVID-19 hospital admissions forecasting with leading indicators and ensemble methods in England

Hospitalisations from COVID-19 with Omicron sub-lineages have put a sustained pressure on the English healthcare system. Understanding the expected healthcare demand enables more effective and timely planning from public health. We collect syndromic surveillance sources, which include online search data, NHS 111 telephonic and online triages. Incorporating this data we explore generalised additive models, generalised linear mixed-models, penalised generalised linear models and model ensemble methods to forecast over a two-week forecast horizon at an NHS Trust level. Furthermore, we showcase how model combinations improve forecast scoring through a mean ensemble, weighted ensemble, and ensemble by regression. Validated over multiple Omicron waves, at different spatial scales, we show that leading indicators can improve performance of forecasting models, particularly at epidemic changepoints. Using a variety of scoring rules, we show that ensemble approaches outperformed all individual models, providing higher performance at a 21-day window than the corresponding individual models at 14-days. We introduce a modelling structure used by public health officials in England in 2022 to inform NHS healthcare strategy and policy decision making. This paper explores the significance of ensemble methods to improve forecasting performance and how novel syndromic surveillance can be practically applied in epidemic forecasting

Mechanistic investigation of Rh(i)-catalysed asymmetric Suzuki–Miyaura coupling with racemic allyl halides

Understanding how catalytic asymmetric reactions with racemic starting materials can operate would enable new enantioselective cross-coupling reactions that give chiral products. Here we propose a catalytic cycle for the highly enantioselective Rh(I)-catalysed Suzuki–Miyaura coupling of boronic acids and racemic allyl halides. Natural abundance 13C kinetic isotope effects provide quantitative information about the transition-state structures of two key elementary steps in the catalytic cycle, transmetallation and oxidative addition. Experiments with configurationally stable, deuterium-labelled substrates revealed that oxidative addition can happen via syn- or anti-pathways, which control diastereoselectivity. Density functional theory calculations attribute the extremely high enantioselectivity to reductive elimination from a common Rh complex formed from both allyl halide enantiomers. Our conclusions are supported by analysis of the reaction kinetics. These insights into the sequence of bond-forming steps and their transition-state structures will contribute to our understanding of asymmetric Rh–allyl chemistry and enable the discovery and application of asymmetric reactions with racemic substrates

The <i>Plasmodium</i> eukaryotic initiation factor-2α kinase IK2 controls the latency of sporozoites in the mosquito salivary glands

Sporozoites, the invasive form of malaria parasites transmitted by mosquitoes, are quiescent while in the insect salivary glands. Sporozoites only differentiate inside of the hepatocytes of the mammalian host. We show that sporozoite latency is an active process controlled by a eukaryotic initiation factor-2α (eIF2α) kinase (IK2) and a phosphatase. IK2 activity is dominant in salivary gland sporozoites, leading to an inhibition of translation and accumulation of stalled mRNAs into granules. When sporozoites are injected into the mammalian host, an eIF2α phosphatase removes the PO4 from eIF2α-P, and the repression of translation is alleviated to permit their transformation into liver stages. In IK2 knockout sporozoites, eIF2α is not phosphorylated and the parasites transform prematurely into liver stages and lose their infectivity. Thus, to complete their life cycle, Plasmodium sporozoites exploit the mechanism that regulates stress responses in eukaryotic cells