Understanding the competing pathways leading to hydropyrene and isoelisabethatriene

Terpene synthases are responsible for the biosynthesis of terpenes, the largest family of natural products. Hydropyrene synthase generates hydropyrene and hydropyrenol as its main products along with two byproducts, isoelisabethatrienes A and B. Fascinatingly, a single active site mutation (M75L) diverts the product distribution towards isoelisabethatrienes A and B. In the current work, we study the competing pathways leading to these products using quantum chemical calculations in the gas phase. We show that there is a great thermodynamic preference for hydropyrene and hydropyrenol formation, and hence most likely in the synthesis of the isoelisabethatriene products kinetic control is at play

Towards a comprehensive understanding of the structural dynamics of a bacterial diterpene synthase during catalysis

Terpenes constitute the largest and structurally most diverse natural product family. Most terpenoids exhibit a stereochemically complex macrocyclic core, which is generated by C–C bond forming of aliphatic oligo-prenyl precursors. This reaction is catalysed by terpene synthases (TPSs), which are capable of chaperoning highly reactive carbocation intermediates through an enzyme-specific reaction. Due to the instability of carbocation intermediates, the proteins’ structural dynamics and enzyme:substrate interactions during TPS catalysis remain elusive. Here, we present the structure of the diterpene synthase CotB2, in complex with an in crystallo cyclised abrupt reaction product and a substrate-derived diphosphate. We captured additional snapshots of the reaction to gain an overview of CotB2’s catalytic mechanism. To enhance insights into catalysis, structural information is augmented with multiscale molecular dynamic simulations. Our data represent fundamental TPS structure dynamics during catalysis, which ultimately enable rational engineering towards tailored terpene macrocycles that are inaccessible by conventional chemical synthesis

Role of Microsolvation and Quantum Effects in the Accurate Prediction of Kinetic Isotope Effects: The Case of Hydrogen Atom Abstraction in Ethanol by Atomic Hydrogen in Aqueous Solution

Hydrogen abstraction from ethanol by atomic hydrogen in aqueous solution is studied using two theoretical approaches: the multipath variational transition state theory (MP-VTST) and a path-integral formalism in combination with free-energy perturbation and umbrella sampling (PI-FEP/UM). The performance of the models is compared to experimental values of H kinetic isotope effects (KIE). Solvation models used in this study ranged from purely implicit, via mixed–microsolvation treated quantum mechanically via the density functional theory (DFT) to fully explicit representation of the solvent, which was incorporated using a combined quantum mechanical-molecular mechanical (QM/MM) potential. The effects of the transition state conformation and the position of microsolvating water molecules interacting with the solute on the KIE are discussed. The KIEs are in good agreement with experiment when MP-VTST is used together with a model that includes microsolvation of the polar part of ethanol by five or six water molecules, emphasizing the importance of explicit solvation in KIE calculations. Both, MP-VTST and PI-FEP/UM enable detailed characterization of nuclear quantum effects accompanying the hydrogen atom transfer reaction in aqueous solutionThis work was partially supported by the National Science Center in Poland (Sonata BIS grant UMO-2014/14/E/ST4/00041) and in part by PLGrid Infrastructure (Poland). S.K. acknowledges the Erasmus+ programme within which his 3-month project conducted at the University of Santiago de Compostela was possible. A.F-.R. thanks the Consellería de Cultura, Educación e Ordenación Universitaria (Axuda para Consolidación e Estructuración de unidades de investigación competitivas do Sistema Universitario de Galicia, Xunta de Galicia ED431C 2017/17 & Centro singular de investigación de Galicia acreditación 2016-2019, ED431G/09) and the European Regional Development Fund (ERDF). D.F-.C. also thanks Xunta de Galicia for financial support through a postdoctoral grantS

The Vehicle, February 1960, Vol. 2 no. 1

Vol. 2, No. 1 Table of Contents Editorialpage 2 A White Man\u27s BurdenRobert Mills Frenchpage 4 Passing TrainWayne Bakerpage 8 AutumnMajor Dan Ragainpage 8 Chaos in CulturevilleJ.B. Youngpage 9 Cure-allJerry N. Whitepage 13 Love-Long DistanceMary Ellen Mockbeepage 13 Metropolitan CaravanThomas McPeakpage 14 Ode to the Lion HuntersRichard Blairpage 16 ImmortalityM.E.M.page 16 EntranceSam Martinpage 16https://thekeep.eiu.edu/vehicle/1006/thumbnail.jp

The Vehicle, February 1960, Vol. 2 no. 1

Vol. 2, No. 1 Table of Contents Editorialpage 2 A White Man\u27s BurdenRobert Mills Frenchpage 4 Passing TrainWayne Bakerpage 8 AutumnMajor Dan Ragainpage 8 Chaos in CulturevilleJ.B. Youngpage 9 Cure-allJerry N. Whitepage 13 Love-Long DistanceMary Ellen Mockbeepage 13 Metropolitan CaravanThomas McPeakpage 14 Ode to the Lion HuntersRichard Blairpage 16 ImmortalityM.E.M.page 16 EntranceSam Martinpage 16https://thekeep.eiu.edu/vehicle/1006/thumbnail.jp

Roadmap on Photovoltaic Absorber Materials for Sustainable Energy Conversion

Photovoltaics (PVs) are a critical technology for curbing growing levels of anthropogenic greenhouse gas emissions, and meeting increases in future demand for low-carbon electricity. In order to fulfil ambitions for net-zero carbon dioxide equivalent (CO2eq) emissions worldwide, the global cumulative capacity of solar PVs must increase by an order of magnitude from 0.9 TWp in 2021 to 8.5 TWp by 2050 according to the International Renewable Energy Agency, which is considered to be a highly conservative estimate. In 2020, the Henry Royce Institute brought together the UK PV community to discuss the critical technological and infrastructure challenges that need to be overcome to address the vast challenges in accelerating PV deployment. Herein, we examine the key developments in the global community, especially the progress made in the field since this earlier roadmap, bringing together experts primarily from the UK across the breadth of the photovoltaics community. The focus is both on the challenges in improving the efficiency, stability and levelized cost of electricity of current technologies for utility-scale PVs, as well as the fundamental questions in novel technologies that can have a significant impact on emerging markets, such as indoor PVs, space PVs, and agrivoltaics. We discuss challenges in advanced metrology and computational tools, as well as the growing synergies between PVs and solar fuels, and offer a perspective on the environmental sustainability of the PV industry. Through this roadmap, we emphasize promising pathways forward in both the short- and long-term, and for communities working on technologies across a range of maturity levels to learn from each other.Comment: 160 pages, 21 figure

GWAS of Suicide Attempt in Psychiatric Disorders Identifies Association With Major Depression Polygenic Risk Scores

Objective: Over 90% of suicide attempters have a psychiatric diagnosis, however twin and family studies suggest that the genetic etiology of suicide attempt (SA) is partially distinct from that of the psychiatric disorders themselves. Here, we present the largest genome-wide association study (GWAS) on suicide attempt using major depressive disorder (MDD), bipolar disorder (BIP) and schizophrenia (SCZ) cohorts from the Psychiatric Genomics Consortium. Method: Samples comprise 1622 suicide attempters and 8786 non-attempters with MDD, 3264 attempters and 5500 non-attempters with BIP and 1683 attempters and 2946 non-attempters with SCZ. SA GWAS were performed by comparing attempters to non-attempters in each disorder followed by meta-analyses across disorders. Polygenic risk scoring was used to investigate the genetic relationship between SA and the psychiatric disorders. Results: Three genome-wide significant loci for SA were found: one associated with SA in MDD, one in BIP, and one in the meta-analysis of SA in mood disorders. These associations were not replicated in independent mood disorder cohorts from the UK Biobank and iPSYCH. No significant associations were found in the meta-analysis of all three disorders. Polygenic risk scores for major depression were significantly associated with SA in MDD (R2=0.25%, P=0.0006), BIP (R2=0.24%, P=0.0002) and SCZ (R2=0.40%, P=0.0006). Conclusions: This study provides new information on genetic associations and demonstrates that genetic liability for major depression increases risk for suicide attempt across psychiatric disorders. Further collaborative efforts to increase sample size hold potential to robustly identify genetic associations and gain biological insights into the etiology of suicide attempt

Hair Cortisol in Twins : Heritability and Genetic Overlap with Psychological Variables and Stress-System Genes

A. Palotie on työryhmän jäsen.Hair cortisol concentration (HCC) is a promising measure of long-term hypothalamus-pituitary-adrenal (HPA) axis activity. Previous research has suggested an association between HCC and psychological variables, and initial studies of inter-individual variance in HCC have implicated genetic factors. However, whether HCC and psychological variables share genetic risk factors remains unclear. The aims of the present twin study were to: (i) assess the heritability of HCC; (ii) estimate the phenotypic and genetic correlation between HPA axis activity and the psychological variables perceived stress, depressive symptoms, and neuroticism; using formal genetic twin models and molecular genetic methods, i.e. polygenic risk scores (PRS). HCC was measured in 671 adolescents and young adults. These included 115 monozygotic and 183 dizygotic twin-pairs. For 432 subjects PRS scores for plasma cortisol, major depression, and neuroticism were calculated using data from large genome wide association studies. The twin model revealed a heritability for HCC of 72%. No significant phenotypic or genetic correlation was found between HCC and the three psychological variables of interest. PRS did not explain variance in HCC. The present data suggest that HCC is highly heritable. However, the data do not support a strong biological link between HCC and any of the investigated psychological variables.Peer reviewe

The Science Performance of JWST as Characterized in Commissioning

This paper characterizes the actual science performance of the James Webb Space Telescope (JWST), as determined from the six month commissioning period. We summarize the performance of the spacecraft, telescope, science instruments, and ground system, with an emphasis on differences from pre-launch expectations. Commissioning has made clear that JWST is fully capable of achieving the discoveries for which it was built. Moreover, almost across the board, the science performance of JWST is better than expected; in most cases, JWST will go deeper faster than expected. The telescope and instrument suite have demonstrated the sensitivity, stability, image quality, and spectral range that are necessary to transform our understanding of the cosmos through observations spanning from near-earth asteroids to the most distant galaxies.Comment: 5th version as accepted to PASP; 31 pages, 18 figures; https://iopscience.iop.org/article/10.1088/1538-3873/acb29

BLOOM: A 176B-Parameter Open-Access Multilingual Language Model

Large language models (LLMs) have been shown to be able to perform new tasks based on a few demonstrations or natural language instructions. While these capabilities have led to widespread adoption, most LLMs are developed by resource-rich organizations and are frequently kept from the public. As a step towards democratizing this powerful technology, we present BLOOM, a 176B-parameter open-access language model designed and built thanks to a collaboration of hundreds of researchers. BLOOM is a decoder-only Transformer language model that was trained on the ROOTS corpus, a dataset comprising hundreds of sources in 46 natural and 13 programming languages (59 in total). We find that BLOOM achieves competitive performance on a wide variety of benchmarks, with stronger results after undergoing multitask prompted finetuning. To facilitate future research and applications using LLMs, we publicly release our models and code under the Responsible AI License