1. |
- Gerasimov, Jennifer Yevgenia, 1985-, et al.
(författare)
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Rational Materials Design for In Operando Electropolymerization of Evolvable Organic Electrochemical Transistors
- 2022
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Ingår i: Advanced Functional Materials. - : John Wiley and Sons Inc. - 1616-301X .- 1616-3028. ; 32
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Tidskriftsartikel (refereegranskat)abstract
- Organic electrochemical transistors formed by in operando electropolymerization of the semiconducting channel are increasingly becoming recognized as a simple and effective implementation of synapses in neuromorphic hardware. However, very few studies have reported the requirements that must be met to ensure that the polymer spreads along the substrate to form a functional conducting channel. The nature of the interface between the substrate and various monomer precursors of conducting polymers through molecular dynamics simulations is investigated, showing that monomer adsorption to the substrate produces an increase in the effective monomer concentration at the surface. By evaluating combinatorial couples of monomers baring various sidechains with differently functionalized substrates, it is shown that the interactions between the substrate and the monomer precursor control the lateral growth of a polymer film along an inert substrate. This effect has implications for fabricating synaptic systems on inexpensive, flexible substrates. © 2022 The Authors.
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2. |
- Strannegård, Claes, 1962, et al.
(författare)
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Ecosystem Models Based on Artificial Intelligence
- 2022
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Ingår i: 34th Workshop of the Swedish Artificial Intelligence Society, SAIS 2022. - : IEEE.
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Konferensbidrag (refereegranskat)abstract
- Ecosystem models can be used for understanding general phenomena of evolution, ecology, and ethology. They can also be used for analyzing and predicting the ecological consequences of human activities on specific ecosystems, e.g., the effects of agriculture, forestry, construction, hunting, and fishing. We argue that powerful ecosystem models need to include reasonable models of the physical environment and of animal behavior. We also argue that several well-known ecosystem models are unsatisfactory in this regard. Then we present the open-source ecosystem simulator Ecotwin, which is built on top of the game engine Unity. To model a specific ecosystem in Ecotwin, we first generate a 3D Unity model of the physical environment, based on topographic or bathymetric data. Then we insert digital 3D models of the organisms of interest into the environment model. Each organism is equipped with a genome and capable of sexual or asexual reproduction. An organism dies if it runs out of some vital resource or reaches its maximum age. The animal models are equipped with behavioral models that include sensors, actions, reward signals, and mechanisms of learning and decision-making. Finally, we illustrate how Ecotwin works by building and running one terrestrial and one marine ecosystem model.
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3. |
- Atance, Sara Romeo, et al.
(författare)
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De Novo Drug Design Using Reinforcement Learning with Graph- Based Deep Generative Models
- 2022
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Ingår i: Journal of Chemical Information and Modeling. - : American Chemical Society (ACS). - 1549-960X .- 1549-9596. ; 62:20, s. 4863-4872
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Tidskriftsartikel (refereegranskat)abstract
- Machine learning provides effective computational tools for exploring the chemical space via deep generative models. Here, we propose a new reinforcement learning scheme to finetune graph-based deep generative models for de novo molecular design tasks. We show how our computational framework can successfully guide a pretrained generative model toward the generation of molecules with a specific property profile, even when such molecules are not present in the training set and unlikely to be generated by the pretrained model. We explored the following tasks: generating molecules of decreasing/increasing size, increasing drug-likeness, and increasing bioactivity. Using the proposed approach, we achieve a model which generates diverse compounds with predicted DRD2 activity for 95% of sampled molecules, outperforming previously reported methods on this metric.
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4. |
- Chakrabarti, Kalyan S., et al.
(författare)
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A litmus test for classifying recognition mechanisms of transiently binding proteins
- 2022
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Ingår i: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723 .- 2041-1723. ; 13:1
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Tidskriftsartikel (refereegranskat)abstract
- Partner recognition in protein binding is critical for all biological functions, and yet, delineating its mechanism is challenging, especially when recognition happens within microseconds. We present a theoretical and experimental framework based on straight-forward nuclear magnetic resonance relaxation dispersion measurements to investigate protein binding mechanisms on sub-millisecond timescales, which are beyond the reach of standard rapid-mixing experiments. This framework predicts that conformational selection prevails on ubiquitin’s paradigmatic interaction with an SH3 (Src-homology 3) domain. By contrast, the SH3 domain recognizes ubiquitin in a two-state binding process. Subsequent molecular dynamics simulations and Markov state modeling reveal that the ubiquitin conformation selected for binding exhibits a characteristically extended C-terminus. Our framework is robust and expandable for implementation in other binding scenarios with the potential to show that conformational selection might be the design principle of the hubs in protein interaction networks.
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5. |
- Chemtob, Raphaelle A, et al.
(författare)
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Stroke in acute type A aortic dissection: the Nordic Consortium for Acute Type A Aortic Dissection (NORCAAD).
- 2020
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Ingår i: European journal of cardio-thoracic surgery : official journal of the European Association for Cardio-thoracic Surgery. - 1873-734X. ; 58:5, s. 1027-1034
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Tidskriftsartikel (refereegranskat)abstract
- Stroke is a serious complication in patients with acute type A aortic dissection (ATAAD). Previous studies investigating stroke in ATAAD patients have been limited by small cohorts and have shown diverging results. We sought to identify risk factors for stroke and to evaluate the effect of stroke on outcomes in surgical ATAAD patients.The Nordic Consortium for Acute Type A Aortic Dissection database included patients operated for ATAAD at 8 Scandinavian Hospitals between 2005 and 2014.Stroke occurred in 177 (15.7%) out of 1128 patients. Patients with stroke presented more frequently with cerebral malperfusion (20.6% vs 6.3%, P<0.001), syncope (30.6% vs 17.6%, P<0.001), cardiogenic shock (33.1% vs 20.7%, P<0.001) and pericardial tamponade (25.9% vs 14.7%, P<0.001) and more often underwent total aortic arch replacement (10.7% vs 4.7%, P=0.016), compared to patients without stroke. In the 86 patients presenting with cerebral malperfusion, 38.4% developed stroke. Thirty-day and 5-year mortality in patients with and without stroke were 27.1% vs 13.6% and 42.9% vs 25.6%, respectively. Stroke was an independent predictor of early- [odds ratio 2.02, 95% confidence interval (CI) 1.34-3.05; P<0.001] and midterm mortality (hazard ratio 1.68, 95% CI 1.27-2.23; P<0.001).Stroke in ATAAD patients is associated with increased early- and midterm mortality. Preoperative cerebral malperfusion and impaired haemodynamics, as well as total aortic arch replacement, were more frequent among patients who developed stroke. Importantly, a large proportion of patients presenting with cerebral malperfusion did not develop a permanent stroke, indicating that signs of cerebral malperfusion should not be considered a contraindication for surgery.
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6. |
- Geijer, Cecilia, 1980, et al.
(författare)
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Genomic and transcriptomic analysis of Candida intermedia reveals the genetic determinants for its xylose-converting capacity
- 2020
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Ingår i: Biotechnology for Biofuels. - : Springer Science and Business Media LLC. - 1754-6834. ; 13:1
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Tidskriftsartikel (refereegranskat)abstract
- Background An economically viable production of biofuels and biochemicals from lignocellulose requires microorganisms that can readily convert both the cellulosic and hemicellulosic fractions into product. The yeast Candida intermedia displays a high capacity for uptake and conversion of several lignocellulosic sugars including the abundant pentose d-xylose, an underutilized carbon source since most industrially relevant microorganisms cannot naturally ferment it. Thus, C. intermedia constitutes an important source of knowledge and genetic information that could be transferred to industrial microorganisms such as Saccharomyces cerevisiae to improve their capacity to ferment lignocellulose-derived xylose. Results To understand the genetic determinants that underlie the metabolic properties of C. intermedia, we sequenced the genomes of both the in-house-isolated strain CBS 141442 and the reference strain PYCC 4715. De novo genome assembly and subsequent analysis revealed C. intermedia to be a haploid species belonging to the CTG clade of ascomycetous yeasts. The two strains have highly similar genome sizes and number of protein-encoding genes, but they differ on the chromosomal level due to numerous translocations of large and small genomic segments. The transcriptional profiles for CBS 141442 grown in medium with either high or low concentrations of glucose and xylose were determined through RNA-sequencing analysis, revealing distinct clusters of co-regulated genes in response to different specific growth rates, carbon sources and osmotic stress. Analysis of the genomic and transcriptomic data also identified multiple xylose reductases, one of which displayed dual NADH/NADPH co-factor specificity that likely plays an important role for co-factor recycling during xylose fermentation. Conclusions In the present study, we performed the first genomic and transcriptomic analysis of C. intermedia and identified several novel genes for conversion of xylose. Together the results provide insights into the mechanisms underlying saccharide utilization in C. intermedia and reveal potential target genes to aid in xylose fermentation in S. cerevisiae.
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7. |
- Geirsson, Arnar, et al.
(författare)
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Hospital volumes and later year of operation correlates with better outcomes in acute Type A aortic dissection
- 2018
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Ingår i: European Journal of Cardio-Thoracic Surgery. - : Oxford University Press. - 1010-7940 .- 1873-734X. ; 53:1, s. 276-281
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Tidskriftsartikel (refereegranskat)abstract
- OBJECTIVES: Acute Type A aortic dissection remains a life-threatening disease, but there are indications that its surgical mortality is decreasing. The aim of this report was to study how surgical mortality has changed and what influences those changes.METHODS: Nordic Consortium for Acute Type A Aortic Dissection is a retrospective database comprising 1159 patients (mean age 61.6 ± 12.2 years, 68% male) treated for acute Type A aortic dissection at 8 centres in Denmark, Finland, Iceland and Sweden from 2005 to 2014. Data gathered included demographics, symptoms, type of procedure, complications and 30-day mortality.RESULTS: The annual number of operations increased significantly from 85 in 2005 to 150 in 2014 (P < 0.001). Chest pain was present in 85% of patients, 24% were hypotensive on presentation and 28% had malperfusion syndrome. Open distal anastomosis technique under hypothermic circulatory arrest was used in 85% of cases and its use increased significantly throughout the study. The 30-day mortality decreased from 24% in 2005 to 13% in 2014 (P = 0.003). Independent predictors for 30-day mortality were preoperative cardiac arrest, malperfusion syndrome, Penn Class C, Penn Class B and C and cardiopulmonary bypass time, whereas later calendar year and higher hospital operative volumes predicted improved survival.CONCLUSIONS: Surgical mortality for acute Type A aortic dissection remains high but has decreased significantly over the last decade. This correlated with later year of operation and increased the number of operations performed per year, indicating that cumulative surgical experience contributes significantly to improved surgical outcomes.
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8. |
- Genheden, Samuel, et al.
(författare)
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Prediction of the Chemical Context for Buchwald-Hartwig Coupling Reactions
- 2022
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Ingår i: Molecular Informatics. - : Wiley. - 1868-1751 .- 1868-1743. ; 41:8
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Tidskriftsartikel (refereegranskat)abstract
- We present machine learning models for predicting the chemical context for Buchwald-Hartwig coupling reactions, i. e., what chemicals to add to the reactants to give a productive reaction. Using reaction data from in-house electronic lab notebooks, we train two models: one based on single-label data and one based on multi-label data. Both models show excellent top-3 accuracy of approximately 90 %, which suggests strong predictivity. Furthermore, there seems to be an advantage of including multi-label data because the multi-label model shows higher accuracy and better sensitivity for the individual contexts than the single-label model. Although the models are performant, we also show that such models need to be re-trained periodically as there is a strong temporal characteristic to the usage of different contexts. Therefore, a model trained on historical data will decrease in usefulness with time as newer and better contexts emerge and replace older ones. We hypothesize that such significant transitions in the context-usage will likely affect any model predicting chemical contexts trained on historical data. Consequently, training context prediction models warrants careful planning of what data is used for training and how often the model needs to be re-trained.
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9. |
- Hempel, Tim, et al.
(författare)
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Markov field models: Scaling molecular kinetics approaches to large molecular machines
- 2022
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Ingår i: Current Opinion in Structural Biology. - : Elsevier BV. - 1879-033X .- 0959-440X. ; 77
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Forskningsöversikt (refereegranskat)abstract
- With recent advances in structural biology, including experi-mental techniques and deep learning-enabled high-precision structure predictions, molecular dynamics methods that scale up to large biomolecular systems are required. Current state-of-the-art approaches in molecular dynamics modeling focus on encoding global configurations of molecular systems as distinct states. This paradigm commands us to map out all possible structures and sample transitions between them, a task that becomes impossible for large-scale systems such as biomolecular complexes. To arrive at scalable molecular models, we suggest moving away from global state de-scriptions to a set of coupled models that each describe the dynamics of local domains or sites of the molecular system. We describe limitations in the current state-of-the-art global -state Markovian modeling approaches and then introduce Markov field models as an umbrella term that includes models from various scientific communities, including Independent Markov decomposition, Ising and Potts models, and (dynamic) graphical models, and evaluate their use for computational molecular biology. Finally, we give a few examples of early adoptions of these ideas for modeling molecular kinetics and thermodynamics.
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10. |
- Hempel, Tim, et al.
(författare)
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Molecular mechanism of inhibiting the SARS-CoV-2 cell entry facilitator TMPRSS2 with camostat and nafamostat
- 2021
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Ingår i: Chemical Science. - : Royal Society of Chemistry (RSC). - 2041-6539 .- 2041-6520. ; 12:3, s. 983-992
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Tidskriftsartikel (refereegranskat)abstract
- The entry of the coronavirus SARS-CoV-2 into human lung cells can be inhibited by the approved drugs camostat and nafamostat. Here we elucidate the molecular mechanism of these drugs by combining experiments and simulations. In vitro assays confirm that both drugs inhibit the human protein TMPRSS2, a SARS-Cov-2 spike protein activator. As no experimental structure is available, we provide a model of the TMPRSS2 equilibrium structure and its fluctuations by relaxing an initial homology structure with extensive 330 microseconds of all-atom molecular dynamics (MD) and Markov modeling. Through Markov modeling, we describe the binding process of both drugs and a metabolic product of camostat (GBPA) to TMPRSS2, reaching a Michaelis complex (MC) state, which precedes the formation of a long-lived covalent inhibitory state. We find that nafamostat has a higher MC population than camostat and GBPA, suggesting that nafamostat is more readily available to form the stable covalent enzyme-substrate intermediate, effectively explaining its high potency. This model is backed by our in vitro experiments and consistent with previous virus cell entry assays. Our TMPRSS2-drug structures are made public to guide the design of more potent and specific inhibitors.
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