Transfer learning for affordable and high quality tunneling splittings from instanton calculations

The combination of transfer learning (TL) a low level potential energy surface (PES) to a higher level of electronic structure theory together with ring-polymer instanton (RPI) theory is explored and applied to malonaldehyde. The RPI approach provides a semiclassical approximation of the tunneling splitting and depends sensitively on the accuracy of the PES. With second order M{\o}ller-Plesset perturbation theory (MP2) as the low-level (LL) model and energies and forces from coupled cluster singles, doubles and perturbative triples (CCSD(T)) as the high-level (HL) model, it is demonstrated that CCSD(T) information from only 25 to 50 judiciously selected structures along and around the instanton path suffice to reach HL-accuracy for the tunneling splitting. In addition, the global quality of the HL-PES is demonstrated through a mean average error of 0.3 kcal/mol for energies up to 40 kcal/mol above the minimum energy structure (a factor of 2 higher than the energies employed during TL) and $< 2$ cm$^{-1}$ for harmonic frequencies compared with computationally challenging normal mode calculations at the CCSD(T) level

ML Models of Vibrating H2_2CO: Comparing Reproducing Kernels, FCHL and PhysNet

Machine Learning (ML) has become a promising tool for improving the quality of atomistic simulations. Using formaldehyde as a benchmark system for intramolecular interactions, a comparative assessment of ML models based on state-of-the-art variants of deep neural networks (NN), reproducing kernel Hilbert space (RKHS+F), and kernel ridge regression (KRR) is presented. Learning curves for energies and atomic forces indicate rapid convergence towards excellent predictions for B3LYP, MP2, and CCSD(T)-F12 reference results for modestly sized (in the hundreds) training sets. Typically, learning curve off-sets decay as one goes from NN (PhysNet) to RKHS+F to KRR (FCHL). Conversely, the predictive power for extrapolation of energies towards new geometries increases in the same order with RKHS+F and FCHL performing almost equally. For harmonic vibrational frequencies, the picture is less clear, with PhysNet and FCHL yielding respectively flat learning at $\sim$ 1 and $\sim$ 0.2 cm$^{-1}$ no matter which reference method, while RKHS+F models level off for B3LYP, and exhibit continued improvements for MP2 and CCSD(T)-F12. Finite-temperature molecular dynamics (MD) simulations with the same initial conditions yield indistinguishable infrared spectra with good performance compared with experiment except for the high-frequency modes involving hydrogen stretch motion which is a known limitation of MD for vibrational spectroscopy. For sufficiently large training set sizes all three models can detect insufficient convergence (``noise'') of the reference electronic structure calculations in that the learning curves level off. Transfer learning (TL) from B3LYP to CCSD(T)-F12 with PhysNet indicates that additional improvements in data efficiency can be achieved

COVID-19 risk stratification algorithms based on sTREM-1 and IL-6 in emergency department.

The coronavirus disease 2019 (COVID-19) pandemic has led to surges of patients presenting to emergency departments (EDs) and potentially overwhelming health systems. We sought to assess the predictive accuracy of host biomarkers at clinical presentation to the ED for adverse outcome. Prospective observational study of PCR-confirmed COVID-19 patients in the ED of a Swiss hospital. Concentrations of inflammatory and endothelial dysfunction biomarkers were determined at clinical presentation. We evaluated the accuracy of clinical signs and these biomarkers in predicting 30-day intubation/mortality, and oxygen requirement by calculating the area under the receiver-operating characteristic curve and by classification and regression tree analysis. Of 76 included patients with COVID-19, 24 were outpatients or hospitalized without oxygen requirement, 35 hospitalized with oxygen requirement, and 17 intubated/died. We found that soluble triggering receptor expressed on myeloid cells had the best prognostic accuracy for 30-day intubation/mortality (area under the receiver-operating characteristic curve, 0.86; 95% CI, 0.77-0.95) and IL-6 measured at presentation to the ED had the best accuracy for 30-day oxygen requirement (area under the receiver-operating characteristic curve, 0.84; 95% CI, 0.74-0.94). An algorithm based on respiratory rate and sTREM-1 predicted 30-day intubation/mortality with 94% sensitivity and 0.1 negative likelihood ratio. An IL-6-based algorithm had 98% sensitivity and 0.04 negative likelihood ratio for 30-day oxygen requirement. sTREM-1 and IL-6 concentrations in COVID-19 in the ED have good predictive accuracy for intubation/mortality and oxygen requirement. sTREM-1- and IL-6-based algorithms are highly sensitive to identify patients with adverse outcome and could serve as early triage tools

Conformational and state-specific effects in reactions of 2,3-dibromobutadiene with Coulomb-crystallized calcium ions

Recent advances in experimental methodology enabled studies of the quantum-state- and conformational dependence of chemical reactions under precisely controlled conditions in the gas phase. Here, we generated samples of selected gauche and s-trans 2,3-dibromobutadiene (DBB) by electrostatic deflection in a molecular beam and studied their reaction with Coulomb crystals of laser-cooled Ca + ions in an ion trap. The rate coefficients for the total reaction were found to strongly depend on both the conformation of DBB and the electronic state of Ca + . In the (4p) 2 P 1/2 and (3d) 2 D 3/2 excited states of Ca + , the reaction is capture-limited and faster for the gauche conformer due to long-range ion-dipole interactions. In the (4s) 2 S 1/2 ground state of Ca + , the reaction rate for s-trans DBB still conforms with the capture limit, while that for gauche DBB is strongly suppressed. The experimental observations were analysed with the help of adiabatic capture theory, ab initio calculations and reactive molecular dynamics simulations on a machine-learned full-dimensional potential energy surface of the system. The theory yields near-quantitative agreement for s-trans -DBB, but overestimates the reactivity of the gauche -conformer compared to the experiment. The present study points to the important role of molecular geometry even in strongly reactive exothermic systems and illustrates striking differences in the reactivity of individual conformers in gas-phase ion-molecule reactions

A first update on mapping the human genetic architecture of COVID-19

peer reviewe

Dyadisches Coping Inventar (DCI): Ein Fragebogen zur Erfassung des partnerschaftlichen Umgangs mit Stress

Stress und Stressbewältigung werden innerhalb von Partnerschaften zunehmend als dyadische Phänomene begriffen. Um dieser Sichtweise diagnostisch Rechnung zu tragen, wird das Dyadische Coping Inventar (DCI) zur Erfassung des partner-schaftlichen Umgangs mit Stress vorgestellt. Es handelt sich dabei um eine Weiter-entwicklung des Fragebogens zum dyadischen Coping (FDCT-N, Bodenmann 2000). Die faktorielle und psychometrische Überprüfung erfolgte an insgesamt N = 2399 Personen. Die Ergebnisse sprechen für die Testgüte des Instruments. Die theoretisch postulierte Faktorenstruktur konnte durch Faktorenanalysen empirische Evidenz finden. Die internen Konsistenzen fielen insgesamt gut aus, die Test-Retest-Korrelationen lagen erwartungsgemäß im mittleren Bereich. Die Konstruktvalidität war ebenfalls gut, die kriterienbezogene Validität befriedigend. Weiterhin werden Cut-Off-Werte präsentiert, die erlauben, Paare nach der Güte des dyadischen Copings einzuteilen. Das DCI eignet sich gleichermaßen für klinische Fragestellungen (z.B. Interventions-forschung), Partnerschaftsdiagnostik und Therapieevaluation sowie für entwicklungs- oder gesundheitspsychologische Fragestellungen

The inhibition of MAPK potentiates the anti-angiogenic efficacy of mTOR inhibitors

Malgré les nombreux progrès effectués dans la compréhension du cancer, cette maladie reste encore souvent incurable.¦Récemment, il a été démontré qu'afin de progresser un cancer doit développer de nouveaux vaisseaux sanguins lors d'un processus appelé angiogenèse tumorale. Il a aussi été démontré que l'inhibition de ce processus réduisait la croissance tumorale et de ce fait représente une importante cible thérapeutique contre le cancer.¦Les mécanismes impliqués dans l'angiogenèse tumorale ont été partiellement caractérisés et impliquent la prolifération, la survie et la migration des cellules endothéliales, cellules qui forment la paroi des vaisseaux sanguins. Quelques molécules régulant ces fonctions endothéliales ont été identifiées. Parmi celle-ci, une protéine intracellulaire appelée mTOR joue un rôle important dans l'angiogenèse tumorale. En effet, l'inhibition de mTOR par des molécules telle que la rapamycine, réduit l'angiogenèse dans de nombreux modèles expérimentaux ainsi que dans les tumeurs de patients traités par ces inhibiteurs.¦Notre étude montre toutefois que l'inhibition de mTOR dans les cellules endothéliales induit l'activation d'autres molécules comme la MAPK qui favorise la prolifération et la survie endothéliale et de ce fait réduit la capacité anti-angiogénique des inhibiteurs de mTOR. De plus, nous avons montré que le traitement de cellules endothéliales par des inhibiteurs de mTOR en combinaison avec des inhibiteurs de MAPK diminuait la prolifération, la survie et la migration endothéliales de manière additive comparée à une inhibition de mTOR ou de MAPK seule. Nous avons obtenu des résultats similaires dans un modèle d'angiogenèse in vitro. Finalement, nos résultats ont été confirmés in vivo dans un modèle de xénogreffe tumorale chez la souris immuno-compromise. Un traitement combiné d'inhibiteurs de mTOR et de MAPK produisait un effet anti-angiogénique supérieur à un traitement d'inhibiteur de mTOR ou de MAPK seul chez les souris immuno-compromises porteuses de tumeurs sous-cutanées.¦En résumé, nos résultats montrent que l'inhibition de mTOR dans les cellules endothéliales induit l'activation de MAPK qui compromet l'efficacité anti-angiogénique des inhibiteurs de mTOR. Ils démontrent également que la combinaison d'inhibiteurs de mTOR et de MAPK induit une efficacité anti-angiogénique supérieure à une inhibition de mTOR ou de MAPK seule. Nous proposons ainsi que l'utilisation de protocoles thérapeutiques qui bloquent à la fois mTOR et MAPK représente une approche prometteuse pour bloquer l'angiogenèse tumorale et donc la progression tumorale et mérite d'être évaluée chez les patients souffrant de cancers