An Artificial Intelligence Approach for Tackling Conformational Energy Uncertainties in Chiroptical Spectroscopies

Determination of the absolute configuration of chiral molecules is a prerequisite for obtaining a fundamental understanding in any chirality-related field. The interaction with polarised light has proven to be a powerful means to determine this absolute configuration, but its application rests on the comparison between experimental and computed spectra for which the inherent uncertainty in conformational Boltzmann factors has proven to be extremely hard to tackle. Here we present a novel approach that overcomes this issue by combining a genetic algorithm that identifies the relevant conformers by accounting for the uncertainties in DFT relative energies, and a hierarchical clustering algorithm that analyses the trends in the spectra of the considered conformers and identifies on-the-fly when a given chiroptical technique is not able to make reliable predictions. The effectiveness of this approach is demonstrated by considering the challenging cases of papuamine and haliclonadiamine, two bis-indane natural products with eight chiral centres and considerable conformational heterogeneity that could not be assigned unambiguously with current approaches.</p

Tree method for quantum vortex dynamics

We present a numerical method to compute the evolution of vortex filaments in superfluid helium. The method is based on a tree algorithm which considerably speeds up the calculation of Biot-Savart integrals. We show that the computational cost scales as Nlog{(N) rather than N squared, where $N$ is the number of discretization points. We test the method and its properties for a variety of vortex configurations, ranging from simple vortex rings to a counterflow vortex tangle, and compare results against the Local Induction Approximation and the exact Biot-Savart law.Comment: 12 pages, 10 figure

Alterações nas reservas de sementes de Dalbergia nigra ((Vell.) Fr. All. ex Benth.) durante a hidratação

Seed imbibitions is the first stage of the germination process and is characterized by the hydration of tissues and cells and the activation and/or induction of the enzymes responsible for mobilizing reserves for respiration and the construction of new cell structures. The objective of this study was to investigate the alterations in reserve substances during slow hydration of Bahia Rosewood (Dalbergia nigra) seeds in water. Seeds from two different lots (Lot I and II) were placed in saturated desiccators (95-99% RH) to hydrate at 15 and 25 °C until water contents of 10, 15, 20 and 25% were reached. At each level of hydration, changes in lipid reserves, soluble carbohydrates, starch and soluble proteins were evaluated. The mobilization of reserves was similarly assessed in both lots, with no differences being observed between the two hydration temperatures. Lipid contents showed little variation during hydration, while the contents of soluble carbohydrates and starch decreased after the 15% water content level. Soluble proteins showed a gradual tendency to decrease between the control (dry seeds) up to 25% water content

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease