On the mass of atoms in molecules: Beyond the Born-Oppenheimer approximation

Describing the dynamics of nuclei in molecules requires a potential energy surface, which is traditionally provided by the Born-Oppenheimer or adiabatic approximation. However, we also need to assign masses to the nuclei. There, the Born-Oppenheimer picture does not account for the inertia of the electrons and only bare nuclear masses are considered. Nowadays, experimental accuracy challenges the theoretical predictions of rotational and vibrational spectra and requires to include the participation of electrons in the internal motion of the molecule. More than 80 years after the original work of Born and Oppenheimer, this issue still is not solved in general. Here, we present a theoretical and numerical framework to address this problem in a general and rigorous way. Starting from the exact factorization of the electron-nuclear wave function, we include electronic effects beyond the Born-Oppenheimer regime in a perturbative way via position-dependent corrections to the bare nuclear masses. This maintains an adiabatic-like point of view: the nuclear degrees of freedom feel the presence of the electrons via a single potential energy surface, whereas the inertia of electrons is accounted for and the total mass of the system is recovered. This constitutes a general framework for describing the mass acquired by slow degrees of freedom due to the inertia of light, bounded particles. We illustrate it with a model of proton transfer, where the light particle is the proton, and with corrections to the vibrational spectra of molecules. Inclusion of the light particle inertia allows to gain orders of magnitude in accuracy

Stickstoffeffizienz von unterschiedlich aufbereiteten Misten in einer Ackerbaufruchtfolge auf Lösslehm

Schlussfolgerungen Unter der Einschränkung, dass die alleinige Betrachtung der N-Wirkung nur einen Teil des N-Haushaltes ausmacht (z.B. Einbau von N in den Humuskörper), können aus den vorliegenden Ergebnissen folgende Schlussfolgerungen gezogen werden: • Bei der aeroben Rotte bzw. Kompostierung von Mist wurden im Vergleich zur anaeroben Lagerung von Mist grössere N-Verluste gemessen, d.h. es wurde bei diesen Verfahren folglich weniger Stickstoff auf die Parzellen ausgebracht. • Bei der Anwendung auf dem Feld erzielten Rottemist und Mistkompost im Vergleich zu Stapelmist jedoch eine bessere N-Wirkung. Dies macht deutlich, dass bei der Beurteilung unterschiedlicher Mistformen neben N-Verlusten und N-Gehalten insbesondere die N-Wirkung (Mineralisierungseigenschaften) berücksichtigt werden muss. • Mit qualitativ hochwertigem Grünabfallkompost kombiniert mit Güllegaben konnten vergleichbare Erträge wie bei den ausschliesslich mit Hofdüngern gedüngten Parzellen erzielt werden. Die N-Wirkung ist dabei aber aufgrund des Holzanteils der Grünabfallkomposte deutlich tiefer als bei Rottemist und Mistkompost. • Mit Vollgülle wurden – bei leicht höherer N-Wirkung – ähnliche Entzüge wie mit Rottemist und Mistkompost erreicht

Elevational species shifts in a warmer climate are overestimated when based on weather station data

Strong topographic variation interacting with low stature alpine vegetation creates a multitude of micro-habitats poorly represented by common 2m above the ground meteorological measurements (weather station data). However, the extent to which the actual habitat temperatures in alpine landscapes deviate from meteorological data at different spatial scales has rarely been quantified. In this study, we assessed thermal surface and soil conditions across topographically rich alpine landscapes by thermal imagery and miniature data loggers from regional (2-km2) to plot (1-m2) scale. The data were used to quantify the effects of spatial sampling resolution on current micro-habitat distributions and habitat loss due to climate warming scenarios. Soil temperatures showed substantial variation among slopes (2-3K) dependent on slope exposure, within slopes (3-4K) due to micro-topography and within 1-m2 plots (1K) as a result of plant cover effects. A reduction of spatial sampling resolution from 1 × 1m to 100 × 100m leads to an underestimation of current habitat diversity by 25% and predicts a six-times higher habitat loss in a 2-K warming scenario. Our results demonstrate that weather station data are unable to reflect the complex thermal patterns of aerodynamically decoupled alpine vegetation at the investigated scales. Thus, the use of interpolated weather station data to describe alpine life conditions without considering the micro-topographically induced thermal mosaic might lead to misinterpretation and inaccurate predictio

Electronic density response to molecular geometric changes from explicit electronic susceptibility calculations

We present a first principles approach to compute the response of the molecular electronic charge distribution to a geometric distortion. The scheme is based on an explicit representation of the linear electronic susceptibility. The linear electronic susceptibility is a tensor quantity which directly links the first-order electronic response density to the perturbation potential, without requiring self-consistency. We first show that the electronic susceptibility is almost invariant to small changes in the molecular geometry. We then compute the dipole moments from the response density induced by the geometrical changes. We verify the accuracy by comparing the results to the corresponding values obtained from the self- consistent calculations of the ground-state densities in both geometries

Depression is associated with decreased severity and lower mortality in non-elderly hospitalized adults with influenza in the United States

Background: Depression is associated with risk for chronic disease, though its relationship with infectious diseases is less understood. Depression may modify the clinical outcomes of patients with infectious diseases such as influenza via its association with inflammation. The objective of this study was to evaluate the relationships between depression and clinical outcomes in non-elderly adults with influenza infection. Methods: This was a secondary analysis of the Nationwide Inpatient Sample database, years 2012-2016. Hospitalized adults aged 18-65 admitted during each influenza season were included. Depression status was documented via ICD-10 codes. The association between depression and clinical outcomes (e.g. disease severity, length of hospital stay, and inpatient all-cause mortality) were evaluated using multivariable regression modeling. Results: A total of 44,292 patients were included, 12% with depression. After adjustment for confounding, non-elderly influenza patients with depression had a 3.8% decreased risk of a severe disease (95% CI: 1.9% - 5.7%; P=0.028). Conclusions: This study suggests that in non-elderly hospitalized patients with influenza, depression is associated with a decreased severity of illness and acute mortality. Chronic inflammation in those with depression may enhance the ability of the immune response to limit influenza infection or reduce pathologic acute inflammation associated with influenza disease

How to evaluate community predictions without thresholding?

Stacked species distribution models (S-SDM) provide a tool to make spatial predictions about communities by first modelling individual species and then stacking the modelled predictions to form assemblages. The evaluation of the predictive performance is usually based on a comparison of the observed and predicted community properties (e.g. species richness, composition). However, the most available and widely used evaluation metrics require the thresholding of single species' predicted probabilities of occurrence to obtain binary outcomes (i.e. presence/absence). This binarization can introduce unnecessary bias and error. Herein, we present and demonstrate the use of several groups of new or rarely used evaluation approaches and metrics for both species richness and community composition that do not require thresholding but instead directly compare the predicted probabilities of occurrences of species to the presence/absence observations in the assemblages. Community AUC, which is based on traditional AUC, measures the ability of a model to differentiate between species presences or absences at a given site according to their predicted probabilities of occurrence. Summing the probabilities gives the expected species richness and allows the estimation of the probability that the observed species richness is not different from the expected species richness based on the species' probabilities of occurrence. The traditional Sorensen and Jaccard similarity indices (which are based on presences/absences) were adapted to maxSorensen and maxJaccard and to probSorensen and probJaccard (which use probabilities directly). A further approach (improvement over null models) compares the predictions based on S-SDMs with the expectations from the null models to estimate the improvement in both species richness and composition predictions. Additionally, all metrics can be described against the environmental conditions of sites (e.g. elevation) to highlight the abilities of models to detect the variation in the strength of the community assembly processes in different environments. These metrics offer an unbiased view of the performance of community predictions compared to metrics that requiring thresholding. As such, they allow more straightforward comparisons of model performance among studies (i.e. they are not influenced by any subjective thresholding decisions).Peer reviewe

Biogeophysical controls on soil-atmosphere thermal differences : implications on warming Arctic ecosystems

Soil temperature (ST) has a key role in Arctic ecosystem functioning and global environmental change. However, soil thermal conditions do not necessarily follow synoptic temperature variations. This is because local biogeophysical processes can lead to a pronounced soil-atmosphere thermal offset (Delta T) while altering the coupling (beta Tau) between ST and ambient air temperature (AAT). Here, we aim to uncover the spatiotemporal variation in these parameters and identify their main environmental drivers. By deploying a unique network of 322 temperature loggers and surveying biogeophysical processes across an Arctic landscape, we found that the spatial variation in Delta T during the AAT 0 period, Delta T was controlled by soil characteristics, vegetation and solar radiation (Delta T = -0.6 degrees C +/- 1.0 degrees C). Importantly, Delta T was not constant throughout the seasons reflecting the influence of beta Tau on the rate of local soil warming being stronger after (mean beta Tau = 0.8 +/- 0.1) than before (beta Tau = 0.2 +/- 0.2) snowmelt. Our results highlight the need for continuous microclimatic and local environmental monitoring, and suggest a potential for large buffering and non-uniform warming of snow-dominated Arctic ecosystems under projected temperature increase.Peer reviewe

Prognostic value of clinical and MRI features in the screening of lipomatous lesions

BACKGROUND AND OBJECTIVES: Differentiation of lipomatous tumors mostly requires diagnostic biopsy but is essential to decide for the most adequate therapy. This study aims to investigate the prognostic value of available clinical and radiological features with regard to malignancy of the lesion, recurrence and survival. METHODS: In this retrospective cohort study, 104 patients with a biopsy-proven lipomatous tumor between 2010 and 2015 and a minimum clinical follow-up of two years were enrolled. Next to clinical features (age, gender, location of the lesion, histopathologic diagnosis, stage of disease, time to recurrence and death), MRI parameters were recorded retrospectively and blinded to the histological diagnosis. RESULTS: Malignant lipomatous tumors were associated with location in the lower extremities and MRI features like thick septation (>2 mm), presence of a non-adipose mass, foci of high T2/STIR signal and contrast agent enhancement. A non-adipose mass was a predictor for recurrence and inferior overall survival, while lesions with high T2/STIR signal showed higher risk of recurrence only. In combination, clinical and radiological features (lower extremities, septation > 2 mm, existence of non-adipose mass, contrast enhancement, and foci of high T2/STIR signal) predicted a malignant lipomatous tumor with an accuracy of 0.941 (95% CI of 0.899-0.983; 87% sensitivity, 86% specificity). CONCLUSION: Localization and characteristic MR features predict malignancy in most lipomatous lesions. Non-adipose masses are a poor prognostic factor, being associated with tumor recurrence and disease-related death

A novel multiplex qPCR targeting 23S rDNA for diagnosis of swine dysentery and porcine intestinal spirochaetosis

Figure S1. Consensus sequence alignment of the target DNA region within 23S ribosomal DNA. Primers (Brachy primer for. and Brachy primer rev.) on the target DNA are marked in grey. The probe for B. hyodysenteriae (Probe_hyo) is highlighted in yellow, the probe for B. pilosicoli (Probe_pilo) in purple, and the probe for the B. intermedia/B. innocens/B. murdochii (probe inter) in green. Differences in single residues are marked in red. (PDF 112 kb