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BackgroundAlthough conventional prediction models for surgical patients often ignore intraoperative time-series data, deep learning approaches are well-suited to incorporate time-varying and non-linear data with complex interactions. Blood lactate concentration is one important clinical marker that can reflect the adequacy of systemic perfusion during cardiac surgery. During cardiac surgery and cardiopulmonary bypass, minute-level data is available on key parameters that affect perfusion. The goal of this study was to use machine learning and deep learning approaches to predict maximum blood lactate concentrations after cardiac surgery. We hypothesized that models using minute-level intraoperative data as inputs would have the best predictive performance. MethodsAdults who underwent cardiac surgery with cardiopulmonary bypass were eligible. The primary outcome was maximum lactate concentration within 24 h postoperatively. We considered three classes of predictive models, using the performance metric of mean absolute error across testing folds: (1) static models using baseline preoperative variables, (2) augmentation of the static models with intraoperative statistics, and (3) a dynamic approach that integrates preoperative variables with intraoperative time series data. Results2,187 patients were included. For three models that only used baseline characteristics (linear regression, random forest, artificial neural network) to predict maximum postoperative lactate concentration, the prediction error ranged from a median of 2.52 mmol/L (IQR 2.46, 2.56) to 2.58 mmol/L (IQR 2.54, 2.60). The inclusion of intraoperative summary statistics (including intraoperative lactate concentration) improved model performance, with the prediction error ranging from a median of 2.09 mmol/L (IQR 2.04, 2.14) to 2.12 mmol/L (IQR 2.06, 2.16). For two modelling approaches (recurrent neural network, transformer) that can utilize intraoperative time-series data, the lowest prediction error was obtained with a range of median 1.96 mmol/L (IQR 1.87, 2.05) to 1.97 mmol/L (IQR 1.92, 2.05). Intraoperative lactate concentration was the most important predictive feature based on Shapley additive values. Anemia and weight were also important predictors, but there was heterogeneity in the importance of other features. ConclusionPostoperative lactate concentrations can be predicted using baseline and intraoperative data with moderate accuracy. These results reflect the value of intraoperative data in the prediction of clinically relevant outcomes to guide perioperative management. 

Explaining why animal groups vary in size is a fundamental problem in behavioral ecology. One hypothesis is that life-history differences among individuals lead to sorting of phenotypes into groups of different sizes where each individual does best. This hypothesis predicts that individuals should be relatively consistent in their use of particular group sizes across time. Little is known about whether animals’ choice of group size is repeatable across their lives, especially in long-lived species. We studied consistency in choice of breeding-colony size in colonially nesting cliff swallows ( Petrochelidon pyrrhonota ) in western Nebraska, United States, over a 32-year period, following 6,296 birds for at least four breeding seasons. Formal repeatability of size choice for the population was about 0.41. About 45% of individuals were relatively consistent in choice of colony size, while about 40% varied widely in the colony size they occupied. Birds using the smaller and larger colonies appeared more consistent in size use than birds occupying more intermediate sized colonies. Consistency in colony size was also influenced by whether a bird used the same physical colony site each year and whether the site had been fumigated to remove ectoparasites. The difference between the final and initial colony sizes for an individual, a measure of the net change in its colony size over its life, did not significantly depart from 0 for the dataset as a whole. However, different year-cohorts did show significant net change in colony size, both positive and negative, that may have reflected fluctuating selection on colony size among years based on climatic conditions. The results support phenotypic sorting as an explanation for group size variation, although cliff swallows also likely use past experience at a given site and the extent of ectoparasitism to select breeding colonies. 

Abstract The design, principles of operation, calibration, and data analysis approaches of the Michelson Interferometer for Global High-resolution Thermospheric Imaging (MIGHTI) on the NASA Ionospheric Connection (ICON) satellite have been documented prior to the ICON launch. Here we update and expand on the MIGHTI wind data analysis and discuss the on-orbit instrument performance. In particular, we show typical raw data and we describe key processing steps, including the correction of a “signal-intensity dependent phase shift,” which is necessitated by unexpected detector behavior. We describe a new zero-wind calibration approach that is preferred over the originally planned approach due to its higher precision. Similar to the original approach, the new approach is independent of any a priori data. A detailed update on the wind uncertainties is provided and compared to the mission requirements, showing that MIGHTI has met the ICON mission requirements. While MIGHTI observations are not required to produce absolute airglow brightness profiles, we describe a relative brightness profile product, which is included in the published data. We briefly review the spatial resolution of the MIGHTI wind data in addition to the data coverage and data gaps that occurred during the nominal mission. Finally, we include comparisons of the MIGHTI wind data with ground-based Fabry-Perot interferometer observations and meteor radar observations, updating previous studies with more recent data, again showing good agreement. The data processing steps covered in this work and all the derived wind data correspond to the MIGHTI data release Version 5 (v05). 

Some birds exhibit a maxillary overhang, in which the tip of the upper beak projects beyond the lower mandible and may curve downward. The overhang is thought to help control ectoparasites on the feathers. Little is known about the extent to which the maxillary overhang varies spatially or temporally within populations of the same species. The colonial cliff swallow ( Petrochelidon pyrrhonota ) has relatively recently shifted to almost exclusive use of artificial structures such as bridges and highway culverts for nesting and consequently has been exposed to higher levels of parasitism than on its ancestral cliff nesting sites. We examined whether increased ectoparasitism may have favored recent changes in the extent of the maxillary overhang. Using a specimen collection of cliff swallows from western Nebraska, USA, spanning 40 years and field data on live birds, we found that the extent of the maxillary overhang increased across years in a nonlinear way, peaking in the late 2000’s, and varied inversely with cliff swallow colony size for unknown reasons. The number of fleas on nestling cliff swallows declined in general over this period. Those birds with perceptible overhangs had fewer swallow bugs on the outside of their nest, but they did not have higher nesting success than birds with no overhangs. The intraspecific variation in the maxillary overhang in cliff swallows was partly consistent with it having a functional role in combatting ectoparasites. The temporal increase in the extent of the overhang may be a response by cliff swallows to their relatively recent increased exposure to parasitism. Our results demonstrate that this avian morphological trait can change rapidly over time. 

Rubidium atoms in a honeycomb optical lattice are driven through band structure singularities. 

Abstract The survival of insects that are dormant in winter may either increase or decrease as a consequence of elevated winter temperatures under climate change. Warming can be deleterious when metabolism of the overwintering life stages increases to the point that energy reserves are exhausted before postoverwintering reemergence. We examined experimentally how overwintering survival of swallow bugs (Hemiptera: Cimicidae: Cimex vicarius Horvath), an ectoparasite primarily of cliff swallows (Passeriformes: Hirundinidae: Petrochelidon pyrrhonota Vieillot), was affected by a 3°C rise in mean daily temperature for populations in Oklahoma, Nebraska, and North Dakota. Adult and nymphal swallow bugs exposed to elevated temperature had an average reduction of approximately 31% in overwintering survival (from July/August to April/May), relative to controls exposed to current region-specific ambient-like conditions. Adult males in both groups survived less well in Nebraska and North Dakota than adult males in Oklahoma, but there was no consistent latitudinal effect of the elevated heat treatment. Our results indicate that projected increases in mean temperature in the Great Plains by 2050 could result in fewer swallow bugs surviving the winter and thus a reduced population size upon the arrival of their primary host in the spring, potentially affecting cliff swallow reproductive success, site use, and breeding phenology. Global climate change may alter the dynamics of host–parasite systems by reducing overall parasite abundance.