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Herein, we investigate supramolecular gelation behavior of a dendronized triphenylamine bis-urea macrocycle (1) in toluene in the presence and absence of sulfoxide chain stoppers. Macrocycle 1 assembles in the sol phase through intermolecular hy-drogen bonding interactions, spontaneously transitioning into a gel state when left undisturbed at room temperature. In tolu-ene, 1 displays a critical gelation concentration of 0.066 wt%, classifying it as a super-gelator. Furthermore, it exhibits a thermoreversible gel-sol phase transition as well as thixotropic behavior. Temperature-dependent 1H NMR spectroscopy is employed to probe the sol phase assembly of 1 with the size variations at different temperatures assessed by 2D DOSY. Rheological experiments at 10 °C were used to measure gelation response to mechanical stimuli. An amplitude sweep test highlights a linear viscoelastic region. Additionally, the self-healing behavior of gel 1 was verified through a series of strain cycles, where it showed complete recovery. Addition of chain stoppers 10% versus 1 of dimethyl sulfoxide (DMSO) and diphenyl sulfoxide (DPS) lead to weaker gels with smaller differences between the storage and the loss moduli. Rheological analysis revealed slower/partial recovery for the gel containing chain stoppers. Gels assembled from macrocyclic building blocks may retain homogeneous binding cavity and channels offering novel functional properties. 

The ability to control molecular-scale motion using electrostatic interactions was demonstrated using an N -phenylsuccinimide molecular rotor with an electrostatic pyridyl-gate. Protonation of the pyridal-gate forms stabilizing electrostatic interactions in the transition state of the bond rotation process that lowers the rotational barrier and increases the rate of rotation by two orders of magnitude. Molecular modeling and energy decomposition analysis confirm the dominant role of attractive electrostatic interactions in lowering the bond rotation transition state. 

Abstract Deep learning (DL) models can harness electronic health records (EHRs) to predict diseases and extract radiologic findings for diagnosis. With ambulatory chest radiographs (CXRs) frequently ordered, we investigated detecting type 2 diabetes (T2D) by combining radiographic and EHR data using a DL model. Our model, developed from 271,065 CXRs and 160,244 patients, was tested on a prospective dataset of 9,943 CXRs. Here we show the model effectively detected T2D with a ROC AUC of 0.84 and a 16% prevalence. The algorithm flagged 1,381 cases (14%) as suspicious for T2D. External validation at a distinct institution yielded a ROC AUC of 0.77, with 5% of patients subsequently diagnosed with T2D. Explainable AI techniques revealed correlations between specific adiposity measures and high predictivity, suggesting CXRs’ potential for enhanced T2D screening. 

Abstract Harvest of wild organisms is an important component of human culture, economy, and recreation, but can also put species at risk of extinction. Decisions that guide successful management actions therefore rely on the ability of researchers to link changes in demographic processes to the anthropogenic actions or environmental changes that underlie variation in demographic parameters.Ecologists often use population models or maximum sustained yield curves to estimate the impacts of harvest on wildlife and fish populations. Applications of these models usually focus exclusively on the impact of harvest and often fail to consider adequately other potential, often collinear, mechanistic drivers of the observed relationships between harvest and demographic rates. In this study, we used an integrated population model and long‐term data (1973–2016) to examine the relationships among hunting and natural mortality, the number of hunters, habitat conditions, and population size of blue‐winged tealSpatula discors, an abundant North American dabbling duck with a relatively fast‐paced life history strategy.Over the last two and a half decades of the study, teal abundance tripled, hunting mortality probability increased slightly (), and natural mortality probability increased substantially () at greater population densities. We demonstrate strong density‐dependent effects on natural mortality and fecundity as population density increased, indicative of compensatory harvest mortality and compensatory natality. Critically, an analysis that only assessed the relationship between survival and hunting mortality would spuriously indicate depensatory mortality due to multicollinearity between abundance, natural mortality and hunting mortality.Our findings demonstrate that models that only consider the direct effect of hunting on survival or natural mortality can fail to accurately assess the mechanistic impact of hunting on population dynamics due to multicollinearity among demographic drivers. This multicollinearity limits inference and may have strong impacts on applied management actions globally. 

Abstract The management of sustainable harvest of animal populations is of great ecological and conservation importance. Development of formal quantitative tools to estimate and mitigate the impacts of harvest on animal populations has positively impacted conservation efforts.The vast majority of existing harvest models, however, do not simultaneously estimate ecological and harvest impacts on demographic parameters and population trends. Given that the impacts of ecological drivers are often equal to or greater than the effects of harvest, and can covary with harvest, this disconnect has the potential to lead to flawed inference.In this study, we used Bayesian hierarchical models and a 43‐year capture–mark–recovery dataset from 404,241 female mallardsAnas platyrhynchosreleased in the North American midcontinent to estimate mallard demographic parameters. Furthermore, we model the dynamics of waterfowl hunters and habitat, and the direct and indirect effects of anthropogenic and ecological processes on mallard demographic parameters.We demonstrate that density dependence, habitat conditions and harvest can simultaneously impact demographic parameters of female mallards, and discuss implications for existing and future harvest management models.Our results demonstrate the importance of controlling for multicollinearity among demographic drivers in harvest management models, and provide evidence for multiple mechanisms that lead to partial compensation of mallard harvest. We provide a novel model structure to assess these relationships that may allow for improved inference and prediction in future iterations of harvest management models across taxa.