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Marine heatwaves are increasing in frequency and duration, threatening tropical reef ecosystems through intensified coral bleaching events. We examined a strikingly variable spatial pattern of bleaching in Moorea, French Polynesia following a heatwave that lasted from November 2018 to July 2019. In July 2019, four months after the onset of bleaching, we surveyed > 5000 individual colonies of the two dominant coral genera,PocilloporaandAcropora, at 10 m and 17 m water depths, at six forereef sites around the island where temperature was measured. We found severe bleaching increased with colony size for both coral genera, butAcroporableached more severely thanPocilloporaoverall. Acroporableached more at 10 m than 17 m, likely due to higher light availability at 10 m compared to 17 m, or greater daily temperature fluctuation at depth. Bleaching inPocilloporacorals did not differ with depth but instead varied with the interaction of colony size and Accumulated Heat Stress (AHS), in that larger colonies (> 30 cm) were more sensitive to AHS than mid-size (10–29 cm) or small colonies (5–9 cm). Our findings provide insight into complex interactions among coral taxa, colony size, and water depth that produce high spatial variation in bleaching and related coral mortality.

 

Experiential purchases (focused ondoingrather thanhaving) provide more satisfaction than material goods. Here, we examine a different downstream consequence of spending money on experiences: fostering social connection. Consumers reported feeling more kinship with someone who had made a similar experiential purchase than someone who had made a similar material purchase—a result tied to the greater centrality of experiences to one's identity. This greater sense of connection that experiences provide applied even when someone else had made a similar, but superior purchase. Participants also reported feeling more connected to others in general, not just those who have made the same purchase, when reflecting on experiential consumption—and these feelings of connection were expressed in a greater desire to engage in social activities when participants considered their experiential purchases than when they considered their material purchases. Together, these results demonstrate that experiential consumption enhances people's social connection quite broadly.

 

GWSkyNet-Multiis a machine learning model developed for the classification of candidate gravitational-wave events detected by the LIGO and Virgo observatories. The model uses limited information released in the low-latency Open Public Alerts to produce prediction scores indicating whether an event is a merger of two black holes (BHs), a merger involving a neutron star (NS), or a non-astrophysical glitch. This facilitates time-sensitive decisions about whether to perform electromagnetic follow-up of candidate events during LIGO-Virgo-KAGRA (LVK) observing runs. However, it is not well understood how the model is leveraging the limited information available to make its predictions. As a deep learning neural network, the inner workings of the model can be difficult to interpret, impacting our trust in its validity and robustness. We tackle this issue by systematically perturbing the model and its inputs to explain what underlying features and correlations it has learned for distinguishing the sources. We show that the localization area of the 2D sky maps and the computed coherence versus incoherence Bayes factors are used as strong predictors for distinguishing between real events and glitches. The estimated distance to the source is further used to discriminate between binary BH mergers and mergers involving NSs. We leverage these findings to show that events misclassified byGWSkyNet-Multiin LVK’s third observing run have distinct sky areas, coherence factors, and distance values that influence the predictions and explain these misclassifications. The results help identify the model’s limitations and inform potential avenues for further optimization.

 

Abstract Biologics, pharmaceuticals containing or derived from living organisms, such as vaccines, antibodies, stem cells, blood, and blood products are a cornerstone of modern medicine. However, nearly all biologics have a major deficiency: they are inherently unstable, requiring storage under constant cold conditions. The so-called ‘cold-chain’, while effective, represents a serious economic and logistical hurdle for deploying biologics in remote, underdeveloped, or austere settings where access to cold-chain infrastructure ranging from refrigerators and freezers to stable electricity is limited. To address this issue, we explore the possibility of using anhydrobiosis, the ability of organisms such as tardigrades to enter a reversible state of suspended animation brought on by extreme drying, as a jumping off point in the development of dry storage technology that would allow biologics to be kept in a desiccated state under not only ambient but elevated temperatures. Here we examine the ability of different protein and sugar-based mediators of anhydrobiosis derived from tardigrades and other anhydrobiotic organisms to stabilize Human Blood Clotting Factor VIII under repeated dehydration/rehydration cycles, thermal stress, and long-term dry storage conditions. We find that while both protein and sugar-based protectants can stabilize the biologic pharmaceutical Human Blood Clotting Factor VIII under all these conditions, protein-based mediators offer more accessible avenues for engineering and thus tuning of protective function. Using classic protein engineering approaches, we fine tune the biophysical properties of a protein-based mediator of anhydrobiosis derived from a tardigrade, CAHS D. Modulating the ability of CAHS D to form hydrogels make the protein better or worse at providing protection to Human Blood Clotting Factor VIII under different conditions. This study demonstrates the effectiveness of tardigrade CAHS proteins and other mediators of desiccation tolerance at preserving the function of a biologic without the need for the cold-chain. In addition, our study demonstrates that engineering approaches can tune natural products to serve specific protective functions, such as coping with desiccation cycling versus thermal stress. Ultimately, these findings provide a proof of principle that our reliance on the cold-chain to stabilize life-saving pharmaceuticals can be broken using natural and engineered mediators of desiccation tolerance. 

The morphology of semiconducting polymer thin films is known to have a profound effect on their opto-electronic properties. Although considerable efforts have been made to control and understand the processes which influence the structures of these systems, it remains largely unclear what physical factors determine the arrangement of polymer chains in spin-cast films. Here, we investigate the role that the liquid–vapor interfaces in chlorobenzene solutions of poly(3-hexylthiophene) [P3HT] play in the conformational geometries adopted by the polymers. Using all-atom molecular dynamics (MD), and supported by toy-model simulations, we demonstrate that, with increasing concentration, P3HT oligomers in solution exhibit a strong propensity for the liquid–vapor interface. Due to the differential solubility of the backbone and side chains of the oligomers, in the vicinity of this interface, hexyl chains and the thiophene rings, have a clear orientational preference with respect to the liquid surface. At high concentrations, we additionally establish a substantial degree of inter-oligomer alignment and thiophene ring stacking near the interface. Our results broadly concur with the limited existing experimental evidence and we suggest that the interfacial structure can act as a template for film structure. We argue that the differences in solvent affinity of the side chain and backbone moieties are the driving force for the anisotropic orientations of the polymers near the interface. This finer grained description contrasts with the usual monolithic characterization of polymer units. Since this phenomenon can be controlled by concurrent chemical design and the choice of solvents, this work establishes a fabrication principle which may be useful to develop more highly functional polymer films. 

Amorphous calcium carbonate is an important precursor for biomineralization in marine organisms. Key outstanding problems include understanding the structure of amorphous calcium carbonate and rationalizing its metastability as an amorphous phase. Here we report high-quality atomistic models of amorphous calcium carbonate generated using state-of-the-art interatomic potentials to help guide fits to X-ray total scattering data. Exploiting a recently developed inversion approach, we extract from these models the effective Ca⋯Ca interaction potential governing the structure. This potential contains minima at two competing distances, corresponding to the two different ways that carbonate ions bridge Ca²⁺-ion pairs. We reveal an unexpected mapping to the Lennard-Jones–Gauss model normally studied in the context of computational soft matter. The empirical model parameters for amorphous calcium carbonate take values known to promote structural complexity. We thus show that both the complex structure and its resilience to crystallization are actually encoded in the geometrically frustrated effective interactions between Ca²⁺ions.

 

The major transitions in evolution include events and processes that result in the emergence of new levels of biological individuality. For collectives to undergo Darwinian evolution, their traits must be heritable, but the emergence of higher-level heritability is poorly understood and has long been considered a stumbling block for nascent evolutionary transitions. Using analytical models, synthetic biology, and biologically-informed simulations, we explored the emergence of trait heritability during the evolution of multicellularity. Prior work on the evolution of multicellularity has asserted that substantial collective-level trait heritability either emerges only late in the transition or requires some evolutionary change subsequent to the formation of clonal multicellular groups. In a prior analytical model, we showed that collective-level heritability not only exists but is usually more heritable than the underlying cell-level trait upon which it is based, as soon as multicellular groups form. Here, we show that key assumptions and predictions of that model are borne out in a real engineered biological system, with important implications for the emergence of collective-level heritability.