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NoElastocaloric cooling is a promising solid-state alternative to vapor-compression refrigeration. In conventional systems, such as natural rubber, deformation induces entropy change accompanied by temperature release. Unloading the material restores the entropic state and is accompanied by cooling. Inverse elastocaloric effects have been detailed in shape memory alloys, where deformation induces loss of order and cooling. Here, we report on a distinctive inverse elastocaloric effect in liquid crystalline elastomers (LCEs) containing supramolecular hydrogen bonds. Upon deformation, the supramolecular LCE exhibits initial organization but then disorganizes as the intramesogenic hydrogen bonds are broken. Due to the liquid crystalline nature of the dimeric supramolecular bonds, the mechanochemical bond breakage manifests in a disruption in order. By disrupting the extent of liquid crystallinity in the system, we hypothesize that the network disorganizes to the deformation (e.g., entropy increases) and produces an inverse elastocaloric output.t Available 

Cholesteric liquid crystals (CLCs) exhibit Bragg reflection due to their spontaneous self-assembly into a one-dimensional photonic structure. Retaining this cholesteric order in a polymer network requires functionalizing liquid crystals with reactive end groups. However, conventional chemistries for synthesizing cholesteric liquid crystalline polymers often result in poor surface alignment and reduced optical quality. In this work, we investigate a thiol−ene step-growth polymerization approach to fabricate cholesteric liquid crystalline elastomers (CLCEs) with tunable mechanical properties and improved optical quality. By varying the cross-link density, we systematically study the effects on haze, cross-linking degree, and mechanical response. Compared to existing cholesteric liquid crystalline polymers, the thiol−ene-based CLCEs exhibit enhanced surface alignment, reduced haze, and greater mechanical tunability. These materials are further benchmarked against CLCEs synthesized via thiol−acrylate chain transfer polymerization, highlighting the advantages of the thiol−ene reaction for achieving precisely controlled properties in cholesteric polymer networks. 

The directional deformation of liquid crystalline elastomers (LCEs) is predicated on alignment, enforced by various processing techniques. Specifically, surface-aligned LCEs can exhibit higher temperature thermomechanical responses and weakened strain−temperature coupling in comparison to LCEs subjected to mechanical or rheological alignment. Recently, we reported enhanced stimuli response of mechanically aligned LCEs containing supramolecular liquid crystals. Here, we prepare supramolecular LCEs via surface-enforced alignment to study the impact of the supramolecular bond strength and intermolecular forces. This was evaluated using oxybenzoic acid (OBA) derivatives with and without pendant methyl groups as well as via oxybenzoic acid-pyridine complexes. Increased incorporation of supramolecular mesogens reduces the isotropic transition temperature and generally increases the strain−temperature coupling. The number of elastically active strands per unit volume, hydrogen bond conformations, and network morphology are affected by the supramolecular mesogens and influence the observed stimuli response. Overall, reduced intermolecular interactions correlate with more desirable actuation properties, demonstrating the influence of the supramolecular mesogen’s structure. 

The presence of heterogeneity in susceptibility, differences between hosts in their likelihood of becoming infected, can fundamentally alter disease dynamics and public health responses, for example, by changing the final epidemic size, the duration of an epidemic, and even the vaccination threshold required to achieve herd immunity. Yet, heterogeneity in susceptibility is notoriously difficult to detect and measure, especially early in an epidemic. Here we develop a method that can be used to detect and estimate heterogeneity in susceptibility given contact by using contact tracing data, which are typically collected early in the course of an outbreak. This approach provides the capability, given sufficient data, to estimate and account for the effects of this heterogeneity before they become apparent during an epidemic. It additionally provides the capability to analyze the wealth of contact tracing data available for previous epidemics and estimate heterogeneity in susceptibility for disease systems in which it has never been estimated previously. The premise of our approach is that highly susceptible individuals become infected more often than less susceptible individuals, and so individuals not infected after appearing in contact networks should be less susceptible than average. This change in susceptibility can be detected and quantified when individuals show up in a second contact network after not being infected in the first. To develop our method, we simulated contact tracing data from artificial populations with known levels of heterogeneity in susceptibility according to underlying discrete or continuous distributions of susceptibilities. We analyzed these data to determine the parameter space under which we are able to detect heterogeneity and the accuracy with which we are able to estimate it. We found that our power to detect heterogeneity increases with larger sample sizes, greater heterogeneity, and intermediate fractions of contacts becoming infected in the discrete case or greater fractions of contacts becoming infected in the continuous case. We also found that we are able to reliably estimate heterogeneity and disease dynamics. Ultimately, this means that contact tracing data alone are sufficient to detect and quantify heterogeneity in susceptibility. 

Arachidonic acid (AA) metabolites have been associated with several diseases across various organ systems, including the cardiovascular, pulmonary, and renal systems. Lipid mediators generated from AA oxidation have been studied to control macrophages, T-cells, cytokines, and fibroblasts, and regulate inflammatory mediators that induce vascular remodeling and dysfunction. AA is metabolized by cyclooxygenase (COX), lipoxygenase (LOX), and cytochrome P450 (CYP) to generate anti-inflammatory, pro-inflammatory, and pro-resolutory oxidized lipids. As comorbid states such as diabetes, hypertension, and obesity become more prevalent in cardiovascular disease, studying the expression of AA pathway genes and their association with these diseases can provide unique pathophysiological insights. In addition, the AA pathway of oxidized lipids exhibits diverse functions across different organ systems, where a lipid can be both anti-inflammatory and pro-inflammatory depending on the location of metabolic activity. Therefore, we aimed to characterize the gene expression of these lipid enzymes and receptors throughout multi-organ diseases via a transcriptomic meta-analysis using the Gene Expression Omnibus (GEO) Database. In our study, we found that distinct AA pathways were expressed in various comorbid conditions, especially those with prominent inflammatory risk factors. Comorbidities, such as hypertension, diabetes, and obesity appeared to contribute to elevated expression of pro-inflammatory lipid mediator genes. Our results demonstrate that expression of inflammatory AA pathway genes may potentiate and attenuate disease; therefore, we suggest further exploration of these pathways as therapeutic targets to improve outcomes. 

A common assumption in the evolution of virulence theory literature is that pathogens transmit better when they exploit their host more heavily, but by doing so, they impose a greater risk of killing their host, thus truncating infectious periods and reducing their own opportunities for transmission. Here, I derive an equation for the magnitude of this cost in terms of the infection fatality rate, and in doing so, I show that there are many cases where mortality costs are too small to plausibly constrain increases in host exploitation by pathogens. I propose that pathogen evolution may often be constrained by detection costs, whereby hosts alter their behaviour when infection is detectable, and thus reduce pathogen opportunities for onward transmission. I then derive an inequality to illustrate when mortality costs or detection costs impose stronger constraints on pathogen evolution, and I use empirical data from the literature to demonstrate that detection costs are frequently large in both human and animal populations. Finally, I give examples of how evolutionary predictions can change depending on whether costs of host exploitation are borne out through mortality or detection. 

Harmful algal blooms are increasing globally and pose serious health concerns releasing cyanotoxins. Microcystin-LR (MC-LR), one of the most frequently produced cyanotoxins, has recently been detected in aerosols generated by the normal motions of affected bodies of water. MC-LR aerosol exposure has been linked to a pro-inflammatory influence on the airways of mice; however, little is understood about the underlying mechanism or the potential consequences. This study aimed to investigate the pro-inflammatory effects of aerosolized MC-LR on murine airways. C57BL/6 and BALB/c mice were exposed to MC-LR aerosols, as these strains are predisposed to type 1/type 17 and type 2 immune responses, respectively. Exposure to MC-LR induced granulocytic inflammation in C57BL/6 but not BALB/c mice, as observed by increased expression of cytokines MIP-1α, CXCL1, CCL2, and GM-CSF compared with their respective vehicle controls. Furthermore, the upregulation of interleukins IL-17A and IL-12 is consistent with Th1- and Th17-driven type 1/type 17 inflammation. Histological analysis confirmed inflammation in the C57BL/6 lungs, with elevated neutrophils and macrophages in the bronchoalveolar lavage fluid and increased pro-inflammatory and pro-resolving oxidized lipids. In contrast, BALB/c mice showed no significant airway inflammation. These results highlight the ability of aerosolized MC-LR to trigger harmful airway inflammation, requiring further research, particularly into populations with predispositions to type 1/type 17 inflammation. 

A lack of tractable experimental systems in which to test hypotheses about the ecological and evolutionary drivers of disease spillover and emergence has limited our understanding of these processes. Here we introduce a promising system: Caenorhabditis hosts and Orsay virus, a positive-sense single-stranded RNA virus that naturally infects C. elegans . We assayed species across the Caenorhabditis tree and found Orsay virus susceptibility in 21 of 84 wild strains belonging to 14 of 44 species. Confirming patterns documented in other systems, we detected effects of host phylogeny on susceptibility. We then tested whether susceptible strains were capable of transmitting Orsay virus by transplanting exposed hosts and determining whether they transmitted infection to conspecifics during serial passage. We found no evidence of transmission in 10 strains (virus undetectable after passaging in all replicates), evidence of low-level transmission in 5 strains (virus lost between passage 1 and 5 in at least one replicate) and evidence of sustained transmission in 6 strains (including all three experimental C. elegans strains) in at least one replicate. Transmission was strongly associated with viral amplification in exposed populations. Variation in Orsay virus susceptibility and transmission among Caenorhabditis strains suggests that the system could be powerful for studying spillover and emergence.