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AIM: We investigated the effects of disease on the local abundances and distributions of species at continental scales by examining the impacts of white‐nose syndrome, an infectious disease of hibernating bats, which has recently emerged in North America. LOCATION: North America and Europe. METHODS: We used four decades of population counts from 1108 populations to compare the local abundances of bats in North America before and after the emergence of white‐nose syndrome to the situation in Europe, where the disease is endemic. We also examined the probability of local extinction for six species of hibernating bats in eastern North America and assessed the influence of winter colony size prior to the emergence of white‐nose syndrome on the risk of local extinction. RESULTS: White‐nose syndrome has caused a 10‐fold decrease in the abundance of bats at hibernacula in North America, eliminating large differences in species abundance patterns that existed between Europe and North America prior to disease emergence. White‐nose syndrome has also caused extensive local extinctions (up to 69% of sites in a single species). For five out of six species, the risk of local extinction was lower in larger winter populations, as expected from theory, but for the most affected species, the northern long‐eared bat (Myotis septentrionalis), extinction risk was constant across winter colony sizes, demonstrating that disease can sometimes eliminate numerical rarity as the dominant driver of extinction risk by driving both small and large populations extinct. MAIN CONCLUSIONS: Species interactions, including disease, play an underappreciated role in macroecological patterns and influence broad patterns of species abundance, occurrence and extinction.

This episode began on Jan. 30, when my wife and I decided to venture downtown to do some Saturday shopping. Well, we had a nice time shopping, but when we returned to the car, much to our dismay, a parking ticket had found its way underneath our windshield wiper.

Exposure to intrauterine inflammation (IUI) is associated with short- and long-term adverse perinatal outcomes. However, little data exist on utilizing placenta to prognosticate fetal injury in this scenario. Our study aimed to utilize imaging modalities to evaluate mechanisms contributing to placental injury following IUI exposure and correlated it to concomitant fetal brain injury. CD1 pregnant dams underwent laparotomies and received intrauterine injections of either lipopolysaccharide (LPS; a model of IUI) or phosphate-buffered saline (PBS). In utero ultrasound Doppler velocimetry of uterine and umbilical arteries and magnetic resonance imaging (MRI) of placental volumes with confirmatory immunohistochemical (vimentin) and histochemistry (fibrin) analyses were performed. ELISA for thrombosis markers, fibrinogen and fibrin was performed to analyze thrombi in placenta. Fetal brain immunohistochemistry was performed to detect microglial activation (ionized calcium-binding adaptor molecule 1, Iba1). On ultrasound, LPS group demonstrated elevated resistance indices, pulsatility indices and a greater occurrence of absent end-diastolic flow in the umbilical and uterine arteries. In the fetus, there was an increased cardiac Tei indices in the LPS group. MRI revealed decreased volume of placenta in the LPS group associated with placental thinning and placental endothelial damage on immunohistochemistry. Decreased fibrinogen content and more thrombi staining in placenta exposed to maternal LPS indicated the hypercoagulability. Furthermore, the expression of Iba1was significantly associated with placental thickness (r = -0.7890, Pearson correlation coefficient). Our data indicate that IUI can trigger events leading to maternal placental malperfusion and fetal vessel resistance, as well as predispose the developing fetus to cardiac dysfunction and brain damage. Furthermore, our data suggest that prenatal ultrasound can be a real-time clinical tool for assessing fetal risk for adverse neurologic outcomes following the potential IUI exposure.

Pemphigus vulgaris (PV) is a life-threatening autoimmune mucocutaneous blistering disease which is to a large extent genetically determined, and results, at least in part, from the deleterious activity of autoantibodies directed against desmoglein (DSG)3, a prominent intra-epidermal adhesion molecule. Those autoantibodies lead to decreased membranal DSG3 expression in keratinocytes (KCs), thereby destabilizing cell–cell adhesion within the epidermis and leading to blister formation. We previously showed that rs17315309, a strong risk variant for PV within the promoter of the ST18 transcription factor gene, promotes epidermal ST18 up-regulation in a p53/p63-dependent manner. Accordingly, ST18 was found to be overexpressed in the skin of PV patients. Increased ST18 expression was then shown to markedly augment PV autoantibodies-mediated loss of KCs cohesion. Here, we demonstrate that ST18 overexpression significantly increases autoantibody-mediated DSG3 down-regulation in keratinocytes. In addition, DSG3 decreased expression boosts p53 function through p38 mitogen-activated protein kinase (p38MAPK) activation and dramatically augments p53-dependent ST18 promoter activity. Finally, the PV risk variant rs17315309 is associated with increased p53 expression in PV skin. Taken collectively, these observations reveal a novel self-amplifying pathomechanism involving ST18, DSG3, p38 and p53, capable of perpetuating disease activity, and therefore indicative of novel actionable molecular targets in PV.

In line with the recent industrial trends of hyperconnectivity, 5G technology deployment, the Internet of Things (IoT) and Industry 4.0, the ultimate goal of corrosion prevention is the invention of smart coatings that are able to assess their own condition, predict the onset of corrosion and alert users just before it happens. It is of particular interest to tackle corrosion that occurs in non-accessible areas where human inspectors or handheld devices are useless. To accomplish this, a variety of technologies that are embedded or could potentially be embedded into the coatings are being developed to monitor coating condition, which are based, for instance, on the evolution of electrochemical or mechanical properties over time. For these technologies to be fully embedded into the coatings and work remotely, solutions are needed for connectivity and power supply. A paradigm shift from routine prescheduled maintenance to condition-based preventive maintenance could then become a reality. In this work, the technologies that enable the in-service monitoring of organic anticorrosion coatings were compiled. Soon, some of them could be integrated into the sensing elements of autonomous, connected neural-like networks that are capable of remotely assessing the condition of the anticorrosion protection of future infrastructures.

Assessing sensitivity to unmeasured confounding is an important step in observational studies, which typically estimate effects under the assumption that all confounders are measured. In this paper, we develop a sensitivity analysis framework for balancing weights estimators, an increasingly popular approach that solves an optimization problem to obtain weights that directly minimizes covariate imbalance. In particular, we adapt a sensitivity analysis framework using the percentile bootstrap for a broad class of balancing weights estimators. We prove that the percentile bootstrap procedure can, with only minor modifications, yield valid confidence intervals for causal effects under restrictions on the level of unmeasured confounding. We also propose an amplification to allow for interpretable sensitivity parameters in the balancing weights framework. We illustrate our method through extensive real data examples.