Search

Abstract Objective Improving care transitions for older adults can reduce emergency department (ED) visits, adverse events, and empower community autonomy. We conducted an inductive qualitative content analysis to identify themes emerging from comments to better understand ED care transitions. Methods The LEARNING WISDOM prospective longitudinal observational cohort includes older adults (≥ 65 years) who experienced a care transition after an ED visit from both before and during COVID-19. Their comments on this transition were collected via phone interview and transcribed. We conducted an inductive qualitative content analysis with randomly selected comments until saturation. Themes that arose from comments were coded and organized into frequencies and proportions. We followed the Standards for Reporting Qualitative Research (SRQR). Results Comments from 690 patients (339 pre-COVID, 351 during COVID) composed of 351 women (50.9%) and 339 men (49.1%) were analyzed. Patients were satisfied with acute emergency care, and the proportion of patients with positive acute care experiences increased with the COVID-19 pandemic. Negative patient comments were most often related to communication between health providers across the care continuum and the professionalism of personnel in the ED. Comments concerning home care became more neutral with the COVID-19 pandemic. Conclusion Patients were satisfied overall with acute care but reported gaps in professionalism and follow-up communication between providers. Comments may have changed in tone from positive to neutral regarding home care over the COVID-19 pandemic due to service slowdowns. Addressing these concerns may improve the quality of care transitions and provide future pandemic mitigation strategies.

Reaching a surface temperature of 50 °C in a heavily populated region, like Paris, would have devastating effects. Although such a high value seems far from the present-day record of 42.6 °C, its occurrence cannot be dismissed by the end of the 21st century, due to the continuous increase of global mean temperature. In this paper, we address two questions that were asked by the City of Paris to a group of scientists: When does this event start to be likely? What are the prevailing meteorological conditions? We base our study on the CMIP6 simulation ensemble. Many of the CMIP6 yield biases in temperature. Rather than using methods of bias correction, which are not necessarily adapted to high extremes, we propose a pragmatic approach of model selection in order to seek such high temperature events that are deemed realistic. We analyze the meteorological conditions leading to first occurrences of such hot events and their common atmospheric patterns. This paper describes a simple data mining approach (on a large ensemble of climate model simulations) which could be adapted to other regions of the world, in order to help decision makers anticipating and adapting to such devastating meteorological events.

Summary: The mechanical environment generated through the adhesive interaction of endothelial cells (ECs) with the matrix controls nuclear tension, preventing aberrant gene synthesis and the transition from restrictive to leaky endothelium, a hallmark of acute lung injury (ALI). However, the mechanisms controlling tension transmission to the nucleus and EC-restrictive fate remain elusive. Here, we demonstrate that, in a kinase-independent manner, focal adhesion kinase (FAK) safeguards tension transmission to the nucleus to maintain EC-restrictive fate. In FAK-depleted ECs, robust activation of the RhoA-Rho-kinase pathway increased EC tension and phosphorylation of the nuclear envelope protein, emerin, activating DNMT3a. Activated DNMT3a methylates the KLF2 promoter, impairing the synthesis of KLF2 and its target S1PR1 to induce the leaky EC transcriptome. Repleting FAK (wild type or kinase dead) or inhibiting RhoA-emerin-DNMT3a activities in damaged lung ECs restored KLF2 transcription of the restrictive EC transcriptome. Thus, FAK sensing and control of tension transmission to the nucleus govern restrictive endothelium to maintain lung homeostasis.

Abstract Mid‐tropospheric deep depressions in summer over the North Atlantic are shown to have strongly increased in the eastern and strongly decreased in the western North Atlantic region. This evolution is linked to a change in baroclinicity in the west of the North Atlantic ocean and over the North American coast, likely due to the increased surface temperature there. Deep depressions in the Eastern North Atlantic are linked to a temperature pattern typical of extreme heat events in the region. The same analysis is applied to a sample of CMIP6 model outputs, and no such trends are found. This study suggests a link between the observed increase of summer extreme heat events in the region and the increase of the number of Atlantic depressions. The failure of CMIP6 models to reproduce these events can consequently also reside in an incorrect reproduction of this specific feature of midlatitude atmospheric dynamics.

During the summer of 2021, the North American Pacific Northwest was affected by an extreme heatwave that broke previous temperature records by several degrees. The event caused severe impacts on human life and ecosystems, and was associated with the superposition of concurrent drivers, whose effects were amplified by climate change. We evaluate whether this record-breaking heatwave could have been foreseen prior to its observation, and how climate change affects North American Pacific Northwest worst-case heatwave scenarios. To this purpose, we use a stochastic weather generator with empirical importance sampling. The generator simulates extreme temperature sequences using circulation analogues, chosen with an importance sampling based on the daily maximum temperature over the region that recorded the most extreme impacts. We show how some of the large-scale drivers of the event can be obtained form the circulation analogues, even if such information is not directly given to the stochastic weather generator.

We present a data-driven emulator, a stochastic weather generator (SWG), suitable for estimating probabilities of prolonged heat waves in France and Scandinavia. This emulator is based on the method of analogs of circulation to which we add temperature and soil moisture as predictor fields. We train the emulator on an intermediate complexity climate model run and show that it is capable of predicting conditional probabilities (forecasting) of heat waves out of sample. Special attention is payed that this prediction is evaluated using a proper score appropriate for rare events. To accelerate the computation of analogs, dimensionality reduction techniques are applied and the performance is evaluated. The probabilistic prediction achieved with SWG is compared with the one achieved with a convolutional neural network (CNN). With the availability of hundreds of years of training data, CNNs perform better at the task of probabilistic prediction. In addition, we show that the SWG emulator trained on 80 years of data is capable of estimating extreme return times of order of thousands of years for heat waves longer than several days more precisely than the fit based on generalized extreme value distribution. Finally, the quality of its synthetic extreme teleconnection patterns obtained with SWG is studied. We showcase two examples of such synthetic teleconnection patterns for heat waves in France and Scandinavia that compare favorably to the very long climate model control run.

This study presents a systematic literature review (SLR) of the Advanced Work Packaging (AWP) methodology, focusing on identifying barriers to its adoption. The review encompasses an analysis of 287 documents from 2013 to 2023, including conference articles, doctoral theses, journal articles, master theses, reports, and organizational documents. Following a rigorous selection process, 59 of these documents were identified as pertinent to the investigation. This research employs a dual approach. First, a scientometric analysis to map the collaborative networks of authors and the co-occurrence of keywords, providing a comprehensive picture of the research landscape in AWP. Second, the study delves into the main barriers hindering the adoption of AWP, as revealed through the SLR of the selected documents. The findings offer an overlay network visualization of coauthorship and a network visualization of keyword co-occurrence. The study culminates in a detailed identification of primary AWP barriers, suggestions for future research directions, and potential lines of inquiry within the field. This work contributes to the existing body of knowledge by offering a novel perspective on the challenges associated with AWP implementation and provides a foundation for future scholarly endeavors in this domain.

The European Green Deal aims to reduce the pesticide use, notably by developing biocontrol products to protect crops from diseases. Indeed, the use of significant amounts of chemicals negatively impact the environment such as soil microbial biodiversity or groundwater quality, and human health. Grapevine ( Vitis vinifera ) was selected as one of the first targeted crop due to its economic importance and its dependence on fungicides to control the main damaging diseases worldwide: grey mold, downy and powdery mildews. Chitosan, a biopolymer extracted from crustacean exoskeletons, has been used as a biocontrol agent in many plant species, including grapevine, against a variety of cryptogamic diseases such as downy mildew ( Plasmopara viticola ), powdery mildew ( Erysiphe necator ) and grey mold ( Botrytis cinerea ). However, the precise molecular mechanisms underlying its mode of action remain unclear: is it a direct biopesticide effect or an indirect elicitation activity, or both? In this study, we investigated six chitosans with diverse degrees of polymerization (DP) ranging from low to high DP (12, 25, 33, 44, 100, and 470). We scrutinized their biological activities by evaluating both their antifungal properties and their abilities to induce grapevine immune responses. To investigate their elicitor activity, we analyzed their ability to induce MAPKs phosphorylation, the activation of defense genes and metabolite changes in grapevine. Our results indicate that the chitosans with a low DP are more effective in inducing grapevine defenses and possess the strongest biopesticide effect against B. cinerea and P. viticola . We identified chitosan with DP12 as the most efficient resistance inducer. Then, chitosan DP12 has been tested against downy and powdery mildews in the vineyard trials performed during the last three years. Results obtained indicated that a chitosan-based biocontrol product could be sufficiently efficient when the amount of pathogen inoculum is quite low and could be combined with only two fungicide treatments during whole season programs to obtain a good protection efficiency. On the whole, a chitosan-based biocontrol product could become an interesting alternative to meet the chemicals reduction targeted in sustainable viticulture., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Brulé, Héloir, Roudaire, Villette, Bonnet, Pascal, Darblade, Crozier, Hugueney, Coma and Poinssot.)