Understanding park visitors’ soundscape perception using subjective and objective measurement

Environmental noise knows no boundaries, affecting even protected areas. Noise pollution, originating from both external and internal sources, imposes costs on these areas. It is associated with adverse health effects, while natural sounds contribute to cognitive and emotional improvements as ecosystem services. When it comes to parks, individual visitors hold unique perceptions of soundscapes, which can be shaped by various factors such as their motivations for visiting, personal norms, attitudes towards specific sounds, and expectations. In this study, we utilized linear models and geospatial data to evaluate how visitors’ personal norms and attitudes, the park’s acoustic environment, visitor counts, and the acoustic environment of visitors’ neighborhoods influenced their perception of soundscapes at Muir Woods National Monument. Our findings indicate that visitors’ subjective experiences had a greater impact on their perception of the park’s soundscape compared to purely acoustic factors like sound level of the park itself. Specifically, we found that motivations to hear natural sounds, interference caused by noise, sensitivity to noise, and the sound levels of visitors’ home neighborhoods influenced visitors’ perception of the park’s soundscape. Understanding how personal factors shape visitors’ soundscape perception can assist urban and non-urban park planners in effectively managing visitor experiences and expectations

Climatic warming destabilizes forest ant communities

How will ecological communities change in response to climate warming? Direct effects of temperature and indirect cascading effects of species interactions are already altering the structure of local communities, but the dynamics of community change are still poorly understood. We explore the cumulative effects of warming on the dynamics and turnover of forest ant communities that were warmed as part of a 5-year climate manipulation experiment at two sites in eastern North America. At the community level, warming consistently increased occupancy of nests and decreased extinction and nest abandonment. This consistency was largely driven by strong responses of a subset of thermophilic species at each site. As colonies of thermophilic species persisted in nests for longer periods of time under warmer temperatures, turnover was diminished, and species interactions were likely altered. We found that dynamical (Lyapunov) community stability decreased with warming both within and between sites. These results refute null expectations of simple temperature-driven increases in the activity and movement of thermophilic ectotherms. The reduction in stability under warming contrasts with the findings of previous studies that suggest resilience of species interactions to experimental and natural warming. In the face of warmer, no-analog climates, communities of the future May become increasingly fragile and unstable

Loss of CD103+ DCs and Mucosal IL-17+ and IL-22+ Lymphocytes is Associated with Mucosal Damage in SIV Infection

HIV/SIV disease progression is associated with multifocal damage to the GI tract epithelial barrier that correlates with microbial translocation and persistent pathological immune activation but the underlying mechanisms remain unclear. Investigating alterations in mucosal immunity during SIV infection, we found that damage to the colonic epithelial barrier was associated with loss of multiple lineages of IL-17-producing lymphocytes, cells that microarray analysis showed express genes important for enterocyte homeostasis, including IL-22. IL-22-producing lymphocytes were also lost after SIV infection. Potentially explaining coordinate loss of these distinct populations, we also observed loss of CD103+ DCs after SIV infection which associated with loss of IL-17 and IL-22-producing lymphocytes. CD103+ DCs expressed genes associated with promotion of IL-17/IL-22+ cells, and co-culture of CD103+ DCs and naïve T-cells led to increased IL17A and RORc expression in differentiating T-cells. These results reveal complex interactions between mucosal immune cell subsets providing potential mechanistic insights into mechanisms of mucosal immune dysregulation during HIV/SIV infection, and offer hints for development of novel therapeutic strategies to address this aspect of AIDS virus pathogenesis

Notch regulates BMP responsiveness and lateral branching in vessel networks via SMAD6

Functional blood vessel growth depends on generation of distinct but coordinated responses from endothelial cells. Bone morphogenetic proteins (BMP), part of the TGFβ superfamily, bind receptors to induce phosphorylation and nuclear translocation of SMAD transcription factors (R-SMAD1/5/8) and regulate vessel growth. However, SMAD1/5/8 signalling results in both pro- and anti-angiogenic outputs, highlighting a poor understanding of the complexities of BMP signalling in the vasculature. Here we show that BMP6 and BMP2 ligands are pro-angiogenic in vitro and in vivo, and that lateral vessel branching requires threshold levels of R-SMAD phosphorylation. Endothelial cell responsiveness to these pro-angiogenic BMP ligands is regulated by Notch status and Notch sets responsiveness by regulating a cell-intrinsic BMP inhibitor, SMAD6, which affects BMP responses upstream of target gene expression. Thus, we reveal a paradigm for Notch-dependent regulation of angiogenesis: Notch regulates SMAD6 expression to affect BMP responsiveness of endothelial cells and new vessel branch formation

A presynaptic endosomal trafficking pathway controls synaptic growth signaling

Association of Nwk with SNX16 promotes down-regulation of synaptic growth signaling at the interface between early and recycling endosomes

Expanding the diversity of mycobacteriophages: insights into genome architecture and evolution.

Mycobacteriophages are viruses that infect mycobacterial hosts such as Mycobacterium smegmatis and Mycobacterium tuberculosis. All mycobacteriophages characterized to date are dsDNA tailed phages, and have either siphoviral or myoviral morphotypes. However, their genetic diversity is considerable, and although sixty-two genomes have been sequenced and comparatively analyzed, these likely represent only a small portion of the diversity of the mycobacteriophage population at large. Here we report the isolation, sequencing and comparative genomic analysis of 18 new mycobacteriophages isolated from geographically distinct locations within the United States. Although no clear correlation between location and genome type can be discerned, these genomes expand our knowledge of mycobacteriophage diversity and enhance our understanding of the roles of mobile elements in viral evolution. Expansion of the number of mycobacteriophages grouped within Cluster A provides insights into the basis of immune specificity in these temperate phages, and we also describe a novel example of apparent immunity theft. The isolation and genomic analysis of bacteriophages by freshman college students provides an example of an authentic research experience for novice scientists

Nature meets nurture: molecular genetics of gastric cancer

The immensity of genes and molecules implicated in gastric carcinogenesis is overwhelming and the relevant importance of some of these molecules is too often unclear. This review serves to bring us up-to-date with the latest findings as well as to look at the larger picture in terms of how to tackle the problem of solving this multi-piece puzzle. In this review, the environmental nurturing of intestinal cancer is discussed, beginning with epidemiology (known causative factors for inducing molecular change), an update of H. pylori research, including the role of inflammation and stem cells in premalignant lesions. The role of E-cadherin in the nature (genotype) of diffuse gastric cancer is highlighted, and finally the ever growing discipline of SNP analysis (including IL1B) is discussed

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages