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Background: Gunshots affect those directly involved in an incident and those in the surrounding community. The community-level impact of nighttime gunshots, which may be particularly disruptive to the sleep of nearby community members, is unknown. Objective: Our aim is to estimate the number of people potentially affected by nighttime gunshots and the relationship between nighttime gunshots and median household income in the USA. Design: We collected publicly available data on the timing and location of gunshots in six U.S. cities (Baltimore, MD; Boston, MA; Washington, D.C.; New York, NY; Philadelphia, PA; and Portland, OR) from 2015 to 2021. We then analyzed the data by computing rate ratios (RRs) to compare the frequency of gunshots during nighttime hours (6:00 pm to 5:59 am) versus daytime hours (6:00 am to 5:59 pm). Additionally, we used geospatial mapping to create choropleth maps to visualize the variation in nighttime gunshot density across cities. We estimated, using city-wide population, person-nights potentially impacted by the sound of gunshots within areas of 0.2- (low) and 0.5-mile (high) radius. Finally, for five of six cities where data on median household income were available by census tract, we built nonlinear regression models to estimate the relationship between the number of nighttime gunshots and median household income. Key Results: We analyzed 72,236 gunshots. Gunshots were more common during the nighttime than daytime (overall RR = 2.5). Analyses demonstrated that the low estimates for the mean annual number of person-nights impacted by nighttime gunshots were 0.4 million in Baltimore and Portland, 1.3 million in Philadelphia, 1.6 million in Boston, 2.9 million in New York City, and 5.9 million in Washington. The number of nighttime gunshots was inversely related to median household income. Conclusions: Nighttime gunshots are prevalent, particularly in low-income neighborhoods, and may have under-recognized effects on the surrounding community. [ABSTRACT FROM AUTHOR]

The pork industry is an essential part of the global food system, providing a significant source of protein for people around the world. A major factor restraining productivity and compromising animal wellbeing in the pork industry is disease outbreaks in pigs throughout the production process: widespread outbreaks can lead to losses as high as 10% of the U.S. pig population in extreme years. In this study, we present a machine learning model to predict the emergence of infection in swine production systems throughout the production process on a daily basis, a potential precursor to outbreaks whose detection is vital for disease prevention and mitigation. We determine features that provide the most value in predicting infection, which include nearby farm density, historical test rates, piglet inventory, feed consumption during the gestation period, and wind speed and direction. We utilize these features to produce a generalizable machine learning model, evaluate the model's ability to predict outbreaks both seven and 30 days in advance, allowing for early warning of disease infection, and evaluate our model on two swine production systems and analyze the effects of data availability and data granularity in the context of our two swine systems with different volumes of data. Our results demonstrate good ability to predict infection in both systems with a balanced accuracy of 85.3 % on any disease in the first system and balanced accuracies (average prediction accuracy on positive and negative samples) of 58.5 % , 58.7 % , 72.8 % and 74.8 % on porcine reproductive and respiratory syndrome, porcine epidemic diarrhea virus, influenza A virus, and Mycoplasma hyopneumoniae in the second system, respectively, using the six most important predictors in all cases. These models provide daily infection probabilities that can be used by veterinarians and other stakeholders as a benchmark to more timely support preventive and control strategies on farms. [ABSTRACT FROM AUTHOR]

Hand vaccinating is time consuming and inefficient. Oral vaccines delivered by drenching are less likely to be used due to a lack of labor on farms. Current environmental enrichment (EE) technologies do not allow pigs to express certain natural behaviors such as rooting and getting a reward. We developed a sprayer so that domestic pigs can self-apply any liquid. By adding an attractant (pig maternal pheromone), the use of EE devices by individual pigs can be increased. In this study, we used a Salmonella oral vaccine to evaluate efficacy of three delivery methods: (1) Control, no vaccine, (2) hand drenching as labeled, and (3) self-administration by this EE rooting device. All pigs sprayed themselves within 80 min of exposure to the EE device. While control pigs had little or no Salmonella serum and oral fluid IgG or IgA, hand-drenched and self-vaccinated pigs built similar levels of both serum and oral fluid IgA and IgG. We conclude we were able to significantly reduce human labor needed and achieved 100% efficacy in eliciting a serologic response when pigs self-administered a Salmonella vaccine. This technology could benefit commercial pig production while providing an enriched behavioral environment. Self-vaccination could also assist in control or immunization of feral swine and improve domestic pig health and food safety. [ABSTRACT FROM AUTHOR]

Antimicrobial resistance (AMR) is one of the major challenges of the century and should be addressed with a One Health approach. This study aimed to develop a tool that can provide a better understanding of AMR patterns and improve management practices in swine production systems to reduce its spread between farms. We generated similarity networks based on the phenotypic AMR pattern for each farm with information on important bacterial pathogens for swine farming based on the Euclidean distance. We included seven pathogens: Actinobacillus suis, Bordetella bronchiseptica, Escherichia coli, Glaesserella parasuis, Pasteurella multocida, Salmonella spp., and Streptococcus suis; and up to seventeen antibiotics from ten classes. A threshold criterion was developed to reduce the density of the networks and generate communities based on their AMR profiles. A total of 479 farms were included in the study although not all bacteria information was available on each farm. We observed significant differences in the morphology, number of nodes and characteristics of pathogen networks, as well as in the number of communities and susceptibility profiles of the pathogens to different antimicrobial drugs. The methodology presented here could be a useful tool to improve health management, biosecurity measures and prioritize interventions to reduce AMR spread in swine farming. [ABSTRACT FROM AUTHOR]

Alzheimer's Disease (AD) and Related Dementias (ADRD) are a growing concern across the globe. Unfortunately, racial/ethnic minorities in the United States (U.S.), such as Chinese Americans, have lower ADRD knowledge, and these individuals are less likely to be targeted and engaged in recommended dementia prevention and care. The objective of this study is to examine knowledge, attitudes, and beliefs about healthy aging and ADRD among older Chinese Americans living in New York City. Chinese Americans with very low English proficiency were recruited from a senior center in New York City. Accordingly, surveys were translated and focus groups were conducted in Mandarin or Cantonese. Questionnaires assessed demographic and health characteristics. Focus groups followed an open-ended protocol which was guided by the published literature. Focus group discussions were audio recorded, transcribed, and translated to English for qualitative analysis. Analysis of qualitative data proceeded according to the constant comparative method. A total of 18 participants were recruited. Average age of participants was 76.4 years and participants were 72.2% female. The majority were married (72.2%). Participants reported chronic conditions, including diabetes (38.9%) and dyslipidemia (22.2%). Participants commonly reported that their health limited their ability to accomplish things (66.7%) and achieve things (66.7%). While 16.7% of participants reported no bodily pain, slight pain was reported by 44.4%, moderate pain by 33.3%, and extreme pain by 5.6%. Qualitative analysis revealed several prominent themes, including: (1) perceptions about normal aging; (2) fears about loneliness and cognitive decline; (3) understanding of healthy aging; (4) cultural influences on aging; and (5) perceptions of ADRD. Results from this study highlight a set of cultural beliefs about healthy aging as well as knowledge, attitudes, and beliefs pertaining to ADRD. These results may inform opportunities for increasing healthy aging practices and knowledge about dementia among underserved older Chinese Americans. [ABSTRACT FROM AUTHOR]

Conversation about health messages and campaigns is common, and message-related conversations are increasingly recognized as a consequential factor in shaping message effects. The evidence base is limited, however, about the conditions under which conversation may help or hinder health communication efforts. In this study, college students (N = 301) first watched a short sleep video and were randomly assigned to either talk with a partner in an online chat conversation or proceed directly to a short survey. Unknown to participants, the chat partner was a confederate coached to say positive things about sleep and the message ('positive' chat condition), negative things ('negative' chat condition), or unrelated things ('natural' chat condition). All respondents completed a short survey on beliefs about sleep, reactions to the message, and intentions to get adequate sleep. Respondents had greater intentions to engage in healthy sleep when they engaged in positive conversation following message exposure than when they engaged in negative conversation after the message (p < 0.001). Positive emotion experienced in response to the message and positive chat perceptions were significant predictors (p < 0.05) of intentions to achieve healthy sleep. Health message designers may benefit from understanding how messages are exchanged in peer-to-peer conversation to better predict and explain their effects. [ABSTRACT FROM AUTHOR]

Describes an analytical flat-plate photobioreactor with a spectrally attenuated light source for the incubation of phytoplankton under dynamic light regimes. Method used to determine the level of liquid; Basis of culturing apparatus of the analytical photobioreactor; Importance of the design to use in photophysiological and bio-physical studies of microalgae.

Purpose of Review: In this current review, we describe the benefits of community-based and "precision and personalized population health" (P3H) approaches to assessing and addressing sleep health problems and sleep-related cardiovascular diseases (CVD) among vulnerable populations such as racial/ethnic minorities, the elderly, and the socioeconomically disadvantaged. Recent Findings: Very few sleep health programs utilize a community-based or P3H approach, which may account for low estimates of sleep health problems, related CVD outcomes, and inadequate healthcare infrastructure to address sleep-related health outcomes at the community and population level. We describe community-based and P3H approaches and programs as solutions to accurately capture estimates of sleep health and reduce burden of sleep health problems and corollary CVD outcomes at the level of the community and population. Specifically, we describe seven critical steps needed to successfully implement a community-based and P3H approach to address sleep health problems. Summary: Community-based and P3H approaches are effective strategies to assessing and addressing sleep health problems and related health conditions. [ABSTRACT FROM AUTHOR]