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BACKGROUND: Exposure to fine particulate matter (PM2.5) increases the risk of asthma exacerbations, and thus, monitoring personal exposure to PM2.5 may aid in disease self-management. Low-cost, portable air pollution sensors offer a convenient way to measure personal pollution exposure directly and may improve personalized monitoring compared with traditional methods that rely on stationary monitoring stations. We aimed to understand whether adults with asthma would be willing to use personal sensors to monitor their exposure to air pollution and to assess the feasibility of using sensors to measure real-time PM2.5 exposure. METHODS: We conducted semi-structured interviews with 15 adults with asthma to understand their willingness to use a personal pollution sensor and their privacy preferences with regard to sensor data. Student research assistants used HabitatMap AirBeam devices to take PM2.5 measurements at 1-s intervals while walking in Philadelphia neighborhoods in May-August 2018. AirBeam PM2.5 measurements were compared to concurrent measurements taken by three nearby regulatory monitors. RESULTS: All interview participants stated that they would use a personal air pollution sensor, though the consensus was that devices should be small (watch- or palm-sized) and light. Patients were generally unconcerned about privacy or sharing their GPS location, with only two stating they would not share their GPS location under any circumstances. PM2.5 measurements were taken using AirBeam sensors on 34 walks that extended through five Philadelphia neighborhoods. The range of sensor PM2.5 measurements was 0.6-97.6 µg/mL (mean 6.8 µg/mL), compared to 0-22.6 µg/mL (mean 9.0 µg/mL) measured by nearby regulatory monitors. Compared to stationary measurements, which were only available as 1-h integrated averages at discrete monitoring sites, sensor measurements permitted characterization of fine-scale fluctuations in PM2.5 levels over time and space. CONCLUSIONS: Patients were generally interested in using sensors to monitor their personal exposure to PM2.5 and willing to share personal sensor data with health care providers and researchers. Compared to traditional methods of personal exposure assessment, sensors captured personalized air quality information at higher spatiotemporal resolution. Improvements to currently available sensors, including more reliable Bluetooth connectivity, increased portability, and longer battery life would facilitate their use in a general patient population.

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This exercise satisfies the Liaison Committee on Medical Education Standard 7.3 for medical student training in the scientific method. The students are challenged, individually and in small groups, to state and test hypotheses based on real patient data concerning risk factors for the development of hepatocellular carcinoma.

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A wide range of datasets containing geographically distributed measures of the environment and social factors is currently available, and as low-cost sensors and other devices become increasingly used, the volume of these data will continue to grow. Because such factors influence many health outcomes, researchers with varied interests often repeat tasks related to gathering and preparing these data for studies. We created Sensor-based Analysis of Pollution in the Philadelphia Region with Information on Neighborhoods and the Environment (SAPPHIRINE), offered as a web application and R package, to integrate pollution, crime, social disadvantage, and traffic data relevant to investigators, citizen scientists, and policy makers in the Greater Philadelphia Area. SAPPHIRINE's capabilities include providing interactive maps and customizable data retrieval to aid in the visual identification of pollution and other factor hotspots, as well as hypothesis generation regarding relationships among these factors and health outcomes.

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Efforts to enhance Electronic Health Record (EHR) data for the study of conditions in which social and economic variables play a prominent role include linking clinical data to sources of external information via patient-specific geocodes. This approach is convenient, but whether geographic-area-level information from secondary sources is adequate as a surrogate of individual-level information is not fully understood. We used Behavioral Risk Factor Surveillance System (BRFSS) epidemiologic data to compare associations of individual income, median aggregate income, and Area Deprivation Index (ADI)-a validated score of U.S. socioeconomic deprivation-with various health outcomes. Median income and ADI assigned according to respondent area of residence were significantly associated with various health outcomes, but with substantially lower effect sizes than those of individual income. Our results show the limited ability of median income and ADI at the level of metropolitan/micropolitan statistical areas versus individual income for use as measures of socioeconomic status.

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Exposure to pollutants impacts health and has been associated with a range of diseases, including respiratory and heart diseases, as well as all-cause mortality. Because taking exposure measures for individual studies is costly and impractical, most rely on data from sources such as the Environmental Protection Agency (EPA), which provides a wealth of publicly available pollution measures taken at over two thousand monitoring sites across the United States. While EPA data is readily available, estimating pollution exposure at a given latitude-longitude location remains computationally intensive. We developed Pollution-Associated Risk Geospatial Analysis SITE (PARGASITE), an online web-application and R package, that can be used to estimate levels of pollutants in the U.S. for 2005 through 2017 at user-defined geographic locations and time ranges. We demonstrate how PARGASITE can facilitate the study of associations between exposures and health outcomes using as an example an analysis of asthma risk factors among adults.

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BACKGROUND: Asthma is a chronic inflammatory lung disease that affects 18.7 million U.S. adults. Electronic health records (EHRs) are a unique source of information that can be leveraged to understand factors associated with asthma in real-life populations. In this study, we identify demographic factors and comorbidities associated with asthma exacerbations among adults according to EHR-derived data and compare these findings to those of epidemiological studies. METHODS: We obtained University of Pennsylvania Hospital System EHR-derived data for asthma encounters occurring between 2011 and 2014. Regression analyses were performed to model asthma exacerbation frequency as explained by age, sex, race/ethnicity, health insurance type, smoking status, body mass index (BMI) and various comorbidities. We analyzed data from the National Health and Nutrition Examination Survey (NHANES) from 2001 to 2012 to compare findings with those from the EHR-derived data. RESULTS: Based on data from 9068 adult patients with asthma, 33.37% had at least one exacerbation over the four-year study period. In a proportional odds logistic regression predicting number of exacerbations during the study period (levels: 0, 1-2, 3-4, 5+ exacerbations), after controlling for age, race/ethnicity, sex, health insurance type, and smoking status, the highest odds ratios (ORs) of significantly associated factors were: chronic bronchitis (2.70), sinusitis (1.50), emphysema (1.39), fluid and electrolyte disorders (1.35), class 3 obesity (1.32), and diabetes (1.28). An analysis of NHANES data showed associations for class 3 obesity, anemia and chronic bronchitis with exacerbation frequency in an adjusted model controlling for age, race/ethnicity, sex, financial class and smoking status. CONCLUSIONS: EHR-derived data is helpful to understand exacerbations in real-life asthma patients, facilitating design of detailed studies and interventions tailored for specific populations.

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Electronic Health Record (EHR)-derived data is a valuable resource for research, and efforts are underway to overcome some of its limitations by using data from external sources to gain a fuller picture of patient characteristics, symptoms, and exposures. Our goal was to assess the utility of augmenting EHR data with geocoded patient addresses to identify geospatial variation of disease that is not explained by EHR-derived demographic factors. Using 2011-2014 encounter data from 27,604 University of Pennsylvania Hospital System asthma patients, we identified factors associated with asthma exacerbations: risk was higher in female, black, middle aged to elderly, and obese patients, as well as those with positive smoking history and with Medicare or Medicaid vs. private insurance. Significant geospatial variability of asthma exacerbations was found using generalized additive models, even after adjusting for demographic factors. Our work shows that geospatial data can be used to cost-effectively enhance EHR data.

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BACKGROUND: Asthma, a chronic respiratory disease affecting over 18.7 million American adults, has marked disparities by gender, race/ethnicity and socioeconomic status. Our goal was to identify gender-specific demographic and socioeconomic determinants of asthma prevalence among U.S. adults using data from the Behavioral Risk Factors Surveillance System (BRFSS) and the National Health and Nutrition Examination Survey (NHANES). METHODS: Gender-specific regression analyses were performed to model the relationship between asthma prevalence with age, race/ethnicity, income, education level, smoking status, and body mass index (BMI), while taking into account the study designs. RESULTS: Based on BRFSS data from 1,003,894 respondents, weighted asthma prevalence was 6.2% in males and 10.6% in females. Asthma prevalence among grade 2 obese and grade 3 obese vs. not overweight or obese women was 2.5 and 3.5 times higher, respectively, while that in men was 1.7 and 2.4 times higher; asthma prevalence among current vs. never smoker women was 1.4 times higher, while that in men was 1.1 times higher. Similar results were obtained with NHANES data from 13,364 respondents: asthma prevalence among grade 2 obese and grade 3 obese vs. not overweight or obese respondents was 2.0 and 3.3 times higher for women, though there was no significant difference for men; asthma prevalence among current vs. never smokers was 1.8 times higher for women and not significantly different in men. Asthma prevalence by race/ethnicity and income levels did not differ considerably between men and women. CONCLUSIONS: Our results underscore the importance of obesity and smoking as modifiable asthma risk factors that most strongly affect women.

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Varicella-zoster virus (VZV) grows efficiently in quiescent cells in vivo and in culture, and virus infection activates cell cycle and signaling pathways without cell division. VZV ORFs have been identified that determine the tissue tropism for nondividing skin, T cells, and neurons in SCID-Hu mouse models. The normal cell cycle status of human foreskin fibroblasts was characterized and was dysregulated upon infection by VZV. The expression of cyclins A, B1, and D3 was highly elevated but did not correspond with extensive cellular DNA synthesis. Cell cycle arrest may be due to activation of the DNA damage response during VZV DNA replication. Other host regulatory proteins were induced in infected cells, including p27, p53, and ATM kinase. A possible explanation for the increase in cell cycle regulatory proteins is activation of transcription factors during VZV infection. There is evidence that VZV infection activates transcription factors through the mitogen-activated protein kinase pathways extracellular-regulated kinase (ERK) and c-Jun N-terminal (transpose these parts of the compound noun) kinase (JNK), which could selectively increase cyclin levels. Some of these perturbed cell functions are essential for VZV replication, such as cyclin-dependent kinase (CDK) activity, and reveal targets for interventions.

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Varicella-zoster virus (VZV) replicates in quiescent T cells, neurons, and skin cells. In cultured fibroblasts (HFFs), VZV induces host cyclin expression and cyclin-dependent kinase (CDK) activity without causing cell cycle progression. CDK1/cyclin B1 phosphorylates the major viral transactivator, and the CDK inhibitor roscovitine prevents VZV mRNA transcription. We investigated the antiviral effects of additional compounds that target CDKs or other cell cycle enzymes in culture, ex vivo, and in vivo. Cytotoxicity and cell growth arrest doses were determined by Neutral Red assay. Antiviral effects were evaluated in HFFs by plaque assay, genome copy number, and bioluminescence. Positive controls were acyclovir (400 microM) and phosphonoacetic acid (PAA, 1 mM). Test compounds were roscovitine, aloisine A, and purvalanol A (CDK inhibitors), aphidicolin (inhibits human and herpesvirus DNA polymerase), l-mimosine (indirectly inhibits human DNA polymerase), and DRB (inhibits casein kinase 2). All had antiviral effects below the concentrations required for cell growth arrest. Compounds were tested in skin organ culture at EC(99) doses; all prevented VZV replication in skin, except for aloisine A and purvalanol A. In SCID mice with skin xenografts, roscovitine (0.7 mg/kg/day) was as effective as PAA (36 mg/kg/day). The screening systems described here are useful models for evaluating novel antiviral drugs for VZV.

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Fibropapillomatosis (FP) of marine turtles is an emerging neoplastic disease associated with infection by a novel turtle herpesvirus, fibropapilloma-associated turtle herpesvirus (FPTHV). This report presents 23 kb of the genome of an FPTHV infecting a Hawaiian green turtle (Chelonia mydas). By sequence homology, the open reading frames in this contig correspond to herpes simplex virus genes UL23 through UL36. The order, orientation, and homology of these putative genes indicate that FPTHV is a member of the Alphaherpesvirinae. The UL27-, UL30-, and UL34-homologous open reading frames from FPTHVs infecting nine FP-affected marine turtles from seven geographic areas and three turtle species (C. mydas, Caretta caretta, and Lepidochelys olivacea) were compared. A high degree of nucleotide sequence conservation was found among these virus variants. However, geographic variations were also found: the FPTHVs examined here form four groups, corresponding to the Atlantic Ocean, West pacific, mid-Pacific, and east Pacific. Our results indicate that FPTHV was established in marine turtle populations prior to the emergence of FP as it is currently known.

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We document three examples of fibropapillomatosis by histology, quantitative polymerase chain reaction (qPCR), and sequence analysis from three different geographic areas. Tumors compatible in morphology with fibropapillomatosis were seen in green turtles from Puerto Rico and San Diego (California) and in a hybrid loggerhead/ hawksbill turtle from Florida Bay (Florida). Tumors were confirmed as fibropapillomas on histology, although severity of disease varied between cases. Polymerase chain reaction (PCR) analyses revealed infection with the fibropapilloma-associated turtle herpesvirus (FPTHV) in all cases, albeit at highly variable copy numbers per cell. Alignment of a portion of the polymerase gene from each fibropapilloma-associated turtle herpesvirus isolate demonstrated geographic variation in sequence. These cases illustrate geographic variation in both the pathology and the virology of fibropapillomatosis.

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Fibropapillomatosis (FP) of marine turtles is a neoplastic disease of ecological concern. A fibropapilloma-associated turtle herpesvirus (FPTHV) is consistently present, usually at loads exceeding one virus copy per tumor cell. DNA from an array of parasites of green turtles (Chelonia mydas) was examined with quantitative PCR (qPCR) to determine whether any carried viral loads are sufficient to implicate them as vectors for FPTHV. Marine leeches (Ozobranchus spp.) were found to carry high viral DNA loads; some samples approached 10 million copies per leech. Isopycnic sucrose density gradient/qPCR analysis confirmed that some of these copies were associated with particles of the density of enveloped viruses. The data implicate the marine leech Ozobranchus as a mechanical vector for FPTHV. Quantitative RT-PCR analysis of FPTHV gene expression indicated that most of the FPTHV copies in a fibropapilloma have restricted DNA polymerase expression, suggestive of latent infection.

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