Phenology, Within-Vineyard Distribution, and Seasonal Movement of Eastern Grape Leafhopper (Homoptera: Cicadellidae) in New York Vineyards

Seasonal changes in within-vineyard distribution and abundance of Erythroneura comes (Say) adults and nymphs were investigated from 1989 to 1992. Trap catches of adults were highest in May and were concentrated in wooded areas next to vineyards. In 1989 and 1990 surveys, nymphal densities did not decline as distance from the vineyard edge increased. In 1991, however, nymphal densities were significantly higher at vineyard edges than in vineyard interiors in July, suggesting that oviposition initially was aggregated at vineyard edges. Subsequently, nymphal densities at vineyard edges and interiors were similar. Cumulative degree days (DD) for mean observation of first nymphs, first-generation, and second-generation peak populations, sampled at 14 vineyards in 1989, 1990, and 1991, were 390 ± 71, 648 ± 86, and 1,190 ± 154 DD (mean ± SD; base 10°C), respectively. Nymphal densities exceeded a provisional threshold of five per leaf in only 2, 25, 13, and 8% of vineyards untreated with insecticides in 1989, 1990, 1991, and 1992, respectively. These results show that leafhoppers do not cause economic injury in most New York vineyards in most years. Reduced insecticide strategies recently implemented for grape berry moth control will not greatly increase the need for insecticide applications directed at leafhoppers in New Yor

Detecting Change: Observations of Temperature and Precipitation Across Virginia’s Climate Divisions

Modern global climate change is primarily attributable to human activities and the release of greenhouse gases into the atmosphere. Climate change impacts span a range of sectors, including agriculture, forestry, public health, and water resource management. The Commonwealth of Virginia has already and will continue to deal with many of these impacts, yet lacks concentrated effort to detect, document, and adapt to local climate changes. This study documents observed changes in temperature and precipitation across Virginia’s six climate divisions. Mean seasonal anomalies of minimum temperature, maximum temperature, and precipitation from 1986 to 2016 are examined relative to a long-term 1895-2000 baseline. Additionally, the study assesses and reports full-record (1895-2016) trends for each climate division. Results demonstrate warming across all climate divisions in Virginia, particularly during the winter season (December, January, and February). Precipitation changes vary across the Commonwealth and seasons. Drying conditions, particularly in the Eastern and Western Piedmont, are noteworthy during the summer, while wetter conditions prevail in the spring and autumn. Former Governor Kaine’s 2008 Climate Action Plan and subsequent 2016 update by Governor McAuliffe’s administration called for a Virginia climate information clearinghouse where the public and decision-makers could efficiently access valuable weather and climate information. This paper represents a first step in this yet unrealized plan

Reconstructing Cardiac Electrical Excitations from Optical Mapping Recordings

The reconstruction of electrical excitation patterns through the unobserved depth of the tissue is essential to realizing the potential of computational models in cardiac medicine. We have utilized experimental optical-mapping recordings of cardiac electrical excitation on the epicardial and endocardial surfaces of a canine ventricle as observations directing a local ensemble transform Kalman Filter (LETKF) data assimilation scheme. We demonstrate that the inclusion of explicit information about the stimulation protocol can marginally improve the confidence of the ensemble reconstruction and the reliability of the assimilation over time. Likewise, we consider the efficacy of stochastic modeling additions to the assimilation scheme in the context of experimentally derived observation sets. Approximation error is addressed at both the observation and modeling stages, through the uncertainty of observations and the specification of the model used in the assimilation ensemble. We find that perturbative modifications to the observations have marginal to deleterious effects on the accuracy and robustness of the state reconstruction. Further, we find that incorporating additional information from the observations into the model itself (in the case of stimulus and stochastic currents) has a marginal improvement on the reconstruction accuracy over a fully autonomous model, while complicating the model itself and thus introducing potential for new types of model error. That the inclusion of explicit modeling information has negligible to negative effects on the reconstruction implies the need for new avenues for optimization of data assimilation schemes applied to cardiac electrical excitation.Comment: main text: 18 pages, 10 figures; supplement: 5 pages, 9 figures, 2 movie

Environmental signal integration by a modular AND gate

Microorganisms use genetic circuits to integrate environmental information. We have constructed a synthetic AND gate in the bacterium Escherichia coli that integrates information from two promoters as inputs and activates a promoter output only when both input promoters are transcriptionally active. The integration occurs via an interaction between an mRNA and tRNA. The first promoter controls the transcription of a T7 RNA polymerase gene with two internal amber stop codons blocking translation. The second promoter controls the amber suppressor tRNA supD. When both components are transcribed, T7 RNA polymerase is synthesized and this in turn activates a T7 promoter. Because inputs and outputs are promoters, the design is modular; that is, it can be reconnected to integrate different input signals and the output can be used to drive different cellular responses. We demonstrate this modularity by wiring the gate to integrate natural promoters (responding to Mg2+ and AI-1) and using it to implement a phenotypic output (invasion of mammalian cells). A mathematical model of the transfer function is derived and parameterized using experimental data

Performance of the Universal Vital Assessment (UVA) Mortality Risk Score in Hospitalized Adults with Infection in Rwanda: A Retrospective External Validation Study

BACKGROUND: We previously derived a Universal Vital Assessment (UVA) score to better risk-stratify hospitalized patients in sub-Saharan Africa, including those with infection. Here, we aimed to externally validate the performance of the UVA score using previously collected data from patients hospitalized with acute infection in Rwanda. METHODS: We performed a secondary analysis of data collected from adults ≥18 years with acute infection admitted to Gitwe District Hospital in Rwanda from 2016 until 2017. We calculated the UVA score from the time of admission and at 72 hours after admission. We also calculated quick sepsis-related organ failure assessment (qSOFA) and modified early warning scores (MEWS). We calculated amalgamated qSOFA scores by inserting UVA cut-offs into the qSOFA score, and modified UVA scores by removing the HIV criterion. The performance of each score determined by the area under the receiver operator characteristic curve (AUC) was the primary outcome measure. RESULTS: We included 573 hospitalized adult patients with acute infection of whom 40 (7%) died in-hospital. The admission AUCs (95% confidence interval [CI]) for the prediction of mortality by the scores were: UVA, 0.77 (0.68-0.85); modified UVA, 0.77 (0.68-0.85); qSOFA, 0.66 (0.56-0.75), amalgamated qSOFA, 0.71 (0.61-0.80); and MEWS, 0.74 (0.64, 0.83). The positive predictive values (95% CI) of the scores at commonly used cut-offs were: UVA \u3e4, 0.35 (0.15-0.59); modified UVA \u3e4, 0.35 (0.15-0.59); qSOFA \u3e1, 0.14 (0.07-0.24); amalgamated qSOFA \u3e1, 0.44 (0.20-0.70); and MEWS \u3e5, 0.14 (0.08-0.22). The 72 hour (N = 236) AUC (95% CI) for the prediction of mortality by UVA was 0.59 (0.43-0.74). The Chi-Square test for linear trend did not identify an association between mortality and delta UVA score at 72 hours (p = 0.82). CONCLUSIONS: The admission UVA score and amalgamated qSOFA score had good predictive ability for mortality in adult patients admitted to hospital with acute infection in Rwanda. The UVA score could be used to assist with triage decisions and clinical interventions, for baseline risk stratification in clinical studies, and in a clinical definition of sepsis in Africa

Evaluation of Emergency Medicine Community Educational Program

Out-of-hospital emergencies occur frequently, and laypersons are often the first to respond to these events. As an outreach to our local communities, we developed “Basic Emergency Interventions Everyone Should Know,” a three-hour program addressing cardiopulmonary resuscitation and automated external defibrillator use, heart attack and stroke recognition and intervention, choking and bleeding interventions and infant and child safety. Each session lasted 45 minutes and was facilitated by volunteers from the emergency department staff. A self-administered 13-item questionnaire was completed by each participant before and after the program. A total of 183 participants completed the training and questionnaires. Average score pre-training was nine while the average score post-training was 12 out of a possible 13 (P< .0001). At the conclusion of the program 97% of participants felt the training was very valuable and 100% would recommend the program to other members of their community

A refined, controlled 16S rRNA gene sequencing approach reveals limited detection of cerebrospinal fluid microbiota in children with bacterial meningitis

Advances in both laboratory and computational components of high-throughput 16S amplicon sequencing (16S HTS) have markedly increased its sensitivity and specificity. Additionally, these refinements have better delineated the limits of sensitivity, and contributions of contamination to these limits, for 16S HTS that are particularly relevant for samples with low bacterial loads, such as human cerebrospinal fluid (CSF). The objectives of this work were to (i) optimize the performance of 16S HTS in CSF samples with low bacterial loads by defining and addressing potential sources of error, and (ii) perform refined 16S HTS on CSF samples from children diagnosed with bacterial meningitis and compare results with those from microbiological cultures. Several bench and computational approaches were taken to address potential sources of error for low bacterial load samples. We compared DNA yields and sequencing results after applying three different DNA extraction approaches to an artificially constructed mock-bacterial community. We also compared two postsequencing computational contaminant removal strategies, decontam R and full contaminant sequence removal. All three extraction techniques followed by decontam R yielded similar results for the mock community. We then applied these methods to 22 CSF samples from children diagnosed with meningitis, which has low bacterial loads relative to other clinical infection samples. The refined 16S HTS pipelines identified the cultured bacterial genus as the dominant organism for only 3 of these samples. We found that all three DNA extraction techniques followed by decontam R generated similar DNA yields for mock communities at the low bacterial loads representative of CSF samples. However, the limits of detection imposed by reagent contaminants and methodologic bias precluded the accurate detection of bacteria in CSF from children with culture-confirmed meningitis using these approaches, despite rigorous controls and sophisticated computational approaches. Although we did not find current DNA-based diagnostics to be useful for pediatric meningitis samples, the utility of these methods for CSF shunt infection remains undefined. Future advances in sample processing methods to minimize or eliminate contamination will be required to improve the sensitivity and specificity of these methods for pediatric meningitis