Iowa IPM Notes—Prevention, Detection, and Control of Bed Bugs in the Home

Bug bugs are embarrassing and annoying. This fact sheet answers common questions related to preventing, detecting and controlling bed bugs in the home.https://lib.dr.iastate.edu/extension_ag_pubs/1181/thumbnail.jp

Effects of transgenic Bacillus thuringiensis corn pollen on the monarch butterfly

Transgenic Bt corn has been widely planted in Iowa. This study considered whether plant tissues released by Bt corn (pollen and anthers) have an effect on monarch butterfly larvae

Black Cutworm Scouting Advisory

With the unseasonably warm temperatures occurring earlier this year, we asked black cutworm monitoring participants to place moth traps during the end of March. The first moth was recorded in Muscatine County on March 20. Peak flights have been reported by cooperators in many parts of Iowa this year. Our predictions of cutting dates (the date when black cutworm larvae are likely to be damaging corn) are based on recorded peak flights which took place near the end of March and approximately two weeks later in Iowa. The map (Fig. 1) shows the predicted cutting dates for Iowa climate divisions. Where there are two dates, the top date is an estimate based on moth captures that occurred near the end of March; all other dates are based on mid-April captures

Temporal trends in recording of diabetes on death certificates: results from Translating Research Into Action for Diabetes (TRIAD)

OBJECTIVE: To determine the frequency that diabetes is reported on death certificates of decedents with known diabetes and describe trends in reporting over 8 years. RESEARCH DESIGN AND METHODS: Data were obtained from 11,927 participants with diabetes who were enrolled in Translating Research into Action for Diabetes, a multicenter prospective observational study of diabetes care in managed care. Data on decedents (N=2,261) were obtained from the National Death Index from 1 January 2000 through 31 December 2007. The primary dependent variables were the presence of the ICD-10 codes for diabetes listed anywhere on the death certificate or as the underlying cause of death. RESULTS: Diabetes was recorded on 41% of death certificates and as the underlying cause of death for 13% of decedents with diabetes. Diabetes was significantly more likely to be reported on the death certificate of decedents dying of cardiovascular disease than all other causes. There was a statistically significant trend of increased reporting of diabetes as the underlying cause of death over time (P<0.001), which persisted after controlling for duration of diabetes at death. The increase in reporting of diabetes as the underlying cause of death was associated with a decrease in the reporting of cardiovascular disease as the underlying cause of death (P<0.001). CONCLUSIONS: Death certificates continue to underestimate the prevalence of diabetes among decedents. The increase in reporting of diabetes as the underlying cause of death over the past 8 years will likely impact estimates of the burden of diabetes in the U.S

Predictors of mortality over 8 years in type 2 diabetic patients: Translating Research Into Action for Diabetes (TRIAD)

OBJECTIVE To examine demographic, socioeconomic, and biological risk factors for all-cause, cardiovascular, and noncardiovascular mortality in patients with type 2 diabetes over 8 years and to construct mortality prediction equations. RESEARCH DESIGN AND METHODS Beginning in 2000, survey and medical record information was obtained from 8,334 participants in Translating Research Into Action for Diabetes (TRIAD), a multicenter prospective observational study of diabetes care in managed care. The National Death Index was searched annually to obtain data on deaths over an 8-year follow-up period (2000–2007). Predictors examined included age, sex, race, education, income, smoking, age at diagnosis of diabetes, duration and treatment of diabetes, BMI, complications, comorbidities, and medication use. RESULTS There were 1,616 (19%) deaths over the 8-year period. In the most parsimonious equation, the predictors of all-cause mortality included older age, male sex, white race, lower income, smoking, insulin treatment, nephropathy, history of dyslipidemia, higher LDL cholesterol, angina/myocardial infarction/other coronary disease/coronary angioplasty/bypass, congestive heart failure, aspirin, β-blocker, and diuretic use, and higher Charlson Index. CONCLUSIONS Risk of death can be predicted in people with type 2 diabetes using simple demographic, socioeconomic, and biological risk factors with fair reliability. Such prediction equations are essential for computer simulation models of diabetes progression and may, with further validation, be useful for patient management

Analysis of the In Vivo Transcriptome of Bordetella pertussis during Infection of Mice

Bordetella pertussis causes the disease whooping cough through coordinated control of virulence factors by the Bordetella virulence gene system. Microarrays and, more recently, RNA sequencing (RNA-seq) have been used to describe in vitro gene expression profiles of B. pertussis and other pathogens. In previous studies, we have analyzed the in vitro gene expression profiles of B. pertussis, and we hypothesize that the infection transcriptome profile in vivo is significantly different from that under laboratory growth conditions. To study the infection transcriptome of B. pertussis, we developed a simple filtration technique for isolation of bacteria from infected lungs. The work flow involves filtering the bacteria out of the lung homogenate using a 5-μm-pore-size syringe filter. The captured bacteria are then lysed to isolate RNA for Illumina library preparation and RNA-seq analysis. Upon comparing the in vitro and in vivo gene expression profiles, we identified 351 and 255 genes as activated and repressed, respectively, during murine lung infection. As expected, numerous genes associated with virulent-phase growth were activated in the murine host, including pertussis toxin (PT), the PT secretion apparatus, and the type III secretion system. A significant number of genes encoding iron acquisition and heme uptake proteins were highly expressed during infection, supporting iron acquisition as critical for B. pertussis survival in vivo. Numerous metabolic genes were repressed during infection. Overall, these data shed light on the gene expression profile of B. pertussisduring infection, and this method will facilitate efforts to understand how this pathogen causes infection

Eavesdropping on the Arctic: Automated bioacoustics reveal dynamics in songbird breeding phenology

Bioacoustic networks could vastly expand the coverage of wildlife monitoring to complement satellite observations of climate and vegetation. This approach would enable global-scale understanding of how climate change influences phenomena such as migratory timing of avian species. The enormous data sets that autonomous recorders typically generate demand automated analyses that remain largely undeveloped. We devised automated signal processing and machine learning approaches to estimate dates on which songbird communities arrived at arctic breeding grounds. Acoustically estimated dates agreed well with those determined via traditional surveys and were strongly related to the landscape’s snow-free dates. We found that environmental conditions heavily influenced daily variation in songbird vocal activity, especially before egg laying. Our novel approaches demonstrate that variation in avian migratory arrival can be detected autonomously. Large-scale deployment of this innovation in wildlife monitoring would enable the coverage necessary to assess and forecast changes in bird migration in the face of climate change

Predictors and Impact of Intensification of Antihyperglycemic Therapy in Type 2 Diabetes: Translating Research into Action for Diabetes (TRIAD)

ObjectiveThe purpose of this study was to examine the predictors of intensification of antihyperglycemic therapy in patients with type 2 diabetes; its impact on A1C, body weight, symptoms of anxiety/depression, and health status; and patient characteristics associated with improvement in A1C.Research design and methodsWe analyzed survey, medical record, and health plan administrative data collected in Translating Research into Action for Diabetes (TRIAD). We examined patients who were using diet/exercise or oral antihyperglycemic medications at baseline, had A1C &gt;7.2%, and stayed with the same therapy or intensified therapy (initiated or increased the number of classes of oral antihyperglycemic medications or began insulin) over 18 months.ResultsOf 1,093 patients, 520 intensified therapy with oral medications or insulin. Patients intensifying therapy were aged 58 +/- 12 years, had diabetes duration of 11 +/- 9 years, and had A1C of 9.1 +/- 1.5%. Younger age and higher A1C were associated with therapy intensification. Compared with patients who did not intensify therapy, those who intensified therapy experienced a 0.49% reduction in A1C (P &lt; 0.0001), a 3-pound increase in weight (P = 0.003), and no change in anxiety/depression (P = 0.5) or health status (P = 0.2). Among those who intensified therapy, improvement in A1C was associated with higher baseline A1C, older age, black race/ethnicity, lower income, and more physician visits.ConclusionsTreatment intensification improved glycemic control with no worsening of anxiety/depression or health status, especially in elderly, lower-income, and minority patients with type 2 diabetes. Interventions are needed to overcome clinical inertia when patients might benefit from treatment intensification and improved glycemic control