Inhibition of insulin-like growth factor 2 mRNA-binding protein 1 sensitizes colorectal cancer cells to chemotherapeutics.

Although colorectal cancer (CRC) treatment has seen a remarkable improvement in the recent years, many patients will develop metastasis due to the resistance of cancer cells to chemotherapeutics. Targeting mechanisms driving the resistance of CRC cells to treatment would significantly reduce cases of metastasis and death. Induction of insulin-like growth factor 2 mRNA-binding protein 1 (IGF2BP1), a direct target of the Wnt/ß-catenin signaling pathway, might promote resistance of CRC cells to treatment via activation of anti-apoptotic pathways and induction of the multidrug resistance (MDR1) membrane transporter that pumps drugs out of the cells. We hypothesized that inhibition of IGF2BP1 will sensitize CRC cells to chemotherapeutics. We used CRC cell lines with different status of activation of Wnt signaling to show that inhibition of IGF2BP1 potentiates the anti-growth and anti-proliferative effects of chemotherapeutics on CRC cells with activated Wnt/ß-catenin signaling pathway. We observed that the inhibition of IGF2BP1 significantly increases apoptosis in the same cells. A remarkable reduction in the migratory capability of those cells was noted as well. We found that inhibition of IGF2BP1 is sufficient to decrease the resistance of chemotherapy-resistant cancer cells with activated Wnt/ß-catenin signaling pathway. These findings portray IGF2BP1 as a good candidate for CRC therapy.

Quantitative Risk Assessment Model of Human Salmonellosis Resulting from Consumption of Broiler Chicken.

(1) Background: Salmonella infections are a major cause of illnesses in the United States. Each year around 450 people die from the disease and more than 23,000 people are hospitalized. Salmonella outbreaks are commonly associated with eggs, meat and poultry. In this study, a quantitative risk assessment model (QRAM) was developed to determine Salmonella infections in broiler chicken. (2) Methods: Data of positive Salmonella infections were obtained from the United States Department of Agriculture (USDA) and the Centers for Disease Control and Prevention (CDC) Foodborne Disease Outbreak Surveillance System, in addition to published literature. The Decision Tools @RISK add-in software was used for various analyses and to develop the QRAM. The farm-to-fork pathway was modeled as a series of unit operations and associated pathogen events that included initial contamination at the broiler house (node 1), contamination at the slaughter house (node 2), contamination at retail (node 3), cross-contamination during serving and cooking (node 4), and finally the dose⁻response model after consumption. (3) Results: QRAM of Salmonella infections from broiler meat showed highest contribution of infection from the retail node (33.5%). (4) Conclusions: This QRAM that predicts the risk of Salmonella infections could be used as a guiding tool to manage the Salmonella control programs.

The status of geo-environmental health in Mississippi: Application of spatiotemporal statistics to improve health and air quality.

Data enabled research with a spatial perspective may help to combat human diseases in an informed and cost-effective manner. Understanding the changing patterns of environmental degradation is essential to help in determining the health outcomes such as asthma of a community. In this research, Mississippi asthma-related prevalence data for 2003-2011 were analyzed using spatial statistical techniques in Geographic Information Systems. Geocoding by ZIP code, choropleth mapping, and hotspot analysis techniques were applied to map the spatial data. Disease rates were calculated for every ZIP code region from 2009 to 2011. The highest rates (4-5.5%) were found in Prairie in Monroe County for three consecutive years. Statistically significant hotspots were observed in urban regions of Jackson and Gulf port with steady increase near urban Jackson and the area between Jackson and meridian metropolis. For 2009-2011, spatial signatures of urban risk factors were found in dense population areas, which was confirmed from regression analysis of asthma patients with population data (linear increase of R2 = 0.648, as it reaches a population size of 3,5000 per ZIP code and the relationship decreased to 59% as the population size increased above 3,5000 to a maximum of 4,7000 per ZIP code). The observed correlation coefficient (r) between monthly mean O3 and asthma prevalence was moderately positive during 2009-2011 (r = 0.57). The regression model also indicated that 2011 annual PM2.5 has a statistically significant influence on the aggravation of the asthma cases (adjusted R-squared 0.93) and the 2011 PM2.5 depended on asthma per capita and poverty rate as well. The present study indicates that Jackson urban area and coastal Mississippi are to be observed for disease prevalence in future. The current results and GIS disease maps may be used by federal and state health authorities to identify at-risk populations and health advisory.

The recent outbreaks and reemergence of poliovirus in war and conflict-affected areas.

BACKGROUND: Poliomyelitis is a highly infectious disease caused by poliovirus, which becomes difficult to manage/eradicate in politically unstable areas. The objectives of this study were to determine the movement and management of such polio outbreaks in endemic countries and countries with reoccurring cases of polio and to determine the effect of political instability on polio eradication. METHODS: In this study, the extent of polio outbreaks was examined and modeled using statistical methodologies and mapped with GIS software. Data on polio cases and immunization were collected for countries with polio cases for the period 2011 to 2014. Weekly data from the Global Polio Eradication Initiative were collected for selected countries. The recent virus origin and current movement was mapped using GIS. Correlations between immunization rates, the Global Peace Index (GPI), and other indicators of a country's political stability with polio outbreaks were determined. Data were analyzed using SAS 9.4 and ArcGIS 10. RESULTS: For several reasons, Pakistan remains highly vulnerable to new incidences of polio (306 cases in 2014). Overall immunization rates showed a steady decline over time in selected countries. Countries with polio cases were shown to have high rates of infant mortality, and their GPI ranked between 2.0 and 3.3; displaced populations, level of violent crime rating, and political instability also were ranked high for several countries. CONCLUSION: Polio was shown to be high in areas with increased conflict and instability. Displaced populations living in hard-to-reach areas may lack access to proper vaccination and health care. Wars and conflict have also resulted in the reemergence of polio in otherwise polio-free countries.

Salmonella infections modelling in Mississippi using neural network and geographical information system (GIS).

OBJECTIVES: Mississippi (MS) is one of the southern states with high rates of foodborne infections. The objectives of this paper are to determine the extent of Salmonella and Escherichia coli infections in MS, and determine the Salmonella infections correlation with socioeconomic status using geographical information system (GIS) and neural network models. METHODS: In this study, the relevant updated data of foodborne illness for southern states, from 2002 to 2011, were collected and used in the GIS and neural networks models. Data were collected from the Centers for Disease Control and Prevention (CDC), MS state Department of Health and the other states department of health. The correlation between low socioeconomic status and Salmonella infections were determined using models created by several software packages, including SAS, ArcGIS @RISK and NeuroShell. RESULTS: Results of this study showed a significant increase in Salmonella outbreaks in MS during the study period, with highest rates in 2011 (47.84 ± 24.41 cases/100,000; p<0.001). MS had the highest rates of Salmonella outbreaks compared with other states (36 ± 6.29 cases/100,000; p<0.001). Regional and district variations in the rates were also observed. GIS maps of Salmonella outbreaks in MS in 2010 and 2011 showed the districts with higher rates of Salmonella. Regression analysis and neural network models showed a moderate correlation between cases of Salmonella infections and low socioeconomic factors. Poverty was shown to have a negative correlation with Salmonella outbreaks (R(2)=0.152, p<0.05). CONCLUSIONS: Geographic location besides socioeconomic status may contribute to the high rates of Salmonella outbreaks in MS. Understanding the geographical and economic relationship with infectious diseases will help to determine effective methods to reduce outbreaks within low socioeconomic status communities.

Effects of climate change on Salmonella infections.

BACKGROUND: Climate change and global warming have been reported to increase spread of foodborne pathogens. To understand these effects on Salmonella infections, modeling approaches such as regression analysis and neural network (NN) were used. METHODS: Monthly data for Salmonella outbreaks in Mississippi (MS), Tennessee (TN), and Alabama (AL) were analyzed from 2002 to 2011 using analysis of variance and time series analysis. Meteorological data were collected and the correlation with salmonellosis was examined using regression analysis and NN. RESULTS: A seasonal trend in Salmonella infections was observed (p<0.001). Strong positive correlation was found between high temperature and Salmonella infections in MS and for the combined states (MS, TN, AL) models (R(2)=0.554; R(2)=0.415, respectively). NN models showed a strong effect of rise in temperature on the Salmonella outbreaks. In this study, an increase of 1°F was shown to result in four cases increase of Salmonella in MS. However, no correlation between monthly average precipitation rate and Salmonella infections was observed. CONCLUSION: There is consistent evidence that gastrointestinal infection with bacterial pathogens is positively correlated with ambient temperature, as warmer temperatures enable more rapid replication. Warming trends in the United States and specifically in the southern states may increase rates of Salmonella infections.

Relationships between obesity and cardiovascular diseases in four southern states and Colorado.

Obesity is among the leading causes of elevated cardiovascular disease (CVD) mortality and morbidity. In the present study, the associations between the increase in body mass index (BMI) and the increase rates of CVD and high blood pressure (HBP) in the states of Mississippi, Alabama, Louisiana, Tennessee, and Colorado are examined using regression analysis and by means of neural network models for obesity and HBP. Data from Behavioral Risk Factor Surveillance System were obtained and analyzed for obesity rates, percent of myocardial infarction, stroke, and HBP from 2005-2009. Results of this study showed a low association between obesity and myocardial infarction rates (R2=0.067); a moderate association with stroke rates ((R2=0.462); and a strong association with HBP rates ((R2=0.811). The highest rates of obesity, CVD, and HBP were found in Mississippi, while Colorado had the lowest rates. Maintaining healthy weight helps reduce the risks of developing CVD.

Soil resources area affects herbivore health.

Soil productivity effects nutritive quality of food plants, growth of humans and animals, and reproductive health of domestic animals. Game-range surveys sometimes poorly explained variations in wildlife populations, but classification of survey data by major soil types improved effectiveness. Our study evaluates possible health effects of lower condition and reproductive rates for wild populations of Odocoileus virginianus Zimmerman (white-tailed deer) in some physiographic regions of Mississippi. We analyzed condition and reproductive data for 2400 female deer from the Mississippi Department of Wildlife, Fisheries, and Parks herd health evaluations from 1991-1998. We evaluated age, body mass (Mass), kidney mass, kidney fat mass, number of corpora lutea (CL) and fetuses, as well as fetal ages. Region affected kidney fat index (KFI), which is a body condition index, and numbers of fetuses of adults (P≤0.001). Region affected numbers of CL of adults (P≤0.002). Mass and conception date (CD) were affected (P≤0.001) by region which interacted significantly with age for Mass (P≤0.001) and CD (P<0.04). Soil region appears to be a major factor influencing physical characteristics of female deer.

Effects of socioeconomic factors on obesity rates in four southern states and Colorado.

OBJECTIVE: To examine the association between the increase in body mass index (BMI) and socioeconomic factors (eg, income level, % below poverty line, unemployment rates and persons receiving food stamps) in Mississippi, Alabama, Louisiana, Tennessee and Colorado. DESIGN: Data from Behavioral Risk Factor Surveillance System, United States Department of Agriculture and the United States Department of Labor/Bureau of Labor were obtained and analyzed for the years 1995-2008. RESULTS: Results from this study showed a strong association between obesity and the tested variables (R2 = .767). Factors more closely related with obesity were: income below poverty level; receipt of food stamps; unemployment; and general income level. The coefficient of determination for these variables were 0.438, 0.427, 0.103 and 0.018, respectively. The highest rate of obesity was found in Mississippi (26.5% +/- 4.13%) followed by Alabama (25.18% +/- 4.41%), while Colorado had the lowest rate of obesity (15.4% +/- 2.63%). By ethnicity, African Americans had the highest rate of obesity (32.64 +/- 5.99%). CONCLUSION: We found a significant effect of consumption of low-quality food, due to economic factors, on increased BMI. Besides physical activity, the quality and the quantity of food are important factors that contribute to obesity rates.