Modeling Overdispersion, Autocorrelation, and Zero-Inflated Count Data Via Generalized Additive Models and Bayesian Statistics in an Aphid Population Study.

Count variables are often positively skewed and may include many zero observations, requiring specific statistical approaches. Interpreting abiotic factor changes in insect populations of crop pests, under this condition, can be difficult. The analysis becomes even more complicated because of possible temporal or spatial correlation, irregularly spaced data, heterogeneity over time, and zero inflation. Generalized additive models (GAM) are important tools to evaluate abiotic factors. Moreover, Markov chain Monte Carlo (MCMC) techniques can be used to fit a model that contains a temporal correlation structure, based on Bayesian statistics (BGAM). We compared methods of modeling the effects of temperature, precipitation, and time for the Brevicoryne brassicae (L.) population in Uberlândia, Brasil. We applied the proposed BGAM to the data, comparing this to the GAM model with and without autocorrelation for time, using the statistical programming language R. Analysis of deviance identified significant effects of the smoothers for precipitation and time on the frequentist models. With BGAM, the problem in variance estimations for precipitation and temperature from the previous models was solved. Furthermore, trace and density plots for population-level effects for all parameters converged well. The estimated smoothing curves showed a linear effect with an increase of precipitation, where lower precipitation indicated no presence of the aphid. The average temperature did not affect the aphid incidence. Autocorrelation was solved with ARMA structures, and the excess of zero was solved with zero-inflation models. The example of B. brassicae incidence showed how well abiotic (and biotic) factors can be modeled and analyzed using BGAM.

Inhibition of inducible nitric oxide synthase-derived nitric oxide as a therapeutical target for acute pancreatitis induced by secretory phospholipase A2.

BACKGROUND: Nitric oxide is a key signalling molecule in the pathogenesis of inflammation, but its role in acute pancreatitis and related abdominal pain induced by secretory phospholipase A2 (sPLA2 ) from Crotalus durissus terrificus (Cdt) venom has not been investigated. METHODS: Male Wistar rats were i.v. injected with L-NAME (20 mg/kg), aminoguanidine (AG, 50 mg/kg), 7-nitroindazole (7-NI, 10 mg/kg) or vehicle 10 min before or 60 min after the injection of sPLA2 (300 µg/kg) into the common bile duct. After 4 h of sPLA2 injection, abdominal hyperalgesia and inflammation were assessed in addition to serum amylase, nitrite/nitrate (NOx), pancreas lipoperoxidation and 3-nitrotyrosine (3-NT) contents. RESULTS: sPLA2 -induced acute pancreatitis, related abdominal hyperalgesia, hyperamylasemia and increased concentration of NOx were not correlated with lipoperoxidation or increased 3-NT in the pancreas. Pretreatment with all the nitric oxide synthase (NOS) inhibitors significantly reduced abdominal mechanical hyperalgesia, but only iNOS blockade by AG suppressed pancreas oedema and serum NOx increase. The therapeutic approach with all the NOS inhibitors produced a similar reduction pattern of the abdominal hyperalgesia, but AG treatment also inhibited serum hyperamylasemia and NOx concentrations and pancreatic myeloperoxidase. The nNOS blockade by 7-NI treatment also inhibited myeloperoxidase activity in both pancreas and lung. CONCLUSIONS: Therapeutic blockade of iNOS or nNOS provides benefits in terms of inhibition of the acute pancreatitis-related abdominal hyperalgesia, while iNOS inhibition also ameliorates the inflammatory cell influx to the pancreas and reduces the resultant hyperamylasemia and NOx levels, thus representing alternative pharmacological strategies for treatment of clinical pancreatitis associated with increased PLA2 .