Deviation of spontaneous firing in frog medullar auditory units from the renewal point process

Statistical characteristics of spontaneous activity (distribution of interspike intervals, hazard function, autocorrelation function, autocorrelation function for the process with mixed intervals, and interdependence between adjoining intervals) were analyzed for 123 neurons of the frog medullar dorsal nucleus (homolog of the mammalian cochlear nucleus). In the majority of cells, this activity was distinct from the Poisson process, and firing periodicity was noticed in some cases. In addition, deviations of the spontaneous activity from the renewal process were usually observed. Weak yet reliable positive interspike-interval correlation was typical of most neurons; however, a negative correlation between short adjoining intervals was recorded for some units. These data suggest the effects of memory in the activity of single neurons of the auditory system.     

FD香葱生产中的危害分析与关键环节控制

将HACCCP体系引入FD(真空冷冻干燥)香葱生产过程中,经危害分析找出关键控制点,通过过程控制提高产品合格率,降低危害发生的风险,形成一套行之有效的食品安全管理体系.     

Biomonitoring of metal(oid)s in mining-affected Borcka Dam Lake coupled with public health outcomes

Due to increased anthropogenic activities, the aquatic environment is exposed to pollutants much more than ever. These pollutants go into the food chain and can pose a health risk to human. Correlatively, Borcka Dam Lake, Turkey has been affected by mining activities since decades. In the present study, therefore, Cu, Pb, As, Zn, Mn, Cd, Cr, and Se concentrations in water, sediment, and different tissues (muscle, gill, liver) of 11 fish species sampled from the lake were analyzed regarding metal(oid)s pollution and potential human health risk through fish consumption. The metal(oid) concentrations in the water were below the limit values recommended by USEPA for aquatic life criteria but sediments were heavily polluted by As, Cu, Pb, and Zn based on Sediment Quality Guideline. The lowest metal(oid) values among tissues for all fish species were determined in muscle (p < 0.05) which was lower than the limits for human consumption declared by European Union Regulation. Target Hazard Quotient and Hazard Index used non-cancer risk estimate which was lower than 1. In the view of these results, the consumption of fish caught from the Borcka Dam Lake may not pose a potential risk to human.     

Application of the Hazard Quotient Method in Remedial Decisions: A Comparison of Human and Ecological Risk Assessments

This paper evaluates the relative roles of the human health hazard index (HI) and the ecological risk assessment hazard quotient (HQ) in remedial decision-making. Through an analysis of HI outcomes drawn from Superfund Records of Decision, the reduced importance of the HI statistic in human health risk assessments is demonstrated, and the high visibility of the ecological risk assessment (ERA) HQ for terrestrial receptors (birds and mammals) is underscored. Three HQ method limitations common to both HHRA and ERA, deriving either from the mathematical construct of the HQ (a simple binary measure, indicating that an animal's exposure either exceeds its toxicity value or does not) or from dose-response outcomes in animal trials, are reviewed. Two additional HQ limitations unique to ERA (i.e., a propensity for the HQ to easily exceed its threshold value, and a propensity for it to assume values that are unreasonably high), and deriving from the complexities of estimating bird and mammal dietary intakes of contaminants and the availability of toxicological effects information, are also identified. The paper cautions of the potential to err in concluding that terrestrial site receptors are at risk when the HQ threshold is exceeded, and regardless of the toxicological information (NOAELs, LOAELs, etc.) used. It recognizes that because other methods of terrestrial assessment are presently unavailable, HQs are sometimes, out of necessity, used to justify a remedial action. The analysis and discussion are intended to remind ecological risk assessors that the HQ is a measure of a level of concern only and not a measure of risk     

Predicting cumulative incidence probability by direct binomial regression

We suggest a new simple approach for estimation and assessmentof covariate effects for the cumulative incidence curve in thecompeting risks model. We consider a semiparametric regressionmodel where some effects may be time-varying and some may beconstant over time. Our estimator can be implemented by standardsoftware. Our simulation study shows that the estimator workswell and has finite-sample properties comparable with the subdistributionapproach. We apply the method to bone marrow transplant dataand estimate the cumulative incidence of death in complete remissionfollowing a bone marrow transplantation. Here death in completeremission and relapse are two competing events.     

Health risk perspectives of metal(loid) exposure via consumption of striped venus clam (Chamelea gallina Linnaeus, 1758)

The metal(loid)s are mainly transported to the Black Sea via rivers and affect the coastal area where fisheries are intensive. Chamelea gallina (striped venus clam) is the most abundant mollusk species in the Black Sea and used as a bioindicator for monitoring of metal(loid) pollution. In this respect, the concentrations of As, Cd, Cr, Cu, Pb, and Zn in C. gallina collected from 16 different locations along the Black Sea coast (Turkey, Bulgaria, and Russia) were determined and evaluated for the potential human health risk. The results obtained were found to be below the maximum permissible limits indicated in the food safety guidelines. Similarly, the analyzed metal(loid)s did not pose a potential hazard to humans for consumption of the C. gallina, regarding provisional tolerable weekly intake described by the Joint FAO/WHO Expert Committee on Food Additives (JECFA). Moreover, target hazard quotient and hazard index were found to be lower than 1 for not only average consumer but also the consumer who consumed a portion (160 g) once a week. In contrast, consumption of C. gallina could cause health risks for Cd and As in case of increasing portion sizes.     

Assessment of heavy metal contamination of rice grains (Oryza sativa) and soil from Ada field,Enugu, Nigeria: Estimating the human healtrisk

The concentrations of heavy metals in rice grains and soils from Ada cultivated fields were investigated. Rice and soil samples were digested and the heavy metal concentrations determined using atomic absorption spectrophotometer. The results showed the following concentrations of metals (mg/kg): soil—Pb (4.64 ± 2.18), Cd (0.83 ± 0.83), Zn (20.26 ± 18.60), Mn (68.90 ± 19.91), Ni (3.46 ± 2.42), and Cr (21.41 ± 14.6); rice—Pb (3.99 ± 1.43), Cd (1.10 ± 0.53), Zn (65.37 ± 58.09), Mn (37.81 ± 5.82), Ni (3.12 ± 1.49), and Cr (10.87 ± 6.47). The Canadian, Nigerian and Chinese maximum allowable concentration for cadmium in soil were exceeded by 15%, 30%, and 85% of the soil samples, respectively. Heavy metals in all the rice samples evaluated were found to be above the World Health Organization (WHO) maximum permissible limit for lead, cadmium, and chromium. Strong positive and significant correlations were observed between some metal pairs in soil and rice indicating the similarity in origin. The estimated daily intakes of Pb and Cd from rice grown on the fields were higher than the safety levels established by WHO and the Joint FAO/WHO Expert Committee Food Additive, respectively. Hazard quotients and total hazard index for Pb and Cd were greater than 1. This indicates that consumption of rice from these fields will likely induce adverse health effects arising largely from Pb and Cd exposure.     

Toxicological evaluation of multi-class pesticide residues in vegetables and associated human health risk study for adults and children

This article describes, for the first time in 10 years, the toxicological evaluation of pesticide residues in highly consumed vegetables (35 commodities) and health risk studies. Among 1075 vegetable samples consisting mainly of tuber, root, fruiting, and Brassica, 20% of samples contained 38 pesticides in the range of 0.005–18.7 mg/kg and 1% > maximum residue limits (MRLs). Organophosphates and chloronitrile were most frequently found (20%) in the pesticide class. The highest concentration of 18.7 mg/kg was noted for dichlofluanid. Fruiting vegetables (8%), especially tomatoes (5%), were the most contaminated, while multi-residues were determined in 5% of the samples. Risk assessment was performed by analytical results and consumption on the 97.5 percentile expressed as hazard index (HI) and hazard quotient (HQ). The highest chronic HI was calculated for diazinon in lettuce (32% Acceptable Daily Intake (ADI) adults and 36% children) and for forbidden dieldrin in carrots (26%, 62% ADI). The highest acute HI was estimated for dichlofluanid in lettuce (69% Acute Reference Dose (ARfD)) for adults, whereas for children it was above the acceptance values of ARfD (168%). Organophosphate insecticides with common mode of action showed the greatest HQ (108% ADI). Vegetables may not be a serious problem for consumers, but investigations on pesticide residues are necessary to ensure food safety and the protection of human health, especially toward children who are more highly exposed to pesticides than adults.     

A Process Chaining Approach toward Product Design for Environment

This article presents an approach toward product design for environment (DfE) at the level that integrates environmental hazard analysis with models of transformation processes. As a complementary analysis tool to life-cycle assessment (LCA), this method would support detailed design decisions through modeling of a "process chain" for a subset of the product's life cycle. The building blocks for this approach are a set of unit process models that can convert process and design parameters into estimates for energy utilization, production scrap, and ancillary waste flows. These values for quantity of environmental releases can be integrated using a multicriiteria environmental hazard evaluation methodology that can estimate the "qualrty" of environmental releases. Finally, the waste information can be used to support a design model that can link design parameters to material, process, and operational parameter selection. A case study illustrating printed circuit board (PCB) assembly is presented to show process chain implementation in manufacturing applications.     

Nonparametric association analysis of bivariate left‐truncated competing risks data

We develop time‐varying association analyses for onset ages of two lung infections to address the statistical challenges in utilizing registry data where onset ages are left‐truncated by ages of entry and competing‐risk censored by deaths. Two types of association estimators are proposed based on conditional cause‐specific hazard function and cumulative incidence function that are adapted from unconditional quantities to handle left truncation. Asymptotic properties of the estimators are established by using the empirical process techniques. Our simulation study shows that the estimators perform well with moderate sample sizes. We apply our methods to the Cystic Fibrosis Foundation Registry data to study the relationship between onset ages of Pseudomonas aeruginosa and Staphylococcus aureus infections.     

On the relation between the cause-specific hazard and the subdistribution rate for competing risks data: The Fine–Gray model revisited

The Fine–Gray proportional subdistribution hazards model has been puzzling many people since its introduction. The main reason for the uneasy feeling is that the approach considers individuals still at risk for an event of cause 1 after they fell victim to the competing risk of cause 2. The subdistribution hazard and the extended risk sets, where subjects who failed of the competing risk remain in the risk set, are generally perceived as unnatural . One could say it is somewhat of a riddle why the Fine–Gray approach yields valid inference. To take away these uneasy feelings, we explore the link between the Fine–Gray and cause-specific approaches in more detail. We introduce the reduction factor as representing the proportion of subjects in the Fine–Gray risk set that has not yet experienced a competing event. In the presence of covariates, the dependence of the reduction factor on a covariate gives information on how the effect of the covariate on the cause-specific hazard and the subdistribution hazard relate. We discuss estimation and modeling of the reduction factor, and show how they can be used in various ways to estimate cumulative incidences, given the covariates. Methods are illustrated on data of the European Society for Blood and Marrow Transplantation.     

A case study of the influence of local weather on Aedes aegypti (L.) aging and mortality

The survival rate of mosquitoes is an important topic that affects many aspects of decision‐making in mosquito management. This study aims to estimate the variability in the survival rate of Ae. aegypti, and climate factors that are related to such variability. It is generally assumed that the daily probability of mosquito survival is independent of natural environment conditions and age. To test this assumption, a three‐year fieldwork (2005–2007) and experimental study was conducted at Fortaleza‐CE in Brazil with the aim of estimating daily survival rates of the dengue vector Aedes aegypti under natural conditions in an urban city. Survival rates of mosquitoes may be age‐dependent and statistical analysis is a sensitive approach for comparing patterns of mosquito survival. We studied whether weather conditions occurring on a particular day influence the mortality observed on that particular day. We therefore focused on the impact of daily meteorological fluctuations around a given climate average, rather than on the influence of climate itself. With regard to survival time, multivariate analyses using the stepwise logistic regression model, adjusted for daily temperature, relative humidity, and saturated vapor pressure deficit (SVPD), suggest that age, the seasonal factor, and the SVPD were the most dependent mortality factors. Similar results were obtained using the Cox proportional hazard model, which explores the relationships between the survival and explanatory variables.     

Competing Risks Data Analysis with High-dimensional Covariates:An Application in Bladder Cancer

Analysis of microarray data is associated with the methodological problems of high dimension and small sample size. Various methods have been used for variable selection in highdimension and small sample size cases with a single survival endpoint. However, little effort has been directed toward addressing competing risks where there is more than one failure risks. This study compared three typical variable selection techniques including Lasso, elastic net, and likelihood-based boosting for high-dimensional time-to-event data with competing risks. The performance of these methods was evaluated via a simulation study by analyzing a real dataset related to bladder cancer patients using time-dependent receiver operator characteristic(ROC) curve and bootstrap.632+ prediction error curves. The elastic net penalization method was shown to outperform Lasso and boosting. Based on the elastic net, 33 genes out of 1381 genes related to bladder cancer were selected. By fitting to the Fine and Gray model, eight genes were highly significant(P 0.001). Among them, expression of RTN4, SON, IGF1 R, SNRPE, PTGR1, PLEK, and ETFDH was associated with a decrease in survival time, whereas SMARCAD1 expression was associated with an increase in survival time. This study indicates that the elastic net has a higher capacity than the Lasso and boosting for the prediction of survival time in bladder cancer patients.Moreover, genes selected by all methods improved the predictive power of the model based on only clinical variables, indicating the value of information contained in the microarray features.