Critical Effects

The selectivity of pervaporation membranes varies considerably and has a critical effect on the overall separation obtained. The range of results that can be obtained for the same solutions and different membranes is illustrated in Figure 41 for the separation of acetone from water using two types of membrane (89). The figure shows the concentration of acetone in the permeate as a function of the concentration in the feed. The two membranes shown have dramatically different properties. The siUcone mbber membrane removes acetone selectively, whereas the cross-linked poly(vinyl alcohol) (PVA) membrane removes water selectively. This difference occurs because siUcone mbber is hydrophobic and mbbery, thus permeates the acetone preferentially. PVA, on the other hand, is hydrophilic and glassy, thus permeates the small hydrophilic water molecules preferentially. 

The dried malted barley is ground and mashed in a tub, after which the Hquid portion is drained off, cooled, and placed in the fermentor. After fermentation, a batch distillation system is usually used to separate the whisky from the fermented wort. The stiU consists of a copper ketde with a spiral tube or "worm" leading from the top. The dimensions and shape of the stills have a critical effect on the character of the whisky. The product taken off in the first part of the distillation is called foreshots (heads). The middle portion is the high wines and the last portion is the feints (tails). The middle portion is redistilled at the 140—160° proof (70—80%) range and matured in used oak cooperage. 

Organ-spcctfic Defining organ-specific effects and defining chemically induced critical effects... 

There are several limitations to tliis approach that must be acknowledged. As mentioned earlier, tlie level of concern does not increase linearly as the reference dose is approached or exceeded because the RfDs do not luive equal accuracy or precision and are not based on the same severity of effects. Moreover, luizm-d quotients are combined for substances with RfDs based on critical effects of vaiy ing toxicological significance. Also, it will often be the case that RfDs of varying levels of confidence Uiat include different uncertainty adjustments and modifying factors will be combined (c.g., extrapolation from animals to hmnans, from LOAELs to NOAELs, or from one exposure duration to anoUier). 

EPA has derived an RfD of. 00025 mg/kg/day, based on a NOAEL of 0.025 for reduced hematocrit, erythrocyte counts, and hemoglobin (cholinesterase inhibition was also listed as a critical effect but the reason for this was not explained). This NOAEL appears to be from the same study as for the ATSDR chronic-duration oral MRL, although the study is referenced differently (IRIS 2001). 

For chemicals in general the identification of a potential hazard normally arises from the application of in vitro tests or from short-term toxicity studies undertaken in laboratory animals (up to a period of 90 days in the case of the rat where the test material normally should not exceed 1% of the total diet). This usually enables a critical effect to be assessed. 

Stages in hazard characterization according to the European Commission s Scientific Steering Committee are (1) establishment of the dose-response relationship for each critical effect (2) identification of the most sensitive species and strain (3) characterization of the mode of action and mechanisms of critical effects (including the possible roles of active metabolites) (4) high to low dose (exposure) extrapolation and interspecies extrapolation and (5) evaluation of factors that can influence severity and duration of adverse health effects. 

The expression (1/Z+ 1)] exp[— AHl /RT] at 0.85 V, better reflects the reality of a partially oxidized Pt surface and the critical effect of active site availability on the rate of the ORR. Effects of site availability were not considered in the calculations in Nprskov et al. [2004] of ORR activity for various metals. The expression used to calculate activity defined the ordinate parameter in the ORR volcano plots presented. This parameter was defined in Nprskov et al. [2004] as kT min,- log(k,/ko). 

Several reports identified nonlethal effects in humans acutely exposed to arsine. These reports, however, lacked definitive exposure data but verified hematologic disorders leading to renal failure as critical effects of arsine exposure. Bulmer et al. (1940) (as cited in Elkins 1959) reconstructed an exposure incident at a gold extraction facility and estimated that subchronic (up to 8 mon) exposure to 0.12 ppm arsine resulted in jaundice and anemia (see Section 2.2.1). The lack of definitive exposure data for humans necessitates the use of animal data for quantitative estimation of AEGL values. Derivation of AEGL-2 values based upon limited human data (Flury and Zernik 1931) was considered but rejected because the data were poorly documented and inconsistent with other data showing lethality at lower cumulative exposures. 

ATSDR has calculated an MRL of 6 ppm for acute inhalation exposure to hexachloroethane based on a NOAEL of 48 ppm from a study in pregnant rats. The critical effect was tremors, which occurred during an 11-day exposure period at a LOAEL of 260 ppm (Weeks et al. 1979). The intermediate inhalation MRL of 6 ppm was also calculated from a NOAEL of 48 ppm observed in a 6-week study in which tremors were observed in rats exposed intermittently at 260 ppm (Weeks et al. 1979). 

However, no studies on fetal exposure are available for setting TEFs. Thus there is a need for dose-response studies of the critical effects, based on synthetic mixtures reflecting the human exposure situation. The WHO TEFs for dioxins, dibenzofurans and PCBs for humans and mammals are given in Table 3. 

The critical effect of intermediate-duration exposure to -hexane in humans is neurotoxicity, specifically peripheral neuropathy. No inhalation MRL was derived for this duration because the reports of neurological effects in humans were predominantly case reports with inadequate documentation of exposure levels or comparison with unexposed groups. A large database on neurological effects in rats exists for this duration however, the design of these experiments precluded documentation of clear dose-response relationships within a single study. Because of the limited database for oral exposure to -hexane and the lack of toxicokinetic data for this route, no MRL was derived for oral exposure to -hexane. 

The critical effect for -hexane is neurotoxicity, and the sensitive species is the rat. The EPA used LOAELs from the same study to establish a Reference Concentration (RfC) of 0.2 mg/m3 (0.06 ppm) for... 

The smaller the critical effect size, the larger the necessary sample size. Subtle effects require greater efforts. 

ATSDR has derived a chronic oral MRL of 0.0003 mg/kg/day based on a laboratory animal study showing neurotoxic effects in dogs (Kettering Lab 1969). The EPA reference dose for endrin is 3xl0 4 mg/kg/day, and the critical dose is 0.025 mg/kg/day (IRIS 1995). Critical effects were occasional convulsions and mild histological lesions in the liver (Kettering Lab 1969). No EPA reference concentration exists for the compound. 

The maximum endo.exo ratio occurs above the critical density, suggesting that it is not a critical effect. Again, this effect was rationalized on the basis of a solvent potential tuning phenomenon, where the number of solvent molecules per molecule of substrate is optimized to favour one particular transition state. No... 

Physiological Buffer Systems Recently, a lot of efforts have been made on how to increase the biorelevance of the Caco-2 model [63, 47, 64, 65,105], Historically, the media used for Caco-2 experiments were buffered at pH 7.4 on both sides of the monolayer. The pH in the cellular interstice and blood compartment is known to be 7.4. However, the pH in the upper GI tract under fasted conditions ranges from 5.0 to 6.5, with an acidic microclimate existing just above the epithelial cell layer estimated to be between 5.8 and 6.3 [90], The pH of the apical medium can have a critical effect on the transport of drugs, especially for drugs with a pKa close to 7, or when pH-dependent transporters are involved. 

As expected, the terminal functional groups mainly determine the reactivity of these siloxane oligomers towards other reactants. The variations in the backbone composition have critical effects on the glass transition temperature, solubility parameter, thermal stability and surface behavior of the resulting oligomers(12,13). 

FIGURE 14 Standardized Pareto plot. The standardized effects are plotted as a function of their extends.The dark line is the border of decision according to a t-test. Critical effects exceed this line. 

The statistical evaluation leads to a limit value, i.e., a critical effect, and all effects. Ex, that are in absolute value larger than or equal to the limit value are considered significant. The limit value is usually based on the t-test statistic given in the following equation " " ... 

TABLE 10 Effects on the Responses of Table 8 and Critical Effects According to Different Statistical Interpretation Methods... 

The critical effect, Ecriticai, depends on the (tabulated) critical t-value, tcriticaij and on (SE)e. The tcridcai depends on the number of degrees of freedom associated with (SE) and is usually considered at a significance level a = 0.05 (occasionally also a = 0.01). An effect is considered significant if xl > Emtical- In a robustness test, (SE)e can be estimated in different... 

The most appropriate approaches estimate the error based on a priori considered negligible effects, such as dummies, or on the algorithm of Dong. They usually result in similar critical effects. 

The error estimate based on replicates at nominal level results in underestimated critical effects, and consequently a high number of effects is considered significant, which practically are not relevant, e.g., the effects of A, C, D, I, E, and J on response Rs at significance level a = 0.05 (Table 10). A possible reason is that the replicates are measured under repeatability conditions. For duplicated design experiments, a similar problem might occur. However, in Table 11 it is not the case or the critical effect is only slightly underestimated. In case underestimation occurs for a response related to the quantitative aspect, the method would incorrectly be considered non-robust, since effects considered significant occur. This is fundamentally not a problem, because one will react when it is not necessary. It just leads to a waste of time and money. The opposite situation is worse. 

The error estimate based on the variance of the design experiments themselves leads to similar critical effects as the algorithm of Dong when no or small significant effects occur. However, when a large effect is present, e.g., that of factor B on Rs in Table 10 or that of factor D on response MTs t in Table 11, the error is overestimated, compared to the algorithm of Dong. 

For example, the effect of factor A on response CR t at ot = 0.05 was found significant when using the variance from duplicated design experiments to estimate the critical effect (see Table 11). However, since this factor represents different CE equipments, i.e., is discrete, calculating a non-significance interval is irrelevant. 

Suppose a factor X has 45, 50, and 55 as extreme low, nominal, and extreme high levels, respectively, and an effect of 100 on response Y, with the critical effect equal to 80. Then the non-significance interval limits for this factor are [46.0,54.0], which means that when restricting the levels of X to this interval, the quantitative aspect of the method is considered robust. It can be noticed that the interval is symmetrically around the nominal level and meant for factors thus examined, i.e., with extreme levels symmetrically around the nominal. 

In references 71 and 72, SST limits are defined based on experience, and the examined responses should fall within these limits. The two papers do not provide much information concerning the robustness test performed. Therefore, it is not evident to comment on the analysis applied, or to suggest alternatives. In reference 73, a graphical analysis of the estimated effects by means of bar plots was performed. In reference 74, a statistical analysis was made in which an estimation of error based on negligible two-factor interaction effects was used to obtain the critical effects between levels [—1,0] and [0,4-1]. 

In references 82-86, the results were treated statistically. Main effects and standard errors were calculated. In references 83, 85, and 86 also a graphical interpretation by means of bar plots was performed. Both positive and negative effects were seen on these plots, but all effects between levels [—1,0] are negative, while all those between [0,4-1] are positive. Possibly, the length of the bars represents the absolute value of the factor effects, and all effects for the interval [—1,0] seem to be given a negative sign, while all those for [0,4-1] a positive. However, the above are assumptions since no details were provided. In references 83 and 86, critical effects are drawn on the bar plots. 

An alternative approach to analyze the data from the reflected PB designs would be to calculate the effects between [—1,0] and [0,+l], and then calculating critical effects between [—1,0] and [0,+l] with the algorithm of Dong (Section VII.B.2.(c)). Since normally there is no reason why the error estimates for the intervals [—1,0] and [0,+l] would be different, they could be pooled, resulting in one error estimate and one critical effect. 

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