Paul David Sponseller, M.D.

• Chief, Division of Pediatric Orthopaedics
• Professor of Orthopaedic Surgery

https://www.hopkinsmedicine.org/profiles/results/directory/profile/0004804/paul-sponseller

The results of a meta-analysis by the fixed-effects method are thus valid only if this is a reasonable assumption to make antibiotics for acne bad purchase cheap cefixime online. This assumption cannot be reasonably made if the combined studies differ with respect to important design attributes (Table 9 infection 6 weeks after hysterectomy order 100 mg cefixime overnight delivery. If current medical knowledge suggests that the effect of an intervention should differ in various situations (such as those shown in Table 9 infection 3 months after miscarriage effective 100 mg cefixime. A meta-analysis by the randomeffects method [66] is advocated for these circumstances infection 1 mind games cefixime 100 mg low cost. The assumption of a random-effects analysis is that the effect of the exposure or treatment varies from study to study antibiotic resistant gonorrhea 2015 generic cefixime 100 mg without a prescription, being randomly positioned about some central value antimicrobial journals impact factor buy 100mg cefixime. This value is the summary or "average" effect of the exposure or treatment across the combined studies. In a fixed-effects analysis, only within-studies variation influences the uncertainty of the summary effect across the combined studies that are calculated by the overview. This sampling variation is inversely proportional to the sample size of each report. No between-studies variation is presumed to exist when a fixed-effects analysis is conducted, as all included studies are assumed to measure the same (fixed) effect of the exposure or treatment. Therefore, the differences among the studies in the magnitude and direction of the reported treatment effect do not influence the uncertainty that surrounds the summary effect calculated by the meta-analysis. On the contrary, in a random-effects analysis, both within-studies and between-studies variation influence the uncertainty surrounding the calculated summary effect. The uncertainty associated with the measured estimate of the effect increases if the sample size of the combined studies is small, because small sample sizes result in large within-studies variation. The uncertainty increases further if the combined studies differ in important design characteristics (such as those shown in Table 9. The more the combined studies differ in important design characteristics, the greater the expected differences in the estimates of the effect(s) calculated by these studies; therefore, the greater also the between-studies variation, and the greater the uncertainty surrounding the summary effect calculated by the meta-analysis. Small studies have more of an impact on the calculated "average" effect when a random- (as opposed to fixed-) effects analysis is undertaken. When the literature eligible for analysis consists of one (or a few) large investigations and many small studies, a single large report may dominate the findings of an overview conducted by a fixedeffects method. This analysis would take only the within-studies variation into account, and would thus weigh studies with large sample sizes (and small within-studies variation) more favorably than small reports. Therefore, the conclusions of the overview could, for the most part, reflect the results of these few large studies, as opposed to the composite evidence from all completed studies. In contrast, the findings of a meta-analysis by the random-effects method would reflect the combination of within- and between-studies variation. The more the combined studies differ in important design attributes, the more important the betweenstudies variation becomes, as compared to the within-studies variation. As a result, the more the influence of a single large study diminishes, and the more the stated conclusions of the overview accomplish the purpose of the meta-analysis, which is to examine the effect of an exposure or treatment in many, different situations. If there are no important design differences between the combined studies, random- and fixed-effects analyses will produce similar results. On the contrary, if there are substantive differences among the studies, the two methods of analysis will produce disparate results [64]. Fixed- and random-effects analyses are based on different conceptions of the proper role, scope, and meaning of meta-analysis. Assessment of the Combinability of the Reports Included in the Meta-Analysis Results of separate studies should be combined by the methods of meta-analysis only when the estimates of effect size that they have reported are sufficiently close to one another. A discussion of the homogeneity (or heterogeneity) of the studies must precede any integration of studies in a meta-analysis. Study results should not be integrated in the presence of unexplained heterogeneity, although this principle is very often not adhered to in published meta-analyses. In this situation, the hypothesis of homogeneity is rejected, and the results of the studies should not be combined. Such statistical heterogeneity generally reflects the medical heterogeneity of the studies. The Q test statistic is a chi-square test with n - 1 degrees of freedom (where n = number of studies included in the overview). I2 does not inherently depend on the number of studies included in the analysis, and it is expressed as a percentage. For this reason, it has intuitive meaning to the reader, and it can be directly compared between meta-analyses. Low heterogeneity corresponds to I2 values of <25%, while high heterogeneity is reflected in I2 values of >75% [72]. Instead, they suggested that quantification of heterogeneity is only one component of a wider investigation of variability across studies; and that the interpretation of a given degree of heterogeneity will differ according to whether the estimates of effect from the various studies show the same direction of effect. The simplest method for explaining heterogeneity is a stratification of the eligible studies based on design, quality, and/or characteristics of enrolled patients and/or administered interventions or exposures. Providing that the hypothesis of homogeneity is not rejected within each stratum following such stratification of the available studies, the calculated stratum-specific "average" treatment effects may help explain the disagreements among the available reports. Regression techniques offer a more elegant method for explaining heterogeneity among studies [80]. Only the subgroup analysis of studies conducted in cardiac surgery [21, 23, 25, 28, 29] produced a statistically significant (p < 0. Both the cardiac-surgery and the noncardiac-surgery studies were homogeneous (p > 0. Cardiac-surgery studies enrolled a total of 2,990 patients; noncardiac-surgery studies a total of 5,045. Most importantly, the relevance of the findings to patient care must be explained to the reader. In addition, readers of overviews must be reminded that meta-analyses use historical material from studies published over a considerable period, because this historical nature of the material may influence the applicability of the findings to contemporary clinical practice. This is probably because the findings of meta-analyses are susceptible to the effects of selection and observation bias, in a manner similar to the results of traditional observational original reports. An observational study conducted at a single institution and investigating the effect of an exposure or treatment on a disease must enroll all patients who are sequentially admitted to that hospital or service with a specific diagnosis. Similarly, the validity of a meta-analysis depends on the complete sampling of all the studies performed on a particular topic. Validity can be preserved if a representative sample is obtained, but any incomplete sample is a potentially biased one [87]. Unfortunately, meta-analysts may not be able to locate all published studies, because computerized data bases do not cover all periodicals, search algorithms often fail to identify relevant articles, and the indexing of studies is imperfect [88]. Even if the literature is optimally searched, studies published as government reports, book chapters, dissertations, conference proceedings, etc. Published trials differ systematically from unpublished ones, in that they are more likely to have a larger sample, and to have generated statistically significant results [89]. The systematic exclusion of small and negative studies from a meta-analysis that conditions eligibility on achievement of publication status is known as publication bias [90]. Multivariate analysis showed that the better odds of publication could not be explained by the quality of study design. On the contrary, there was a trend towards a greater number of statistically significant results with poorer quality studies [91]. Selection bias can arise not only during retrieval of studies from the literature, but also during assessment of the eligibility of the retrieved reports. In evaluating the quality of investigations, analysts may be influenced by knowledge of the study results or journal of publication. They may even be inclined to modify eligibility criteria, so as to include in the overview reports from prestigious journals. According to Felson [87], selection bias is the principal reason for discrepant results in meta-analyses. Different teams of analysts may base their conclusions on alternate sets of original reports, generating either statistically significant or null. This was also the explanation for the discrepant results between the meta-analysis [18] whose results are depicted in. Meta-Analyses of Studies of Diagnostic-Test Accuracy Development of new fields often requires the development of new methods [93]. These two quantities are interdependent, and they also depend on the cutoff point used in each study for judging the results of the test to be positive; sensitivity can be increased by decreasing the cutoff point and decreasing the specificity, or vice versa. Accordingly, methods for integrating the findings of these reports must address the interdependence between sensitivity and specificity, and the influence of the cutoff point used in each study on the corresponding estimate of accuracy. To meet the former objective, the estimates of sensitivity are not combined independently of the estimates of specificity, but the two components of accuracy Table 9. If this initial analysis shows that the accuracy of the laboratory test is constant within a range of 164 E. Statistical methods for integrating data on laboratory test accuracy have both been developed and are under development [94, 95]. D is a logodds ratio that measures how well the test discriminates between subjects with and without the disease. S is a measure of the threshold for classifying a test result to be positive, and it equals the sum of the logits. Fit a simple linear regression model using the quantities Di and Si from each study D=a+bS C. By employing this logarithmic transformation, it is possible to use a line to represent a curvilinear relationship. The intercept of the model (a) is the estimated logodds ratio when the accuracy of the test remains constant as the cutoff point varies from study to study. The regression coefficient or slope (b) provides an estimate of the extent to which the logodds ratio depends on the cutoff used. Also if b does not differ significantly from zero, the accuracy of the test does not depend on the particular cutoff point used in each study, and the accuracy of the test across the combined studies can be summarized by the logodds ratio given by the intercept a. The most important obstacle, however, to the use of meta-analysis for integrating results of studies of diagnostic-test accuracy are the suboptimal technical or scientific merits of the studies available for analysis. When the accuracy of an index laboratory test is investigated, an assumption is made that the employed "gold standard" can definitively discriminate between individuals with and without disease. Available tests with established diagnostic accuracy rarely meet the definition of a "gold standard"; however, those evaluating the diagnostic accuracy of new laboratory tests must strive to use the best available method for ascertaining the presence of disease in their study population. Ideally, all enrolled patients should undergo complete diagnostic work-ups without knowledge of the results of the laboratory test under evaluation. However, if the "gold standard" requires an invasive procedure, it may be desirable to restrict its use to a subset of the study population. This approach is acceptable only if the selection of patients for verification by the "gold standard" is random. If the patients who undergo the invasive procedure are selected based on abnormal results from other tests, or because 9 Meta-Analysis: A Statistical Method to Integrate Information Provided by Different Studies 167 they have risk factors for disease, etc. The accuracy of a laboratory test should be assessed in consecutive patients, or patients selected randomly for inclusion in the study, and all enrolled patients should be included in the analysis. No withdrawals of patients can be permitted following their inclusion in the study, because of equivocal test results or any other reason. The methods for carrying out the test under evaluation and the gold standard should be described in sufficient detail, and the cutoff point used for judging either test to be positive should be specified. Alternatively, if a single cutoff point is used, the clinical appropriateness of the chosen cutoff point should be discussed. The clinical setting in which the test is evaluated should be stated explicitly, and a description of the characteristics of the enrolled patients. When the available studies of the accuracy of a laboratory test differ in important study characteristics (such as the employed cutoff point or the disease prevalence in the included population), the diagnostic accuracy of the test should be assumed to differ from study to study, according to the varying characteristics of each study. Therefore, in such a situation, a random-effects method should be used to integrate the findings of the available studies. Random-effects methods that take into account the dependence of sensitivity and specificity on the cutoff point used in each study continue to be developed. Another impediment to the use of meta-analysis in pathology is that individuals included in studies of diagnostic-test accuracy are not allocated randomly by the investigators to have (or to not have) the disease of interest. The validity of statistical tests is guaranteed only if the allocation of subjects to comparison arms is random. Knowledge of this distribution is a prerequisite for assigning significance levels to any observed differences. If the allocation of subjects to groups is not random, the validity of tests of significance depends on additional assumptions about the comparability of the groups and the appropriateness of the statistical models. The effect of publication bias on studies of diagnostic-test accuracy is not as well researched, but many investigators suspect that the published studies of diagnostic-test accuracy are a biased subset that tends to overestimate the diagnostic accuracy of the test under evaluation. Furthermore, meta-analyses can be an important research tool for the systematic evaluation of the quality of published studies and for the disciplined investigation of reasons for disagreements among reports.

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The 25 and 100 ppm exposure groups were tested for 2 weeks prior to the onset of dichloromethane exposure antibiotics for uti how long buy cefixime 100mg mastercard. Starting at week 9 infection night sweats discount 100mg cefixime free shipping, mice exposed to 25 ppm dichloromethane exhibited increases in spontaneous activity infection 1 mind games buy cefixime 100mg without prescription, but no quantitative measurements or statistical analyses were reported antibiotic resistance global statistics generic cefixime 100 mg with amex. The authors stated that no significant effect was observed in the group exposed to 100 ppm antimicrobial laundry detergent effective cefixime 100 mg. Groups of rats (12/sex/exposure level) were exposed to 0 bacterial meningitis order cefixime 100mg with mastercard, 50, 200, or 2,000 ppm dichloromethane 6 hours/day, 5 days/week for 13 weeks. Then, the rat was placed in a clear plastic box to evaluate locomotor activity and then responsiveness to touch, E-16 sharp noise, and tail pinch. In a study by Alexeef and Kilgore (1983), a learning and memory evaluation was conducted following acute exposure to dichloromethane. Mice were exposed to 168 mg/L (~47,000 ppm) dichloromethane and were tested for learning ability by using a passive-avoidance conditioning task. In the passive avoidance task, mice were placed on a metal platform that extended into a hole. If the mouse went into the hole (a darkened area, which would be the preferred area for the mouse), it received a foot shock. Prior to the training session, mice were exposed to either air or ~47,000 ppm dichloromethane. Animals were exposed to dichloromethane until there was a loss of the righting reflex, which would take about 20 seconds on average, and then placed back in their home cage. One hour after exposure, animals were trained to learn the passive avoidance task. A mouse was considered to have learned the task once it remained on the platform for at least 30 seconds without entering the hole. Mice were then tested for recollection of the task at either 1, 2, or 4 days after the initial training session. In the learning phase of the task, 74% of the control mice retained the task in comparison to 59% of the dichloromethane-exposed group, indicating the significant effect of dichloromethane on learning. There was also an age-related effect since exposed 3-week-old mice were less likely to recall the task than 5- or 8-week-old mice. Dichloromethane at the exposure used in the study was demonstrated to be nonanalgesic, since pain-response times were comparable to those in air-exposed animals in the hot-plate pain test, and therefore, the results of the passive avoidance test were not confounded by potential analgesic effects. As a result, it is demonstrated that exposure to an acute and high concentration of dichloromethane alters learning ability in mice. The effect of dichloromethane on sensory stimuli was evaluated by measuring sensory-evoked responses during an acute exposure (Rebert et al. Twelve adult male rats were implanted with chronic E-17 epidural electrodes placed over the visual and somatosensory cortices. Each rat served as its own control, with a 1-week recovery period between testing sessions. In a subchronic exposure study, male and female F344 rats were exposed to dichloromethane 6 hours/day, 5 days/week for 13 weeks beginning at 16 weeks of age (Mattsson et al. For electrophysiological measures, rats were surgically implanted with epidural electrodes 10 weeks after the onset of exposure. However, it should be noted that all of the electrophysiological measures were conducted at least 65 hours after the last dichloromethane exposure. As a result, it can be concluded that a subchronic exposure to dichloromethane in adult rats did not result in persistent changes in any of the neurophysiological measures that were evaluated in this study. The potential for differential effects based on age (either in the young or at more advanced ages) was not examined in this study. The studies evaluating specific neurochemical changes in relation to dichloromethane exposure include studies of effects of short-term (3-day to 2-week) exposures (Fuxe et al. In the 1,000 ppm constant exposure group, acid proteinase activity was below the levels observed in control animals in the first week but increased to levels above control animals in the second week. Rats were exposed to 70, 300, and 1,000 ppm dichloromethane 6 hours/day for 3 consecutive days. Additional groups of rats were exposed to the same levels of dichloromethane and given intraperitoneal injections of the tyrosine hydroxylase inhibitor, -methyl-dl-p-tyrosine methyl ester (H44/68), 2 hours prior to sacrifice. Catecholamine levels were measured in the hypothalamus, frontal cortex, and caudate nucleus among other brain regions. In the medial part of the caudate nucleus, which is involved in memory processes, catecholamine levels were significantly higher (12%) in the 70 ppm group but significantly lower in the 300 ppm (1%) and 1,000 ppm (8%) groups compared with controls. The impact of dichloromethane was also evaluated on the hypothalamic-pituitary gonadal axis. The hypothalamus regulates secretion of reproductive hormones, such as follicle-stimulating hormone and luteinizing hormone. However, when rats were dosed concurrently with H44/68 and dichloromethane, statistically significant, inversely dose-related increases in luteinizing hormone levels were observed (330, 233, and 172% higher than controls in the 70, 300, and 1,000 ppm groups, respectively). Overall, the study demonstrates significant changes in catecholamine levels in the hypothalamus and caudate nucleus. No significant changes in catecholamine levels in the frontal cortex were reported. Catecholamine level changes in the hypothalamus did not appear to significantly affect hormone release; however, decreased catecholamine levels in the caudate nucleus at higher exposures may lead to memory and learning impairment. E-19 A series of studies were conducted in male and female Mongolian gerbils exposed continuously to 210 (Karlsson et al. High mortality rates occurred at 350 (6/10 males and 3/10 females by 71 days) and 700 ppm (10/10 males and 9/10 females by 52 days). Increased astroglial proteins were found in the frontal and sensory motor cerebral cortex, which directly correlated to the astrogliosis that was observed in those areas. After the solvent-free exposure period, brains were removed and the olfactory bulbs and cerebral cortices were dissected. Brain weights and weights of the dissected brain regions were the same between control and dichloromethane-exposed animals. The total protein concentration per wet weight was not significantly different between dichloromethane-exposed and control animals. In a companion paper, in which only the 210 ppm level was tested, it was found that exposure to dichloromethane decreased the levels of glutamate, -aminobutyric acid, and phosphoethanolamine in the frontal cortex, while glutamine and -aminobutyric acid were increased in the posterior cerebellar vermis (Briving et al. The gerbils did not have a solvent-free exposure period as in the other two studies (Karlsson et al. Neurological changes have been investigated by measuring changes in neurotransmitter levels and changes in neurotransmitter localization. Changes in catecholamine levels in the caudate nucleus after an acute exposure (Fuxe et al. Additionally, changes in the hippocampus also suggest memory effects after a long-term, continual exposure to dichloromethane, although no conclusive evidence has been presented to date. Noted neurobehavioral effects that may be linked to impaired cerebellar function include changes in motor activity and impaired neuromuscular function (Moser et al. Liver Tumor Characterization Studies Several studies have examined the time course of appearance of liver tumors in B6C3F1 mice exposed to 2,000 or 4,000 ppm and possible links between hepatic nonneoplastic cytotoxicity, enhanced hepatic cell proliferation, and the development of liver tumors (Casanova et al. The studies provide no clear evidence for a sustained liver cell proliferation response to dichloromethane that can be linked to the development of dichloromethane-induced liver tumors. Additionally, a few studies have examined if dichloromethane-induced liver tumors are the result of proto-oncogene activation and tumor suppressor gene inactivation (Maronpot et al. The six stop-exposure protocols were 26 weeks of exposure followed by 78 weeks without exposure, 78 weeks without exposure followed by 26 weeks of exposure, 52 weeks without exposure followed by 52 weeks with exposure, 52 weeks of exposure followed by 52 weeks without exposure, 78 weeks of exposure followed by 26 weeks without exposure, and 26 weeks without exposure followed by 78 weeks of exposure. A control group (no exposure, 104 weeks duration) and a maximum exposure (104 weeks duration) group were also included. Exposure for 26 weeks did not result in an increased incidence of liver tumors (adenomas or carcinomas). Respective percentages of animals with liver tumors were 27 (18/67), 40 (27/67), and 34% (23/67) for the controls, early 26-week exposure, and late 26-week exposure groups, respectively. Exposure to 2,000 ppm for 52 weeks (followed by no exposure until 104 weeks), 78 weeks (either early or late exposure periods), or 104 weeks produced increased incidences of mice with liver tumors (p < 0. Respective percentages of animals with liver tumors (adenomas and carcinomas combined) were 44 (28/64), 31 (21/67), 62 (42/68), 48 (32/67), and 69% (47/68) for the 52-(early exposure), 52-(late exposure), 78-(early exposure), 78-(late exposure), and 104-week exposure periods, respectively. With the 78-week exposures, the difference in the liver tumor incidence between the early and late exposure periods was statistically significant (p < 0. Histopathologic examination of liver tissue at interim killings at eight time periods (13, 26, 52, 68, 75, 78, 83, or 91 weeks) of exposure to 2,000 ppm (n = 20 mice per killing) found no evidence of nonneoplastic cytotoxicity that preceded the appearance of proliferative neoplastic liver lesions. Incidences of mice with liver adenomas or carcinomas were elevated (between 40 and 60%) at five of the six interim killings after 52 weeks. The incidence rates at each time period were 0/20 (0%) at 13 weeks, 1/20 (5%) at 26 weeks, 8/20 (40%) at 52 weeks, 4/26 (15%) at 68 weeks, 13/20 (65%) at 75 weeks, 12/19 (63%) at 78 weeks, 8/20 (40%) at 83 weeks, and 20/30 (66%) at 91 weeks. The collected liver lesion data identify no exposure-related increased incidence of nonneoplastic liver lesions that could be temporally linked to liver tumor development. Liver tumors first appeared at about the same time in control and exposed animals (52 weeks). To label liver cells in S-phase, tritiated thymidine (1- to 4-week exposure protocols) or bromodeoxyuridine (13- to 78-week protocols) was administered subcutaneously via an osmotic mini-pump for 6 days prior to killing. Labeled hepatocytes in liver sections (from 10 mice in each exposure/duration group) were counted to assess the number of cells in S-phase per 1,000 cells. S-phase labeling indices in livers of exposed mice at most killings were equivalent to or less than those in control mice. A transient increase in S-phase labeling index of about two- to fivefold over controls was observed at the 2-week killing of mice exposed to 1,000, 4,000, or 8,000 ppm. Because of the transient nature and small magnitude of the response, it is not expected to be of significance to the promotion of liver tumors in chronically exposed mice. S-phase labeling was accomplished by immunohistologic staining for proliferating cell nuclear antigen in liver sections from 24 control mice and 15 exposed mice, with livers showing foci of cellular alteration. In both control and exposed livers, the labeling index was about four- to fivefold higher in foci of cellular alteration than in surrounding unaffected liver tissue. Adenoma and focus of alteration were first detected at 26 weeks (2/10 versus 0/10 in controls). At 52 weeks, 4/10 exposed mice had proliferative lesions (one focus, one adenoma, and two carcinomas), compared with 1/10 in controls (one adenoma). At 78 weeks, 7/10 exposed mice had proliferative lesions (two foci, three adenomas, six carcinomas) compared with 1/10 in controls (one adenoma). In summary, the results indicate that inhalation exposure to 2,000 ppm dichloromethane produced an increased incidence of liver tumors in female B6C3F1 mice. No evidence was found for sustained cell proliferation or liver tissue degeneration in response to dichloromethane exposure, but exposure was associated with relative liver weight increases and hepatocellular hypertrophy. Three or four groups of three mice were exposed to 146, 498, 1,553, or 3,923 ppm unlabeled dichloromethane for 2 days and then exposed to [14C]-labeled dichloromethane for 6 hours on the third day. In the six "stop-exposure" protocol experiments (described in the previous discussion of liver tumor characterization studies), early but not late exposure for 26 or 52 weeks resulted in an increased incidence of animals with lung tumors (adenoma or carcinomas). With the 78-week exposures, both the early and late exposure regimens produced an increased incidence of lung tumors compared with controls (56 [38/68] and 19% [13/68], respectively), compared with the incidence of 63% (42/67) seen in the group exposed for the full 104 weeks. Thus, a plateauing of risk was seen, with similar incidence rates seen with the early 52-week, early 78-week, and 104-week exposure periods. The difference in the lung tumor incidence between the early and late exposure periods of similar duration was statistically significant (p < 0. A greater increase in multiplicity of lung tumors was also seen with the early 78-week exposure period. As with the liver tumor data from the same series of experiments, these data suggest that early exposure was more effective than late exposure and that the increased risk continued after cessation of exposure. Histopathologic examination of lung tissue from mice killed at 13, 26, 52, 68, 75, 78, 83, or 91 weeks of exposure to 2,000 ppm (n = 20 mice per killing) found no evidence of nonneoplastic cytotoxicity that preceded the appearance of proliferative neoplastic lung lesions. In contrast, incidences of mice with lung adenomas or carcinomas (combined) were elevated at interim killings 52 weeks; incidences for the interim killings of mice exposed to 2,000 ppm (6 hours/day, 5 days/week) between 13 and 91 weeks were 0/20 (0%) at 13 weeks, 0/20 (0%) at 26 weeks, 6/20 (30%) at 52 weeks, 6/26 (23%) at 68 weeks, 8/20 (40%) at 75 weeks, 9/19 (47%) at 78 weeks, 10/20 (50%) at 83 weeks, and 14/30 (47%) at 91 weeks. Lung hyperplasia was found at an increased incidence only at 91 weeks, well after the 26- and 52-week periods that induced increased incidences of mice with lung tumors. There were no exposure-related histopathologic or labeling index changes in the alveoli, but lower labeling indices were found in the bronchiolar epithelium of exposed mice compared with controls. In hamsters that did not develop tumors in response to chronic inhalation exposure to 3,500 ppm dichloromethane (Burek et al. To measure cell proliferation, mice (n = 5 per exposure-duration group) were given subcutaneous doses of tritiated thymidine for 5 consecutive days prior to killing. Labeled cells in bronchiolar or alveolar epithelium in lung sections were counted to assess the number of cells in S-phase per 1,000 cells. Counts of bronchiolar epithelium cells in S-phase in exposed mice sacrificed on days 2, 5, 8, and 9 were approximately 2-, 15-, 3-, and 5-fold higher, respectively, than those of E-25 unexposed mice at day 0 of the experiment. In exposed mice sacrificed on days 89, 92, and 93, less than twofold increases in bronchiolar epithelium cell labeling were observed. Increased cell labeling was found in alveolar epithelium only on day 8 (about seven- to eightfold increase) and day 9 (about fourfold increase). Vacuolation of the Clara cells of the bronchiolar epithelium was observed on day 2 (scored as ++, majority of cells affected), day 9 (+++, virtually all the cells affected), and day 44 (+, moderate effect to cells) but was not apparent on days 5, 8, 40, 43, 89, 92, or 93. The appearance and disappearance of the Clara cell vacuolation was generally correlated with the appearance and disappearance of enhanced cell proliferation in the bronchiolar epithelium; enhanced cell proliferation was observed on days 2, 5, 8, and 9 (along with appearance of Clara cell vacuolation on days 2 and 9) but was not observed on days 89, 92, and 93 when Clara cell lesions also were not observed. This suggests that cell proliferation was enhanced in response to Clara cell damage but was not sustained with repeated exposure to dichloromethane.

Several studies were designed to evaluate the genotoxicity of selected glyphosate formulations in vivo; similar to findings from in vivo studies using glyphosate technical antibiotics gas dogs order genuine cefixime on-line, mixed results were obtained from in vivo exposure to glyphosate-containing products homeopathic antibiotics for sinus infection buy cefixime. Roundup induced mutations in Drosophila in a sexlinked recessive lethal mutation assay (Kale et al infection control today purchase genuine cefixime online. The potential for Roundup to induce chromosomal aberrations and/or micronuclei in bone marrow cells has been assessed in several studies in which the test chemical was administered to mice via intraperitoneal injection bacteria in florida waters generic 100mg cefixime overnight delivery. Although intraperitoneal administration of Roundup at 25 and 50 mg/kg resulted in significantly increased frequencies of chromosomal aberrations and micronuclei antimicrobial agents antibiotics generic cefixime 100 mg without a prescription, both doses appeared to be cytotoxic global antibiotic resistance journal purchase 100mg cefixime fast delivery, as indicated by time- and dose-related significant decreases in mitotic indices (Prasad et al. Roundup induced micronuclei in bone marrow from mice administered the chemical via intraperitoneal injection at 300 mg/kg (expressed as glyphosate) (Bolognesi et al. Negative results were reported in two other studies that evaluated micronucleus induction in bone marrow cells from mice treated by intraperitoneal injection of Roundup (Grisolia 2002; Rank et al. In the study of Grisolia (2002), polyoxyethylene amine surfactant accounted for 12% of the formulation. However, comparison of results across available studies was precluded due to lack of information regarding the composition of the various formulations tested. Many agencies, organizations, and/or expert panels have reviewed available genotoxicity data and concluded that the data do not support a genotoxicity role for glyphosate, at least at concentrations relevant to human exposure. For more detailed information regarding genotoxicity evaluations and conclusions of these agencies, organizations, and/or expert panels, consult corresponding references. The action of glyphosate on the shikimate pathway is not of direct human concern because this pathway does not exist in mammals. However, animal exposures to glyphosate could impact the shikimate pathway of gut bacteria, thereby affecting the gut microbiome (Aitbali et al. Some transgenic plants have been genetically altered to express N-acetyltransferase proteins. Although glyphosate is generally considered to be of relatively low toxicity to mammals, the following mechanisms of action have been proposed: Hepatotoxicity. Glyphosate treatment also resulted in an approximately 2-fold increase in glyoxylate. Because glyoxylate is formed endogenously, the increase in glyoxylate level in the liver may be a result of glyphosate acting on mechanisms responsible for endogenous production of glyoxylate. The study authors demonstrated that glyoxylate inhibited liver fatty acid oxidation enzymes in mice and that glyphosate treatment increased triglycerides and cholesteryl esters, which was considered a likely result of the diversion of fatty acids toward lipid pathways other than oxidation. An in vitro assessment of Roundup cytotoxicity on human L-02 hepatocytes determined that exposure induced structural and morphological changes in cell membranes, mitochondria and nuclei, in addition to cell shrinkage, nuclear fragmentation, and mitochondrial vacuolar degenerations (Luo et al. Study authors determined that the Roundupinduced overproduction of reactive oxygen species led to oxidative stress responses affecting normal cell function. The study authors noted that the increases in cystatin C and interleukin-18 suggest that glyphosate-based formulations might induce apoptosis and mitochondrial toxicity. Those rats administered glyphosate-based formulation were the only ones to exhibit severe histopathologic kidney lesions. The study authors suggested that these results did not support a nephrotoxic role for glyphosate alone. George and Shukla (2013) examined whether the mechanism of action for glyphosate and its potentially tumor-promoting properties could be elucidated; previously the research group found glyphosate to cause tumor promotion in mouse skin carcinogenesis (George et al. In an in-vitro model, human skin keratinocyte, or HaCaT cells, were exposed to up to 1 mM of glyphosate for 72 hours. Taken together, glyphosate-based formulations, and comparatively to a lesser degree, glyphosate, are implicated in generating oxidative damage, which in turn may lead to dermal toxicity. The study authors suggested that exposure to Roundup might lead to excessive extracellular glutamate levels and resulting glutamate excitotoxicity and oxidative stress in rat hippocampus. The study used a range of concentrations similar to levels found in patients and occupational exposures. Glyphosate permeated across the blood brain barrier via a transcellular mechanism. Subsequently, neuronal cell metabolic activity and glucose uptake in brain microvascular endothelial cells was observed. Study authors suggest that exposure to glyphosate may lead to increased blood brain barrier permeability and alteration of glucose metabolism resulting in neurological damage. Granulosa cell proliferation and estradiol production were impaired, but no effects were observed on theca cell proliferation or steroidogenesis. The results suggest that glyphosate may affect the reproductive system in cattle via direct action on ovarian function. Genes related to oxidative-stress (cat, sod2, gpx) were found expressed at greater levels than the control group; on the other hand, expression of apoptosis related genes including Bcl-2 (inhibits apoptosis) decreased, while Bax (pro-apoptosis gene), increased. These formulations induced dose-dependent cell death, and induced cell mitochondrial dysfunction, lipid droplet accumulation, and disruption of cell detoxification systems. Additionally, the penetration and accumulation of glyphosate formulants in cells led to cell death. Absorbed glyphosate is readily distributed via the blood, but does not accumulate in any particular organ or tissue. Approximately two-thirds of an oral dose of glyphosate is excreted in the feces as unabsorbed parent compound. Observations of increased urinary glyphosate levels among 48 farmer-applicators following application of glyphosatecontaining products is evidence that inhaled glyphosate can be absorbed (Acquavella et al. However, dermal absorption was likely involved in some cases because mean urinary glyphosate was higher among those farmers (14/48) who did not use rubber gloves. Detectable levels of urinary glyphosate were also measured in children of the farmers who were present during mixing, loading, or application of the herbicide; exposures among the children may have involved inhalation and/or dermal routes. No information was located regarding the toxicokinetics of inhaled glyphosate in laboratory animals. Numerous reports of systemic effects following intentional or unintentional ingestion of glyphosatecontaining products serve as additional evidence that ingested glyphosate is absorbed. Several groups of investigators have evaluated the absorption of glyphosate following oral exposure in laboratory animals, particularly rats. Results from comparative studies of oral, intravenous, and intraperitoneal administration of glyphosate indicated that urinary radioactivity represented the amount of glyphosate absorbed and fecal radioactivity represented the amount of unabsorbed glyphosate following oral exposure. Although quantitative data were not included in the study report, the study authors estimated that 30% of the 5. In another study, male Sprague-Dawley rats received a single gavage dose of 12C- and 14 C-glyphosate at 10 mg/kg (Brewster et al. Increased urinary glyphosate levels among 48 farmer-applicators following application of glyphosatecontaining products is evidence that glyphosate can be absorbed (Acquavella et al. In vitro studies using human skin samples indicate that dermal penetration of glyphosate is very low. Twelve-hour in vivo application of the test substance diluted 1:29 with water at concentrations of 25 or 270 g/cm2 resulted in 7-day recovery of 0. An in vitro study using rat skin membranes, applied glyphosate formulations, concentration and field diluted, for 8 hours at concentrations of 6. The highest radioactivity level was found in the small intestine, reaching a peak level of approximately 10% of the administered dose at 6 hours postdosing; radioactivity in the large intestine peaked at approximately 1. Liver, kidney, skin, and blood each accounted for <1% of the administered dose at each time point. By 24 hours postdosing, <1% of the administered dose remained in all tissues combined. The tissue to blood ratio for bone increased with time suggesting a slower elimination from bone compared to blood. The observation of radioactivity in urine and feces collected from rhesus monkeys following dermal application of a 14C-labeled Roundup formulation is demonstration of systemic distribution following dermal absorption (Wester et al. However, at sacrifice 7 days posttreatment, no radioactivity was detected in spleen, ovaries, kidney, brain, abdominal fat, bone marrow, upper spinal column, or central nervous system fluid. Radioactivity measured in bone marrow samples taken 30 minutes postinjection amounted to approximately 0. Total urinary excretion of glyphosate and its metabolite during 4 days postingestion was 3. Following a single gavage dose of administered radiolabeled glyphosate (>99% purity) to SpragueDawley rats, expired air accounted for <0. In addition to its potential role in glyphosate metabolism, gut microflora can also be impacted by exposure to glyphosate and glyphosate-based herbicides. Though the shikimate pathway is absent in mammals, the shikimate pathway in animal gut microbes synthesizes amino acids (Aitbali et al. Rodents orally exposed to doses of glyphosate-based herbicides ranging from 5 to 500 mg/kg/d showed a significant decrease in bacteria count and changes in community composition (Aitbali et al. A study using fecal samples from Roundup-exposed Sprague-Dawley rats also found changes in bacterial community composition (Lozano et al. Decreases in bacteria count were also observed in rodents orally exposed to 5 mg/kg/d of glyphosate technical (Aitbali et al. However, fecal samples from Sprague-Dawley rats orally exposed to doses of glyphosate or Glyfonova found that while minimal changes in bacteria composition were observed, exposure to the glyphosate formulation appeared to have a more pronounced effect than exposure to glyphosate technical (Nielsen et al. While the implications of alterations in the gut microbiome are unclear, some animal studies suggest neurologic and behavioral changes (Aitbali et al. In one study, urinary glyphosate levels were evaluated in 48 farmer-applicators prior to application of glyphosate-containing products, immediately following application, and for 3 days thereafter (Acquavella et al. Urinary glyphosate was detectable in 15% (7/47) of the farmers prior to application, in 60% (29/48) of the farmers immediately following application, and in only 27% (13/48) of the farmers on postapplication day 3. No information was located regarding elimination or excretion following inhalation exposure of laboratory animals to glyphosate. Glyphosate has been detected in feces and urine of individuals who intentionally or accidentally ingested relatively large amounts of glyphosate. Results from animal studies identify the feces and urine as major routes of elimination following oral exposure to glyphosate. For example, among male and female Sprague-Dawley rats administered 14 C-glyphosate (99% purity) via a single gavage dose at 10 mg/kg, during 7 days posttreatment, radioactivity recovered in the feces averaged 62. There were no significant differences in fecal and urinary excretion among rats dosed with unlabeled glyphosate for 14 days followed by a single oral dose of radiolabeled glyphosate. In male F344/N rats administered a single gavage dose of 14C-glyphosate (purity 99%) in distilled water at 5. Very little ingested glyphosate is eliminated via routes other than feces and urine. Among SpragueDawley rats administered radiolabeled glyphosate (>99% purity) by a single gavage dose, <0. However, in a study that evaluated urinary glyphosate levels in 48 farmerapplicators involved in application of glyphosate-containing products, mean urinary glyphosate was higher among those farmers (14/48) who did not use rubber gloves, indicating that some glyphosate had been absorbed through the skin (Acquavella et al. Twelve-hour application of the test substance at concentrations of 25 or 270 g/cm2 resulted in 7-day recovery of 0. Assuming first-order kinetics, the half-life of elimination from the bone marrow was estimated at 7. A half-life for elimination of radioactivity from plasma was approximately 1 hour for both sexes. These results indicate that glyphosate reaching the blood was rapidly eliminated and that the small fraction reaching bone marrow was rapidly eliminated. Potential effects on offspring resulting from exposures of parental germ cells are considered, as well as any indirect effects on the fetus and neonate resulting from maternal exposure during gestation and lactation. Children may be more or less susceptible than adults to health effects from exposure to hazardous substances and the relationship may change with developmental age. A susceptible population may exhibit different or enhanced responses to certain chemicals than most persons exposed to the same level of these chemicals in the environment. Factors involved with increased susceptibility may include genetic makeup, age, health and nutritional status, and exposure to other toxic substances. These parameters can reduce detoxification or excretion or compromise organ function. Limited information was located regarding possible age- or gender-related differences in susceptibility to toxic effects from glyphosate technical or glyphosate formulations. Microbiome profiling of the gut resulted in significant changes in overall bacterial composition in the pups only (particularly apparent prior to puberty); this effect was noted for glyphosate and for Roundup Bioflow. The preferred biomarkers of exposure are generally the substance itself, substance-specific metabolites in readily obtainable body fluid(s), or excreta.

Since gavage exposures give a brief but high body burden for the same total dose compared to an exposure regimen that spreads out the exposure over a period of hours (inhalation specifically) antibiotic resistance in bacteria buy generic cefixime pills, even at the same total dose in the same species treatment for dog's broken toenail cheap cefixime 100 mg on line, one may see saturation from the oral exposure but not in the time-distributed exposure infection quality control staff in a sterilization order 100 mg cefixime otc. In contrast bacteria bacillus cheap 100mg cefixime with visa, when increasing the dose from 1 to 50 mg/kg dichloromethane antibiotics for uti during pregnancy order 100mg cefixime, more than an order of magnitude lower than the dose used by Pankow et al antibiotics for uti safe for breastfeeding buy cefixime 100 mg with mastercard. If a metabolite had an effect on an enzyme activity, one would expect that effect to be time-dependent: as more metabolite is produced (over the minutes and hours after the beginning of an exposure), metabolite-induced inhibition would lead to a decrease in enzyme activity, and hence a decrease in the rate constant (k) or Vmax. The model assumes that these constants are not time-dependent, however, and for the most part, appears to be consistent with the toxicokinetic data. In short, if there was a strong time-dependence (due to inhibition) in the rate constants, the model would not fit as well as it does. That the models can describe those data well without explicitly including time-dependent inhibition suggests that the impact of such inhibition is not significant. An additional point to consider is that as long as the model accurately describes the shift in metabolism between the two pathways, the specific mechanism by which the shift occurs. At the in vivo dichloromethane concentrations, the high Km observed by Reitz et al. Therefore, the potential impact of formaldehyde on either pathway cannot be evaluated. Because the metric is a rate of metabolism, and the clearance of metabolites is generally expected to be slower in the human compared with the rat (assuming clearance scales as body weight0. Are the uncertainties in the dose metric selection and calculations appropriately considered and discussed Comments: Four reviewers noted agreement with the choice of the dose metric (one indicating the choice the the justification for the choice was limited, however), and one reviewer did not comment directly on these questions. Two other reviewers did not comment on this question because it was outside their area of expertise. Comments: Three reviewers raised questions regarding the use of the toxicokinetic scaling factor to account for potential differences between the rat and the human in the rate of clearance of metabolites. The reviewers agreed on the underlying foundation for the use of the scaling factor. The reviewers disagreed, however, on the optimal approach for addressing this uncertainty, as described below. Response: this issue concerns a specific mechanism-metabolic clearance-for which there is information on animal-human differences. In contrast, the more "highly desirable" metric, tissue metabolite concentration, is not a metric that can be feasibly estimated and used. In individuals with lower metabolism, the parent dichloromethane concentration will be higher at a given level of A-7 exposure compared with those with higher metabolism. Since the mode of action is that dichloromethane is metabolically activated, higher risk is expected for populations with higher metabolism. Hence, parent concentration is inversely correlated with risk, so use of the parent concentration has poor relevance to the mode of action. Allometric scaling is commonly used because it represents the expected, or most likely, variation in metabolic clearance across species. Therefore, the use of the rate of metabolism metric with the scaling factor is believed to have the lowest uncertainty. This reviewer also indicated a high degree of uncertainty in the model due to the lack of data on metabolite kinetics, which otherwise could be used to validate or calibrate the scaling factor used. A-8 Response: Lindstedt and Schaeffer (2002) reviewed the use of allometry for anatomical and physiological parameters. Overall metabolic rates were assessed by the metric of resting oxygen uptake and found to vary with an exponent of 0. When the regression was performed with data from only mice, rats, dogs, and humans, the exponent obtained was 0. That this scaling captures observed mouse:human differences in dichloromethane metabolism is reflected by the fact that the mean VmaxC obtained for the mouse by Marino et al. The magnitude of the scaling factor would increase if an exponent value less than 0. Mahmood and Sahajwalla (2002), cited by the one reviewer, estimated scaling coefficient values for biliary clearance of 8 drugs. Tang and Mayersohn (2005) evaluated total clearance data for a much larger set of compounds, 61, for which coefficient values ranged from 0. The range of these A-9 results indicates the possible range of coefficient values and hence uncertainty in the scaling for clearance of dichloromethane metabolism. Given that the mean coefficient value obtained for the Tang and Mayersohn (2005) data set was 0. Relative to the lowest coefficient value reported by Tang and Mayersohn (2005), 0. The results for a range pharmaceutical compounds is in agreement with the comment that the lack of data to evaluate or calibrate clearance of the metabolite creates a potentially large uncertainty in model predictions. Are the model assumptions and parameters clearly presented and scientifically supported Two reviewers did not comment on this question because it was outside their area of expertise. Table 3-5 provides a comparison of parameters used in the previous assessment and those used in the current mouse model. To account for potential clearance rate differences, the mouse internal dose metric was adjusted by dividing by a toxicokinetic scaling factor to obtain a humanequivalent internal dose. Are the choices of dose metric and toxicokinetic scaling factor appropriate and scientifically supported Comments: One reviewer stated that the use of the scaling factor was appropriate and clearly explained. Four reviewers did not provide comments in response to this charge question (two of these noting that it was outside their area of expertise). One reviewer noted that "the application of the toxicokinetic scaling as done would be appropriate when the chemical entity (metabolite) itself is the active moiety (which is the case), further metabolism/reaction renders it inactive (which is likely the case), and the rate of the metabolism/reaction process is proportional to the liver perfusion rate, cardiac output or to the body surface (which is not known to be the case). Response: As noted by the reviewer, the first two elements justifying the use of the scaling factor are met. With respect to the third element, it is not known that the rate of reaction is proportional to the liver perfusion rate, cardiac output, or body surface area. It is also important to note that it is not known that the rate of reaction is not proportional to these factors. Comments: One reviewer raised two questions about the extrapolation of the animal results to humans. The other issue concerns target tissue concordance and the potential relevance to the observation of leukemia and other types of cancers that were not observed in mice. This reviewer noted the uncertainties arising from these issues as another justification for the use of the scaling factor, and suggested that additional discussion of the potential underestimation of exposure to reactive metabolites should be added. The 1st percentile of these distributions was selected to represent the most sensitive portion of the population. This distribution of human internal doses was used with the tumor risk factor to generate a distribution of oral slope factors or inhalation unit risks. Response: Below ~20% of the Km (which has units of concentration), the rate of reaction becomes indistinguishable from a first-order reaction, as it depends on the probability that a substrate molecule collides with an unoccupied active site on the enzyme. Thus, at low A-12 concentrations ([Substrate] << Km) the rate of enzyme-catalyzed reactions becomes proportional to the concentration of the substrate(s) and enzyme. This procedure explicitly accounts for variability that results from these known factors that influence toxicokinetics and dosimetry and so allows for the generation of dosimetric distributions based on population variability. However, one must then select a point on the dosimetric distribution corresponding to a portion or percentile of the population one effectively wishes to protect. The first percentile of the distribution was selected for derivation of the RfD and RfC as a low but non-zero population percentile that can be estimated by computational statistical sampling in a reasonable amount of time. This reviewer then asked for clarification regarding the assumption of higher human responsiveness as discussed in the justification of the A-13 use of the scaling factor in the 1987 dichloromethane assessment, and differences between this assumption and the use of the scaling factor in the current assessment. Response: the explanation of what was done in the 1987 dichloromethane assessment was clarified in Section 3. For cancer, it is assumed that given the same average tissue concentration of active metabolite, humans would have the same average cancer risk as rodents. Because metabolism and other clearance mechanisms (blood perfusion, respiration, renal filtration) are all expected to be about sevenfold slower in a 70-kg human than a 30-g mouse, the second term (relative metabolite clearance), which is in the denominator, is assumed to be 1/7 (one over the toxicokinetic scaling factor). In the 1987 assessment, the scaling factor was applied to adjust for both interspecies differences in processes that lead to differences in internal doses. Does the set of model parameter distributions adequately account for population variability and parameter uncertainty in estimating human equivalent doses Are the human parameter values and distributions clearly presented and scientifically supported Comments: One reviewer considered the development and inclusion of the parameter distributions that reflected both parameter uncertainty and interindividual variation to be an important addition to the earlier published version of this model, and that these distributions and their development were clearly explained and scientifically justified. This reviewer specifically noted support for the use of the data from Lipscomb et al. Two reviewers did not comment on this charge question because it was outside their area of expertise. Protein activity is not necessarily proportional to protein levels, and protein levels are more difficult to quantify accurately. Comments: One reviewer asked how the mass balance of the flows and volumes was ensured during the Monte Carlo iterations. Response: As indicated in the last column of Table B-3, after each set of Monte Carlo samples for fractional blood flows; for example, the sampled values were divided by the sum of the sampled values, so that the sum of the resulting fractions equal one. Noncancer Toxicity of Dichloromethane Oral reference dose (RfD) for dichloromethane B1. A chronic RfD for dichloromethane has been derived from a 2-year oral (drinking water) study in the rat (Serota et al. Please comment on whether the selection of this study as the principal study is scientifically supported and clearly described. One reviewer also suggested that the choice of the principal study would be strengthened by inclusion of a graphical presentation of the different endpoints based on internal dose metrics. An increase in the incidence of liver lesions (foci/areas of alteration) was selected as the critical effect for the RfD. Please comment on whether the selection of this critical effect is scientifically supported and clearly described. Comments: Six reviewers supported the selection of liver lesions (foci/areas of alteration) as the critical effect for the RfD. One of these reviewers reiterated the idea of presenting an exposure response array based on internal dose metrics to strengthen the selection of the critical effect. Response: A response that addresses the recommendation for an exposure response array based on internal dose metrics is provided under RfD Charge Question B1. One of the reviewer who agreed with the modeling noted the approach and several assumptions result in a "conservative" RfD. One reviewer disagreed with applying a toxicokinetic scaling factor to the internal dose. This reviewer also suggested that it would be useful to show alternative RfDs based on other dose metrics. A 10% extra risk of increased foci/areas of alterations was applied under the A-18 assumption that it represents a minimal biologically significant degree of change. Response: There are currently no mechanistic data to support or derive a biologically-based model or to inform the model selection from among the available empirical models. The interspecies scaling factor accounts for some of the uncertainty in overall dichloromethane metabolism. A chronic RfC for dichloromethane has been derived from a 2-year inhalation bioassay in rats (Nitschke et al. Please identify and provide the rationale for any other studies that should be selected as the principal study. One reviewer suggested that a graphical display of endpoint data based on internal dose metrics would strengthen the choice of the principal study. Response: A response that addresses the critical effect (hepatic vacuolization) is provided under RfC Charge Question B6. A response that addresses the recommendation for an exposure response array based on internal dose metrics is provided under RfD Charge Question B1. Comments: Two reviewers noted the value of the findings from epidemiological studies of neurological effects in workers exposed to dichloromethane as supportive data for the RfC derived from the animal data. An increase in the incidence of hepatic vacuolation was selected as the critical effect for the RfC. Please identify and provide the rationale for any other endpoints that should be selected as the critical effect. Comments: Five reviewers supported the selection of hepatic vacuolation as the critical effect for the RfC. One reviewer questioned the biological significance of hepatic vacuolation as the critical effect, noting that hepatic vacuolation appeared to be a high-dose effect in female rats only, was incompletely reported in the male rat, and had no human correlate. This reviewer suggested that these limitations should be noted in the Toxicological Review. Response: A discussion of biological relevance of hepatic vacuolation was added to the discussion of the selection of the critical effect in Section 5. In addition, a discussion of the dose-response pattern seen in the Nitschke et al. Three reviewers reiterated comments that had also been offered in response to other charge questions. One reviewer questioned the use of the first percentile human equivalent in the RfC derivation, and one reviewer questioned the use of a toxicokinetic scaling factor. However, this analysis does not account for potential concerns of neurodevelopmental toxicity associated with the parent compound or possibly other metabolites. Dichloromethane exposure is known to produce neurotoxicity in humans and adult animals (see Sections 4. The parent compound can pass through the placental barrier (Withey and Karpinski, 1985; Anders and Sunram, 1982). Increased risk of pulmonary infectious diseases, particularly bronchitis-related mortality, is also suggested by some of the cohort studies of exposed workers (Radican et al. A-25 Response: A response to this comment is provided under RfD Charge Question B4.

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