Examining Race-Related Error in Two-Compartment Models of Body Composition Assessment: A Systematic Review and Meta-Analysis.

BACKGROUND: The Brozek and Siri formulas estimate relative adiposity (%Fat) from total body density (Db) using a 2-compartment (2C) model. Racial/ethnic differences in Db have been reported, along with subsequent errors in estimated %Fat. OBJECTIVE: The primary aim of this systematic review and meta-analysis was to examine potential race/ethnic differences in the accuracy of the Brozek and Siri 2C formulas using aggregate-level data. METHODS: Peer-reviewed studies available in English that provided 2C and 4C estimates of %Fat were located using searches of the PubMed (n = 150), Scopus (n = 170), and Web of Science (n = 138) online electronic databases. Random-effects models were used to determine potential differences between racial groups using a mean ES and 95% confidence intervals. RESULTS: The cumulative results from 78 effects indicate that the relative accuracy of the Brozek equation did not vary between racial groups (between group p = 0.053). In contrast, the Siri equation slightly underestimated %Fat for Asian adults (ESWMD = -1.40%, 95%CI -2.33% to -0.46%; p = 0.004) and Black adults (ESWMD = -1.10%, 95%CI -2.11% to -0.08%; p = 0.034), with no significant differences observed in Hispanic adults (ESWMD = 0.64%, 95%CI -1.02% to 2.31%; p = 0.448) and White adults (ESWMD = 0.08%, 95%CI -0.42% to 0.57%; p = 0.766) (between group p = 0.019). CONCLUSION: Small, but statistically significant, error was found between racial groups when estimating %Fat using the 2C Siri equation when compared to 4C models. However, the observed error due to race/ethnicity appears to be of little clinical or practical significance when using either equation.

Using ultrafiltration to concentrate and detect Bacillus anthracis, Bacillus atrophaeus subspecies globigii, and Cryptosporidium parvum in 100-liter water samples.

A strategy that uses ultrafiltration (UF) to concentrate microorganisms from water samples has been developed and tested. This strategy was tested using 100-liter water samples with volume reduction achieved through ultrafiltration and recycling the microorganisms of interest through a retentate vessel, rather than returning them to the sample container, where they might pose an incremental hazard to sample takers or the environment. Three protocols based on this strategy were tested. The first protocol entailed sample volume reduction and collection of the final reduced sample. The second and third protocols both incorporated pretreatment of the filter and fluid lines with a solution to prevent microorganisms from adhering. In the second protocol, the filter was back flushed with a surfactant solution to recover microorganisms. The third protocol used recirculation of a surfactant solution to recover microorganisms. Tests were undertaken using 100-liter water samples spiked with approximately 100 or 1000 microorganisms (1 or 10 per liter). Test microorganisms included Bacillus anthracis Sterne strain, Bacillus atrophaeus subsp. globigii, and Cryptosporidium parvum. The first protocol had significantly lower recovery than the other two. Back flushing resulted in higher recovery than forward flushing, but the difference was not statistically significant.

Genotyping Cryptosporidium parvum with an hsp70 single-nucleotide polymorphism microarray.

We investigated the application of an oligonucleotide microarray to (i) specifically detect Cryptosporidium spp., (ii) differentiate between closely related C. parvum isolates and Cryptosporidium species, and (iii) differentiate between principle genotypes known to infect humans. A microarray of 68 capture probes targeting seven single-nucleotide polymorphisms (SNPs) within a 190-bp region of the hsp70 gene of Cryptosporidium parvum was constructed. Labeled hsp70 targets were generated by PCR with biotin- or Cy3-labeled primers. Hybridization conditions were optimized for hybridization time, temperature, and salt concentration. Two genotype I C. parvum isolates (TU502 and UG502), two C. parvum genotype II isolates (Iowa and GCH1), and DNAs from 22 non-Cryptosporidium sp. organisms were used to test method specificity. Only DNAs from C. parvum isolates produced labeled amplicons that could be hybridized to and detected on the array. Hybridization patterns between genotypes were visually distinct, but identification of SNPs required statistical analysis of the signal intensity data. The results indicated that correct mismatch discrimination could be achieved for all seven SNPs for the UG502 isolate, five of seven SNPs for the TU502 isolate, and six of seven SNPs for both the Iowa and GCH1 isolates. Even without perfect mismatch discrimination, the microarray method unambiguously distinguished between genotype I and genotype II isolates and demonstrated the potential to differentiate between other isolates and species on a single microarray. This method may provide a powerful new tool for water utilities and public health officials for assessing point and nonpoint source contamination of water supplies.