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By using MALDI-TOF-TOF-MS analysis and MS/MS database, 15 differentially expressed protein spots were more reliable identified.
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In Neumark et al. (Ind Labor Relat Rev 67:608-648, 2014), we present evidence that their methods fail to isolate more reliable identifying information and lead to incorrect conclusions.
However, Neumark et al. (2014) provide evidence that the methods advocated by the above two studies do not isolate more reliable identifying information (or even throw out much useful and potentially valid identifying information), leading to incorrect conclusions.
In Neumark et al. (2014, hereafter NSW), we presented evidence that the methods advocated in these studies do not isolate more reliable identifying information (i.e., better comparison groups) and thus are flawed and lead to incorrect conclusions.
Taken together with the null results of the more reliable studies identified above, the positive findings from these selected studies of veterans are more likely to be spurious than valid.
The results show that overall they identify the same parcels as potential change areas but different experts are more reliable at identifying change in specific landscape types.
Compared to cultivation-based approaches, molecular techniques are more reliable for identifying microbial agents associated with endodontic infections.
Our results suggest that the streamline approach is advantageous for characterising the connectivity of long white matter tracts (PCC mPFC), whilst the probabilistic approach was more reliable at identifying PCC IPC connections.
Researchers have reported that pronouns are actually more reliable in identifying depression than negative emotion words.
This preliminary study shows that MLVA may be more reliable in identifying clusters of epidemiologically related isolates which may represent an outbreak of MRSA.
Cancer cell subpopulations based only upon marker expression are likely to be inaccurate due to antigenic plasticity and therefore studies based upon functional assays are likely more reliable to identify tumor stem cells.
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