Counting error in the line-intercept method of measuring root length

The line-intercept method is widely used to estimate the length of roots washed from soil samples. Human error in root length estimates has not been quantified and is needed for error analysis and specification of training/testing requirements for new workers. Nine or ten individuals counted four samples of roots on each of five days. One sample was counted on each of the days to test day-to-day variation. A coefficient of variation of 10% was typically obtained for estimates of the length of a single sample by the counters. An uncertainty of about 7% resulted from differences in how a sample was arranged on the grid and how the counters varied as a group from day-to-day. Certain individuals tended to yield estimates appreciably higher or lower than the entire group, so new workers must be adequately evaluated.     

A Microcomputer Program for Evaluating Sampling Error: an Application to Stereological Methods for Electron Microscopy

In situations where there is a need to minimize sampling error or sample size, the coefficient of variation (CV) may be used to evaluate sampling error as a function of the number of observations or subjects in a sample. For example, CV is useful for estimating the minimum number of electron micrographs (N_min) required to obtain a representative field sample for stereological analysis. To facilitate the determination of N_min, we have written a program (COEFficient) for DOS microcomputers which calculates CVs. COEF assists the user in reducing error to that which solely reflects biological variability, thereby minimizing the time and cost of subsequent analyses.     

A novel validation and calibration method for motion capture systems based on micro-triangulation

Motion capture systems are widely used to measure human kinematics. Nevertheless, users must consider system errors when evaluating their results. Most validation techniques for these systems are based on relative distance and displacement measurements. In contrast, our study aimed to analyse the absolute volume accuracy of optical motion capture systems by means of engineering surveying reference measurement of the marker coordinates (uncertainty: 0.75 mm). The method is exemplified on an 18 camera OptiTrack Flex13 motion capture system. The absolute accuracy was defined by the root mean square error (RMSE) between the coordinates measured by the camera system and by engineering surveying (micro-triangulation). The original RMSE of 1.82 mm due to scaling error was managed to be reduced to 0.77 mm while the correlation of errors to their distance from the origin reduced from 0.855 to 0.209. A simply feasible but less accurate absolute accuracy compensation method using tape measure on large distances was also tested, which resulted in similar scaling compensation compared to the surveying method or direct wand size compensation by a high precision 3D scanner. The presented validation methods can be less precise in some respects as compared to previous techniques, but they address an error type, which has not been and cannot be studied with the previous validation methods.     

Ablating both Fabp1 and Scp2/Scpx (TKO) induces hepatic phospholipid and cholesterol accumulation in high fat-fed mice

Although singly ablating Fabp1 or Scp2/Scpx genes may exacerbate the impact of high fat diet (HFD) on whole body phenotype and non-alcoholic fatty liver disease (NAFLD), concomitant upregulation of the non-ablated gene, preference for ad libitum fed HFD, and sex differences complicate interpretation. Therefore, these issues were addressed in male and female mice ablated in both genes (Fabp1/Scp2/Scpx null or TKO) and pair-fed HFD. Wild-type (WT) males gained more body weight as fat tissue mass (FTM) and exhibited higher hepatic lipid accumulation than WT females. The greater hepatic lipid accumulation in WT males was associated with higher hepatic expression of enzymes in glyceride synthesis, higher hepatic bile acids, and upregulation of transporters involved in hepatic reuptake of serum bile acids. While TKO had little effect on whole body phenotype and hepatic bile acid accumulation in either sex, TKO increased hepatic accumulation of lipids in both, specifically phospholipid and cholesteryl esters in males and females and free cholesterol in females. TKO-induced increases in glycerides were attributed not only to complete loss of FABP1, SCP2 and SCPx, but also in part to sex-dependent upregulation of hepatic lipogenic enzymes. These data with WT and TKO mice pair-fed HFD indicate that: i) Sex significantly impacted the ability of HFD to increase body weight, induce hepatic lipid accumulation and increase hepatic bile acids; and ii) TKO exacerbated the HFD ability to induce hepatic lipid accumulation, regardless of sex, but did not significantly alter whole body phenotype in either sex.     

Count data in biology—Data transformation or model reformation?

Statistical analyses are an integral component of scientific research, and for decades, biologists have applied transformations to data to meet the normal error assumptions for F and t tests. Over the years, there has been a movement from data transformation toward model reformation—the use of non‐normal error structures within the framework of the generalized linear model (GLM). The principal advantage of model reformation is that parameters are estimated on the original, rather than the transformed scale. However, data transformation has been shown to give better control over type I error, for simulated data with known error structures. We conducted a literature review of statistical textbooks directed toward biologists and of journal articles published in the primary literature to determine temporal trends in both the text recommendations and the practice in the refereed literature over the past 35 years. In this review, a trend of increasing use of reformation in the primary literature was evident, moving from no use of reformation before 1996 to >50% of the articles reviewed applying GLM after 2006. However, no such trend was observed in the recommendations in statistical textbooks. We then undertook 12 analyses based on published datasets in which we compared the type I error estimates, residual plot diagnostics, and coefficients yielded by analyses using square root transformations, log transformations, and the GLM. All analyses yielded acceptable residual versus fit plots and had similar p‐values within each analysis, but as expected, the coefficient estimates differed substantially. Furthermore, no consensus could be found in the literature regarding a procedure to back‐transform the coefficient estimates obtained from linear models performed on transformed datasets. This lack of consistency among coefficient estimates constitutes a major argument for model reformation over data transformation in biology.     

Enzymatic and Immunologic Identification of Succinic Semialdehyde Dehydrogenase in Rat and Human Neural and Nonneural Tissues

Abstract: We have identified succinic semialdehyde dehydrogenase protein in rat and human neural and nonneural tissues. Tissue localization was determined by enzymatic assay and by western immunoblotting using polyclonal antibodies raised in rabbit against the purified rat brain protein. Although brain shows the highest level of succinic semialdehyde dehydrogenase activity, substantial amounts of enzyme activity occur in mammalian liver, pituitary, heart, and ovary. We further demonstrate the absence of succinic semialdehyde dehydrogenase enzyme activity and protein in brain, liver, and kidney tissue samples from an individual affected with succinic semialdehyde dehydrogenase deficiency, thereby verifying the specificity of our antibodies.