Quality control in resting-state fMRI: the benefits of visual inspection.

Background: A variety of quality control (QC) approaches are employed in resting-state functional magnetic resonance imaging (rs-fMRI) to determine data quality and ultimately inclusion or exclusion of a fMRI data set in group analysis. Reliability of rs-fMRI data can be improved by censoring or "scrubbing" volumes affected by motion. While censoring preserves the integrity of participant-level data, including excessively censored data sets in group analyses may add noise. Quantitative motion-related metrics are frequently reported in the literature; however, qualitative visual inspection can sometimes catch errors or other issues that may be missed by quantitative metrics alone. In this paper, we describe our methods for performing QC of rs-fMRI data using software-generated quantitative and qualitative output and trained visual inspection. Results: The data provided for this QC paper had relatively low motion-censoring, thus quantitative QC resulted in no exclusions. Qualitative checks of the data resulted in limited exclusions due to potential incidental findings and failed pre-processing scripts. Conclusion: Visual inspection in addition to the review of quantitative QC metrics is an important component to ensure high quality and accuracy in rs-fMRI data analysis.

Integrative proteomics and metabolomics profiling to understand the biochemical basis of beef muscle darkening at a slightly elevated pH.

Previous studies investigated the biochemical basis of dark-cutting conditions at elevated muscle pH (above 6), but the molecular basis at slightly above normal pH (between 5.6 and 5.8) is still unclear. The objective was to determine protein and metabolite profiles to elucidate postmortem muscle darkening at slightly elevated pH. Loins were selected based on the criteria established in our laboratory before sample collections, such as pH less than 5.8, L* values (muscle lightness) less than 38, and not discounted by the grader (high-pH beef with dark color are discounted and not sold in retail stores). Six bright red loins (longissimus lumborum) at normal-pH (average pH = 5.57) and six dark-colored strip loins at slightly elevated pH (average pH = 5.70) from A maturity carcasses were obtained within 72-h postmortem from a commercial beef purveyor. Surface color, oxygen consumption, metmyoglobin reducing activity, protein, and metabolite profiles were determined on normal-pH and dark-colored steaks at slightly elevated pH. Enzymes related to glycogen metabolism and glycolytic pathways were more differently abundant than metabolites associated with these pathways. The results indicated that oxygen consumption and metmyoglobin reducing activity were greater (P < 0.05) in darker steaks than normal-pH steaks. Enzymes involved with glycogen catabolic pathways and glycogen storage disease showed lower abundance in dark beef. The tricarboxylic acid metabolite, aconitic acid, was overabundant in darker-colored beef than normal-pH beef, but glucose derivative metabolites were less abundant. The majority of glycogenolytic proteins and metabolites reported as overabundant in the previous dark-cutting studies at high pH (>6.4) also did not show significant differences in the current study. Therefore, our data suggest enzymes involved in glycogen metabolism, in part, create a threshold for muscle darkening than metabolites.

A bright cherry-red color beef is ideal during meat retail and carcass grading. Any deviation from a bright red color, such as dark red color, at the interface of the 12th and 13th rib-eye area leads to carcass discounts. Various studies have determined protein, metabolite, and mitochondrial profiles to understand the biochemical basis of dark-cutting beef (muscle pH greater than 6); however, limited knowledge is currently available on muscle darkening at a slightly elevated pH. Bright red loins at normal muscle pH and darker color loins at slightly elevated pH (not discounted by a grader) were collected 72-h postmortem from a commercial beef purveyor. Surface color, oxygen consumption, metmyoglobin reducing activity, protein, and metabolite profiles were determined on normal-pH and dark-colored steaks at slightly elevated pH. The results indicated that oxygen consumption and metmyoglobin reducing activity were greater in darker steaks than normal-pH steaks. Furthermore, the protein abundance profiles of enzymes related to glycogen metabolism and glycolytic pathways were more differently abundant than metabolites associated with these pathways. Understanding the factors involved in the occurrence of dark color steaks help to minimize losses due to discount carcasses.

Evaluation of taurine neuroprotection in aged rats with traumatic brain injury.

Despite higher rates of hospitalization and mortality following traumatic brain injury (TBI) in patients over 65 years old, older patients remain underrepresented in drug development studies. Worse outcomes in older individuals compared to younger adults could be attributed to exacerbated injury mechanisms including oxidative stress, inflammation, blood-brain barrier disruption, and bioenergetic dysfunction. Accordingly, pleiotropic treatments are attractive candidates for neuroprotection. Taurine, an endogenous amino acid with antioxidant, anti-inflammatory, anti-apoptotic, osmolytic, and neuromodulator effects, is neuroprotective in adult rats with TBI. However, its effects in the aged brain have not been evaluated. We subjected aged male rats to a unilateral controlled cortical impact injury to the sensorimotor cortex, and randomized them into four treatment groups: saline or 25 mg/kg, 50 mg/kg, or 200 mg/kg i.p. taurine. Treatments were administered 20 min post-injury and daily for 7 days. We assessed sensorimotor function on post-TBI days 1-14 and tissue loss on day 14 using T2-weighted magnetic resonance imaging. Experimenters were blinded to the treatment group for the duration of the study. We did not observe neuroprotective effects of taurine on functional impairment or tissue loss in aged rats after TBI. These findings in aged rats are in contrast to previous reports of taurine neuroprotection in younger animals. Advanced age is an important variable for drug development studies in TBI, and further research is required to better understand how aging may influence mechanisms of taurine neuroprotection.

Multiple testing with heterogeneous multinomial distributions.

Standard false discovery rate (FDR) procedures can provide misleading inference when testing multiple null hypotheses with heterogeneous multinomial data. For example, in the motivating study the goal is to identify species of bacteria near the roots of wheat plants (rhizobacteria) that are moderately or strongly associated with productivity. However, standard procedures discover the most abundant species even when their association is weak and fail to discover many moderate and strong associations when the species are not abundant. This article provides a new FDR-controlling method based on a finite mixture of multinomial distributions and shows that it tends to discover more moderate and strong associations and fewer weak associations when the data are heterogeneous across tests. The new method is applied to the rhizobacteria data and performs favorably over competing methods.

Classes of Multiple Decision Functions Strongly Controlling FWER and FDR.

Two general classes of multiple decision functions, where each member of the first class strongly controls the family-wise error rate (FWER), while each member of the second class strongly controls the false discovery rate (FDR), are described. These classes offer the possibility that optimal multiple decision functions with respect to a pre-specified Type II error criterion, such as the missed discovery rate (MDR), could be found which control the FWER or FDR Type I error rates. The gain in MDR of the associated FDR-controlling procedure relative to the well-known Benjamini-Hochberg (BH) procedure is demonstrated via a modest simulation study with gamma-distributed component data. Such multiple decision functions may have the potential of being utilized in multiple testing, specifically in the analysis of high-dimensional data sets.

Compound p-value statistics for multiple testing procedures.

Many multiple testing procedures make use of the p-values from the individual pairs of hypothesis tests, and are valid if the p-value statistics are independent and uniformly distributed under the null hypotheses. However, it has recently been shown that these types of multiple testing procedures are inefficient since such p-values do not depend upon all of the available data. This paper provides tools for constructing compound p-value statistics, which are those that depend upon all of the available data, but still satisfy the conditions of independence and uniformity under the null hypotheses. Several examples are provided, including a class of compound p-value statistics for testing location shifts. It is demonstrated, both analytically and through simulations, that multiple testing procedures tend to reject more false null hypotheses when applied to these compound p-values rather than the usual p-values, and at the same time still guarantee the desired type I error rate control. The compound p-values are used to analyze a real microarray data set and allow for more rejected null hypotheses.

Characterization and identification of productivity-associated rhizobacteria in wheat.

The rhizosphere is populated by a numerous and diverse array of rhizobacteria, and many impact productivity in largely unknown ways. Here we characterize the rhizobacterial community in a wheat variety categorized according to shoot biomass using 16S rRNA pyrosequencing abundance data. Plants were grown in homogenized field soil under greenhouse conditions, and DNA was extracted and pyrosequenced, resulting in 29,007 quality sequences. Operational taxonomic units (OTUs) that were significantly associated with biomass productivity were identified using an exact test adjusted for the false-discovery rate. The productivity deviation expressed as a percentage of the total mean square for regression (PMSR) was determined for each OTU. Out of 719 OTUs, 42 showed significant positive associations and 39 showed significant negative associations (q value, ≤0.05). OTUs with the greatest net positive associations, by genus, were as follows: Duganella, OTU 43 and OTU 3; Janthinobacterium, OTU 278; Pseudomonas, OTU 588; and Cellvibrio, OTU 1847. Those with negative associations were as follows: Bacteria, OTU 273; Chryseobacterium, OTU 508; Proteobacteria, OTU 249; and Enterobacter, OTU 357. Shoot biomass productivity was strongly correlated with the balance between the overall abundances of positive- and negative-productivity-associated OTUs. High-productivity rhizospheres contained 9.2 significant positives for every negatively associated rhizobacterium, while low-productivity rhizospheres showed 2.3 significant negatives for every positively associated rhizobacterium. Overall rhizobacterial community diversity as measured by the Chao1, Shannon, and Simpson indexes was nonlinearly related to productivity, closely fitting a wavelike cubic equation. We conclude that shoot biomass productivity is strongly related to the ratio of positive- to negative-productivity-associated rhizobacteria in the rhizosphere. This study identifies significant OTUs composing the productive and unproductive rhizobacterial communities.

POWER-ENHANCED MULTIPLE DECISION FUNCTIONS CONTROLLING FAMILY-WISE ERROR AND FALSE DISCOVERY RATES.

Improved procedures, in terms of smaller missed discovery rates (MDR), for performing multiple hypotheses testing with weak and strong control of the family-wise error rate (FWER) or the false discovery rate (FDR) are developed and studied. The improvement over existing procedures such as the Sidák procedure for FWER control and the Benjamini-Hochberg (BH) procedure for FDR control is achieved by exploiting possible differences in the powers of the individual tests. Results signal the need to take into account the powers of the individual tests and to have multiple hypotheses decision functions which are not limited to simply using the individual p-values, as is the case, for example, with the Sidák, Bonferroni, or BH procedures. They also enhance understanding of the role of the powers of individual tests, or more precisely the receiver operating characteristic (ROC) functions of decision processes, in the search for better multiple hypotheses testing procedures. A decision-theoretic framework is utilized, and through auxiliary randomizers the procedures could be used with discrete or mixed-type data or with rank-based nonparametric tests. This is in contrast to existing p-value based procedures whose theoretical validity is contingent on each of these p-value statistics being stochastically equal to or greater than a standard uniform variable under the null hypothesis. Proposed procedures are relevant in the analysis of high-dimensional "large M, small n" data sets arising in the natural, physical, medical, economic and social sciences, whose generation and creation is accelerated by advances in high-throughput technology, notably, but not limited to, microarray technology.

Randomised P-values and nonparametric procedures in multiple testing.

The validity of many multiple hypothesis testing procedures for false discovery rate (FDR) control relies on the assumption that P-value statistics are uniformly distributed under the null hypotheses. However, this assumption fails if the test statistics have discrete distributions or if the distributional model for the observables is misspecified. A stochastic process framework is introduced that, with the aid of a uniform variate, admits P-value statistics to satisfy the uniformity condition even when test statistics have discrete distributions. This allows nonparametric tests to be used to generate P-value statistics satisfying the uniformity condition. The resulting multiple testing procedures are therefore endowed with robustness properties. Simulation studies suggest that nonparametric randomised test P-values allow for these FDR methods to perform better when the model for the observables is nonparametric or misspecified.

Mechanistic insight into the ability of American ginseng to suppress colon cancer associated with colitis.

We have recently shown that American ginseng (AG) prevents and treats mouse colitis. Because both mice and humans with chronic colitis have a high colon cancer risk, we tested the hypothesis that AG can be used to prevent colitis-driven colon cancer. Using the azoxymethane (AOM)/dextran sulfate sodium (DSS) mouse model of ulcerative colitis, we show that AG can suppress colon cancer associated with colitis. To explore the molecular mechanisms of the anticancer effects of AG, we also carried out antibody array experiments on colon cells isolated at a precancerous stage. We found there were 82 protein end points that were either significantly higher (41 proteins) or significantly lower (41 proteins) in the AOM + DSS group compared with the AOM-alone (control) group. In contrast, there were only 19 protein end points that were either significantly higher (10 proteins) or significantly lower (9 proteins) in the AOM + DSS + AG group compared with the AOM-alone (control) group. Overall, these results suggest that AG keeps the colon environment in metabolic equilibrium when mice are treated with AOM + DSS and gives insight into the mechanisms by which AG protects from colon cancer associated with colitis.

Resveratrol suppresses colitis and colon cancer associated with colitis.

Resveratrol is a naturally occurring polyphenol that exhibits pleiotropic health beneficial effects, including anti-inflammatory, cardio-protective, and cancer-protective activities. It is recognized as one of the more promising natural molecules in the prevention and treatment of chronic inflammatory and autoimmune disorders. Ulcerative colitis is an idiopathic, chronic inflammatory disease of the colon associated with a high colon cancer risk. Here, we used a dextran sulfate sodium (DSS) mouse model of colitis, which resembles human ulcerative colitis pathology. Resveratrol mixed in food ameliorates DSS-induced colitis in mice in a dose-dependent manner. Resveratrol significantly improves inflammation score, downregulates the percentage of neutrophils in the mesenteric lymph nodes and lamina propria, and modulates CD3(+) T cells that express tumor necrosis factor-alpha and IFN-gamma. Markers of inflammation and inflammatory stress (p53 and p53-phospho-Ser(15)) are also downregulated by resveratrol. Because chronic colitis drives colon cancer risk, we carried out experiments to determine the chemopreventive properties of resveratrol. Tumor incidence is reduced from 80% in mice treated with azoxymethane (AOM) + DSS to 20% in mice treated with AOM + DSS + resveratrol (300 ppm). Tumor multiplicity also decreased with resveratrol treatment. AOM + DSS-treated mice had 2.4 +/- 0.7 tumors per animal compared with AOM + DSS + 300 ppm resveratrol, which had 0.2 +/- 0.13 tumors per animal. The current study indicates that resveratrol is a useful, nontoxic complementary and alternative strategy to abate colitis and potentially colon cancer associated with colitis.