Current challenges in metabolomics for diabetes research: a vital functional genomic tool or just a ploy for gaining funding?

2008 ◽  
Vol 34 (1) ◽  
pp. 1-5 ◽  
Author(s):  
Julian L. Griffin ◽  
Antonio Vidal-Puig
Keyword(s):  
Animal Studies ◽  
Gene Knockout ◽  
Tca Cycle ◽  
Small Sample ◽  
Human Populations ◽  
Diabetes Research ◽  
Functional Genomic ◽  
High Concentration ◽  
Small Sample Sizes ◽  
Analytical Tools

Metabolomics aims to profile all the small molecule metabolites found within a cell, tissue, organ, or organism and use this information to understand a biological manipulation such as a drug intervention or a gene knockout. While neither mass spectrometry or NMR spectroscopy, the two most commonly used analytical tools in metabolomics, can provide a complete coverage of the metabolome, compared with other functional genomic tools for profiling biological moieties the approach is cheap and high throughput. In diabetes and obesity research this has provided the opportunity to assess large human populations or investigate a range of different tissues in animal studies both rapidly and cheaply. However, the approach has a number of major challenges, particularly with the interpretation of the data obtained. For example, some key pathways are better represented by high concentration metabolites inside the cell, and thus, the coverage of the metabolome may become biased towards these pathways (e.g., the TCA cycle, amino acid metabolism). There is also the challenge of statistically modeling datasets with large numbers of variables but relatively small sample sizes. This perspective discusses our own experience of some of the benefits and pitfalls with using metabolomics to understand diseases associated with type 2 diabetes.

scholarly journals Mitochondrial portraits of human populations using median networks.

Genetics ◽  
1995 ◽  
Vol 141 (2) ◽  
pp. 743-753 ◽  
Author(s):  
H J Bandelt ◽  
P Forster ◽  
B C Sykes ◽  
M B Richards
Keyword(s):  
Sequence Data ◽  
Hypervariable Region ◽  
Small Sample ◽  
Human Populations ◽  
Sample Sizes ◽  
Median Network ◽  
Sequencing Errors ◽  
Mitochondrial Haplotypes ◽  
And Migration ◽  
Small Sample Sizes

Abstract Analysis of variation in the hypervariable region of mitochondrial DNA (mtDNA) has emerged as an important tool for studying human evolution and migration. However, attempts to reconstruct optimal intraspecific mtDNA phylogenies frequently fail because parallel mutation events partly obscure the true evolutionary pathways. This makes it inadvisable to present a single phylogenetic tree at the expense of neglecting equally acceptable ones. As an alternative, we propose a novel network approach for portraying mtDNA relationships. For small sample sizes (< approximately 50), an unmodified median network contains all most parsimonious trees, displays graphically the full information content of the sequence data, and can easily be generated by hand. For larger sample sizes, we reduce the complexity of the network by identifying parallelisms. This reduction procedure is guided by a compatibility argument and an additional source of phylogenetic information: the frequencies of the mitochondrial haplotypes. As a spin-off, our approach can also assist in identifying sequencing errors, which manifest themselves in implausible network substructures. We illustrate the advantages of our approach with several examples from existing data sets.

scholarly journals Frontiers in RNA biology: advances from a small fly Drosophila melanogaster

2016 ◽  
Vol 38 (2) ◽  
pp. 21-25
Author(s):  
James B. Brown ◽  
Susan E. Celniker
Keyword(s):  
Rna Processing ◽  
Small Sample ◽  
Rna Seq ◽  
Ribonucleoprotein Complexes ◽  
Rna Biology ◽  
Cell Type Specific ◽  
Exciting Time ◽  
Small Sample Sizes ◽  
Analytical Tools ◽  
Processing Mechanisms

In this article, we discuss emerging frontiers in RNA biology from a historical perspective. The field is currently undergoing yet another transformative expansion. RNA-seq has revealed that splicing, and, more generally, RNA processing is far more complex than expected, and the mechanisms of regulation are correspondingly sophisticated. Our understanding of the molecular machines involved in RNA metabolism is incomplete and derives from small sample sizes. Even if we manage to complete a catalogue of molecular species, RNA isoforms and the ribonucleoprotein complexes that drive their genesis, the horizons of molecular dynamics and cell-type-specific processing mechanisms await. This is an exciting time to enter into the study of RNA biology; analytical tools, wet and dry, are advancing rapidly, and each new measurement modality brings into view another new function or activity of versatile RNA. Since the dawn of sequence-based RNA biology, we have come a long way.

The Effect of Prebiotic Products on Decreasing Adiposity Parameters in Overweight and Obese Individuals: A Systematic Review and Meta- Analysis

2020 ◽  
Vol 28 (2) ◽  
pp. 419-431
Author(s):  
Hua Qu ◽  
Lei Song ◽  
Ying Zhang ◽  
Zhu-ye Gao ◽  
Da-zhuo Shi
Keyword(s):  
Body Weight ◽  
Fat Mass ◽  
Animal Studies ◽  
Weighted Mean Difference ◽  
Meta Analysis ◽  
Small Sample ◽  
Inflammatory Biomarkers ◽  
Cochrane Library ◽  
Small Sample Sizes ◽  
Factor Α

Background: Prebiotics are substrates selectively utilized by host microorganisms to confer health benefits. The potential of prebiotics to decrease body weight in overweight/obese individuals was suggested by some clinical and animal studies. However, these studies were based on relatively small sample sizes and the precise effects of prebiotic products have not yet been evaluated. Therefore, the present meta-analysis of Randomized Controlled Trials (RCTs) was designed to comprehensively assess the effects of prebiotic products on overweight and obese individuals. Methods: PubMed, EMBASE and Cochrane Library were searched to identify RCT investigating the effects of prebiotic products on overweight and obese individuals. We calculated the pooled weighted mean difference (WMD) to assess the effects of prebiotic products on Body Mass Index (BMI), body weight, fat mass and inflammatory biomarkers. Results: Twelve RCTs with a total of 535 overweight and obese individuals were enrolled. Compared with placebo, prebiotic products decreased C reactive protein (WMD, -1.06 mg/L; 95%CI, -1.72 to - 0.40; p=0.002), tumour necrosis factor-α(WMD, -0.64 pg/mL; 95%CI, -1.11 to -0.18; p=0.006) and other inflammatory markers, such as interleukin-1β，lipopolysaccharide (p<0.05); whereas no reductions in BMI (WMD, -0.20 kg/m2; 95%CI, -0.58 to 0.19; p=0.32), body weight (WMD, -0.51 kg; 95%CI, -1.18 to 0.16; p=0.14) and fat mass (WMD, 0.11 kg; 95%CI, -0.04 to 0.25; p=0.15) were observed. Conclusion: In the present analysis, comprehensive evidence suggested that prebiotic products did not decrease adiposity parameters (BMI, body weight and body fat mass), but they could decrease the levels of systemic inflammatory biomarkers, implying adherence to prebiotic products might be a promising complementary approach to managing inflammatory states in overweight and obese individuals.

scholarly journals Molecular Biomarkers of Electroconvulsive Therapy Effects and Clinical Response: Understanding the Present to Shape the Future

2021 ◽  
Vol 11 (9) ◽  
pp. 1120
Author(s):  
Elisabetta Maffioletti ◽  
Rosana Carvalho Silva ◽  
Marco Bortolomasi ◽  
Bernhard T. Baune ◽  
Massimo Gennarelli ◽  
...  
Keyword(s):  
Electroconvulsive Therapy ◽  
Animal Studies ◽  
Acute Stress ◽  
Biological Systems ◽  
Research Field ◽  
Conclusive Evidence ◽  
Small Sample ◽  
The Future ◽  
Experimental Analogue ◽  
Small Sample Sizes

Electroconvulsive therapy (ECT) represents an effective intervention for treatment-resistant depression (TRD). One priority of this research field is the clarification of ECT response mechanisms and the identification of biomarkers predicting its outcomes. We propose an overview of the molecular studies on ECT, concerning its course and outcome prediction, including also animal studies on electroconvulsive seizures (ECS), an experimental analogue of ECT. Most of these investigations underlie biological systems related to major depressive disorder (MDD), such as the neurotrophic and inflammatory/immune ones, indicating effects of ECT on these processes. Studies about neurotrophins, like the brain-derived neurotrophic factor (BDNF) and the vascular endothelial growth factor (VEGF), have shown evidence concerning ECT neurotrophic effects. The inflammatory/immune system has also been studied, suggesting an acute stress reaction following an ECT session. However, at the end of the treatment, ECT produces a reduction in inflammatory-associated biomarkers such as cortisol, TNF-alpha and interleukin 6. Other biological systems, including the monoaminergic and the endocrine, have been sparsely investigated. Despite some promising results, limitations exist. Most of the studies are concentrated on one or few markers and many studies are relatively old, with small sample sizes and methodological biases. Expression studies on gene transcripts and microRNAs are rare and genetic studies are sparse. To date, no conclusive evidence regarding ECT molecular markers has been reached; however, the future may be just around the corner.

scholarly journals Molecular approaches for a better understanding of the epidemiology and population genetics ofLeishmania

Parasitology ◽  
2010 ◽  
Vol 138 (4) ◽  
pp. 405-425 ◽  
Author(s):  
G. SCHÖNIAN ◽  
K. KUHLS ◽  
I. L. MAURICIO
Keyword(s):  
Gold Standard ◽  
Population Genetic ◽  
Field Studies ◽  
Epidemiological Studies ◽  
Small Sample ◽  
Clinical Samples ◽  
Molecular Approaches ◽  
Sexual Recombination ◽  
Small Sample Sizes ◽  
Analytical Tools

SUMMARYMolecular approaches are being used increasingly for epidemiological studies of visceral and cutaneous leishmaniases. Several molecular markers resolving genetic differences betweenLeishmaniaparasites at species and strain levels have been developed to address key epidemiological and population genetic questions. The current gold standard, multilocus enzyme typing (MLEE), needs cultured parasites and lacks discriminatory power. PCR assays identifying species directly with clinical samples have proven useful in numerous field studies. Multilocus sequence typing (MLST) is potentially the most powerful phylogenetic approach and will, most probably, replace MLEE in the future. Multilocus microsatellite typing (MLMT) is able to discriminate below the zymodeme level and seems to be the best candidate for becoming the gold standard for distinction of strains. Population genetic studies by MLMT revealed geographical and hierarchic population structure inL. tropica, L. majorand theL. donovanicomplex. The existence of hybrids and gene flow betweenLeishmaniapopulations suggests that sexual recombination is more frequent than previously thought. However, typing and analytical tools need to be further improved. Accessible databases should be created and sustained for integrating data obtained by different researchers. This would allow for global analyses and help to avoid biases in analyses due to small sample sizes.

Integrating Visual and Bayesian Statistical Analyses in Single Case Experimental Research to Evaluate the Effectiveness and Magnitude of a Comprehensive Behavioral Intervention

2018 ◽  
Author(s):  
Prathiba Natesan ◽  
Smita Mehta
Keyword(s):  
Behavioral Intervention ◽  
Effect Size ◽  
Rate Ratio ◽  
Visual Analysis ◽  
Single Case ◽  
Small Sample ◽  
Statistical Analyses ◽  
Data Types ◽  
Ratio Effect ◽  
Small Sample Sizes

Single case experimental designs (SCEDs) have become an indispensable methodology where randomized control trials may be impossible or even inappropriate. However, the nature of SCED data presents challenges for both visual and statistical analyses. Small sample sizes, autocorrelations, data types, and design types render many parametric statistical analyses and maximum likelihood approaches ineffective. The presence of autocorrelation decreases interrater reliability in visual analysis. The purpose of the present study is to demonstrate a newly developed model called the Bayesian unknown change-point (BUCP) model which overcomes all the above-mentioned data analytic challenges. This is the first study to formulate and demonstrate rate ratio effect size for autocorrelated data, which has remained an open question in SCED research until now. This expository study also compares and contrasts the results from BUCP model with visual analysis, and rate ratio effect size with nonoverlap of all pairs (NAP) effect size. Data from a comprehensive behavioral intervention are used for the demonstration.

No Evidence that Experiencing Physical Warmth Promotes Interpersonal Warmth: Two Failures to Replicate Williams and Bargh (2008)

2018 ◽  
Author(s):  
Christopher Chabris ◽  
Patrick Ryan Heck ◽  
Jaclyn Mandart ◽  
Daniel Jacob Benjamin ◽  
Daniel J. Simons
Keyword(s):  
Null Hypothesis ◽  
Small Sample ◽  
Sample Sizes ◽  
Double Blind ◽  
Bayesian Analyses ◽  
Physical Warmth ◽  
Small Sample Sizes ◽  
Interpersonal Warmth

Williams and Bargh (2008) reported that holding a hot cup of coffee caused participants to judge a person’s personality as warmer, and that holding a therapeutic heat pad caused participants to choose rewards for other people rather than for themselves. These experiments featured large effects (r = .28 and .31), small sample sizes (41 and 53 participants), and barely statistically significant results. We attempted to replicate both experiments in field settings with more than triple the sample sizes (128 and 177) and double-blind procedures, but found near-zero effects (r = –.03 and .02). In both cases, Bayesian analyses suggest there is substantially more evidence for the null hypothesis of no effect than for the original physical warmth priming hypothesis.

scholarly journals Non-Invasive Monitoring of Adrenocortical Activity in Three Sympatric Desert Gerbil Species

Animals ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 75
Author(s):  
Álvaro Navarro-Castilla ◽  
Mario Garrido ◽  
Hadas Hawlena ◽  
Isabel Barja
Keyword(s):  
Small Sample ◽  
Post Injection ◽  
Control Groups ◽  
Treatment Groups ◽  
Adrenocortical Activity ◽  
Non Invasive ◽  
Endocrine Status ◽  
Corticosterone Metabolites ◽  
Small Sample Sizes ◽  
Fecal Corticosterone Metabolites

The study of the endocrine status can be useful to understand wildlife responses to the changing environment. Here, we validated an enzyme immunoassay (EIA) to non-invasively monitor adrenocortical activity by measuring fecal corticosterone metabolites (FCM) in three sympatric gerbil species (Gerbillus andersoni, G. gerbillus and G. pyramidum) from the Northwestern Negev Desert’s sands (Israel). Animals included into treatment groups were injected with adrenocorticotropic hormone (ACTH) to stimulate adrenocortical activity, while control groups received a saline solution. Feces were collected at different intervals and FCM were quantified by an EIA. Basal FCM levels were similar in the three species. The ACTH effect was evidenced, but the time of FCM peak concentrations appearance differed between the species (6–24 h post-injection). Furthermore, FCM peak values were observed sooner in G. andersoni females than in males (6 h and 18 h post-injection, respectively). G. andersoni and G. gerbillus males in control groups also increased FCM levels (18 h and 48 h post-injection, respectively). Despite the small sample sizes, our results confirmed the EIA suitability for analyzing FCM in these species as a reliable indicator of the adrenocortical activity. This study also revealed that close species, and individuals within a species, can respond differently to the same stressor.

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