scholarly journals Collaborative open science as a way to reproducibility and new insights in primate cognition research

2019 ◽  
Author(s):  
Many Primates ◽  
Drew Altschul ◽  
Michael J. Beran ◽  
Manuel Bohn ◽  
Kai Caspar ◽  
...  
Keyword(s):  
Large Scale ◽  
Open Science ◽  
Small Sample ◽  
Primate Species ◽  
Primate Cognition ◽  
Research Attention ◽  
Questionable Research Practices ◽  
Wide Range ◽  
Research Questions ◽  
Small Sample Sizes

The field of primate cognition studies how primates, including humans, perceive, process, store, retrieve, and use information to guide decision making and other behavior. Much of this research is motivated by a desire to understand how these abilities evolved. Large and diverse samples from a wide range of species are vital to achieving this goal. In reality, however, primate cognition research suffers from small sample sizes and is often limited to a handful of species, which constrains the evolutionary inferences we can draw. We conducted a systematic review of primate cognition research published between 2014 and 2019 to quantify the extent of this problem. Across 574 studies, the median sample size was 7 individuals. Less than 15% of primate species were studied at all, and only 19% of studies included more than one species. Further, the species that were studied varied widely in how much research attention they received, partly because a small number of test sites contributed most of the studies. These results suggest that the generalizability of primate cognition studies may be severely limited. Publication bias, questionable research practices, and a lack of replication attempts may exacerbate these problems. We describe the ManyPrimates project as one approach to overcoming some of these issues by establishing an infrastructure for large-scale collaboration in primate cognition research. Building on similar initiatives in other areas of psychology, this approach has already yielded one of the largest and most diverse primate samples to date and enables us to ask many research questions that can only be addressed through collaboration.

scholarly journals Collaboration and Open Science Initiatives in Primate Research

2021 ◽  
Author(s):  
ManyPrimates ◽  
Alba Motes Rodrigo ◽  
Charlotte Canteloup ◽  
Sonja J. Ebel ◽  
Christopher I Petkov ◽  
...  
Keyword(s):  
Cognitive Abilities ◽  
Large Scale ◽  
Open Science ◽  
Small Sample ◽  
Primate Research ◽  
Research Model ◽  
Primate Cognition ◽  
History Of ◽  
Small Sample Sizes ◽  
Successful Collaboration

Traditionally, primate cognition research has been conducted by independent teams on small populations of a few species. Such limited variation and small sample sizes pose problems that prevent us from reconstructing the evolutionary history of primate cognition. In this chapter, we discuss how large-scale collaboration, a research model successfully implemented in other fields, makes it possible to obtain the large and diverse datasets needed to conduct robust comparative analysis of primate cognitive abilities. We discuss the advantages and challenges of large-scale collaborations and argue for the need for more open science practices in the field. We describe these collaborative projects in psychology and primatology and introduce ManyPrimates as the first, successful collaboration that has established an infrastructure for large-scale, inclusive research in primate cognition. Considering examples of large-scale collaborations both in primatology and psychology, we conclude that this type of research model is feasible and has the potential to address otherwise unattainable questions in primate cognition.

scholarly journals Use of Antiplatelet Agents Decreases the Positive Predictive Value of Fecal Immunochemical Tests for Colorectal Cancer but Does Not Affect Their Sensitivity

2021 ◽  
Vol 11 (6) ◽  
pp. 497
Author(s):  
Yoonsuk Jung ◽  
Eui Im ◽  
Jinhee Lee ◽  
Hyeah Lee ◽  
Changmo Moon
Keyword(s):  
Colorectal Cancer ◽  
Large Scale ◽  
Screening Program ◽  
Antiplatelet Agents ◽  
Population Based ◽  
Small Sample ◽  
Antithrombotic Agents ◽  
Predictive Values ◽  
Prescription Rates ◽  
Small Sample Sizes

Previous studies have evaluated the effects of antithrombotic agents on the performance of fecal immunochemical tests (FITs) for the detection of colorectal cancer (CRC), but the results were inconsistent and based on small sample sizes. We studied this topic using a large-scale population-based database. Using the Korean National Cancer Screening Program Database, we compared the performance of FITs for CRC detection between users and non-users of antiplatelet agents and warfarin. Non-users were matched according to age and sex. Among 5,426,469 eligible participants, 768,733 used antiplatelet agents (mono/dual/triple therapy, n = 701,683/63,211/3839), and 19,569 used warfarin, while 4,638,167 were non-users. Among antiplatelet agents, aspirin, clopidogrel, and cilostazol ranked first, second, and third, respectively, in terms of prescription rates. Users of antiplatelet agents (3.62% vs. 4.45%; relative risk (RR): 0.83; 95% confidence interval (CI): 0.78–0.88), aspirin (3.66% vs. 4.13%; RR: 0.90; 95% CI: 0.83–0.97), and clopidogrel (3.48% vs. 4.88%; RR: 0.72; 95% CI: 0.61–0.86) had lower positive predictive values (PPVs) for CRC detection than non-users. However, there were no significant differences in PPV between cilostazol vs. non-users and warfarin users vs. non-users. For PPV, the RR (users vs. non-users) for antiplatelet monotherapy was 0.86, while the RRs for dual and triple antiplatelet therapies (excluding cilostazol) were 0.67 and 0.22, respectively. For all antithrombotic agents, the sensitivity for CRC detection was not different between users and non-users. Use of antiplatelet agents, except cilostazol, may increase the false positives without improving the sensitivity of FITs for CRC detection.

Modelling macroparasite aggregation using a nematode-sheep system: the Weibull distribution as an alternative to the Negative Binomial distribution?

Parasitology ◽  
2005 ◽  
Vol 131 (3) ◽  
pp. 393-401 ◽  
Author(s):  
S. GABA ◽  
V. GINOT ◽  
J. CABARET
Keyword(s):  
Weibull Distribution ◽  
Negative Binomial Distribution ◽  
Binomial Distribution ◽  
Negative Binomial ◽  
Information Criterion ◽  
Gastrointestinal Nematode ◽  
Small Sample ◽  
Parameter Estimations ◽  
Wide Range ◽  
Small Sample Sizes

Macroparasites are almost always aggregated across their host populations, hence the Negative Binomial Distribution (NBD) with its exponent parameter k is widely used for modelling, quantifying or analysing parasite distributions. However, many studies have pointed out some drawbacks in the use of the NBD, with respect to the sensitivity of k to the mean number of parasites per host or the under-representation of the heavily infected hosts in the estimate of k. In this study, we compare the fit of the NBD with 4 other widely used distributions on observed parasitic gastrointestinal nematode distributions in their sheep host populations (11 datasets). Distributions were fitted to observed data using maximum likelihood estimator and the best fits were selected using the Akaike's Information Criterion (AIC). A simulation study was also conducted in order to assess the possible bias in parameter estimations especially in the case of small sample sizes. We found that the NBD is seldom the best fit for gastrointestinal nematode distributions. The Weibull distribution was clearly more appropriate over a very wide range of degrees of aggregation, mainly because it was more flexible in fitting the heavily infected hosts. Moreover, the Weibull distribution estimates are less sensitive to sample size. Thus, when possible, we suggest to carefully check on observed data if the NBD is appropriate before conducting any further analysis on parasite distributions.

scholarly journals Age and sex dependent variability of type 2 dopamine receptors in the human brain: A large-scale PET cohort

2021 ◽  
Author(s):  
Tuulia Malén ◽  
Tomi Karjalainen ◽  
Janne Isojärvi ◽  
Aki Vehtari ◽  
Paul-Christian Bürkner ◽  
...  
Keyword(s):  
Human Brain ◽  
Large Scale ◽  
Movement Control ◽  
Heterogeneous Data ◽  
Small Sample ◽  
Cross Sectional ◽  
Psychiatric Conditions ◽  
Small Sample Sizes ◽  
Age And Sex

BACKGROUND: The dopamine system contributes to a multitude of functions ranging from reward and motivation to learning and movement control, making it a key component in goal-directed behavior. Altered dopaminergic function is observed in neurological and psychiatric conditions. Numerous factors have been proposed to influence dopamine function, but due to small sample sizes and heterogeneous data analysis methods in previous studies their specific and joint contributions remain unresolved. METHODS: In this cross-sectional register-based study we investigated how age, sex, body mass index (BMI), as well as cerebral hemisphere and regional volume influence striatal type 2 dopamine receptor (D2R) availability in the human brain. We analyzed a large historical dataset (n=156, 120 males and 36 females) of [11C]raclopride PET scans performed between 2004 and 2018. RESULTS: Striatal D2R availability decreased through age for both sexes and was higher in females versus males throughout age. BMI and striatal D2R availability were weakly associated. There was no consistent lateralization of striatal D2R. The observed effects were independent of regional volumes. These results were validated using two different spatial normalization methods, and the age and sex effects also replicated in an independent sample (n=135). CONCLUSIONS: D2R density is dependent on age and sex, which may contribute to the vulnerability of neurological and psychiatric conditions involving altering D2R expression.

scholarly journals Epigenome-wide meta-analysis of blood DNA methylation and its association with subcortical volumes: findings from the ENIGMA Epigenetics Working Group

2019 ◽  
Author(s):  
Tianye Jia ◽  
Congying Chu ◽  
Yun Liu ◽  
Jenny van Dongen ◽  
Evangelos Papastergios ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Nucleus Accumbens ◽  
Large Scale ◽  
Biomarker Discovery ◽  
Association Studies ◽  
Meta Analysis ◽  
Hippocampal Volume ◽  
Small Sample ◽  
Small Sample Sizes ◽  
Meta Analyses

AbstractDNA methylation, which is modulated by both genetic factors and environmental exposures, may offer a unique opportunity to discover novel biomarkers of disease-related brain phenotypes, even when measured in other tissues than brain, such as blood. A few studies of small sample sizes have revealed associations between blood DNA methylation and neuropsychopathology, however, large-scale epigenome-wide association studies (EWAS) are needed to investigate the utility of DNA methylation profiling as a peripheral marker for the brain. Here, in an analysis of eleven international cohorts, totalling 3337 individuals, we report epigenome-wide meta-analyses of blood DNA methylation with volumes of the hippocampus, thalamus and nucleus accumbens (NAcc)—three subcortical regions selected for their associations with disease and heritability and volumetric variability. Analyses of individual CpGs revealed genome-wide significant associations with hippocampal volume at two loci. No significant associations were found for analyses of thalamus and nucleus accumbens volumes. Cluster-based analyses revealed additional differentially methylated regions (DMRs) associated with hippocampal volume. DNA methylation at these loci affected expression of proximal genes involved in learning and memory, stem cell maintenance and differentiation, fatty acid metabolism and type-2 diabetes. These DNA methylation marks, their interaction with genetic variants and their impact on gene expression offer new insights into the relationship between epigenetic variation and brain structure and may provide the basis for biomarker discovery in neurodegeneration and neuropsychiatric conditions.

scholarly journals Defining the biological bases of individual differences in musicality

2015 ◽  
Vol 370 (1664) ◽  
pp. 20140092 ◽  
Author(s):  
Bruno Gingras ◽  
Henkjan Honing ◽  
Isabelle Peretz ◽  
Laurel J. Trainor ◽  
Simon E. Fisher
Keyword(s):  
Large Scale ◽  
Twin Studies ◽  
Small Sample ◽  
Aptitude Tests ◽  
Large Scale Assessment ◽  
Genome Wide ◽  
Entry Points ◽  
High Heritability ◽  
Small Sample Sizes ◽  
Complex Human Traits

Advances in molecular technologies make it possible to pinpoint genomic factors associated with complex human traits. For cognition and behaviour, identification of underlying genes provides new entry points for deciphering the key neurobiological pathways. In the past decade, the search for genetic correlates of musicality has gained traction. Reports have documented familial clustering for different extremes of ability, including amusia and absolute pitch (AP), with twin studies demonstrating high heritability for some music-related skills, such as pitch perception. Certain chromosomal regions have been linked to AP and musical aptitude, while individual candidate genes have been investigated in relation to aptitude and creativity. Most recently, researchers in this field started performing genome-wide association scans. Thus far, studies have been hampered by relatively small sample sizes and limitations in defining components of musicality, including an emphasis on skills that can only be assessed in trained musicians. With opportunities to administer standardized aptitude tests online, systematic large-scale assessment of musical abilities is now feasible, an important step towards high-powered genome-wide screens. Here, we offer a synthesis of existing literatures and outline concrete suggestions for the development of comprehensive operational tools for the analysis of musical phenotypes.

scholarly journals Massive Factorial Design Untangles Coding Sequences Determinants of Translation Efficacy

2017 ◽  
Author(s):  
Guillaume Cambray ◽  
Joao C. Guimaraes ◽  
Adam Paul Arkin
Keyword(s):  
Large Scale ◽  
Small Sample ◽  
Translation Efficiency ◽  
E Coli ◽  
Synthetic Dna ◽  
Critical Design ◽  
Codon Composition ◽  
Expression Activity ◽  
Small Sample Sizes ◽  
Epigenetic Disruption

AbstractComparative analyses of natural sequences or variant libraries are often used to infer mechanisms of expression, activity and evolution. Contingent selective histories and small sample sizes can profoundly bias such approaches. Both limitations can be lifted using precise design of large-scale DNA synthesis. Here, we precisely design 5E. coligenomes worth of synthetic DNA to untangle the relative contributions of 8 interlaced sequence properties described independently as major determinants of translation inEscherichia coli. To expose hierarchical effects, we engineer an inducible translational coupling device enabling epigenetic disruption of mRNA secondary structures. We find that properties commonly believed to modulate translation generally explain less than a third of the variation in protein production. We describe dominant effects of mRNA structures over codon composition on both initiation and elongation, and previously uncharacterized relationships among factors controlling translation. These results advance our understanding of translation efficiency and expose critical design challenges.

scholarly journals Population Genetics Study of Isoniazid Resistance Mutations and Evolution of Multidrug-Resistant Mycobacterium tuberculosis

2006 ◽  
Vol 50 (8) ◽  
pp. 2640-2649 ◽  
Author(s):  
Manzour Hernando Hazbón ◽  
Michael Brimacombe ◽  
Miriam Bobadilla del Valle ◽  
Magali Cavatore ◽  
Marta Inírida Guerrero ◽  
...  
Keyword(s):  
Mycobacterium Tuberculosis ◽  
Large Scale ◽  
Sample Selection ◽  
Multidrug Resistant ◽  
Small Sample ◽  
Inverse Association ◽  
Resistance Mutations ◽  
Isoniazid Resistance ◽  
Large Scale Analysis ◽  
Small Sample Sizes

ABSTRACT The molecular basis for isoniazid resistance in Mycobacterium tuberculosis is complex. Putative isoniazid resistance mutations have been identified in katG, ahpC, inhA, kasA, and ndh. However, small sample sizes and related potential biases in sample selection have precluded the development of statistically valid and significant population genetic analyses of clinical isoniazid resistance. We present the first large-scale analysis of 240 alleles previously associated with isoniazid resistance in a diverse set of 608 isoniazid-susceptible and 403 isoniazid-resistant clinical M. tuberculosis isolates. We detected 12 mutant alleles in isoniazid-susceptible isolates, suggesting that these alleles are not involved in isoniazid resistance. However, mutations in katG, ahpC, and inhA were strongly associated with isoniazid resistance, while kasA mutations were associated with isoniazid susceptibility. Remarkably, the distribution of isoniazid resistance-associated mutations was different in isoniazid-monoresistant isolates from that in multidrug-resistant isolates, with significantly fewer isoniazid resistance mutations in the isoniazid-monoresistant group. Mutations in katG315 were significantly more common in the multidrug-resistant isolates. Conversely, mutations in the inhA promoter were significantly more common in isoniazid-monoresistant isolates. We tested for interactions among mutations and resistance to different drugs. Mutations in katG, ahpC, and inhA were associated with rifampin resistance, but only katG315 mutations were associated with ethambutol resistance. There was also a significant inverse association between katG315 mutations and mutations in ahpC or inhA and between mutations in kasA and mutations in ahpC. Our results suggest that isoniazid resistance and the evolution of multidrug-resistant strains are complex dynamic processes that may be influenced by interactions between genes and drug-resistant phenotypes.

scholarly journals Current Understanding of Religion, Spirituality, and Their Neurobiological Correlates

2020 ◽  
Author(s):  
James I. Rim ◽  
Jesse Caleb Ojeda ◽  
Connie Svob ◽  
Jürgen Kayser ◽  
Elisa Drews ◽  
...  
Keyword(s):  
Functional Neuroimaging ◽  
Brain Regions ◽  
Posterior Cingulate Cortex ◽  
Clinical Applications ◽  
Small Sample ◽  
Control Group ◽  
Religion And Spirituality ◽  
Wide Range ◽  
Small Sample Sizes ◽  
And Behavior

Religion and spirituality (R/S) have been prominent aspects of most human cultures through the ages; however, scientific inquiry into this phenomenon has been limited. We conducted a systematic literature review of research on the neurobiological correlates of R/S, which resulted in 25 reports studying primarily R/S with electroencephalography, structural neuroimaging (MRI), and functional neuroimaging (fMRI, PET). These studies investigated a wide range of religions (e.g., Christianity, Buddhism, Islam) and R/S states and behaviors (e.g., resting state, prayer, judgments) and employed a wide range of methodologies, some of which (e.g., no control group, varying measures of religiosity, small sample sizes) raise concerns about the validity of the results. Despite these limitations, the findings of these studies collectively suggest that the experience of R/S has specific neurobiological correlates and that these correlates are distinct from non-R/S counterparts. The findings implicate several brain regions potentially associated with R/S development and behavior, including the medial frontal cortex, orbitofrontal cortex, precuneus, posterior cingulate cortex, default mode network, and caudate. This research may suggest future clinical applications and interventions related to R/S and various disorders, including mood, anxiety, psychotic, pain, and vertiginous disorders. Further studies with more rigorous study designs are warranted to elucidate the neurobiological mechanisms of R/S and their potential clinical applications.

scholarly journals Meta-matching: a simple framework to translate phenotypic predictive models from big to small data

2020 ◽  
Author(s):  
Tong He ◽  
Lijun An ◽  
Jiashi Feng ◽  
Danilo Bzdok ◽  
Avram J Holmes ◽  
...  
Keyword(s):  
Brain Imaging ◽  
Predictive Models ◽  
Large Scale ◽  
Prediction Performance ◽  
Small Sample ◽  
Small Scale ◽  
Small Data ◽  
Imaging Data ◽  
Resting State Functional Connectivity ◽  
Wide Range

AbstractThere is significant interest in using brain imaging data to predict non-brain-imaging phenotypes in individual participants. However, most prediction studies are underpowered, relying on less than a few hundred participants, leading to low reliability and inflated prediction performance. Yet, small sample sizes are unavoidable when studying clinical populations or addressing focused neuroscience questions. Here, we propose a simple framework – “meta-matching” – to translate predictive models from large-scale datasets to new unseen non-brain-imaging phenotypes in boutique studies. The key observation is that many large-scale datasets collect a wide range inter-correlated phenotypic measures. Therefore, a unique phenotype from a boutique study likely correlates with (but is not the same as) some phenotypes in some large-scale datasets. Meta-matching exploits these correlations to boost prediction in the boutique study. We applied meta-matching to the problem of predicting non-brain-imaging phenotypes using resting-state functional connectivity (RSFC). Using the UK Biobank (N = 36,848), we demonstrated that meta-matching can boost the prediction of new phenotypes in small independent datasets by 100% to 400% in many scenarios. When considering relative prediction performance, meta-matching significantly improved phenotypic prediction even in samples with 10 participants. When considering absolute prediction performance, meta-matching significantly improved phenotypic prediction when there were least 50 participants. With a growing number of large-scale population-level datasets collecting an increasing number of phenotypic measures, our results represent a lower bound on the potential of meta-matching to elevate small-scale boutique studies.

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