Biology subjects

Reynolds, R. C.

Publications and source records attributed to Reynolds, R. C..

3 recordsLinked to original sources

bioRxiv2018

A tail of two sides: Artificially doubled false positive rates in neuroimaging due to the sidedness choice with t-tests

One-sided t-tests are widely used in neuroimaging data analysis. While such a test may be applicable when investigating specific regions and prior information about directionality is present, we argue here that it is often mis-applied, with severe consequences for false positive rate (FPR) control. Conceptually, a pair of one-sided t-tests conducted in tandem (e.g., to test separately for both positive and negative effects), effectively amounts to a two-sided t-test. However, replacing the two-sided test with a pair of one-sided tests without multiple comparisons correction essentially doubles the intended FPR of statements made about the same study; that is, the actual family-wise error (FWE) of results at the whole brain level would be 10% instead of the 5% intended by the researcher. Therefore, we strongly recommend that, unless otherwise explicitly justified, two-sided t-tests be applied instead of two simultaneous one-sided t-tests.

neuroscience↗

bioRxiv2018

FMRI processing with AFNI: Some comments and corrections on \"Exploring the Impact of Analysis Software on Task fMRI Results\"

A recent study posted on bioRxiv by Bowring, Maumet and Nichols aimed to compare results of FMRI data that had been processed with three commonly used software packages (AFNI, FSL and SPM). Their stated purpose was to use \"default\" settings of each softwares pipeline for task-based FMRI, and then to quantify overlaps in final clustering results and to measure similarity/dissimilarity in the final outcomes of packages. While in theory the setup sounds simple (implement each packages defaults and compare results), practical realities make this difficult. For example, different softwares would recommend different spatial resolutions of the final data, but for the sake of comparisons, the same value must be used across all. Moreover, we would say that AFNI does not have an explicit default pipeline available: a wide diversity of datasets and study designs are acquired across the neuroimaging community, often requiring bespoke tailoring of basic processing rather than a \"one-size-fits-all\" pipeline. However, we do have strong recommendations for certain steps, and we are also aware that the choice of a given step might place requirements on other processing steps. Given the very clear reporting of the AFNI pipeline used in Bowring et al. paper, we take this opportunity to comment on some of these aspects of processing with AFNI here, clarifying a few mistakes therein and also offering recommendations. We provide point-by-point considerations of using AFNIs processing pipeline design tool at the individual level, afni_proc.py, along with supplementary programs; while specifically discussed in the context of the present usage, many of these choices may serve as useful starting points for broader processing. It is our intention/hope that the user should examine data quality at every step, and we demonstrate how this is facilitated in AFNI, as well.

neuroscience↗

bioRxiv2017

Regulated release of cryptococcal polysaccharide drives virulence and suppresses immune cell infiltration into the central nervous system

Cryptococcus neoformans is a common environmental yeast and opportunistic pathogen responsible for 15% of AIDS-related deaths worldwide. Mortality primarily results from meningoencephalitis, which occurs when fungal cells disseminate from the initial pulmonary infection site and spread to the brain. A key C. neoformans virulence trait is the polysaccharide capsule. Capsule shields C. neoformans from immune-mediated recognition and destruction. The main capsule component, glucuronoxylomannan (GXM), is found both attached to the cell surface and free in the extracellular space (as exo-GXM). Exo-GXM accumulates in patient serum and cerebrospinal fluid at g/mL concentrations, has well-documented immunosuppressive properties, and correlates with poor patient outcomes. However, it is poorly understood whether exo-GXM release is regulated or the result of shedding during normal capsule turnover. We demonstrate that exo-GXM release is regulated by environmental cues and inversely correlates with surface capsule levels. We identified genes specifically involved in exo-GXM release that do not alter surface capsule thickness. The first mutant, liv7{triangleup}, released less GXM than wild-type cells when capsule is not induced. The second mutant, cnag_00658{triangleup}, released more exo-GXM under capsule-inducing conditions. Exo-GXM release observed in vitro correlated with polystyrene adherence, virulence, and fungal burden during murine infection. Additionally, we find that exo-GXM reduces cell size and capsule thickness in capsule-inducing conditions, potentially influencing dissemination. Finally, we demonstrated that exo-GXM prevents immune cell infiltration into the brain during disseminated infection and highly inflammatory intracranial infection. Our data suggest that exo-GXM performs a different role from capsule GXM during infection, altering cell size and suppressing inflammation.\n\nImportanceCryptococcus neoformans is a leading cause of life-threatening meningoencephalitis in humans. C. neoformans cells produce an immunosuppressive polysaccharide, glucuronoxylomannan (GXM), that is the main component of a protective surface capsule. GXM is also released free into extracellular space as exo-GXM, although the distinction between cell-attached GXM and exo-GXM has been unclear. Exo-GXM influences the outcome of infection, is the basis for current diagnostic tools, and has potential therapeutic applications. This study increases our basic understanding of the fungal biology that regulates polysaccharide release, suggesting that the release of cell-attached GXM and exo-GXM are distinctly regulated. We also introduce a new concept that exo-GXM may alter cell body and capsule size, thereby influencing dissemination in the host. Finally, we provide experimental evidence to confirm clinical observations that exo-GXM influences inflammation during brain infection.

microbiology↗