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1.  Approaching Expert Results Using a Hierarchical Cerebellum Parcellation Protocol for Multiple Inexpert Human Raters 
NeuroImage  2012;64:616-629.
Volumetric measurements obtained from image parcellation have been instrumental in uncovering structure-function relationships. However, anatomical study of the cerebellum is a challenging task. Because of its complex structure, expert human raters have been necessary for reliable and accurate segmentation and parcellation. Such delineations are time-consuming and prohibitively expensive for large studies. Therefore, we present a three-part cerebellar parcellation system that utilizes multiple inexpert human raters that can efficiently and expediently produce results nearly on par with those of experts. This system includes a hierarchical delineation protocol, a rapid verification and evaluation process, and statistical fusion of the inexpert rater parcellations. The quality of the raters’ and fused parcellations was established by examining their Dice similarity coefficient, region of interest (ROI) volumes, and the intraclass correlation coefficient of region volume. The intra-rater ICC was found to be 0.93 at the finest level of parcellation.
doi:10.1016/j.neuroimage.2012.08.075
PMCID: PMC3590024  PMID: 22975160
Human Cerebellum; Manual labeling; Delineation; Parcellation; STAPLE; STAPLER; Label fusion
2.  Colonization patterns of soil microbial communities in the Atacama Desert 
Microbiome  2013;1:28.
Background
The Atacama Desert is one of the driest deserts in the world and its soil, with extremely low moisture, organic carbon content, and oxidizing conditions, is considered to be at the dry limit for life.
Results
Analyses of high throughput DNA sequence data revealed that bacterial communities from six geographic locations in the hyper-arid core and along a North-South moisture gradient were structurally and phylogenetically distinct (ANOVA test for observed operating taxonomic units at 97% similarity (OTU0.03), P <0.001) and that communities from locations in the hyper-arid zone displayed the lowest levels of diversity. We found bacterial taxa similar to those found in other arid soil communities with an abundance of Rubrobacterales, Actinomycetales, Acidimicrobiales, and a number of families from the Thermoleophilia. The extremely low abundance of Firmicutes indicated that most bacteria in the soil were in the form of vegetative cells. Integrating molecular data with climate and soil geochemistry, we found that air relative humidity (RH) and soil conductivity significantly correlated with microbial communities’ diversity metrics (least squares linear regression for observed OTU0.03 and air RH and soil conductivity, P <0.001; UniFrac PCoA Spearman’s correlation for air RH and soil conductivity, P <0.0001), indicating that water availability and salt content are key factors in shaping the Atacama soil microbiome. Mineralization studies showed communities actively metabolizing in all soil samples, with increased rates in soils from the southern locations.
Conclusions
Our results suggest that microorganisms in the driest soils of the Atacama Desert are in a state of stasis for most of the time, but can potentially metabolize if presented with liquid water for a sufficient duration. Over geological time, rare rain events and physicochemical factors potentially played a major role in selecting micro-organisms that are most adapted to extreme desiccating conditions.
doi:10.1186/2049-2618-1-28
PMCID: PMC3971613  PMID: 24451153
Soil microbial communities; Extreme environment; Arid soil; Atacama Desert; Desertification; High-throughput 16S rRNA sequencing
3.  A Computational Neurodegenerative Disease Progression Score: Method and Results with the Alzheimer’s Disease Neuroimaging Initiative Cohort 
NeuroImage  2012;63(3):1478-1486.
While neurodegenerative diseases are characterized by steady degeneration over relatively long timelines, it is widely believed that the early stages are the most promising for therapeutic intervention, before irreversible neuronal loss occurs. Developing a therapeutic response requires a precise measure of disease progression. However, since the early stages are for the most part asymptomatic, obtaining accurate measures of disease progression is difficult. Longitudinal databases of hundreds of subjects observed during several years with tens of validated biomarkers are becoming available, allowing the use of computational methods. We propose a widely applicable statistical methodology for creating a disease progression score (DPS), using multiple biomarkers, for subjects with a neurodegenerative disease. The proposed methodology was evaluated for Alzheimer’s disease (AD) using the publicly available AD Neuroimaging Initiative (ADNI) database, yielding an Alzheimer’s DPS or ADPS score for each subject and each time-point in the database. In addition, a common description of biomarker changes was produced allowing for an ordering of the biomarkers. The Rey Auditory Verbal Learning Test delayed recall was found to be the earliest biomarker to become abnormal. The group of biomarkers comprising the volume of the hippocampus and the protein concentration amyloid beta and Tau were next in the timeline, and these were followed by three cognitive biomarkers. The proposed methodology thus has potential to stage individuals according to their state of disease progression relative to a population and to deduce common behaviors of biomarkers in the disease itself.
doi:10.1016/j.neuroimage.2012.07.059
PMCID: PMC3472161  PMID: 22885136
Neurodegenerative diseases; Alzheimer’s disease; biomarkers; disease progression score
4.  [125I]FIAU imaging in a preclinical model of lung infection: quantification of bacterial load 
2'-Fluoro-2'-deoxy-1β-D-arabinofuranosyl-5-[125I]iodouracil ([125I]FIAU), a substrate for the thymidine kinase (TK) present in most bacteria, has been used as an imaging agent for single photon emission computed tomography (SPECT) in an experimental model of lung infection. Using SPECT-CT we show that [125I]FIAU is specific for bacterial infection rather than sterile inflammation. We report [125I]FIAU lung uptake values of 1.26 ± 0.20 percent injected dose per gram (%ID/g) in normal controls, 1.69 ± 0.32 %ID/g in lung inflammation and up to 7.14 ± 1.09 %ID/g in lung infection in ex vivo biodistribution studies at 24 h after intranasal administration of bacteria. Images of [125I]FIAU signal within lung can be used to estimate the number of bacteria present, with a limit of detection of 109 colony forming units per mL on the X-SPECT scanner. [125I]FIAU-Based bacterial imaging may be useful in preclinical models to facilitate the development of new antibiotics, particularly in cases where a corresponding human trial is planned.
PMCID: PMC3477740  PMID: 23133816
Inflammation; thymidine kinase; nucleoside; SPECT; PET; molecular imaging
5.  Feasibility of geometric-intensity based semi-automated delineation of the tentorium cerebelli from MRI scans 
This paper describes a feasibility study of a method for delineating the tentorium cerebelli in MRI brain scans. The tentorium cerebelli is a thin sheet of dura matter covering the cerebellum and separating it from the posterior part of the temporal lobe and the occipital lobe of the cerebral hemispheres. Cortical structures such as the parahippocampal gyrus can be indistinguishable from tentorium in MPRAGE and T1 weighted magnetic resonance image scans. Similar intensities in these neighboring regions make it difficult to perform accurate cortical analysis in neuroimaging studies of schizophrenia and Alzheimer's disease. A semi-automated, geometric, intensity-based procedure for delineating the tentorium from a whole brain scan is described. Initial and final curves are traced within the tentorium. A cost function, based on intensity and Euclidean distance, is computed between the two curves using the Fast Marching method. The initial curve is then evolved to the final curve based on the gradient of the computed costs, generating a series of intermediate curves. These curves are then used to generate a triangulated surface of the tentorium. For three scans, surfaces were found to be within 2 voxels from hand-segmentations.
doi:10.1111/j.1552-6569.2009.00405.x
PMCID: PMC2889204  PMID: 19659568
tentorium cerebelli; parahippocampal gyrus; fast marching method
6.  Noninvasive Pulmonary [18F]-2-Fluoro-Deoxy-d-Glucose Positron Emission Tomography Correlates with Bactericidal Activity of Tuberculosis Drug Treatment▿ † 
Antimicrobial Agents and Chemotherapy  2009;53(11):4879-4884.
Tools for monitoring response to tuberculosis (TB) treatment are time-consuming and resource intensive. Noninvasive biomarkers have the potential to accelerate TB drug development, but to date, little progress has been made in utilizing imaging technologies. Therefore, in this study, we used noninvasive imaging to monitor response to TB treatment. BALB/c and C3HeB/FeJ mice were aerosol infected with Mycobacterium tuberculosis and administered bactericidal (standard and highly active) or bacteriostatic TB drug regimens. Serial pulmonary [18F]-2-fluoro-deoxy-d-glucose (FDG) positron emission tomography (PET) was compared with standard microbiologic methods to monitor the response to treatment. [18F]FDG-PET correctly identified the bactericidal activity of the drug regimens. Imaging required fewer animals; was available in real time, as opposed to having CFU counts 4 weeks later; and could also detect TB relapse in a time frame similar to that of the standard method. Lesion-specific [18F]FDG-PET activity also broadly correlated with TB treatment in C3HeB/FeJ mice that develop caseating lesions. These studies demonstrate the application of noninvasive imaging to monitor TB treatment response. By reducing animal numbers, these biomarkers will allow cost-effective studies of more expensive animal models of TB. Validated markers may also be useful as “point-of-care” methods to monitor TB treatment in humans.
doi:10.1128/AAC.00789-09
PMCID: PMC2772305  PMID: 19738022
7.  Where Have All the Interactions Gone? Estimating the Coverage of Two-Hybrid Protein Interaction Maps 
PLoS Computational Biology  2007;3(11):e214.
Yeast two-hybrid screens are an important method for mapping pairwise physical interactions between proteins. The fraction of interactions detected in independent screens can be very small, and an outstanding challenge is to determine the reason for the low overlap. Low overlap can arise from either a high false-discovery rate (interaction sets have low overlap because each set is contaminated by a large number of stochastic false-positive interactions) or a high false-negative rate (interaction sets have low overlap because each misses many true interactions). We extend capture–recapture theory to provide the first unified model for false-positive and false-negative rates for two-hybrid screens. Analysis of yeast, worm, and fly data indicates that 25% to 45% of the reported interactions are likely false positives. Membrane proteins have higher false-discovery rates on average, and signal transduction proteins have lower rates. The overall false-negative rate ranges from 75% for worm to 90% for fly, which arises from a roughly 50% false-negative rate due to statistical undersampling and a 55% to 85% false-negative rate due to proteins that appear to be systematically lost from the assays. Finally, statistical model selection conclusively rejects the Erdös-Rényi network model in favor of the power law model for yeast and the truncated power law for worm and fly degree distributions. Much as genome sequencing coverage estimates were essential for planning the human genome sequencing project, the coverage estimates developed here will be valuable for guiding future proteomic screens. All software and datasets are available in Datasets S1 and S2, Figures S1–S5, and Tables S1−S6, and are also available from our Web site, http://www.baderzone.org.
Author Summary
The genome sequence of an organism provides a parts list of proteins, but not an instruction manual for assembling the parts into a cell. Assembly instructions now come from experiments such as two-hybrid screens that detect physical interactions between pairs of proteins. Defining the resources required for generating a full interaction map requires accurate estimates of the false-negative and false-positive rates of genome-scale screens. Two-hybrid screens often select a query protein and sample its interaction partners. True partners may be missed, and false partners may be spuriously identified. This sampling process resembles a capture–recapture experiment, except that classical capture–recapture theory assumes no false positives. Novel extensions to capture–recapture theory permit its application to proteomic screens. This new theory provides statistically grounded answers to long-standing questions: false-discovery rates of high-throughput screens (possibly over 50% per unique interaction, but probably no more than 15% per clone); the quality of different screening libraries; protein properties leading to “sticky” or “promiscuous” interactions; the global network topology; and, most importantly, the coverage of existing two-hybrid maps. Models estimate roughly 30,000 total pairwise interactions in yeast and 500,000 to 1,000,000 in metazoans. The majority of these interactions remain to be discovered.
doi:10.1371/journal.pcbi.0030214
PMCID: PMC2082503  PMID: 18039026
8.  Self-Organization in High-Density Bacterial Colonies: Efficient Crowd Control 
PLoS Biology  2007;5(11):e302.
Colonies of bacterial cells can display complex collective dynamics, frequently culminating in the formation of biofilms and other ordered super-structures. Recent studies suggest that to cope with local environmental challenges, bacterial cells can actively seek out small chambers or cavities and assemble there, engaging in quorum sensing behavior. By using a novel microfluidic device, we showed that within chambers of distinct shapes and sizes allowing continuous cell escape, bacterial colonies can gradually self-organize. The directions of orientation of cells, their growth, and collective motion are mutually correlated and dictated by the chamber walls and locations of chamber exits. The ultimate highly organized steady state is conducive to a more-organized escape of cells from the chambers and increased access of nutrients into and evacuation of waste out of the colonies. Using a computational model, we suggest that the lengths of the cells might be optimized to maximize self-organization while minimizing the potential for stampede-like exit blockage. The self-organization described here may be crucial for the early stage of the organization of high-density bacterial colonies populating small, physically confined growth niches. It suggests that this phenomenon can play a critical role in bacterial biofilm initiation and development of other complex multicellular bacterial super-structures, including those implicated in infectious diseases.
Author Summary
Bacterial cells form colonies with complex organization (aka biofilms), particularly in response to hostile environmental conditions. Recent studies have shown that biofilm development occurs when bacterial cells seek out small cavities and populate them at high densities. However, bacteria in cavities may suffer from poor nutrient supply or waste removal, or disorganized expansion leading to blockage of cell escape. In this study, we observed Escherichia coli in a microfluidic device that allows direct observation of the growth and development of cell colonies in microchambers of different shapes and sizes through multiple generations. Combining this experimentation with computational analysis of colony growth and expansion, we characterize a process of colony self-organization that results in a high degree of correlation between the directions of cell orientation and growth of collective cell movement. We also find that this self-organization can significantly facilitate efficient escape of cells from the confines of cavities where they reside, while improving the access of nutrients into the colony interior. Finally, we suggest that the aspect ratio of the shape of E. coli and other similar bacteria might be generally subject to a constraint related to colony self-organization.
In nature, bacteria often found themselves in high-density colonies. The combination of a novel microfluidic device and computational analysis reveals an unexpected self-organization behavior of tightly packed bacterial cells.
doi:10.1371/journal.pbio.0050302
PMCID: PMC2043048  PMID: 18044986
9.  Where Have All the Interactions Gone? Estimating the Coverage of Two-Hybrid Protein Interaction Maps 
PLoS Computational Biology  2007;3(11):e214.
Yeast two-hybrid screens are an important method for mapping pairwise physical interactions between proteins. The fraction of interactions detected in independent screens can be very small, and an outstanding challenge is to determine the reason for the low overlap. Low overlap can arise from either a high false-discovery rate (interaction sets have low overlap because each set is contaminated by a large number of stochastic false-positive interactions) or a high false-negative rate (interaction sets have low overlap because each misses many true interactions). We extend capture–recapture theory to provide the first unified model for false-positive and false-negative rates for two-hybrid screens. Analysis of yeast, worm, and fly data indicates that 25% to 45% of the reported interactions are likely false positives. Membrane proteins have higher false-discovery rates on average, and signal transduction proteins have lower rates. The overall false-negative rate ranges from 75% for worm to 90% for fly, which arises from a roughly 50% false-negative rate due to statistical undersampling and a 55% to 85% false-negative rate due to proteins that appear to be systematically lost from the assays. Finally, statistical model selection conclusively rejects the Erdös-Rényi network model in favor of the power law model for yeast and the truncated power law for worm and fly degree distributions. Much as genome sequencing coverage estimates were essential for planning the human genome sequencing project, the coverage estimates developed here will be valuable for guiding future proteomic screens. All software and datasets are available in Datasets S1 and S2, Figures S1–S5, and Tables S1−S6, and are also available from our Web site, http://www.baderzone.org.
Author Summary
The genome sequence of an organism provides a parts list of proteins, but not an instruction manual for assembling the parts into a cell. Assembly instructions now come from experiments such as two-hybrid screens that detect physical interactions between pairs of proteins. Defining the resources required for generating a full interaction map requires accurate estimates of the false-negative and false-positive rates of genome-scale screens. Two-hybrid screens often select a query protein and sample its interaction partners. True partners may be missed, and false partners may be spuriously identified. This sampling process resembles a capture–recapture experiment, except that classical capture–recapture theory assumes no false positives. Novel extensions to capture–recapture theory permit its application to proteomic screens. This new theory provides statistically grounded answers to long-standing questions: false-discovery rates of high-throughput screens (possibly over 50% per unique interaction, but probably no more than 15% per clone); the quality of different screening libraries; protein properties leading to “sticky” or “promiscuous” interactions; the global network topology; and, most importantly, the coverage of existing two-hybrid maps. Models estimate roughly 30,000 total pairwise interactions in yeast and 500,000 to 1,000,000 in metazoans. The majority of these interactions remain to be discovered.
doi:10.1371/journal.pcbi.0030214
PMCID: PMC2082503  PMID: 18039026

Results 1-9 (9)