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1.  Integration of network biology and imaging to study cancer phenotypes and responses 
Ever growing “omics” data and continuously accumulated biological knowledge provide an unprecedented opportunity to identify molecular biomarkers and their interactions that are responsible for cancer phenotypes that can be accurately defined by clinical measurements such as in vivo imaging. Since signaling or regulatory networks are dynamic and context-specific, systematic efforts to characterize such structural alterations must effectively distinguish significant network rewiring from random background fluctuations. Here we introduced a novel integration of network biology and imaging to study cancer phenotypes and responses to treatments at the molecular systems level. Specifically, Differential Dependence Network (DDN) analysis was used to detect statistically significant topological rewiring in molecular networks between two phenotypic conditions, and in vivo Magnetic Resonance Imaging (MRI) was used to more accurately define phenotypic sample groups for such differential analysis. We applied DDN to analyze two distinct phenotypic groups of breast cancer and study how genomic instability affects the molecular network topologies in high-grade ovarian cancer. Further, FDA-approved arsenic trioxide (ATO) and the ND2-SmoA1 mouse model of Medulloblastoma (MB) were used to extend our analyses of combined MRI and Reverse Phase Protein Microarray (RPMA) data to assess tumor responses to ATO and to uncover the complexity of therapeutic molecular biology.
PMCID: PMC4348060  PMID: 25750594
Network biology; MRI; differential network; cancer biology
2.  Simultaneously Extracting Multiple Parameters via Fitting One Single Autocorrelation Function Curve in Diffuse Correlation Spectroscopy 
Near-infrared diffuse correlation spectroscopy (DCS) has recently been employed for noninvasive acquisition of blood flow information in deep tissues. Based on the established correlation diffusion equation, the light intensity autocorrelation function detected by DCS is determined by a blood flow index αDB, tissue absorption coefficient μa, reduced scattering coefficient μs’, and a coherence factor β. The present study is designed to investigate the possibility of extracting multiple parameters such as μa, μs’, β, and αDB through fitting one single autocorrelation function curve and evaluate the performance of different fitting methods. For this purpose, computer simulations, tissue-like phantom experiments and in-vivo tissue measurements were utilized. The results suggest that it is impractical to simultaneously fit αDB and μa or αDB and μs’ from one single autocorrelation function curve due to the large crosstalk between these paired parameters. However, simultaneously fitting β and αDB is feasible and generates more accurate estimation with smaller standard deviation compared to the conventional two-step fitting method (i.e., first calculating β and then fitting αDB). The outcomes from this study provide a crucial guidance for DCS data analysis.
PMCID: PMC4337031  PMID: 23193446
Near-infrared spectroscopy; diffuse correlation spectroscopy; blood flow; noise model; autocorrelation function
3.  Diffuse Correlation Spectroscopy (DCS) for Assessment of Tissue Blood Flow in Skeletal Muscle: Recent Progress 
Near-infrared diffuse correlation spectroscopy (DCS) is an emerging technology for monitoring blood flow in various tissues. This article reviews the recent progress of DCS for the assessment of skeletal muscle blood flow, including the developments in technology allowing use during dynamic exercise and muscular electrical stimulation, the utilization for diagnosis of muscle vascular diseases, and the applications for evaluating treatment effects. The limitations of current DCS studies and future perspective are finally discussed.
PMCID: PMC3979478  PMID: 24724043
Diffuse Correlation Spectroscopy (DCS); Skeletal muscle; Blood flow; Motion artifact; Gating algorithm; Peripheral Arterial Disease (PAD)
4.  Fibromyalgia is Associated With Altered Skeletal Muscle Characteristics Which May Contribute to Post-Exertional Fatigue in Post-Menopausal Women 
Arthritis and rheumatism  2013;65(2):519-528.
To identify muscle physiological properties that may contribute to post-exertional fatigue and malaise in women with fibromyalgia (FM).
Healthy postmenopausal women with (n=11) and without (n=11) fibromyalgia, age 51–70 years, participated in this study. Physical characteristics along with self-reported questionnaires were evaluated. Strength loss and tissue oxygenation in response to a fatiguing exercise protocol were used to quantify fatigability and the local muscle hemodynamic profile. Muscle biopsies were obtained to assess between-group differences in baseline muscle properties using histochemical, immunohistochemical and electron microscopic analyses.
No significant difference in muscle fatigue in response to exercise was apparent between healthy controls and subjects with FM. However, self-reported fatigue and pain were correlated to prolonged loss of strength following 12-min of recovery in subjects with FM. Although there was no difference in percent SDH positive (type I) and SDH negative (type II) fibers or in mean fiber cross-sectional area between groups, subjects with FM showed greater size variability and altered fiber size distribution. Only in healthy controls, fatigue-resistance was strongly correlated with the size of SDH positive fibers and hemoglobin oxygenation. By contrast, subjects with FM with the highest percentage of SDH positive fibers recovered strength most effectively, which was correlated to capillary density. However, overall, capillary density was lower in subjects with FM.
Peripheral mechanisms i.e. altered muscle fiber size distribution and decreased capillary density may contribute to post-exertional fatigue in subjects with FM. Understanding these defects in fibromyalgic muscle may provide valuable insight for treatment.
PMCID: PMC3558634  PMID: 23124535
6.  Tumor Vascular Microenvironment Determines Responsiveness to Photodynamic Therapy 
Cancer Research  2012;72(8):2079-2088.
The efficacy of photodynamic therapy (PDT) depends upon the delivery of both photosensitizing drug and oxygen. In this study, we hypothesized that local vascular microenvironment is a determinant of tumor response to PDT. Tumor vascularization and its basement membrane (collagen) were studied as a function of supplementation with basement membrane matrix (Matrigel) at the time of tumor cell inoculation. Effects on vascular composition with consequences to tumor hypoxia, photosensitizer uptake and PDT response were measured. Matrigel-supplemented tumors developed more normalized vasculature, composed of smaller and more uniformly-spaced blood vessels than their unsupplemented counterparts, but these changes did not affect tumor oxygenation or PDT-mediated direct cytotoxicity. However, PDT-induced vascular damage increased in Matrigel-supplemented tumors, following an affinity of the photosensitizer Photofrin for collagen-containing vascular basement membrane coupled with increased collagen content in these tumors. The more highly-collagenated tumors demonstrated more vascular congestion and ischemia after PDT, along with a higher probability of curative outcome that was collagen dependent. In the presence of photosensitizer-collagen localization, PDT effects on collagen were evidenced by a decrease in its association with vessels. Together, our findings demonstrate that photosensitizer localization to collagen increases vascular damage and improves treatment efficacy in tumors with greater collagen content. The vascular basement membrane is thus identified to be a determinant of therapeutic outcome in PDT of tumors.
PMCID: PMC3328659  PMID: 22374982
collagen; photodynamic therapy; microenvironment; normalization; vasculature
7.  Simultaneous measurement of deep tissue blood flow and oxygenation using noncontact diffuse correlation spectroscopy flow-oximeter 
Scientific Reports  2013;3:1358.
We report a novel noncontact diffuse correlation spectroscopy flow-oximeter for simultaneous quantification of relative changes in tissue blood flow (rBF) and oxygenation (Δ[oxygenation]). The noncontact probe was compared against a contact probe in tissue-like phantoms and forearm muscles (n = 10), and the dynamic trends in both rBF and Δ[oxygenation] were found to be highly correlated. However, the magnitudes of Δ[oxygenation] measured by the two probes were significantly different. Monte Carlo simulations and phantom experiments revealed that the arm curvature resulted in a significant underestimation (~−20%) for the noncontact measurements in Δ[oxygenation], but not in rBF. Other factors that may cause the residual discrepancies between the contact and noncontact measurements were discussed, and further comparisons with other established technologies are needed to identify/quantify these factors. Our research paves the way for noncontact and simultaneous monitoring of blood flow and oxygenation in soft and vulnerable tissues without distorting tissue hemodynamics.
PMCID: PMC3584314  PMID: 23446991
8.  Noncontact diffuse correlation spectroscopy for noninvasive deep tissue blood flow measurement 
Journal of Biomedical Optics  2012;17(1):010502.
A noncontact diffuse correlation spectroscopy (DCS) probe has been developed using two separated optical paths for the source and detector. This unique design avoids the interference between the source and detector and allows large source-detector separations for deep tissue blood flow measurements. The noncontact probe has been calibrated against a contact probe in a tissue-like phantom solution and human muscle tissues; flow changes concurrently measured by the two probes are highly correlated in both phantom (R2=0.89, p<10−5) and real-tissue (R2=0.77, p<10−5, n=9) tests. The noncontact DCS holds promise for measuring blood flow in vulnerable (e.g., pressure ulcer) and soft (e.g., breast) tissues without distorting tissue hemodynamic properties.
PMCID: PMC4019367  PMID: 22352631
noncontact; diffuse; correlation; spectroscopy; deep tissue; blood flow
9.  Comparative Analysis of Methods for Identifying Recurrent Copy Number Alterations in Cancer 
PLoS ONE  2012;7(12):e52516.
Recurrent copy number alterations (CNAs) play an important role in cancer genesis. While a number of computational methods have been proposed for identifying such CNAs, their relative merits remain largely unknown in practice since very few efforts have been focused on comparative analysis of the methods. To facilitate studies of recurrent CNA identification in cancer genome, it is imperative to conduct a comprehensive comparison of performance and limitations among existing methods. In this paper, six representative methods proposed in the latest six years are compared. These include one-stage and two-stage approaches, working with raw intensity ratio data and discretized data respectively. They are based on various techniques such as kernel regression, correlation matrix diagonal segmentation, semi-parametric permutation and cyclic permutation schemes. We explore multiple criteria including type I error rate, detection power, Receiver Operating Characteristics (ROC) curve and the area under curve (AUC), and computational complexity, to evaluate performance of the methods under multiple simulation scenarios. We also characterize their abilities on applications to two real datasets obtained from cancers with lung adenocarcinoma and glioblastoma. This comparison study reveals general characteristics of the existing methods for identifying recurrent CNAs, and further provides new insights into their strengths and weaknesses. It is believed helpful to accelerate the development of novel and improved methods.
PMCID: PMC3527554  PMID: 23285074
10.  Noninvasive optical characterization of muscle blood flow, oxygenation, and metabolism in women with fibromyalgia 
Arthritis Research & Therapy  2012;14(6):R236.
Women with fibromyalgia (FM) have symptoms of increased muscular fatigue and reduced exercise tolerance, which may be associated with alterations in muscle microcirculation and oxygen metabolism. This study used near-infrared diffuse optical spectroscopies to noninvasively evaluate muscle blood flow, blood oxygenation and oxygen metabolism during leg fatiguing exercise and during arm arterial cuff occlusion in post-menopausal women with and without FM.
Fourteen women with FM and twenty-three well-matched healthy controls participated in this study. For the fatiguing exercise protocol, the subject was instructed to perform 6 sets of 12 isometric contractions of knee extensor muscles with intensity steadily increasing from 20 to 70% maximal voluntary isometric contraction (MVIC). For the cuff occlusion protocol, forearm arterial blood flow was occluded via a tourniquet on the upper arm for 3 minutes. Leg or arm muscle hemodynamics, including relative blood flow (rBF), oxy- and deoxy-hemoglobin concentration ([HbO2] and [Hb]), total hemoglobin concentration (THC) and blood oxygen saturation (StO2), were continuously monitored throughout protocols using a custom-built hybrid diffuse optical instrument that combined a commercial near-infrared oximeter for tissue oxygenation measurements and a custom-designed diffuse correlation spectroscopy (DCS) flowmeter for tissue blood flow measurements. Relative oxygen extraction fraction (rOEF) and oxygen consumption rate (rVO2) were calculated from the measured blood flow and oxygenation data. Post-manipulation (fatiguing exercise or cuff occlusion) recovery in muscle hemodynamics was characterized by the recovery half-time, a time interval from the end of manipulation to the time that tissue hemodynamics reached a half-maximal value.
Subjects with FM had similar hemodynamic and metabolic response/recovery patterns as healthy controls during exercise and during arterial occlusion. However, tissue rOEF during exercise in subjects with FM was significantly lower than in healthy controls, and the half-times of oxygenation recovery (Δ[HbO2] and Δ[Hb]) were significantly longer following fatiguing exercise and cuff occlusion.
Our results suggest an alteration of muscle oxygen utilization in the FM population. This study demonstrates the potential of using combined diffuse optical spectroscopies (i.e., NIRS/DCS) to comprehensively evaluate tissue oxygen and flow kinetics in skeletal muscle.
PMCID: PMC3674608  PMID: 23116302
11.  Diffuse optical monitoring of repeated cerebral ischemia in mice 
Optics Express  2011;19(21):20301-20315.
Occlusions of bilateral common carotid arteries (bi-CCA) in mice are popular models for the investigation of transient forebrain ischemia. Currently available technologies for assessing cerebral blood flow (CBF) and oxygenation in ischemic mice have limitations. This study tests a novel near-infrared diffuse correlation spectroscopy (DCS) flow-oximeter for monitoring both CBF and cerebral oxygenation in mice undergoing repeated transient forebrain ischemia. Concurrent flow measurements in a mouse brain were first conducted for validation purposes; DCS measurement was found highly correlated with laser Doppler measurement (R2 = 0.94) and less susceptible to motion artifacts. With unique designs in experimental protocols and fiber-optic probes, we have demonstrated high sensitivities of DCS flow-oximeter in detecting the regional heterogeneity of CBF responses in different hemispheres and global changes of both CBF and cerebral oxygenation across two hemispheres in mice undergoing repeated 2-minute bi-CCA occlusions over 5 days. More than 75% CBF reductions were found during bi-CCA occlusions in mice, which may be considered as a threshold to determine a successful bi-CCA occlusion. With the progress of repeated 2-minute bi-CCA occlusions over days, a longitudinal decline in the magnitudes of CBF reduction was observed, indicating the brain adaptation to cerebral ischemia through the repeated preconditioning.
PMCID: PMC3495871  PMID: 21997041
(170.0170) Medical optics and biotechnology; (170.3660) Light propagation in tissues; (170.3880) Medical and biological imaging; (170.6480) Spectroscopy, speckle
12.  Genome-wide identification of significant aberrations in cancer genome 
BMC Genomics  2012;13:342.
Somatic Copy Number Alterations (CNAs) in human genomes are present in almost all human cancers. Systematic efforts to characterize such structural variants must effectively distinguish significant consensus events from random background aberrations. Here we introduce Significant Aberration in Cancer (SAIC), a new method for characterizing and assessing the statistical significance of recurrent CNA units. Three main features of SAIC include: (1) exploiting the intrinsic correlation among consecutive probes to assign a score to each CNA unit instead of single probes; (2) performing permutations on CNA units that preserve correlations inherent in the copy number data; and (3) iteratively detecting Significant Copy Number Aberrations (SCAs) and estimating an unbiased null distribution by applying an SCA-exclusive permutation scheme.
We test and compare the performance of SAIC against four peer methods (GISTIC, STAC, KC-SMART, CMDS) on a large number of simulation datasets. Experimental results show that SAIC outperforms peer methods in terms of larger area under the Receiver Operating Characteristics curve and increased detection power. We then apply SAIC to analyze structural genomic aberrations acquired in four real cancer genome-wide copy number data sets (ovarian cancer, metastatic prostate cancer, lung adenocarcinoma, glioblastoma). When compared with previously reported results, SAIC successfully identifies most SCAs known to be of biological significance and associated with oncogenes (e.g., KRAS, CCNE1, and MYC) or tumor suppressor genes (e.g., CDKN2A/B). Furthermore, SAIC identifies a number of novel SCAs in these copy number data that encompass tumor related genes and may warrant further studies.
Supported by a well-grounded theoretical framework, SAIC has been developed and used to identify SCAs in various cancer copy number data sets, providing useful information to study the landscape of cancer genomes. Open–source and platform-independent SAIC software is implemented using C++, together with R scripts for data formatting and Perl scripts for user interfacing, and it is easy to install and efficient to use. The source code and documentation are freely available at
PMCID: PMC3428679  PMID: 22839576
13.  BACOM: in silico detection of genomic deletion types and correction of normal cell contamination in copy number data 
Bioinformatics  2011;27(11):1473-1480.
Motivation: Identification of somatic DNA copy number alterations (CNAs) and significant consensus events (SCEs) in cancer genomes is a main task in discovering potential cancer-driving genes such as oncogenes and tumor suppressors. The recent development of SNP array technology has facilitated studies on copy number changes at a genome-wide scale with high resolution. However, existing copy number analysis methods are oblivious to normal cell contamination and cannot distinguish between contributions of cancerous and normal cells to the measured copy number signals. This contamination could significantly confound downstream analysis of CNAs and affect the power to detect SCEs in clinical samples.
Results: We report here a statistically principled in silico approach, Bayesian Analysis of COpy number Mixtures (BACOM), to accurately estimate genomic deletion type and normal tissue contamination, and accordingly recover the true copy number profile in cancer cells. We tested the proposed method on two simulated datasets, two prostate cancer datasets and The Cancer Genome Atlas high-grade ovarian dataset, and obtained very promising results supported by the ground truth and biological plausibility. Moreover, based on a large number of comparative simulation studies, the proposed method gives significantly improved power to detect SCEs after in silico correction of normal tissue contamination. We develop a cross-platform open-source Java application that implements the whole pipeline of copy number analysis of heterogeneous cancer tissues including relevant processing steps. We also provide an R interface, bacomR, for running BACOM within the R environment, making it straightforward to include in existing data pipelines.
Availability: The cross-platform, stand-alone Java application, BACOM, the R interface, bacomR, all source code and the simulation data used in this article are freely available at authors' web site:
Supplementary Information: Supplementary data are available at Bioinformatics online.
PMCID: PMC3102226  PMID: 21498400
14.  PUGSVM: a caBIGTM analytical tool for multiclass gene selection and predictive classification 
Bioinformatics  2010;27(5):736-738.
Summary: Phenotypic Up-regulated Gene Support Vector Machine (PUGSVM) is a cancer Biomedical Informatics Grid (caBIG™) analytical tool for multiclass gene selection and classification. PUGSVM addresses the problem of imbalanced class separability, small sample size and high gene space dimensionality, where multiclass gene markers are defined by the union of one-versus-everyone phenotypic upregulated genes, and used by a well-matched one-versus-rest support vector machine. PUGSVM provides a simple yet more accurate strategy to identify statistically reproducible mechanistic marker genes for characterization of heterogeneous diseases.
Supplementary information: Supplementary data are available at Bioinformatics online.
PMCID: PMC3042183  PMID: 21186245
15.  Noninvasive diffuse optical monitoring of head and neck tumor blood flow and oxygenation during radiation delivery 
Biomedical Optics Express  2012;3(2):259-272.
This study explored using a novel diffuse correlation spectroscopy (DCS) flow-oximeter to noninvasively monitor blood flow and oxygenation changes in head and neck tumors during radiation delivery. A fiber-optic probe connected to the DCS flow-oximeter was placed on the surface of the radiologically/clinically involved cervical lymph node. The DCS flow-oximeter in the treatment room was remotely operated by a computer in the control room. From the early measurements, abnormal signals were observed when the optical device was placed in close proximity to the radiation beams. Through phantom tests, the artifacts were shown to be caused by scattered x rays and consequentially avoided by moving the optical device away from the x-ray beams. Eleven patients with head and neck tumors were continually measured once a week over a treatment period of seven weeks, although there were some missing data due to the patient related events. Large inter-patient variations in tumor hemodynamic responses were observed during radiation delivery. A significant increase in tumor blood flow was observed at the first week of treatment, which may be a physiologic response to hypoxia created by radiation oxygen consumption. Only small and insignificant changes were found in tumor blood oxygenation, suggesting that oxygen utilizations in tumors during the short period of fractional radiation deliveries were either minimal or balanced by other effects such as blood flow regulation. Further investigations in a large patient population are needed to correlate the individual hemodynamic responses with the clinical outcomes for determining the prognostic value of optical measurements.
PMCID: PMC3269843  PMID: 22312579
(170.0170) Medical optics and biotechnology; (170.3660) Light propagation in tissues; (170.3880) Medical and biological imaging; (170.6480) Spectroscopy, speckle
16.  Direct measurement of tissue blood flow and metabolism with diffuse optics 
Diffuse optics has proven useful for quantitative assessment of tissue oxy- and deoxyhaemoglobin concentrations and, more recently, for measurement of microvascular blood flow. In this paper, we focus on the flow monitoring technique: diffuse correlation spectroscopy (DCS). Representative clinical and pre-clinical studies from our laboratory illustrate the potential of DCS. Validation of DCS blood flow indices in human brain and muscle is presented. Comparison of DCS with arterial spin-labelled MRI, xenon-CT and Doppler ultrasound shows good agreement (0.50
PMCID: PMC3263785  PMID: 22006897
diffuse correlation spectroscopy; blood flow; cerebral blood flow; oxygen metabolism; brain; cancer
Journal of biomedical optics  2009;14(3):034015.
We used a nonimpact inertial rotational model of a closed head injury in neonatal piglets to simulate the conditions following traumatic brain injury in infants. Diffuse optical techniques, including diffuse reflectance spectroscopy and diffuse correlation spectroscopy (DCS), were used to measure cerebral blood oxygenation and blood flow continuously and noninvasively before injury and up to 6 h after the injury. The DCS measurements of relative cerebral blood flow were validated against the fluorescent microsphere method. A strong linear correlation was observed between the two techniques (R = 0.89, p < 0.00001). Injury-induced cerebral hemodynamic changes were quantified, and significant changes were found in oxy- and deoxy-hemoglobin concentrations, total hemoglobin concentration, blood oxygen saturation, and cerebral blood flow after the injury. The diffuse optical measurements were robust and also correlated well with recordings of vital physiological parameters over the 6-h monitoring period, such as mean arterial blood pressure, arterial oxygen saturation, and heart rate. Finally, the diffuse optical techniques demonstrated sensitivity to dynamic physiological events, such as apnea, cardiac arrest, and hypertonic saline infusion. In total, the investigation corraborates potential of the optical methods for bedside monitoring of pediatric and adult human patients in the neurointensive care unit.
PMCID: PMC3169814  PMID: 19566308
diffuse correlation spectroscopy (DCS); diffuse reflectance spectroscopy (DRS); cerebral hemodynamics; cerebral blood flow; traumatic brain injury; near—infrared spectroscopy (NIRS)
Radiation research  2010;174(3):331-340.
Photodynamic therapy (PDT) with low light fluence rate has rarely been studied in protocols that use short drug–light intervals and thus deliver illumination while plasma concentrations of photosensitizer are high, creating a prominent vascular response. In this study, the effects of light fluence rate on PDT response were investigated using motexafin lutetium (10 mg/kg) in combination with 730 nm light and a 180-min drug–light interval. At 180 min, the plasma level of photosensitizer was 5.7 ng/μl compared to 3.1 ng/mg in RIF tumor, and PDT-mediated vascular effects were confirmed by a spasmodic decrease in blood flow during illumination. Light delivery at 25 mW/cm2 significantly improved long-term tumor responses over that at 75 mW/cm2. This effect could not be attributed to oxygen conservation at low fluence rate, because 25 mW/cm2 PDT provided little benefit to tumor hemoglobin oxygen saturation. However, 25 mW/cm2 PDT did prolong the duration of ischemic insult during illumination and was correspondingly associated with greater decreases in perfusion immediately after PDT, followed by smaller increases in total hemoglobin concentration in the hours after PDT. Increases in blood volume suggest blood pooling from suboptimal vascular damage; thus the smaller increases after 25 mW/cm2 PDT provide evidence of more widespread vascular damage, which was accompanied by greater decreases in clonogenic survival. Further study of low fluence rate as a means to improve responses to PDT under conditions designed to predominantly damage vasculature is warranted.
PMCID: PMC2995951  PMID: 20726728
BMC Genomics  2011;12:344.
Interactions among genetic loci are believed to play an important role in disease risk. While many methods have been proposed for detecting such interactions, their relative performance remains largely unclear, mainly because different data sources, detection performance criteria, and experimental protocols were used in the papers introducing these methods and in subsequent studies. Moreover, there have been very few studies strictly focused on comparison of existing methods. Given the importance of detecting gene-gene and gene-environment interactions, a rigorous, comprehensive comparison of performance and limitations of available interaction detection methods is warranted.
We report a comparison of eight representative methods, of which seven were specifically designed to detect interactions among single nucleotide polymorphisms (SNPs), with the last a popular main-effect testing method used as a baseline for performance evaluation. The selected methods, multifactor dimensionality reduction (MDR), full interaction model (FIM), information gain (IG), Bayesian epistasis association mapping (BEAM), SNP harvester (SH), maximum entropy conditional probability modeling (MECPM), logistic regression with an interaction term (LRIT), and logistic regression (LR) were compared on a large number of simulated data sets, each, consistent with complex disease models, embedding multiple sets of interacting SNPs, under different interaction models. The assessment criteria included several relevant detection power measures, family-wise type I error rate, and computational complexity. There are several important results from this study. First, while some SNPs in interactions with strong effects are successfully detected, most of the methods miss many interacting SNPs at an acceptable rate of false positives. In this study, the best-performing method was MECPM. Second, the statistical significance assessment criteria, used by some of the methods to control the type I error rate, are quite conservative, thereby limiting their power and making it difficult to fairly compare them. Third, as expected, power varies for different models and as a function of penetrance, minor allele frequency, linkage disequilibrium and marginal effects. Fourth, the analytical relationships between power and these factors are derived, aiding in the interpretation of the study results. Fifth, for these methods the magnitude of the main effect influences the power of the tests. Sixth, most methods can detect some ground-truth SNPs but have modest power to detect the whole set of interacting SNPs.
This comparison study provides new insights into the strengths and limitations of current methods for detecting interacting loci. This study, along with freely available simulation tools we provide, should help support development of improved methods. The simulation tools are available at:
PMCID: PMC3161015  PMID: 21729295
Biomedical Optics Express  2011;2(7):1969-1985.
In this study we evaluate the influences of optical property assumptions on near-infrared diffuse correlation spectroscopy (DCS) flow index measurements. The optical properties, absorption coefficient (µa) and reduced scattering coefficient (µs′), are independently varied using liquid phantoms and measured concurrently with the flow index using a hybrid optical system combining a dual-wavelength DCS flow device with a commercial frequency-domain tissue-oximeter. DCS flow indices are calculated at two wavelengths (785 and 830 nm) using measured µa and µs′ or assumed constant µa and µs′. Inaccurate µs′ assumptions resulted in much greater flow index errors than inaccurate µa. Underestimated/overestimated µs′ from −35%/+175% lead to flow index errors of +110%/−80%, whereas underestimated/overestimated µa from −40%/+150% lead to −20%/+40%, regardless of the wavelengths used. Examination of a clinical study involving human head and neck tumors indicates up to +280% flow index errors resulted from inter-patient optical property variations. These findings suggest that studies involving significant µa and µs′ changes should concurrently measure flow index and optical properties for accurate extraction of blood flow information.
PMCID: PMC3130582  PMID: 21750773
(170.0170) Medical optics and biotechnology; (170.3660) Light propagation in tissues; (170.3880) Medical and biological imaging; (170.6480) Spectroscopy, speckle
Neurocritical care  2010;12(2):173-180.
This study assesses the utility of a hybrid optical instrument for noninvasive transcranial monitoring in the neurointensive care unit. The instrument is based on diffuse correlation spectroscopy (DCS) for measurement of cerebral blood flow (CBF), and near-infrared spectroscopy (NIRS) for measurement of oxy- and deoxy-hemoglobin concentration. DCS/NIRS measurements of CBF and oxygenation from frontal lobes are compared with concurrent xenon-enhanced computed tomography (XeCT) in patients during induced blood pressure changes and carbon dioxide arterial partial pressure variation.
Seven neurocritical care patients were included in the study. Relative CBF measured by DCS (rCBFDCS), and changes in oxy-hemoglobin (ΔHbO2), deoxy-hemoglobin (ΔHb), and total hemoglobin concentration (ΔTHC), measured by NIRS, were continuously monitored throughout XeCT during a baseline scan and a scan after intervention. CBF from XeCT regions-of-interest (ROIs) under the optical probes were used to calculate relative XeCT CBF (rCBFXeCT) and were then compared to rCBFDCS. Spearman’s rank coefficients were employed to test for associations between rCBFDCS and rCBFXeCT, as well as between rCBF from both modalities and NIRS parameters.
rCBFDCS and rCBFXeCT showed good correlation (rs = 0.73, P = 0.010) across the patient cohort. Moderate correlations between rCBFDCS and ΔHbO2/ΔTHC were also observed. Both NIRS and DCS distinguished the effects of xenon inhalation on CBF, which varied among the patients.
DCS measurements of CBF and NIRS measurements of tissue blood oxygenation were successfully obtained in neurocritical care patients. The potential for DCS to provide continuous, noninvasive bedside monitoring for the purpose of CBF management and individualized care is demonstrated.
PMCID: PMC2844468  PMID: 19908166
Near-infrared spectroscopy; Diffuse correlation spectroscopy; Cerebral blood flow; Xenon CT; Neurocritical care
Genome-wide association studies (GWAS) have been widely applied to identify informative SNPs associated with common and complex diseases. Besides single-SNP analysis, the interaction between SNPs is believed to play an important role in disease risk due to the complex networking of genetic regulations. While many approaches have been proposed for detecting SNP interactions, the relative performance and merits of these methods in practice are largely unclear. In this paper, a ground-truth based comparative study is reported involving 9 popular SNP detection methods using realistic simulation datasets. The results provide general characteristics and guidelines on these methods that may be informative to the biological investigators.
PMCID: PMC2998769  PMID: 21151836
Genome-wide association study; single-nucleotide polymorphism; SNP interaction
Photodynamic therapy (PDT) can lead to the creation of heterogeneous, response-limiting hypoxia during illumination, which may be controlled in part through illumination fluence rate. In the present report we consider 1) regional differences in hypoxia, vascular response, and cell kill as a function of tumor depth and 2) the role of fluence rate as a mediator of depth-dependent regional intratumor heterogeneity. Intradermal RIF murine tumors were treated with Photofrin-PDT using surface illumination at an irradiance of 75 or 38 mW/cm2. Regional heterogeneity in tumor response was examined through comparison of effects in the surface vs. base of tumors, i.e. along a plane parallel to the skin surface and perpendicular to the incident illumination. 75 mW/cm2-PDT created significantly greater hypoxia in tumor bases relative to their surfaces. Increased hypoxia in the tumor base could not be attributed to regional differences in Photofrin concentration nor effects of fluence rate distribution on photochemical oxygen consumption, but significant depth-dependent heterogeneity in vascular responses and cytotoxic response were detected. At a lower fluence rate of 38 mW/cm2, no detectable regional differences in hypoxia or cytotoxic responses were apparent, and heterogeneity in vascular response was significantly less than that during 75 mW/cm2-PDT. This research suggests that the benefits of low-fluence-rate-PDT are mediated in part by a reduction in intratumor heterogeneity in hypoxic, vascular and cytotoxic responses.
PMCID: PMC2834171  PMID: 20024165
photodynamic therapy; fluence rate; hypoxia; EF3; blood flow
Bioinformatics  2009;25(19):2478-2485.
Motivation: In both genome-wide association studies (GWAS) and pathway analysis, the modest sample size relative to the number of genetic markers presents formidable computational, statistical and methodological challenges for accurately identifying markers/interactions and for building phenotype-predictive models.
Results: We address these objectives via maximum entropy conditional probability modeling (MECPM), coupled with a novel model structure search. Unlike neural networks and support vector machines (SVMs), MECPM makes explicit and is determined by the interactions that confer phenotype-predictive power. Our method identifies both a marker subset and the multiple k-way interactions between these markers. Additional key aspects are: (i) evaluation of a select subset of up to five-way interactions while retaining relatively low complexity; (ii) flexible single nucleotide polymorphism (SNP) coding (dominant, recessive) within each interaction; (iii) no mathematical interaction form assumed; (iv) model structure and order selection based on the Bayesian Information Criterion, which fairly compares interactions at different orders and automatically sets the experiment-wide significance level; (v) MECPM directly yields a phenotype-predictive model. MECPM was compared with a panel of methods on datasets with up to 1000 SNPs and up to eight embedded penetrance function (i.e. ground-truth) interactions, including a five-way, involving less than 20 SNPs. MECPM achieved improved sensitivity and specificity for detecting both ground-truth markers and interactions, compared with previous methods.
Supplementary information:Supplementary data are available at Bioinformatics online.
PMCID: PMC3140808  PMID: 19608708
Biomedical Optics Express  2010;1(2):500-511.
The influence of muscle fiber motion during exercise on diffuse correlation spectroscopy (DCS) measurements of skeletal muscle blood flow is explored. Isotonic (with muscle fiber motion) and isometric (without muscle fiber motion) plantar flexion exercises were performed at 30% of maximal force on a dynamometer, and muscle blood flow was continuously monitored on the medial gastrocnemius (calf) muscle of a healthy volunteer using DCS. During exercise, dynamometer recordings including footplate position, footplate angular velocity, and plantar flexion torque were obtained. Muscle fiber motions introduced artifacts into the DCS signals, causing an overestimation of blood flow changes. We show how proper co-registration of dynamometer recordings and DCS measurements enables separation of the true blood flow responses during exercise from those affected by the motion artifacts.
PMCID: PMC3018004  PMID: 21258485
(170.0170) Medical optics and biotechnology; (170.3660) Light propagation in tissues; (170.3880) Medical and biological imaging; (170.6480) Spectroscopy, speckle

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