Maximum Likelihood Estimation of Exponentials in Unknown Colored Noise for Target Identification in Synthetic Aperture Radar Images

This dissertation develops techniques for estimating exponential signals in unknown colored noise. The Maximum Likelihood (ML) estimators of the exponential parameters are developed. Techniques are developed for one and two dimensional exponentials, for both the deterministic and stochastic ML model. The techniques are applied to Synthetic Aperture Radar (SAR) data whose point scatterers are modeled as damped exponentials. These estimated scatterer locations (exponentials frequencies) are potential features for model-based target recognition. The estimators developed in this dissertation may be applied with any parametrically modeled noise having a zero mean and a consistent estimator of the noise covariance matrix. ML techniques are developed for a single instance of data in colored noise which is modeled in one dimension as (1) stationary noise, (2) autoregressive (AR) noise and (3) autoregressive moving-average (ARMA) noise and in two dimensions as (1) stationary noise, and (2) white noise driving an exponential filter. The classical ML approach is used to solve for parameters which can be decoupled from the estimation problem. The remaining nonlinear optimization to find the exponential frequencies is then solved by extending white noise ML techniques to colored noise. In the case of deterministic ML, the computationally efficient, one and two-dimensional Iterative Quadratic Maximum Likelihood (IQML) methods are extended to colored noise. In the case of stochastic ML, the one and two-dimensional Method of Direction Estimation (MODE) techniques are extended to colored noise. Simulations show that the techniques perform close to the Cramer-Rao bound when the model matches the observed noise

Maximum Likelihood Estimation of Exponentials in Unknown Colored Noise for Target in Identification Synthetic Aperture Radar Images

This dissertation develops techniques for estimating exponential signals in unknown colored noise. The Maximum Likelihood ML estimators of the exponential parameters are developed. Techniques are developed for one and two dimensional exponentials, for both the deterministic and stochastic ML model. The techniques are applied to Synthetic Aperture Radar SAR data whose point scatterers are modeled as damped exponentials. These estimated scatterer locations exponentials frequencies are potential features for model-based target recognition. The estimators developed in this dissertation may be applied with any parametrically modeled noise having a zero mean and a consistent estimator of the noise covariance matrix. ML techniques are developed for a single instance of data in colored noise which is modeled in one dimension as 1 stationary noise, 2 autoregressive AR noise and 3 autoregressive moving-average ARMA noise and in two dimensions as 1 stationary noise, and 2 white noise driving an exponential filter. The classical ML approach is used to solve for parameters which can be decoupled from the estimation problem. The remaining nonlinear optimization to find the exponential frequencies is then solved by extending white noise ML techniques to colored noise. In the case of deterministic ML, the computationally efficient, one and two-dimensional Iterative Quadratic Maximum Likelihood IQML methods are extended to colored noise. In the case of stochastic ML, the one and two-dimensional Method of Direction Estimation MODE techniques are extended to colored noise. Simulations show that the techniques perform close to the Cramer-Rao bound when the model matches the observed noise

Inhibition of Myostatin Signaling through Notch Activation following Acute Resistance Exercise

Myostatin is a TGFb family member and negative regulator of muscle size. Due to the complexity of the molecular pathway between myostatin mRNA/protein and changes in transcription, it has been difficult to understand whether myostatin plays a role in resistance exercise-induced skeletal muscle hypertrophy. To circumvent this problem, we determined the expression of a unique myostatin target gene, Mighty, following resistance exercise. Mighty mRNA increased by 6 h (82.9624.21%) and remained high out to 48 h (56.5619.67%) after resistance exercise. Further examination of the soleus, plantaris and tibialis anterior muscles showed that the change in Mighty mRNA at 6 h correlated with the increase in muscle size associated with this protocol (R2 = 0.9996). The increase in Mighty mRNA occurred both independent of Smad2 phosphorylation and in spite of an increase in myostatin mRNA (341.86147.14% at 3 h). The myostatin inhibitor SKI remained unchanged. However, activated Notch, another potential inhibitor of TGFb signaling, increased immediately following resistance exercise (83611.2%) and stayed elevated out to 6 h (78616.6%). Electroportion of the Notch intracellular domain into the tibialis anterior resulted in an increase in Mighty mRNA (63613.4%) that was equivalent to the canonical Notch target HES-1 (94.467.32%). These data suggest that acute resistance exercise decreases myostatin signaling through the activation of the TGFb inhibitor Notch resulting in a decrease in myostatin transcriptional activity that correlates well with muscle hypertrophy

Hepatitis C Virus Infection in Guinea-Bissau: A Sexually Transmitted Genotype 2 with Parenteral Amplification?

BACKGROUND: Sub-Saharan Africa is the continent with the highest prevalence of Hepatitis C virus (HCV) infection. Genotype 2 HCV is thought to have originated from West Africa several hundred years ago. Mechanisms of transmission remain poorly understood. METHODOLOGY/PRINCIPAL FINDINGS: To delineate mechanisms for HCV transmission in West Africa, we conducted a cross-sectional survey of individuals aged ≥50 years in Bissau, Guinea-Bissau. Dried blood spots were obtained for HCV serology and PCR amplification. Prevalence of HCV was 4.4% (47/1066) among women and 5.0% (27/544) among men. In multivariate analysis, the independent risk factors for HCV infection were age (baseline: 50–59 y; 60–69 y, adjusted odds ratio [AOR]: 1.67, 95% CI: 0.91–3.06; ≥70 y, AOR: 3.47, 95% CI: 1.89–6.39), belonging to the Papel, Mancanha, Balanta or Mandjako ethnic groups (AOR: 2.45, 95% CI:1.32–4.53), originating from the Biombo, Cacheu or Oio regions north of Bissau (AOR: 4.16, 95% CI: 1.18–14.73) and having bought or sold sexual services (AOR: 3.60, 95% CI: 1.88–6.89). Of 57 isolates that could be genotyped, 56 were genotype 2. CONCLUSIONS: Our results suggest that transmission of HCV genotype 2 in West Africa occurs through sexual intercourse. In specific locations and subpopulations, medical interventions may have amplified transmission parenterally

Molecular Epidemiology of Endemic Human T-Lymphotropic Virus Type 1 in a Rural Community in Guinea-Bissau

Human T-Lymphotropic Virus type 1 (HTLV-1) affects millions of people worldwide. It is very similar to Simian T-Lymphotropic Virus, a virus that circulates in monkeys. HTLV-1 causes a lethal form of leukemia (Adult T-cell Leukemia) and a debilitating neurological syndrome (HTLV-associated myelopathy/tropical spastic paraparesis) in approximately 5% of infected people. Based on sequence variation, HTLV-1 can be divided into 7 subtypes (1a–1g) with the Cosmopolitan subtype 1a further subdivided into subgroups (A–E). We examined HTLV-1 diversity in a rural area in Guinea-Bissau, a country in West Africa with a high HTLV-1 prevalence (5%). We found that most viruses belong to the Cosmopolitan subtype 1a, subgroup D, but 2 viruses belonged to subtype 1g. This subtype had thus far only been found in monkey hunters in Cameroon, who were probably recently infected by monkeys. Our findings indicate that this subtype has spread beyond Central Africa. An important, unresolved question is whether persons with this subtype were infected by monkeys or through human-to-human transmission

Role of CCL3L1-CCR5 Genotypes in the Epidemic Spread of HIV-1 and Evaluation of Vaccine Efficacy

Polymorphisms in CCR5, the major coreceptor for HIV, and CCL3L1, a potent CCR5 ligand and HIV-suppressive chemokine, are determinants of HIV-AIDS susceptibility. Here, we mathematically modeled the potential impact of these genetic factors on the epidemic spread of HIV, as well as on its prevention.Ro, the basic reproductive number, is a fundamental concept in explaining the emergence and persistence of epidemics. By modeling sexual transmission among HIV+/HIV- partner pairs, we find that Ro estimates, and concordantly, the temporal and spatial patterns of HIV outgrowth are highly dependent on the infecting partners' CCL3L1-CCR5 genotype. Ro was least and highest when the infected partner possessed protective and detrimental CCL3L1-CCR5 genotypes, respectively. The modeling data indicate that in populations such as Pygmies with a high CCL3L1 gene dose and protective CCR5 genotypes, the spread of HIV might be minimal. Additionally, Pc, the critical vaccination proportion, an estimate of the fraction of the population that must be vaccinated successfully to eradicate an epidemic was <1 only when the infected partner had a protective CCL3L1-CCR5 genotype. Since in practice Pc cannot be >1, to prevent epidemic spread, population groups defined by specific CCL3L1-CCR5 genotypes might require repeated vaccination, or as our models suggest, a vaccine with an efficacy of >70%. Further, failure to account for CCL3L1-CCR5-based genetic risk might confound estimates of vaccine efficacy. For example, in a modeled trial of 500 subjects, misallocation of CCL3L1-CCR5 genotype of only 25 (5%) subjects between placebo and vaccine arms results in a relative error of approximately 12% from the true vaccine efficacy.CCL3L1-CCR5 genotypes may impact on the dynamics of the HIV epidemic and, consequently, the observed heterogeneous global distribution of HIV infection. As Ro is lowest when the infecting partner has beneficial CCL3L1-CCR5 genotypes, we infer that therapeutic vaccines directed towards reducing the infectivity of the host may play a role in halting epidemic spread. Further, CCL3L1-CCR5 genotype may provide critical guidance for optimizing the design and evaluation of HIV-1 vaccine trials and prevention programs

Benthic and Hyporheic Macroinvertebrate Distribution Within the Heads and Tails of Riffles During Baseflow Conditions

The distribution of lotic fauna is widely acknowledged to be patchy reflecting the interaction between biotic and abiotic factors. In an in-situ field study, the distribution of benthic and hyporheic invertebrates in the heads (downwelling) and tails (upwelling) of riffles were examined during stable baseflow conditions. Riffle heads were found to contain a greater proportion of interstitial fine sediment than riffle tails. Significant differences in the composition of benthic communities were associated with the amount of fine sediment. Riffle tail habitats supported a greater abundance and diversity of invertebrates sensitive to fine sediment such as EPT taxa. Shredder feeding taxa were more abundant in riffle heads suggesting greater availability of organic matter. In contrast, no significant differences in the hyporheic community were recorded between riffle heads and tails. We hypothesise that clogging of hyporheic interstices with fine sediments may have resulted in the homogenization of the invertebrate community by limiting faunal movement into the hyporheic zone at both the riffle head and tail. The results suggest that vertical hydrological exchange significantly influences the distribution of fine sediment and macroinvertebrate communities at the riffle scale

A framework for human microbiome research

A variety of microbial communities and their genes (the microbiome) exist throughout the human body, with fundamental roles in human health and disease. The National Institutes of Health (NIH)-funded Human Microbiome Project Consortium has established a population-scale framework to develop metagenomic protocols, resulting in a broad range of quality-controlled resources and data including standardized methods for creating, processing and interpreting distinct types of high-throughput metagenomic data available to the scientific community. Here we present resources from a population of 242 healthy adults sampled at 15 or 18 body sites up to three times, which have generated 5,177 microbial taxonomic profiles from 16S ribosomal RNA genes and over 3.5 terabases of metagenomic sequence so far. In parallel, approximately 800 reference strains isolated from the human body have been sequenced. Collectively, these data represent the largest resource describing the abundance and variety of the human microbiome, while providing a framework for current and future studies

Structure, function and diversity of the healthy human microbiome

Author Posting. © The Authors, 2012. This article is posted here by permission of Nature Publishing Group. The definitive version was published in Nature 486 (2012): 207-214, doi:10.1038/nature11234.Studies of the human microbiome have revealed that even healthy individuals differ remarkably in the microbes that occupy habitats such as the gut, skin and vagina. Much of this diversity remains unexplained, although diet, environment, host genetics and early microbial exposure have all been implicated. Accordingly, to characterize the ecology of human-associated microbial communities, the Human Microbiome Project has analysed the largest cohort and set of distinct, clinically relevant body habitats so far. We found the diversity and abundance of each habitat’s signature microbes to vary widely even among healthy subjects, with strong niche specialization both within and among individuals. The project encountered an estimated 81–99% of the genera, enzyme families and community configurations occupied by the healthy Western microbiome. Metagenomic carriage of metabolic pathways was stable among individuals despite variation in community structure, and ethnic/racial background proved to be one of the strongest associations of both pathways and microbes with clinical metadata. These results thus delineate the range of structural and functional configurations normal in the microbial communities of a healthy population, enabling future characterization of the epidemiology, ecology and translational applications of the human microbiome.This research was supported in part by National Institutes of Health grants U54HG004969 to B.W.B.; U54HG003273 to R.A.G.; U54HG004973 to R.A.G., S.K.H. and J.F.P.; U54HG003067 to E.S.Lander; U54AI084844 to K.E.N.; N01AI30071 to R.L.Strausberg; U54HG004968 to G.M.W.; U01HG004866 to O.R.W.; U54HG003079 to R.K.W.; R01HG005969 to C.H.; R01HG004872 to R.K.; R01HG004885 to M.P.; R01HG005975 to P.D.S.; R01HG004908 to Y.Y.; R01HG004900 to M.K.Cho and P. Sankar; R01HG005171 to D.E.H.; R01HG004853 to A.L.M.; R01HG004856 to R.R.; R01HG004877 to R.R.S. and R.F.; R01HG005172 to P. Spicer.; R01HG004857 to M.P.; R01HG004906 to T.M.S.; R21HG005811 to E.A.V.; M.J.B. was supported by UH2AR057506; G.A.B. was supported by UH2AI083263 and UH3AI083263 (G.A.B., C. N. Cornelissen, L. K. Eaves and J. F. Strauss); S.M.H. was supported by UH3DK083993 (V. B. Young, E. B. Chang, F. Meyer, T. M. S., M. L. Sogin, J. M. Tiedje); K.P.R. was supported by UH2DK083990 (J. V.); J.A.S. and H.H.K. were supported by UH2AR057504 and UH3AR057504 (J.A.S.); DP2OD001500 to K.M.A.; N01HG62088 to the Coriell Institute for Medical Research; U01DE016937 to F.E.D.; S.K.H. was supported by RC1DE0202098 and R01DE021574 (S.K.H. and H. Li); J.I. was supported by R21CA139193 (J.I. and D. S. Michaud); K.P.L. was supported by P30DE020751 (D. J. Smith); Army Research Office grant W911NF-11-1-0473 to C.H.; National Science Foundation grants NSF DBI-1053486 to C.H. and NSF IIS-0812111 to M.P.; The Office of Science of the US Department of Energy under Contract No. DE-AC02-05CH11231 for P.S. C.; LANL Laboratory-Directed Research and Development grant 20100034DR and the US Defense Threat Reduction Agency grants B104153I and B084531I to P.S.C.; Research Foundation - Flanders (FWO) grant to K.F. and J.Raes; R.K. is an HHMI Early Career Scientist; Gordon&BettyMoore Foundation funding and institutional funding fromthe J. David Gladstone Institutes to K.S.P.; A.M.S. was supported by fellowships provided by the Rackham Graduate School and the NIH Molecular Mechanisms in Microbial Pathogenesis Training Grant T32AI007528; a Crohn’s and Colitis Foundation of Canada Grant in Aid of Research to E.A.V.; 2010 IBM Faculty Award to K.C.W.; analysis of the HMPdata was performed using National Energy Research Scientific Computing resources, the BluBioU Computational Resource at Rice University

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead