Analysis and classification of 1H-NMR spectra by multifractal analysis.

The objective of this research focuses on the development of a statistical methodology able to answer the question of whether variation in the intake of sulfur amino acids (SAA) affects the metabolic process. Traditional approaches, which evaluate specific biomarkers after a series of preprocessing procedures, have been criticized as not being fully informative, as well as inappropriate for translation of methodology. Rather than focusing on particular biomarkers, our proposed methodology involves the multifractal analysis that measures the inhomogeneity of regularity of the proton nuclear magnetic resonance (1H-NMR) spectrum by wavelet-based multifractal spectrum. With two different statistical models (Model-I and Model-II), three different geometric features of the multifractal spectrum of each 1H-NMR spectrum (spectral mode, left slope, and broadness) are employed to evaluate the effect of SAA and discriminate 1H-NMR spectra associated with different treatments. The investigated effects of SAA include group effect (high and low doses of SAA), depletion/repletion effect, and time over data effect. The 1H-NMR spectra analysis outcomes show that group effect is significant for both models. The hourly variation in time and depletion/repletion effects does not show noticeable differences for the three features in Model-I. However, these two effects are significant for the spectral mode feature in Model-II. The 1H-NMR spectra of the SAA low groups exhibit highly regular patterns with more variability than that of the SAA high groups for both models. Moreover, the discriminatory analysis conducted using the support vector machine and the principal components analysis shows that the 1H-NMR spectra of SAA high and low groups can be easily discriminatory for both models, while the spectra of depletion and repletion within these groups are discriminatory for Model-I and Model-II. Therefore, the study outcomes imply that the amount of SAA is important and that SAA intake affects mostly the hourly variation of the metabolic process and the difference between depletion and repletion each day. In conclusion, the proposed multifractal analysis of 1H-NMR spectra provides a novel tool to investigate metabolic processes.

Early detection of ovarian cancer by wavelet analysis of protein mass spectra.

Accurate and efficient detection of ovarian cancer at early stages is critical to ensure proper treatments for patients. Among the first-line modalities investigated in studies of early diagnosis are features distilled from protein mass spectra. This method, however, considers only a specific subset of spectral responses and ignores the interplay among protein expression levels, which can also contain diagnostic information. We propose a new modality that automatically searches protein mass spectra for discriminatory features by considering the self-similar nature of the spectra. Self-similarity is assessed by taking a wavelet decomposition of protein mass spectra and estimating the rate of level-wise decay in the energies of the resulting wavelet coefficients. Level-wise energies are estimated in a robust manner using distance variance, and rates are estimated locally via a rolling window approach. This results in a collection of rates that can be used to characterize the interplay among proteins, which can be indicative of cancer presence. Discriminatory descriptors are then selected from these evolutionary rates and used as classifying features. The proposed wavelet-based features are used in conjunction with features proposed in the existing literature for early stage diagnosis of ovarian cancer using two datasets published by the American National Cancer Institute. Including the wavelet-based features from the new modality results in improvements in diagnostic performance for early-stage ovarian cancer detection. This demonstrates the ability of the proposed modality to characterize new ovarian cancer diagnostic information.

Wavelet-based approach for diagnosing attention deficit hyperactivity disorder (ADHD).

Attention deficit hyperactivity disorder (ADHD) is a common cognitive disorder affecting children. ADHD can interfere with educational, social, and emotional development, so early detection is essential for obtaining proper care. Standard ADHD diagnostic protocols rely heavily on subjective assessments of perceived behavior. An objective diagnostic measure would be a welcome development and potentially aid in accurately and efficiently diagnosing ADHD. Analysis of pupillary dynamics has been proposed as a promising alternative method of detecting affected individuals effectively. This study proposes a method based on the self-similarity of pupillary dynamics and assesses its strength as a potential diagnostic biomarker. Localized discriminatory features are developed in the wavelet domain and selected via a rolling window method to build classifiers. The application on a task-based pupil diameter time series dataset of children aged 10-12 years shows that the proposed method achieves greater than 78% accuracy in detecting ADHD. Comparing with a recent approach that constructs features in the original data domain, the proposed wavelet-based classifier achieves more accurate ADHD classification with fewer features. The findings suggest that the proposed diagnostic procedure involving interpretable wavelet-based self-similarity features of pupil diameter data can potentially aid in improving the efficacy of ADHD diagnosis.

Three-Dimensional Field Optimization Method: Gold-Standard Validation of a Novel Color Doppler Method for Quantifying Mitral Regurgitation.

BACKGROUND: Accurate diagnosis of mitral regurgitation (MR) severity is central to proper treatment. Although numerous approaches exist, an accurate, gold-standard clinical technique remains elusive. The authors previously reported on the initial development and demonstration of the automated three-dimensional (3D) field optimization method (FOM) algorithm, which exploits 3D color Doppler ultrasound imaging and builds on existing MR quantification techniques. The aim of the present study was to extensively validate 3D FOM in terms of accuracy, ease of use, and repeatability. METHODS: Three-dimensional FOM was applied to five explanted ovine mitral valves in a left heart simulator, which were systematically perturbed to yield a total of 29 unique regurgitant geometries. Three-dimensional FOM was compared with a gold-standard flow probe, as well as the most clinically prevalent MR volume quantification technique, the two-dimensional (2D) proximal isovelocity surface area (PISA) method. RESULTS: Overall, 3D FOM overestimated and 2D PISA underestimated MR volume, but 3D FOM error had smaller magnitude (5.2 ± 9.9 mL) than 2D PISA error (-6.9 ± 7.7 mL). Two-dimensional PISA remained superior in diagnosis for round orifices and especially mild MR, as predicted by ultrasound physics theory. For slit-type orifices and severe MR, 3D FOM showed significant improvement over 2D PISA. Three-dimensional FOM processing was technically simpler and significantly faster than 2D PISA and required fewer ultrasound acquisitions. Three-dimensional FOM did not show significant interuser variability, whereas 2D PISA did. CONCLUSIONS: Three-dimensional FOM may provide increased clinical value compared with 2D PISA because of increased accuracy in the case of complex or severe regurgitant orifices as well as its greater repeatability and simpler work flow.

Characterizing exons and introns by regularity of nucleotide strings.

BACKGROUND: Translation of nucleotides into a numeric form has been approached in many ways and has allowed researchers to investigate the properties of protein-coding sequences and noncoding sequences. Typically, more pronounced long-range correlations and increased regularity were found in intron-containing genes and in non-transcribed regulatory DNA sequences, compared to cDNA sequences or intron-less genes. The regularity is assessed by spectral tools defined on numerical translates. In most popular approaches of numerical translation the resulting spectra depend on the assignment of numerical values to nucleotides. Our contribution is to propose and illustrate a spectra which remains invariant to the translation rules used in traditional approaches. RESULTS: We outline a methodology for representing sequences of DNA nucleotides as numeric matrices in order to analytically investigate important structural characteristics of DNA. This representation allows us to compute the 2-dimensional wavelet transformation and assess regularity characteristics of the sequence via the slope of the wavelet spectra. In addition to computing a global slope measure for a sequence, we can apply our methodology for overlapping sections of nucleotides to obtain an "evolutionary slope." To illustrate our methodology, we analyzed 376 gene sequences from the first chromosome of the honeybee. CONCLUSION: For the genes analyzed, we find that introns are significantly more regular (lead to more negative spectral slopes) than exons, which agrees with the results from the literature where regularity is measured on "DNA walks". However, unlike DNA walks where the nucleotides are assigned numerical values depending on nucleotide characteristics (purine-pyrimidine, weak-strong hydrogen bonds, keto-amino, etc.) or other spatial assignments, the proposed spectral tool is invariant to the assignment of nucleotides. Thus, ambiguity in numerical translation of nucleotides is eliminated.

A combined evidence Bayesian method for human ancestry inference applied to Afro-Colombians.

Uniparental genetic markers, mitochondrial DNA (mtDNA) and Y chromosomal DNA, are widely used for the inference of human ancestry. However, the resolution of ancestral origins based on mtDNA haplotypes is limited by the fact that such haplotypes are often found to be distributed across wide geographical regions. We have addressed this issue here by combining two sources of ancestry information that have typically been considered separately: historical records regarding population origins and genetic information on mtDNA haplotypes. To combine these distinct data sources, we applied a Bayesian approach that considers historical records, in the form of prior probabilities, together with data on the geographical distribution of mtDNA haplotypes, formulated as likelihoods, to yield ancestry assignments from posterior probabilities. This combined evidence Bayesian approach to ancestry assignment was evaluated for its ability to accurately assign sub-continental African ancestral origins to Afro-Colombians based on their mtDNA haplotypes. We demonstrate that the incorporation of historical prior probabilities via this analytical framework can provide for substantially increased resolution in sub-continental African ancestry assignment for members of this population. In addition, a personalized approach to ancestry assignment that involves the tuning of priors to individual mtDNA haplotypes yields even greater resolution for individual ancestry assignment. Despite the fact that Colombia has a large population of Afro-descendants, the ancestry of this community has been understudied relative to populations with primarily European and Native American ancestry. Thus, the application of the kind of combined evidence approach developed here to the study of ancestry in the Afro-Colombian population has the potential to be impactful. The formal Bayesian analytical framework we propose for combining historical and genetic information also has the potential to be widely applied across various global populations and for different genetic markers.

Current Efavirenz (EFV) or ritonavir-boosted lopinavir (LPV/r) use correlates with elevate markers of atherosclerosis in HIV-infected subjects in Addis Ababa, Ethiopia.

BACKGROUND: HIV patients on antiretroviral therapy have shown elevated incidence of dyslipidemia, lipodystrophy, and cardiovascular disease (CVD). Most studies, however, focus on cohorts from developed countries, with less data available for these co-morbidities in Ethiopia and sub-Saharan Africa. METHODS: Adult HIV-negative (n = 36), treatment naïve (n = 51), efavirenz (EFV)-treated (n = 91), nevirapine (NVP)-treated (n = 95), or ritonavir-boosted lopinavir (LPV/r)-treated (n=44) subjects were recruited from Black Lion Hospital in Addis Ababa, Ethiopia. Aortic pressure, augmentation pressure, and pulse wave velocity (PWV) were measured via applanation tonometry and carotid intima-media thickness (cIMT) and carotid arterial stiffness, and brachial artery flow-mediated dilation (FMD) were measured via non-invasive ultrasound. Body mass index, waist-to-hip circumference ratio (WHR), skinfold thickness, and self-reported fat redistribution were used to quantify lipodystrophy. CD4+ cell count, plasma HIV RNA levels, fasting glucose, total-, HDL-, and LDL-cholesterol, triglycerides, hsCRP, sVCAM-1, sICAM-1, leptin and complete blood count were measured. RESULTS: PWV and normalized cIMT were elevate and FMD impaired in EFV- and LPV/r-treated subjects compared to NVP-treated subjects; normalized cIMT was also elevated and FMD impaired in the EFV- and LPV/r-treated subjects compared to treatment-naïve subjects. cIMT was not statistically different across groups. Treated subjects exhibited elevated markers of dyslipidemia, inflammation, and lipodystrophy. PWV was associated with age, current EFV and LPV/r used, heart rate, blood pressure, triglycerides, LDL, and hsCRP, FMD with age, HIV duration, WHR, and glucose, and cIMT with age, current EFV use, skinfold thickness, and blood pressure. CONCLUSIONS: Current EFV- or LPV/r-treatment, but not NVP-treatment, correlated with elevated markers of atherosclerosis, which may involve mechanisms distinct from traditional risk factors.

Whole-body immunoPET reveals active SIV dynamics in viremic and antiretroviral therapy-treated macaques.

The detection of viral dynamics and localization in the context of controlled HIV infection remains a challenge and is limited to blood and biopsies. We developed a method to capture total-body simian immunodeficiency virus (SIV) replication using immunoPET (antibody-targeted positron emission tomography). The administration of a poly(ethylene glycol)-modified, (64)Cu-labeled SIV Gp120-specific antibody led to readily detectable signals in the gastrointestinal and respiratory tract, lymphoid tissues and reproductive organs of viremic monkeys. Viral signals were reduced in aviremic antiretroviral-treated monkeys but detectable in colon, select lymph nodes, small bowel, nasal turbinates, the genital tract and lung. In elite controllers, virus was detected primarily in foci in the small bowel, select lymphoid areas and the male reproductive tract, as confirmed by quantitative reverse-transcription PCR (qRT-PCR) and immunohistochemistry. This real-time, in vivo viral imaging method has broad applications to the study of immunodeficiency virus pathogenesis, drug and vaccine development, and the potential for clinical translation.

Image denoising with 2D scale-mixing complex wavelet transforms.

This paper introduces an image denoising procedure based on a 2D scale-mixing complex-valued wavelet transform. Both the minimal (unitary) and redundant (maximum overlap) versions of the transform are used. The covariance structure of white noise in wavelet domain is established. Estimation is performed via empirical Bayesian techniques, including versions that preserve the phase of the complex-valued wavelet coefficients and those that do not. The new procedure exhibits excellent quantitative and visual performance, which is demonstrated by simulation on standard test images.

Multifractal analysis for nutritional assessment.

The concept of multifractality is currently used to describe self-similar and complex scaling properties observed in numerous biological signals. Fractals are geometric objects or dynamic variations which exhibit some degree of similarity (irregularity) to the original object in a wide range of scales. This approach determines irregularity of biologic signal as an indicator of adaptability, the capability to respond to unpredictable stress, and health. In the present work, we propose the application of multifractal analysis of wavelet-transformed proton nuclear magnetic resonance ((1)H NMR) spectra of plasma to determine nutritional insufficiency. For validation of this method on (1)H NMR signal of human plasma, standard deviation from classical statistical approach and Hurst exponent (H), left slope and partition function from multifractal analysis were extracted from (1)H NMR spectra to test whether multifractal indices could discriminate healthy subjects from unhealthy, intensive care unit patients. After validation, the multifractal approach was applied to spectra of plasma from a modified crossover study of sulfur amino acid insufficiency and tested for associations with blood lipids. The results showed that standard deviation and H, but not left slope, were significantly different for sulfur amino acid sufficiency and insufficiency. Quadratic discriminant analysis of H, left slope and the partition function showed 78% overall classification accuracy according to sulfur amino acid status. Triglycerides and apolipoprotein C3 were significantly correlated with a multifractal model containing H, left slope, and standard deviation, and cholesterol and high-sensitivity C-reactive protein were significantly correlated to H. In conclusion, multifractal analysis of (1)H NMR spectra provides a new approach to characterize nutritional status.

Biphasic fusion of the murine posterior frontal suture.

BACKGROUND: Craniosynostosis is the premature fusion of cranial sutures early in development. Mice are commonly used to study the mechanisms driving both normal and pathologic cranial suture development. Despite their frequency of use as a model, the time course of bone formation and mineralization during fusion of mouse posterior frontal suture is not well defined. METHODS: To address this, C57Bl/6J mice were euthanized at ages ranging from 6 to 107 days, and the posterior frontal sutures were imaged using micro-computed tomography. Scans were analyzed with an image-processing algorithm that was previously validated with serial histology to quantify both suture fusion and mineral content. The expression profile of genes associated with key developmental time points was examined using real-time polymerase chain reaction in both the bone and the dura. RESULTS: Results demonstrate that the bones of the posterior frontal suture come together during days 10 to 20 and then increase in mineral content and volume between days 21 and 45. The onset of posterior frontal suture fusion was associated with an increase in cartilage-associated genes on day 12. Later mineralization of the suture was associated with an increase in mRNAs for osteoblast differentiation markers, bone morphogenetic proteins, and bone morphogenetic protein inhibitors. CONCLUSIONS: Complete analysis fusion posterior frontal suture shows that it occurs in a discontinuous biphasic manner. The first phase is from days 10 to 20 and involves production of cartilage. A second mineralization phase from days 21 to 45 was seen with both the imaging algorithm and changes in gene expression.

Statistically significant contrasts between EMG waveforms revealed using wavelet-based functional ANOVA.

We developed wavelet-based functional ANOVA (wfANOVA) as a novel approach for comparing neurophysiological signals that are functions of time. Temporal resolution is often sacrificed by analyzing such data in large time bins, increasing statistical power by reducing the number of comparisons. We performed ANOVA in the wavelet domain because differences between curves tend to be represented by a few temporally localized wavelets, which we transformed back to the time domain for visualization. We compared wfANOVA and ANOVA performed in the time domain (tANOVA) on both experimental electromyographic (EMG) signals from responses to perturbation during standing balance across changes in peak perturbation acceleration (3 levels) and velocity (4 levels) and on simulated data with known contrasts. In experimental EMG data, wfANOVA revealed the continuous shape and magnitude of significant differences over time without a priori selection of time bins. However, tANOVA revealed only the largest differences at discontinuous time points, resulting in features with later onsets and shorter durations than those identified using wfANOVA (P < 0.02). Furthermore, wfANOVA required significantly fewer (~1/4;×; P < 0.015) significant F tests than tANOVA, resulting in post hoc tests with increased power. In simulated EMG data, wfANOVA identified known contrast curves with a high level of precision (r(2) = 0.94 ± 0.08) and performed better than tANOVA across noise levels (P < <0.01). Therefore, wfANOVA may be useful for revealing differences in the shape and magnitude of neurophysiological signals (e.g., EMG, firing rates) across multiple conditions with both high temporal resolution and high statistical power.

Constructing stochastic models from deterministic process equations by propensity adjustment.

BACKGROUND: Gillespie's stochastic simulation algorithm (SSA) for chemical reactions admits three kinds of elementary processes, namely, mass action reactions of 0th, 1st or 2nd order. All other types of reaction processes, for instance those containing non-integer kinetic orders or following other types of kinetic laws, are assumed to be convertible to one of the three elementary kinds, so that SSA can validly be applied. However, the conversion to elementary reactions is often difficult, if not impossible. Within deterministic contexts, a strategy of model reduction is often used. Such a reduction simplifies the actual system of reactions by merging or approximating intermediate steps and omitting reactants such as transient complexes. It would be valuable to adopt a similar reduction strategy to stochastic modelling. Indeed, efforts have been devoted to manipulating the chemical master equation (CME) in order to achieve a proper propensity function for a reduced stochastic system. However, manipulations of CME are almost always complicated, and successes have been limited to relative simple cases. RESULTS: We propose a rather general strategy for converting a deterministic process model into a corresponding stochastic model and characterize the mathematical connections between the two. The deterministic framework is assumed to be a generalized mass action system and the stochastic analogue is in the format of the chemical master equation. The analysis identifies situations: where a direct conversion is valid; where internal noise affecting the system needs to be taken into account; and where the propensity function must be mathematically adjusted. The conversion from deterministic to stochastic models is illustrated with several representative examples, including reversible reactions with feedback controls, Michaelis-Menten enzyme kinetics, a genetic regulatory motif, and stochastic focusing. CONCLUSIONS: The construction of a stochastic model for a biochemical network requires the utilization of information associated with an equation-based model. The conversion strategy proposed here guides a model design process that ensures a valid transition between deterministic and stochastic models.

Age-related differences in the morphology of microdamage propagation in trabecular bone.

Microdamage density has been shown to increase with age in trabecular bone and is associated with decreased fracture toughness. Numerous studies of crack propagation in cortical bone have been conducted, but data in trabecular bone is lacking. In this study, propagation of severe, linear, and diffuse damage was examined in trabecular bone cores from the femoral head of younger (61.3±3.1 years) and older (75.0±3.9 years) men and women. Using a two-step mechanical testing protocol, damage was first initiated with static uniaxial compression to 0.8% strain then propagated at a normalized stress level of 0.005 to a strain endpoint of 0.8%. Coupling mechanical testing with a dual-fluorescent staining technique, the number and length/area of propagating cracks were quantified. It was found that the number of cycles to the test endpoint was substantially decreased in older compared to younger samples (younger: 77,372±15,984 cycles; older: 34,944±11,964 cycles, p=0.06). This corresponded with a greater number of severely damaged trabeculae expanding in area during the fatigue test in the older group. In the younger group, diffusely damaged trabeculae had a greater damage area, which illustrates an efficient energy dissipation mechanism. These results suggest that age-related differences in fatigue life of human trabecular bone may be due to differences in propagated microdamage morphology.

Age-related changes in human trabecular bone: Relationship between microstructural stress and strain and damage morphology.

Accumulation of microdamage in aging and disease can cause skeletal fragility and is one of several factors contributing to osteoporotic fractures. To better understand the role of microdamage in fragility fracture, the mechanisms of bone failure must be elucidated on a tissue-level scale where interactions between bone matrix properties, the local biomechanical environment, and bone architecture are concurrently examined for their contributions to microdamage formation. A technique combining histological damage assessment of individual trabeculae with linear finite element solutions of trabecular von Mises and principal stress and strain was used to compare the damage initiation threshold between pre-menopausal (32-37 years, n=3 donors) and post-menopausal (71-80 years, n=3 donors) femoral cadaveric bone. Strong associations between damage morphology and stress and strain parameters were observed in both groups, and an age-related decrease in undamaged trabecular von Mises stress was detected. In trabeculae from younger donors, the 95% CI for von Mises stress on undamaged regions ranged from 50.7-67.9MPa, whereas in trabeculae from older donors, stresses were significantly lower (38.7-50.2, p<0.01). Local microarchitectural analysis indicated that thinner, rod-like trabeculae oriented along the loading axis are more susceptible to severe microdamage formation in older individuals, while only rod-like architecture was associated with severe damage in younger individuals. This study therefore provides insight into how damage initiation and morphology relate to local trabecular microstructure and the associated stresses and strains under loading. Furthermore, by comparison of samples from pre- and post-menopausal women, the results suggest that trabeculae from younger individuals can sustain higher stresses prior to microdamage initiation.

Breath analysis by mass spectrometry: a new tool for breast cancer detection?

Breath analysis has received attention as a noninvasive diagnostic tool with increasing research into its potential usefulness. We are investigating the utility of the analysis of breath volatile organic compounds (VOCs) as an effective modality for breast cancer (BC) detection and monitoring by collecting breath samples with a simple portable device to determine whether BC patients have breath VOCs distinct from those in healthy volunteers. We prospectively enrolled 20 healthy volunteers and 20 newly diagnosed stage II-IV BC patients. The study subjects deeply exhaled into a commercially available Teflon/valved breath sampler equipped with a rapid passive diffusive sampler five times at 5-minute intervals trapping alveolar breath VOCs. The exhaled breath samples were analyzed by thermal desorption/gas chromatography/mass spectrometry monitoring 383 VOCs in the breath of both populations. Our results indicate that aggregate low-dimensional summaries and compound quantities result in specific patterns that can confirm BC. We found a definite clustering of the presence of BC from cancer-free points. Overall sensitivity was 72 per cent and specificity was 64 per cent resulting in a correct classification rate of approximately 77 per cent. Our data show promising evidence that BC patients can be differentiated from healthy volunteers through distinct breath VOCs.

Ecological-type inference in matched-pair studies with fixed marginal totals.

This paper applies a Bayesian approach to ecological-type inference in matched-pair studies because traditional methods that assume parallel tables are not directly applicable. The proposed procedure is based on a hierarchical Bayes structure which models information about the within-pair association. The proposed algorithm relies on Markov chain Monte Carlo simulation, recovers the full table, and reports its accuracy in terms of credible sets for the cell counts. This methodology is motivated and illustrated with examples from split-mouth designs assessing the effectiveness of dental sealant materials and cross-over trials comparing two forms of insulin.

One year of alendronate treatment lowers microstructural stresses associated with trabecular microdamage initiation.

Alendronate, an anti-remodeling agent, is commonly used to treat patients suffering from osteoporosis by increasing bone mineral density. Though fracture risk is lowered, an increase in microdamage accumulation has been documented in patients receiving alendronate, leading to questions about the potentially detrimental effects of remodeling suppression on the local tissue (material) properties. In this study, trabecular bone cores from the distal femur of beagle dogs treated for one year with alendronate, at doses scaled by weight to approximate osteoporotic and Paget's disease treatment doses in humans, were subjected to uniaxial compression to induce microdamage. Tissue level von Mises stresses were computed for alendronate-treated and non-treated controls using finite element analysis and correlated to microdamage morphology. Using a modified version of the Moore and Gibson classification for damage morphology, we determined that the von Mises stress for trabeculae exhibiting severe and linear microcrack patterns was decreased by approximately 25% in samples treated with alendronate compared with non-treated controls (p<0.01), whereas there was no reduction in the von Mises stress state for diffuse microdamage formation. Furthermore, an examination of the architectural and structural characteristics of damaged trabeculae demonstrated that severely damaged trabeculae were thinner, more aligned with the loading axis, and less mineralized than undamaged trabeculae in alendronate-treated samples (p<0.01). Similar relationships with damage morphology were found only with trabecular orientation in vehicle-treated control dogs. These results indicate that changes in bone's architecture and matrix properties associated with one year of alendronate administration reduce trabecular bone's ability to resist the formation of loading-induced severe and linear microcracks, both of which dissipate less energy prior to fracture than does diffuse damage.

Self-similarity in NMR Spectra: An Application in Assessing the Level of Cysteine.

High resolution of NMR spectroscopic data of biosamples are a rich source of information on the metabolic response to physiological variation or pathological events. There are many advantages of NMR techniques such as the sample preparation is fast, simple and non-invasive. Statistical analysis of NMR spectra usually focuses on differential expression of large resonance intensity corresponding to abundant metabolites and involves several data preprocessing steps. In this paper we estimate functional components of spectra and test their significance using multiscale techniques. We also explore scaling in NMR spectra and use the systematic variability of scaling descriptors to predict the level of cysteine, an important precursor of glutathione, a control antioxidant in human body. This is motivated by high cost (in time and resources) of traditional methods for assessing cysteine level by high performance liquid chromatograph (HPLC).