New method for quantification and statistical analysis of nociceptive reflex receptive fields in humans

A method for quantifying nociceptive withdrawal reflex receptive fields in human volunteers and patients is described. The reflex receptive field (RRF) for a specific muscle denotes the cutaneous area from which a muscle contraction can be evoked by a nociceptive stimulus. The method is based on random stimulations presented in a blinded sequence to 10 stimulation sites. The sensitivity map is derived by interpolating the reflex responses evoked from the 10 sites. A set of features describing the size and location of the RRF is presented based on statistical analysis of the sensitivity map within every subject. The features include RRF area, volume, peak location and center of gravity. The method was applied to 30 healthy volunteers. Electrical stimuli were applied to the sole of the foot evoking reflexes in the ankle flexor tibialis anterior. The RRF area covered a fraction of 0.57+/-0.06 (S.E.M.) of the foot and was located on the medial, distal part of the sole of the foot. An intramuscular injection into flexor digitorum brevis of capsaicin was performed in one spinal cord injured subject to attempt modulation of the reflex receptive field. The RRF area, RRF volume and location of the peak reflex response appear to be the most sensitive measures for detecting modulation of spinal nociceptive processing. This new method has important potential applications for exploring aspects of central plasticity in volunteers and patients. It may be utilized as a new diagnostic tool for central hypersensitivity and quantification of therapeutic interventions.

Evaluating northern hardwood management using retrospective analysis and diameter distributions

Northern hardwood management was assessed throughout the state of Michigan using data collected on recently harvested stands in 2010 and 2011. Methods of forensic estimation of diameter at breast height were compared and an ideal, localized equation form was selected for use in reconstructing pre-harvest stand structures. Comparisons showed differences in predictive ability among available equation forms which led to substantial financial differences when used to estimate the value of removed timber. Management on all stands was then compared among state, private, and corporate landowners. Comparisons of harvest intensities against a liberal interpretation of a well-established management guideline showed that approximately one third of harvests were conducted in a manner which may imply that the guideline was followed. One third showed higher levels of removals than recommended, and one third of harvests were less intensive than recommended. Multiple management guidelines and postulated objectives were then synthesized into a novel system of harvest taxonomy, against which all harvests were compared. This further comparison showed approximately the same proportions of harvests, while distinguishing sanitation cuts and the future productive potential of harvests cut more intensely than suggested by guidelines. Stand structures are commonly represented using diameter distributions. Parametric and nonparametric techniques for describing diameter distributions were employed on pre-harvest and post-harvest data. A common polynomial regression procedure was found to be highly sensitive to the method of histogram construction which provides the data points for the regression. The discriminative ability of kernel density estimation was substantially different from that of the polynomial regression technique.

Slope stability analysis of the Pacaya Volcano, Guatemala, using limit equilibrium and finite element method

The Pacaya volcanic complex is part of the Central American volcanic arc, which is associated with the subduction of the Cocos tectonic plate under the Caribbean plate. Located 30 km south of Guatemala City, Pacaya is situated on the southern rim of the Amatitlan Caldera. It is the largest post-caldera volcano, and has been one of Central America’s most active volcanoes over the last 500 years. Between 400 and 2000 years B.P, the Pacaya volcano had experienced a huge collapse, which resulted in the formation of horseshoe-shaped scarp that is still visible. In the recent years, several smaller collapses have been associated with the activity of the volcano (in 1961 and 2010) affecting its northwestern flanks, which are likely to be induced by the local and regional stress changes. The similar orientation of dry and volcanic fissures and the distribution of new vents would likely explain the reactivation of the pre-existing stress configuration responsible for the old-collapse. This paper presents the first stability analysis of the Pacaya volcanic flank. The inputs for the geological and geotechnical models were defined based on the stratigraphical, lithological, structural data, and material properties obtained from field survey and lab tests. According to the mechanical characteristics, three lithotechnical units were defined: Lava, Lava-Breccia and Breccia-Lava. The Hoek and Brown’s failure criterion was applied for each lithotechnical unit and the rock mass friction angle, apparent cohesion, and strength and deformation characteristics were computed in a specified stress range. Further, the stability of the volcano was evaluated by two-dimensional analysis performed by Limit Equilibrium (LEM, ROCSCIENCE) and Finite Element Method (FEM, PHASE 2 7.0). The stability analysis mainly focused on the modern Pacaya volcano built inside the collapse amphitheatre of “Old Pacaya”. The volcanic instability was assessed based on the variability of safety factor using deterministic, sensitivity, and probabilistic analysis considering the gravitational instability and the effects of external forces such as magma pressure and seismicity as potential triggering mechanisms of lateral collapse. The preliminary results from the analysis provide two insights: first, the least stable sector is on the south-western flank of the volcano; second, the lowest safety factor value suggests that the edifice is stable under gravity alone, and the external triggering mechanism can represent a likely destabilizing factor.

IDENTIFICATION OF GENES CONTROLLING BIOLOGICAL PROCESSES AND PATHWAYS THROUGH STATISTICAL ANALYSIS AND NETWORK RECONSTRUCTION

The developmental processes and functions of an organism are controlled by the genes and the proteins that are derived from these genes. The identification of key genes and the reconstruction of gene networks can provide a model to help us understand the regulatory mechanisms for the initiation and progression of biological processes or functional abnormalities (e.g. diseases) in living organisms. In this dissertation, I have developed statistical methods to identify the genes and transcription factors (TFs) involved in biological processes, constructed their regulatory networks, and also evaluated some existing association methods to find robust methods for coexpression analyses. Two kinds of data sets were used for this work: genotype data and gene expression microarray data. On the basis of these data sets, this dissertation has two major parts, together forming six chapters. The first part deals with developing association methods for rare variants using genotype data (chapter 4 and 5). The second part deals with developing and/or evaluating statistical methods to identify genes and TFs involved in biological processes, and construction of their regulatory networks using gene expression data (chapter 2, 3, and 6). For the first part, I have developed two methods to find the groupwise association of rare variants with given diseases or traits. The first method is based on kernel machine learning and can be applied to both quantitative as well as qualitative traits. Simulation results showed that the proposed method has improved power over the existing weighted sum method (WS) in most settings. The second method uses multiple phenotypes to select a few top significant genes. It then finds the association of each gene with each phenotype while controlling the population stratification by adjusting the data for ancestry using principal components. This method was applied to GAW 17 data and was able to find several disease risk genes. For the second part, I have worked on three problems. First problem involved evaluation of eight gene association methods. A very comprehensive comparison of these methods with further analysis clearly demonstrates the distinct and common performance of these eight gene association methods. For the second problem, an algorithm named the bottom-up graphical Gaussian model was developed to identify the TFs that regulate pathway genes and reconstruct their hierarchical regulatory networks. This algorithm has produced very significant results and it is the first report to produce such hierarchical networks for these pathways. The third problem dealt with developing another algorithm called the top-down graphical Gaussian model that identifies the network governed by a specific TF. The network produced by the algorithm is proven to be of very high accuracy.

Combined ultrasmall superparamagnetic particles of iron oxide-enhanced and diffusion-weighted magnetic resonance imaging reliably detect pelvic lymph node metastases in normal-sized nodes of bladder and prostate cancer patients

BACKGROUND: Lymph node staging of bladder or prostate cancer using conventional imaging is limited. Newer approaches such as ultrasmall superparamagnetic particles of iron oxide (USPIO) and diffusion-weighted magnetic resonance imaging (DW-MRI) have inconsistent diagnostic accuracy and are difficult to interpret. OBJECTIVE: To assess whether combined USPIO and DW-MRI (USPIO-DW-MRI) improves staging of normal-sized lymph nodes in bladder and/or prostate cancer patients. DESIGN, SETTING, AND PARTICIPANTS: Twenty-one consecutive patients with bladder and/or prostate cancer were enrolled between May and October 2008. One patient was excluded secondary to bone metastases detected on DW-MRI with subsequent abstention from surgery. INTERVENTION: Patients preoperatively underwent 3-T MRI before and after administration of lymphotropic USPIO using conventional MRI sequences combined with DW-MRI. Surgery consisted of extended pelvic lymphadenectomy and resection of primary tumors. MEASUREMENTS: Diagnostic accuracies of the new combined USPIO-DW-MRI approach compared with the "classic" reading method evaluating USPIO images without and with DW-MRI versus histopathology were evaluated. Duration of the two reading methods was noted for each patient. RESULTS AND LIMITATIONS: Diagnostic accuracy (90% per patient or per pelvic side) was comparable for the classic and the USPIO-DW-MRI reading method, while time of analysis with 80 min (range 45-180 min) for the classic and 13 min (range 5-90 min) for the USPIO-DW-MRI method was significantly shorter (p<0.0001). Interobserver agreement (three blinded readers) was high with a kappa value of 0.75 and 0.84, respectively. Histopathological analysis showed metastases in 26 of 802 analyzed lymph nodes (3.2%). Of these, 24 nodes (92%) were correctly diagnosed as positive on USPIO-DW-MRI. In two patients, one micrometastasis each (1.0x0.2 mm; 0.7x0.4 mm) was missed in all imaging studies. CONCLUSIONS: USPIO-DW-MRI is a fast and accurate method for detecting pelvic lymph node metastases, even in normal-sized nodes of bladder or prostate cancer patients.

Nutritional risk screening (NRS 2002): a new method based on an analysis of controlled clinical trials

A system for screening of nutritional risk is described. It is based on the concept that nutritional support is indicated in patients who are severely ill with increased nutritional requirements, or who are severely undernourished, or who have certain degrees of severity of disease in combination with certain degrees of undernutrition. Degrees of severity of disease and undernutrition were defined as absent, mild, moderate or severe from data sets in a selected number of randomized controlled trials (RCTs) and converted to a numeric score. After completion, the screening system was validated against all published RCTs known to us of nutritional support vs spontaneous intake to investigate whether the screening system could distinguish between trials with a positive outcome and trials with no effect on outcome.

An analysis of variance type method to describe and compare steady states in clinical data

Identifying and comparing different steady states is an important task for clinical decision making. Data from unequal sources, comprising diverse patient status information, have to be interpreted. In order to compare results an expressive representation is the key. In this contribution we suggest a criterion to calculate a context-sensitive value based on variance analysis and discuss its advantages and limitations referring to a clinical data example obtained during anesthesia. Different drug plasma target levels of the anesthetic propofol were preset to reach and maintain clinically desirable steady state conditions with target controlled infusion (TCI). At the same time systolic blood pressure was monitored, depth of anesthesia was recorded using the bispectral index (BIS) and propofol plasma concentrations were determined in venous blood samples. The presented analysis of variance (ANOVA) is used to quantify how accurately steady states can be monitored and compared using the three methods of measurement.

Beyond the tree of texts: Building an empirical model of scribal variation through graph analysis of texts and stemmata

Stemmatology, or the reconstruction of the transmission history of texts, is a field that stands particularly to gain from digital methods. Many scholars already take stemmatic approaches that rely heavily on computational analysis of the collated text (e.g. Robinson and O’Hara 1996; Salemans 2000; Heikkilä 2005; Windram et al. 2008 among many others). Although there is great value in computationally assisted stemmatology, providing as it does a reproducible result and allowing access to the relevant methodological process in related fields such as evolutionary biology, computational stemmatics is not without its critics. The current state-of-the-art effectively forces scholars to choose between a preconceived judgment of the significance of textual differences (the Lachmannian or neo-Lachmannian approach, and the weighted phylogenetic approach) or to make no judgment at all (the unweighted phylogenetic approach). Some basis for judgment of the significance of variation is sorely needed for medieval text criticism in particular. By this, we mean that there is a need for a statistical empirical profile of the text-genealogical significance of the different sorts of variation in different sorts of medieval texts. The rules that apply to copies of Greek and Latin classics may not apply to copies of medieval Dutch story collections; the practices of copying authoritative texts such as the Bible will most likely have been different from the practices of copying the Lives of local saints and other commonly adapted texts. It is nevertheless imperative that we have a consistent, flexible, and analytically tractable model for capturing these phenomena of transmission. In this article, we present a computational model that captures most of the phenomena of text variation, and a method for analysis of one or more stemma hypotheses against the variation model. We apply this method to three ‘artificial traditions’ (i.e. texts copied under laboratory conditions by scholars to study the properties of text variation) and four genuine medieval traditions whose transmission history is known or deduced in varying degrees. Although our findings are necessarily limited by the small number of texts at our disposal, we demonstrate here some of the wide variety of calculations that can be made using our model. Certain of our results call sharply into question the utility of excluding ‘trivial’ variation such as orthographic and spelling changes from stemmatic analysis.

Living Renal Allograft Transplantation: Diffusion-weighted MR Imaging in Longitudinal Follow-up of the Donated and the Remaining Kidney.

Purpose To determine whether diffusion-weighted (DW) magnetic resonance (MR) imaging in living renal allograft donation allows monitoring of potential changes in the nontransplanted remaining kidney of the donor because of unilateral nephrectomy and changes in the transplanted kidney before and after transplantation in donor and recipient, respectively, and whether DW MR parameters are correlated in the same kidney before and after transplantation. Materials and Methods The study protocol was approved by the local ethics committee; written informed consent was obtained. Thirteen healthy kidney donors and their corresponding recipients prospectively underwent DW MR imaging (multiple b values) in donors before donation and in donors and recipients at day 8 and months 3 and 12 after donation. Total apparent diffusion coefficient (ADCT) values were determined; contribution of microcirculation was quantified in perfusion fraction (FP). Longitudinal changes of diffusion parameters were compared (repeated-measures one-way analysis of variance with post hoc pairwise comparisons). Correlations were tested (linear regression). Results ADCT values in nontransplanted kidney of donors increased from a preexplantation value of (188 ± 9 [standard deviation]) to (202 ± 11) × 10(-5) mm(2)/sec in medulla and from (199 ± 11) to (210 ± 13) × 10(-5) mm(2)/sec in cortex 1 week after donation (P < .004). Medullary, but not cortical, ADCT values stayed increased up to 1 year. ADCT values in allografts in recipients were stable. Compared with values obtained before transplantation in donors, the corticomedullary difference was reduced in allografts (P < .03). Cortical ADCT values correlated with estimated glomerular filtration rate in recipients (R = 0.56, P < .001) but not donors. Cortical ADCT values in the same kidney before transplantation in donors correlated with those in recipients on day 8 after transplantation (R = 0.77, P = .006). FP did not show significant changes. Conclusion DW MR imaging depicts early adaptations in the remaining nontransplanted kidney of donors after nephrectomy. All diffusion parameters remained constant in allograft recipients after transplantation. This method has potential monitoring utility, although assessment of clinical relevance is needed. © RSNA, 2013 Online supplemental material is available for this article.

Characterization of microcirculation in multiple sclerosis lesions by dynamic texture parameter analysis (DTPA)

OBJECTIVE Texture analysis is an alternative method to quantitatively assess MR-images. In this study, we introduce dynamic texture parameter analysis (DTPA), a novel technique to investigate the temporal evolution of texture parameters using dynamic susceptibility contrast enhanced (DSCE) imaging. Here, we aim to introduce the method and its application on enhancing lesions (EL), non-enhancing lesions (NEL) and normal appearing white matter (NAWM) in multiple sclerosis (MS). METHODS We investigated 18 patients with MS and clinical isolated syndrome (CIS), according to the 2010 McDonald's criteria using DSCE imaging at different field strengths (1.5 and 3 Tesla). Tissues of interest (TOIs) were defined within 27 EL, 29 NEL and 37 NAWM areas after normalization and eight histogram-based texture parameter maps (TPMs) were computed. TPMs quantify the heterogeneity of the TOI. For every TOI, the average, variance, skewness, kurtosis and variance-of-the-variance statistical parameters were calculated. These TOI parameters were further analyzed using one-way ANOVA followed by multiple Wilcoxon sum rank testing corrected for multiple comparisons. RESULTS Tissue- and time-dependent differences were observed in the dynamics of computed texture parameters. Sixteen parameters discriminated between EL, NEL and NAWM (pAVG = 0.0005). Significant differences in the DTPA texture maps were found during inflow (52 parameters), outflow (40 parameters) and reperfusion (62 parameters). The strongest discriminators among the TPMs were observed in the variance-related parameters, while skewness and kurtosis TPMs were in general less sensitive to detect differences between the tissues. CONCLUSION DTPA of DSCE image time series revealed characteristic time responses for ELs, NELs and NAWM. This may be further used for a refined quantitative grading of MS lesions during their evolution from acute to chronic state. DTPA discriminates lesions beyond features of enhancement or T2-hypersignal, on a numeric scale allowing for a more subtle grading of MS-lesions.

A Modification of the Response Method of Tidal Analysis

An easily implemented extension of the standard response method of tidal analysis is outlined. The modification improves the extraction of both the steady and the tidal components from problematic time series by calculating tidal response weights uncontaminated by missing or anomalous data. Examples of time series containing data gaps and anomalous events are analyzed to demonstrate the applicability and advantage of the proposed method.