GEOSTATISTICAL INFERENCE UNDER PREFERENTIAL SAMPLING

Geostatistics involves the fitting of spatially continuous models to spatially discrete data (Chil`es and Delfiner, 1999). Preferential sampling arises when the process that determines the data-locations and the process being modelled are stochastically dependent. Conventional geostatistical methods assume, if only implicitly, that sampling is non-preferential. However, these methods are often used in situations where sampling is likely to be preferential. For example, in mineral exploration samples may be concentrated in areas thought likely to yield high-grade ore. We give a general expression for the likelihood function of preferentially sampled geostatistical data and describe how this can be evaluated approximately using Monte Carlo methods. We present a model for preferential sampling, and demonstrate through simulated examples that ignoring preferential sampling can lead to seriously misleading inferences. We describe an application of the model to a set of bio-monitoring data from Galicia, northern Spain, in which making allowance for preferential sampling materially changes the inferences.

Causal Inference in Observational Studies with Outcome-Dependent Sampling

In this paper, we consider estimation of the causal effect of a treatment on an outcome from observational data collected in two phases. In the first phase, a simple random sample of individuals are drawn from a population. On these individuals, information is obtained on treatment, outcome, and a few low-dimensional confounders. These individuals are then stratified according to these factors. In the second phase, a random sub-sample of individuals are drawn from each stratum, with known, stratum-specific selection probabilities. On these individuals, a rich set of confounding factors are collected. In this setting, we introduce four estimators: (1) simple inverse weighted, (2) locally efficient, (3) doubly robust and (4)enriched inverse weighted. We evaluate the finite-sample performance of these estimators in a simulation study. We also use our methodology to estimate the causal effect of trauma care on in-hospital mortality using data from the National Study of Cost and Outcomes of Trauma.

Analyzing Bivariate Survival Data with Interval Sampling and Application to Cancer Epidemiology

In medical follow-up studies, ordered bivariate survival data are frequently encountered when bivariate failure events are used as the outcomes to identify the progression of a disease. In cancer studies interest could be focused on bivariate failure times, for example, time from birth to cancer onset and time from cancer onset to death. This paper considers a sampling scheme where the first failure event (cancer onset) is identified within a calendar time interval, the time of the initiating event (birth) can be retrospectively confirmed, and the occurrence of the second event (death) is observed sub ject to right censoring. To analyze this type of bivariate failure time data, it is important to recognize the presence of bias arising due to interval sampling. In this paper, nonparametric and semiparametric methods are developed to analyze the bivariate survival data with interval sampling under stationary and semi-stationary conditions. Numerical studies demonstrate the proposed estimating approaches perform well with practical sample sizes in different simulated models. We apply the proposed methods to SEER ovarian cancer registry data for illustration of the methods and theory.

Detection of surfactant proteins A and D in human tear fluid and the human lacrimal system

PURPOSE: To evaluate the expression and presence of surfactant protein (SP) A and SP-D in the lacrimal apparatus, at the ocular surface, and in tears in healthy and pathologic states. METHODS: Expression of mRNA for SP-A and SP-D was analyzed by RT-PCR in healthy lacrimal gland, conjunctiva, cornea, and nasolacrimal ducts as well as in a spontaneously immortalized conjunctival epithelial cell line (HCjE; IOBA-NHC) and a SV40-transfected cornea epithelial cell line (HCE). Deposition of SP-A and SP-D was determined by Western blot, dot blot, and immunohistochemistry in healthy tissues, in tears, aqueous humor, and in sections of different corneal abnormalities (keratoconus, herpetic keratitis, and Staphylococcus aureus-based ulceration). Cell lines were stimulated with different cytokines and bacterial components and were analyzed for the production of SP-A and SP-D by immunohistochemistry. RESULTS: The presence of SP-A and SP-D on mRNA and protein levels was evidenced in healthy lacrimal gland, conjunctiva, cornea, and nasolacrimal duct samples. Moreover, both proteins were present in tears but were absent in aqueous humor. Immunohistochemistry revealed the production of both peptides by acinar epithelial cells of the lacrimal gland and epithelial cells of the conjunctiva and nasolacrimal ducts, whereas goblet cells revealed no reactivity. Healthy cornea revealed weak reactivity on epithelial surface cells only. In contrast, SP-A and SP-D revealed strong reactivity in patients with herpetic keratitis and corneal ulceration surrounding lesions and in several immigrated defense cells. Reactivity in corneal epithelium and endothelium was also seen in patients with keratoconus. Cell culture experiments revealed that SP-A and SP-D are produced by both epithelial cell lines without and after stimulation with cytokines and bacterial components. CONCLUSIONS: These results show that SP-A, in addition to SP-D, is a peptide of the tear film. Based on the known direct and indirect antimicrobial effects of collectins, the surfactant-associated proteins A and D seem to be involved in several ocular surface diseases.

Similarities in the Subgingival Microbiota Assessed by a Curet Sampling Method at Sites With Chronic Periodontitis

Background: The goal of this study was to determine whether site-specific differences in the subgingival microbiota could be detected by the checkerboard method in subjects with periodontitis. Methods: Subjects with at least six periodontal pockets with a probing depth (PD) between 5 and 7 mm were enrolled in the study. Subgingival plaque samples were collected with sterile curets by a single-stroke procedure at six selected periodontal sites from 161 subjects (966 subgingival sites). Subgingival bacterial samples were assayed with the checkerboard DNA-DNA hybridization method identifying 37 species. Results: Probing depths of 5, 6, and 7 mm were found at 50% (n = 483), 34% (n = 328), and 16% (n = 155) of sites, respectively. Statistical analysis failed to demonstrate differences in the sum of bacterial counts by tooth type (P = 0.18) or specific location of the sample (P = 0.78). With the exceptions of Campylobacter gracilis (P <0.001) and Actinomyces naeslundii (P <0.001), analysis by general linear model multivariate regression failed to identify subject or sample location factors as explanatory to microbiologic results. A trend of difference in bacterial load by tooth type was found for Prevotella nigrescens (P <0.01). At a cutoff level of >/=1.0 x 10(5), Porphyromonas gingivalis and Tannerella forsythia (previously T. forsythensis) were present at 48.0% to 56.3% and 46.0% to 51.2% of sampled sites, respectively. Conclusions: Given the similarities in the clinical evidence of periodontitis, the presence and levels of 37 species commonly studied in periodontitis are similar, with no differences between molar, premolar, and incisor/cuspid subgingival sites. This may facilitate microbiologic sampling strategies in subjects during periodontal therapy.

Hermitian curve interpolation for CT-data re-sampling

Purpose: Development of an interpolation algorithm for re‐sampling spatially distributed CT‐data with the following features: global and local integral conservation, avoidance of negative interpolation values for positively defined datasets and the ability to control re‐sampling artifacts. Method and Materials: The interpolation can be separated into two steps: first, the discrete CT‐data has to be continuously distributed by an analytic function considering the boundary conditions. Generally, this function is determined by piecewise interpolation. Instead of using linear or high order polynomialinterpolations, which do not fulfill all the above mentioned features, a special form of Hermitian curve interpolation is used to solve the interpolation problem with respect to the required boundary conditions. A single parameter is determined, by which the behavior of the interpolation function is controlled. Second, the interpolated data have to be re‐distributed with respect to the requested grid. Results: The new algorithm was compared with commonly used interpolation functions based on linear and second order polynomial. It is demonstrated that these interpolation functions may over‐ or underestimate the source data by about 10%–20% while the parameter of the new algorithm can be adjusted in order to significantly reduce these interpolation errors. Finally, the performance and accuracy of the algorithm was tested by re‐gridding a series of X‐ray CT‐images. Conclusion: Inaccurate sampling values may occur due to the lack of integral conservation. Re‐sampling algorithms using high order polynomialinterpolation functions may result in significant artifacts of the re‐sampled data. Such artifacts can be avoided by using the new algorithm based on Hermitian curve interpolation

Proteins in silico-modeling and sampling

Proteins are linear chain molecules made out of amino acids. Only when they fold to their native states, they become functional. This dissertation aims to model the solvent (environment) effect and to develop & implement enhanced sampling methods that enable a reliable study of the protein folding problem in silico. We have developed an enhanced solvation model based on the solution to the Poisson-Boltzmann equation in order to describe the solvent effect. Following the quantum mechanical Polarizable Continuum Model (PCM), we decomposed net solvation free energy into three physical terms– Polarization, Dispersion and Cavitation. All the terms were implemented, analyzed and parametrized individually to obtain a high level of accuracy. In order to describe the thermodynamics of proteins, their conformational space needs to be sampled thoroughly. Simulations of proteins are hampered by slow relaxation due to their rugged free-energy landscape, with the barriers between minima being higher than the thermal energy at physiological temperatures. In order to overcome this problem a number of approaches have been proposed of which replica exchange method (REM) is the most popular. In this dissertation we describe a new variant of canonical replica exchange method in the context of molecular dynamic simulation. The advantage of this new method is the easily tunable high acceptance rate for the replica exchange. We call our method Microcanonical Replica Exchange Molecular Dynamic (MREMD). We have described the theoretical frame work, comment on its actual implementation, and its application to Trp-cage mini-protein in implicit solvent. We have been able to correctly predict the folding thermodynamics of this protein using our approach.

Sampling-Design Effects on Properties of Species-Area Relationships - A Case Study from Estonian Dry Grassland Communities

Despite widespread use of species-area relationships (SARs), dispute remains over the most representative SAR model. Using data of small-scale SARs of Estonian dry grassland communities, we address three questions: (1) Which model describes these SARs best when known artifacts are excluded? (2) How do deviating sampling procedures (marginal instead of central position of the smaller plots in relation to the largest plot; single values instead of average values; randomly located subplots instead of nested subplots) influence the properties of the SARs? (3) Are those effects likely to bias the selection of the best model? Our general dataset consisted of 16 series of nested-plots (1 cm(2)-100 m(2), any-part system), each of which comprised five series of subplots located in the four corners and the centre of the 100-m(2) plot. Data for the three pairs of compared sampling designs were generated from this dataset by subsampling. Five function types (power, quadratic power, logarithmic, Michaelis-Menten, Lomolino) were fitted with non-linear regression. In some of the communities, we found extremely high species densities (including bryophytes and lichens), namely up to eight species in 1 cm(2) and up to 140 species in 100 m(2), which appear to be the highest documented values on these scales. For SARs constructed from nested-plot average-value data, the regular power function generally was the best model, closely followed by the quadratic power function, while the logarithmic and Michaelis-Menten functions performed poorly throughout. However, the relative fit of the latter two models increased significantly relative to the respective best model when the single-value or random-sampling method was applied, however, the power function normally remained far superior. These results confirm the hypothesis that both single-value and random-sampling approaches cause artifacts by increasing stochasticity in the data, which can lead to the selection of inappropriate models.

Expression of atrophy mRNA relates to tendon tear size in supraspinatus muscle

Skeletal muscle atrophy and fatty infiltration develop after tendon tearing. The extent of atrophy serves as one prognostic factor for the outcome of surgical repair of rotator cuff tendon tears. We asked whether mRNA of genes involved in regulation of degradative processes leading to muscle atrophy, ie, FOXOs, MSTN, calpains, cathepsins, and transcripts of the ubiquitin-proteasome pathway, are overexpressed in the supraspinatus muscle in patients with and without rotator cuff tears. We evaluated biopsy specimens collected during surgery of 53 consecutive patients with different sizes of rotator cuff tendon tears and six without tears. The levels of corresponding gene transcripts in total RNA extracts were assessed by semiquantitative reverse transcriptase-polymerase chain reaction (RT-PCR) analysis. Supraspinatus muscle atrophy was assessed by MRI. The area of muscle tissue (or atrophy), decreased (increased) with increasing tendon tear size. The transcripts of CAPN1, UBE2B, and UBE3A were upregulated more than twofold in massive rotator cuff tears as opposed to smaller tears or patients without tears. These atrophy gene products may be involved in cellular processes that impair functional recovery of affected muscles after surgical rotator cuff repair. However, the damaging effects of gene products in their respective proteolytic processes on muscle structures and proteins remains to be investigated.

Adipogenic and myogenic gene expression in rotator cuff muscle of the sheep after tendon tear

Chronic rotator cuff tendon tears lead to fatty infiltration and muscle atrophy with impaired physiological functions of the affected muscles. However, the cellular and molecular mechanisms of corresponding pathophysiological processes remain unknown. The purpose of this study was to characterize the expression pattern of adipogenic (PPARgamma, C/EBPbeta) and myogenic (myostatin, myogenin, Myf-5) transcription factors in infraspinatus muscle of sheep after tenotomy, implantation of a tension device, refixation of the tendon, and rehabilitation, reflecting a model of chronic rotator cuff tears. In contrast to human patients, the presented sheep model allows a temporal evaluation of the expression of a given marker in the same individual over time. Semiquantitative RT/PCR analysis of PPARgammaã, myostatin, myogenin, Myf-5, and C/EBPbeta transcript levels was carried out with sheep muscle biopsy-derived total RNA. We found a significantly increased expression of Myf-5 and PPARgamma after tenotomy and a significant change for Myf-5 and C/EBPbeta after continuous traction and refixation. This experimental sheep model allows the molecular analysis of pathomechanisms of muscular changes after rotator cuff tear. The results point to a crucial role of the transcription factors PPARgamma, C/EBPbeta, and Myf-5 in impairment and regeneration of rotator cuff muscles after tendon tears in sheep.