Statistical characterization and development of summary measures of non-normal distributions of nuclear morphometry data from prostate cancer cells for use as prognostic indicators

Nuclear morphometry (NM) uses image analysis to measure features of the cell nucleus which are classified as: bulk properties, shape or form, and DNA distribution. Studies have used these measurements as diagnostic and prognostic indicators of disease with inconclusive results. The distributional properties of these variables have not been systematically investigated although much of the medical data exhibit nonnormal distributions. Measurements are done on several hundred cells per patient so summary measurements reflecting the underlying distribution are needed.^ Distributional characteristics of 34 NM variables from prostate cancer cells were investigated using graphical and analytical techniques. Cells per sample ranged from 52 to 458. A small sample of patients with benign prostatic hyperplasia (BPH), representing non-cancer cells, was used for general comparison with the cancer cells.^ Data transformations such as log, square root and 1/x did not yield normality as measured by the Shapiro-Wilks test for normality. A modulus transformation, used for distributions having abnormal kurtosis values, also did not produce normality.^ Kernel density histograms of the 34 variables exhibited non-normality and 18 variables also exhibited bimodality. A bimodality coefficient was calculated and 3 variables: DNA concentration, shape and elongation, showed the strongest evidence of bimodality and were studied further.^ Two analytical approaches were used to obtain a summary measure for each variable for each patient: cluster analysis to determine significant clusters and a mixture model analysis using a two component model having a Gaussian distribution with equal variances. The mixture component parameters were used to bootstrap the log likelihood ratio to determine the significant number of components, 1 or 2. These summary measures were used as predictors of disease severity in several proportional odds logistic regression models. The disease severity scale had 5 levels and was constructed of 3 components: extracapsulary penetration (ECP), lymph node involvement (LN+) and seminal vesicle involvement (SV+) which represent surrogate measures of prognosis. The summary measures were not strong predictors of disease severity. There was some indication from the mixture model results that there were changes in mean levels and proportions of the components in the lower severity levels. ^

Extended kalman filter for estimation of parameters in nonlinear state-space models of biochemical networks.

It is system dynamics that determines the function of cells, tissues and organisms. To develop mathematical models and estimate their parameters are an essential issue for studying dynamic behaviors of biological systems which include metabolic networks, genetic regulatory networks and signal transduction pathways, under perturbation of external stimuli. In general, biological dynamic systems are partially observed. Therefore, a natural way to model dynamic biological systems is to employ nonlinear state-space equations. Although statistical methods for parameter estimation of linear models in biological dynamic systems have been developed intensively in the recent years, the estimation of both states and parameters of nonlinear dynamic systems remains a challenging task. In this report, we apply extended Kalman Filter (EKF) to the estimation of both states and parameters of nonlinear state-space models. To evaluate the performance of the EKF for parameter estimation, we apply the EKF to a simulation dataset and two real datasets: JAK-STAT signal transduction pathway and Ras/Raf/MEK/ERK signaling transduction pathways datasets. The preliminary results show that EKF can accurately estimate the parameters and predict states in nonlinear state-space equations for modeling dynamic biochemical networks.

Molecular cross talk between misfolded proteins in animal models of Alzheimer's and prion diseases.

The central event in protein misfolding disorders (PMDs) is the accumulation of a misfolded form of a naturally expressed protein. Despite the diversity of clinical symptoms associated with different PMDs, many similarities in their mechanism suggest that distinct pathologies may cross talk at the molecular level. The main goal of this study was to analyze the interaction of the protein misfolding processes implicated in Alzheimer's and prion diseases. For this purpose, we inoculated prions in an Alzheimer's transgenic mouse model that develop typical amyloid plaques and followed the progression of pathological changes over time. Our findings show a dramatic acceleration and exacerbation of both pathologies. The onset of prion disease symptoms in transgenic mice appeared significantly faster with a concomitant increase on the level of misfolded prion protein in the brain. A striking increase in amyloid plaque deposition was observed in prion-infected mice compared with their noninoculated counterparts. Histological and biochemical studies showed the association of the two misfolded proteins in the brain and in vitro experiments showed that protein misfolding can be enhanced by a cross-seeding mechanism. These results suggest a profound interaction between Alzheimer's and prion pathologies, indicating that one protein misfolding process may be an important risk factor for the development of a second one. Our findings may have important implications to understand the origin and progression of PMDs.

Genetic and hormonal factors modulate spreading depression and transient hemiparesis in mouse models of familial hemiplegic migraine type 1.

Familial hemiplegic migraine type 1 (FHM1) is an autosomal dominant subtype of migraine with aura that is associated with hemiparesis. As with other types of migraine, it affects women more frequently than men. FHM1 is caused by mutations in the CACNA1A gene, which encodes the alpha1A subunit of Cav2.1 channels; the R192Q mutation in CACNA1A causes a mild form of FHM1, whereas the S218L mutation causes a severe, often lethal phenotype. Spreading depression (SD), a slowly propagating neuronal and glial cell depolarization that leads to depression of neuronal activity, is the most likely cause of migraine aura. Here, we have shown that transgenic mice expressing R192Q or S218L FHM1 mutations have increased SD frequency and propagation speed; enhanced corticostriatal propagation; and, similar to the human FHM1 phenotype, more severe and prolonged post-SD neurological deficits. The susceptibility to SD and neurological deficits is affected by allele dosage and is higher in S218L than R192Q mutants. Further, female S218L and R192Q mutant mice were more susceptible to SD and neurological deficits than males. This sex difference was abrogated by ovariectomy and senescence and was partially restored by estrogen replacement, implicating ovarian hormones in the observed sex differences in humans with FHM1. These findings demonstrate that genetic and hormonal factors modulate susceptibility to SD and neurological deficits in FHM1 mutant mice, providing a potential mechanism for the phenotypic diversity of human migraine and aura.

THE MECHANISM OF TUMORIGENESIS IN THE IMMORTALIZED HUMAN PANCREATIC CELL LINES: CELL CULTURE MODELS OF HUMAN PANCREATIC CANCER

The mechanism of tumorigenesis in the immortalized human pancreatic cell lines: cell culture models of human pancreatic cancer Pancreatic ductal adenocarcinoma (PDAC) is the most lethal cancer in the world. The most common genetic lesions identified in PDAC include activation of K-ras (90%) and Her2 (70%), loss of p16 (95%) and p14 (40%), inactivation p53 (50-75%) and Smad4 (55%). However, the role of these signature gene alterations in PDAC is still not well understood, especially, how these genetic lesions individually or in combination contribute mechanistically to human pancreatic oncogenesis is still elusive. Moreover, a cell culture transformation model with sequential accumulation of signature genetic alterations in human pancreatic ductal cells that resembles the multiple-step human pancreatic carcinogenesis is still not established. In the present study, through the stepwise introduction of the signature genetic alterations in PDAC into the HPV16-E6E7 immortalized human pancreatic duct epithelial (HPDE) cell line and the hTERT immortalized human pancreatic ductal HPNE cell line, we developed the novel experimental cell culture transformation models with the most frequent gene alterations in PDAC and further dissected the molecular mechanism of transformation. We demonstrated that the combination of activation of K-ras and Her2, inactivation of p16/p14 and Smad4, or K-ras mutation plus p16 inactivation, was sufficient for the tumorigenic transformation of HPDE or HPNE cells respectively. We found that these transformed cells exhibited enhanced cell proliferation, anchorage-independent growth in soft agar, and grew tumors with PDAC histopathological features in orthotopic mouse model. Molecular analysis showed that the activation of K-ras and Her2 downstream effector pathways –MAPK, RalA, FAK, together with upregulation of cyclins and c-myc were involved in the malignant transformation. We discovered that MDM2, BMP7 and Bmi-1 were overexpressed in the tumorigenic HPDE cells, and that Smad4 played important roles in regulation of BMP7 and Bmi-1 gene expression and the tumorigenic transformation of HPDE cells. IPA signaling pathway analysis of microarray data revealed that abnormal signaling pathways are involved in transformation. This study is the first complete transformation model of human pancreatic ductal cells with the most common gene alterations in PDAC. Altogether, these novel transformation models more closely recapitulate the human pancreatic carcinogenesis from the cell origin, gene lesion, and activation of specific signaling pathway and histopathological features.

Cultural models of healing and health: An ethnography of professional nurses and healers

Cultural models of the domains healing and health are important in how people understand health and their behavior regarding it. The biomedicine model has been predominant in Western society. Recent popularity of holistic health and alternative healing modalities contrasts with the biomedical model and the assumptions upon which that model has been practiced. The holistic health movement characterizes an effort by health care providers and others such as nurses to expand the biomedical model and has often incorporated alternative modalities. This research described and compared the cultural models of healing of professional nurses and alternative healers. A group of nursing faculty who promote a holistic model were compared to a group of healers using healing touch. Ethnographic methods of participant observation, free listing and pile sort were used. Theoretical sampling in the free listings reached saturation at 18 in the group of nurses and 21 in the group of healers. Categories consistent for both groups emerged from the data. These were: physical, mental, attitude, relationships, spiritual, self management, and health seeking including biomedical and alternative resources. The healers had little differentiation between the concepts health and healing. The nurses, however, had more elements in self management for health and in health seeking for healing. This reflects the nurse's role in facilitating the shift in locus of responsibility between health and healing. The healers provided more specific information regarding alternative resources. The healer's conceptualization of health was embedded in a spiritual belief system and contrasted dramatically with that of biomedicine. The healer's models also contrasted with holistic health in the areas of holism, locus of responsibility, and dealing with uncertainty. The similarity between the groups and their dissimilarity to biomedicine suggest a larger cultural shift in beliefs regarding health care. ^

Models of DNA sequence evolution

Models of DNA sequence evolution and methods for estimating evolutionary distances are needed for studying the rate and pattern of molecular evolution and for inferring the evolutionary relationships of organisms or genes. In this dissertation, several new models and methods are developed.^ The rate variation among nucleotide sites: To obtain unbiased estimates of evolutionary distances, the rate heterogeneity among nucleotide sites of a gene should be considered. Commonly, it is assumed that the substitution rate varies among sites according to a gamma distribution (gamma model) or, more generally, an invariant+gamma model which includes some invariable sites. A maximum likelihood (ML) approach was developed for estimating the shape parameter of the gamma distribution $(\alpha)$ and/or the proportion of invariable sites $(\theta).$ Computer simulation showed that (1) under the gamma model, $\alpha$ can be well estimated from 3 or 4 sequences if the sequence length is long; and (2) the distance estimate is unbiased and robust against violations of the assumptions of the invariant+gamma model.^ However, this ML method requires a huge amount of computational time and is useful only for less than 6 sequences. Therefore, I developed a fast method for estimating $\alpha,$ which is easy to implement and requires no knowledge of tree. A computer program was developed for estimating $\alpha$ and evolutionary distances, which can handle the number of sequences as large as 30.^ Evolutionary distances under the stationary, time-reversible (SR) model: The SR model is a general model of nucleotide substitution, which assumes (i) stationary nucleotide frequencies and (ii) time-reversibility. It can be extended to SRV model which allows rate variation among sites. I developed a method for estimating the distance under the SR or SRV model, as well as the variance-covariance matrix of distances. Computer simulation showed that the SR method is better than a simpler method when the sequence length $L>1,000$ bp and is robust against deviations from time-reversibility. As expected, when the rate varies among sites, the SRV method is much better than the SR method.^ The evolutionary distances under nonstationary nucleotide frequencies: The statistical properties of the paralinear and LogDet distances under nonstationary nucleotide frequencies were studied. First, I developed formulas for correcting the estimation biases of the paralinear and LogDet distances. The performances of these formulas and the formulas for sampling variances were examined by computer simulation. Second, I developed a method for estimating the variance-covariance matrix of the paralinear distance, so that statistical tests of phylogenies can be conducted when the nucleotide frequencies are nonstationary. Third, a new method for testing the molecular clock hypothesis was developed in the nonstationary case. ^

A comparison of Markov and generalized linear models of hospital mortality

This paper reports a comparison of three modeling strategies for the analysis of hospital mortality in a sample of general medicine inpatients in a Department of Veterans Affairs medical center. Logistic regression, a Markov chain model, and longitudinal logistic regression were evaluated on predictive performance as measured by the c-index and on accuracy of expected numbers of deaths compared to observed. The logistic regression used patient information collected at admission; the Markov model was comprised of two absorbing states for discharge and death and three transient states reflecting increasing severity of illness as measured by laboratory data collected during the hospital stay; longitudinal regression employed Generalized Estimating Equations (GEE) to model covariance structure for the repeated binary outcome. Results showed that the logistic regression predicted hospital mortality as well as the alternative methods but was limited in scope of application. The Markov chain provides insights into how day to day changes of illness severity lead to discharge or death. The longitudinal logistic regression showed that increasing illness trajectory is associated with hospital mortality. The conclusion is reached that for standard applications in modeling hospital mortality, logistic regression is adequate, but for new challenges facing health services research today, alternative methods are equally predictive, practical, and can provide new insights. ^

Non-staphylococcal infections of cardiac implantable electronic devices

Background. The number of infections of cardiac implantable electronic devices (CIED) continues to escalate out of proportion to the increase rate of device implantation. Staphylococcal organisms account for 70% to 90% of all CIED infections. However, little is known about non-staphylococcal infections, which have been described only in case reports, small case series or combined in larger studies with staphylococcal CIED infections, thereby diluting their individual impact. ^ Methods. A retrospective review of hospital records of patients admitted with a CIED-related infections were identified within four academic hospitals in Houston, Texas between 2002 and 2009. ^ Results. Of the 504 identified patients with CIED-related infection, 80 (16%) had a non-staphylococcal infection and were the focus of this study. Although the demographics and comorbities of subjects were comparable to other reports, our study illustrates many key points: (a) the microbiologic diversity of non-staphylococcal infections was rather extensive, as it included other Gram-positive bacteria like streptococci and enterococci, a variety of Gram-negative bacteria, atypical bacteria including Nocardia and Mycobacteria, and fungi like Candida and Aspergillus; (b) the duration of CIED insertion prior to non-staphylococcal infection was relatively prolong (mean, 109 ± 27 weeks), of these 44% had their device previously manipulated within a mean of 29.5 ± 6 weeks; (c) non-staphylococcal organisms appear to be less virulent, cause prolonged clinical symptoms prior to admission (mean, 48 ± 12.8 days), and are associated with a lower mortality (4%) than staphylococcal organisms; (d) thirteen patients (16%) presented with CIED-related endocarditis; (e) although not described in prior reports, we identified 3 definite and 2 suspected cases of secondary Gram-negative bacteremia seeding of the CIED; and (f) inappropriate antimicrobial coverage was provided in approximately 50% of patients with non-staphylococcal infections for a mean period of 2.1 days. ^ Conclusions. Non-staphylococcal CIED-related infections are prevalent and diverse with a relatively low virulence and mortality rate. Since non-staphylococcal organisms are capable of secondarily seeding the CIED, a high suspicion for CIED-related infection is warranted in patients with bloodstream infection. Additionally, in patients with suspected CIED infection, adequate Gram positive and -negative antibacterial coverage should be administered until microbiologic data become available.^

A comparison of healthcare access, healthcare utilization and asthma self-management for Hispanic children in border and non-border regions of Texas

The purpose of this culminating experience was to investigate the relationships between healthcare utilization, insurance coverage, and socioeconomic characteristics of children with asthma along the Texas-Mexico Border. A secondary data analysis was conducted on cross-sectional data from the Texas Child Asthma Call-back Survey, a follow-up survey to the random digit dialed Behavior Risk Factor Surveillance Study (BRFSS) conducted between 2006-2009 ( n = 556 adults living in households with a child with asthma).^ The proportion of Hispanic children with asthma in Border areas of Texas was more than twice that of non-Border areas (84.8% vs. 28.8%). Parents in Border areas were less likely to have their own health insurance (OR = 0.251, 95% C.I. = 0.117-0.540) and less likely to complete the survey in English than Spanish (OR = 0.251 95% C.I. = 0.117-0.540) than parents in non-Border areas. No significant socio-economic or health care utilization differences were noted between Hispanic children living in Border areas compared to Hispanic children living in non-Border areas. Children with asthma along the Texas-Mexico Border, regardless of ethnicity and language, have insurance coverage rates, reported cost barriers to care, symptom management, and medication usage patterns similar to those in non-Border areas. When compared to English-speakers, Spanish-speaking parents in Texas as a whole are far less likely to be taught what to do during an asthma attack (50.2% vs. 78.6%).^ Language preference, rather than ethnicity or geographical residence, played a larger role on childhood asthma-related health disparities for children in Texas. Spanish-speaking parents in are less likely to receive adequate asthma self-management education. Investigating the effects of Hispanic acculturation rates and incongruent parent-child health insurance coverage may provide better insight into the health disparities of children along the Texas-Mexico Border.^

Post-transcriptional Regulation of Mammalian Gene Expression in Non-coding Region of Target RNA

Tumor Suppressor Candidate 2 (TUSC2) is a novel tumor suppressor gene located in the human chromosome 3p21.3 region. TUSC2 mRNA transcripts could be detected on Northern blots in both normal lung and some lung cancer cell lines, but no endogenous TUSC2 protein could be detected in a majority of lung cancer cell lines. Mechanisms regulating TUSC2 protein expression and its inactivation in primary lung cancer cells are largely unknown. We investigated the role of the 5’- and 3’-untranslated regions (UTRs) of the TUSC2 gene in the regulation of TUSC2 protein expression. We found that two small upstream open-reading frames (uORFs) in the 5’UTR of TUSC2 could markedly inhibit the translational initiation of TUSC2 protein by interfering with the “scanning” of the ribosome initiation complexes. Site-specific stem-loop array reverse transcription-polymerase chain reaction (SLA-RT-PCR) verified several micoRNAs (miRNAs) targeted at 3’UTR and directed TUSC2 cleavage and degradation. In addition, we used the established let-7-targeted high mobility group A2 (Hmga2) mRNA as a model system to study the mechanism of regulation of target mRNA by miRNAs in mammalian cells under physiological conditions. There have been no evidence of direct link between mRNA downregulation and mRNA cleavages mediated by miRNAs. Here we showed that the endonucleolytic cleavages on mRNAs were initiated by mammalian miRNA in seed pairing style. Let-7 directed cleavage activities among the eight predicted potential target sites have varied efficiency, which are influenced by the positional and the structural contexts in the UTR. The 5’ cleaved RNA fragments were mostly oligouridylated at their 3’-termini and accumulated for delayed 5’–3’ degradation. RNA fragment oligouridylation played important roles in marking RNA fragments for delayed bulk degradation and in converting RNA degradation mode from 3’–5’ to 5’–3’ with cooperative efforts from both endonucleolytic and non-catalytic miRNA-induced silencing complex (miRISC). Our findings point to a mammalian miRNA-mediated mechanism for the regulation of mRNA that miRNA can decrease target mRNA through target mRNA cleavage and uridine addition