myogenin: Human candidate gene and knockout mouse effect

The myogenin gene encodes an evolutionarily conserved basic helix-loop-helix transcription factor that regulates the expression of skeletal muscle-specific genes and its homozygous deletion results in mice who die of respiratory failure at birth. The histology of skeletal muscle in the myogenin null mice is reminiscent of that found in some severe congenital myopathy patients, many of whom also die of respiratory complications and provides the rationale that an aberrant human myogenin (myf4) coding region could be associated with some congenital myopathy conditions.^ With PCR, we found similarly sized amplimers for the three exons of the myogenin gene in 37 patient and 40 control samples. In contrast to the GeneBank sequence for human myogenin, we report several differences in flanking and coding regions plus an additional 659 and 498 bps in the first and second introns, respectively, in all patients and controls. We also find a novel (CA)-dinucleotide repeat in the second intron. No causative mutations were detected in the myogenin coding regions of genomic DNA from patients with severe congenital myopathy.^ Severe congenital myopathies in humans are often associated with respiratory complications and pulmonary hypoplasia. We have employed the myogenin null mouse, which lacks normal development of skeletal muscle fibers as a genetically defined severe congenital myopathy mouse model to evaluate the effect of absent fetal breathing movement on pulmonary development.^ Significant differences are observed at embryonic days E14, E17 and E20 of lung:body weight, total DNA and histologically, suggesting that the myogenin null lungs are hypoplastic. RT-PCR, in-situ immunofluorescence and EM reveal pneumocyte type II differentiation in both null and wild lungs as early as E14. However, at E14, myogenin null lungs have decreased BrdU incorporation while E17 through term, augmented cell death is detected in the myogenin null lungs, not seen in wild littermates. Absent mechanical forces appear to impair normal growth, but not maturation, of the developing lungs in myogenin null mouse.^ These investigations provide the basis for delineating the DNA sequence of the myogenin gene and and highlight the importance of skeletal muscle development in utero for normal lung organogenesis. My observation of no mutations within the coding regions of the human myogenin gene in DNA from patients with severe congenital myopathy do not support any association with this condition. ^

The association between maternal use of selective serotonin reuptake inhibitors during pregnancy and adverse pregnancy outcomes

Maternal use of SSRIs for depression and anxiety during pregnancy has increased over the last decade. Recent studies have questioned the safety of these antidepressants when used in during pregnancy. The aim of this project is to assess the associations between maternal SSRI use and GH, SGA, and preterm birth using data from a U.S. population-based study with self-reported exposure information. ^ The study population is comprised of mothers of control infants from the NBDPS, an ongoing, multi-state, population-based case-control study. Mothers were asked about any use of medications during pregnancy, including the dates they started and stopped taking each medication. Maternal GH was self-reported, while gestational age and birth weight were calculated from information on birth certificates or medical records. ^ Our study found that women exposed to SSRIs in the first trimester and beyond had a higher odds of GH compared to unexposed women (aOR=1.96, 95% CI=1.02-3.74). Women who used SSRIs only in the first trimester had no increased odds of GH (aOR=0.77, 95% CI=0.24-2.50). Women who used SSRIs throughout their entire pregnancy had a two-fold increase in the odds of delivering an SGA infant compared to unexposed women (aOR=2.16, 95% CI=1.01-4.62), while women who reported SSRI use only in the first trimester had a decreased odds of delivering an SGA infant (aOR=0.56, 95% CI=0.14-2.34). Finally, both women who used SSRIs in the first trimester only (aOR=1.58, 95% CI=0.71-3.51) and women who used SSRIs in the first trimester and beyond (aOR=1.49, 95% CI=0.76-2.90) had an increased odds of delivering preterm compared to unexposed women. ^ Results from our study suggest that women who use SSRIs in the first trimester and beyond have an increased and significant odds of GH and SGA. An increase in the odds of preterm birth was also observed among women exposed in this period and is consistent with the results of previous studies which had much larger sample sizes. Women who use SSRIs only in the first trimester appear to have no increased odds of GH or SGA, but may have an increased odds of preterm birth. These findings are consistent with previous studies and highlight how exposure to SSRIs at different points in gestation may result in different risks for these outcomes. ^

Posttraumatic stress disorder among veterans of the Operation Iraqi Freedom (OIF) and Operation Enduring Freedom (OEF) wars: Psychological comorbidities, postdeployment social support and unit support

Much attention has been given to treating Operation Iraqi Freedom/Operation Enduring (OIF/OEF) Veterans with posttraumatic stress disorder (PTSD). However, little attention is given to those Veterans who do not meet diagnostic criteria for PTSD but who may still benefit from intervention. Research is needed to investigate the impact of how different racial/ethnic backgrounds, different levels of social support and comorbid mental health disorders impact OIF/OEF Veterans with varying levels of PTSD. The purpose of this dissertation is to examine the association of comorbid Axis I disorders, race/ethnicity, different levels of postdeployment social support and unit support on OIF/OEF Veterans with varying levels of PTSD. Data for this dissertation were from postdeployment screenings of OIF/OEF Veterans from a large Veterans Affairs hospital in southeast Texas. To examine the study hypotheses, we conducted multinomial logistic regressions of the clinician reported data. ^ The first article examined the prevalence of subthreshold and full levels of PTSD and compared Axis I and alcohol use comorbidity rates among 1,362 OIF/OEF Veterans with varying levels of PTSD. Results suggest that OIF/OEF Veterans with subthreshold PTSD experience similar levels of psychological distress as those with full PTSD and highlight the need to provide timely and appropriate mental health services to individuals who may not meet the diagnostic criteria for full PTSD. ^ These results suggest that OIF/OEF Veterans of all race/ethnicities can benefit from strong social support systems. Postdeployment social support was found to be a protective factor against the development of PTSD among White, Black and Hispanic veterans while deployment unit support was a protective factor only among Black Veterans. The second article investigated the association between postdeployment social support and unit support with varying levels of PTSD by race/ethnicity among 1,115 OIF/OEF Veterans. ^ The results of this study can help to formulate treatment and interventions for OIF/OEF Veterans with varying levels of PTSD and social support systems.^

Using incomplete citation data for MEDLINE results ranking.

Information overload is a significant problem for modern medicine. Searching MEDLINE for common topics often retrieves more relevant documents than users can review. Therefore, we must identify documents that are not only relevant, but also important. Our system ranks articles using citation counts and the PageRank algorithm, incorporating data from the Science Citation Index. However, citation data is usually incomplete. Therefore, we explore the relationship between the quantity of citation information available to the system and the quality of the result ranking. Specifically, we test the ability of citation count and PageRank to identify "important articles" as defined by experts from large result sets with decreasing citation information. We found that PageRank performs better than simple citation counts, but both algorithms are surprisingly robust to information loss. We conclude that even an incomplete citation database is likely to be effective for importance ranking.

Using incomplete citation data for MEDLINE results ranking.

Information overload is a significant problem for modern medicine. Searching MEDLINE for common topics often retrieves more relevant documents than users can review. Therefore, we must identify documents that are not only relevant, but also important. Our system ranks articles using citation counts and the PageRank algorithm, incorporating data from the Science Citation Index. However, citation data is usually incomplete. Therefore, we explore the relationship between the quantity of citation information available to the system and the quality of the result ranking. Specifically, we test the ability of citation count and PageRank to identify "important articles" as defined by experts from large result sets with decreasing citation information. We found that PageRank performs better than simple citation counts, but both algorithms are surprisingly robust to information loss. We conclude that even an incomplete citation database is likely to be effective for importance ranking.

NETWORK TOPOLOGY IN HUMAN PROTEIN INTERACTION DATA PREDICTS FUNCTIONAL ASSOCIATION

High-throughput assays, such as yeast two-hybrid system, have generated a huge amount of protein-protein interaction (PPI) data in the past decade. This tremendously increases the need for developing reliable methods to systematically and automatically suggest protein functions and relationships between them. With the available PPI data, it is now possible to study the functions and relationships in the context of a large-scale network. To data, several network-based schemes have been provided to effectively annotate protein functions on a large scale. However, due to those inherent noises in high-throughput data generation, new methods and algorithms should be developed to increase the reliability of functional annotations. Previous work in a yeast PPI network (Samanta and Liang, 2003) has shown that the local connection topology, particularly for two proteins sharing an unusually large number of neighbors, can predict functional associations between proteins, and hence suggest their functions. One advantage of the work is that their algorithm is not sensitive to noises (false positives) in high-throughput PPI data. In this study, we improved their prediction scheme by developing a new algorithm and new methods which we applied on a human PPI network to make a genome-wide functional inference. We used the new algorithm to measure and reduce the influence of hub proteins on detecting functionally associated proteins. We used the annotations of the Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) as independent and unbiased benchmarks to evaluate our algorithms and methods within the human PPI network. We showed that, compared with the previous work from Samanta and Liang, our algorithm and methods developed in this study improved the overall quality of functional inferences for human proteins. By applying the algorithms to the human PPI network, we obtained 4,233 significant functional associations among 1,754 proteins. Further comparisons of their KEGG and GO annotations allowed us to assign 466 KEGG pathway annotations to 274 proteins and 123 GO annotations to 114 proteins with estimated false discovery rates of <21% for KEGG and <30% for GO. We clustered 1,729 proteins by their functional associations and made pathway analysis to identify several subclusters that are highly enriched in certain signaling pathways. Particularly, we performed a detailed analysis on a subcluster enriched in the transforming growth factor β signaling pathway (P<10-50) which is important in cell proliferation and tumorigenesis. Analysis of another four subclusters also suggested potential new players in six signaling pathways worthy of further experimental investigations. Our study gives clear insight into the common neighbor-based prediction scheme and provides a reliable method for large-scale functional annotations in this post-genomic era.

Intravenous mesenchymal stem cell therapy for traumatic brain injury.

OBJECT: Cell therapy has shown preclinical promise in the treatment of many diseases, and its application is being translated to the clinical arena. Intravenous mesenchymal stem cell (MSC) therapy has been shown to improve functional recovery after traumatic brain injury (TBI). Herein, the authors report on their attempts to reproduce such observations, including detailed characterizations of the MSC population, non-bromodeoxyuridine-based cell labeling, macroscopic and microscopic cell tracking, quantification of cells traversing the pulmonary microvasculature, and well-validated measurement of motor and cognitive function recovery. METHODS: Rat MSCs were isolated, expanded in vitro, immunophenotyped, and labeled. Four million MSCs were intravenously infused into Sprague-Dawley rats 24 hours after receiving a moderate, unilateral controlled cortical impact TBI. Infrared macroscopic cell tracking was used to identify cell distribution. Immunohistochemical analysis of brain and lung tissues 48 hours and 2 weeks postinfusion revealed transplanted cells in these locations, and these cells were quantified. Intraarterial blood sampling and flow cytometry were used to quantify the number of transplanted cells reaching the arterial circulation. Motor and cognitive behavioral testing was performed to evaluate functional recovery. RESULTS: At 48 hours post-MSC infusion, the majority of cells were localized to the lungs. Between 1.5 and 3.7% of the infused cells were estimated to traverse the lungs and reach the arterial circulation, 0.295% reached the carotid artery, and a very small percentage reached the cerebral parenchyma (0.0005%) and remained there. Almost no cells were identified in the brain tissue at 2 weeks postinfusion. No motor or cognitive functional improvements in recovery were identified. CONCLUSIONS: The intravenous infusion of MSCs appeared neither to result in significant acute or prolonged cerebral engraftment of cells nor to modify the recovery of motor or cognitive function. Less than 4% of the infused cells were likely to traverse the pulmonary microvasculature and reach the arterial circulation, a phenomenon termed the "pulmonary first-pass effect," which may limit the efficacy of this therapeutic approach. The data in this study contradict the findings of previous reports and highlight the potential shortcomings of acute, single-dose, intravenous MSC therapy for TBI.

Diffusion tensor imaging of rat spinal cord in vivo

Magnetic resonance imaging, with its exquisite soft tissue contrast, is an ideal modality for investigating spinal cord pathology. While conventional MRI techniques are very sensitive for spinal cord pathology, their specificity is somewhat limited. Diffusion MRI is an advanced technique which is a very sensitive and specific indicator of the integrity of white matter tracts. Diffusion imaging has been shown to detect early ischemic changes in white matter, while conventional imaging demonstrates no change. By acquiring the complete apparent diffusion tensor (ADT), tissue diffusion properties can be expressed in terms of quantitative and rotationally invariant parameters. ^ Systematic study of SCI in vivo requires controlled animal models such as the popular rat model. To date, studies of spinal cord using ADT imaging have been performed exclusively in fixed, excised spinal cords, introducing inevitable artifacts and losing the benefits of MRI's noninvasive nature. In vivo imaging reflects the actual in vivo tissue properties, and allows each animal to be imaged at multiple time points, greatly reducing the number of animals required to achieve statistical significance. Because the spinal cord is very small, the available signal-to-noise ratio (SNR) is very low. Prior spin-echo based ADT studies of rat spinal cord have relied on high magnetic field strengths and long imaging times—on the order of 10 hours—for adequate SNR. Such long imaging times are incompatible with in vivo imaging, and are not relevant for imaging the early phases following SCI. Echo planar imaging (EPI) is one of the fastest imaging methods, and is popular for diffusion imaging. However, EPI further lowers the image SNR, and is very sensitive to small imperfections in the magnetic field, such as those introduced by the bony spine. Additionally, The small field-of-view (FOV) needed for spinal cord imaging requires large imaging gradients which generate EPI artifacts. The addition of diffusion gradients introduces yet further artifacts. ^ This work develops a method for rapid EPI-based in vivo diffusion imaging of rat spinal cord. The method involves improving the SNR using an implantable coil; reducing magnetic field inhomogeneities by means of an autoshim, and correcting EPI artifacts by post-processing. New EPI artifacts due to diffusion gradients described, and post-processing correction techniques are developed. ^ These techniques were used to obtain rotationally invariant diffusion parameters from 9 animals in vivo, and were validated using the gold-standard, but slow, spinecho based diffusion sequence. These are the first reported measurements of the ADT in spinal cord in vivo . ^ Many of the techniques described are equally applicable toward imaging of human spinal cord. We anticipate that these techniques will aid in evaluating and optimizing potential therapies, and will lead to improved patient care. ^

THEORETICAL STUDIES ON THE METHODS OF RECONSTRUCTING PHYLOGENETIC TREES FROM DNA SEQUENCE DATA (MOLECULAR EVOLUTION, HOMINOID EVOLUTION, COMPUTER SIMULATION)

(1) A mathematical theory for computing the probabilities of various nucleotide configurations is developed, and the probability of obtaining the correct phylogenetic tree (model tree) from sequence data is evaluated for six phylogenetic tree-making methods (UPGMA, distance Wagner method, transformed distance method, Fitch-Margoliash's method, maximum parsimony method, and compatibility method). The number of nucleotides (m*) necessary to obtain the correct tree with a probability of 95% is estimated with special reference to the human, chimpanzee, and gorilla divergence. m* is at least 4,200, but the availability of outgroup species greatly reduces m* for all methods except UPGMA. m* increases if transitions occur more frequently than transversions as in the case of mitochondrial DNA. (2) A new tree-making method called the neighbor-joining method is proposed. This method is applicable either for distance data or character state data. Computer simulation has shown that the neighbor-joining method is generally better than UPGMA, Farris' method, Li's method, and modified Farris method on recovering the true topology when distance data are used. A related method, the simultaneous partitioning method, is also discussed. (3) The maximum likelihood (ML) method for phylogeny reconstruction under the assumption of both constant and varying evolutionary rates is studied, and a new algorithm for obtaining the ML tree is presented. This method gives a tree similar to that obtained by UPGMA when constant evolutionary rate is assumed, whereas it gives a tree similar to that obtained by the maximum parsimony tree and the neighbor-joining method when varying evolutionary rate is assumed. ^

Theory of uncertainty in illness in patients with cancer of unknown primary origin: Structure providers as antecedents of uncertainty in a population of cancer patients with an unknown primary diagnosis

Uncertainty has been found to be a major component of the cancer experience and can dramatically affect psychosocial adaptation and outcomes of a patient's disease state (McCormick, 2002). Patients with a diagnosis of Carcinoma of Unknown Primary (CUP) may experience higher levels of uncertainty due to the unpredictability of current and future symptoms, limited treatment options and an undetermined life expectancy. To date, only one study has touched upon uncertainty and its' effects on those with CUP but no information exists concerning the effects of uncertainty regarding diagnosis and treatment on the distress level and psychosocial adjustment of this population (Parker & Lenzi, 2003). ^ Mishel's Uncertainty in Illness Theory (1984) proposes that uncertainty is preceded by three variables, one of which being Structure Providers. Structure Providers include credible authority, the degree of trust and confidence the patient has with their doctor, education and social support. It was the goal of this study to examine the relationship between uncertainty and Structure Providers to support the following hypotheses: (1) There will be a negative association between credible authority and uncertainty, (2) There will be a negative association between education level and uncertainty, and (3) There will be a negative association between social support and uncertainty. ^ This cross-sectional analysis utilized data from 219 patients following their initial consultation with their oncologist. Data included the Mishel Uncertainty in Illness Scale (MUIS) which was used to determine patients' uncertainty levels, the Medical Outcomes Study-Social Support Scale (MOSS-SSS) to assess patients, levels of social support, the Patient Satisfaction Questionnaire (PSQ-18) and the Cancer Diagnostic Interview Scale (CDIS) to measure credible authority and general demographic information to assess age, education, marital status and ethnicity. ^ In this study we found that uncertainty levels were generally higher in this sample as compared to other types of cancer populations. And while our results seemed to support most of our hypothesis, we were only able to show significant associations between two. The analyses indicated that credible authority measured by both the CDIS and the PSQ was a significant predictor of uncertainty as was social support measured by the MOSS-SS. Education has shown to have an inconsistent pattern of effect in relation to uncertainty and in the current study there was not enough data to significantly support our hypothesis. ^ The results of this study generally support Mishel's Theory of Uncertainty in Illness and highlight the importance of taking into consideration patients, psychosocial factors as well as employing proper communication practices between physicians and their patients.^

Logistic regression with incompletely observed binary

Logistic regression is one of the most important tools in the analysis of epidemiological and clinical data. Such data often contain missing values for one or more variables. Common practice is to eliminate all individuals for whom any information is missing. This deletion approach does not make efficient use of available information and often introduces bias.^ Two methods were developed to estimate logistic regression coefficients for mixed dichotomous and continuous covariates including partially observed binary covariates. The data were assumed missing at random (MAR). One method (PD) used predictive distribution as weight to calculate the average of the logistic regressions performing on all possible values of missing observations, and the second method (RS) used a variant of resampling technique. Additional seven methods were compared with these two approaches in a simulation study. They are: (1) Analysis based on only the complete cases, (2) Substituting the mean of the observed values for the missing value, (3) An imputation technique based on the proportions of observed data, (4) Regressing the partially observed covariates on the remaining continuous covariates, (5) Regressing the partially observed covariates on the remaining continuous covariates conditional on response variable, (6) Regressing the partially observed covariates on the remaining continuous covariates and response variable, and (7) EM algorithm. Both proposed methods showed smaller standard errors (s.e.) for the coefficient involving the partially observed covariate and for the other coefficients as well. However, both methods, especially PD, are computationally demanding; thus for analysis of large data sets with partially observed covariates, further refinement of these approaches is needed. ^