Efficacy of hepatic transplantation in patients with primary sclerosing cholangitis

Controlled trials to assess the therapeutic benefit of orthotopic hepatic transplantation (OHTx) for primary sclerosing cholangitis (PSC) cannot be justified in view of improvement of patient survival after this operation since 1981. However, the actual patient survival with OHTx can be compared with the Mayo model estimated survival probabilities without OHTx. This model, which encompasses physical, biochemical and histopathologic parameters of PSC, was constructed from a study of 392 conservatively treated PSC patients at five international centers in England and North America. We compared the actual survival of 216 adult patients with the diagnosis of advanced PSC who underwent hepatic replacement with the expected survival estimated by the Mayo PSC natural history model, 'the simulated control technique.' OHTx was performed at the University of Pittsburgh and Mayo Medical Center between 5 December 1981 and 26 December 1990. The mean (plus or minus standard deviation) post-OHTx follow-up period was 34 ± 25 months (range of zero to 104 months). Before transplantation, biliary or portal hypertensive operation, or both, was performed upon 104 patients. At operation, the mean age of recipients was 42.1 ± 11.3 years and the mean value of total serum bilirubin was 13.3 ± 13.0 milligrams per deciliter. Extensive septal fibrosis and cirrhosis were histologically documented in 97 percent of the patients, with splenomegaly in 63 percent. Immunosuppressive therapy was based primarily on cyclosporin in 184 recipients and FK-506 in 32. Within six months, the Kaplan-Meier survival probability after OHTx (0.89) already was higher than predicted by the Mayo model (0.83). At five years, the Kaplan-Meier actual survival with OHTx was 0.73 compared with 0.28 expected Mayo model survival. The overall increased survival rate with transplantation was statistically significant (chi-square equals 126.6; p<0.001). At all risk stratifications, OHTx significantly improved survival with a p value of 0.031 (low risk), 0.001 (moderate risk) and <0.001 (high risk). Thus, OHTx is effective therapy for PSC. Disease gravity and unsuspected cholangiocarcinoma in the excised native liver adversely influenced short and long term survival rates after transplantation, respectively

Regulatory feedback response mechanisms to phosphate starvation in rice

Phosphorus is a growth-limiting nutrient for plants. The growing scarcity of phosphate stocks threatens global food security. Phosphate-uptake regulation is so complex and incompletely known that attempts to improve phosphorus use efficiency have had extremely limited success. This study improves our understanding of the molecular mechanisms underlying phosphate uptake by investigating the transcriptional dynamics of two regulators: the Ubiquitin ligase PHO2 and the long non-coding RNA IPS1. Temporal measurements of RNA levels have been integrated into mechanistic mathematical models using advanced statistical techniques. Models based solely on current knowledge could not adequately explain the temporal expression profiles. Further modeling and bioinformatics analysis have led to the prediction of three regulatory features: the PHO2 protein mediates the degradation of its own transcriptional activator to maintain constant PHO2 mRNA levels; the binding affinity of the transcriptional activator of PHO2 is impaired by a phosphate-sensitive transcriptional repressor/inhibitor; and the extremely high levels of IPS1 and its rapid disappearance upon Pi re-supply are best explained by Pi-sensitive RNA protection. This work offers both new opportunities for plant phosphate research that will be essential for informing the development of phosphate efficient crop varieties, and a foundation for the development of models integrating phosphate with other stress responses

Effects of the Training Dataset Characteristics on the Performance of Nine Species Distribution Models: Application to Diabrotica virgifera virgifera

Many distribution models developed to predict the presence/absence of invasive alien species need to be fitted to a training dataset before practical use. The training dataset is characterized by the number of recorded presences/absences and by their geographical locations. The aim of this paper is to study the effect of the training dataset characteristics on model performance and to compare the relative importance of three factors influencing model predictive capability; size of training dataset, stage of the biological invasion, and choice of input variables. Nine models were assessed for their ability to predict the distribution of the western corn rootworm, Diabrotica virgifera virgifera, a major pest of corn in North America that has recently invaded Europe. Twenty-six training datasets of various sizes (from 10 to 428 presence records) corresponding to two different stages of invasion (1955 and 1980) and three sets of input bioclimatic variables (19 variables, six variables selected using information on insect biology, and three linear combinations of 19 variables derived from Principal Component Analysis) were considered. The models were fitted to each training dataset in turn and their performance was assessed using independent data from North America and Europe. The models were ranked according to the area under the Receiver Operating Characteristic curve and the likelihood ratio. Model performance was highly sensitive to the geographical area used for calibration; most of the models performed poorly when fitted to a restricted area corresponding to an early stage of the invasion. Our results also showed that Principal Component Analysis was useful in reducing the number of model input variables for the models that performed poorly with 19 input variables. DOMAIN, Environmental Distance, MAXENT, and Envelope Score were the most accurate models but all the models tested in this study led to a substantial rate of mis-classification

Assessment of predictive models for chlorophyll-a concentration of a tropical lake

<p>Abstract</p> <p>Background</p> <p>This study assesses four predictive ecological models; Fuzzy Logic (FL), Recurrent Artificial Neural Network (RANN), Hybrid Evolutionary Algorithm (HEA) and multiple linear regressions (MLR) to forecast chlorophyll- a concentration using limnological data from 2001 through 2004 of unstratified shallow, oligotrophic to mesotrophic tropical Putrajaya Lake (Malaysia). Performances of the models are assessed using Root Mean Square Error (RMSE), correlation coefficient (r), and Area under the Receiving Operating Characteristic (ROC) curve (AUC). Chlorophyll-a have been used to estimate algal biomass in aquatic ecosystem as it is common in most algae. Algal biomass indicates of the trophic status of a water body. Chlorophyll- a therefore, is an effective indicator for monitoring eutrophication which is a common problem of lakes and reservoirs all over the world. Assessments of these predictive models are necessary towards developing a reliable algorithm to estimate chlorophyll- a concentration for eutrophication management of tropical lakes.</p> <p>Results</p> <p>Same data set was used for models development and the data was divided into two sets; training and testing to avoid biasness in results. FL and RANN models were developed using parameters selected through sensitivity analysis. The selected variables were water temperature, pH, dissolved oxygen, ammonia nitrogen, nitrate nitrogen and Secchi depth. Dissolved oxygen, selected through stepwise procedure, was used to develop the MLR model. HEA model used parameters selected using genetic algorithm (GA). The selected parameters were pH, Secchi depth, dissolved oxygen and nitrate nitrogen. RMSE, r, and AUC values for MLR model were (4.60, 0.5, and 0.76), FL model were (4.49, 0.6, and 0.84), RANN model were (4.28, 0.7, and 0.79) and HEA model were (4.27, 0.7, and 0.82) respectively. Performance inconsistencies between four models in terms of performance criteria in this study resulted from the methodology used in measuring the performance. RMSE is based on the level of error of prediction whereas AUC is based on binary classification task.</p> <p>Conclusions</p> <p>Overall, HEA produced the best performance in terms of RMSE, r, and AUC values. This was followed by FL, RANN, and MLR.</p

Resource Selection and Its Implications for Wide-Ranging Mammals of the Brazilian Cerrado

Conserving animals beyond protected areas is critical because even the largest reserves may be too small to maintain viable populations for many wide-ranging species. Identification of landscape features that will promote persistence of a diverse array of species is a high priority, particularly, for protected areas that reside in regions of otherwise extensive habitat loss. This is the case for Emas National Park, a small but important protected area located in the Brazilian Cerrado, the world's most biologically diverse savanna. Emas Park is a large-mammal global conservation priority area but is too small to protect wide-ranging mammals for the long-term and conserving these populations will depend on the landscape surrounding the park. We employed novel, noninvasive methods to determine the relative importance of resources found within the park, as well as identify landscape features that promote persistence of wide-ranging mammals outside reserve borders. We used scat detection dogs to survey for five large mammals of conservation concern: giant armadillo (Priodontes maximus), giant anteater (Myrmecophaga tridactyla), maned wolf (Chrysocyon brachyurus), jaguar (Panthera onca), and puma (Puma concolor). We estimated resource selection probability functions for each species from 1,572 scat locations and 434 giant armadillo burrow locations. Results indicate that giant armadillos and jaguars are highly selective of natural habitats, which makes both species sensitive to landscape change from agricultural development. Due to the high amount of such development outside of the Emas Park boundary, the park provides rare resource conditions that are particularly important for these two species. We also reveal that both woodland and forest vegetation remnants enable use of the agricultural landscape as a whole for maned wolves, pumas, and giant anteaters. We identify those features and their landscape compositions that should be prioritized for conservation, arguing that a multi-faceted approach is required to protect these species

FGF4 and Retinoic Acid Direct Differentiation of hESCs into PDX1-Expressing Foregut Endoderm in a Time- and Concentration-Dependent Manner

BACKGROUND: Retinoic acid (RA) and fibroblast growth factor 4 (FGF4) signaling control endoderm patterning and pancreas induction/expansion. Based on these findings, RA and FGFs, excluding FGF4, have frequently been used in differentiation protocols to direct differentiation of hESCs into endodermal and pancreatic cell types. In vivo, these signaling pathways act in a temporal and concentration-dependent manner. However, in vitro, the underlying basis for the time of addition of growth and differentiation factors (GDFs), including RA and FGFs, as well as the concentration is lacking. Thus, in order to develop robust and reliable differentiation protocols of ESCs into mature pancreatic cell types, including insulin-producing beta cells, it will be important to mechanistically understand each specification step. This includes differentiation of mesendoderm/definitive endoderm into foregut endoderm--the origin of pancreatic endoderm. METHODOLOGY/PRINCIPAL FINDINGS: Here, we provide data on the individual and combinatorial role of RA and FGF4 in directing differentiation of ActivinA (AA)-induced hESCs into PDX1-expressing cells. FGF4's ability to affect endoderm patterning and specification in vitro has so far not been tested. By testing out the optimal concentration and timing of addition of FGF4 and RA, we present a robust differentiation protocol that on average generates 32% PDX1(+) cells. Furthermore, we show that RA is required for converting AA-induced hESCs into PDX1(+) cells, and that part of the underlying mechanism involves FGF receptor signaling. Finally, further characterization of the PDX1(+) cells suggests that they represent foregut endoderm not yet committed to pancreatic, posterior stomach, or duodenal endoderm. CONCLUSION/SIGNIFICANCE: In conclusion, we show that RA and FGF4 jointly direct differentiation of PDX1(+) foregut endoderm in a robust and efficient manner. RA signaling mediated by the early induction of RARbeta through AA/Wnt3a is required for PDX1 expression. Part of RA's activity is mediated by FGF signaling

Cholesterol Metabolism Is Required for Intracellular Hedgehog Signal Transduction In Vivo

We describe the rudolph mouse, a mutant with striking defects in both central nervous system and skeletal development. Rudolph is an allele of the cholesterol biosynthetic enzyme, hydroxysteroid (17-beta) dehydrogenase 7, which is an intriguing finding given the recent implication of oxysterols in mediating intracellular Hedgehog (Hh) signaling. We see an abnormal sterol profile and decreased Hh target gene induction in the rudolph mutant, both in vivo and in vitro. Reduced Hh signaling has been proposed to contribute to the phenotypes of congenital diseases of cholesterol metabolism. Recent in vitro and pharmacological data also indicate a requirement for intracellular cholesterol synthesis for proper regulation of Hh activity via Smoothened. The data presented here are the first in vivo genetic evidence supporting both of these hypotheses, revealing a role for embryonic cholesterol metabolism in both CNS development and normal Hh signaling

The importance of organizational characteristics for improving outcomes in patients with chronic disease: a systematic review of congestive heart failure

Luci K. Leykum, Jacqueline Pugh, Valerie Lawrence, and Polly H. Noel are with the South Texas Veterans Health Care System and Department of Medicine, University of Texas Health Science Center at San Antonio, San Antonio TX, 78229, USA -- Michael Parchman is with the South Texas Veterans Health Care System and Department of Family and Community Medicine, University of Texas Health Science Center at San Antonio, San Antonio TX, 78229, USA -- Reuben R. McDaniel Jr. is with the McComb's School of Business, University of Texas at Austin, Austin TX, USABackground: Despite applications of models of care and organizational or system-level interventions to improve patient outcomes for chronic disease, consistent improvements have not been achieved. This may reflect a mismatch between the interventions and the nature of the settings in which they are attempted. The application of complex adaptive systems (CAS) framework to understand clinical systems and inform efforts to improve them may lead to more successful interventions. We performed a systematic review of interventions to improve outcomes of patients with congestive heart failure (CHF) to examine whether interventions consistent with CAS are more likely to be effective. We then examine differences between interventions that are most effective for improving outcomes for patients with CHF versus previously published data for type 2 diabetes to explore the potential impact of the nature of the disease on the types of interventions that are more likely to be effective. Methods: We conducted a systematic review of the literature between 1998 and 2008 of organizational interventions to improve care of patients with CHF. Two independent reviewers independently assessed studies that met inclusion criteria to determine whether each reported intervention reflected one or more CAS characteristics. The effectiveness of interventions was rated as either 0 (no effect), 0.5 (mixed effect), or 1.0 (effective) based on the type, number, and significance of reported outcomes. Fisher's exact test was used to examine the association between CAS characteristics and intervention effectiveness. Specific CAS characteristics associated with intervention effectiveness for CHF were contrasted with previously published data for type 2 diabetes. Results and discussion: Forty-four studies describing 46 interventions met eligibility criteria. All interventions utilized at least one CAS characteristic, and 85% were either 'mixed effect' or 'effective' in terms of outcomes. The number of CAS characteristics present in each intervention was associated with effectiveness (p < 0.001), supporting the idea that interventions consistent with CAS are more likely to be effective. The individual CAS characteristics associated with CHF intervention effectiveness were learning, self-organization, and co-evolution, a finding different from our previously published analysis of interventions for diabetes. We suggest this difference may be related to the degree of uncertainty involved in caring for patients with diabetes versus CHF. Conclusion: These results suggest that for interventions to be effective, they must be consistent with the CAS nature of clinical systems. The difference in specific CAS characteristics associated with intervention effectiveness for CHF and diabetes suggests that interventions must also take into account attributes of the disease.McCombs School of [email protected]

Developmental Exposure to a Toxic Spill Compromises Long-Term Reproductive Performance in a Wild, Long-Lived Bird: The White Stork (Ciconia ciconia)

Background/Objective: Exposure to environmental contaminants may result in reduced reproductive success and long- lasting population declines in vertebrates. Emerging data from laboratory studies on model species suggest that certain life- stages, such as development, should be of special concern. However, detailed investigations of long-term consequences of developmental exposure to environmental chemicals on breeding performance are currently lacking in wild populations of long-lived vertebrates. Here, we studied how the developmental exposure to a mine spill (Aznalco´ llar, SW Spain, April 1998) may affect fitness under natural conditions in a long-lived bird, the White Stork (Ciconia ciconia). Methodology: The reproductive performance of individually-banded storks that were or not developmentally exposed to the spill (i.e. hatched before or after the spill) was compared when these individuals were simultaneously breeding during the seven years after the spill occurred (1999–2005). Principal Findings: Female storks developmentally exposed to the spill experienced a premature breeding senescence compared with their non-developmentally exposed counterparts, doing so after departing from an unusually higher productivity in their early reproductive life (non-developmentally exposed females: 0.560.33SE fledglings/year at 3-yr old vs. 1.3860.31SE at 6–7 yr old; developmentally exposed females: 1.560.30SE fledglings/year at 3-yr old vs. 0.8660.25SE at 6– 7 yr old). Conclusions/Significance: Following life-history theory, we propose that costly sub-lethal effects reported in stork nestlings after low-level exposure to the spill-derived contaminants might play an important role in shaping this pattern of reproduction, with a clear potential impact on population dynamics. Overall, our study provides evidence that environmental disasters can have long-term, multigenerational consequences on wildlife, particularly when affecting developing individuals, and warns about the risk of widespread low-level contamination in realistic scenarios.Peer reviewe

Gene Expression Profiling of a Mouse Model of Pancreatic Islet Dysmorphogenesis

In the past decade, several transcription factors critical for pancreas organogenesis have been identified. Despite this success, many of the factors necessary for proper islet morphogenesis and function remain uncharacterized. Previous studies have shown that transgenic over-expression of the transcription factor Hnf6 specifically in the pancreatic endocrine cell lineage resulted in disruptions in islet morphogenesis, including dysfunctional endocrine cell sorting, increased individual islet size, increased number of peripheral endocrine cell types, and failure of islets to migrate away from the ductal epithelium. The mechanisms whereby maintained Hnf6 causes defects in islet morphogenesis have yet to be elucidated.We exploited the dysmorphic islets in Hnf6 transgenic animals as a tool to identify factors important for islet morphogenesis. Genome-wide microarray analysis was used to identify differences in the gene expression profiles of late gestation and early postnatal total pancreas tissue from wild type and Hnf6 transgenic animals. Here we report the identification of genes with an altered expression in Hnf6 transgenic animals and highlight factors with potential importance in islet morphogenesis. Importantly, gene products involved in cell adhesion, cell migration, ECM remodeling and proliferation were found to be altered in Hnf6 transgenic pancreata, revealing specific candidates that can now be analyzed directly for their role in these processes during islet development.This study provides a unique dataset that can act as a starting point for other investigators to explore the role of the identified genes in pancreatogenesis, islet morphogenesis and mature beta cell function