A decision support system to facilitate management of patients with acute gastrointestinal bleeding

Objective: To develop a model to predict the bleeding source and identify the cohort amongst patients with acute gastrointestinal bleeding (GIB) who require urgent intervention, including endoscopy. Patients with acute GIB, an unpredictable event, are most commonly evaluated and managed by non-gastroenterologists. Rapid and consistently reliable risk stratification of patients with acute GIB for urgent endoscopy may potentially improve outcomes amongst such patients by targeting scarce health-care resources to those who need it the most. Design and methods: Using ICD-9 codes for acute GIB, 189 patients with acute GIB and all. available data variables required to develop and test models were identified from a hospital medical records database. Data on 122 patients was utilized for development of the model and on 67 patients utilized to perform comparative analysis of the models. Clinical data such as presenting signs and symptoms, demographic data, presence of co-morbidities, laboratory data and corresponding endoscopic diagnosis and outcomes were collected. Clinical data and endoscopic diagnosis collected for each patient was utilized to retrospectively ascertain optimal management for each patient. Clinical presentations and corresponding treatment was utilized as training examples. Eight mathematical models including artificial neural network (ANN), support vector machine (SVM), k-nearest neighbor, linear discriminant analysis (LDA), shrunken centroid (SC), random forest (RF), logistic regression, and boosting were trained and tested. The performance of these models was compared using standard statistical analysis and ROC curves. Results: Overall the random forest model best predicted the source, need for resuscitation, and disposition with accuracies of approximately 80% or higher (accuracy for endoscopy was greater than 75%). The area under ROC curve for RF was greater than 0.85, indicating excellent performance by the random forest model Conclusion: While most mathematical models are effective as a decision support system for evaluation and management of patients with acute GIB, in our testing, the RF model consistently demonstrated the best performance. Amongst patients presenting with acute GIB, mathematical models may facilitate the identification of the source of GIB, need for intervention and allow optimization of care and healthcare resource allocation; these however require further validation. (c) 2007 Elsevier B.V. All rights reserved.

Genetic analysis of forest species Eugenia uniflora L. through of newly developed SSR markers

Nine microsatellite loci for genetic analysis of three populations of the tropical tree Eugenia uniflora L. (pitanga or Brazilian cherry) from fragments of semideciduous forest were developed. We used the technique of building a (GA)(n) and (CA)(n) microsatellite-enriched library by capture with streptavidin-coated magnetic beads. We assessed the polymorphism of seven microsatellites in 84 mature trees found in three areas (Ribeir (a) over tildeo Preto, Tambau and S (a) over tildeo Jose do Rio Pardo), highly impacted by the agricultural practices, in a large region among Pardo river and Mogi-Guacu river basins, in state of S (a) over tildeo Paulo, Brazil. All loci were polymorphic, and the number of alleles was high, ranging from 6 to 24, with a mean of 14.4. All stands showed the same high level of genetic diversity (mean H(E) = 0.83) and a low genetic differentiation (mean F(ST) = 0.031), indicating that genetic diversity was higher within rather than among populations. Seven of the nine loci were highly variable, and sufficiently informative for E. uniflora. It was concluded that these new SSR markers can be efficiently used for gene flow studies.

Ticks (Acari : ixodidae) infesting wild birds in an Atlantic forest area in the state of Sao Paulo, Brazil, with isolation of Rickettsia from the tick Amblyomma longirostre

During field work in Nazare Paulista, state of Sao Paulo, Brazil, we found 13 (56.5%) of 23 birds (mostly Passeriformes) to be infested by 28 larvae and I nymph of Amblyomma spp. Two larvae were reared to the adult stage, being taxonomically identified as Amblyomma parkeri Fonseca and Aragao, whereas five larvae and one nymph were identified as Amblyomma longirostre Koch. All six A. longirostre specimens were shown to be infected by rickettsia, as demonstrated by polymerase chain reaction (PCR) targeting two rickettsial genes (gltA and ompA) or isolation of rickettsia in cell culture from one of the ticks. This isolate was designated as strain AL, which was established in Vero cell culture and was molecularly characterized by DNA sequencing fragments of the rickettsial genes gltA, htrA, ompA, and ompB. Phylogenetic analyses inferred from ompA and ompB partial sequences showed a high degree of similarity of strain AL with Rickettsia sp. strain ARANHA, previously detected by PCR in A. longirostre ticks from Rondonia, northern Brazil. We conclude that strain AL is a new rickettsia genotype belonging to the same species of strain ARANHA, which are closely related to Candidatus `R. amblyomniii`. Further studies should elucidate if strains AL and ARANHA are different strains of Candidatus `R. amblyommii` or are a new species.

Survey of Ticks (Acari: Ixodidae) and Their Rickettsia in an Atlantic Rain Forest Reserve in the State of Sao Paulo, Brazil

The current study investigated the occurrence of ticks and their rickettsiae in the Serra do Mar State Park, which encompasses one of the largest Atlantic rain forest reserves of Brazil. From July 2008 to June 2009, a total of 2,439 ticks (2,196 free living and 243 collected on hosts) was collected, encompassing the following 13 species: Amblyomma aureolatum (Pallas), Amblyomma brasiliense Aragao, Amblyomma dubitatum Neumann, Amblyomma fuscum Neumann, Amblyomma incisum Neumann, Amblyomma longirostre (Koch), Amblyomma naponense (Packard), Amblyomma nodosum Neumann, Amblyomma ovale Koch, Haemaphysalis juxtakochi Cooley, Ixodes aragaoi Fonseca, Lodes loricatus Neumann, and Rhipicephalus sanguineus (Latreille). Ticks were submitted to polymerase chain reaction assays targeting portions of the rickettsial genes gltA and ompA. Polymerase chain reaction products were DNA sequenced and compared with corresponding sequences available in GenBank. Rickettsia bellii, a rickettsia of unknown pathogenicity, was detected in one A. aureolatum, one A. ovate, and three A. incisum specimens. At least 8.8% (3/34) of the free-living A. ovale ticks, 13.6% (8/59) of the A. ovale ticks collected from dogs, and 1.9% (1/54) of the R. sanguineus (Latreille) ticks were found to be infected by Rickettsia sp strain Atlantic rain forest, a novel strain that has been shown to cause an eschar-associated spotted fever in the state of Sao Paulo. Our results suggest that A. ovale is the vector of Rickettsia sp strain Atlantic rain forest in the state of Sao Paulo.

Ticks (Acari: Ixodidae) Infesting Birds in an Atlantic Rain Forest Region of Brazil

Brazil has the third richest bird diversity of the world; however, there are few data concerning ticks (Acari: Ixodidae) parazitizing birds. The aim of the study was to report tick infestations on wild birds from an Atlantic rain forest region of Brazil. During 2 yr, ticks were collected from birds and from the environment in 12 forest sites. A total of 1,725 birds were captured representing 80 species from 24 families. In total, 223 (13%) birds were found infested by immature stages of Amblyomma ticks: 1,800 larvae and 539 nymphs. The prevalence of ticks was higher among-birds from the families Thamnophilidae, Conopophagidae, and Momotidae. The most common tick parasitizing birds was Amblyomma nodosum Koch. Other tick species, Amblyomma coelebs Neumann, Amblyomma cajennense (F.), Amblyomma ovale Koch, Amblyomma longirostre (Koch), Amblyomma calcaratum Neumann, and Amblyomma naponense (Packard), were found sporadically. Among free-living ticks collected in the environment, A. cajennense was the most common, followed by A. coelebs, A. naponense, Amblyomma brasilense Aragao, and Hemaphysalis juxtakochi Cooley.

Integrating high and moderate spatial resolution image data to estimate forest age structure

The collection of spatial information to quantify changes to the state and condition of the environment is a fundamental component of conservation or sustainable utilization of tropical and subtropical forests, Age is an important structural attribute of old-growth forests influencing biological diversity in Australia eucalypt forests. Aerial photograph interpretation has traditionally been used for mapping the age and structure of forest stands. However this method is subjective and is not able to accurately capture fine to landscape scale variation necessary for ecological studies. Identification and mapping of fine to landscape scale vegetative structural attributes will allow the compilation of information associated with Montreal Process indicators lb and ld, which seek to determine linkages between age structure and the diversity and abundance of forest fauna populations. This project integrated measurements of structural attributes derived from a canopy-height elevation model with results from a geometrical-optical/spectral mixture analysis model to map forest age structure at a landscape scale. The availability of multiple-scale data allows the transfer of high-resolution attributes to landscape scale monitoring. Multispectral image data were obtained from a DMSV (Digital Multi-Spectral Video) sensor over St Mary's State Forest in Southeast Queensland, Australia. Local scene variance levels for different forest tapes calculated from the DMSV data were used to optimize the tree density and canopy size output in a geometric-optical model applied to a Landsat Thematic Mapper (TU) data set. Airborne laser scanner data obtained over the project area were used to calibrate a digital filter to extract tree heights from a digital elevation model that was derived from scanned colour stereopairs. The modelled estimates of tree height, crown size, and tree density were used to produce a decision-tree classification of forest successional stage at a landscape scale. The results obtained (72% accuracy), were limited in validation, but demonstrate potential for using the multi-scale methodology to provide spatial information for forestry policy objectives (ie., monitoring forest age structure).

Subtropical drosophilids in Australia can be characterized by adult distribution across vegetation type and by height above forest floor

Understanding the pattern in which adult drosophilids of different species are distributed across and within different vegetation types is necessary for accurate interpretation of their local ecology and diversity. Such studies have been conducted mainly in temperate regions, and there is no basis for extrapolating their conclusions to tropical areas. This study describes the vertical distribution (0-20 m) of drosophilids attracted to banana baits in five different vegetation types in subtropical eastern Australia including open woodland, and rain-forest types. The distribution of most of the 15 common species could be characterized three-dimensionally by vegetation type and height above forest floor. Only one species, Scaptodrosophila lativittata, was common in all vegetation types and it was a canopy species in rain forests and a ground-level species in open woodland. Vertical distribution of some species clearly matched that of their larval hosts, but it did not in others. For example, the fungivore Leucophenga scutellata was mostly trapped well above the forest floor, yet it breeds at ground level, suggesting behavioural mode can influence vertical distributions. We conclude that the vertical dimension, although still poorly understood in relation to drosophilid habitats, needs to be taken into account when conducting and interpreting studies aimed at understanding drosophilid populations and communities in the subtropics.