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At least 1,153 records · Page 64Linked to original sources
PubMed2002

Mechanism of action of Melaleuca alternifolia (tea tree) oil on Staphylococcus aureus determined by time-kill, lysis, leakage, and salt tolerance assays and electron microscopy.

The essential oil of Melaleuca alternifolia (tea tree) has broad-spectrum antimicrobial activity. The mechanisms of action of tea tree oil and three of its components, 1,8-cineole, terpinen-4-ol, and alpha-terpineol, against Staphylococcus aureus ATCC 9144 were investigated. Treatment with these agents at their MICs and two times their MICs, particularly treatment with terpinen-4-ol and alpha-terpineol, reduced the viability of S. aureus. None of the agents caused lysis, as determined by measurement of the optical density at 620 nm, although cells became disproportionately sensitive to subsequent autolysis. Loss of 260-nm-absorbing material occurred after treatment with concentrations equivalent to the MIC, particularly after treatment with 1,8-cineole and alpha-terpineol. S. aureus organisms treated with tea tree oil or its components at the MIC or two times the MIC showed a significant loss of tolerance to NaCl. When the agents were tested at one-half the MIC, only 1,8-cineole significantly reduced the tolerance of S. aureus to NaCl. Electron microscopy of terpinen-4-ol-treated cells showed the formation of mesosomes and the loss of cytoplasmic contents. The predisposition to lysis, the loss of 260-nm-absorbing material, the loss of tolerance to NaCl, and the altered morphology seen by electron microscopy all suggest that tea tree oil and its components compromise the cytoplasmic membrane.

Anti-Infective Agents, Local↗
PubMed1995

Prognostic trees to aid prognosis in patients with cutaneous malignant melanoma. Scottish Melanoma Group.

OBJECTIVES: To design user friendly guides to prognosis for patients who have had invasive primary cutaneous malignant melanomas surgically excised. DESIGN: Adaptation of the classification tree method was used to derive prognostic trees for four different subgroups of malignant melanoma patients in whom known and possible prognostic variables interacted in different ways. SETTING: Scotland. SUBJECTS: Statistical modelling for prognostic trees was based on 1978 patients whose primary malignant melanoma was first diagnosed in 1979-86 for whom five year follow up and all relevant clinical pathological data were available. The resultant model was validated with 300 patients first diagnosed in 1987 for whom the same information was available. MAIN OUTCOME MEASURES: Actual and predicted rate of survival after diagnosis of primary cutaneous malignant melanoma. RESULTS: The four subgroups of patients were men and women with ulcerated and non-ulcerated cutaneous primary melanomas. Validation of the model showed excellent agreement between actual status of patients in the relevant subgroups and their status as predicted by the model. CONCLUSIONS: The prognostic trees are simple to use and give more accurate prognosis for individual patients than is currently available from tumour thickness alone.

Decision Trees↗
PubMed2004

Nonlinear system modelling via optimal design of neural trees.

This paper introduces a flexible neural tree model. The model is computed as a flexible multi-layer feed-forward neural network. A hybrid learning/evolutionary approach to automatically optimize the neural tree model is also proposed. The approach includes a modified probabilistic incremental program evolution algorithm (MPIPE) to evolve and determine a optimal structure of the neural tree and a parameter learning algorithm to optimize the free parameters embedded in the neural tree. The performance and effectiveness of the proposed method are evaluated using function approximation, time series prediction and system identification problems and compared with the related methods.

Algorithms↗
PubMed1990

IgG4 antibodies in hay fever patients. Difference in IgG4 response to tree pollen and grass pollen allergens.

Total IgE and IgE and IgG4 antibodies to offending allergens were studied in 118 hay fever patients allergic to tree pollen and grass pollen allergens. No difference in the level of total IgE and IgE antibodies was found between these two groups while the IgG4 antibody level was significantly higher in tree pollen allergic patients. It is suggested that the IgG4 antibodies to tree pollen allergens can be stimulated by structurally related allergens of vegetable food and are probably involved in tree pollen-associated food hypersensitivity.

Adolescent↗
PubMedDate not supplied

ROC curves for classification trees.

A common problem in medical diagnosis is to combine information from several tests or patient characteristics into a decision rule to distinguish diseased from healthy patients. Among the statistical procedures proposed to solve this problem, recursive partitioning is appealing for the easily-used and intuitive nature of the rules it produces. The rules have the form of classification trees, in which each node of the tree represents a simple question about one of the predictor variables, and the branch taken depends on the answer. The authors consider the role of misclassification costs in developing classification trees. By varying the ratio of costs assigned to false negatives and false positives, a series of classification trees are generated, each optimal for some range of cost ratios, and each with a different sensitivity and specificity. The set of sensitivity-specificity combinations define a curve that can be used like an ROC curve.

Child, Preschool↗
PubMed1995

Extending the elements of tree-structured regression.

The usage of tree-structured or recursive partitioning methods has grown steadily in the decade since the appearance of the definitive monograph 'Classification and Regression Trees'. Accompanying this growth have been many methodologic and software extensions that have served to give the tree-structured approach even wider applicability. This overview highlights some of these developments, emphasizing the regression setting. An illustrative example describes how tree-structured regression, modified to handle right-censored, left-truncated survival data with time-dependent covariates, can be used to assess whether rates of progression from HIV to AIDS have changed over time.

Acquired Immunodeficiency Syndrome↗
PubMed2005

EvDTree: structure-dependent substitution profiles based on decision tree classification of 3D environments.

BACKGROUND: Structure-dependent substitution matrices increase the accuracy of sequence alignments when the 3D structure of one sequence is known, and are successful e.g. in fold recognition. We propose a new automated method, EvDTree, based on a decision tree algorithm, for automatic derivation of amino acid substitution probabilities from a set of sequence-structure alignments. The main advantage over other approaches is an unbiased automatic selection of the most informative structural descriptors and associated values or thresholds. This feature allows automatic derivation of structure-dependent substitution scores for any specific set of structures, without the need to empirically determine best descriptors and parameters. RESULTS: Decision trees for residue substitutions were constructed for each residue type from sequence-structure alignments extracted from the HOMSTRAD database. For each tree cluster, environment-dependent substitution profiles were derived. The resulting structure-dependent substitution scores were assessed using a criterion based on the mean ranking of observed substitution among all possible substitutions and in sequence-structure alignments. The automatically built EvDTree substitution scores provide significantly better results than conventional matrices and similar or slightly better results than other structure-dependent matrices. EvDTree has been applied to small disulfide-rich proteins as a test case to automatically derive specific substitutions scores providing better results than non-specific substitution scores. Analyses of the decision tree classifications provide useful information on the relative importance of different structural descriptors. CONCLUSIONS: We propose a fully automatic method for the classification of structural environments and inference of structure-dependent substitution profiles. We show that this approach is more accurate than existing methods for various applications. The easy adaptation of EvDTree to any specific data set opens the way for class-specific structure-dependent substitution scores which can be used in threading-based remote homology searches.

Alanine↗
PubMed2006

Mastectomy or breast conserving surgery? Factors affecting type of surgical treatment for breast cancer--a classification tree approach.

BACKGROUND: A critical choice facing breast cancer patients is which surgical treatment--mastectomy or breast conserving surgery (BCS)--is most appropriate. Several studies have investigated factors that impact the type of surgery chosen, identifying features such as place of residence, age at diagnosis, tumor size, socio-economic and racial/ethnic elements as relevant. Such assessment of "propensity" is important in understanding issues such as a reported under-utilisation of BCS among women for whom such treatment was not contraindicated. Using Western Australian (WA) data, we further examine the factors associated with the type of surgical treatment for breast cancer using a classification tree approach. This approach deals naturally with complicated interactions between factors, and so allows flexible and interpretable models for treatment choice to be built that add to the current understanding of this complex decision process. METHODS: Data was extracted from the WA Cancer Registry on women diagnosed with breast cancer in WA from 1990 to 2000. Subjects' treatment preferences were predicted from covariates using both classification trees and logistic regression. RESULTS: Tumor size was the primary determinant of patient choice, subjects with tumors smaller than 20 mm in diameter preferring BCS. For subjects with tumors greater than 20 mm in diameter factors such as patient age, nodal status, and tumor histology become relevant as predictors of patient choice. CONCLUSION: Classification trees perform as well as logistic regression for predicting patient choice, but are much easier to interpret for clinical use. The selected tree can inform clinicians' advice to patients.

Adult↗
PubMed2000

[A new decision tree method for statistical analysis of quantitative data obtained in toxicity studies on rodents].

Regarding the statistical analysis of the quantitative data obtained in control and dosage groups in toxicity studies, we tried to simplify the decision tree method. In a new decision tree presented in this article, one-way analysis of variance and Kruskal-Wallis nonparametric analysis of variance are excluded from the traditional decision tree: (1) Bartlett's test is used as a test for the equality of k variances: (2) Then, if the k sampled populations have equal variances (p > 0.05 by the Bartlett's test), Dunnett's multiple comparison test is performed: otherwise, Steel's test is used. This new method, which increases the power in some conditions, may serve as an alternative to the traditional decision tree method.

Analysis of Variance↗
PubMedDate not supplied

[Occurrence and biology of Rhodnius neglectus Lent, 1954 in palm trees of suburban areas of Belo Horizonte, Minas Gerais].

Eighty-one "macaubeiras" palm-trees (Acrocomia sclerocarpa) from the periphery of Belo Horizonte city were cut down and dissected between April 1979 and July 1980. 60.5% of the trees were positive for R. neglectus and 463 specimens of this insect were collected, providing a mean rate of 9,45 individuals for positive palm-trees. R. neglectus seems to present a single annual generation in this region, but evidence was obtained that two generations may occur. Its spawn period is related to the hot months of the year, when younger insects prevail over the adults. This observation suggests that higher population densities are related to better feeding conditions and to minor densities of specific predators such as Telenomus sp., ants, spiders, hemipters, scorpions and pseudo scorpionidae. The Trypanosoma cruzi infection index was 15,9%, suggesting that R. neglectus is a very important vector of silvatic infections in the region. Marsupials are the main vertebrate source of T. cruzi infection. R. neglectus is strongly associated with palm-trees in the area, and with the various species of birds that haunt them. So far, there is no evidence suggesting R. neglectus to be an important vector of human Chagas' disease in the region.

Animals↗
PubMed2006

Roots of pioneer trees in the lower sub-tropical area of Dinghushan, Guangdong, China.

Representative pioneer tree root systems in the subtropical area of South China were examined with regard to their structure, underground stratification and biomass distribution. Excavation of skeleton roots and observation of fine roots of seven species including the Euphorbiaceae, Theaceae, Melastomataceae, Lauraceae and Fagaceae families was carried out. The results showed that: (1) Pioneer tree roots in the first stage of natural succession were of two types, one characterized by taproot system with bulky plagiotropic branches; the other characterized by flat root system with several tabular roots. The late mesophilous tree roots were characterized by one obvious taproot and tactic braches roots up and down. Shrub species roots were characterized by heart fibrous root type featured both by horizontally and transversally growing branches. Root shapes varied in different dominant species at different stages of succession. (2) Roots of the different species varied in the external features-color, periderm and structure of freshly cut slash. (3) In a set of successional stages the biomass of tree roots increased linearly with the age of growth. During monsoon, the total root biomass amounted to 115.70 t/ha in the evergreen broad-leaved forest; 50.61 t/ha in needle and broad-leaved mixed forest dominated by coniferous forest; and 64.20 t/ha in broad-and needle-leaved mixed forest dominated by broad-leaved heliophytes, and are comparable to the underground biomass observed in similar tropical forests. This is the first report about roots characteristics of forest in the lower sub-tropical area of Dinghushan, Guangdong, China.

Biomass↗
PubMed2006

Evaluating the long-term metacommunity dynamics of tree hole mosquitoes.

Four different conceptual models of metacommunities have been proposed, termed "patch dynamics," "species sorting", "mass effect", and "neutral". These models simplify thinking about metacommunities and improve our understanding of the role of spatial dynamics both in structuring communities and in determining local and regional diversity. We tested whether mosquito communities inhabiting water-filled tree holes in southeastern Florida, U.S.A., displayed any of the characteristics and dynamics predicted by the four models. The densities of the five most common species in 3-8 tree holes were monitored every two weeks during 1978-2003. We tested relationships between habitat variables and species densities, spatial synchrony, the presence of life history trade-offs, and species turnover. Dynamics showed strong elements of species sorting, but with considerable turnover, as predicted by the patch dynamics model. Consistent with patch dynamics, there was substantial asynchrony in dynamics for different tree holes, substantial species turnover in space and time, and an occupancy/colonization trade-off. Substantial correlations of density and occupancy with tree hole volume were consistent with the species-sorting model, but unlike this model, species did not have permanent refuges. No evidence of mass effects was found, and correlations between habitat variables and dynamics were inconsistent with neutral models. Our results did not match a single model and therefore caution against overly simplifying metacommunity dynamics by using one dynamical characteristic to select a particular metacommunity perspective.

Animals↗
PubMedDate not supplied

Tree species for recovering nitrogen from dairy-farm effluent in New Zealand.

Land treatment of dairy-farm effluent is being widely adopted as an alternative to disposal into surface waters in New Zealand. This study investigated water balances and associated N leaching from short-rotation forest (SRF) species irrigated with dairy-farm effluent. Single trees were grown in lysimeters filled with Manawatu fine sandy loam (mixed mesic Dystric Eutrochrept). Dairy-farm effluent was applied during two irrigation periods at 21.5 mm wk(-1) with a total loading equivalent to 870 kg N ha(-1) occurring over 17 mo. Following tree harvest in April 1997, measurements continued until August 1997 to monitor tree reestablishment. Cumulative N leached did not differ between lysimeters in which evergreen Sydney blue gum (Eucalyptus saligna Sm.) and shining gum [Eucalyptus nitens (H. Deane & Maiden) Maiden] and deciduous kinu-yanagi (Salix kinuyanagi Kimura) were grown. Leachate N concentrations of all treatments were on average higher than the New Zealand drinking water standard of 11.3 mg N L(-1). The E. nitens and S. kinuyanagi treatments leached 33 and 35 kg N ha(-1) yr(-1) in 1996 following application of 236 kg N ha(-1) during the first irrigation season. Leaf area was strongly correlated to evapotranspiration, drainage volume, and nitrogen leached. The majority of leaching in the tree treatments occurred after harvest. Reducing the leaching in the regrowth phase may be achieved through timing harvest in the spring when growth rates are higher and leaching potential is lower. Based on N uptake rates observed in this study and average pond discharge, a plantation of 5.4 ha would be required for N recovery on a typical dairy farm in New Zealand.

Agriculture↗
PubMed1988

A decision tree for early differentiation between obstructive and non-obstructive jaundice.

We present a method for early differentiation between obstructive and non-obstructive jaundice. On the basis of 14 variables (clinical data and clinical chemical tests, all available within 48 h) a simple decision tree or flow chart has been constructed. The diagnostic yield was as follows: 857 of 982 consecutive jaundiced patients (87%) in a data base and 98 of 108 patients in an independent test sample (91%) were correctly classified. Decision trees for the differentiation between benign or malignant causes within the obstructive group and between acute or chronic causes within the non-obstructive group are also presented. The resulting four-way classification was correct for 77% of the patients in the data base and for 72% of the patients in the test sample. The decision trees are compared with previous methods founded on Bayes' rule and logistic discrimination. The decision trees enable a quick and reliable classification of jaundiced patients, thus providing a valid basis for rational planning of the further diagnostic study.

Cholestasis↗
PubMed1991

Prediction tree for severely head-injured patients.

Prediction tree techniques are employed in the analysis of data from 555 patients admitted to the Medical College of Virginia hospitals with severe head injuries. Twenty-three prognostic indicators are examined to predict the distribution of 12-month outcomes among the five Glasgow Outcome Scale categories. A tree diagram, illustrating the prognostic pattern, provides critical threshold levels that split the patients into subgroups with varying degrees of risk. It is a visually useful way to look at the prognosis of head-injured patients. In previous analyses addressing this prediction problem, the same set of prognostic factors (age, motor score, and pupillary response) was used for all patients. These approaches might be considered inflexible because more informative prediction may be achieved by somewhat different combinations of factors for different patients. Tree analysis reveals that the pattern of important prognostic factors differs among various patient subgroups, although the three previously mentioned factors are still of primary importance. For example, it is noted that information concerning intracerebral lesions is useful in predicting outcome for certain patients. The overall predictive accuracy of the tree technique for these data is 77.7%, which is somewhat higher than that obtained via standard prediction methods. The predictive accuracy is highest among patients who have a good recovery or die; it is lower for patients having intermediate outcomes.

Adult↗
PubMed1999

Immunophenotypic diagnosis of acute leukemia by using decision tree induction.

We describe a model for decision making for bone marrow immunophenotypic analysis of acute leukemia. In this study, we used decision tree induction as an information processing system for the analysis of flow cytometry immunophenotype results of bone marrow specimens obtained for the diagnosis of acute leukemia. By using decision tree analysis, we queried which antibodies and at what percentage cut-offs led to particular diagnoses. Flow cytometry results of up to 27 monoclonal antibodies from bone marrow specimens of 175 adult and pediatric cases were used: acute lymphoblastic leukemia (n = 80), myeloid leukemia (n = 44), mixed lineage (n = 16), and reactive marrow (n = 35). The percentage of positive cells was used as input data, and the diagnoses were used as output of the information processing system. Results of the decision tree showed an easy, accurate, and intuitive algorithm that can delineate a hierarchy of antibodies relevant to diagnosis. A correct discrimination of acute myeloid and lymphoid leukemia from benign bone marrow can be inferred by using the results of four to eight from a panel of up to 27 antibodies with an accuracy of 95%. Here, we describe a computer-aided model that uses decision tree induction applied to flow cytometry immunophenotype data. If generalizable, this technique may be an alternative approach to modeling complex information like that seen in hematopathology and may complement the immunologist's interpretation, along with cytochemistry and morphology results, in the diagnosis of acute leukemia.

Acute Disease↗
PubMed1999

The influence of class discretization to attribute hierarchy of decision trees.

Decision support systems that help physicians are becoming very important part of medical decision making. They are based on different models and the best of them are providing an explanation together with an accurate, reliable and quick response. One of the most viable among decision-making models is the concept of decision trees, already successfully used for many medical decision making purposes. Although effective and reliable, the traditional decision tree construction approach still contains several deficiencies. Therefore we decided to develop and compare several decision supporting models, each of them built with different discretization of attributes and decision classes. For the construction of decision trees we used MtDeciT, in our laboratory developed tool for building decision trees using the classical induction method. All solutions were evolved for determining the influence of basic properties of child and his/her parents to length of successful breastfeeding. A comparison between developed models and obtained results has shown that the way of discretization obviously plays a great role in the reliable and accurate real-world medical decision making.

Adult↗
PubMed2001

Methods of statistical analysis of quantitative data obtained by toxicological bioassays using rodents in Japan: historical transition of the decision tree.

Massive amounts of quantitative data are being obtained by toxicity tests with time. These data sometimes include the data with a different distribution pattern or with different numbers of animals in each group. The tree-type algorithm has long been used commonly to promptly analyze the difference between the control group and dosage groups. In Japan, the decision tree has been used since 1982 with several modifications of the initial procedure. Recently, the method has been revised to have a high power. The changes have been made in two directions; one is a sophisticated method and the other is a simplified method. In this paper, the historical transition of the decision tree is described and the future of the decision tree forecasted.

Animals↗