Building a home for the science of nursing education: developing the NLN web-based repository.
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Abstracting and Indexing↗
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Results for “Tree building”
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[Chronic cough in children: etiology and decision trees].
Recurrent or chronic cough can be the symptom of a worrying condition which must be diagnosed without delay (cystic fibrosis, asthma, bronchial foreign body, bronchiectasis). Investigation of recurrent or chronic cough is based on simple principles: careful history-taking concerning the characteristics of the cough, full clinical examination to look for any associated symptoms, and auxological assessment to detect any interruption in weight increase. Only when this initial evaluation has been carried out can complementary investigations be sought. Ordinary respiratory infections that are part of the building up of immunity are predominant in coughs of children aged under 6 years and are aggravated by deleterious factors such as passive exposure to tobacco, early introduction to communal life, and urban pollution. We describe the most frequent causes of cough and their frequency according to the age of the child.
Age Factors↗
Vasculogenesis in the early quail blastodisc as studied with a monoclonal antibody recognizing endothelial cells.
QH1, a monoclonal antibody that recognizes quail endothelial and haemopoietic cells, was applied to quail blastodiscs in toto, in order to analyse by immunofluorescence the emergence of the vascular tree. The first endothelial cells were detected in the area opaca at the headfold stage and in the area pellucida at the 1-somite stage. Single cells then interconnected progressively, especially in the anterior intestinal portal and along the somites building up the linings of the heart and dorsal aortas. This study demonstrates that endothelial cells differentiate as single entities 4 h earlier in development than hitherto detected and that the vascular network forms secondarily. The horseshoe shape of the extraembryonic area vasculosa is also a secondary acquisition. A nonvascularized area persists until later (at least the 14-somite stage) in the region of the regressing primitive streak.
Animals↗
[Feasibility to introduce rare tree species Pinus sibirica into China].
Pinus sibirica growing mainly in Siberia of Russia is distributed over the Euro-Asia Taiga forest belt. There are many high-quality populations due to a great deal of variations. This kind of tree has an advantage of standing up to frigid environment, and can spread out in such places that have cold weather and high altitude. In China, boreal forest is a wide-spreaded type of forest that has the largest area and high volume. For this reason, it is feasible to introduce Pinus sibirica into the region that the condition is suitable. Introducing this kind of tree is a strategic project that can improve the structure and quality of our boreal forest. Introducing it can not only meet the demands of improved variety in short time, but also do the experiment of producing edible seeds and build up the developing center of nut, which can be a way of getting rid of poverty of forest region in heavy frigid area where is regarded as infertile area for farming formerly.
China↗
MyESL: A Software for Evolutionary Sparse Learning in Molecular Phylogenetics and Genomics.
Evolutionary sparse learning uses supervised machine learning to build evolutionary models where genomic sites loci are parameters. It uses the Least Absolute Shrinkage and Selection Operator with bi-level sparsity to connect a specific phylogenetic hypothesis with sequence variation across genomic loci. The MyESL software addresses the need for open-source tools to perform evolutionary sparse learning analyses, offering features to preprocess input phylogenomic alignments, post-process output models to generate molecular evolutionary metrics, and make Least Absolute Shrinkage and Selection Operator regression adaptable and efficient for phylogenetic trees and alignments. The core of MyESL, which constructs models with logistic regressions using bi-level sparsity, is written in C++. Its input data preprocessing and result post-processing tools are developed in Python. Compared to other tools, MyESL is more computationally efficient and provides evolution-friendly inputs and outputs. These features have already enabled the use of MyESL in two phylogenomic applications, one to identify outlier sequences and fragile clades in inferred phylogenies and another to build genetic models of convergent traits. In addition to the use in a Python environment, MyESL is available as a standalone executable compatible across multiple platforms, which can be directly integrated into scripts and third-party software. The source code, executable, and documentation for MyESL are openly accessible at https://github.com/kumarlabgit/MyESL.
Phylogeny↗
GeneSeer: a sage for gene names and genomic resources.
BACKGROUND: Independent identification of genes in different organisms and assays has led to a multitude of names for each gene. This balkanization makes it difficult to use gene names to locate genomic resources, homologs in other species and relevant publications. METHODS: We solve the naming problem by collecting data from a variety of sources and building a name-translation database. We have also built a table of homologs across several model organisms: H. sapiens, M. musculus, R. norvegicus, D. melanogaster, C. elegans, S. cerevisiae, S. pombe and A. thaliana. This allows GeneSeer to draw phylogenetic trees and identify the closest homologs. This, in turn, allows the use of names from one species to identify homologous genes in another species. A website http://geneseer.cshl.org/ is connected to the database to allow user-friendly access to our tools and external genomic resources using familiar gene names. CONCLUSION: GeneSeer allows access to gene information through common names and can map sequences to names. GeneSeer also allows identification of homologs and paralogs for a given gene. A variety of genomic data such as sequences, SNPs, splice variants, expression patterns and others can be accessed through the GeneSeer interface. It is freely available over the web http://geneseer.cshl.org/ and can be incorporated in other tools through an http-based software interface described on the website. It is currently used as the search engine in the RNAi codex resource, which is a portal for short hairpin RNA (shRNA) gene-silencing constructs.
Alternative Splicing↗
Predicting host tropism in influenza a viruses: insights from multi-segment nucleotide signatures.
BACKGROUND: Influenza A virus (IAV) poses a significant public health threat due to its cross-species transmission and complex host adaptation mechanisms. This study integrated whole-genome data from avian, human, swine, and bovine IAV strains, using machine learning to predict viral host tropism based on nucleotide site features and to identify key sites driving host adaptation along with their synergistic effects. METHODS: A total of 64,000 IAV sequences from avian, human, swine, and bovine hosts were analyzed to build host-prediction models. A four-class classification framework (avian, human, swine, bovine) was constructed using nucleotide site features from all eight genomic segments (PB2, PB1, PA, HA, NP, NA, MP, NS). Eight machine learning algorithms (logistic regression, decision tree, random forest, SVM, KNN, gradient boosting, XGBoost, LightGBM) were benchmarked via 10-fold stratified cross-validation. Model performance was evaluated using accuracy, precision, recall, F1-score, AUPRC, and AUC. SHAP (SHapley Additive exPlanations) analysis prioritized critical nucleotide sites, while bivariate association tests identified synergistic/antagonistic interactions between sites. Nucleotide composition profiles were compared across host groups using hierarchical clustering and heatmap visualization. RESULTS: The XGBoost algorithm demonstrated the best and most stable performance, achieving an AUC value of over 0.95 in distinguishing human-derived sequences from non-human ones. SHAP analysis identified the top 20 critical nucleotide sites for each gene segment, such as sites 46 and 698 in the NS segment. Nucleotide composition analysis revealed high similarity between human and swine sequences in the HA and PB2 segments, and between avian and bovine sequences. The HA segment was particularly challenging in differentiating human from swine strains. Bivariate site association analysis uncovered significant synergistic or antagonistic effects between key sites within gene segments, forming complex networks. For instance, in the NS segment, a positive prediction contribution was observed when sites 371, 698, and 419 were all G. CONCLUSIONS: This study advances our mechanistic understanding of IAV host adaptation, identifies molecular determinants for zoonotic risk stratification, and establishes a scalable machine learning framework for predicting viral host tropism through nucleotide signature analysis, thereby enhancing surveillance strategies and informing preventive measures against emerging viral threats.
Influenza A virus↗
Web access to data in a mobile ECG monitoring system.
Cardiovascular diseases and, in particular, diseases related to arrhythmias are a problem that affects a significant percentage of the population, being one of the major causes of death in Europe. New advances in the fields of PDAs, mobile phones, wireless communications and vital parameter sensors have permitted the development of revolutionary medical monitoring systems, which strikingly improve the lifestyle of patients. However, not all those monitoring systems provide patients with real assistance - anywhere and at any time. We have developed a system that goes a step further than the previous approaches, being designed to capture, record and, as a distinctive feature, locally analyze the ECG signals in a PDA carried by the patient. In that sense, the system has a decision support module based on decision tree methods that can detect, with high precision, any arrhythmias that the user may be suffering. Alarms can then be activated in time to alert a medical center in order to provide the proper medical assistance. One of our aims when building the system has been to optimize limited and expensive resources like PDA memory size and wireless communication costs. Moreover, accessibility is also an important feature of the system that has been achieved by the development of web services to query the data computed in the PDA. In this way, authorized personnel (physicians and relatives) can easily obtain access to that data.
Computer Systems↗
Risk factors for heatstroke. A case-control study.
To identify risk factors associated with heatstroke, a case-control study in St Louis and Kansas City, Mo, was conducted during July and August 1980. Questionnaire data were gathered for 156 persons with heatstroke (severe heat illness with documented hyperthermia) and 462 control subjects matched by age, sex, and neighborhood of residence. A stepwise linear logistic regression procedure was used to identify factors significantly associated with heatstroke. Alcoholism, living on the higher floors of multistory buildings, and using major tranquilizers (phenothiazines, butyrophenones, or thioxanthenes) were factors associated with increased risk. Factors associated with decreased risk were using home air conditioning, spending more time in air-conditioned places, and living in a residence well shaded by trees and shrubs. Being able to care for oneself, characteristically undertaking vigorous physical activity, but reducing such activity during the heat, and taking extra liquid were also associated with decreased risk. Our findings also suggest effective preventive measures. During a heat wave, the greatest attention should be directed toward high-risk groups, and relief efforts should include measures shown to be associated with reduced risk.
Air Conditioning↗
Knowledge discovery in GenBank.
We describe various methods designed to discover knowledge in the GenBank nucleic acid sequence database. Using a grammatical model of gene structure, we create a parse tree of a gene using features listed in the FEATURE TABLE. The parse tree infers features that are not explicitly listed, but which follow from the listed features. This method discovers 30% more introns and 40% more exons when applied to a globin gene subset of GenBank. Parse tree construction also entails resolving ambiguity and inconsistency within a FEATURE TABLE. We transform the parse tree into an augmented FEATURE TABLE that represents inferred gene structure explicitly and unambiguously, thereby greatly improving the utility of the FEATURE TABLE to researchers. We then describe various analogical reasoning techniques designed to exploit the homologous nature of genes. We build a classification hierarchy that reflects the evolutionary relationship between genes. Descriptive grammars of gene classes are then induced from the instance grammars of genes. Case based reasoning techniques use these abstract gene class descriptions to predict the presence and location of regulatory features not listed in the FEATURE TABLE. A cross-validation test shows a success rate of 87% on a globin gene subset of GenBank.
Algorithms↗
Vegetation of the selected forest stands and land use in the Carpathian Mountains.
Within the framework of the project "Effects of forest health on biodiversity with emphasis on air pollution in the Carpathian Mountains" 26 permanent study sites were established in the vicinity of the ozone monitoring sites. The study sites were located on the NW-SE transect through the Western (12 sites), Eastern (11 sites) and Southern (3 sites) Carpathians in forest ecosystems typical of each area. Some of the forest monitoring sites were located in national parks, biosphere reserves and areas of protected landscape. Each permanent site of 0.7 ha area consisted of 5 small 500m(2) circular plots, arranged in the form of a cross, i.e. four placed on the cardinal points (N, E, S, W) and one in the center. Phytosociological records were done twice during the 1998 growing season using the Braun-Blanquet's method. The study sites represented various types of forest: Picea abies stands (8), beech (Fagus sylvatica) stands (10), fir (Abies alba) stands (2) and mixed beech-fir, spruce-fir and beech-spruce stands (6). Age of most stands was 80-100 years. Degree of crown damage varied greatly between sites, a percentage of damaged trees decrease in Carpathians from West to East. It corresponds well with the O(3) level in these areas. Typical damage by O(3) in herb layer species in several Carpathian sites were found. Land-use map for the entire Carpathian Mountains and two detailed land use maps for Tatras (Western Carpathians) and Retezat (Southern Carpathians) are presented. A little more than half of the Carpathian territory is forested. The most densely forested are Eastern Carpathians, while the most sparsely Western Carpathians. Arable lands occupy 22.6% of the Carpathians, pastures and meadows 6.2%, water bodies 1.9%, and build up areas several percent. In the highest elevation of the Carpathians alpine meadows (11.3%) and rocks (3.5%) are distributed.
Agriculture↗
Lignin structure in a mutant pine deficient in cinnamyl alcohol dehydrogenase.
Cinnamyl alcohol dehydrogenase (CAD) activity is deficient in loblolly pine (Pinus taeda L.) harboring a mutated allele of the cad gene (cad-n1). We compared lignin structure of CAD-deficient and wild-type pines, both types segregating within full-sib families obtained by controlled crosses. The type and frequency of lignin building units and distribution of interunit bonds were determined from the GC-MS analysis of thioacidolysis monomers and dimers. While the lignin content was only slightly reduced, the lignin structure was dramatically modified by the mutation in both mature and juvenile trees. Lignins from CAD-deficient pine displayed unusually high levels of coniferaldehyde and dihydroconiferyl alcohol. In addition, biphenyl and biphenyl ether bonds were in large excess in these abnormal lignins. These results suggest that the CAD-deficient pines efficiently compensate for the shortage in normal lignin precursors by utilizing nontraditional wall phenolics to construct unusual lignins particularly enriched in resistant interunit bonds.
Alcohol Oxidoreductases↗
Tropical forests and the global carbon cycle: impacts of atmospheric carbon dioxide, climate change and rate of deforestation.
The remaining carbon stocks in wet tropical forests are currently at risk because of anthropogenic deforestation, but also because of the possibility of release driven by climate change. To identify the relative roles of CO2 increase, changing temperature and rainfall, and deforestation in the future, and the magnitude of their impact on atmospheric CO2 concentrations, we have applied a dynamic global vegetation model, using multiple scenarios of tropical deforestation (extrapolated from two estimates of current rates) and multiple scenarios of changing climate (derived from four independent offline general circulation model simulations). Results show that deforestation will probably produce large losses of carbon, despite the uncertainty about the deforestation rates. Some climate models produce additional large fluxes due to increased drought stress caused by rising temperature and decreasing rainfall. One climate model, however, produces an additional carbon sink. Taken together, our estimates of additional carbon emissions during the twenty-first century, for all climate and deforestation scenarios, range from 101 to 367 Gt C, resulting in CO2 concentration increases above background values between 29 and 129 p.p.m. An evaluation of the method indicates that better estimates of tropical carbon sources and sinks require improved assessments of current and future deforestation, and more consistent precipitation scenarios from climate models. Notwithstanding the uncertainties, continued tropical deforestation will most certainly play a very large role in the build-up of future greenhouse gas concentrations.
Atmosphere↗
Functional genomics and cell wall biosynthesis in loblolly pine.
Loblolly pine (Pinus taeda L.) is the most widely planted tree species in the USA and an important tree in commercial forestry world-wide. The large genome size and long generation time of this species present obstacles to both breeding and molecular genetic analysis. Gene discovery by partial DNA sequence determination of cDNA clones is an effective means of building a knowledge base for molecular investigations of mechanisms governing aspects of pine growth and development, including the commercially relevant properties of secondary cell walls in wood. Microarray experiments utilizing pine cDNA clones can be used to gain additional information about the potential roles of expressed genes in wood formation. Different methods have been used to analyze data from first-generation pine microarrays, with differing degrees of success. Disparities in predictions of differential gene expression between cDNA sequencing experiments and microarray experiments arise from differences in the nature of the respective analyses, but both approaches provide lists of candidate genes which should be further investigated for potential roles in cell wall formation in differentiating pine secondary xylem. Some of these genes seem to be specific to pine, while others also occur in model plants such as Arabidopsis, where they could be more efficiently investigated.
Arabidopsis↗
A knowledge-based approach to the deflocculation problem: integrating on-line, off-line, and heuristic information.
A knowledge-based approach for the supervision of the deflocculation problem in activated sludge processes was considered and successfully applied to a full-scale plant. To do that, a methodology that integrates on-line, off-line and heuristic information has been proposed. This methodology consists of three steps: (i). development of a decision tree (which involves knowledge acquisition and representation); (ii). implementation into a rule-based system; and (iii). validation. The set of symptoms most useful in diagnosing the deflocculation problem has been identified, the different branches to diagnose pin-point floc and dispersed growth have been built (using generic and specific knowledge), and all this knowledge has been codified into an object-oriented shell. The results obtained in the application of this knowledge-based approach to the Granollers WWTP (which treats about 130000 inhabitants-equivalents) showed that the system was able to identify correctly the problem with reasonable accuracy. Our positive experience building this system suggests that this approach is a practical and valuable element to include in an intelligent supervisory system combining numerical and reasoning techniques.
Artificial Intelligence↗
Use of influence diagrams to structure medical decisions.
Influence diagrams are compact representations of decision problems that are mathematically equivalent to decision trees. The authors present five important principles for structuring a decision as an influence diagram: 1) start at the value node and work back to the decision nodes; 2) draw the arcs in the direction that makes the probabilities easiest to assess; 3) use informational arcs to specify which events will have been observed at the time each decision is made; 4) ensure that missing arcs reflect intentional assertions about conditional independence and the timing of observations; and 5) ensure that there are no cycles in the influence diagram. They then build an influence diagram for the problem of staging non-small-cell lung cancer as an illustration. Influence diagrams offer several strengths for structuring medical decisions. They represent graphically and compactly the probabilistic relationships between parameters in the model. Influence diagrams also allow the model to be structured in a fashion that eases the necessary probability assessments, regardless of whether the assessments are based on available evidence or on expert judgment. Influence diagrams provide an important complement to decision trees, especially for representing probabilistic relationships among variables in a decision model.
Carcinoma, Non-Small-Cell Lung↗
Building phenotypic character matrices for phylogenetic inference: exploration of 35 years of practice.
Recent methodological development in phylogenetic inference has focused predominantly on molecular data. However, renewed interest in other data types, particularly morphological data, has followed from the increased recognition of the power of total evidence and tip-dating approaches, including fossil data, for inference of time-scaled trees and rates of evolution. However, attention has largely focused on the improvement of models of morphological evolution and other analytical tools with much less discussion about data acquisition itself. Here we review past and current practice for describing and collecting morphological data for phylogenetic inference. We present a systematic review of 164 phylogenetic analyses conducted over the last 35 years and focused on a diverse group of extinct arthropods: trilobites. Trends in increasing matrix size, data type, and coding strategy are evident. Where present, polymorphic characters have been predominantly derived from discretized continuous characters, although increasingly practitioners are utilizing alternative approaches for the treatment of quantitative characters. Not surprisingly, traditional indices that describe character consistency are highly correlated with matrix size but show surprising variation at different taxonomic scales. More recent attempts to describe data quality using information theory imply that characters can have high information content even if data are missing for many tips, providing support against the exclusion of characters because of missing data. In consideration of this, as well as advances in the study of developmental biology and variational complexity, we identify several avenues for increasing the quality and quantity of morphological data going forward.
Phylogeny↗
Absence of systemic immunologic changes during dose build-up phase and early maintenance period in effective specific sublingual immunotherapy in children.
BACKGROUND: Sublingual immunotherapy (SLIT) has been reported to be a safe treatment for inhalant allergies in children. Yet the immunologic mechanisms resulting in clinical improvement are poorly understood. OBJECTIVE: To identify early systemic immunologic changes during the first 8 weeks of clinically effective SLIT to grass pollen, tree pollen or house dust mite in paediatric patients with allergic rhinoconjunctivitis and/or asthma. METHODS: Peripheral blood mononuclear cells and plasma samples of 13 children with reduced symptoms after 1 year of SLIT were obtained before therapy and at 2 and 8 weeks after the initiation of SLIT. Allergen-specific lymphocyte proliferation assays were performed, and allergen-induced cytokine production (IL-2, IL-4, IL-10, IFN-gamma, and TGF-beta(1)) was measured by ELISA and flow cytometry. Allergen-specific IgE, IgG1, IgG4, and IgA levels in plasma samples were determined in ELISA. RESULTS: During the first 8 weeks of successful SLIT, allergen-specific lymphoproliferation (n=13) as well as levels of allergen-specific intracellular (n=8) and secreted cytokines (n=9) did not change significantly. In addition, no alterations in levels of allergen-specific Igs (n=7) were observed. CONCLUSION: We could not find any early systemic immunologic changes during the first 8 weeks of clinically effective SLIT to inhalant allergens in paediatric patients with allergic rhinoconjunctivitis and/or asthma.
Administration, Sublingual↗