ERRATUM: New Body Mass Estimates for Omomys carteri,a Middle Eocene Primate From North America. Am J Phys Anthropol 109:41–52.

Payseur BA, Covert HA, Vinyard CJ, Dagosto M. 1999. New Body Mass Estimates for Omomys carteri, a Middle Eocene Primate From North America. Am J Phys Anthropol 109:41–52. This article included an incomplete Table 2. The final two columns, showing “Intercept” and “SEE” data were omitted. The complete Table 2, with these two columns included, is provided below.     

High definition bronchoscopy: a randomized exploratory study of diagnostic value compared to standard white light bronchoscopy and autofluorescence bronchoscopy

Background

Videobronchoscopy is an essential diagnostic procedure for evaluation of the central airways and pivotal for the diagnosis and staging of lung cancer. Technological improvements have resulted in high definition (HD) images with advanced real time image enhancement techniques (i-scan).

Objectives

In this study we aimed to explore the sensitivity of HD+ i-scan bronchoscopy for detection of epithelial changes like vascular abnormalities and suspicious preinvasive lesions, and tumors.

Methods

In patients scheduled for a therapeutic or diagnostic procedure under general anesthesia videos of the bronchial tree were made using 5 videobronchoscopy modes in random order: normal white light videobronchoscopy (WLB), HD-bronchoscopy (HD), HD bronchoscopy with surface enhancement technique (i-scan1), HD with surface- and tone enhancement technique (i-scan2) and dual mode autofluorescence videobronchoscopy (AFB). The videos were scored in random order by two independent and blinded expert bronchoscopists.

Results

In 29 patients all videos were available for analysis. Vascular abnormalities were scored most frequently in HD + i-scan2 bronchoscopy (1.33 ± 0.29 abnormal or suspicious sites per patient) as compared to 0.12 ± 0.05 site for AFB (P = 0.003). Sites suspicious for preinvasive lesions were most frequently reported using AFB (0.74 ± 0.12 sites per patient) as compared to 0.17 ± 0.06 for both WLB and HD bronchoscopy (P = 0.003). Tumors were detected equally by all modalities. The preferred modality was HD bronchoscopy with i-scan (tone- plus surface and surface enhancement in respectively 38% and 35% of cases P = 0.006).

Conclusions

This study shows that high definition bronchoscopy with image enhancement technique may result in better detection of subtle vascular abnormalities in the airways. Since these abnormalities may be related to preneoplastic lesions and tumors this is of clinical relevance. Further investigations using this technique relating imaging to histology are warranted.     

The BioLexicon: a large-scale terminological resource for biomedical text mining

Background

Due to the rapidly expanding body of biomedical literature, biologists require increasingly sophisticated and efficient systems to help them to search for relevant information. Such systems should account for the multiple written variants used to represent biomedical concepts, and allow the user to search for specific pieces of knowledge (or events) involving these concepts, e.g., protein-protein interactions. Such functionality requires access to detailed information about words used in the biomedical literature. Existing databases and ontologies often have a specific focus and are oriented towards human use. Consequently, biological knowledge is dispersed amongst many resources, which often do not attempt to account for the large and frequently changing set of variants that appear in the literature. Additionally, such resources typically do not provide information about how terms relate to each other in texts to describe events.

Results

This article provides an overview of the design, construction and evaluation of a large-scale lexical and conceptual resource for the biomedical domain, the BioLexicon. The resource can be exploited by text mining tools at several levels, e.g., part-of-speech tagging, recognition of biomedical entities, and the extraction of events in which they are involved. As such, the BioLexicon must account for real usage of words in biomedical texts. In particular, the BioLexicon gathers together different types of terms from several existing data resources into a single, unified repository, and augments them with new term variants automatically extracted from biomedical literature. Extraction of events is facilitated through the inclusion of biologically pertinent verbs (around which events are typically organized) together with information about typical patterns of grammatical and semantic behaviour, which are acquired from domain-specific texts. In order to foster interoperability, the BioLexicon is modelled using the Lexical Markup Framework, an ISO standard.

Conclusions

The BioLexicon contains over 2.2 M lexical entries and over 1.8 M terminological variants, as well as over 3.3 M semantic relations, including over 2 M synonymy relations. Its exploitation can benefit both application developers and users. We demonstrate some such benefits by describing integration of the resource into a number of different tools, and evaluating improvements in performance that this can bring.     

Application of Artificial Intelligence/Machine Vision & Learning for the Development of a Live Single-cell Phenotypic Biomarker Test to Predict Prostate Cancer Tumor Aggressiveness

To assess the usefulness and applications of machine vision (MV) and machine learning (ML) techniques that have been used to develop a single cell-based phenotypic (live and fixed biomarkers) platform that correlates with tumor biological aggressiveness and risk stratification, 100 fresh prostate samples were acquired, and areas of prostate cancer were determined by post-surgery pathology reports logged by an independent pathologist. The prostate samples were dissociated into single-cell suspensions in the presence of an extracellular matrix formulation. These samples were analyzed via live-cell microscopy. Dynamic and fixed phenotypic biomarkers per cell were quantified using objective MV software and ML algorithms. The predictive nature of the ML algorithms was developed in two stages. First, random forest (RF) algorithms were developed using 70% of the samples. The developed algorithms were then tested for their predictive performance using the blinded test dataset that contained 30% of the samples in the second stage. Based on the ROC (receiver operating characteristic) curve analysis, thresholds were set to maximize both sensitivity and specificity. We determined the sensitivity and specificity of the assay by comparing the algorithm-generated predictions with adverse pathologic features in the radical prostatectomy (RP) specimens. Using MV and ML algorithms, the biomarkers predictive of adverse pathology at RP were ranked and a prostate cancer patient risk stratification test was developed that distinguishes patients based on surgical adverse pathology features. The ability to identify and track large numbers of individual cells over the length of the microscopy experimental monitoring cycles, in an automated way, created a large biomarker dataset of primary biomarkers. This biomarker dataset was then interrogated with ML algorithms used to correlate with post-surgical adverse pathology findings. Algorithms were generated that predicted adverse pathology with >0.85 sensitivity and specificity and an AUC (area under the curve) of >0.85. Phenotypic biomarkers provide cellular and molecular details that are informative for predicting post-surgical adverse pathologies when considering tumor biopsy samples. Artificial intelligence ML-based approaches for cancer risk stratification are emerging as important and powerful tools to compliment current measures of risk stratification. These techniques have capabilities to address tumor heterogeneity and the molecular complexity of prostate cancer. Specifically, the phenotypic test is a novel example of leveraging biomarkers and advances in MV and ML for developing a powerful prognostic and risk-stratification tool for prostate cancer patients.     

Quirks of dye nomenclature. 3. Trypan blue

Trypan blue is colorant from the 19^th century that has an association with Africa as a chemotherapeutic agent against protozoan (Trypanosomal) infections, which cause sleeping sickness. The dye still is used for staining biopsies, living cells and organisms, and it also has been used as a colorant for textiles.     

Prediction and course of symptoms and lung function around an exacerbation in chronic obstructive pulmonary disease

Background

Frequent exacerbations induce a high burden to Chronic Obstructive Pulmonary Disease (COPD). We investigated the course of exacerbations in the published COSMIC study that investigated the effects of 1-year withdrawal of fluticasone after a 3-month run-in treatment period with salmeterol/fluticasone in patients with COPD.

Methods

In 373 patients, we evaluated diary cards for symptoms, Peak Expiratory Flow (PEF), and salbutamol use and assessed their course during exacerbations.

Results

There were 492 exacerbations in 224 patients. The level of symptoms of cough, sputum, dyspnea and nocturnal awakening steadily increased from 2 weeks prior to exacerbation, with a sharp rise during the last week. Symptoms of cough, sputum, and dyspnea reverted to baseline values at different rates (after 4, 4, and 7 weeks respectively), whereas symptoms of nocturnal awakening were still increased after eight weeks. The course of symptoms was similar around a first and second exacerbation. Increases in symptoms and salbutamol use and decreases in PEF were associated with a higher risk to develop an exacerbation, but with moderate predictive values, the areas under the receiver operating curves ranging from 0.63 to 0.70.

Conclusions

Exacerbations of COPD are associated with increased symptoms that persist for weeks and the course is very similar between a first and second exacerbation. COPD exacerbations are preceded by increased symptoms and salbutamol use and lower PEF, yet predictive values are too low to warrant daily use in clinical practice.     

Mechanical ventilation with high tidal volumes attenuates myocardial dysfunction by decreasing cardiac edema in a rat model of LPS-induced peritonitis

Background

Injurious mechanical ventilation (MV) may augment organ injury remote from the lungs. During sepsis, myocardial dysfunction is common and increased endothelial activation and permeability can cause myocardial edema, which may, among other factors, hamper myocardial function. We investigated the effects of MV with injuriously high tidal volumes on the myocardium in an animal model of sepsis.

Methods

Normal rats and intraperitoneal (i.p.) lipopolysaccharide (LPS)-treated rats were ventilated with low (6 ml/kg) and high (19 ml/kg) tidal volumes (Vt) under general anesthesia. Non-ventilated animals served as controls. Mean arterial pressure (MAP), central venous pressure (CVP), cardiac output (CO) and pulmonary plateau pressure (P_plat) were measured. Ex vivo myocardial function was measured in isolated Langendorff-perfused hearts. Cardiac expression of endothelial vascular cell adhesion molecule (VCAM)-1 and edema were measured to evaluate endothelial inflammation and leakage.

Results

MAP decreased after LPS-treatment and Vt-dependently, both independent of each other and with interaction. MV Vt-dependently increased CVP and Pplat and decreased CO. LPS-induced peritonitis decreased myocardial function ex vivo but MV attenuated systolic dysfunction Vt-dependently. Cardiac endothelial VCAM-1 expression was increased by LPS treatment independent of MV. Cardiac edema was lowered Vt-dependently by MV, particularly after LPS, and correlated inversely with systolic myocardial function parameters ex vivo.

Conclusion

MV attenuated LPS-induced systolic myocardial dysfunction in a Vt-dependent manner. This was associated with a reduction in cardiac edema following a lower transmural coronary venous outflow pressure during LPS-induced coronary inflammation.     

A covariotide model explains apparent phylogenetic structure of oxygenic photosynthetic lineages

The aims of the work were (1) to develop statistical tests to identify whether substitution takes place under a covariotide model in sequences used for phylogenetic inference and (2) to determine the influence of covariotide substitution on phylogenetic trees inferred for photosynthetic and other organisms. (Covariotide and covarion models are ones in which sites that are variable in some parts of the underlying tree are invariable in others and vice versa.) Two tests were developed. The first was a contingency test, and the second was an inequality test comparing the expected number of variable sites in two groups with the observed number. Application of these tests to 16S rDNA and tufA sequences from a range of nonphotosynthetic prokaryotes and oxygenic photosynthetic prokaryotes and eukaryotes suggests the occurrence of a covariotide mechanism. The degree of support for partitioning of taxa in reconstructed trees involving these organisms was determined in the presence or absence of sites showing particular substitution patterns. This analysis showed that the support for splits between (1) photosynthetic eukaryotes and prokaryotes and (2) photosynthetic and nonphotosynthetic organisms could be accounted for by patterns arising from covariotide substitution. We show that the additional problem of compositional bias in sequence data needs to be considered in the context of patterns of covariotide/covarion substitution. We argue that while covariotide or covarion substitution may give rise to phylogenetically informative patterns in sequence data, this may not always be so.      

Using ontologies to describe mouse phenotypes

The mouse is an important model of human genetic disease. Describing phenotypes of mutant mice in a standard, structured manner that will facilitate data mining is a major challenge for bioinformatics. Here we describe a novel, compositional approach to this problem which combines core ontologies from a variety of sources. This produces a framework with greater flexibility, power and economy than previous approaches. We discuss some of the issues this approach raises.