115 resultados para categorical and mix datasets


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This paper presents and discusses further aspects of the subjectivist interpretation of probability (also known as the 'personalist' view of probabilities) as initiated in earlier forensic and legal literature. It shows that operational devices to elicit subjective probabilities - in particular the so-called scoring rules - provide additional arguments in support of the standpoint according to which categorical claims of forensic individualisation do not follow from a formal analysis under that view of probability theory.

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BACKGROUND: Prehospital oligoanalgesia is prevalent among trauma victims, even when the emergency medical services team includes a physician. We investigated if not only patients' characteristics but physicians' practice variations contributed to prehospital oligoanalgesia. METHODS: Patient records of conscious adult trauma victims transported by our air rescue helicopter service over 10 yr were reviewed retrospectively. Oligoanalgesia was defined as a numeric rating scale (NRS) >3 at hospital admission. Multilevel logistic regression analysis was used to predict oligoanalgesia, accounting first for patient case-mix, and then physician-level clustering. The intraclass correlation was expressed as the median odds ratio (MOR). RESULTS: A total of 1202 patients and 77 physicians were included in the study. NRS at the scene was 6.9 (1.9). The prevalence of oligoanalgesia was 43%. Physicians had a median of 5.7 yr (inter-quartile range: 4.2-7.5) of post-graduate training and 27% were female. In our multilevel analysis, significant predictors of oligoanalgesia were: no analgesia [odds ratio (OR) 8.8], National Advisory Committee for Aeronautics V on site (OR 4.4), NRS on site (OR 1.5 per additional NRS unit >4), female physician (OR 2.0), and years of post-graduate experience [>4.0 to ≤5.0 (OR 1.3), >3.0 to ≤4.0 (OR 1.6), >2.0 to ≤3.0 (OR 2.6), and ≤2.0 yr (OR 16.7)]. The MOR was 2.6, and was statistically significant. CONCLUSIONS: Physicians' practice variations contributed to oligoanalgesia, a factor often overlooked in analyses of prehospital pain management. Further exploration of the sources of these variations may provide innovative targets for quality improvement programmes to achieve consistent pain relief for trauma victims.

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Peripheral T-cell lymphoma, not otherwise specified is a heterogeneous group of aggressive neoplasms with indistinct borders. By gene expression profiling we previously reported unsupervised clusters of peripheral T-cell lymphomas, not otherwise specified correlating with CD30 expression. In this work we extended the analysis of peripheral T-cell lymphoma molecular profiles to prototypical CD30(+) peripheral T-cell lymphomas (anaplastic large cell lymphomas), and validated mRNA expression profiles at the protein level. Existing transcriptomic datasets from peripheral T-cell lymphomas, not otherwise specified and anaplastic large cell lymphomas were reanalyzed. Twenty-one markers were selected for immunohistochemical validation on 80 peripheral T-cell lymphoma samples (not otherwise specified, CD30(+) and CD30(-); anaplastic large cell lymphomas, ALK(+) and ALK(-)), and differences between subgroups were assessed. Clinical follow-up was recorded. Compared to CD30(-) tumors, CD30(+) peripheral T-cell lymphomas, not otherwise specified were significantly enriched in ALK(-) anaplastic large cell lymphoma-related genes. By immunohistochemistry, CD30(+) peripheral T-cell lymphomas, not otherwise specified differed significantly from CD30(-) samples [down-regulated expression of T-cell receptor-associated proximal tyrosine kinases (Lck, Fyn, Itk) and of proteins involved in T-cell differentiation/activation (CD69, ICOS, CD52, NFATc2); upregulation of JunB and MUM1], while overlapping with anaplastic large cell lymphomas. CD30(-) peripheral T-cell lymphomas, not otherwise specified tended to have an inferior clinical outcome compared to the CD30(+) subgroups. In conclusion, we show molecular and phenotypic features common to CD30(+) peripheral T-cell lymphomas, and significant differences between CD30(-) and CD30(+) peripheral T-cell lymphomas, not otherwise specified, suggesting that CD30 expression might delineate two biologically distinct subgroups.

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BACKGROUND: The RUNX1 transcription factor gene is frequently mutated in sporadic myeloid and lymphoid leukemia through translocation, point mutation or amplification. It is also responsible for a familial platelet disorder with predisposition to acute myeloid leukemia (FPD-AML). The disruption of the largely unknown biological pathways controlled by RUNX1 is likely to be responsible for the development of leukemia. We have used multiple microarray platforms and bioinformatic techniques to help identify these biological pathways to aid in the understanding of why RUNX1 mutations lead to leukemia. RESULTS: Here we report genes regulated either directly or indirectly by RUNX1 based on the study of gene expression profiles generated from 3 different human and mouse platforms. The platforms used were global gene expression profiling of: 1) cell lines with RUNX1 mutations from FPD-AML patients, 2) over-expression of RUNX1 and CBFbeta, and 3) Runx1 knockout mouse embryos using either cDNA or Affymetrix microarrays. We observe that our datasets (lists of differentially expressed genes) significantly correlate with published microarray data from sporadic AML patients with mutations in either RUNX1 or its cofactor, CBFbeta. A number of biological processes were identified among the differentially expressed genes and functional assays suggest that heterozygous RUNX1 point mutations in patients with FPD-AML impair cell proliferation, microtubule dynamics and possibly genetic stability. In addition, analysis of the regulatory regions of the differentially expressed genes has for the first time systematically identified numerous potential novel RUNX1 target genes. CONCLUSION: This work is the first large-scale study attempting to identify the genetic networks regulated by RUNX1, a master regulator in the development of the hematopoietic system and leukemia. The biological pathways and target genes controlled by RUNX1 will have considerable importance in disease progression in both familial and sporadic leukemia as well as therapeutic implications

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Abstract. Terrestrial laser scanning (TLS) is one of the most promising surveying techniques for rockslope characteriza- tion and monitoring. Landslide and rockfall movements can be detected by means of comparison of sequential scans. One of the most pressing challenges of natural hazards is com- bined temporal and spatial prediction of rockfall. An outdoor experiment was performed to ascertain whether the TLS in- strumental error is small enough to enable detection of pre- cursory displacements of millimetric magnitude. This con- sists of a known displacement of three objects relative to a stable surface. Results show that millimetric changes cannot be detected by the analysis of the unprocessed datasets. Dis- placement measurement are improved considerably by ap- plying Nearest Neighbour (NN) averaging, which reduces the error (1σ ) up to a factor of 6. This technique was ap- plied to displacements prior to the April 2007 rockfall event at Castellfollit de la Roca, Spain. The maximum precursory displacement measured was 45 mm, approximately 2.5 times the standard deviation of the model comparison, hampering the distinction between actual displacement and instrumen- tal error using conventional methodologies. Encouragingly, the precursory displacement was clearly detected by apply- ing the NN averaging method. These results show that mil- limetric displacements prior to failure can be detected using TLS.

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INTRODUCTION: We aimed to investigate the characteristics and outcome of patients suffering early major worsening (EMW) after acute ischemic stroke (AIS) and assess the parameters associated with it. METHODS: All consecutive patients with AIS in the ASTRAL registry until 10/2010 were included. EMW was defined as an NIHSS increase of ≥8 points within the first 24 h after admission. The Bootstrap version of the Kolmogorov-Smirnov test and the χ(2)-test were used for the comparison of continuous and categorical covariates, respectively, between patients with and without EMW. Multiple logistic regression analysis was performed to identify independent predictors of EMW. RESULTS: Among 2155 patients, 43 (2.0 %) had an EMW. EMW was independently associated with hemorrhagic transformation (OR 22.6, 95 % CI 9.4-54.2), cervical artery dissection (OR 9.5, 95 % CI 4.4-20.6), initial dysarthria (OR 3.7, 95 % CI 1.7-8.0), and intravenous thrombolysis (OR 2.1, 95 % CI 1.1-4.3), whereas a negative association was identified with initial eye deviation (OR 0.4, 95 % CI 0.2-0.9). Favorable outcome at 3 and 12 months was less frequent in patients with EMW compared to patients without (11.6 vs. 55.3 % and 16.3 vs. 50.7 %, respectively), and case fatality was higher (53.5 vs. 12.9 % and 55.8 vs. 16.8 %, respectively). Stroke recurrence within 3 months in surviving patients was similar between patients with and without EMW (9.3 vs. 9.0 %, respectively). CONCLUSIONS: Worsening of ≥8 points in the NIHSS score during the first 24 h in AIS patients is related to cervical artery dissection and hemorrhagic transformation. It justifies urgent repeat parenchymal and arterial imaging. Both conditions may be influenced by targeted interventions in the acute phase of stroke.

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Neuroimaging studies analyzing neurophysiological signals are typically based on comparing averages of peri-stimulus epochs across experimental conditions. This approach can however be problematic in the case of high-level cognitive tasks, where response variability across trials is expected to be high and in cases where subjects cannot be considered part of a group. The main goal of this thesis has been to address this issue by developing a novel approach for analyzing electroencephalography (EEG) responses at the single-trial level. This approach takes advantage of the spatial distribution of the electric field on the scalp (topography) and exploits repetitions across trials for quantifying the degree of discrimination between experimental conditions through a classification scheme. In the first part of this thesis, I developed and validated this new method (Tzovara et al., 2012a,b). Its general applicability was demonstrated with three separate datasets, two in the visual modality and one in the auditory. This development allowed then to target two new lines of research, one in basic and one in clinical neuroscience, which represent the second and third part of this thesis respectively. For the second part of this thesis (Tzovara et al., 2012c), I employed the developed method for assessing the timing of exploratory decision-making. Using single-trial topographic EEG activity during presentation of a choice's payoff, I could predict the subjects' subsequent decisions. This prediction was due to a topographic difference which appeared on average at ~516ms after the presentation of payoff and was subject-specific. These results exploit for the first time the temporal correlates of individual subjects' decisions and additionally show that the underlying neural generators start differentiating their responses already ~880ms before the button press. Finally, in the third part of this project, I focused on a clinical study with the goal of assessing the degree of intact neural functions in comatose patients. Auditory EEG responses were assessed through a classical mismatch negativity paradigm, during the very early phase of coma, which is currently under-investigated. By taking advantage of the decoding method developed in the first part of the thesis, I could quantify the degree of auditory discrimination at the single patient level (Tzovara et al., in press). Our results showed for the first time that even patients who do not survive the coma can discriminate sounds at the neural level, during the first hours after coma onset. Importantly, an improvement in auditory discrimination during the first 48hours of coma was predictive of awakening and survival, with 100% positive predictive value. - L'analyse des signaux électrophysiologiques en neuroimagerie se base typiquement sur la comparaison des réponses neurophysiologiques à différentes conditions expérimentales qui sont moyennées après plusieurs répétitions d'une tâche. Pourtant, cette approche peut être problématique dans le cas des fonctions cognitives de haut niveau, où la variabilité des réponses entre les essais peut être très élevéeou dans le cas où des sujets individuels ne peuvent pas être considérés comme partie d'un groupe. Le but principal de cette thèse est d'investiguer cette problématique en développant une nouvelle approche pour l'analyse des réponses d'électroencephalographie (EEG) au niveau de chaque essai. Cette approche se base sur la modélisation de la distribution du champ électrique sur le crâne (topographie) et profite des répétitions parmi les essais afin de quantifier, à l'aide d'un schéma de classification, le degré de discrimination entre des conditions expérimentales. Dans la première partie de cette thèse, j'ai développé et validé cette nouvelle méthode (Tzovara et al., 2012a,b). Son applicabilité générale a été démontrée avec trois ensembles de données, deux dans le domaine visuel et un dans l'auditif. Ce développement a permis de cibler deux nouvelles lignes de recherche, la première dans le domaine des neurosciences cognitives et l'autre dans le domaine des neurosciences cliniques, représentant respectivement la deuxième et troisième partie de ce projet. En particulier, pour la partie cognitive, j'ai appliqué cette méthode pour évaluer l'information temporelle de la prise des décisions (Tzovara et al., 2012c). En se basant sur l'activité topographique de l'EEG au niveau de chaque essai pendant la présentation de la récompense liée à un choix, on a pu prédire les décisions suivantes des sujets (en termes d'exploration/exploitation). Cette prédiction s'appuie sur une différence topographique qui apparaît en moyenne ~516ms après la présentation de la récompense. Ces résultats exploitent pour la première fois, les corrélés temporels des décisions au niveau de chaque sujet séparément et montrent que les générateurs neuronaux de ces décisions commencent à différentier leurs réponses déjà depuis ~880ms avant que les sujets appuient sur le bouton. Finalement, pour la dernière partie de ce projet, je me suis focalisée sur une étude Clinique afin d'évaluer le degré des fonctions neuronales intactes chez les patients comateux. Des réponses EEG auditives ont été examinées avec un paradigme classique de mismatch negativity, pendant la phase précoce du coma qui est actuellement sous-investiguée. En utilisant la méthode de décodage développée dans la première partie de la thèse, j'ai pu quantifier le degré de discrimination auditive au niveau de chaque patient (Tzovara et al., in press). Nos résultats montrent pour la première fois que même des patients comateux qui ne vont pas survivre peuvent discriminer des sons au niveau neuronal, lors de la phase aigue du coma. De plus, une amélioration dans la discrimination auditive pendant les premières 48heures du coma a été observée seulement chez des patients qui se sont réveillés par la suite (100% de valeur prédictive pour un réveil).

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Background: The variety of DNA microarray formats and datasets presently available offers an unprecedented opportunity to perform insightful comparisons of heterogeneous data. Cross-species studies, in particular, have the power of identifying conserved, functionally important molecular processes. Validation of discoveries can now often be performed in readily available public data which frequently requires cross-platform studies.Cross-platform and cross-species analyses require matching probes on different microarray formats. This can be achieved using the information in microarray annotations and additional molecular biology databases, such as orthology databases. Although annotations and other biological information are stored using modern database models ( e. g. relational), they are very often distributed and shared as tables in text files, i.e. flat file databases. This common flat database format thus provides a simple and robust solution to flexibly integrate various sources of information and a basis for the combined analysis of heterogeneous gene expression profiles.Results: We provide annotationTools, a Bioconductor-compliant R package to annotate microarray experiments and integrate heterogeneous gene expression profiles using annotation and other molecular biology information available as flat file databases. First, annotationTools contains a specialized set of functions for mining this widely used database format in a systematic manner. It thus offers a straightforward solution for annotating microarray experiments. Second, building on these basic functions and relying on the combination of information from several databases, it provides tools to easily perform cross-species analyses of gene expression data.Here, we present two example applications of annotationTools that are of direct relevance for the analysis of heterogeneous gene expression profiles, namely a cross-platform mapping of probes and a cross-species mapping of orthologous probes using different orthology databases. We also show how to perform an explorative comparison of disease-related transcriptional changes in human patients and in a genetic mouse model.Conclusion: The R package annotationTools provides a simple solution to handle microarray annotation and orthology tables, as well as other flat molecular biology databases. Thereby, it allows easy integration and analysis of heterogeneous microarray experiments across different technological platforms or species.

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The purpose of this paper is to describe the development and to test the reliability of a new method called INTERMED, for health service needs assessment. The INTERMED integrates the biopsychosocial aspects of disease and the relationship between patient and health care system in a comprehensive scheme and reflects an operationalized conceptual approach to case mix or case complexity. The method is developed to enhance interdisciplinary communication between (para-) medical specialists and to provide a method to describe case complexity for clinical, scientific, and educational purposes. First, a feasibility study (N = 21 patients) was conducted which included double scoring and discussion of the results. This led to a version of the instrument on which two interrater reliability studies were performed. In study 1, the INTERMED was double scored for 14 patients admitted to an internal ward by a psychiatrist and an internist on the basis of a joint interview conducted by both. In study 2, on the basis of medical charts, two clinicians separately double scored the INTERMED in 16 patients referred to the outpatient psychiatric consultation service. Averaged over both studies, in 94.2% of all ratings there was no important difference between the raters (more than 1 point difference). As a research interview, it takes about 20 minutes; as part of the whole process of history taking it takes about 15 minutes. In both studies, improvements were suggested by the results. Analyses of study 1 revealed that on most items there was considerable agreement; some items were improved. Also, the reference point for the prognoses was changed so that it reflected both short- and long-term prognoses. Analyses of study 2 showed that in this setting, less agreement between the raters was obtained due to the fact that the raters were less experienced and the scoring procedure was more susceptible to differences. Some improvements--mainly of the anchor points--were specified which may further enhance interrater reliability. The INTERMED proves to be a reliable method for classifying patients' care needs, especially when used by experienced raters scoring by patient interview. It can be a useful tool in assessing patients' care needs, as well as the level of needed adjustment between general and mental health service delivery. The INTERMED is easily applicable in the clinical setting at low time-costs.

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Long-range Terrestrial Laser Scanning (TLS) is widely used in studies on rock slope instabilities. TLS point clouds allow the creation of high-resolution digital elevation models for detailed mapping of landslide morphologies and the measurement of the orientation of main discontinuities. Multi-temporal TLS datasets enable the quantification of slope displacements and rockfall volumes. We present three case studies using TLS for the investigation and monitoring of rock slope instabilities in Norway: 1) the analysis of 3D displacement of the Oksfjellet rock slope failure (Troms, northern Norway); 2) the detection and quantification of rockfalls along the sliding surfaces and at the front of the Kvitfjellet rock slope instability (Møre og Romsdal, western Norway); 3) the analysis of discontinuities and rotational movements of an unstable block at Stampa (Sogn og Fjordane, western Norway). These case studies highlight the possibilities but also limitations of TLS in investigating and monitoring unstable rock slopes.

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The development of susceptibility maps for debris flows is of primary importance due to population pressure in hazardous zones. However, hazard assessment by processbased modelling at a regional scale is difficult due to the complex nature of the phenomenon, the variability of local controlling factors, and the uncertainty in modelling parameters. A regional assessment must consider a simplified approach that is not highly parameter dependant and that can provide zonation with minimum data requirements. A distributed empirical model has thus been developed for regional susceptibility assessments using essentially a digital elevation model (DEM). The model is called Flow-R for Flow path assessment of gravitational hazards at a Regional scale (available free of charge under www.flow-r.org) and has been successfully applied to different case studies in various countries with variable data quality. It provides a substantial basis for a preliminary susceptibility assessment at a regional scale. The model was also found relevant to assess other natural hazards such as rockfall, snow avalanches and floods. The model allows for automatic source area delineation, given user criteria, and for the assessment of the propagation extent based on various spreading algorithms and simple frictional laws.We developed a new spreading algorithm, an improved version of Holmgren's direction algorithm, that is less sensitive to small variations of the DEM and that is avoiding over-channelization, and so produces more realistic extents. The choices of the datasets and the algorithms are open to the user, which makes it compliant for various applications and dataset availability. Amongst the possible datasets, the DEM is the only one that is really needed for both the source area delineation and the propagation assessment; its quality is of major importance for the results accuracy. We consider a 10m DEM resolution as a good compromise between processing time and quality of results. However, valuable results have still been obtained on the basis of lower quality DEMs with 25m resolution.

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If childcare policy has become topical in most OECD countries over the last ten years or so, actual developments display huge cross-national variations. Countries like Sweden and Denmark spend around 2 per cent of GDP on this service, and provide affordable childcare places to most children below school age. At the other extreme, in Southern Europe, only around 10 per cent of this age group has access to formal daycare. Against this background, this article aims to account for cross-national variations in childcare services. It distinguishes two dependent variables: the coverage rate and the proportion of GDP spent subsidising childcare services. Using a mix of cross-sectional and pooled times-series methods, it tests a series of hypotheses concerning the determinants of the development of this policy. Its main conclusion for the coverage rate is that key factors are public spending and wage dispersion (both positive). For spending, key factors are the proportion of women in parliaments (positive) and spending on age-related policies (negative).

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BACKGROUND: Studies about the association between body mass index (BMI) and health-related quality of life (HRQOL) are often limited, because they 1) did not include a broad range of health-risk behaviors as covariates; 2) relied on clinical samples, which might lead to biased results; and 3) did not incorporate underweight individuals. Hence, this study aims to examine associations between BMI (from being underweight through obesity) and HRQOL in a population-based sample, while considering multiple health-risk behaviors (low physical activity, risky alcohol consumption, daily cigarette smoking, frequent cannabis use) as well as socio-demographic characteristics. METHODS: A total of 5 387 young Swiss men (mean age = 19.99; standard deviation = 1.24) of a cross-sectional population-based study were included. BMI was calculated (kg/m²) based on self-reported height and weight and divided into 'underweight' (<18.5), 'normal weight' (18.5-24.9), 'overweight' (25.0-29.9) and 'obese' (≥30.0). Mental and physical HRQOL was assessed via the SF-12v2. Self-reported information on physical activity, substance use (alcohol, cigarettes, and cannabis) and socio-demographic characteristics also was collected. Logistic regression analyses were conducted to study the associations between BMI categories and below average mental or physical HRQOL. Substance use variables and socio-demographic variables were used as covariates. RESULTS: Altogether, 76.3% were normal weight, whereas 3.3% were underweight, 16.5% overweight and 3.9% obese. Being overweight or obese was associated with reduced physical HRQOL (adjusted OR [95% CI] = 1.58 [1.18-2.13] and 2.45 [1.57-3.83], respectively), whereas being underweight predicted reduced mental HRQOL (adjusted OR [95% CI] = 1.49 [1.08-2.05]). Surprisingly, obesity decreased the likelihood of experiencing below average mental HRQOL (adjusted OR [95% CI] = 0.66 [0.46-0.94]). Besides BMI, expressed as a categorical variable, all health-risk behaviors and socio-demographic variables were associated with reduced physical and/or mental HRQOL. CONCLUSIONS: Deviations from normal weight are, even after controlling for important health-risk behaviors and socio-demographic characteristics, associated with compromised physical or mental HRQOL among young men. Hence, preventive programs should aim to preserve or re-establish normal weight. The self-appraised positive mental well-being of obese men noted here, which possibly reflects a response shift, might complicate such efforts.

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Recently, kernel-based Machine Learning methods have gained great popularity in many data analysis and data mining fields: pattern recognition, biocomputing, speech and vision, engineering, remote sensing etc. The paper describes the use of kernel methods to approach the processing of large datasets from environmental monitoring networks. Several typical problems of the environmental sciences and their solutions provided by kernel-based methods are considered: classification of categorical data (soil type classification), mapping of environmental and pollution continuous information (pollution of soil by radionuclides), mapping with auxiliary information (climatic data from Aral Sea region). The promising developments, such as automatic emergency hot spot detection and monitoring network optimization are discussed as well.

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Some introduced ant populations have an extraordinary social organization, called unicoloniality, whereby individuals mix freely within large supercolonies. We investigated whether this mode of social organization also exists in native populations of the Argentine ant Linepithema humile. Behavioral analyses revealed the presence of 11 supercolonies (width 1 to 515 m) over a 3-km transect. As in the introduced range, there was always strong aggression between but never within supercolonies. The genetic data were in perfect agreement with the behavioral tests, all nests being assigned to identical supercolonies with the different methods. There was strong genetic differentiation between supercolonies but no genetic differentiation among nests within supercolonies. We never found more than a single mitochondrial haplotype per supercolony, further supporting the view that supercolonies are closed breeding units. Genetic and chemical distances between supercolonies were positively correlated, but there were no other significant associations between geographic, genetic, chemical, and behavioral distances. A comparison of supercolonies sampled in 1999 and 2005 revealed a very high turnover, with about one-third of the supercolonies being replaced yearly. This dynamic is likely to involve strong competition between supercolonies and thus act as a potent selective force maintaining unicoloniality over evolutionary time.