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PubMed2005

Design and psychometric evaluation of the Psychological Adaptation to Genetic Information Scale.

PURPOSE: To develop and psychometrically evaluate the Psychological Adaptation to Genetic Information Scale (PAGIS). DESIGN: A cross-sectional, Web-based survey of participants (n=323) recruited via Internet electronic mailing lists or Websites for people affected by genetic diseases. METHODS: Item analysis, confirmatory principal components analysis, and internal consistency reliability using Cronbach's alpha were used to construct the 26-item PAGIS. FINDINGS: Five factors (nonintrusiveness, support, self-worth, certainty, and self-efficacy) explained 57.7% of the variance in psychological adaptation to genetic information. The internal consistency reliability of the total PAGIS was .90, and the subscale reliabilities ranged from .77 to .87. CONCLUSIONS: Psychological adaptation to genetic information is a multidimensional phenomenon comprised of nonintrusiveness, support, self-worth, certainty, and self-efficacy. The PAGIS has initial reliability and validity for use in future research.

Adaptation, Psychological↗

PubMed1996

Kinematic determinants of human locomotion.

1. The aim of this study was to find kinematic patterns that are invariant across the normal range of locomotion speeds. Subjects walked at different, freely chosen speeds ranging from 0.9 to 2.1 m s-1, while motion and ground reaction forces on the right side of the body were recorded in three-dimensional space. 2. The time course of the anatomical angles of flexion-extension at the hip and ankle was variable not only across subjects, but even from trial to trial in the same subject. By contrast, the time course of the changes in the angles of elevation of each limb segment (pelvis, thigh, shank and foot) relative to the vertical was stereotyped across subjects. 3. To compare the waveforms across speeds, data were scaled in time relative to gait cycle duration. The pattern of ground reaction forces was highly speed dependent. Several distinct families of curves could be recognized in the flexion-extension angles at the hip and ankle. Instead, the waveforms of global length and elevation of the limb, elevation angles of all limb segments and flexion-extension at the knee were invariant with speed. 4. When gait trajectories at all speeds are plotted in the position space defined by the elevation angles of the limb segments, they describe regular loops on a plane. The statistical characteristics of these angular covariations were quantified by means of principal component analysis. The first two principal components accounted together for > 99% of the total experimental variance, and were quantitatively comparable in all subjects. 5. This constraint of planar covariation of the elevation angles is closely reminiscent of that previously described for the control of posture. The existence of laws of intersegmental co-ordination, common to the control of posture and locomotion, presumably assures the maintenance of dynamic equilibrium during forward progression, and the anticipatory adaptation to potentially destabilizing factors by means of co-ordinated kinematic synergies of the whole body.

Adult↗

PubMed2004

Dissociation of slow waves and fast oscillations above 200 Hz during GABA application in rat somatosensory cortex.

Fast electrical oscillations (FOs; > 200 Hz), superimposed on vibrissa-evoked slow potentials, may support rapid sensory integration in neocortex. Yet, while it is well established that the positive/negative (P1/N1) slow wave of the somatosensory evoked potential primarily reflects sequential activation of supragranular and infragranular pyramidal cells mediated chiefly via excitatory chemical synaptic pathways, little is known about the generation of FOs. In this study, laminar current source-density analysis and principal component analysis indicated that FOs are generated by two dipolar current sources situated in the supra- and infragranular layers, similar in laminar location to the two current dipoles associated with the slow wave. However, exogenous GABA application reversibly abolished the N1 slow wave, leaving the P1 intact, while the FO was unaffected by GABA. Furthermore, reductions in both supra- and infragranular cortical unit discharge during application of GABA suggests that FO generation is not dependent on the same intracortical synaptic circuits that are associated with the N1 slow wave. These data suggest a marked functional dissociation between neural mechanisms underlying the slow and fast components of the vibrissa-evoked response.

Animals↗

PubMed1998

Selection and combination of acoustic features for the description of pathologic voices.

The glottal to noise excitation ratio (GNE) is an acoustic measure designed to assess the amount of noise in a pulse train generated by the oscillation of the vocal folds. So far its properties have only been studied for synthesized signals, where it was found to be independent of variations of fundamental frequency (jitter) and amplitude (shimmer). On the other hand, other features designed for the same purpose like NNE (normalized noise energy) or CHNR (cepstrum based harmonics-to-noise ratio) did not show this independence. This advantage of the GNE over NNE and CHNR, as well as its general applicability in voice quality assessment, is now tested for real speech using a large group of pathologic voices (n = 447). A set of four acoustic features is extracted from a total of 22 mostly well-known acoustic voice quality measures by correlation analysis, mutual information analysis, and principal components analysis. Three of these measures are chosen to assess primarily different aspects of signal aperiodicity, while the fourth one indicates the noise content of the signal. All analysis methods lead to the same feature set that consists of a measure of period correlation, jitter, shimmer, and GNE. The two-dimensional projection of this set named "hoarseness diagram" allows a graphical illustration of voice quality that can be easily interpreted.

Adolescent↗

PubMed2000

Differentiation between Candida dubliniensis and Candida albicans by fatty acid methyl ester analysis using gas-liquid chromatography.

Candida dubliniensis is often found in mixed culture with C. albicans, but its recognition is hampered as the color of its colonies in primary culture on CHROMagar Candida varies. Furthermore, definite identification of C. dubliniensis is difficult to achieve, time-consuming, and expensive. Therefore, a method to discriminate between these two closely related yeast species by fatty acid methyl ester (FAME) analysis using gas-liquid chromatography (Sherlock Microbial Identification System [MIS]; MIDI, Inc., Newark, Del.) was developed. Although the chromatograms of these two species revealed no obvious differences when applying FAME analysis, a new library (CADLIB) was successfully created using Sherlock Library Generation Software (MIDI). The amount and frequency of FAME was analyzed using library training files (n = 10 for each species), preferentially those comprising reference strains. For testing the performance of the CADLIB, clinical isolates genetically assigned to the respective species (C. albicans, n = 32; C. dubliniensis, n = 28) were chromatographically analyzed. For each isolate tested, MIS computed a similarity index (SI) indicating a hierarchy of possible strain fits. When using the newly created library CADLIB, the SIs for C. albicans and C. dubliniensis ranged from 0.11 to 0.96 and 0.53 to 0. 93 (for all but one), respectively. Only three isolates of C. albicans (9.4%) were misidentified as C. dubliniensis, whereas all isolates of C. dubliniensis were correctly identified. Resulting differentiation accuracy was 90.6% for C. albicans and 100% for C. dubliniensis. Cluster analysis and principal component analysis of the resulting FAME profiles showed two clearly distinguishable clusters matching up with two assigned species for the strains tested. Thus, the created library proved to be well suited to discriminate between these two species.

AIDS-Related Opportunistic Infections↗

PubMed2025

Use of IR Biotyper as a feasible methodology to type Klebsiella pneumoniae.

UNLABELLED: Klebsiella pneumoniae is one of the most frequently reported healthcare-associated pathogens. The current gold standard approach to perform the epidemiological typing of these bacteria is Whole Genome Sequencing (WGS), which is an expensive and challenging procedure. IR Biotyper (Bruker Daltonics, GmbH) is a new equipment based on Fourier transform infrared spectroscopy, which allows a rapid, low-cost, and user-friendly method to type bacterial isolates. However, there is a need for studies that evaluate the efficacy of the IR Biotyper. The aim of this study was to evaluate the capability of IR Biotyper to type K. pneumoniae according to sequence type (ST) and capsular type-using K locus (KL)-as well as to develop a classifier using machine learning. Seventy-three isolates of K. pneumoniae previously characterized by WGS were selected for IR Biotyper analysis using principal component analysis for dimensionality reduction, Euclidean, and unweighted pair group method with arithmetic mean (UPGMA) for clustering method, and spectra were analyzed in the 1,300-800 cm⁻¹ wavenumber range. Among these, 54 isolates were used to create a classifier, and 19 were used to validate the classifier. When considering the ST, ST307 was grouped in the same cluster as ST11. When KL was considered for the analysis, the clusters were 100% correctly grouped according to their KL type. Furthermore, the classifier developed was able to classify the isolates according to KL with a high concordance. This study showed that KL correlates well with KL for typing K. pneumoniae isolates using the IR Biotyper. Additionally, IR Biotyper demonstrated to be a cost-effective method and a promising tool to classify isolates within minutes. IMPORTANCE: Klebsiella pneumoniae is a major cause of severe hospital infections, and controlling its spread requires quick identification and comparison of bacterial strains. WGS is accurate but expensive, slow, and technically demanding. In this study, we evaluated the IR Biotyper, a device that uses infrared light to analyze bacteria and group them by capsule type-a key feature linked to their spread. The IR Biotyper matched WGS results with high accuracy, delivering results in minutes instead of days. This fast, affordable method can help hospitals detect outbreaks earlier and respond more effectively. Our findings suggest that the IR Biotyper is a valuable tool for routine use in microbiology laboratories, supporting epidemiological surveillance and outbreak control.

Klebsiella pneumoniae↗

PubMed1994

Relation of principal components of ECG maps to loci of wall motion abnormality in old myocardial infarction.

The purpose of this study was to examine the correlation between body surface potential distribution and the extent of abnormally contracting segments (ACS) of the left ventricle in patients with old myocardial infarction (MI). Body surface potential distribution was quantitatively analyzed using principal component analysis. The first six principal components were extracted from data set obtained from both 25 normal subjects and 100 patients. The z scores (principal component weights) were calculated in a time domain at every 4 or 8 ms in another 81 patients with previous MI. In anterior MI, the second z scores on T wave and the fourth z scores on QRS complex were significantly lower in the presence than in the absence of ACS at the lateral wall. In inferior MI, the first z scores on QRS complex, the second on T wave, and the third on both Q and T represented significant differences between the presence and the absence of ACS at the posterior wall. Minute differences in the extent of ACS were sensitively and noninvasively detected on z scores of principal components.

Adolescent↗

PubMed2004

Molecular prediction of response to 5-fluorouracil and interferon-alpha combination chemotherapy in advanced hepatocellular carcinoma.

PURPOSE: The prognosis of hepatocellular carcinoma (HCC) is very poor, particularly in patients with tumors that have invaded the major branches of the portal vein. Combination chemotherapy with intra-arterial 5-fluorouracil and subcutaneous interferon-alpha has shown promising results for such advanced HCC, but it is important to develop the ability to accurately predict chemotherapeutic responses. EXPERIMENTAL DESIGN: We analyzed the expression of 3,080 genes using a polymerase chain reaction-based array in 20 HCC patients who were treated with combination chemotherapy after reduction surgery. After unsupervised analyses, a supervised classification method for predicting chemotherapeutic responses was constructed. To minimize the number of predictive genes, we used a random permutation test to select only significant (P < 0.01) genes. A leave-one-out cross-validation confirmed the gene selection. We also prepared an additional 11 cases for validation of predictive performance. RESULTS: Hierarchical clustering analysis and principal component analysis with all 3,080 genes revealed distinct gene expression patterns in responders (those with complete response or partial response) and nonresponders (those with stable disease or progressive disease) to the combination chemotherapy. Using a weighted-voting classification method with either all genes or only significant genes as assessed by permutation testing, the objective responses to treatment were correctly predicted in 17 of 20 cases (accuracy, 85%; positive predictive value, 100%; negative predictive value, 80%). Moreover, patients in the validation dataset could be classified into two distinct prognostic groups using 63 predictive genes. CONCLUSIONS: Molecular analysis of 63 genes can predict the response of patients with advanced HCC and major portal vein tumor thrombi to combination chemotherapy with 5-fluorouracil and interferon-alpha.

Adult↗

PubMed2003

Global gene expression profiles in fibroblasts from synovial, skin and lymphoid tissue reveals distinct cytokine and chemokine expression patterns.

We investigated the extent to which fibroblasts isolated from diverse tissues differ in their capacity to modulate inflammation by comparing the global gene expression profiles of cultured human fibroblasts from skin, acute and chronically inflamed synovium, lymph node and tonsil. The responses of these fibroblasts to TNF-alpha, IFN-gamma and IL-4 stimulation were markedly different, as revealed by hierarchical cluster analysis and principal component analysis. In the absence of exogenous cytokine, synovial and skin fibroblasts exhibited similar patterns of gene expression. However their transcriptional profiles diverged upon treatment with TNF-alpha. This proved to be biologically relevant, as TNF-alpha induced the secretion of different patterns and amounts of IL-6, IL-8 and CCL2 (MCP-1) in the two fibroblast types. Co-culture of skin or synovial fibroblasts with synovial fluid-derived mononuclear cells provided further evidence that these transcriptional differences were functionally significant in an ex vivo setting. Interestingly, the transcriptional response of skin fibroblasts to IL-4 converged with that of TNF-alpha-treated synovial fibroblasts, suggesting resident tissue fibroblasts and their blood-borne precursors may be imprinted by inflammatory cytokines that are characteristic of different tissues. Our data supports the concept that fibroblasts are heterogeneous, and that they contribute to the tissue-specificity of inflammatory reactions. Fibroblasts are therefore likely to play an active role in the persistence of chronic inflammatory reactions.

Adjuvants, Immunologic↗

PubMed1999

Independent factor analysis.

We introduce the independent factor analysis (IFA) method for recovering independent hidden sources from their observed mixtures. IFA generalizes and unifies ordinary factor analysis (FA), principal component analysis (PCA), and independent component analysis (ICA), and can handle not only square noiseless mixing but also the general case where the number of mixtures differs from the number of sources and the data are noisy. IFA is a two-step procedure. In the first step, the source densities, mixing matrix, and noise covariance are estimated from the observed data by maximum likelihood. For this purpose we present an expectation-maximization (EM) algorithm, which performs unsupervised learning of an associated probabilistic model of the mixing situation. Each source in our model is described by a mixture of gaussians; thus, all the probabilistic calculations can be performed analytically. In the second step, the sources are reconstructed from the observed data by an optimal nonlinear estimator. A variational approximation of this algorithm is derived for cases with a large number of sources, where the exact algorithm becomes intractable. Our IFA algorithm reduces to the one for ordinary FA when the sources become gaussian, and to an EM algorithm for PCA in the zero-noise limit. We derive an additional EM algorithm specifically for noiseless IFA. This algorithm is shown to be superior to ICA since it can learn arbitrary source densities from the data. Beyond blind separation, IFA can be used for modeling multidimensional data by a highly constrained mixture of gaussians and as a tool for nonlinear signal encoding.

Algorithms↗

PubMed2006

An illustration of issues in factor extraction and identification of dimensionality in psychological assessment data.

Structural validity has long been regarded as critical to psychological measurement. However, in practical application, issues central to structural validity are often neglected. The purpose of this study was to illustrate the importance of several crucial choices that face researchers attempting to evaluate the structure of data from a given scale. In this study, I compared the structural solutions derived via principal components analysis and principal axis factoring using eigenvalues, scree plots, and traditional parallel analyses with data from the Purpose in Life Test (Crumbaugh & Maholick, 1964). I discuss the importance of structural validity for overall construct validity and the importance of carefully considering factor analytic methodology. I provide recommendations for uses of factor analysis.

Adult↗

PubMed2003

Evaluation of the bitterness of antibiotics using a taste sensor.

The bitterness of nine commercial antibiotics (clarithromycin, erythromycin, cefdinil, doxycycline, vancomycin, tetracycline, minocycline, oxytetracycline and bacampicillin) was evaluated in human gustatory sensation tests with nine volunteers. The bitterness of 0.1-0.3 mM solutions (or suspensions in the case of clarithromycin) of the antibiotics was then measured using an artificial multichannel taste sensor. In the sensor measurements, three variables were used to predict estimated bitterness in single and multiple regression analysis and principal component analysis: sensor output as relative value (R), the change of membrane potential caused by adsorption (C) and C/R. Particularly good correlation was obtained between obtained bitterness scores and predicted scores using C from channel 2 of the sensor (r2=0.870, P<0.005) and C/R values for channels 2 and 3 (r2=0.947, P<0.005). The taste sensor was also successful in assessing the bitterness intensity of clarithromycin powder suspensions of various concentrations. Clarithromycin has a low aqueous solubility but is the most bitter of the nine antibiotics. Sensory data from channel 3 of the sensor predicted the bitterness of clarithromycin powder suspensions and their filtered solutions well. Finally, the bitterness intensity of a commercial clarithromycin dry syrup product (Clarith dry syrup, Taisho Pharmaceutical Co. Ltd, Tokyo, Japan) was evaluated in gustatory sensation tests and using the taste sensor. In Clarith dry syrup the drug is coated with aminoalkyl methacrylate polymer using a spray congealing method. The taste sensor results confirmed that the polymer was successful in almost completely masking the bitter taste of the dry syrup product.

Anti-Bacterial Agents↗

PubMed1994

[Development of quantitative structure-activity relationships and computer-aided drug design].

Recent development of quantitative structure-activity relationships (QSARs) and computer-aided drug design contributed by the author and his coworkers was briefly reviewed. Fuzzy adaptive least-squares (FALS), a pattern recognition method for analysing structure-activity rating data to generate QSAR models was developed. A novel feature of FALS is that the degree to which each sample belongs to its activity class is given by a fuzzy membership function. Using FALS, non-congeneric QSAR analyses of carcinogenicity, mutagenicity, and six kinds of pharmacokinetic properties of miscellaneous organic chemicals were performed to construct predictive models for drug design. In these QSAR analyses, the values of log P (partition coefficient in octanol/water) calculated by the simple method of Moriguchi et al. were used as the descriptor for hydrophobicity. The method of Moriguchi et al. is not only simple and convenient but also reliable in the application to 22 drugs selected by Rekker et al. compared to the Rekker method and the Hansch-Leo method. Lastly, a heulistic search method for active conformers using molecular mechanical conformational analysis and principal component analysis was proposed.

Animals↗

PubMed2005

Communication in collaborative discovery learning.

BACKGROUND: Constructivist approaches to learning focus on learning environments in which students have the opportunity to construct knowledge themselves, and negotiate this knowledge with others. Discovery learning and collaborative learning are examples of learning contexts that cater for knowledge construction processes. We introduce a computer-based learning environment in which the two forms of learning are implemented simultaneously. We focus on the interaction between discovery learning and collaborative learning. AIM: We aim to investigate which communicative activities are frequently used in the discovery learning process and which communicative and discovery activities co-occur. SAMPLE: The study involved 21 pairs of 10th-grade students enrolled in pre-university education, ranging from 15 to 17 years of age. METHOD: Participants worked in dyads on separate screens in a shared discovery learning environment. They communicated using a chat box. In order to find a possible relationship between communicative activities and discovery learning processes, correlational analysis and principal component analysis were performed. RESULT: Significant relationships were found between communicative and discovery activities, as well as five factors combining the communicative process and the discovery learning processes. Communicative activities are performed most frequently during the activities in generating hypotheses, experimental design, and conclusion construction. Argumentation occurs less than expected, and is associated with the construction of conclusions, rather than generating hypotheses. CONCLUSION: Communicative activities co-occur with discovery activities most of the time, as we expected. Further research should concentrate on means to augment communicative and discovery activities that are related to positive learning outcomes.

Adolescent↗

PubMed2006

Prediction of oil and oleic acid concentrations in individual corn (Zea mays L.) kernels using near-infrared reflectance hyperspectral imaging and multivariate analysis.

Due to their heterogeneous structure and variability in form, individual corn (Zea mays L.) kernels present an optical challenge for nondestructive spectroscopic determination of their chemical composition. Increasing demand in agricultural science for knowledge of specific traits in kernels is driving the need to find high-throughput methods of examination. In this study macroscopic near-infrared (NIR) reflectance hyperspectral imaging was used to measure small sets of kernels in the spectroscopic range of 950 nm to 1700 nm. Image analysis and principal component analysis (PCA) were used to determine kernel germ from endosperm regions as well as to define individual kernels as objects out of sets of kernels. Partial least squares (PLS) analysis was used to predict oil or oleic acid concentrations derived from germ or full kernel spectra. The relative precision of the minimum cross-validated root mean square error (RMSECV) and root mean square error of prediction (RMSEP) for oil and oleic acid concentration were compared for two sets of two hundred kernels. An optimal statistical prediction method was determined using a limited set of wavelengths selected by a genetic algorithm. Given these parameters, oil content was predicted with an RMSEP of 0.7% and oleic acid content with an RMSEP of 14% for a given corn kernel.

Agriculture↗

PubMed1993

Self-organizing neural networks as a means of cluster analysis in clinical chemistry.

Connectionist systems (often termed "neural networks") are an alternative way to solve data processing tasks. They differ radically from conventional "von-Neumann" computing devices. Recent work on neural networks in clinical chemistry was done using supervised learning schemes, resulting in models which resemble classical discriminant analysis. The aim of the present study is to make clinical chemists familiar with basic concepts of self-organizing neural networks employing unsupervised learning schemes. Using a benchmark data set on the composition of milk from 22 different mammals, it is demonstrated that self-organizing neural networks are capable of performing tasks similar to classical cluster analysis and principal component analysis. Self-organizing neural networks could be envisaged to provide an alternative way for reducing the dimensionality of complex multivariate data sets, thus producing easily comprehensible low-dimensional "maps" of essential features.

Animals↗

PubMed2005

Identification of male factor infertility using a novel semen quality score and reactive oxygen species levels.

PURPOSE: To determine whether patients with male factor infertility can be accurately identified by calculating a novel semen quality score and measuring levels of reactive oxygen species during routine infertility screening. METHODS: Semen samples from 133 patients and 91 healthy donors were evaluated with manual and computer-assisted semen analysis. A principal component analysis model was employed to calculate a semen quality score. In brief, this score was calculated by base 10 logarithms multiplied by varying weights given to 9 sperm parameters. Reactive oxygen species levels were measured using chemiluminescence assay. RESULTS: The semen quality score had a sensitivity of 80.45% and accuracy of 77% at a cutoff of 93.1 in identifying patients with male factor infertility. The area under the receiver operating characteristic curves for the semen quality score was 84.28% (95% CI: 65.22%-100%). Reactive oxygen species levels [log10 (reactive oxygen species +1)] were significantly higher in male factor infertility patients. Reactive oxygen species had a sensitivity of 83.47% and specificity of 60.52% with an accuracy of 75% at a cutoff of 1.25 in identifying male factor infertility patients. The area under the receiver operating characteristic curve for reactive oxygen species levels was 78.92% (95% CI: 72.60%-85.23%). Semen quality scores were significantly and negatively correlated with reactive oxygen species levels in the donors and the male factor infertility patients. CONCLUSIONS: The semen quality score and reactive oxygen species levels in semen samples appear to be strongly associated with male factor infertility. Because both of these parameters are more sensitive than individual sperm parameters in identifying male factor infertility, they should be included in routine infertility screening.

Case-Control Studies↗

PubMed2026

Microrna Expression in Aurelia aurita Metamorphosis.

INTRODUCTION: In animal taxa and jellyfish, the same genome encodes for the different phenotypes that characterize life stages that follow each other during ontogeny. This situation underscores the existence of profound regulation of genomic information at the epigenetic level. MicroRNAs are fundamental epigenetic regulators. The aim of this study is to evaluate the role of microRNA regulation during jellyfish metamorphosis and to explore the existence of evolutionarily conserved microRNAs. METHODS: Specimens belonging to the 4-metamorphosis stages of A. aurita (polyps, ephyra, young, and adult jellyfish) were bred and collected. The expression of 2,549 miRNAs for each stage was tested using microarray technology. The comparison of microRNA expression for each phase was performed using line plot analysis and Principal Component Analysis of variance (PCA), while the identification of microRNA clusters was performed via volcano plot analysis. RESULTS: A remarkable number of A. aurita miRNAs specifically hybridize with a human miRNA library. Each metamorphosis stage is characterized by a different level of expression of miRNAs: 1) Polyp vs. Ephyra stage: 128 upregulated, 2 downregulated; 2) Ephyra vs. Young stage: 2 upregulated, 135 downregulated; 3) Young vs. Adult stage: 69 upregulated, 6 downregulated. Specific functions inferred from known activities of corresponding miRNAs in higher animals (PubMed database) appear to be coherent with the correlated experimental model. DISCUSSION: Present results reveal that microRNAs with human homologs undergo specific expression changes throughout Aurelia aurita metamorphosis. This observation reinforces the hypothesis of a shared evolutionary origin of certain miRNA families between Cnidaria and Bilateria. The dynamic and stage-specific regulation pattern observed suggests that miRNAs play a key role in orchestrating the complex transitions involved in jellyfish development. These findings point to a broader conservation of epigenetic mechanisms, such as miRNA-mediated gene silencing, which may have emerged early in metazoan evolution and contributed to the regulation of cell differentiation and phenotype modulation. CONCLUSION: The present study highlights the importance of Aurelia aurita as a model for investigating miRNA-driven epigenetic regulation in non-bilaterian animals. The identification of human-homologous miRNAs provides novel insights into the evolutionary stability of the epigenetic machinery and suggests conserved regulatory functions across distant taxa. Although limited by the use of a human-based microarray platform, the data presented here lay a solid foundation for future studies employing sequencing and functional assays to further explore the role of miRNAs in cnidarian development and evolution.

Animals↗