Spreading of aqueous surfactant solutions on oil substrates: Superspreaders vs non-superspreaders.

HYPOTHESIS: The question of why aqueous solutions of some surfactants demonstrate a rapid spreading (superspreading) over hydrophobic solid substrates, while solutions of other similar surfactants do not, has no definitive explanation despite numerous previous studies. The suggested hypothesis for this study assumes that once the spreading coefficient of surfactant is positive, there is a concentration range for solutions of any surfactant which demonstrates rapid spreading. As it is impossible to calculate spreading coefficients for solid substrates, we compare the spreading performance of known superspreaders and non-superspreaders on liquid (oil) substrate. EXPERIMENTS: The kinetics of spreading of aqueous solutions of a series of branched ionic surfactants and non-ionic trisiloxane surfactants on two liquid substrates was studied and compared with the spreading of a surfactant-free liquid, silicone oil. Both dynamic and equilibrium spreading coefficients were calculated using measured surface and interfacial tensions. FINDINGS: There is no difference in spreading rate on liquid substrate between solutions of surfactants proven as superspreaders (while spreading on solid substrate) or non-superspreaders. A rapid spreading (superspreading) with the characteristic rate of spreading O(102-103) mm2/s occurs if the dynamic spreading coefficients exceeds the positive threshold value. If the dynamic spreading coefficient is negative or slightly positive, complete wetting still occurs, but the spreading is slow with the spreading rate is O(1) mm2/s. Spreading exponents for surfactant solutions in the rapid spreading regime are considerably larger than for the surfactant-free liquid. A number of spreading and dewetting patterns were observed depending on the surfactant type, its concentration and substrate.

Analyzing drop coalescence in microfluidic devices with a deep learning generative model.

Predicting drop coalescence based on process parameters is crucial for experimental design in chemical engineering. However, predictive models can suffer from the lack of training data and more importantly, the label imbalance problem. In this study, we propose the use of deep learning generative models to tackle this bottleneck by training the predictive models using generated synthetic data. A novel generative model, named double space conditional variational autoencoder (DSCVAE) is developed for labelled tabular data. By introducing label constraints in both the latent and the original space, DSCVAE is capable of generating consistent and realistic samples compared to the standard conditional variational autoencoder (CVAE). Two predictive models, namely random forest and gradient boosting classifiers, are enhanced on synthetic data and their performances are evaluated based on real experimental data. Numerical results show that a considerable improvement in prediction accuracy can be achieved by using synthetic data and the proposed DSCVAE clearly outperforms the standard CVAE. This research clearly provides more insights into handling imbalanced data for classification problems, especially in chemical engineering.

Quantification of congruence among gene trees with polytomies using overall success of resolution for phylogenomic coalescent analyses.

Gene-tree-inference error can cause species-tree-inference artefacts in summary phylogenomic coalescent analyses. Here we integrate two ways of accommodating these inference errors: collapsing arbitrarily or dubiously resolved gene-tree branches, and subsampling gene trees based on their pairwise congruence. We tested the effect of collapsing gene-tree branches with 0% approximate-likelihood-ratio-test (SH-like aLRT) support in likelihood analyses and strict consensus trees for parsimony, and then subsampled those partially resolved trees based on congruence measures that do not penalize polytomies. For this purpose we developed a new TNT script for congruence sorting (congsort), and used it to calculate topological incongruence for eight phylogenomic datasets using three distance measures: standard Robinson-Foulds (RF) distances; overall success of resolution (OSR), which is based on counting both matching and contradicting clades; and RF contradictions, which only counts contradictory clades. As expected, we found that gene-tree incongruence was often concentrated in clades that are arbitrarily or dubiously resolved and that there was greater congruence between the partially collapsed gene trees and the coalescent and concatenation topologies inferred from those genes. Coalescent branch lengths typically increased as the most incongruent gene trees were excluded, although branch supports typically did not. We investigated two successful and complementary approaches to prioritizing genes for investigation of alignment or homology errors. Coalescent-tree clades that contradicted concatenation-tree clades were generally less robust to gene-tree subsampling than congruent clades. Our preferred approach to collapsing likelihood gene-tree clades (0% SH-like aLRT support) and subsampling those trees (OSR) generally outperformed competing approaches for a large fungal dataset with respect to branch lengths, support and congruence. We recommend widespread application of this approach (and strict consensus trees for parsimony-based analyses) for improving quantification of gene-tree congruence/conflict, estimating coalescent branch lengths, testing robustness of coalescent analyses to gene-tree-estimation error, and improving topological robustness of summary coalescent analyses. This approach is quick and easy to implement, even for huge datasets.

Use of In Vitro Dynamic Colon Model (DCM) to Inform a Physiologically Based Biopharmaceutic Model (PBBM) to Predict the In Vivo Performance of a Modified-Release Formulation of Theophylline.

A physiologically based biopharmaceutic model (PBBM) of a modified-release formulation of theophylline (Uniphyllin Continus® 200 mg tablet) was developed and implemented to predict the pharmacokinetic (PK) data of healthy male volunteers by integrating dissolution profiles measured in a biorelevant in vitro model: the Dynamic Colon Model (DCM). The superiority of the DCM over the United States Pharmacopeia (USP) Apparatus II (USP II) was demonstrated by the superior predictions for the 200 mg tablet (average absolute fold error (AAFE): 1.1-1.3 (DCM) vs. 1.3-1.5 (USP II). The best predictions were obtained using the three motility patterns (antegrade and retrograde propagating waves, baseline) in the DCM, which produced similar PK profiles. However, extensive erosion of the tablet occurred at all agitation speeds used in USP II (25, 50 and 100 rpm), resulting in an increased drug release rate in vitro and overpredicted PK data. The PK data of the Uniphyllin Continus® 400 mg tablet could not be predicted with the same accuracy using dissolution profiles from the DCM, which might be explained by differences in upper gastrointestinal (GI) tract residence times between the 200 and 400 mg tablets. Thus, it is recommended that the DCM be used for dosage forms in which the main release phenomena take place in the distal GI tract. However, the DCM again showed a better performance based on the overall AAFE compared to the USP II. Regional dissolution profiles within the DCM cannot currently be integrated into Simcyp®, which might limit the predictivity of the DCM. Thus, further compartmentalization of the colon within PBBM platforms is required to account for observed intra-regional differences in drug distribution.

Review of the role of surfactant dynamics in drop microfluidics.

Surfactants are employed in microfluidic systems not just for drop stabilisation, but also to study local phenomena in industrial processes. On the scale of a single drop, these include foaming, emulsification and stability of foams and emulsions using statistically significant ensembles of bubbles or drops respectively. In addition, surfactants are often a part of a formulation in microfluidic drop reactors. In all these applications, surfactant dynamics play a crucial role and need to be accounted for. In this review, the effect of surfactant dynamics is considered on the level of standard microfluidic operations: drop formation, movement in channels and coalescence, but also on a more general level, considering the mechanisms controlling surfactant adsorption on time- and length-scales characteristic of microfluidics. Some examples of relevant calculations are provided. The advantages and challenges of the use of microfluidics to measure dynamic interfacial tension at short time-scales are discussed.

Comparison of low-density lipoprotein cholesterol equations in patients with dyslipidaemia receiving cholesterol ester transfer protein inhibition.

AIMS: Low-density lipoprotein (LDL-C) lowering is imperative in cardiovascular disease prevention. We aimed to compare accuracy of three clinically-implemented LDL-C equations in a clinical trial of cholesterol ester transfer protein (CETP) inhibition. METHODS AND RESULTS: Men and women aged 18-75 years with dyslipidaemia were recruited from 17 sites in the Netherlands and Denmark. Patients were randomly assigned to one of nine groups using various combinations of the CETP inhibitor TA-8995 (obicetrapib), statin therapy, and placebo. In pooled measurements over 12 weeks, we calculated LDL-C by the Friedewald, Martin/Hopkins, and Sampson equations, and compared values with preparative ultracentrifugation (PUC) LDL-C overall and with a special interest in the low LDL-C/high triglycerides subgroup. There were 242 patients contributing 921 observations. Overall median LDL-C differences between estimates and PUC were small: Friedewald, 0.00 (25th, 75th: -0.10, 0.08) mmol/L [0 (-4, 3) mg/dL]; Martin/Hopkins, 0.02 (-0.08, 0.10) mmol/L [1 (-3, 4) mg/dL]; and Sampson, 0.05 (-0.03, 0.15) mmol/L [2 (-1, 6) mg/dL]. In the subgroup with estimated LDL-C <1.8 mmol/L (<70 mg/dL) and triglycerides 1.7-4.5 mmol/L (150-399 mg/dL), the Friedewald equation underestimated LDL-C with a median difference versus PUC of -0.25 (-0.33, -0.10) mmol/L [-10 (-13, -4) mg/dL], whereas the median difference by Martin/Hopkins was 0.00 (-0.08, 0.10) mmol/L [0 (-3, 4) mg/dL] and by Sampson was -0.06 (-0.13, 0.00) mmol/L [-2 (-5, 0) mg/dL]. In this subgroup, the proportion of LDL-C observations <1.8 mmol/L (<70 mg/dL) that were correctly classified compared with PUC was 71.4% by Friedewald vs. 100.0% by Martin/Hopkins and 93.1% by Sampson. CONCLUSION: In European patients with dyslipidaemia receiving a CETP inhibitor, we found improved LDL-C accuracy using contemporary equations vs. the Friedewald equation, and the greatest accuracy was observed with the Martin/Hopkins equation. REGISTRATION: ClinicalTrials.gov, NCT01970215.

American Society for Pharmacology and Experimental Therapeutics Division for Pharmacology Education at EB2022-Meeting report.

The American Society for Pharmacology and Experimental Therapeutics (ASPET) held its annual meeting at the Experimental Biology 2022 conference in Philadelphia, PA on April 2-5, 2022. The authors provide a synopsis and discussion of each of the four sessions presented at the meeting under the ASPET Division for Pharmacology Education (DPE).

The Effect of Biorelevant Hydrodynamic Conditions on Drug Dissolution from Extended-Release Tablets in the Dynamic Colon Model.

The in vitro release of theophylline from an extended-release dosage form was studied under different hydrodynamic conditions in a United States Pharmacopoeial (USP) dissolution system II and a bespoke in vitro tubular model of the human colon, the Dynamic Colon Model (DCM). Five biorelevant motility patterns extracted from in vivo data were applied to the DCM, mimicking the human proximal colon under baseline conditions and following stimulation using polyethylene glycol or maltose; these represent the lower and upper bounds of motility normally expected in vivo. In the USPII, tablet dissolution was affected by changing hydrodynamic conditions at different agitation speeds of 25, 50 and 100 rpm. Applying different motility patterns in the DCM affected the dissolution profiles produced, with theophylline release at 24 h ranging from 56.74 ± 2.00% (baseline) to 96.74 ± 9.63% (maltose-stimulated). The concentration profiles of theophylline were markedly localized when measured at different segments of the DCM tube, highlighting the importance of a segmented lumen in intestine models and in generating spatial information to support simple temporal dissolution profiles. The results suggested that the shear stresses invoked by the unstimulated, healthy adult human colon may be lower than those in the USPII at 25 rpm and thus insufficient to achieve total release of a therapeutic compound from a hydroxyethyl cellulose matrix. When operated under stimulated conditions, drug release in the DCM was between that achieved at 25 and 50 rpm in the USPII.

Surfactant-laden droplet size prediction in a flow-focusing microchannel: a data-driven approach.

The control of droplet formation and size using microfluidic devices is a critical operation for both laboratory and industrial applications, e.g. in micro-dosage. Surfactants can be added to improve the stability and control the size of the droplets by modifying their interfacial properties. In this study, a large-scale data set of droplet size was obtained from high-speed imaging experiments conducted on a flow-focusing microchannel where aqueous surfactant-laden droplets were generated in silicone oil. Three types of surfactants were used including anionic, cationic and non-ionic at concentrations below and above the critical micelle concentration (CMC). To predict the final droplet size as a function of flow rates, surfactant type and concentration of surfactant, two data-driven models were built. Using a Bayesian regularised artificial neural network and XGBoost, these models were initially based on four inputs (flow rates of the two phases, interfacial tension at equilibrium and the normalised surfactant concentration). The mean absolute percentage errors (MAPE) show that data-driven models are more accurate (MAPE = 3.9%) compared to semi-empirical models (MAPE = 11.4%). To overcome experimental difficulties in acquiring accurate interfacial tension values under some conditions, both models were also trained with reduced inputs by removing the interfacial tension. The results show again a very good prediction of the droplet diameter. Finally, over 10 000 synthetic data were generated, based on the initial data set, with a Variational Autoencoder (VAE). The high-fidelity of the extended synthetic data set highlights that this method can be a quick and low-cost alternative to study microdroplet formation in future lab on a chip applications, where experimental data may not be readily available.

Correction: Schütt et al. Simulating the Hydrodynamic Conditions of the Human Ascending Colon: A Digital Twin of the Dynamic Colon Model. Pharmaceutics 2022, 14, 184.

In the original publication [...].

Mechanism of gelation in high nickel content cathode slurries for sodium-ion batteries.

Sodium-ion batteries are a prospective sustainable alternative to the ubiquitous lithium-ion batteries due to the abundancy of sodium, and their cobalt free cathodes. The high nickel O3-type oxides show promising energy densities, however, a time dependency in the rheological properties of the composite electrode slurries is observed, which leads to inhomogeneous coatings being produced. A combination of electron microscopy and infra-red spectroscopy were used to monitor the O3-oxide surface changes upon exposure to air, and the effect upon the rheology and stability of the inks was investigated. Upon exposure to air, NaOH rather than Na2CO3 was observed on the surfaces of the powder through FTIR and EDS. The subsequent gelation of the slurry was initiated by the NaOH and dehydrofluorination with crosslinking of PVDF was observed through the reaction product, NaF. Approximately 15% of the CF bonds in PVDF undergo this dehydrofluorination to form NaF. As observed in the relaxation time of fitted rheological data, the gelation undergoes a three-stage process: a dehydrofluorination stage, creating saturated structures, a crosslinking stage, resulting in the highest rate of gelation, and a final crosslinking stage. This work shows the mechanism for instability of high nickel containing powders and electrode slurries, and presents a new time dependent oscillatory rheology test that can be used to determine the process window for these unstable slurry systems.

Ensemble latent assimilation with deep learning surrogate model: application to drop interaction in a microfluidics device.

A major challenge in the field of microfluidics is to predict and control drop interactions. This work develops an image-based data-driven model to forecast drop dynamics based on experiments performed on a microfluidics device. Reduced-order modelling techniques are applied to compress the recorded images into low-dimensional spaces and alleviate the computational cost. Recurrent neural networks are then employed to build a surrogate model of drop interactions by learning the dynamics of compressed variables in the reduced-order space. The surrogate model is integrated with real-time observations using data assimilation. In this paper we developed an ensemble-based latent assimilation algorithm scheme which shows an improvement in terms of accuracy with respect to the previous approaches. This work demonstrates the possibility to create a reliable data-driven model enabling a high fidelity prediction of drop interactions in microfluidics device. The performance of the developed system is evaluated against experimental data (i.e., recorded videos), which are excluded from the training of the surrogate model. The developed scheme is general and can be applied to other dynamical systems.

Benefits of alignment quality-control processing steps and an Angiosperms353 phylogenomics pipeline applied to the Celastrales.

We examined the impact of successive alignment quality-control steps on downstream phylogenomic analyses. We applied a recently published phylogenomics pipeline that was developed for the Angiosperms353 target-sequence-capture probe set to the flowering plant order Celastrales. Our final dataset consists of 158 species, including at least one exemplar from all 109 currently recognized Celastrales genera. We performed nine quality-control steps and compared the inferred resolution, branch support, and topological congruence of the inferred gene and species trees with those generated after each of the first six steps. We describe and justify each of our quality-control steps, including manual masking, in detail so that they may be readily applied to other lineages. We found that highly supported clades could generally be relied upon even if stringent orthology and alignment quality-control measures had not been applied. But separate instances were identified, for both concatenation and coalescence, wherein a clade was highly supported before manual masking but then subsequently contradicted. These results are generally reassuring for broad-scale analyses that use phylogenomics pipelines, but also indicate that we cannot rely exclusively on these analyses to conclude how challenging phylogenetic problems are best resolved.

Simulating the Hydrodynamic Conditions of the Human Ascending Colon: A Digital Twin of the Dynamic Colon Model.

The performance of solid oral dosage forms targeting the colon is typically evaluated using standardised pharmacopeial dissolution apparatuses. However, these fail to replicate colonic hydrodynamics. This study develops a digital twin of the Dynamic Colon Model; a physiologically representative in vitro model of the human proximal colon. Magnetic resonance imaging of the Dynamic Colon Model verified that the digital twin robustly replicated flow patterns under different physiological conditions (media viscosity, volume, and peristaltic wave speed). During local contractile activity, antegrade flows of 0.06-0.78 cm s-1 and backflows of -2.16--0.21 cm s-1 were measured. Mean wall shear rates were strongly time and viscosity dependent although peaks were measured between 3.05-10.12 s-1 and 5.11-20.34 s-1 in the Dynamic Colon Model and its digital twin respectively, comparable to previous estimates of the USPII with paddle speeds of 25 and 50 rpm. It is recommended that viscosity and shear rates are considered when designing future dissolution test methodologies for colon-targeted formulations. In the USPII, paddle speeds >50 rpm may not recreate physiologically relevant shear rates. These findings demonstrate how the combination of biorelevant in vitro and in silico models can provide new insights for dissolution testing beyond established pharmacopeial methods.

Gene-tree misrooting drives conflicts in phylogenomic coalescent analyses of palaeognath birds.

Phylogenomic analyses of ancient rapid radiations can produce conflicting results that are driven by differential sampling of taxa and characters as well as the limitations of alternative analytical methods. We re-examine basal relationships of palaeognath birds (ratites and tinamous) using recently published datasets of nucleotide characters from 20,850 loci as well as 4301 retroelement insertions. The original studies attributed conflicting resolutions of rheas in their inferred coalescent and concatenation trees to concatenation failing in the anomaly zone. By contrast, we find that the coalescent-based resolution of rheas is premised upon extensive gene-tree estimation errors. Furthermore, retroelement insertions contain much more conflict than originally reported and multiple insertion loci support the basal position of rheas found in concatenation trees, while none were reported in the original publication. We demonstrate how even remarkable congruence in phylogenomic studies may be driven by long-branch misplacement of a divergent outgroup, highly incongruent gene trees, differential taxon sampling that can result in gene-tree misrooting errors that bias species-tree inference, and gross homology errors. What was previously interpreted as broad, robustly supported corroboration for a single resolution in coalescent analyses may instead indicate a common bias that taints phylogenomic results across multiple genome-scale datasets. The updated retroelement dataset now supports a species tree with branch lengths that suggest an ancient anomaly zone, and both concatenation and coalescent analyses of the huge nucleotide datasets fail to yield coherent, reliable results in this challenging phylogenetic context.

Luminal Fluid Motion Inside an In Vitro Dissolution Model of the Human Ascending Colon Assessed Using Magnetic Resonance Imaging.

Knowledge of luminal flow inside the human colon remains elusive, despite its importance for the design of new colon-targeted drug delivery systems and physiologically relevant in silico models of dissolution mechanics within the colon. This study uses magnetic resonance imaging (MRI) techniques to visualise, measure and differentiate between different motility patterns within an anatomically representative in vitro dissolution model of the human ascending colon: the dynamic colon model (DCM). The segmented architecture and peristalsis-like contractile activity of the DCM generated flow profiles that were distinct from compendial dissolution apparatuses. MRI enabled different motility patterns to be classified by the degree of mixing-related motion using a new tagging method. Different media viscosities could also be differentiated, which is important for an understanding of colonic pathophysiology, the conditions that a colon-targeted dosage form may be subjected to and the effectiveness of treatments. The tagged MRI data showed that the DCM effectively mimicked wall motion, luminal flow patterns and the velocities of the contents of the human ascending colon. Accurate reproduction of in vivo hydrodynamics is an essential capability for a biorelevant mechanical model of the colon to make it suitable for in vitro data generation for in vitro in vivo evaluation (IVIVE) or in vitro in vivo correlation (IVIVC). This work illustrates how the DCM provides new insight into how motion of the colonic walls may control luminal hydrodynamics, driving erosion of a dosage form and subsequent drug release, compared to traditional pharmacopeial methods.

In vivo models to evaluate ingestible devices: Present status and current trends.

Evaluation of orally ingestible devices is critical to optimize their performance early in development. Using animals as a pre-clinical tool can provide useful information on functionality, yet it is important to recognize that animal gastrointestinal physiology, pathophysiology and anatomy can differ to that in humans and that the most suitable species needs to be selected to inform the evaluation. There has been a move towards in vitro and in silico models rather than animal models in line with the 3Rs (Replacement, Reduction and Refinement) as well as the better control and reproducibility associated with these systems. However, there are still instances where animal models provide the greatest understanding. This paper provides an overview of key aspects of human gastrointestinal anatomy and physiology and compares parameters to those reported in animal species. The value of each species can be determined based upon the parameter of interest from the ingested device when considering the use of pre-clinical animal testing.

In vitro models to evaluate ingestible devices: Present status and current trends.

Orally ingestible medical devices offer significant opportunity in the diagnosis and treatment of gastrointestinal conditions. Their development necessitates the use of models that simulate the gastrointestinal environment on both a macro and micro scale. An evolution in scientific technology has enabled a wide range of in vitro, ex vivo and in vivo models to be developed that replicate the gastrointestinal tract. This review describes the landscape of the existing range of in vitro tools that are available to characterize ingestible devices. Models are presented with details on their benefits and limitations with regards to the evaluation of ingestible devices and examples of their use in the evaluation of such devices is presented where available. The multitude of models available provides a suite of tools that can be used in the evaluation of ingestible devices that should be selected on the functionality of the device and the mechanism of its function.

Modelling and Simulation of the Drug Release from a Solid Dosage Form in the Human Ascending Colon: The Influence of Different Motility Patterns and Fluid Viscosities.

For colonic drug delivery, the ascending part of the colon is the most favourable site as it offers the most suitable environmental conditions for drug dissolution. Commonly, the performance of a drug formulation is assessed using standardised dissolution apparatus, which does not replicate the hydrodynamics and shear stress evoked by wall motion in the colon. In this work, computer simulations are used to analyse and understand the influence of different biorelevant motility patterns on the disintegration/drug release of a solid dosage form (tablet) under different fluid conditions (viscosities) to mimic the ascending colonic environment. Furthermore, the ability of the motility pattern to distribute the drug in the ascending colon luminal environment is analysed to provide data for a spatiotemporal concentration profile. The motility patterns used are derived from in vivo data representing different motility patterns in the human ascending colon. The applied motility patterns show considerable differences in the drug release rate from the tablet, as well as in the ability to distribute the drug along the colon. The drug dissolution/disintegration process from a solid dosage form is primarily influenced by the hydrodynamic and shear stress it experiences, i.e., a combination of motility pattern and fluid viscosity. Reduced fluid motion leads to a more pronounced influence of diffusion in the tablet dissolution process. The motility pattern that provoked frequent single shear stress peaks seemed to be more effective in achieving a higher drug release rate. The ability to simulate drug release profiles under biorelevant colonic environmental conditions provides valuable feedback to better understand the drug formulation and how this can be optimised to ensure that the drug is present in the desired concentration within the ascending colon.

Collapsing dubiously resolved gene-tree branches in phylogenomic coalescent analyses.

In two-step coalescent analyses of phylogenomic data, gene-tree topologies are treated as fixed prior to species-tree inference. Although all gene-tree conflict is assumed to be caused by lineage sorting when applying these methods, in empirical datasets much of the conflict can be caused by estimation error. Weakly supported and even arbitrarily resolved clades are important sources of this estimation error for gene trees inferred from few informative characters relative to the number of sampled terminals, and the resulting extraneous conflict among gene trees can negatively impact species-tree inference. In this study, we quantified the relative severity of alternative methods for collapsing gene-tree branches for seven empirical datasets and quantified their effects on species-tree inference. The branch-collapsing methods that we employed were based on the strict consensus of optimal topologies, various bootstrap thresholds, and 0% approximate likelihood ratio test (SH-like aLRT) support. Up to 86% of internal gene-tree branches are dubiously or arbitrarily resolved in reanalyses of these published phylogenomic datasets, and collapsing these branches increased inferred species-tree coalescent branch lengths by up to 455%. For two datasets, the longer inferred branch lengths sometimes impacted inference of anomaly-zone conditions. Although branch-collapsing methods did not consistently affect the species-tree topology, they often increased branch support. The more severe and clearly justified gene-tree branch-collapsing methods, which we recommend be broadly applied for two-step coalescent analyses, are use of the strict consensus in parsimony analyses and the collapse clades with 0% SH-like aLRT support in likelihood analyses. Collapsing dubiously or arbitrarily resolved branches in gene trees sometimes improved congruence between coalescent-based results and concatenation trees. In such cases, we contend that the resolution provided by concatenation should be preferred and that incomplete lineage sorting is a poor explanation for the initial conflict between phylogenetic approaches.