Structural Analysis to Determine the Core of Hypoxia Response Network

The advent of sophisticated molecular biology techniques allows to deduce the structure of complex biological networks. However, networks tend to be huge and impose computational challenges on traditional mathematical analysis due to their high dimension and lack of reliable kinetic data. To overcome this problem, complex biological networks are decomposed into modules that are assumed to capture essential aspects of the full network''s dynamics. The question that begs for an answer is how to identify the core that is representative of a network''s dynamics, its function and robustness. One of the powerful methods to probe into the structure of a network is Petri net analysis. Petri nets support network visualization and execution. They are also equipped with sound mathematical and formal reasoning based on which a network can be decomposed into modules. The structural analysis provides insight into the robustness and facilitates the identification of fragile nodes. The application of these techniques to a previously proposed hypoxia control network reveals three functional modules responsible for degrading the hypoxia-inducible factor (HIF). Interestingly, the structural analysis identifies superfluous network parts and suggests that the reversibility of the reactions are not important for the essential functionality. The core network is determined to be the union of the three reduced individual modules. The structural analysis results are confirmed by numerical integration of the differential equations induced by the individual modules as well as their composition. The structural analysis leads also to a coarse network structure highlighting the structural principles inherent in the three functional modules. Importantly, our analysis identifies the fragile node in this robust network without which the switch-like behavior is shown to be completely absent.     

The Role of the Neuronal Network in Functional Evolution of the Mammalian Telencephalon

During evolution of the vertebrate telencephalon the analyzing-synthesizing function was divided between two structures: the screen one, optimal for mechanisms of discrete analysis of information, and the neuronal network, in which cortical, functionally specialized modules can create the generalized equivalent of their activity. In the screen and reticular structures, each of these mechanisms got a possibility of developing independently without restricting functional capabilities of the other one. This resulted in formation of two telencephalon structures developing in parallel and functionally related, the cortex and the neostriatum. Experimental data indicate that the neuronal network of neostriatum is a field for interaction of corticofugal signals. These signals form neuronal mosaics reflecting the dynamics of cortical activity as combination patterns. Thereby, in neostriatum, corticofugal signals spread over a large surface of the cortex are transformed into their three-dimensional equivalent similar to population coding of information that takes place in the brain sensory structures. The established system of interrelationships between the cortex and the neostriatum turned out to be rather universal and economic. As a result, a broad spectrum of functional brain capabilities that we can see in various representatives of mammals was formed during a relatively short time with the minimum of structural changes, mainly quantitative in character.     

Origin and Evolution of the Self-Organizing Cytoskeleton in the Network of Eukaryotic Organelles

The eukaryotic cytoskeleton evolved from prokaryotic cytomotive filaments. Prokaryotic filament systems show bewildering structural and dynamic complexity and, in many aspects, prefigure the self-organizing properties of the eukaryotic cytoskeleton. Here, the dynamic properties of the prokaryotic and eukaryotic cytoskeleton are compared, and how these relate to function and evolution of organellar networks is discussed. The evolution of new aspects of filament dynamics in eukaryotes, including severing and branching, and the advent of molecular motors converted the eukaryotic cytoskeleton into a self-organizing “active gel,” the dynamics of which can only be described with computational models. Advances in modeling and comparative genomics hold promise of a better understanding of the evolution of the self-organizing cytoskeleton in early eukaryotes, and its role in the evolution of novel eukaryotic functions, such as amoeboid motility, mitosis, and ciliary swimming.The eukaryotic cytoskeleton organizes space on the cellular scale and this organization influences almost every process in the cell. Organization depends on the mechanochemical properties of the cytoskeleton that dynamically maintain cell shape, position organelles, and macromolecules by trafficking, and drive locomotion via actin-rich cellular protrusions, ciliary beating, or ciliary gliding. The eukaryotic cytoskeleton is best described as an “active gel,” a cross-linked network of polymers (gel) in which many of the links are active motors that can move the polymers relative to each other (Karsenti et al. 2006). Because prokaryotes have only cytoskeletal polymers but lack motor proteins, this “active gel” property clearly sets the eukaryotic cytoskeleton apart from prokaryotic filament systems.Prokaryotes contain elaborate systems of several cytomotive filaments (Löwe and Amos 2009) that share many structural and dynamic features with eukaryotic actin filaments and microtubules (Löwe and Amos 1998; van den Ent et al. 2001). Prokaryotic cytoskeletal filaments may trace back to the first cells and may have originated as higher-order assemblies of enzymes (Noree et al. 2010; Barry and Gitai 2011). These cytomotive filaments are required for the segregation of low copy number plasmids, cell rigidity and cell-wall synthesis, cell division, and occasionally the organization of membranous organelles (Komeili et al. 2006; Thanbichler and Shapiro 2008; Löwe and Amos 2009). These functions are performed by dynamic filament-forming systems that harness the energy from nucleotide hydrolysis to generate forces either via bending or polymerization (Löwe and Amos 2009; Pilhofer and Jensen 2013). Although the identification of actin and tubulin homologs in prokaryotes is a major breakthrough, we are far from understanding the origin of the structural and dynamic complexity of the eukaryotic cytoskeleton.Advances in genome sequencing and comparative genomics now allow a detailed reconstruction of the cytoskeletal components present in the last common ancestor of eukaryotes. These studies all point to an ancestrally complex cytoskeleton, with several families of motors (Wickstead and Gull 2007; Wickstead et al. 2010) and filament-associated proteins and other regulators in place (Jékely 2003; Richards and Cavalier-Smith 2005; Rivero and Cvrcková 2007; Chalkia et al. 2008; Eme et al. 2009; Fritz-Laylin et al. 2010; Eckert et al. 2011; Hammesfahr and Kollmar 2012). Genomic reconstructions and comparative cell biology of single-celled eukaryotes (Raikov 1994; Cavalier-Smith 2013) allow us to infer the cellular features of the ancestral eukaryote. These analyses indicate that amoeboid motility (Fritz-Laylin et al. 2010; although, see Cavalier-Smith 2013), cilia (Cavalier-Smith 2002; Mitchell 2004; Jékely and Arendt 2006; Satir et al. 2008), centrioles (Carvalho-Santos et al. 2010), phagocytosis (Cavalier-Smith 2002; Jékely 2007; Yutin et al. 2009), a midbody during cell division (Eme et al. 2009), mitosis (Raikov 1994), and meiosis (Ramesh et al. 2005) were all ancestral eukaryotic cellular features. The availability of functional information from organisms other than animals and yeasts (e.g., Chlamydomonas, Tetrahymena, Trypanosoma) also allow more reliable inferences about the ancestral functions of cytoskeletal components (i.e., not only their ancestral presence or absence) and their regulation (Demonchy et al. 2009; Lechtreck et al. 2009; Suryavanshi et al. 2010).The ancestral complexity of the cytoskeleton in eukaryotes leaves a huge gap between prokaryotes and the earliest eukaryote we can reconstruct (provided that our rooting of the tree is correct) (Cavalier-Smith 2013). Nevertheless, we can attempt to infer the series of events that happened along the stem lineage, leading to the last common ancestor of eukaryotes. Meaningful answers will require the use of a combination of gene family history reconstructions (Wickstead and Gull 2007; Wickstead et al. 2010), transition analyses (Cavalier-Smith 2002), and computer simulations relevant to cell evolution (Jékely 2008).     

Heterogeneity in the Frequency and Characteristics of Homologous Recombination in Pneumococcal Evolution

The bacterium Streptococcus pneumoniae (pneumococcus) is one of the most important human bacterial pathogens, and a leading cause of morbidity and mortality worldwide. The pneumococcus is also known for undergoing extensive homologous recombination via transformation with exogenous DNA. It has been shown that recombination has a major impact on the evolution of the pathogen, including acquisition of antibiotic resistance and serotype-switching. Nevertheless, the mechanism and the rates of recombination in an epidemiological context remain poorly understood. Here, we proposed several mathematical models to describe the rate and size of recombination in the evolutionary history of two very distinct pneumococcal lineages, PMEN1 and CC180. We found that, in both lineages, the process of homologous recombination was best described by a heterogeneous model of recombination with single, short, frequent replacements, which we call micro-recombinations, and rarer, multi-fragment, saltational replacements, which we call macro-recombinations. Macro-recombination was associated with major phenotypic changes, including serotype-switching events, and thus was a major driver of the diversification of the pathogen. We critically evaluate biological and epidemiological processes that could give rise to the micro-recombination and macro-recombination processes.     

Comparative Genomic and Phylogenetic Analyses Reveal the Evolution of the Core Two-Component Signal Transduction Systems in Enterobacteria

The two-component signal transduction system (TCST) consists of a histidine kinase (HK) and a response regulator (RR). TCSTs play important roles in sensing and reacting to environmental changes, and in bacterial pathogenesis. Previously, we have identified and characterized TCSTs in Erwinia amylovora, a severe plant enterobacterial pathogen, at genome-wide level. Here we conducted a comparative genomic analysis of TCSTs in 53 genomes of 16 enterobacterial species. These species include important plant, animal, human, and insect pathogenic, saprophytic or symbiotic microorganisms. Comparative genomic analysis revealed that enterobacteria contain eight pairs of core TCSTs. Phylogenetic trees reconstructed from a concatenation of the core set of TCSTs from enterobacteria and for individual TCST proteins from species in Proteobacteria showed that most TCST protein trees in the Enterobacteriaceae or in species of the γ-Proteobacteria agreed well with that of the corresponding 16S rRNA gene. It also showed that co-evolutionary relationships existed between cognate partners of the HKs and RRs. Several core TCSTs were quite ancient and universal based on phylogenomic analysis of protein structures. These results indicate that the core TCSTs are relatively conserved, and suggest that these enterobacteria may have maintained their ancient core TCSTs and might acquire specific new TCSTs for their survival in different environments or hosts, or may have evolved new functionalities of the core TCSTs for adaptation to different ecological niches.     

Gene Promoter Evolution Targets the Center of the Human Protein Interaction Network

Assessing the contribution of promoters and coding sequences to gene evolution is an important step toward discovering the major genetic determinants of human evolution. Many specific examples have revealed the evolutionary importance of cis-regulatory regions. However, the relative contribution of regulatory and coding regions to the evolutionary process and whether systemic factors differentially influence their evolution remains unclear. To address these questions, we carried out an analysis at the genome scale to identify signatures of positive selection in human proximal promoters. Next, we examined whether genes with positively selected promoters (Prom⁺ genes) show systemic differences with respect to a set of genes with positively selected protein-coding regions (Cod⁺ genes). We found that the number of genes in each set was not significantly different (8.1% and 8.5%, respectively). Furthermore, a functional analysis showed that, in both cases, positive selection affects almost all biological processes and only a few genes of each group are located in enriched categories, indicating that promoters and coding regions are not evolutionarily specialized with respect to gene function. On the other hand, we show that the topology of the human protein network has a different influence on the molecular evolution of proximal promoters and coding regions. Notably, Prom⁺ genes have an unexpectedly high centrality when compared with a reference distribution (P = 0.008, for Eigenvalue centrality). Moreover, the frequency of Prom⁺ genes increases from the periphery to the center of the protein network (P = 0.02, for the logistic regression coefficient). This means that gene centrality does not constrain the evolution of proximal promoters, unlike the case with coding regions, and further indicates that the evolution of proximal promoters is more efficient in the center of the protein network than in the periphery. These results show that proximal promoters have had a systemic contribution to human evolution by increasing the participation of central genes in the evolutionary process.     

Evolution of the VEGF-Regulated Vascular Network from a Neural Guidance System

The vascular network is closely linked to the neural system, and an interdependence is displayed in healthy and in pathophysiological responses. How has close apposition of two such functionally different systems occurred? Here, we present a hypothesis for the evolution of the vascular network from an ancestral neural guidance system. Biological cornerstones of this hypothesis are the vascular endothelial growth factor (VEGF) protein family and cognate receptors. The primary sequences of such proteins are conserved from invertebrates, such as worms and flies that lack discernible vascular systems compared to mammals, but all these systems have sophisticated neuronal wiring involving such molecules. Ancestral VEGFs and receptors (VEGFRs) could have been used to develop and maintain the nervous system in primitive eukaryotes. During evolution, the demands of increased morphological complexity required systems for transporting molecules and cells, i.e., biological conductive tubes. We propose that the VEGF–VEGFR axis was subverted by evolution to mediate the formation of biological tubes necessary for transport of fluids, e.g., blood. Increasingly, there is evidence that aberrant VEGF-mediated responses are also linked to neuronal dysfunctions ranging from motor neuron disease, stroke, Parkinson’s disease, Alzheimer’s disease, ischemic brain disease, epilepsy, multiple sclerosis, and neuronal repair after injury, as well as common vascular diseases (e.g., retinal disease). Manipulation and correction of the VEGF response in different neural tissues could be an effective strategy to treat different neurological diseases.     

Evolution of Cooperation on Spatial Network with Limited Resource

Considering the external resource offered by environment is limited, here, we will explore the cooperation on spatial networks with limited resource. The individual distributes the limited resource according to the payoffs acquired in games, and one with resource amounts is lower than critical survival resource level will be replaced by the offspring of its neighbors. We find that, for larger temptation to defect, the number of the dead decreases with the resource amount. However the cooperation behavior is interesting, the lower total resource and intermediate temptation to defect can greatly promote the cooperation on square lattice. Our result reveals that the limited resource contributes most to the cooperation.     

Evolution of the Core Genome of Pseudomonas syringae, a Highly Clonal, Endemic Plant Pathogen

Pseudomonas syringae is a common foliar bacterium responsible for many important plant diseases. We studied the population structure and dynamics of the core genome of P. syringae via multilocus sequencing typing (MLST) of 60 strains, representing 21 pathovars and 2 nonpathogens, isolated from a variety of plant hosts. Seven housekeeping genes, dispersed around the P. syringae genome, were sequenced to obtain 400 to 500 nucleotides per gene. Forty unique sequence types were identified, with most strains falling into one of four major clades. Phylogenetic and maximum-likelihood analyses revealed a remarkable degree of congruence among the seven genes, indicating a common evolutionary history for the seven loci. MLST and population genetic analyses also found a very low level of recombination. Overall, mutation was found to be approximately four times more likely than recombination to change any single nucleotide. A skyline plot was used to study the demographic history of P. syringae. The species was found to have maintained a constant population size over time. Strains were also found to remain genetically homogeneous over many years, and when isolated from sites as widespread as the United States and Japan. An analysis of molecular variance found that host association explains only a small proportion of the total genetic variation in the sample. These analyses reveal that with respect to the core genome, P. syringae is a highly clonal and stable species that is endemic within plant populations, yet the genetic variation seen in these genes only weakly predicts host association.     

Temporal Evolution of MRI Characteristics in Dogs with Collagenase-Induced Intracerebral Hemorrhage

Intracerebral hemorrhage (ICH) is one of the most lethal types of stroke. Neuroimaging techniques, particularly MRI, have improved the diagnostic accuracy of ICH. The MRI characteristics of the evolving stages of ICH in humans—but not those in dogs—have been described. In this study, we document the temporal MRI characteristics in a canine model of collagenase-induced ICH. Specifically, ICH was induced in 5 healthy beagles by injecting 500 U of bacterial collagenase from Clostridium histolyticum, which was delivered into the parietal lobe over 5 min by using a microinfusion pump. T1- and T2-weighted, fluid-attenuated inversion recovery, gradient-echo (GRE), and diffusion-weighted (DWI) imaging and measurement of the apparent diffusion coefficient (ADC) were performed serially at 6 different time points (before and 12 h, 3 d, 5 d, 10 d and 24 d after hemorrhage) by using a 3-T MR system. The temporal changes of T1 signal intensity (SI) corresponded well with the reported human data. The temporal changes of T2 and GRE sequences, with the exception of T2 and GRE hyperintensities at the early subacute stage, also matched. ADC measurements were high at the early subacute stage, and DWI-SI positively correlated with T2- and GRE-SI from the early subacute stage onward. In conclusion, MRI is an ideal method for characterizing the temporal evolution of parenchymal alterations after ICH in dogs. These data might be useful for differentiating clinical stages of ICH in dogs.Abbreviations: ADC, apparent diffusion coefficient; DWI, diffusion-weighted imaging; FLAIR, fluid attenuation inversion recovery; GRE, gradient echo; ICH, intracerebral hemorrhage; ROI, region of interest; SIR, signal intensity ratio; WI, weighted imagingIntracerebral hemorrhage (ICH) occurs in 15% to 20% of all stroke patients.¹⁰ In comparison with ischemic stroke, patients with ICH are at higher risk of death and long-term functional disability.¹⁰ Most survivors remain disabled, owing to the hematoma within the brain parenchyma, which can cause severe neurologic deficits.Because of the rapid progression of brain damage during the first hours after ICH, quick recognition and diagnosis are key. Clinical signs are helpful for early diagnosis but are insufficient for the differentiation of ICH from other stroke subtypes. Brain imaging techniques, including CT and MRI, have helped improve the accuracy of diagnosis, which is necessary for the appropriate treatment of acute cerebrovascular accidents.⁵ Previously, MRI was considered unsuitable for detecting early-stage hemorrhage. However, MRI recently was shown to have high sensitivity for detecting hyperacute ICH, superior even to CT.²¹ MRI is now considered the ideal imaging modality for characterizing the temporal and spatial evolution of parenchymal changes after ICH.³⁰The MRI characteristics of ICH vary with the duration of the hematoma, the type of MRI sequence, and various biologic factors.¹⁷ The several forms of hemoglobin (oxyhemoglobin, deoxyhemoglobin, and methemoglobin), which have different magnetic properties, are observed at different times points during hemorrhage, depending on whether they contain unpaired electrons.²⁸ The MR signal intensity (SI) of hemorrhage has been reported for various animal models, from in vitro studies, and during clinical observations.^2,6,12,24 Reflecting the breakdown products of hemoglobin, the MRI features of 5 distinctive stages of ICH have been reported in humans: hyperacute (within 24 h of hemorrhage; intracellular oxyhemoglobin; long T1 and T2 values; iso- to hypointense on T1-weighted images [WI], hyperintense on T2WI); acute (1 to 3 d; intracellular deoxyhemoglobin; long T1, short T2 values; hypointense on T1WI, hypointense on T2WI); early subacute (3 to 7 d; intracellular methemoglobin with intact erythrocyte; short T1 and T2 values; hyperintense on T1WI, hypointense on T2WI); late subacute (7 to 14 d; extracellular methemoglobin with erythrocyte lysis; short T1, long T2 values; hyperintense on T1WI and T2WI); and chronic (after 14 d; ferritin and hemosiderin; long T1, short T2 values; hypointense on T1WI and T2WI).⁴So far, very few clinical studies have assessed the time-dependent evaluation of MRI patterns beyond 24 h in dogs.²³ The clinical setting presents several difficulties to the study of ICH. Because ICH patients are often critically ill, requiring physiologic support, most patients with ICH are unsuitable for MRI due to their medical instability.¹⁵ In dogs, it is frequently impossible to ascertain the precise interval between hemorrhage and MRI scanning. An animal model offers several advantages for studying ICH: histologic analysis in survivors of ICH, the initial testing of novel interventions, homogeneous experimental groups, and a predictable onset of ICH.²⁷An experimental animal model used in human medicine should exhibit certain characteristics, such as ease of standardization and reproducibility, and representation of the principal mechanisms associated with the particular condition in humans.⁸ Small-animal (for example, mice, rats, gerbils) and large-animal (for example, cats, dogs, pigs, sheep, monkeys) models that demonstrate these characteristics have been developed. Although small animals are often more cost-effective and allow for relatively simpler genetic manipulation and management, the use of large-animal models is important in preclinical studies of ICH because these animals have gyrencephalic brains with well-developed white matter that are structurally and functionally similar to human brains.¹⁶ Notably, numerous experimental treatment strategies have been evaluated successfully in rodent models and in vitro, but the vast majority of such modalities subsequently have failed in clinical trials.¹⁸ For all of these reasons, the Stroke Therapy Academic Industry Roundtable strongly recommends the use of appropriate large-animal models of stroke.¹⁹ Among large animals, dogs are readily and economically available, easy to care for, and have predictable intercurrent diseases.Presently, MRI of the brain is extremely useful in confirming stroke, determining the extent of the lesion, and distinguishing between ischemic and hemorrhagic stroke. However, MRI findings of canine ICH are largely based on results from human studies, given the paucity of relevant canine studies. A previous study demonstrated that the time course of ICH stages is much faster in rats than in humans.³ Therefore, we hypothesized that the temporal MRI characteristics of evolving stages of canine ICH differ from those of ICH in humans.Advanced MRI techniques may enable clarification of mechanisms that mediate injury after ICH. Diffusion-weighted imaging (DWI) has already proven useful in the diagnosis and investigation of the natural history of ischemic stroke.⁷ However, the usefulness of those techniques to assess mechanisms of neuronal injury after ICH remains a topic of debate, both in humans and in dogs. Therefore, the purpose of the current study was to evaluate the utility of advanced MRI techniques, including DWI, in the diagnosis of canine ICH, by monitoring the temporal changes in MR images relative to the stage of hematoma in affected dogs.     

Changes throughout a Genetic Network Mask the Contribution of Hox Gene Evolution

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Facebook Use Predicts Declines in Subjective Well-Being in Young Adults

Over 500 million people interact daily with Facebook. Yet, whether Facebook use influences subjective well-being over time is unknown. We addressed this issue using experience-sampling, the most reliable method for measuring in-vivo behavior and psychological experience. We text-messaged people five times per day for two-weeks to examine how Facebook use influences the two components of subjective well-being: how people feel moment-to-moment and how satisfied they are with their lives. Our results indicate that Facebook use predicts negative shifts on both of these variables over time. The more people used Facebook at one time point, the worse they felt the next time we text-messaged them; the more they used Facebook over two-weeks, the more their life satisfaction levels declined over time. Interacting with other people “directly” did not predict these negative outcomes. They were also not moderated by the size of people''s Facebook networks, their perceived supportiveness, motivation for using Facebook, gender, loneliness, self-esteem, or depression. On the surface, Facebook provides an invaluable resource for fulfilling the basic human need for social connection. Rather than enhancing well-being, however, these findings suggest that Facebook may undermine it.     

Clique Size and Network Characteristics in Hyperlink Cinema

Hyperlink cinema is an emergent film genre that seeks to push the boundaries of the medium in order to mirror contemporary life in the globalized community. Films in the genre thus create an interacting network across space and time in such a way as to suggest that people’s lives can intersect on scales that would not have been possible without modern technologies of travel and communication. This allows us to test the hypothesis that new kinds of media might permit us to break through the natural cognitive constraints that limit the number and quality of social relationships we can manage in the conventional face-to-face world. We used network analysis to test this hypothesis with data from 12 hyperlink films, using 10 motion pictures from a more conventional film genre as a control. We found few differences between hyperlink cinema films and the control genre, and few differences between hyperlink cinema films and either the real world or classical drama (e.g., Shakespeare’s plays). Conversation group size seems to be especially resilient to alteration. It seems that, despite many efficiency advantages, modern media are unable to circumvent the constraints imposed by our evolved psychology.     

Characteristics of Misclassified CT Perfusion Ischemic Core in Patients with Acute Ischemic Stroke

Background

CT perfusion (CTP) is used to estimate the extent of ischemic core and penumbra in patients with acute ischemic stroke. CTP reliability, however, is limited. This study aims to identify regions misclassified as ischemic core on CTP, using infarct on follow-up noncontrast CT. We aim to assess differences in volumetric and perfusion characteristics in these regions compared to areas that ended up as infarct on follow-up.

Materials and Methods

This study included 35 patients with >100 mm brain coverage CTP. CTP processing was performed using Philips software (IntelliSpace 7.0). Final infarct was automatically segmented on follow-up noncontrast CT and used as reference. CTP and follow-up noncontrast CT image data were registered. This allowed classification of ischemic lesion agreement (core on CTP: rMTT≥145%, aCBV<2.0 ml/100g and infarct on follow-up noncontrast CT) and misclassified ischemic core (core on CTP, not identified on follow-up noncontrast CT) regions. False discovery ratio (FDR), defined as misclassified ischemic core volume divided by total CTP ischemic core volume, was calculated. Absolute and relative CTP parameters (CBV, CBF, and MTT) were calculated for both misclassified CTP ischemic core and ischemic lesion agreement regions and compared using paired rank-sum tests.

Results

Median total CTP ischemic core volume was 49.7ml (IQR:29.9ml-132ml); median misclassified ischemic core volume was 30.4ml (IQR:20.9ml-77.0ml). Median FDR between patients was 62% (IQR:49%-80%). Median relative mean transit time was 243% (IQR:198%-289%) and 342% (IQR:249%-432%) for misclassified and ischemic lesion agreement regions, respectively. Median absolute cerebral blood volume was 1.59 (IQR:1.43–1.79) ml/100g (P<0.01) and 1.38 (IQR:1.15–1.49) ml/100g (P<0.01) for misclassified ischemic core and ischemic lesion agreement, respectively. All CTP parameter values differed significantly.

Conclusion

For all patients a considerable region of the CTP ischemic core is misclassified. CTP parameters significantly differed between ischemic lesion agreement and misclassified CTP ischemic core, suggesting that CTP analysis may benefit from revisions.