Neuro-evolutionary evidence for a universal fractal primate brain shape.

The cerebral cortex displays a bewildering diversity of shapes and sizes across and within species. Despite this diversity, we present a universal multi-scale description of primate cortices. We show that all cortical shapes can be described as a set of nested folds of different sizes. As neighbouring folds are gradually merged, the cortices of 11 primate species follow a common scale-free morphometric trajectory, that also overlaps with over 70 other mammalian species. Our results indicate that all cerebral cortices are approximations of the same archetypal fractal shape with a fractal dimension of df = 2.5. Importantly, this new understanding enables a more precise quantification of brain morphology as a function of scale. To demonstrate the importance of this new understanding, we show a scale-dependent effect of ageing on brain morphology. We observe a more than fourfold increase in effect size (from two standard deviations to eight standard deviations) at a spatial scale of approximately 2 mm compared to standard morphological analyses. Our new understanding may, therefore, generate superior biomarkers for a range of conditions in the future.

Many of the brain's essential functions ­ from decision-making to movement ­ take place in its outer layer known as the cerebral cortex. The shape of the cerebral cortex varies significantly between species. For instance, in humans, it is folded in to grooves and ridges, whereas in other animals, including mice, it is completely smooth. The structure of the cortex can also differ within a species, and be altered by aging and certain diseases. This vast variation can make it difficult it to characterize and compare the structure of the cortex between different species, ages and diseases. To address this, Wang et al. developed a new mathematical model for describing the shape of the cortex. The model uses a method known as coarse graining to erase, or 'melt away', any cortical folds or structures smaller than a given threshold size. As this threshold increases, the cortex becomes progressively smoother. The relationship between surface areas and threshold sizes indicates the fractal dimension ­ that is, how fragmented the cortex is across different scales. Wang et al. applied their model to the brain scans of eleven primates, including humans, and found the fractal dimension of the cortex was almost exactly 2.5 for all eleven species. This suggests that the cortices of the different primates follow a single fractal shape, which means the folds of each cortex have a similar branching pattern. Although there were distinctions between the species, they were mainly due to the different ranges of fold sizes in each cortex. The model revealed that the broader the range of fold sizes, the more folded the brain ­ but the fractal pattern remains the same. The brain melting method created by Wang et al. provides a new way to characterise cortical shape. Besides revealing a hitherto hidden regularity of nature, they hope that in the future their new method will be useful in assessing brain changes during human development and ageing, and in diseases like Alzheimer's and epilepsy.

Correction: Hierarchical growth in neural networks structure: Organizing inputs by Order of Hierarchical Complexity.

[This corrects the article DOI: 10.1371/journal.pone.0290743.].

Isolation and In Vitro Biological Evaluation of Triterpenes from Salacia grandifolia Leaves.

Salacia grandifolia is naturally found in the Atlantic Forest regions of Brazil. Despite the pharmacological potential of plants from the Salacia genus, phytochemical studies on this species have not been reported in literature. A new triterpene, 28-hydroxyfriedelane-3,15-dione (1), and seven known compounds (friedelan-3-one (2), friedelan-3ß-ol (3), friedelane-3,15-dione (4), 15α-hydroxyfriedelan-3-one (5), 28-hydroxyfriedelan-3-one (6), 30-hydroxyfriedelan-3-one (7), and 29-hydroxyfriedelan-3-one (8)) were obtained from the hexane extract of Salacia grandifolia leaves. These isolated compounds and three extracts, hexane (EH), chloroform (EC), and ethyl acetate (EAE), were assessed for their potential biological activities, which consisted in the evaluation of antiviral activity against a murine coronavirus, mouse hepatitis virus 3 (MHV-3), antibacterial activity against the susceptible and methicillin-resistant Staphylococcus aureus (MRSA), and antileukemia activity against the THP-1 and K-562 cell lines. The extracts EH and EAE along with the triterpenes 1 and 6 exhibited moderate to high antiviral activity, with emphasis on 6, which presented an EC50 value of 2.9 ± 0.3 µM. None of the compounds presented antibacterial activity against the tested strains. The evaluated compounds 1, 4, 6 and 7 exhibited low cytotoxic activity against the tested leukemia cell lines. Taken together, this study comprises an overview for the potential of the Salacia grandifolia biological activities, including a new isolated triterpene.

Anatomical and volumetric description of the guiana dolphin (Sotalia guianensis) brain from an ultra-high-field magnetic resonance imaging.

The Guiana dolphin (Sotalia guianensis) is a common species along Central and South American coastal waters. Although much effort has been made to understand its behavioral ecology and evolution, very little is known about its brain. The use of ultra-high field MRI in anatomical descriptions of cetacean brains is a very promising approach that is still uncommon. In this study, we present for the first time a full anatomical description of the Guiana dolphin's brain based on high-resolution ultra-high-field magnetic resonance imaging, providing an exceptional level of brain anatomical details, and enriching our understanding of the species. Brain structures were labeled and volumetric measurements were delineated for many distinguishable structures, including the gray matter and white matter of the cerebral cortex, amygdala, hippocampus, superior and inferior colliculi, thalamus, corpus callosum, ventricles, brainstem and cerebellum. Additionally, we provide the surface anatomy of the Guiana dolphin brain, including the labeling of main sulci and gyri as well as the calculation of its gyrification index. These neuroanatomical data, absent from the literature to date, will help disentangle the history behind cetacean brain evolution and consequently, mammalian evolution, representing a significant new source for future comparative studies.

Folding of the cerebellar cortex is clade-specific in form but universal in degree.

Like the cerebralcortex, the surface of the cerebellum is repeatedly folded. Unlike the cerebralcortex, however, cerebellar folds are much thinner and more numerous; repeatthemselves largely along a single direction, forming accordion-like folds transverseto the mid-sagittal plane; and occur in all but the smallest cerebella. We haveshown previously that while the location of folds in mammalian cerebral cortex isclade-specific, the overall degree of folding strictly follows a universalpower law relating cortical thickness and the exposed and total surface areas predictedfrom the minimization of the effective free energy of an expanding, self-avoidingsurface of a certain thickness. Here we show that this scaling law extends tothe folding of the mid-sagittal sections of the cerebellum of 53 speciesbelonging to six mammalian clades. Simultaneously, we show that each clade hasa previously unsuspected distinctive spatial pattern of folding evident at themid-sagittal surface of the cerebellum. We note, however, that the mammaliancerebellum folds as a multi-fractal object, because of the difference betweenthe outside-in development of the cerebellar cortex around a preexisting coreof already connected white matter, compared to the inside-out development ofthe cerebral cortex with a white matter volume that develops as the cerebralcortex itself gains neurons. We conclude that repeated folding, one of the mostrecognizable features of biology, can arise simply from the interplay betweenthe universal applicability of the physics of self-organization and biological,phylogenetical clade-specific contingency, without the need for invokingselective pressures in evolution.

Biomechanics of transduction by mechanosensory cilia for prey detection in aquatic organisms.

Surface-feeding aquatic animals navigate towards the source of water disturbances and must differentiate prey from other environmental stimuli. Medicinal leeches locate prey, in part, using a distribution of mechanosensory hairs along their body that deflect under fluid flow. Leech's behavioral responses to surface wave temporal frequency are well documented. However, a surface wave's temporal frequency depends on many underlying environmental and fluid properties that vary substantially in natural habitats (e.g., water depth, temperature). The impact of these variables on neural response and behavior is unknown. Here, we developed a physics-based leech mechanosensor model to examine the impact of environmental and fluid properties on neural response. Our model used the physical properties of a leech cilium and was verified against existing behavioral and electrophysiological data. The model's peak response occurred with waves where the effects of gravity and surface tension were nearly equal (i.e., the phase velocity minimum). This suggests that preferred stimuli are related to the interaction between fundamental properties of the surrounding medium and the mechanical properties of the sensor. This interaction likely tunes the sensor to detect the nondispersive components of the signal, filtering out irrelevant ambient stimuli, and may be a general property of cilia across the animal kingdom.

Machine Learning-Based Virtual Screening of Antibacterial Agents against Methicillin-Susceptible and Resistant Staphylococcus aureus.

The application of computer-aided drug discovery (CADD) approaches has enabled the discovery of new antimicrobial therapeutic agents in the past. The high prevalence of methicillin-resistantStaphylococcus aureus(MRSA) strains promoted this pathogen to a high-priority pathogen for drug development. In this sense, modern CADD techniques can be valuable tools for the search for new antimicrobial agents. We employed a combination of a series of machine learning (ML) techniques to select and evaluate potential compounds with antibacterial activity against methicillin-susceptible S. aureus (MSSA) and MRSA strains. In the present study, we describe the antibacterial activity of six compounds against MSSA and MRSA reference (American Type Culture Collection (ATCC)) strains as well as two clinical strains of MRSA. These compounds showed minimal inhibitory concentrations (MIC) in the range from 12.5 to 200 µM against the different bacterial strains evaluated. Our results constitute relevant proven ML-workflow models to distinctively screen for novel MRSA antibiotics.

Cortical folding correlates to aging and Alzheimer's Disease's cognitive and CSF biomarkers.

This manuscript presents the quantification and correlation of three aspects of Alzheimer's Disease evolution, including structural, biochemical, and cognitive assessments. We aimed to test a novel structural biomarker for neurodegeneration based on a cortical folding model for mammals. Our central hypothesis is that the cortical folding variable, representative of axonal tension in white matter, is an optimal discriminator of pathological aging and correlates with altered loadings in Cerebrospinal Fluid samples and a decline in cognition and memory. We extracted morphological features from T1w 3T MRI acquisitions using FreeSurfer from 77 Healthy Controls (age = 66 ± 8.4, 69% females), 31 Mild Cognitive Impairment (age = 72 ± 4.8, 61% females), and 13 Alzheimer's Disease patients (age = 77 ± 6.1, 62% females) of recruited volunteers in Brazil to test its discriminative power using optimal cut-point analysis. Cortical folding distinguishes the groups with reasonable accuracy (Healthy Control-Alzheimer's Disease, accuracy = 0.82; Healthy Control-Mild Cognitive Impairment, accuracy = 0.56). Moreover, Cerebrospinal Fluid biomarkers (total Tau, A[Formula: see text]1-40, A[Formula: see text]1-42, and Lipoxin) and cognitive scores (Cognitive Index, Rey's Auditory Verbal Learning Test, Trail Making Test, Digit Span Backward) were correlated with the global neurodegeneration in MRI aiming to describe health, disease, and the transition between the two states using morphology.

Aminopyrimidine Derivatives as Multiflavivirus Antiviral Compounds Identified from a Consensus Virtual Screening Approach.

Around three billion people are at risk of infection by the dengue virus (DENV) and potentially other flaviviruses. Worldwide outbreaks of DENV, Zika virus (ZIKV), and yellow fever virus (YFV), the lack of antiviral drugs, and limitations on vaccine usage emphasize the need for novel antiviral research. Here, we propose a consensus virtual screening approach to discover potential protease inhibitors (NS3pro) against different flavivirus. We employed an in silico combination of a hologram quantitative structure-activity relationship (HQSAR) model and molecular docking on characterized binding sites followed by molecular dynamics (MD) simulations, which filtered a data set of 7.6 million compounds to 2,775 hits. Lastly, docking and MD simulations selected six final potential NS3pro inhibitors with stable interactions along the simulations. Five compounds had their antiviral activity confirmed against ZIKV, YFV, DENV-2, and DENV-3 (ranging from 4.21 ± 0.14 to 37.51 ± 0.8 µM), displaying aggregator characteristics for enzymatic inhibition against ZIKV NS3pro (ranging from 28 ± 7 to 70 ± 7 µM). Taken together, the compounds identified in this approach may contribute to the design of promising candidates to treat different flavivirus infections.

Hierarchical growth in neural networks structure: Organizing inputs by Order of Hierarchical Complexity.

Several studies demonstrate that the structure of the brain increases in hierarchical complexity throughout development. We tested if the structure of artificial neural networks also increases in hierarchical complexity while learning a developing task, called the balance beam problem. Previous simulations of this developmental task do not reflect a necessary premise underlying development: a more complex structure can be built out of less complex ones, while ensuring that the more complex structure does not replace the less complex one. In order to address this necessity, we segregated the input set by subsets of increasing Orders of Hierarchical Complexity. This is a complexity measure that has been extensively shown to underlie the complexity behavior and hypothesized to underlie the complexity of the neural structure of the brain. After segregating the input set, minimal neural network models were trained separately for each input subset, and adjacent complexity models were analyzed sequentially to observe whether there was a structural progression. Results show that three different network structural progressions were found, performing with similar accuracy, pointing towards self-organization. Also, more complex structures could be built out of less complex ones without substituting them, successfully addressing catastrophic forgetting and leveraging performance of previous models in the literature. Furthermore, the model structures trained on the two highest complexity subsets performed better than simulations of the balance beam present in the literature. As a major contribution, this work was successful in addressing hierarchical complexity structural growth in neural networks, and is the first that segregates inputs by Order of Hierarchical Complexity. Since this measure can be applied to all domains of data, the present method can be applied to future simulations, systematizing the simulation of developmental and evolutionary structural growth in neural networks.

Effects of anterior temporal lobe resection on cortical morphology.

Neuroimaging can capture brain restructuring after anterior temporal lobe resection (ATLR), a surgical procedure to treat drug-resistant temporal lobe epilepsy (TLE). Here, we examine the effects of this surgery on brain morphology measured in recently-proposed independent variables. We studied 101 individuals with TLE (55 left, 46 right onset) who underwent ATLR. For each individual we considered one pre-surgical MRI and one follow-up MRI 2-13 months after surgery. We used a surface-based method to locally compute traditional morphological variables, and the independent measures K, I, and S, where K measures white matter tension, I captures isometric scaling, and S contains the remaining information about cortical shape. A normative model trained on data from 924 healthy controls was used to debias the data and account for healthy ageing effects occurring during scans. A SurfStat random field theory clustering approach assessed changes across the cortex caused by ATLR. Compared to preoperative data, surgery had marked effects on all morphological measures. Ipsilateral effects were located in the orbitofrontal and inferior frontal gyri, the pre- and postcentral gyri and supramarginal gyrus, and the lateral occipital gyrus and lingual cortex. Contralateral effects were in the lateral occipital gyrus, and inferior frontal gyrus and frontal pole. The restructuring following ATLR is reflected in widespread morphological changes, mainly in regions near the resection, but also remotely in regions that are structurally connected to the anterior temporal lobe. The causes could include mechanical effects, Wallerian degeneration, or compensatory plasticity. The study of independent measures revealed additional effects compared to traditional measures.

Establishing a Baseline for Human Cortical Folding Morphological Variables: A Multisite Study.

Differences in the way human cerebral cortices fold have been correlated to health, disease, development, and aging. However, to obtain a deeper understanding of the mechanisms that generate such differences, it is useful to derive one's morphometric variables from the first principles. This study explores one such set of variables that arise naturally from a model for universal self-similar cortical folding that was validated on comparative neuroanatomical data. We aim to establish a baseline for these variables across the human lifespan using a heterogeneous compilation of cross-sectional datasets as the first step to extending the model to incorporate the time evolution of brain morphology. We extracted the morphological features from structural MRI of 3,650 subjects: 3,095 healthy controls (CTL) and 555 patients with Alzheimer's Disease (AD) from 9 datasets, which were harmonized with a straightforward procedure to reduce the uncertainty due to heterogeneous acquisition and processing. The unprecedented possibility of analyzing such a large number of subjects in this framework allowed us to compare CTL and AD subjects' lifespan trajectories, testing if AD is a form of accelerated aging at the brain structural level. After validating this baseline from development to aging, we estimate the variables' uncertainties and show that Alzheimer's Disease is similar to premature aging when measuring global and local degeneration. This new methodology may allow future studies to explore the structural transition between healthy and pathological aging and may be essential to generate data for the cortical folding process simulations.

Platypnoea-orthodeoxia syndrome and hemidiaphragm paralysis.

A woman in her 70s was admitted to hospital with worsening shortness of breath and no prior respiratory history of note. This patient's shortness of breath was posture-dependent; symptoms were markedly worse and oxygen saturations were lower on sitting upright than in recumbency. Her shortness of breath had started several weeks prior to admission and had slowly worsened. Chest X-ray revealed a raised right hemidiaphragm. Further investigation revealed a patent foramen ovale, which was managed with percutaneous closure. This is one of several cases that demonstrate right-to-left shunting through a septal defect secondary to right hemidiaphragmatic paralysis. However, previous reports have not provided a clear guide for management of these cases. We suggest where patients are admitted with new onset breathlessness and platypnoea-orthodeoxia, a septal defect should be suspected. In this report, we have suggested a flowchart for the investigation and management of platypnoea-orthodeoxia syndrome.

Clinical Translation of Three-Dimensional Scar, Diffusion Tensor Imaging, Four-Dimensional Flow, and Quantitative Perfusion in Cardiac MRI: A Comprehensive Review.

Cardiovascular magnetic resonance (CMR) imaging is a versatile tool that has established itself as the reference method for functional assessment and tissue characterisation. CMR helps to diagnose, monitor disease course and sub-phenotype disease states. Several emerging CMR methods have the potential to offer a personalised medicine approach to treatment. CMR tissue characterisation is used to assess myocardial oedema, inflammation or thrombus in various disease conditions. CMR derived scar maps have the potential to inform ablation therapy-both in atrial and ventricular arrhythmias. Quantitative CMR is pushing boundaries with motion corrections in tissue characterisation and first-pass perfusion. Advanced tissue characterisation by imaging the myocardial fibre orientation using diffusion tensor imaging (DTI), has also demonstrated novel insights in patients with cardiomyopathies. Enhanced flow assessment using four-dimensional flow (4D flow) CMR, where time is the fourth dimension, allows quantification of transvalvular flow to a high degree of accuracy for all four-valves within the same cardiac cycle. This review discusses these emerging methods and others in detail and gives the reader a foresight of how CMR will evolve into a powerful clinical tool in offering a precision medicine approach to treatment, diagnosis, and detection of disease.

Independent components of human brain morphology.

Quantification of brain morphology has become an important cornerstone in understanding brain structure. Measures of cortical morphology such as thickness and surface area are frequently used to compare groups of subjects or characterise longitudinal changes. However, such measures are often treated as independent from each other. A recently described scaling law, derived from a statistical physics model of cortical folding, demonstrates that there is a tight covariance between three commonly used cortical morphology measures: cortical thickness, total surface area, and exposed surface area. We show that assuming the independence of cortical morphology measures can hide features and potentially lead to misinterpretations. Using the scaling law, we account for the covariance between cortical morphology measures and derive novel independent measures of cortical morphology. By applying these new measures, we show that new information can be gained; in our example we show that distinct morphological alterations underlie healthy ageing compared to temporal lobe epilepsy, even on the coarse level of a whole hemisphere. We thus provide a conceptual framework for characterising cortical morphology in a statistically valid and interpretable manner, based on theoretical reasoning about the shape of the cortex.

The application of machine learning techniques to innovative antibacterial discovery and development.

INTRODUCTION: After the initial wave of antibiotic discovery, few novel classes of antibiotics have emerged, with the latest dating back to the 1980's. Furthermore, the pace of antibiotic drug discovery is unable to keep up with the increasing prevalence of antibiotic drug resistance. However, the increasing amount of available data promotes the use of machine learning techniques (MLT) in drug discovery projects (e.g. construction of regression/classification models and ranking/virtual screening of compounds). AREAS COVERED: In this review, the authors cover some of the applications of MLT in medicinal chemistry, focusing on the development of new antibiotics, the prediction of resistance and its mechanisms. The aim of this review is to illustrate the main advantages and disadvantages and the major trends from studies over the past 5 years. EXPERT OPINION: The application of MLT to antibacterial drug discovery can aid the selection of new and potent lead compounds, with desirable pharmacokinetic and toxic profiles for further optimization. The increasing volume of available data along with the constant improvement in computational power and algorithms has meant that we are experiencing a transition in the way we face modern issues such as drug resistance, where our decisions are data-driven and experiments can be focused by data-suggested hypotheses.

EEG dynamical network analysis method reveals the neural signature of visual-motor coordination.

Human visual-motor coordination is an essential function of movement control, which requires interactions of multiple brain regions. Understanding the cortical-motor coordination is important for improving physical therapy for motor disabilities. However, its underlying transient neural dynamics is still largely unknown. In this study, we applied an eigenvector-based dynamical network analysis method to investigate the functional connectivity calculated from electroencephalography (EEG) signals under visual-motor coordination task and to identify its meta-stable states dynamics. We first tested this signal processing on a simulated network to evaluate it in comparison with other dynamical methods, demonstrating that the eigenvector-based dynamical network analysis was able to correctly extract the dynamical features of the evolving networks. Subsequently, the eigenvector-based analysis was applied to EEG data collected under a visual-motor coordination experiment. In the EEG study with participants, the results of both topological analysis and the eigenvector-based dynamical analysis were able to distinguish different experimental conditions of visual tracking task. With the dynamical analysis, we showed that different visual-motor coordination states can be distinguished by investigating the meta-stable states dynamics of the functional connectivity.

Safety and Effectiveness of the Pipeline Flex Embolization Device With Shield Technology for the Treatment of Intracranial Aneurysms: Midterm Results From a Multicenter Study.

BACKGROUND: The safety and efficacy of the first generation of the Pipeline Embolization Device (PED; Medtronic Inc) have been proven in large case series. Ischemic events are one of the most common complications following treatment of aneurysms with flow diverters. The new PED Flex with Shield technology (PED Shield; Medtronic Inc) was introduced to minimize the rate of complications. OBJECTIVE: To evaluate the outcomes of patients harboring aneurysms treated with the PED Shield. METHODS: This was an observational, prospective, single-arm multicenter study of patients treated with the PED Shield. The primary safety endpoint was the absence of major neurological complications and death. The secondary effectiveness endpoint was angiographic occlusion at 6 and 12 mo. Technical complications were also reported. RESULTS: Between November 2017 and December 2018, 151 patients from 7 centers with 182 aneurysms were enrolled. The mean aneurysm size was 7.0 mm; 27 (14.8%) aneurysms were large, and 7 (3.8%) were giant. In 141 of 151 patients (93.4%), the primary endpoint was reached. The overall rate of periprocedural complications was 7.3%. Of the aneurysms, 79.7% met the study's secondary endpoint of complete occlusion at 6 mo and 85.3% at 12 mo. CONCLUSION: The PED Shield is a safe and effective treatment for intracranial aneurysms. The results regarding total occlusion and ischemic complications did not differ from those obtained in case series using previous versions of the PED. Long-term follow-up and comparative studies are required to provide stronger conclusions regarding the reduced thrombogenicity of this device.

Virtual screening of antibacterial compounds by similarity search of Enoyl-ACP reductase (FabI) inhibitors.

Aim: Antibiotic resistance is an alarming issue, as multidrug-resistant bacteria are growing worldwide, hence the decrease of therapeutic potential of available antibiotic arsenal. Among these bacteria, Staphylococcus aureus was pointed by the WHO in the pathogens list to be prioritized in drug development. Methods: We report the use of chemical similarity models for the virtual screening of new antibacterial with structural similarity to known inhibitors of FabI. The potential inhibitors were experimentally evaluated for antibacterial activity and membrane disrupting capabilities. Results & conclusion: These models led to the finding of four new compounds with antibacterial activity, one of which having antimicrobial activity already reported in the literature.

The reliability of the isotropic fractionator method for counting total cells and neurons.

BACKGROUND: The Isotropic Fractionator (IF) is a method to determine the cellular composition of nervous tissue. It has been mostly applied to assess variation across species, where differences are expected to be large enough not to be masked by methodological error. However, understanding the sources of variation in the method is important if the goal is to detect smaller differences, for example, in same-species comparisons. Comparisons between different mice strains suggest that the IF is consistent enough to detect these differences. Nevertheless, the reliability of the method has not yet been examined directly. METHOD: In this study, we evaluate the reliability of the method for the determination of cellular and neuronal numbers of Swiss mice. We performed repeated cell counts of the same material by different experimenters to quantify different sources of variation. RESULTS: In total cell counts, we observed that for the cerebral cortex most of the variance was at the counter level. For the cerebellum, most of the variance is attributed to the sample itself. As for neurons, random error along with the immunostaining correspond to most of the variation, both in the cerebral cortex and in the cerebellum. Test-retest reliability coefficients were relatively high, especially for cell counts. CONCLUSIONS: Although biases between counters and random variation in staining could be problematic when aggregating data from different sources, we offer practical suggestions to improve the reliability of the method. While small, this study is a most needed step towards more precise measurement of the brain's cellular composition.