Unravelling spiral cleavage

Snails, earthworms and flatworms are remarkably different animals, but they all exhibit a very similar mode of early embryogenesis: spiral cleavage. This is one of the most widespread developmental programs in animals, probably ancestral to almost half of the animal phyla, and therefore its study is essential for understanding animal development and evolution. However, our knowledge of spiral cleavage is still in its infancy. Recent technical and conceptual advances, such as the establishment of genome editing and improved phylogenetic resolution, are paving the way for a fresher and deeper look into this fascinating early cleavage mode

Early embryogenesis and organogenesis in the annelid Owenia fusiformis

Annelids are a diverse group of segmented worms within Spiralia, whose embryos exhibit spiral cleavage and a variety of larval forms. While most modern embryological studies focus on species with unequal spiral cleavage nested in Pleistoannelida (Sedentaria + Errantia), a few recent studies looked into Owenia fusiformis, a member of the sister group to all remaining annelids and thus a key lineage to understand annelid and spiralian evolution and development. However, the timing of early cleavage and detailed morphogenetic events leading to the formation of the idiosyncratic mitraria larva of O. fusiformis remain largely unexplored

ERK1/2 is an ancestral organising signal in spiral cleavage

Animal development is classified as conditional or autonomous based on whether cell fates are specified through inductive signals or maternal determinants, respectively. Yet how these two major developmental modes evolved remains unclear. During spiral cleavage—a stereotypic embryogenesis ancestral to 15 invertebrate groups, including molluscs and annelids—most lineages specify cell fates conditionally, while some define the primary axial fates autonomously. To identify the mechanisms driving this change, we study Owenia fusiformis, an early-branching, conditional annelid. In Owenia, ERK1/2-mediated FGF receptor signalling specifies the endomesodermal progenitor. This cell likely acts as an organiser, inducing mesodermal and posterodorsal fates in neighbouring cells and repressing anteriorising signals. The organising role of ERK1/2 in Owenia is shared with molluscs, but not with autonomous annelids. Together, these findings suggest that conditional specification of an ERK1/2(+) embryonic organiser is ancestral in spiral cleavage and was repeatedly lost in annelid lineages with autonomous development

Evolution of the EGFR pathway in Metazoa and its diversification in the planarian Schmidtea mediterranea

This study was funded by grants, BFU2012-31701 and BFU2015-65704-P(Ministerio de Economia y Competitividad/Feder (Spain)) and 2009-SGR-1018 from the Generalitat de Catalunya to FC. SB was supported by a FI fellowship from the Generalitat de Catalunya and a collaboration fellowship from IBUB. JMMD was supported by Marie Curie IEF 329024 fellowship and Sars core budg

Selecting the most relevant brain regions to discriminate Alzheimer's disease patients from healthy controls using multiple kernel learning: A comparison across functional and structural imaging modalities and atlases

BACKGROUND: Machine learning techniques such as support vector machine (SVM) have been applied recently in order to accurately classify individuals with neuropsychiatric disorders such as Alzheimer's disease (AD) based on neuroimaging data. However, the multivariate nature of the SVM approach often precludes the identification of the brain regions that contribute most to classification accuracy. Multiple kernel learning (MKL) is a sparse machine learning method that allows the identification of the most relevant sources for the classification. By parcelating the brain into regions of interest (ROI) it is possible to use each ROI as a source to MKL (ROI-MKL). METHODS: We applied MKL to multimodal neuroimaging data in order to: 1) compare the diagnostic performance of ROI-MKL and whole-brain SVM in discriminating patients with AD from demographically matched healthy controls and 2) identify the most relevant brain regions to the classification. We used two atlases (AAL and Brodmann's) to parcelate the brain into ROIs and applied ROI-MKL to structural (T1) MRI, 18F-FDG-PET and regional cerebral blood flow SPECT (rCBF-SPECT) data acquired from the same subjects (20 patients with early AD and 18 controls). In ROI-MKL, each ROI received a weight (ROI-weight) that indicated the region's relevance to the classification. For each ROI, we also calculated whether there was a predominance of voxels indicating decreased or increased regional activity (for 18F-FDG-PET and rCBF-SPECT) or volume (for T1-MRI) in AD patients. RESULTS: Compared to whole-brain SVM, the ROI-MKL approach resulted in better accuracies (with either atlas) for classification using 18F-FDG-PET (92.5% accuracy for ROI-MKL versus 84% for whole-brain), but not when using rCBF-SPECT or T1-MRI. Although several cortical and subcortical regions contributed to discrimination, high ROI-weights and predominance of hypometabolism and atrophy were identified specially in medial parietal and temporo-limbic cortical regions. Also, the weight of discrimination due to a pattern of increased voxel-weight values in AD individuals was surprisingly high (ranging from approximately 20% to 40% depending on the imaging modality), located mainly in primary sensorimotor and visual cortices and subcortical nuclei. CONCLUSION: The MKL-ROI approach highlights the high discriminative weight of a subset of brain regions of known relevance to AD, the selection of which contributes to increased classification accuracy when applied to 18F-FDG-PET data. Moreover, the MKL-ROI approach demonstrates that brain regions typically spared in mild stages of AD also contribute substantially in the individual discrimination of AD patients from controls

Framingham coronary heart disease risk score can be predicted from structural brain images in elderly subjects

Recent literature has presented evidence that cardiovascular risk factors (CVRF) play an important role on cognitive performance in elderly individuals, both those who are asymptomatic and those who suffer from symptoms of neurodegenerative disorders. Findings from studies applying neuroimaging methods have increasingly reinforced such notion. Studies addressing the impact of CVRF on brain anatomy changes have gained increasing importance, as recent papers have reported gray matter loss predominantly in regions traditionally affected in Alzheimer’s disease (AD) and vascular dementia in the presence of a high degree of cardiovascular risk. In the present paper, we explore the association between CVRF and brain changes using pattern recognition techniques applied to structural MRI and the Framingham score (a composite measure of cardiovascular risk largely used in epidemiological studies) in a sample of healthy elderly individuals. We aim to answer the following questions: is it possible to decode (i.e., to learn information regarding cardiovascular risk from structural brain images) enabling individual predictions? Among clinical measures comprising the Framingham score, are there particular risk factors that stand as more predictable from patterns of brain changes? Our main findings are threefold: (i) we verified that structural changes in spatially distributed patterns in the brain enable statistically significant prediction of Framingham scores. This result is still significant when controlling for the presence of the APOE 4 allele (an important genetic risk factor for both AD and cardiovascular disease). (ii) When considering each risk factor singly, we found different levels of correlation between real and predicted factors; however, single factors were not significantly predictable from brain images when considering APOE4 allele presence as covariate. (iii) We found important gender differences, and the possible causes of that finding are discussed

A Broad Genomic Survey Reveals Multiple Origins and Frequent Losses in the Evolution of Respiratory Hemerythrins and Hemocyanins

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly citedHemerythrins and hemocyanins are respiratory proteins present in some of the most ecologically diverse animal lineages; however, the precise evolutionary history of their enzymatic domains (hemerythrin, hemocyanin M, and tyrosinase) is still not well understood. We survey a wide dataset of prokaryote and eukaryote genomes and RNAseq data to reconstruct the phylogenetic origins of these proteins. We identify new species with hemerythrin, hemocyanin M, and tyrosinase domains in their genomes, particularly within animals, and demonstrate that the current distribution of respiratory proteins is due to several events of lateral gene transfer and/or massive gene loss. We conclude that the last common metazoan ancestor had at least two hemerythrin domains, one hemocyanin M domain, and six tyrosinase domains. The patchy distribution of these proteins among animal lineages can be partially explained by physiological adaptations, making these genes good targets for investigations into the interplay between genomic evolution and physiological constraints. © The Author(s) 2013.This work was funded by the Sars International Centre for Marine Molecular Biology to J.M.M.-D. and A.H., and an ICREA contract, an European Research Council Starting Grant (ERC-2007-StG-206883), and a grant (BFU2011-23434) from Ministerio de Economía y Competitividad (MINECO) to I.R.-T. A.S.-P.’s salary was supported by a pregraduate FPU grant and A.d.M.’s salary from a FPI grant, both from MICINN.Peer Reviewe

Is the treatment with biological or non-biological DMARDS a modifier of periodontal condition in patients with rheumatoid arthritis?

Background and objective: Experimental models suggest the use of different therapy protocols in rheumatoid arthritis (RA) as modulators on periodontal condition. This study evaluated the effects of conventional drug treatment and anti-TNF therapy in patients with RA on microbiological and periodontal condition, establishing the association of markers of periodontal infection with indexes of rheumatic activity. Materials and methods: One hundred seventy nine individuals with RA were evaluated (62 with anti-TNF-. and 115 with only DMARDs). The periodontal evaluation included plaque and gingival indexes, bleeding on probing (BOP), clinical attachment loss (CAL), pocket depth (PD) and subgingival plaque samples for microbiological analysis. Rheumatologic evaluations included a clinical examination, rheumatoid factor (RF), antibodies against cyclic-citrullinated peptides (ACPAs), and activity markers (DAS28-ERS), high sensitive C-reactive protein (hs-CRP), erythrocyte sedimentation rate (ESR). Results: Anti-TNF-alpha therapy influenced periodontal microbiota with a higher frequency of T. denticola (p=0.01). Methotrexate combined with leflunomide exhibited a higher extension of CAL (p=0.005), and anti-TNF-alpha therapy with methotrexate was associated with a lower extension of CAL (p=0.05). The use of corticosteroids exerted a protective effect on the number of teeth (p=0.027). The type of DMARD affected P. gingivalis, T. forsythia and E. nodatum presence. Elevated ACPAs titers were associated with the presence of red complex periodontal pathogens (p=0.025). Bleeding on probing was associated with elevated CPR levels (p=0.05), and ESR was associated with a greater PD (p=0.044) and presence of red complex (p=0.030). Conclusion: Different pharmacological treatments for RA affect the clinical condition and subgingival microbiota