Evolution and diversity of alpha-carbonic anhydrases in the mantle of the Mediterranean mussel (Mytilus galloprovincialis)

The α-carbonic anhydrases (α-CAs) are a large and ancient group of metazoan-specific enzymes. They generate bicarbonate from metabolic carbon dioxide and through calcium carbonate crystal formation play a key role in the regulation of mineralized structures. To better understand how α-CAs contribute to shell mineralization in the marine Mediterranean mussel (Mytilus galloprovincialis) we characterized them in the mantle. Phylogenetic analysis revealed that mollusc α-CA evolution was affected by lineage and species-specific events. Ten α-CAs were found in the Mediterranean mussel mantle and the most abundant form was named, MgNACR, as it grouped with oyster nacreins (NACR). Exposure of the Mediterranean mussel to reduced water salinity (18 vs 37 ppt), caused a significant reduction (p < 0.05) in mantle esterase activity and MgNACR transcript abundance (p < 0.05). Protonograms revealed multiple proteins in the mantle with α-CA hydratase activity and mapped to a protein with a similar size to that deduced for monomeric MgNACR. Our data indicate that MgNACR is a major α-CA enzyme in mantle and that by homology with oyster nacreins likely regulates mussel shell production. We propose that species-dependent α-CA evolution may contribute to explain the diversity of bivalve shell structures and their vulnerability to environmental changes.Agência financiadora European Union 605051 Portuguese national funds from FCT - Foundation for Science and Technology UID/Multi/04326/2019 operational programmes CRESC Algarve 2020 and COMPETE 2020 through project EMBRC FCT UID/Multi/04326/2019 SFRH/BPD/79105/2011 SFRH/BPD/89811/2012 EMBRIC (European Union's Horizon 2020 research and innovation programme) 654008 CAPES, Brazil 88887.116718/2016-00 PT ALG-01-0145-FEDER-022121info:eu-repo/semantics/publishedVersio

Fast Predictive Simple Geodesic Regression

Deformable image registration and regression are important tasks in medical image analysis. However, they are computationally expensive, especially when analyzing large-scale datasets that contain thousands of images. Hence, cluster computing is typically used, making the approaches dependent on such computational infrastructure. Even larger computational resources are required as study sizes increase. This limits the use of deformable image registration and regression for clinical applications and as component algorithms for other image analysis approaches. We therefore propose using a fast predictive approach to perform image registrations. In particular, we employ these fast registration predictions to approximate a simplified geodesic regression model to capture longitudinal brain changes. The resulting method is orders of magnitude faster than the standard optimization-based regression model and hence facilitates large-scale analysis on a single graphics processing unit (GPU). We evaluate our results on 3D brain magnetic resonance images (MRI) from the ADNI datasets.Comment: 19 pages, 10 figures, 13 table

A Statistical Model for Simultaneous Template Estimation, Bias Correction, and Registration of 3D Brain Images

Template estimation plays a crucial role in computational anatomy since it provides reference frames for performing statistical analysis of the underlying anatomical population variability. While building models for template estimation, variability in sites and image acquisition protocols need to be accounted for. To account for such variability, we propose a generative template estimation model that makes simultaneous inference of both bias fields in individual images, deformations for image registration, and variance hyperparameters. In contrast, existing maximum a posterori based methods need to rely on either bias-invariant similarity measures or robust image normalization. Results on synthetic and real brain MRI images demonstrate the capability of the model to capture heterogeneity in intensities and provide a reliable template estimation from registration

Second malignancies in breast cancer patients following radiotherapy: a study in Florence, Italy.

ntroduction: Patients diagnosed with breast cancer are often treated with surgery followed by radiation therapy. In this paper, we evaluate the effect that radiotherapy may have had on the subsequent risk of second malignancies, including the possible influences of age at treatment and menopausal status.Methods: In order to evaluate the long-term consequences of radiotherapy, a cohort study was conducted based on clinical records for 5,248 women treated for breast cancer in Florence (Italy), with continuous follow-up from 1965 to 1994. The Cox proportional hazards model for ungrouped survival data was used to estimate the relative risk for second cancer after radiotherapy.Results: This study indicated an increased relative risk of all second cancers combined following radiotherapy (1.22, 95% CI: 0.88 to 1.69). The increased relative risk appeared five or more years after radiotherapy and appeared to be highest amongst women treated after the menopause (1.61, 95% CI: 1.13 to 2.29). Increased relative risks were observed specifically for leukaemia (8.13, 95% CI: 0.96 to 69.1) and other solid cancers (1.84, 95% CI: 1.06 to 3.16), excluding contralateral breast cancer. For contralateral breast cancer, no raised relative risk was observed during the period more than five years after radiotherapy.Conclusions: The study indicated a raised risk of second malignancies associated with radiotherapy for breast cancer, particularly for women treated after the menopause

Effect of hypoxia-inducible factor 1-alpha (HIF-1α) on proliferation and apoptosis of adrenocorticotropic hormone (ACTH)-secreting pituitary adenoma cells

To understand whether hypoxia-inducible factor 1-alpha (HIF-1α) could protect AtT-20 cells from hypoxia induced apoptosis, we investigated the effects of HIF-1α on proliferation and apoptosis of adrenocorticotropic hormone (ACTH)-secreting pituitary adenoma cells (AtT-20 cells). AtT-20 cells were treated with various concentrations of CoCl2 to induce hypoxia. 3-(4,5-Dimethylthiazol-2-yl)-2,5- diphenyltetrazolium bromide, a yellow tetrazole (MTT) was applied to detect the proliferation of these cells. Western blot assay and real time polymerase chain reaction (PCR) were used to determine the protein and mRNA expressions of HIF-1α, respectively. In addition, AtT-20 cells were transfected with siRNA targeting HIF-1α and treated with different concentrations of CoCl2. The transfection efficacy was assessed by real-time PCR and western blot assay. Apoptosis was measured by fluorescein isothiocyanate (FITC)-annexin V/ propidium iodide (PI) staining and TUNEL staining. The effect of CoCl2 on the proliferation of AtT-20 cells was in a concentration and time dependent manner. When the concentration of CoCl2 was ≤100 μM and/or duration of CoCl2 treatment was ≤48 h, CoCl2 triggered the proliferation of AtT-20 cells. Nevertheless, the apoptosis rate of cells transfected with HIF-1α-siRNA was markedly increased after CoCl2 treatment. These findings suggest that, HIF-1α can promote the proliferation of AtT-20 cells and exert anti-apoptotic effect under hypoxic condition.Key words: Hypoxia inducible factor–1α, cobalt chloride, apoptosis, pituitary adenom

Fast and Accurate Camera Covariance Computation for Large 3D Reconstruction

Estimating uncertainty of camera parameters computed in Structure from Motion (SfM) is an important tool for evaluating the quality of the reconstruction and guiding the reconstruction process. Yet, the quality of the estimated parameters of large reconstructions has been rarely evaluated due to the computational challenges. We present a new algorithm which employs the sparsity of the uncertainty propagation and speeds the computation up about ten times \wrt previous approaches. Our computation is accurate and does not use any approximations. We can compute uncertainties of thousands of cameras in tens of seconds on a standard PC. We also demonstrate that our approach can be effectively used for reconstructions of any size by applying it to smaller sub-reconstructions.Comment: ECCV 201

Possible scale invariant linear magnetoresistance in pyrochlore iridates Bi2Ir2O7

We report the observation of a linear magnetoresistance in single crystals and epitaxial thin films of the pyrochlore iridate Bi2Ir2O7. The linear magnetoresistance is positive and isotropic at low temperatures, without any sign of saturation up to 35 T. As temperature increases, the linear field dependence gradually evolves to a quadratic field dependence. The temperature and field dependence of magnetoresistance of Bi2Ir2O7 bears strikingly resemblance to the scale invariant magnetoresistance observed in the strange metal phase in high Tc cuprates. However, the residual resistivity of Bi2Ir2O7 is more than two orders of magnitude higher than the curpates. Our results suggest that the correlation between linear magnetoresistance and quantum fluctuations may exist beyond high temperature superconductors

Mapping quantitative trait loci in line cross with repeat records

<p>Abstract</p> <p>Background</p> <p>Phenotypes with repeat records from one individual or multiple individuals were often encountered in practices of mapping QTL in linecross. The current genetic mapping method for a trait with repeat records is adopted by simply replacing the phenotype by the average value of the repeat records. This simple treatment has not sufficiently utilized the information from the replication and ignored the impacts of the permanent environmental effects on the accuracy of the estimated QTL.</p> <p>Results</p> <p>We propose to map QTL by using the repeatability model to directly analyze the repeat records rather than simply analyze the mean phenotype, improving the efficiency of QTL detecting because of adequately utilizing the information from data and allowing for the permanent environmental effects. A maximum likelihood method implemented via the expectation-maximization (EM) algorithm is applied to perform the parameter estimation of the repeatability model. The superiority of the mapping method based on the repeatability model over simple analysis using the mean phenotype was demonstrated by a series of simulations.</p> <p>Conclusion</p> <p>Our results suggest that the proposed method can serve as a powerful alternative to existing methods. By mean of the repeatability model, utilizing the repeat records on individual may improve the efficiency of QTL detecting in line cross.</p

The calcitonin-like system is an ancient regulatory system of biomineralization

Biomineralization is the process by which living organisms acquired the capacity to accumulate minerals in tissues. Shells are the biomineralized exoskeleton of marine molluscs produced by the mantle but factors that regulate mantle shell building are still enigmatic. This study sought to identify candidate regulatory factors of molluscan shell mineralization and targeted family B G-protein coupled receptors (GPCRs) and ligands that include calcium regulatory factors in vertebrates, such as calcitonin (CALC). In molluscs, CALC receptor (CALCR) number was variable and arose through lineage and species-specific duplications. The Mediterranean mussel (Mytilus galloprovincialis) mantle transcriptome expresses six CALCR-like and two CALC-precursors encoding four putative mature peptides. Mussel CALCR-like are activated in vitro by vertebrate CALC but only receptor CALCRIIc is activated by the mussel CALCIIa peptide (EC50 = 2.6 ×10-5 M). Ex-vivo incubations of mantle edge tissue and mantle cells with CALCIIa revealed they accumulated significantly more calcium than untreated tissue and cells. Mussel CALCIIa also significantly decreased mantle acid phosphatase activity, which is associated with shell remodelling. Our data indicate the CALC-like system as candidate regulatory factors of shell mineralization. The identification of the CALC system from molluscs to vertebrates suggests it is an ancient and conserved calcium regulatory system of mineralization.CCMAR UIDB/04326/2020; CRESC Algarve 2020 and COMPETE 2020 through project EMBRC.PT ALG-01-0145-FEDER-022121. FCT: DL57/2016/CP1361/CT0020info:eu-repo/semantics/publishedVersio