Functional Characterisation of Alpha-Galactosidase A Mutations as a Basis for a New Classification System in Fabry Disease

This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.The study has been supported partially by an unrestricted scientific grant from Shire Human Genetic Therapies (Germany

Room-Temperature Inter-Dot Coherent Dynamics in Multilayer Quantum Dot Materials

The full blossoming of quantum technologies requires the availability of easy-to-prepare materials where quantum coherences can be effectively initiated, controlled, and exploited, preferably at ambient conditions. Solid-state multilayers of colloidally grown quantum dots (QDs) are highly promising for this task because of the possibility of assembling networks of electronically coupled QDs through the modulation of sizes, inter-dot linkers, and distances. To usefully probe coherence in these materials, the dynamical characterization of their collective quantum mechanically coupled states is needed. Here, we explore by two-dimensional electronic spectroscopy the coherent dynamics of solid-state multilayers of electronically coupled colloidally grown CdSe QDs and complement it by detailed computations. The time evolution of a coherent superposition of states delocalized over more than one QD was captured at ambient conditions. We thus provide important evidence for inter-dot coherences in such solid-state materials, opening up new avenues for the effective application of these materials in quantum technologies

Algorithm engineering for optimal alignment of protein structure distance matrices

Protein structural alignment is an important problem in computational biology. In this paper, we present first successes on provably optimal pairwise alignment of protein inter-residue distance matrices, using the popular Dali scoring function. We introduce the structural alignment problem formally, which enables us to express a variety of scoring functions used in previous work as special cases in a unified framework. Further, we propose the first mathematical model for computing optimal structural alignments based on dense inter-residue distance matrices. We therefore reformulate the problem as a special graph problem and give a tight integer linear programming model. We then present algorithm engineering techniques to handle the huge integer linear programs of real-life distance matrix alignment problems. Applying these techniques, we can compute provably optimal Dali alignments for the very first time

Nuclear medicine procedures and the evaluation of male sexual organs: a short review

Sexuality consists of three aspects that are interrelated and inseparable, biological, physiological and social. The biological aspect considers the individual's capability to give and to receive pleasure. In consequence, it covers the functionality of the sexual organs and the physiology of human sexual response cycle. Diagnostic imaging modalities, such as single photon emission computed tomography (SPECT) and positron emission tomography (PET) have been used to evaluate clinical disorders of the male reproductive system. PET and SPECT procedures basically involve the administration of a radiopharmaceutical that has a higher uptake in a specific tumor or tissue. The aim of this brief review is to present some radiopharmaceuticals that have been used in the clinical evaluation of the male sexual organs (testes, prostate, seminal vesicles, penis) related with male sexuality. This information could be useful in better understanding the male sexual response cycle, as well as the sexual disorders, when considering the male sexual organs and the pelvic floor. Moreover, the findings obtained with PET and SPECT imaging could help to evaluate the efficacy of clinical results of therapeutic procedures. In conclusion, the knowledge from these images could aid in better understanding the physiology of the different organs related with sexuality. Furthermore, they could be important tools to evaluate the physiological integrity of the involved organs, to improve clinical strategies and to accompany the patients under treatment

Undefinability in Inquisitive Logic with Tensor

Logics based on team semantics, such as inquisitive logic and dependence logic, are not closed under uniform substitution. This leads to an interesting separation between expressive power and definability: it may be that an operator O can be added to a language without a gain in expressive power, yet O is not definable in that language. For instance, even though propositional inquisitive logic and propositional dependence logic have the same expressive power, inquisitive disjunction and implication are not definable in propositional dependence logic. A question that has been open for some time in this area is whether the tensor disjunction used in propositional dependence logic is definable in inquisitive logic. We settle this question in the negative. In fact, we show that extending the logical repertoire of inquisitive logic by means of tensor disjunction leads to an independent set of connectives; that is, no connective in the resulting logic is definable in terms of the others.Peer reviewe

Agenesia e lipoma de corpo caloso: relato de caso

The agenesis and lipoma of the corpus callosum is a very rare association. We report the case of a 18-years old woman with rare epileptic seizures since the age of 6 years, normal neurological examination, as well as normal electroencephalogram. The brain computed tomography scanning and the magnetic resonance showed the lipoma and the agenesis of the corpus callosum.A agenesia e lipoma do corpo caloso é uma associação muito rara. Relatamos o caso de uma paciente de 18 anos com raras crises epilépticas desde os 6 anos de idade, exame neurológico normal, assim como eletrencefalograma normal. A tomografia computadorizada de crânio e a ressonância magnética mostraram o lipoma e a agenesia de corpo caloso.Escola Paulista de MedicinaUNIFESP, EPMSciEL

A Mathematical Framework for Protein Structure Comparison

Comparison of protein structures is important for revealing the evolutionary relationship among proteins, predicting protein functions and predicting protein structures. Many methods have been developed in the past to align two or multiple protein structures. Despite the importance of this problem, rigorous mathematical or statistical frameworks have seldom been pursued for general protein structure comparison. One notable issue in this field is that with many different distances used to measure the similarity between protein structures, none of them are proper distances when protein structures of different sequences are compared. Statistical approaches based on those non-proper distances or similarity scores as random variables are thus not mathematically rigorous. In this work, we develop a mathematical framework for protein structure comparison by treating protein structures as three-dimensional curves. Using an elastic Riemannian metric on spaces of curves, geodesic distance, a proper distance on spaces of curves, can be computed for any two protein structures. In this framework, protein structures can be treated as random variables on the shape manifold, and means and covariance can be computed for populations of protein structures. Furthermore, these moments can be used to build Gaussian-type probability distributions of protein structures for use in hypothesis testing. The covariance of a population of protein structures can reveal the population-specific variations and be helpful in improving structure classification. With curves representing protein structures, the matching is performed using elastic shape analysis of curves, which can effectively model conformational changes and insertions/deletions. We show that our method performs comparably with commonly used methods in protein structure classification on a large manually annotated data set

Toward a Surrogate Marker of Malaria Exposure: Modeling Longitudinal Antibody Measurements under Outbreak Conditions

Background: Biomarkers of exposure to Plasmodium falciparum would be a useful tool for the assessment of malaria burden and analysis of intervention and epidemiological studies. Antibodies to pre-erythrocytic antigens represent potential surrogates of exposure. Methods and Findings: In an outbreak cohort of U.S. Marines deployed to Liberia, we modeled pre- and post-deployment IgG against P. falciparum sporozoites by immunofluorescence antibody test, and both IgG and IgM against the P. falciparum circumsporozoite protein by enzyme-linked immunosorbant assay. Modeling seroconversion thresholds by a fixed ratio, linear regression or nonlinear regression produced sensitivity for identification of exposed U.S. Marines between 58-70% and specificities between 87-97%, compared with malaria-naïve U.S. volunteers. Exposure was predicted in 30-45% of the cohort. Conclusion: Each of the three models tested has merits in different studies, but further development and validation in endemic populations is required. Overall, these models provide support for an antibody-based surrogate marker of exposure to malaria

Long-Term Follow-Up After Gene Therapy for Canavan Disease

Canavan disease is a hereditary leukodystrophy caused by mutations in the aspartoacylase gene (ASPA), leading to loss of enzyme activity and increased concentrations of the substrate N-acetylaspartate (NAA) in the brain. Accumulation of NAA results in spongiform degeneration of white matter and severe impairment of psychomotor development. The goal of this prospective cohort study was to assess long-term safety and preliminary efficacy measures after gene therapy with an adeno-associated viral vector carrying the ASPA gene (AAV2-ASPA). Using noninvasive magnetic resonance imaging and standardized clinical rating scales, we observed Canavan disease in 28 patients, with a subset of 13 patients being treated with AAV2-ASPA. Each patient received 9 × 1011 vector genomes via intraparenchymal delivery at six brain infusion sites. Safety data collected over a minimum 5-year follow-up period showed a lack of long-term adverse events related to the AAV2 vector. Posttreatment effects were analyzed using a generalized linear mixed model, which showed changes in predefined surrogate markers of disease progression and clinical assessment subscores. AAV2-ASPA gene therapy resulted in a decrease in elevated NAA in the brain and slowed progression of brain atrophy, with some improvement in seizure frequency and with stabilization of overall clinical status

Mathematical modeling and comparison of protein size distribution in different plant, animal, fungal and microbial species reveals a negative correlation between protein size and protein number, thus providing insight into the evolution of proteomes

<p>Abstract</p> <p>Background</p> <p>The sizes of proteins are relevant to their biochemical structure and for their biological function. The statistical distribution of protein lengths across a diverse set of taxa can provide hints about the evolution of proteomes.</p> <p>Results</p> <p>Using the full genomic sequences of over 1,302 prokaryotic and 140 eukaryotic species two datasets containing 1.2 and 6.1 million proteins were generated and analyzed statistically. The lengthwise distribution of proteins can be roughly described with a gamma type or log-normal model, depending on the species. However the shape parameter of the gamma model has not a fixed value of 2, as previously suggested, but varies between 1.5 and 3 in different species. A gamma model with unrestricted shape parameter described best the distributions in ~48% of the species, whereas the log-normal distribution described better the observed protein sizes in 42% of the species. The gamma restricted function and the sum of exponentials distribution had a better fitting in only ~5% of the species. Eukaryotic proteins have an average size of 472 aa, whereas bacterial (320 aa) and archaeal (283 aa) proteins are significantly smaller (33-40% on average). Average protein sizes in different phylogenetic groups were: Alveolata (628 aa), Amoebozoa (533 aa), Fornicata (543 aa), Placozoa (453 aa), Eumetazoa (486 aa), Fungi (487 aa), Stramenopila (486 aa), Viridiplantae (392 aa). Amino acid composition is biased according to protein size. Protein length correlated negatively with %C, %M, %K, %F, %R, %W, %Y and positively with %D, %E, %Q, %S and %T. Prokaryotic proteins had a different protein size bias for %E, %G, %K and %M as compared to eukaryotes.</p> <p>Conclusions</p> <p>Mathematical modeling of protein length empirical distributions can be used to asses the quality of small ORFs annotation in genomic releases (detection of too many false positive small ORFs). There is a negative correlation between average protein size and total number of proteins among eukaryotes but not in prokaryotes. The %GC content is positively correlated to total protein number and protein size in prokaryotes but not in eukaryotes. Small proteins have a different amino acid bias than larger proteins. Compared to prokaryotic species, the evolution of eukaryotic proteomes was characterized by increased protein number (massive gene duplication) and substantial changes of protein size (domain addition/subtraction).</p