VIRTUAL RECONSTRUCTION OF THE ALMAQAH TEMPLE OF YEHA IN ETHIOPIA BY TERRESTRIAL LASER SCANNING

In autumn 2009 the Almaqah Temple of Yeha in Ethiopia has been recorded by terrestrial laser scanning and digital photogrammetry in cooperation between the Sana'a Branch of the Orient Department of the German Archaeological Institute and the HafenCity University Hamburg. The temple dates from the 7th Century BC and is one of the best preserved buildings of Sabaean architecture in Africa. As a basis for all future project works a geodetic network was established in UTM-coordinates by GPS measurements. The geodata collected will form the basis for all future work on the temple. The deformations of the facades were determined for restoration issues and the existing parts of the temple were modelled by meshing (3D triangulation). Using the scanned point cloud and a technical analysis of the building the Propylon, which is no longer existent today, was virtually reconstructed. In future, the data will also be included in the master plan for touristic development of the region of Axum and Yeha in northern Ethiopia

Specific MRI abnormalities reveal severe perrault syndrome due to CLPP defects

In establishing a genetic diagnosis in heterogeneous neurological disease, clinical characterization and whole exome sequencing (WES) go hand-in-hand. Clinical data are essential, not only to guide WES variant selection and define the clinical severity of a genetic defect but also to identify other patients with defects in the same gene. In an infant patient with sensorineural hearing loss, psychomotor retardation, and epilepsy, WES resulted in identification of a novel homozygous CLPP frameshift mutation (c.21delA). Based on the gene defect and clinical symptoms, the diagnosis Perrault syndrome type 3 (PRLTS3) was established. The patient's brain-MRI revealed specific abnormalities of the subcortical and deep cerebral white matter and the middle blade of the corpus callosum, which was used to identify similar patients in the Amsterdam brain-MRI database, containing over 3000 unclassified leukoencephalopathy cases. In three unrelated patients with similar MRI abnormalities the CLPP gene was sequenced, and in two of them novel missense mutations were identified together with a large deletion that covered part of the CLPP gene on the other allele. The severe neurological and MRI abnormalities in these young patients were due to the drastic impact of the CLPP mutations, correlating with the variation in clinical manifestations among previously reported patients. Our data show that similarity in brain-MRI patterns can be used to identify novel PRLTS3 patients, especially during early disease stages, when only part of the disease manifestations are present. This seems especially applicable to the severely affected cases in which CLPP function is drastically affected and MRI abnormalities are pronounced

Case Series and DARS2 Variant Analysis in Early Severe Forms With Unexpected Presentations

Objective: Leukoencephalopathy with brainstem and spinal cord involvement and lactate elevation (LBSL) is regarded a relatively mild leukodystrophy, diagnosed by characteristic long tract abnormalities on MRI and biallelic variants in DARS2, encoding mitochondrial aspartyl-tRNA synthetase (mtAspRS). DARS2 variants in LBSL are almost invariably compound heterozygous; in 95% of cases, 1 is a leaky splice site variant in intron 2. A few severely affected patients, still fulfilling the MRI criteria, have been described. We noticed highly unusual MRI presentations in 15 cases diagnosed by WES. We examined these cases to determine whether they represent consistent novel LBSL phenotypes. Methods: We reviewed clinical features, MRI abnormalities, and gene variants and investigated the variants' impact on mtAspRS structure and mitochondrial function. Results: We found 2 MRI phenotypes: early severe cerebral hypoplasia/atrophy (9 patients, group 1) and white matter abnormalities without long tract involvement (6 patients, group 2). With antenatal onset, microcephaly, and arrested development, group 1 patients were most severely affected. DARS2 variants were severer than for classic LBSL and severer for group 1 than group 2. All missense variants hit mtAspRS regions involved in tRNAAsp binding, aspartyl-adenosine-5'-monophosphate binding, and/or homodimerization. Missense variants expressed in the yeast DARS2 ortholog showed severely affected mitochondrial function. Conclusions: DARS2 variants are associated with highly heterogeneous phenotypes. New MRI presentations are profound cerebral hypoplasia/atrophy and white matter abnormalities without long tract involvement. Our findings have implications for diagnosis and understanding disease mechanisms, pointing at dominant neuronal/axonal involvement in severe cases. In line with this conclusion, activation of biallelic DARS2 null alleles in conditional transgenic mice leads to massive neuronal apoptosis

Robust probabilistic superposition and comparison of protein structures

<p>Abstract</p> <p>Background</p> <p>Protein structure comparison is a central issue in structural bioinformatics. The standard dissimilarity measure for protein structures is the root mean square deviation (RMSD) of representative atom positions such as α-carbons. To evaluate the RMSD the structures under comparison must be superimposed optimally so as to minimize the RMSD. How to evaluate optimal fits becomes a matter of debate, if the structures contain regions which differ largely - a situation encountered in NMR ensembles and proteins undergoing large-scale conformational transitions.</p> <p>Results</p> <p>We present a probabilistic method for robust superposition and comparison of protein structures. Our method aims to identify the largest structurally invariant core. To do so, we model non-rigid displacements in protein structures with outlier-tolerant probability distributions. These distributions exhibit heavier tails than the Gaussian distribution underlying standard RMSD minimization and thus accommodate highly divergent structural regions. The drawback is that under a heavy-tailed model analytical expressions for the optimal superposition no longer exist. To circumvent this problem we work with a scale mixture representation, which implies a weighted RMSD. We develop two iterative procedures, an Expectation Maximization algorithm and a Gibbs sampler, to estimate the local weights, the optimal superposition, and the parameters of the heavy-tailed distribution. Applications demonstrate that heavy-tailed models capture differences between structures undergoing substantial conformational changes and can be used to assess the precision of NMR structures. By comparing Bayes factors we can automatically choose the most adequate model. Therefore our method is parameter-free.</p> <p>Conclusions</p> <p>Heavy-tailed distributions are well-suited to describe large-scale conformational differences in protein structures. A scale mixture representation facilitates the fitting of these distributions and enables outlier-tolerant superposition.</p

Dysmorphometrics: the modelling of morphological abnormalities

<p>Abstract</p> <p>Background</p> <p>The study of typical morphological variations using quantitative, morphometric descriptors has always interested biologists in general. However, unusual examples of form, such as abnormalities are often encountered in biomedical sciences. Despite the long history of morphometrics, the means to identify and quantify such unusual form differences remains limited.</p> <p>Methods</p> <p>A theoretical concept, called dysmorphometrics, is introduced augmenting current geometric morphometrics with a focus on identifying and modelling form abnormalities. Dysmorphometrics applies the paradigm of detecting form differences as outliers compared to an appropriate norm. To achieve this, the likelihood formulation of landmark superimpositions is extended with outlier processes explicitly introducing a latent variable coding for abnormalities. A tractable solution to this augmented superimposition problem is obtained using Expectation-Maximization. The topography of detected abnormalities is encoded in a dysmorphogram.</p> <p>Results</p> <p>We demonstrate the use of dysmorphometrics to measure abrupt changes in time, asymmetry and discordancy in a set of human faces presenting with facial abnormalities.</p> <p>Conclusion</p> <p>The results clearly illustrate the unique power to reveal unusual form differences given only normative data with clear applications in both biomedical practice & research.</p

Clinico-radiological features, molecular spectrum, and identification of prognostic factors in developmental and epileptic encephalopathy due to inosine triphosphate pyrophosphatase (ITPase) deficiency

Developmental and epileptic encephalopathy 35 (DEE 35) is a severe neurological condition caused by biallelic variants in ITPA, encoding inosine triphosphate pyrophosphatase, an essential enzyme in purine metabolism. We delineate the genotypic and phenotypic spectrum of DEE 35, analyzing possible predictors for adverse clinical outcomes. We investigated a cohort of 28 new patients and reviewed previously described cases, providing a comprehensive characterization of 40 subjects. Exome sequencing was performed to identify underlying ITPA pathogenic variants. Brain MRI (magnetic resonance imaging) scans were systematically analyzed to delineate the neuroradiological spectrum. Survival curves according to the Kaplan–Meier method and log-rank test were used to investigate outcome predictors in different subgroups of patients. We identified 18 distinct ITPA pathogenic variants, including 14 novel variants, and two deletions. All subjects showed profound developmental delay, microcephaly, and refractory epilepsy followed by neurodevelopmental regression. Brain MRI revision revealed a recurrent pattern of delayed myelination and restricted diffusion of early myelinating structures. Congenital microcephaly and cardiac involvement were statistically significant novel clinical predictors of adverse outcomes. We refined the molecular, clinical, and neuroradiological characterization of ITPase deficiency, and identified new clinical predictors which may have a potentially important impact on diagnosis, counseling, and follow-up of affected individuals

Clinico-radiological features, molecular spectrum, and identification of prognostic factors in developmental and epileptic encephalopathy due to inosine triphosphate pyrophosphatase (ITPase) deficiency.

Developmental and epileptic encephalopathy 35 (DEE 35) is a severe neurological condition caused by biallelic variants in ITPA, encoding inosine triphosphate pyrophosphatase, an essential enzyme in purine metabolism. We delineate the genotypic and phenotypic spectrum of DEE 35, analyzing possible predictors for adverse clinical outcomes. We investigated a cohort of 28 new patients and reviewed previously described cases, providing a comprehensive characterization of 40 subjects. Exome sequencing was performed to identify underlying ITPA pathogenic variants. Brain MRI (magnetic resonance imaging) scans were systematically analyzed to delineate the neuroradiological spectrum. Survival curves according to the Kaplan-Meier method and log-rank test were used to investigate outcome predictors in different subgroups of patients. We identified 18 distinct ITPA pathogenic variants, including 14 novel variants, and two deletions. All subjects showed profound developmental delay, microcephaly, and refractory epilepsy followed by neurodevelopmental regression. Brain MRI revision revealed a recurrent pattern of delayed myelination and restricted diffusion of early myelinating structures. Congenital microcephaly and cardiac involvement were statistically significant novel clinical predictors of adverse outcomes. We refined the molecular, clinical, and neuroradiological characterization of ITPase deficiency, and identified new clinical predictors which may have a potentially important impact on diagnosis, counseling, and follow-up of affected individuals

Estimation of Interaction Potentials through the Configurational Temperature Formalism

Molecular interaction potentials are difficult to measure experimentally and hard to compute from first principles, especially for large systems such as proteins. It is therefore desirable to estimate the potential energy that underlies a thermodynamic ensemble from simulated or experimentally determined configurations. This inverse problem of statistical mechanics is challenging because the various potential energy terms can exhibit subtle indirect and correlated effects on the resulting ensemble. A direct approach would try to adapt the force field parameters such that the given configurations are highly probable in the resulting ensemble. But this would require a full simulation of the system whenever a parameter changes. We introduce an extension of the configurational temperature formalism that allows us to circumvent these difficulties and efficiently estimate interaction potentials from molecular configurations. We illustrate the approach for various systems including fluids and a coarse-grained protein model

Calibration of Boltzmann distribution priors in Bayesian data analysis

The Boltzmann distribution is commonly used as a prior probability in Bayesian data analysis. Examples include the Ising model in statistical image analysis and the canonical ensemble based on molecular dynamics force fields in protein structure calculation. These models involve a temperature or weighting factor that needs to be inferred from the data. Bayesian inference stipulates to determine the temperature based on the model evidence. This is challenging because the model evidence, a ratio of two high-dimensional normalization integrals, cannot be calculated analytically. We outline a replica-exchange Monte Carlo scheme that allows us to estimate the model evidence by use of multiple histogram reweighting. The method is illustrated for an Ising model and examples in protein structure determination