320 research outputs found

    Electron Transport through Single and Multiple Quantum Dots:The Formation of a One-Dimensional Bandstructure

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    We describe transport experiments performed on ballistic submicron devices which are defined in the two dimensional electron gas of GaAs/AlGaAs heterostructures by means of metallic gates. Conductance measurements on single quantum dots reveal the formation of magnetically induced zero-dimensional (0D) states. In an array of 15 coupled quantum dots, these 0D-states develop into a 1D bandstructure

    The 5T mouse multiple myeloma model: absence of c-myc oncogene rearrangement in early transplant generations.

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    Consistent chromosomal translocations involving the c-myc cellular oncogene and one of the three immunoglobin loci are typical for human Burkitt's lymphoma, induced mouse plasmacytoma (MPC) and spontaneously arising rat immunocytoma (RIC). Another plasma cell malignancy, multiple myeloma (MM), arising spontaneously in the ageing C57BL/KaLwRij mice, was investigated in order to see whether the MM cells contain c-myc abnormalities of the MPC or RIC type. Rearrangement of the c-myc oncogene was found in the bone marrow cells only in 5T2 MM transplantation line in a mouse of the 24th generation and in none of the seven other MM of the 5T series which were of earlier generations. Since the mouse 5T MM resembles the human MM very closely, including the absence of consistent structural c-myc oncogene abnormalities, it can serve as a useful experimental model for studies on the aetiopathogenesis of this disease

    Ebstein’s anomaly may be caused by mutations in the sarcomere protein gene MYH7

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    Ebstein's anomaly is a rare congenital heart malformation characterised by adherence of the septal and posterior leaflets of the tricuspid valve to the underlying myocardium. Associated abnormalities of left ventricular morphology and function including left ventricular noncompaction (LVNC) have been observed. An association between Ebstein's anomaly with LVNC and mutations in the sarcomeric protein gene MYH7, encoding β-myosin heavy chain, has been shown by recent studies. This might represent a specific subtype of Ebstein's anomaly with a Mendelian inheritance pattern. In this review we discuss the association of MYH7 mutations with Ebstein's anomaly and LVNC and its implications for the clinical care for patients and their family members.Congenital Heart Diseas

    Relative contribution of mutations in genes for autosomal dominant distal hereditary motor neuropathies: a genotype-phenotype correlation study

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    Distal hereditary motor neuropathy (HMN) is a clinically and genetically heterogeneous group of disorders affecting spinal α-motor neurons. Since 2001, mutations in six different genes have been identified for autosomal dominant distal HMN; glycyl-tRNA synthetase (GARS), dynactin 1 (DCTN1), small heat shock 27 kDa protein 1 (HSPB1), small heat shock 22 kDa protein 8 (HSPB8), Berardinelli-Seip congenital lipodystrophy (BSCL2) and senataxin (SETX). In addition a mutation in the (VAMP)-associated protein B and C (VAPB) was found in several Brazilian families with complex and atypical forms of autosomal dominantly inherited motor neuron disease. We have investigated the distribution of mutations in these seven genes in a cohort of 112 familial and isolated patients with a diagnosis of distal motor neuropathy and found nine different disease-causing mutations in HSPB8, HSPB1, BSCL2 and SETX in 17 patients of whom 10 have been previously reported. No mutations were found in GARS, DCTN1 and VAPB. The phenotypic features of patients with mutations in HSPB8, HSPB1, BSCL2 and SETX fit within the distal HMN classification, with only one exception; a C-terminal HSPB1-mutation was associated with upper motor neuron signs. Furthermore, we provide evidence for a genetic mosaicism in transmitting an HSPB1 mutation. This study, performed in a large cohort of familial and isolated distal HMN patients, clearly confirms the genetic and phenotypic heterogeneity of distal HMN and provides a basis for the development of algorithms for diagnostic mutation screening in this group of disorder

    Lack of evidence for a causal role of CALR3 in monogenic cardiomyopathy

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    The pathogenicity of previously published disease-associated genes and variants is sometimes questionable. Large-scale, population-based sequencing studies have uncovered numerous false assignments of pathogenicity. Misinterpretation of sequence variants may have serious implications for the patients and families involved, as genetic test results are increasingly being used in medical decision making. In this study, we assessed the role of the calreticulin-3 gene (CALR3) in cardiomyopathy. CALR3 has been included in several cardiomyopathy gene panels worldwide. Its inclusion is based on a single publication describing two missense variants in patients with hypertrophic cardiomyopathy. In our national cardiomyopathy cohort (n = 6154), we identified 17 unique, rare heterozygous CALR3 variants in 48 probands. Overall, our patient cohort contained a significantly higher number of rare CALR3 variants compared to the ExAC population (p = 0.0036). However, after removing a potential Dutch founder variant, no statistically significant difference was found (p = 0.89). In nine probands, the CALR3 variant was accompanied by a disease-causing variant in another, well-known cardiomyopathy gene. In three families, the CALR3 variant did not segregate with the disease. Furthermore, we could not demonstrate calreticulin-3 protein expression in myocardial tissues at various ages. On the basis of these findings, it seems highly questionable that variants in CALR3 are a monogenic cause of cardiomyopathy

    A mutation update for the FLNC gene in myopathies and cardiomyopathies

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    Filamin C (FLNC) variants are associated with cardiac and muscular phenotypes. Originally, FLNC variants were described in myofibrillar myopathy (MFM) patients. Later, high-throughput screening in cardiomyopathy cohorts determined a prominent role for FLNC in isolated hypertrophic and dilated cardiomyopathies (HCM and DCM). FLNC variants are now among the more prevalent causes of genetic DCM. FLNC-associated DCM is associated with a malignant clinical course and a high risk of sudden cardiac death. The clinical spectrum of FLNC suggests different pathomechanisms related to variant types and their location in the gene. The appropriate functioning of FLNC is crucial for structural integrity and cell signaling of the sarcomere. The secondary protein structure of FLNC is critical to ensure this function. Truncating variants with subsequent haploinsufficiency are associated with DCM and cardiac arrhythmias. Interference with the dimerization and folding of the protein leads to aggregate formation detrim

    A mutation update for the FLNC gene in myopathies and cardiomyopathies

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    Filamin C (FLNC) variants are associated with cardiac and muscular phenotypes. Originally, FLNC variants were described in myofibrillar myopathy (MFM) patients. Later, high-throughput screening in cardiomyopathy cohorts determined a prominent role for FLNC in isolated hypertrophic and dilated cardiomyopathies (HCM and DCM). FLNC variants are now among the more prevalent causes of genetic DCM. FLNC-associated DCM is associated with a malignant clinical course and a high risk of sudden cardiac death. The clinical spectrum of FLNC suggests different pathomechanisms related to variant types and their location in the gene. The appropriate functioning of FLNC is crucial for structural integrity and cell signaling of the sarcomere. The secondary protein structure of FLNC is critical to ensure this function. Truncating variants with subsequent haploinsufficiency are associated with DCM and cardiac arrhythmias. Interference with the dimerization and folding of the protein leads to aggregate formation detrimental for muscle function, as found in HCM and MFM. Variants associated with HCM are predominantly missense variants, which cluster in the ROD2 domain. This domain is important for binding to the sarcomere and to ensure appropriate cell signaling. We here review FLNC genotype–phenotype correlations based on available evidence

    Targeting Protein-Protein Interactions for Parasite Control

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    Finding new drug targets for pathogenic infections would be of great utility for humanity, as there is a large need to develop new drugs to fight infections due to the developing resistance and side effects of current treatments. Current drug targets for pathogen infections involve only a single protein. However, proteins rarely act in isolation, and the majority of biological processes occur via interactions with other proteins, so protein-protein interactions (PPIs) offer a realm of unexplored potential drug targets and are thought to be the next-generation of drug targets. Parasitic worms were chosen for this study because they have deleterious effects on human health, livestock, and plants, costing society billions of dollars annually and many sequenced genomes are available. In this study, we present a computational approach that utilizes whole genomes of 6 parasitic and 1 free-living worm species and 2 hosts. The species were placed in orthologous groups, then binned in species-specific ortholgous groups. Proteins that are essential and conserved among species that span a phyla are of greatest value, as they provide foundations for developing broad-control strategies. Two PPI databases were used to find PPIs within the species specific bins. PPIs with unique helminth proteins and helminth proteins with unique features relative to the host, such as indels, were prioritized as drug targets. The PPIs were scored based on RNAi phenotype and homology to the PDB (Protein DataBank). EST data for the various life stages, GO annotation, and druggability were also taken into consideration. Several PPIs emerged from this study as potential drug targets. A few interactions were supported by co-localization of expression in M. incognita (plant parasite) and B. malayi (H. sapiens parasite), which have extremely different modes of parasitism. As more genomes of pathogens are sequenced and PPI databases expanded, this methodology will become increasingly applicable
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