Structure and Vibrational Spectroscopy of C82 Fullerenol Valent Isomers: An Experimental and Theoretical Joint Study.

Gd@C82OxHy endohedral complexes for advanced biomedical applications (computer tomography, cancer treatment, etc.) were synthesized using high-frequency arc plasma discharge through a mixture of graphite and Gd2O3 oxide. The Gd@C82 endohedral complex was isolated by high-efficiency liquid chromatography and consequently oxidized with the formation of a family of Gd endohedral fullerenols with gross formula Gd@C82O8(OH)20. Fourier-transformed infrared (FTIR) spectroscopy was used to study the structure and spectroscopic properties of the complexes in combination with the DFTB3 electronic structure calculations and infrared spectra simulations. It was shown that the main IR spectral features are formed by a fullerenole C82 cage that allows one to consider the force constants at the DFTB3 level of theory without consideration of gadolinium endohedral ions inside the carbon cage. Based on the comparison of experimental FTIR and theoretical DFTB3 IR spectra, it was found that oxidation of the C82 cage causes the formation of Gd@C82O28H20, with a breakdown of the integrity of the parent C82 cage with the formation of pores between neighboring carbonyl and carboxyl groups. The Gd@C82O6(OOH)2(OH)18 endohedral complex with epoxy, carbonyl and carboxyl groups was considered the most reliable fullerenole structural model.

Central hubs prediction for bio networks by directed hypergraph - GA with validation to COVID-19 PPI.

Network structures have attracted much interest and have been rigorously studied in the past two decades. Researchers used many mathematical tools to represent these networks, and in recent days, hypergraphs play a vital role in this analysis. This paper presents an efficient technique to find the influential nodes using centrality measure of weighted directed hypergraph. Genetic Algorithm is exploited for tuning the weights of the node in the weighted directed hypergraph through which the characterization of the strength of the nodes, such as strong and weak ties by statistical measurements (mean, standard deviation, and quartiles) is identified effectively. Also, the proposed work is applied to various biological networks for identification of influential nodes and results shows the prominence the work over the existing measures. Furthermore, the technique has been applied to COVID-19 viral protein interactions. The proposed algorithm identified some critical human proteins that belong to the enzymes TMPRSS2, ACE2, and AT-II, which have a considerable role in hosting COVID-19 viral proteins and causes for various types of diseases. Hence these proteins can be targeted in drug design for an effective therapeutic against COVID-19.

A Novel Drug Design Strategy: An Inspiration from Encaging Tumor by Metallofullerenol Gd@C82(OH)22.

Cancer remains a major threat to human health worldwide. Cytotoxicity has imposed restrictions on the conventional cytotoxic drug-based chemotherapy. The rapidly-developing nanomedicine has shown great promise in revolutionizing chemotherapy with improved efficiency and reduced toxicity. Gd@C82(OH)22, a novel endohedral metallofullerenol, was first reported by our research group to suppress tumor growth and metastasis efficiently without obvious toxicity. Gd@C82(OH)22 imprisons tumors by facilitating the formation of surrounding fibrous layers which is different from chemotherapeutics that poison tumor cells. In this review, the authors first reported the antineoplastic activity of metallofullerenol Gd@C82(OH)22 followed by further discussions on its new anti-cancer molecular mechanism-tumor encaging. On this basis, the unparalleled advantages of nanomedicine in the future drug design are discussed. The unique interaction modes of Gd@C82(OH)22 with specific targeted biomolecules may shed light on a new avenue for drug design. Depending on the surface characteristics of target biomolecules, nanomedicine, just like a transformable and dynamic key, can self-assemble into suitable shapes to match several locks for the thermodynamic stability, suggesting the target-tailoring ability of nanomedicine.

EIGENVECTOR-BASED CENTRALITY MEASURES FOR TEMPORAL NETWORKS.

Numerous centrality measures have been developed to quantify the importances of nodes in time-independent networks, and many of them can be expressed as the leading eigenvector of some matrix. With the increasing availability of network data that changes in time, it is important to extend such eigenvector-based centrality measures to time-dependent networks. In this paper, we introduce a principled generalization of network centrality measures that is valid for any eigenvector-based centrality. We consider a temporal network with N nodes as a sequence of T layers that describe the network during different time windows, and we couple centrality matrices for the layers into a supra-centrality matrix of size NT × NT whose dominant eigenvector gives the centrality of each node i at each time t. We refer to this eigenvector and its components as a joint centrality, as it reflects the importances of both the node i and the time layer t. We also introduce the concepts of marginal and conditional centralities, which facilitate the study of centrality trajectories over time. We find that the strength of coupling between layers is important for determining multiscale properties of centrality, such as localization phenomena and the time scale of centrality changes. In the strong-coupling regime, we derive expressions for time-averaged centralities, which are given by the zeroth-order terms of a singular perturbation expansion. We also study first-order terms to obtain first-order-mover scores, which concisely describe the magnitude of nodes' centrality changes over time. As examples, we apply our method to three empirical temporal networks: the United States Ph.D. exchange in mathematics, costarring relationships among top-billed actors during the Golden Age of Hollywood, and citations of decisions from the United States Supreme Court.

Reaction Mechanism and Regioselectivity of the Bingel-Hirsch Addition of Dimethyl Bromomalonate to La@C2v -C82.

We quantum chemically explore the thermodynamics and kinetics of all 65 possible mechanistic pathways of the Bingel-Hirsch addition of dimethyl bromomalonate to the endohedral metallofullerene La@C2v -C82 that result from the combination of 24 nonequivalent carbon atoms and 35 different bonds present in La@C2v -C82 by using dispersion-corrected DFT calculations. Experimentally, this reaction leads to four singly bonded derivatives and one fulleroid adduct. Of these five products, only the singly bonded derivative on C23 could be experimentally identified unambiguously. Our calculations show that La@C2v -C82 is not particularly regioselective under Bingel-Hirsch conditions. From the obtained results, however, it is possible to make a tentative assignment of the products observed experimentally. We propose that the observed fulleroid adduct results from the attack at bond 19 and that the singly bonded derivatives correspond to the C2, C19, C21, and C23 initial attacks. However, other possibilities cannot be ruled out completely.

Caging cancer.

This article summarizes the overall issues surrounding cancer for the general audience. Individual differences between patients include genetic and non-genetic differences manifested in various cellular pathways, tumor heterogeneity and variability, differing contribution of tumor microenvironment and potential toward metastasis. Successful treatment of individuals depends on correctly interpreting all these factors and appropriately addressing the actual features by using customized therapy strategies, simultaneously or sequentially. Currently used chemotherapy agents are cytotoxic and typically target one of the major pathways; therefore they have to be applied in combination regimes. Nanomedicines however, have the potential advantage that more than one feature can be built into a complex nanodevice. This yet untapped potential is illustrated on the example of a gadolinium fullerenol cage molecule. Gd@C82(OH)22 has low toxicity, influences several biologic features simultaneously, displays tumoristatic properties, and is effective against triple-negative breast cancer cells. A deeper understanding of the exact relations between the physicochemical characteristics of this system and the biologic events may lead to a new class of efficient anticancer pharmaceutics. FROM THE CLINICAL EDITOR: The search for the magic bullet in the treatment of cancer has long been the dream of clinicians and researchers worldwide. Inherent cellular characteristics of cancer cells have made this task extremely hard to reach. In this article, the author provided a concise summary on the understanding and challenges in the current battle and also illustrated the potential usefulness of the recently developed gadolinium fullerenol cage molecule by describing experimental data from various research groups.

Thermodynamically stable [4 + 2] cycloadducts of lanthanum-encapsulated endohedral metallofullerenes.

The [4 + 2] cycloaddition of o-quinodimethanes, generated in situ from the sultine 4,5-benzo-3,6-dihydro-1,2-oxathiin 2-oxide and its derivative, to La metal-encapsulated fullerenes, La2@C80 or La@C82, afforded the novel derivatives of endohedral metallofullerenes (3a,b, 4a,b and 5b). Molecular structures of the resulting compounds were elucidated using spectroscopic methods such as MALDI-TOF mass, optical absorption, and NMR spectroscopy. The [4 + 2] adducts of La2@C80 (3a,b, and 4a,b) and La@C82 (5b), respectively, retain diamagnetic and paramagnetic properties, as confirmed by EPR spectroscopy. Dynamic NMR measurements of 4a at various temperatures demonstrated the boat-to-boat inversions of the addend. In addition, 5b revealed remarkable thermal stability in comparison with the reported [4 + 2] cycloadduct of pentamethylcyclopentadiene and La@C82 (6). These findings demonstrate the utility of sultines to afford thermodynamically stable endohedral metallofullerene derivatives for the use in material science.

Healthcare resource utilization and associated costs in patients with metastatic urothelial carcinoma: a real-world analysis using German claims data.

AIMS: This retrospective claims data study characterized real-world treatment patterns, healthcare resource utilization (HCRU), and costs in patients with metastatic urothelial carcinoma (mUC) in Germany. MATERIALS AND METHODS: Continuously insured adults with incident mUC diagnosis (=index; ICD-10: C65-C68/C77-C79) in 2015-2019 were identified from two German claims databases. Patients who received first-line (1 L) treatment within 12 months of index were divided into three mutually exclusive sub-cohorts: platinum-based chemotherapy (PB-CT), non-PB-CT, and immunotherapy (IO). Patient characteristics were assessed during a 24-month baseline period; treatments, HCRU, and costs (of the health insurance fund) per patient-year (ppy) were described during 12-month follow-up. RESULTS: We identified 3,226 patients with mUC (mean age, 73.8 years; male, 70.8%; mean Elixhauser Comorbidity Index, 17.6); 1,286 (39.9%) received 1 L treatment within 12 months of index. Of these, 825 (64.2%) received PB-CT, 322 (25.0%) non-PB-CT, and 139 (10.8%) IO. On average, treated patients had 5.1 hospitalizations ppy. Most UC-related hospitalizations ppy were observed in the PB-CT cohort (5.8), followed by the non-PB-CT (4.2) and IO (2.3) cohorts. Mean UC-related hospitalization costs ppy were €22,218 in the treated cohort, €24,294 in PB-CT, €19,079 in IO, and €18,530 in non-PB-CT cohorts. Cancer-related prescription costs ppy averaged €6,323 in treated patients, and €25,955 in IO, €4,318 in non-PB-CT, and €4,270 in PB-CT cohorts. LIMITATIONS: We recognized limitations in our study's sample selection due to unavailable mUC disease status data. We addressed this through an upstream feasibility study conducted in consultation with clinical experts to determine a suitable proxy. Proxies were also used to delineate treatment lines, switches, and discontinuations due to data absence. Furthermore, due to data restrictions, collective dataset analysis was not possible, prompting a meta-analysis for pooled results. CONCLUSIONS: The study shows that mUC is associated with significant HCRU and costs across different types of 1 L systemic therapy.

Rational Design of Dual-Functionalized Gd@C82 Nanoparticles to Relieve Neuronal Cytotoxicity in Alzheimer's Disease via Inhibition of Aß Aggregation.

The accumulation of amyloid-ß (Aß) peptides is a major hallmark of Alzheimer's disease (AD) and plays a crucial role in its pathogenesis. Particularly, the structured oligomeric species rich in ß-sheet formations were implicated in neuronal organelle damage. Addressing this formidable challenge requires identifying candidates capable of inhibiting peptide aggregation or disaggregating preformed oligomers for effective antiaggregation-based AD therapy. Here, we present a dual-functional nanoinhibitor meticulously designed to target the aggregation driving force and amyloid fibril spatial structure. Leveraging the exceptional structural stability and facile tailoring capability of endohedral metallofullerene Gd@C82, we introduce desired hydrogen-binding sites and charged groups, which are abundant on its surface for specific designs. Impressively, these designs endow the resultant functionalized-Gd@C82 nanoparticles (f-Gd@C82 NPs) with high capability of redirecting peptide self-assembly toward disordered, off-pathway species, obstructing the early growth of protofibrils, and disaggregating the preformed well-ordered protofibrils or even mature Aß fibrils. This results in considerable alleviation of Aß peptide-induced neuronal cytotoxicity, rescuing neuronal death and synaptic loss in primary neuron models. Notably, these modifications significantly improved the dispersibility of f-Gd@C82 NPs, thus substantially enhancing its bioavailability. Moreover, f-Gd@C82 NPs demonstrate excellent cytocompatibility with various cell lines and possess the ability to penetrate the blood-brain barrier in mice. Large-scale molecular dynamics simulations illuminate the inhibition and disaggregation mechanisms. Our design successfully overcomes the limitations of other nanocandidates, which often overly rely on hydrophobic interactions or photothermal conversion properties, and offers a viable direction for developing anti-AD agents through the inhibition and even reversal of Aß aggregation.

An exploration on the topologies of SARS-CoV-2/human protein-protein interaction network.

Network biology is an important finding that uncovers the significant elements in viral infection control. Since viruses use the proteins on their surfaces to attach and enter into the host cell, the establishment of virus-host protein interactions is a potent regulator of the global organization of the viral life cycle after virus entry into host cells. In this instance, a topological study on the SARS-CoV-2/Human Protein-Protein Interaction Network (PPIN) evacuates much information about the protein-protein interactions. By making some interruptions to the interaction between proteins and hosts, we can quickly reduce the spread of the disease and get an insight into the target protein for drug development. This paper mainly focused on the graphical and structural complexity of the SARS-CoV-2/Human PPIN. For this purpose, the various primary (distance, radius, diameter, etc…) and advanced levels of graph measures (density, modularity, clustering coefficient, etc…) as well as a few fractal (box dimension, multifractal analysis) and entropy measures have been used. In addition, several graph descriptions and distribution graphs of PPIN offered to gain a thorough understanding of the SARS-CoV-2/Human PPIN. Conclusively, based on our work, we have discovered that PPIN is moderately complex and identified that hiring Nsp8 as a target node will positively affect the PPIN and has pointed out that mathematically found target proteins are matched with already suggested target proteins in the previous survey.Communicated by Ramaswamy H. Sarma.

On Nordhaus-Gaddum type relations of δ-complement graphs.

The δ-complement graphs were introduced by Amrithalakshmi et al. in 2022. In their work, some interesting properties of the graphs such as δ-self-complementary, adjacency, and hamiltonicity were studied. In this work, we study the coloring aspect of the δ-complement graphs. In particular, we provide lower and upper bounds on the product and the summation between the chromatic number and the δ-chromatic number of a graph, in the same fashion as the well-known Nordhaus-Gaddum type relations. Classes of graphs that achieve those bounds are also given. Furthermore, we provide upper bounds on δ-chromatic numbers in terms of the clique numbers and compute the δ-chromatic numbers of certain graphs including ladder graphs, path graphs, complete m-partite graphs, and small-world Farey graphs.

Gd@C82 metallofullerenes for neutron capture therapy-fullerene solubilization by poly(ethylene glycol)-block-poly(2-(N, N-diethylamino)ethyl methacrylate) and resultant efficacy in vitro.

Poly(ethylene glycol)-block-poly(2-(N,N-diethylamino)ethyl methacrylate) (PEG-b-PAMA) was found to solubilize fullerenes such as C60, and this technique was applied to metallofullerenes. Gd@C82 was easily dissolved in water in the presence of PEG-b-PAMA without any covalent derivatization, forming a transparent complex about 20-30 nm in diameter. Low cytotoxicity was confirmed in vitro. Neutron irradiation of cultured cells (colon-26 adenocarcinoma) with Gd@C82-PEG-b-PAMA-complexed nanoparticles showed effective cytotoxicity, indicating the effective emission of gamma rays and internal conversion electrons produced from the neutron capture reaction of Gd. This result suggests a potentially valuable approach to gadolinium-based neutron capture therapy.

Pairwise influences in dynamic choice: network-based model and application.

In this paper, we study the problem of network discovery and influence propagation, and propose an integrated approach for the analysis of lead-lag synchronization in multiple choices. Network models for the processes by which decisions propagate through social interaction have been studied before, but only a few consider unknown structures of interacting agents. In fact, while individual choices are typically observed, inferring individual influences - who influences who - from sequences of dynamic choices requires strong modeling assumptions on the cross-section dependencies of the observed panels. We propose a class of parametric models which extends the vector autoregression to the case of pairwise influences between individual choices over multiple items and supports the analysis of influence propagation. After uncovering a collection of theoretical properties (conditional moments, parameter sensitivity, identifiability and estimation), we provide an economic application to music broadcasting, where a set of songs are diffused over radio stations; we infer station-to-station influences based on the proposed methodology and assess the propagation effect of initial launching stations to maximize songs diffusion. Both on the theoretical and empirical sides, the proposed approach connects fields which are traditionally treated as separated areas: the problem of network discovery and the one of influence propagation.

Costs of in-house genomic profiling and implications for economic evaluation: a case example of non-small cell lung cancer (NSCLC).

OBJECTIVES: Genomic profiling in oncology is vital for determining eligible patients for mutation-specific targeted therapies. Use of commercial genomic testing has the potential to improve patient outcomes. Economic evaluations of in-house genomic profiling typically only include material costs while external commercial services include many other factors. Using non-small cell lung cancer (NSCLC) as an example, this study sought to characterize the unique challenges of costing testing services and their impact on results of economic evaluations. METHODS: Structured interviews with Canadian oncologists, pathologists, and laboratory directors were conducted to identify material and non-material costs associated with genomic-testing laboratories to allow estimation of a more complete cost of in-house testing, with NSCLC cost-per-test calculated using annual operational costs and NSCLC-specific testing volume. A health and budget impact model of in-house versus external commercial profiling services was used to compare the impact of non-material costs on results. RESULTS: In-house testing costs, limited to materials, was $133/single-gene test and $1,400/panel. For a laboratory running 1,300 in-house tests/year, total annual non-material costs included equipment maintenance ($6,842), labor ($502,313; technicians, administrative, and medical staff), shipping/reporting and software updates ($146,050), for an additional $519/test. The combined cost of $652/single-gene and $1,919/panel was compared to a cost of $6,194 for a commercial external test. Based on current Canadian testing patterns and anticipated utilization of external testing, inclusion of in-house non-material costs reduced the estimated 3-year budget impact by 12%. CONCLUSION: When conducting economic evaluation to assess the value of introducing external tests, it is critical that non-material costs of standard testing strategies be measured and incorporated.

Clinical Probe of Cyp2C8*2 Mutants in a Malaria Hyperendemic Zone: Evidence from North-Central, Nigeria.

BACKGROUND: A tremendous level of success has been achieved since the introduction of chloroquine and the combination of amodiaquine and artemisinin for the treatment of both complicated and uncomplicated malaria infections in sub-Saharan Africa. However, the recent discovery of drug resistant strains of Plasmodium falciparum (P.f.) and the ability of the parasite to ingest CYP2C8 into its digestive vacuole is of great public health concern. This study probes the occurrence of CYP2C8*2 allelic mutant amongst malaria patients in North-Central Nigeria. METHODS: Three hundred and eighty five (385) unrelated study participants were screened for current malaria episodes using routine microscopy and/or rapid diagnostic test strips (RDTs). Chelex extraction method was used for single nucleotide polymorphisms (SNPs) and identification of CYP2C8*2 (805A > T) variant respectively. Wild-type (A) and the defective allele (T) were differentiated with the use of Polymerase Chain Reaction-Restriction Fragment Length Polymorphism (PCR-RFLP). The results obtained were further validated with Sanger sequencing of a few samples and thereafter, the genotype data were statistically processed. All alleles obtained were in Hardy Weinberg equilibrium. RESULTS: Out of the 385 participants (45.5% Male and 54.5% Female) genotyped for SNPs, 75 (19.5%) had the autosomal recessive mutant trait. Occurrence of mutant traits was gender and ethnic independent (p > 0.05). Yoruba ethnic group recorded a reduction in proportion of genotypic defective CYP2C8*2 allele (T) (1 in every 8 persons) with a carrier percentage of 13.3% compared with Hausa (26.62%); Igbo (25.37%) and other minority ethnic groups (17.6%). CONCLUSIONS: A remarkable inter-ethnic differences in autosomal recessive CYP2C8*2 allele was observed. By implication, there is a gradual incursion of genetic drift for poor CQ and AQ-Artemisinin metabolizers among the inhabitants.

NETWORK-ENSEMBLE COMPARISONS WITH STOCHASTIC REWIRING AND VON NEUMANN ENTROPY.

Assessing whether a given network is typical or atypical for a random-network ensemble (i.e., network-ensemble comparison) has widespread applications ranging from null-model selection and hypothesis testing to clustering and classifying networks. We develop a framework for network-ensemble comparison by subjecting the network to stochastic rewiring. We study two rewiring processes-uniform and degree-preserved rewiring-which yield random-network ensembles that converge to the Erdos-Rényi and configuration-model ensembles, respectively. We study convergence through von Neumann entropy (VNE)-a network summary statistic measuring information content based on the spectra of a Laplacian matrix-and develop a perturbation analysis for the expected effect of rewiring on VNE. Our analysis yields an estimate for how many rewires are required for a given network to resemble a typical network from an ensemble, offering a computationally efficient quantity for network-ensemble comparison that does not require simulation of the corresponding rewiring process.

Lu2@C82 Nanorods with Enhanced Photoluminescence and Photoelectrochemical Properties.

One-dimensional (1D) single-crystalline hexagonal nanorods of Lu2@C3v(8)-C82 were prepared for the first time using the liquid-liquid interface precipitation (LLIP) method from the interfaces between carbon disulfide (CS2) and isopropyl alcohol (IPA). The length of the nanorods can be readily controlled by varying the concentration of the Lu2@C82 solution in addition to the volume ratio of CS2 to IPA. The latter factor also exhibits a significant influence on the morphology of the crystals. The crystalline structure of the nanorods has been investigated by XRD and selected area electron diffraction (SAED), suggesting a face-centered cubic structure. Photoluminescence of the Lu2@C82 nanorods shows a remarkable enhancement as compared to that of pristine Lu2@C82 powder because of the high crystallinity. Furthermore, we have investigated the photoelectrochemical properties of Lu2@C82 nanorods, proving their potential applications as photodetectors.

Gd@C82-(ethylenediamine)8 Nanoparticle: A New High-Efficiency Water-Soluble ROS Scavenger.

It is important to maintain a reactive oxygen species (ROS) balance in organisms; thus, a valid ROS scavenger with good biocompatibility is urgently required. To prepare a high-efficiency ROS scavenger, multiple ethylenediamine (EDA) groups are bonded for the first time to a metallofullerene Gd@C82 to obtain water-soluble Gd@C82-(EDA)8 nanoparticles (NPs) through a facile solid-liquid reaction. Gd@C82-(EDA)8 NPs with a relatively better conjugation possess an excellent capability to scavenge hydroxyl radicals. Moreover, Gd@C82-(EDA)8 NPs exhibited a remarkable cytoprotective effect against H2O2-induced injuries to human epidermal keratinocytes-adult (HEK-a) cells at a low concentration of 2.5 µM. In contrast, Gd@C82-(OH)26 NPs that modified with hydroxyls show an apparent protective effect at a much higher concentration of 40 µM. This outstanding cytoprotective performance of Gd@C82-(EDA)8 NPs is mainly attributed to their extremely high cellular uptake and comparably strong conjugation. Gd@C82-(EDA)8 NPs with good biocompatibility exhibit excellent ROS scavenging capability even at a significantly low concentration, which promotes its versatile applications in cosmetics and biomedicine.

Gd-Metallofullerenol Nanomaterial Suppresses Pancreatic Cancer Metastasis by Inhibiting the Interaction of Histone Deacetylase 1 and Metastasis-Associated Protein 1.

The treatment of pancreatic cancer frequently fails due to local recurrence and hepatic metastasis. Our previous study found that Gd@C82(OH)22 can suppress pancreatic cancer by inhibiting MMP-2/9 expression. In this study, we further explored the epigenetic mechanism of Gd@C82(OH)22 in human pancreatic cancer metastasis. Gd@C82(OH)22 suppressed tumor metastasis through down-regulation of metastasis-associated protein 1 (MTA1), HDAC1, HIF-1α, and MMP-2/9 and up-regulation of reversion-cysteine protein with the Kazal motif (RECK). The level of acetylation was increased in the promoter region of the RECK gene after Gd@C82(OH)22 treatment. The interaction of MTA1, HDAC1, and HIF-1α was inhibited by Gd@C82(OH)22. Furthermore, large-scale molecular dynamics simulations revealed Gd@C82(OH)22 could serve as an effective HDAC inhibitor to the protein-protein association between HDAC1 and MTA1, especially through MTA1's SANT and ELM2 dimerization domains. Our findings implicate Gd@C82(OH)22 as a novel HDAC inhibitor acting to increase RECK expression by suppressing the MTA1/HDAC1 co-repressor complex. Gd@C82(OH)22 may serve as a potential HDAC1 inhibitor to suppress pancreatic cancer cell invasion and metastasis both in vitro and in vivo. According to computer analysis and experimental validation, Gd@C82(OH)22 activates RECK expression by inhibiting the interaction of HDAC1 and MTA1.

Cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) associated with a novel C82R mutation in the NOTCH3 gene.

Cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) is a rare inherited cerebrovascular disease associated with mutations in the NOTCH3 gene on chromosome 19, and represents the most common hereditary stroke disorder. We describe a pedigree, which suffered the classical clinical CADASIL pattern of migraine headaches, recurrent subcortical infarcts, and subcortical dementia, associated with a previously undescribed missense mutation (c.[244T>C], p.[C82R]) in NOTCH3. This new mutation extends the list of known pathogenic mutations responsible for CADASIL, which are associated with an odd number of cysteine residues within any of the epidermal growth factor-like repeats of Notch3 receptor protein.