Short-patch correction of C/C mismatches in human cells

We examined whether the human nucleotide excision repair complex, which is specialized on the removal of bulky DNA adducts, also displays a correcting activity on base mismatches. The cytosine/cytosine (C/C) lesion was used as a model substrate to monitor the correction of base mismatches in human cells. Fibroblasts with different repair capabilities were transfected with shuttle vectors that contain a site-directed C/C mismatch in the replication origin, accompanied by an additional C/C mismatch in one of the flanking sequences that are not essential for replication. Analysis of the vector progeny obtained from these doubly modified substrates revealed that C/C mismatches were eliminated before DNA synthesis not only in the repair-proficient background, but also when the target cells carried a genetic defect in long-patch mismatch repair, in nucleotide excision repair, or when both pathways were deleted. Furthermore, cells deficient for long-patch mismatch repair as well as a cell line that combines mismatch and nucleotide excision repair defects were able to correct multiple C/C mispairs, placed at distances of 21-44 nt, in an independent manner, such that the removal of each lesion led to individual repair patches. These results support the existence of a concurrent short-patch mechanism that rectifies C/C mismatche

Incomplete inverse spectral and nodal problems for differential pencils

[[abstract]]We prove uniqueness theorems for so-called half inverse spectral problem (and also for some its modification) for second order differential pencils on a finite interval with Robin boundary conditions. Using the obtained result we show that for unique determination of the pencil it is sufficient to specify the nodal points only on a part of the interval slightly exceeding its half.[[notice]]補正完畢[[incitationindex]]SCI[[booktype]]紙本[[booktype]]電子

Distributed Ledger for Provenance Tracking of Artificial Intelligence Assets

High availability of data is responsible for the current trends in Artificial Intelligence (AI) and Machine Learning (ML). However, high-grade datasets are reluctantly shared between actors because of lacking trust and fear of losing control. Provenance tracing systems are a possible measure to build trust by improving transparency. Especially the tracing of AI assets along complete AI value chains bears various challenges such as trust, privacy, confidentiality, traceability, and fair remuneration. In this paper we design a graph-based provenance model for AI assets and their relations within an AI value chain. Moreover, we propose a protocol to exchange AI assets securely to selected parties. The provenance model and exchange protocol are then combined and implemented as a smart contract on a permission-less blockchain. We show how the smart contract enables the tracing of AI assets in an existing industry use case while solving all challenges. Consequently, our smart contract helps to increase traceability and transparency, encourages trust between actors and thus fosters collaboration between them

Inverse problems for Sturm-Liouville equations with boundary conditions linearly dependent on the spectral parameter from partial information

[[abstract]]Abstract.In this paper, we study the inverse spectral problems for Sturm–Liouville equations with boundary conditions linearly dependent on the spectral parameter and show that the potential of such problem can be uniquely determined from partial information on the potential and parts of two spectra, or alternatively, from partial information on the potential and a subset of pairs of eigenvalues and the normalization constants of the corresponding eigenvalues.[[notice]]補正完畢[[journaltype]]國外[[incitationindex]]SCI[[ispeerreviewed]]Y[[booktype]]紙本[[booktype]]電子版[[countrycodes]]DE

ProphNet: A generic prioritization method through propagation of information

This article has been published as part of BMC Bioinformatics Volume 15 Supplement 1, 2014: Integrated Bio-Search: Selected Works from the 12th International Workshop on Network Tools and Applications in Biology (NETTAB 2012).[Background] Prioritization methods have become an useful tool for mining large amounts of data to suggest promising hypotheses in early research stages. Particularly, network-based prioritization tools use a network representation for the interactions between different biological entities to identify novel indirect relationships. However, current network-based prioritization tools are strongly tailored to specific domains of interest (e.g. gene-disease prioritization) and they do not allow to consider networks with more than two types of entities (e.g. genes and diseases). Therefore, the direct application of these methods to accomplish new prioritization tasks is limited.[Results] This work presents ProphNet, a generic network-based prioritization tool that allows to integrate an arbitrary number of interrelated biological entities to accomplish any prioritization task. We tested the performance of ProphNet in comparison with leading network-based prioritization methods, namely rcNet and DomainRBF, for gene-disease and domain-disease prioritization, respectively. The results obtained by ProphNet show a significant improvement in terms of sensitivity and specificity for both tasks. We also applied ProphNet to disease-gene prioritization on Alzheimer, Diabetes Mellitus Type 2 and Breast Cancer to validate the results and identify putative candidate genes involved in these diseases.[Conclusions] ProphNet works on top of any heterogeneous network by integrating information of different types of biological entities to rank entities of a specific type according to their degree of relationship with a query set of entities of another type. Our method works by propagating information across data networks and measuring the correlation between the propagated values for a query and a target sets of entities. ProphNet is available at: http://genome2.ugr.es/prophnet webcite. A Matlab implementation of the algorithm is also available at the website.This work was part of projects P08-TIC-4299 of J. A., Sevilla and TIN2009-13489 of DGICT, Madrid. It was also supported by Plan Propio de Investigación, University of Granada

Identification of Genes with Allelic Imbalance on 6p Associated with Nasopharyngeal Carcinoma in Southern Chinese

Nasopharyngeal carcinoma (NPC) is a malignancy of epithelial origin. The etiology of NPC is complex and includes multiple genetic and environmental factors. We employed case-control analysis to study the association of chromosome 6p regions with NPC. In total, 360 subjects and 360 healthy controls were included, and 233 single nucleotide polymorphisms (SNPs) on 6p were examined. Significant single-marker associations were found for SNPs rs2267633 (p = 4.49×10−5), rs2076483 (most significant, p = 3.36×10−5), and rs29230 (p = 1.43×10−4). The highly associated genes were the gamma-amino butyric acid B receptor 1 (GABBR1), human leukocyte antigen (HLA-A), and HLA complex group 9 (HCG9). Haplotypic associations were found for haplotypes AAA (located within GABBR1, p-value  = 6.46×10−5) and TT (located within HLA-A, p = 0.0014). Further investigation of the homozygous genotype frequencies between cases and controls suggested that micro-deletion regions occur in GABBR1 and neural precursor cell expressed developmentally down-regulated 9 (NEDD9). Quantitative real-time polymerase chain reaction (qPCR) using 11 pairs of NPC biopsy samples confirmed the significant decline in GABBR1 and NEDD9 mRNA expression in the cancer tissues compared to the adjacent non-tumor tissue (p<0.05). Our study demonstrates that multiple chromosome 6p susceptibility loci contribute to the risk of NPC, possibly though GABBR1 and NEDD9 loss of function

Global analysis of estrogen receptor beta binding to breast cancer cell genome reveals an extensive interplay with estrogen receptor alpha for target gene regulation

Background: Estrogen receptors alpha (ERa) and beta (ERb) are transcription factors (TFs) that mediate estrogen signaling and define the hormone-responsive phenotype of breast cancer (BC). The two receptors can be found co-expressed and play specific, often opposite, roles, with ERb being able to modulate the effects of ERa on gene transcription and cell proliferation. ERb is frequently lost in BC, where its presence generally correlates with a better prognosis of the disease. The identification of the genomic targets of ERb in hormone-responsive BC cells is thus a critical step to elucidate the roles of this receptor in estrogen signaling and tumor cell biology. Results: Expression of full-length ERb in hormone-responsive, ERa-positive MCF-7 cells resulted in a marked reduction in cell proliferation in response to estrogen and marked effects on the cell transcriptome. By ChIP-Seq we identified 9702 ERb and 6024 ERa binding sites in estrogen-stimulated cells, comprising sites occupied by either ERb, ERa or both ER subtypes. A search for TF binding matrices revealed that the majority of the binding sites identified comprise one or more Estrogen Response Element and the remaining show binding matrixes for other TFs known to mediate ER interaction with chromatin by tethering, including AP2, E2F and SP1. Of 921 genes differentially regulated by estrogen in ERb+ vs ERb- cells, 424 showed one or more ERb site within 10 kb. These putative primary ERb target genes control cell proliferation, death, differentiation, motility and adhesion, signal transduction and transcription, key cellular processes that might explain the biological and clinical phenotype of tumors expressing this ER subtype. ERb binding in close proximity of several miRNA genes and in the mitochondrial genome, suggests the possible involvement of this receptor in small non-coding RNA biogenesis and mitochondrial genome functions. Conclusions: Results indicate that the vast majority of the genomic targets of ERb can bind also ERa, suggesting that the overall action of ERb on the genome of hormone-responsive BC cells depends mainly on the relative concentration of both ERs in the cell

Convergent transcriptional profiles induced by endogenous estrogen and distinct xenoestrogens in breast cancer cells

Estrogen receptors display high levels of promiscuity in accommodating a wide range of ligand structures, but the functional consequence of changing receptor conformations in complex with distinct agonists is highly controversial. To determine variations in the transactivation capacity induced by different estrogenic agonists, we assessed global transcriptional profiles elicited by natural or synthetic xenoestrogens in comparison with the endogenous hormone 17beta-estradiol. Human MCF7 and T47D carcinoma cells, representing the most frequently used model systems for tumorigenic responses in the mammary gland, were synchronized by hormone starvation during 48 h. Subsequently, a 24 h exposure was carried out with equipotent concentrations of the selected xenoestrogens or 17beta-estradiol. Analysis of messenger RNA was performed on high-density oligonucleotide microarrays that display the sequences of 33,000 human transcripts, yielding a total of 181 gene products that are regulated upon estrogenic stimulation. Surprisingly, genistein (a phytoestrogen), bisphenol-A and polychlorinated biphenyl congener 54 (two synthetic xenoestrogens) produced highly congruent genomic fingerprints by regulating the same range of human genes. Also, the monotonous genomic signature observed in response to xenoestrogens is identical to the transcriptional effects induced by physiological concentrations of 17beta-estradiol. This striking functional convergence indicates that the transcription machinery is largely insensitive to the particular structure of estrogen receptor agonists. The occurrence of such converging transcriptional programs reinforces the hypothesis that multiple xenoestrogenic contaminants, of natural or anthropogenic origin, may act in conjunction with the endogenous hormone to induce additive effects in target tissues

Potential application of gene expression fingerprinting for food safety screening

Drug residues or contaminants with unwanted adverse effects may include tens of thousands of synthetic or natural substances. Although most of these chemicals are usually present in the food at harmless concentrations, it is a tremendous task to identify those samples that pose a possible health hazard to the consumer. Current monitoring actions involve, in most cases, single-endpoint screening tests that detect only a unique chemical entity or a limited group of related substances. One major challenge in the area of food safety is, therefore, the development of multi-endpoint strategies that could increase the efficiency of high-throughput screening procedures. Here, we used human cell lines derived from breast epithelium (MCF-7 and T-47D) to explore the potential impact of microarray-based transcriptomic analyses in allowing the simultaneous detection of a large number of different residues or contaminants. Both cell lines yielded characteristic expression profiles upon exposure to representative chemicals that are often found in food products. Interestingly, this pilot study suggests that T-47D cells respond to treatment with different xenoestrogenic chemicals with distinct expression profiles. Thus, the use of oligonucleotide microarrays may considerably expand the range and improve the specificity of existing reporter bioassays