133 research outputs found
06N-P63\u3b1 and TA-P63\u3b1 exhibit intrinsic differences in transactivation specificities that depend on distinct features of DNA target sites.
TP63 is a member of the TP53 gene family that encodes for up to ten different TA
and 06N isoforms through alternative promoter usage and alternative splicing.
Besides being a master regulator of gene expression for squamous epithelial
proliferation, differentiation and maintenance, P63, through differential
expression of its isoforms, plays important roles in tumorigenesis. All P63
isoforms share an immunoglobulin-like folded DNA binding domain responsible for
binding to sequence-specific response elements (REs), whose overall consensus
sequence is similar to that of the canonical p53 RE. Using a defined assay in
yeast, where P63 isoforms and RE sequences are the only variables, and gene
expression assays in human cell lines, we demonstrated that human TA- and 06N-P63\u3b1
proteins exhibited differences in transactivation specificity not observed with
the corresponding P73 or P53 protein isoforms. These differences 1) were
dependent on specific features of the RE sequence, 2) could be related to
intrinsic differences in their oligomeric state and cooperative DNA binding, and
3) appeared to be conserved in evolution. Since genotoxic stress can change
relative ratio of TA- and 06N-P63\u3b1 protein levels, the different transactivation
specificity of each P63 isoform could potentially influence cellular responses to
specific stresses
Incremental dimension reduction of tensors with random index
We present an incremental, scalable and efficient dimension reduction
technique for tensors that is based on sparse random linear coding. Data is
stored in a compactified representation with fixed size, which makes memory
requirements low and predictable. Component encoding and decoding are performed
on-line without computationally expensive re-analysis of the data set. The
range of tensor indices can be extended dynamically without modifying the
component representation. This idea originates from a mathematical model of
semantic memory and a method known as random indexing in natural language
processing. We generalize the random-indexing algorithm to tensors and present
signal-to-noise-ratio simulations for representations of vectors and matrices.
We present also a mathematical analysis of the approximate orthogonality of
high-dimensional ternary vectors, which is a property that underpins this and
other similar random-coding approaches to dimension reduction. To further
demonstrate the properties of random indexing we present results of a synonym
identification task. The method presented here has some similarities with
random projection and Tucker decomposition, but it performs well at high
dimensionality only (n>10^3). Random indexing is useful for a range of complex
practical problems, e.g., in natural language processing, data mining, pattern
recognition, event detection, graph searching and search engines. Prototype
software is provided. It supports encoding and decoding of tensors of order >=
1 in a unified framework, i.e., vectors, matrices and higher order tensors.Comment: 36 pages, 9 figure
HIV- 1 lentivirus tethering to the genome is associated with transcription factor binding sites found in genes that favour virus survival
Data availability: The databases generated during an/or analysed during the current study are available from the corresponding author on reasonable request.Copyright © The Author(s) 2022. Lentiviral vectors (LV) are attractive for permanent and effective gene therapy. However, integration into the host genome can cause insertional mutagenesis highlighting the importance of understanding of LV integration. Insertion site (IS) tethering is believed to involve cellular proteins such as PSIP1/LEDGF/p75, which binds to the virus pre-integration complexes (PICs) helping to target the virus genome. Transcription factors (TF) that bind both the vector LTR and host genome are also suspected influential to this. To determine the role of TF in the tethering process, we mapped predicted transcription factor binding sites (pTFBS) near to IS chosen by HIV-1 LV using a narrow 20 bp window in infected human induced pluripotent stem cells (iPSCs) and their hepatocyte-like cell (HLC) derivatives. We then aligned the pTFBS with these sequences found in the LTRs of native and self-inactivated LTRs. We found significant enrichment of these sequences for pTFBS essential to HIV-1 life cycle and virus survival. These same sites also appear in HIV-1 patient IS and in mice infected with HIV-1 based LV. This in silco data analysis suggests pTFBS present in the virus LTR and IS sites selected by HIV-1 LV are important to virus survival and propagation.NC3Rs CRACK IT Challenge 21: InMutagene award, sponsored by GSK and Novartis
Cultivar de soja BRS 8381: indicação para os estados de Goiás, Mato Grosso, Minas Gerais e Distrito Federal.
Trabalho publicado também nos Resumos do CONGRESSO BRASILEIRO DE SOJA, 6., 2012, Cuiabá
Influence of particle size on appearance and in vitro efficacy of sunscreens
Nanotechnology applies to diverse sectors of science. In cosmetic area, investments have strengthened the idea that nanoproducts provide innumerable benefits to consumers. Extreme exposition to solar light can cause undesirable effects, thus, adding UV filters in cosmetic products are often used as prevention. Ethylhexyl methoxycinnamate and benzophenone-3 are UV filters widely used in sunscreen formulations, this UV filters absorb UVB and UVA radiation, respectively. In this study, sunscreen formulations were developed as nano and macroemulsion, but composed by the same raw material. Nanoemulsion was obtained by phase inversion temperature method (PIT). Physical and functional properties were evaluated by visual analysis, particle size distribution and by diffuse reflectance spectrophotometry. Achieved nanoemulsion showed bluish brightness aspect, less apparent consistency than macroemulsion, stability longer than 48 hours (22.0 ± 2.0 °C) and bimodal particle size distribution with average (mean) sizes around 10 nm (61%) and 4.5 µm (39%). Macroemulsion showed milky aspect, higher consistency than nanoemulsion, instability after 48 hours (22.0 ± 2.0 °C) and bimodal particle size distribution with average (mean) size around 202 nm (9%) and 10.4 µm (91%). Effectiveness profile of sunscreen formulations remained apparently similar, based on achieved results of in vitro SPF, UVA/UVB ratio and critical wavelength assays
Antibody response elicited by the SARS-CoV-2 vaccine booster in patients with multiple sclerosis: Who gains from it?
Background and purpose: Although two doses of COVID-19 vaccine elicited a protective humoral response in most persons with multiple sclerosis (pwMS), a significant group of them treated with immunosuppressive disease-modifying therapies (DMTs) showed less efficient responses. Methods: This prospective multicenter observational study evaluates differences in immune response after a third vaccine dose in pwMS. Results: Four hundred seventy-three pwMS were analyzed. Compared to untreated patients, there was a 50-fold decrease (95% confidence interval [CI] = 14.3–100.0, p < 0.001) in serum SARS-CoV-2 antibody levels in those on rituximab, a 20-fold decrease (95% CI = 8.3–50.0, p < 0.001) in those on ocrelizumab, and a 2.3-fold decrease (95% CI = 1.2–4.6, p = 0.015) in those on fingolimod. As compared to the antibody levels after the second vaccine dose, patients on the anti-CD20 drugs rituximab and ocrelizumab showed a 2.3-fold lower gain (95% CI = 1.4–3.8, p = 0.001), whereas those on fingolimod showed a 1.7-fold higher gain (95% CI = 1.1–2.7, p = 0.012), compared to patients treated with other DMTs. Conclusions: All pwMS increased their serum SARS-CoV-2 antibody levels after the third vaccine dose. The mean antibody values of patients treated with ocrelizumab/rituximab remained well below the empirical "protective threshold" for risk of infection identified in the CovaXiMS study (>659 binding antibody units/mL), whereas for patients treated with fingolimod this value was significantly closer to the cutoff
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