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Abstract Background Cryopreservation of human spermatozoa is a widely used technique in the assisted reproduction technology laboratory for the storage of gametes for later use, for the fertility preservation and for sperm donation programs. Cryopreservation can cause damage to membrane, cytoskeletal, acrosome and increased oxidative stress, sperm DNA damage and transcriptome changes. To assess the impact of storage time on the transcriptome of frozen human spermatozoa, semen samples were collected from 24 normospermic donors of whom 13 had cryostored semen for a short-time (1 week) and 11 had cryostored semen for a long-time (median 9 years). Results RNA was extracted from each frozen-thawed sperm sample, randomized in pools, and analyzed by microarrays. Five transcripts were in higher abundance in the long-time respect to the short-time storage group. Functional annotation enrichment disclosed that that the length of cryostorage has no effect on critical pathways involved in sperm physiology and function. Conclusions The storage time of cryopreserved human spermatozoa does not affect pathways involved in fertility.

Abstract Background The combination of Programmed Cell Death 1 (PD-1) and Cytotoxic T-Lymphocyte Antigen 4 (CTLA-4) blockade has dramatically improved the overall survival rate for malignant melanoma. Immune checkpoint blockers (ICBs) limit the tumor’s immune escape yet only for approximately a third of all tumors and, in most cases, for a limited amount of time. Several approaches to overcome resistance to ICBs are being investigated among which the addition of epigenetic drugs that are expected to act on both immune and tumor cells. Guadecitabine, a dinucleotide prodrug of a decitabine linked via phosphodiester bond to a guanosine, showed promising results in the phase-1 clinical trial, NIBIT-M4 (NCT02608437). Methods We used the syngeneic B16F10 murine melanoma model to study the effects of immune checkpoint blocking antibodies against CTLA-4 and PD-1 in combination, with and without the addition of Guadecitabine. We comprehensively characterized the tumor’s and the host’s responses under different treatments by flow cytometry, multiplex immunofluorescence and methylation analysis. Results In combination with ICBs, Guadecitabine significantly reduced subcutaneous tumor growth as well as metastases formation compared to ICBs and Guadecitabine treatment. In particular, Guadecitabine greatly enhanced the efficacy of combined ICBs by increasing effector memory CD8+ T cells, inducing effector NK cells in the spleen and reducing tumor infiltrating regulatory T cells and myeloid derived suppressor cells (MDSC), in the tumor microenvironment (TME). Guadecitabine in association with ICBs increased serum levels of IFN-γ and IFN-γ-induced chemokines with anti-angiogenic activity. Guadecitabine led to a general DNA-demethylation, in particular of sites of intermediate methylation levels. Conclusions These results indicate Guadecitabine as a promising epigenetic drug to be added to ICBs therapy.

Analyzing gene expression profiles (GEP) through artificial intelligence provides meaningful insight into cancer disease. This study introduces DeepSHAP Autoencoder Filter for Genes Selection (DSAF-GS), a novel deep learning and explainable artificial intelligence-based approach for feature selection in genomics-scale data. DSAF-GS exploits the autoencoder’s reconstruction capabilities without changing the original feature space, enhancing the interpretation of the results. Explainable artificial intelligence is then used to select the informative genes for chronic lymphocytic leukemia prognosis of 217 cases from a GEP database comprising roughly 20,000 genes. The model for prognosis prediction achieved an accuracy of 86.4%, a sensitivity of 85.0%, and a specificity of 87.5%. According to the proposed approach, predictions were strongly influenced by CEACAM19 and PIGP, moderately influenced by MKL1 and GNE, and poorly influenced by other genes. The 10 most influential genes were selected for further analysis. Among them, FADD, FIBP, FIBP, GNE, IGF1R, MKL1, PIGP, and SLC39A6 were identified in the Reactome pathway database as involved in signal transduction, transcription, protein metabolism, immune system, cell cycle, and apoptosis. Moreover, according to the network model of the 3D protein-protein interaction (PPI) explored using the NetworkAnalyst tool, FADD, FIBP, IGF1R, QTRT1, GNE, SLC39A6, and MKL1 appear coupled into a complex network. Finally, all 10 selected genes showed a predictive power on time to first treatment (TTFT) in univariate analyses on a basic prognostic model including IGHV mutational status, del(11q) and del(17p), NOTCH1 mutations, β2-microglobulin, Rai stage, and B-lymphocytosis known to predict TTFT in CLL. However, only IGF1R [hazard ratio (HR) 1.41, 95% CI 1.08-1.84, P=0.013), COL28A1 (HR 0.32, 95% CI 0.10-0.97, P=0.045), and QTRT1 (HR 7.73, 95% CI 2.48-24.04, P

There is a growing number of multi-domain genomic datasets for human tumors. Multi-domain data are usually interpreted after separately analyzing single-domain data and integrating the results post hoc. Data fusion techniques allow for the real integration of multi-domain data to ideally improve the tumor classification results for the prognosis and prediction of response to therapy. We have previously described the joint singular value decomposition (jSVD) technique as a means of data fusion. Here, we report on the development of these methods in open source code based on R and Python and on the application of these data fusion methods. The Cancer Genome Atlas (TCGA) Skin Cutaneous Melanoma (SKCM) dataset was used as a benchmark to evaluate the potential of the data fusion approaches to improve molecular classification of cancers in a clinically relevant manner. Our data show that the data fusion approach does not generate classification results superior to those obtained using single-domain data. Data from different domains are not entirely independent from each other, and molecular classes are characterized by features that penetrate different domains. Data fusion techniques might be better suited for response prediction, where they could contribute to the identification of predictive features in a domain-independent manner to be used as biomarkers.

Abstract Background Development of resistance to inhibitors of BRAF (BRAFi) and MEK (MEKi) remains a great challenge for targeted therapy in patients with BRAF-mutant melanoma. Here, we explored the role of miRNAs in melanoma acquired resistance to BRAFi. Methods miRNA expression in two BRAF-mutant melanoma cell lines and their dabrafenib-resistant sublines was determined using Affymetrix GeneChip® miRNA 3.1 microarrays and/or qRT-PCR. The effects of miR-126-3p re-expression on proliferation, apoptosis, cell cycle, ERK1/2 and AKT phosphorylation, dabrafenib sensitivity, invasiveness and VEGF-A secretion were evaluated in the dabrafenib-resistant sublines using MTT assays, flow cytometry, immunoblotting, invasion assays in Boyden chambers and ELISA. ADAM9, PIK3R2, MMP7 and CXCR4 expression in the sensitive and dabrafenib-resistant cells was determined by immunoblotting. Small RNA interference was performed to investigate the consequence of VEGFA or ADAM9 silencing on proliferation, invasiveness or dabrafenib sensitivity of the resistant sublines. Long-term proliferation assays were carried out in dabrafenib-sensitive cells to assess the effects of enforced miR-126-3p expression or ADAM9 silencing on resistance development. VEGF-A serum levels in melanoma patients treated with BRAFi or BRAFi+MEKi were evaluated at baseline (T0), after two months of treatment (T2) and at progression (TP) by ELISA. Results miR-126-3p was significantly down-regulated in the dabrafenib-resistant sublines as compared with their parental counterparts. miR-126-3p replacement in the drug-resistant cells inhibited proliferation, cell cycle progression, phosphorylation of ERK1/2 and/or AKT, invasiveness, VEGF-A and ADAM9 expression, and increased dabrafenib sensitivity. VEGFA or ADAM9 silencing impaired proliferation and invasiveness of the drug-resistant sublines. ADAM9 knock-down in the resistant cells increased dabrafenib sensitivity, whereas miR-126-3p enforced expression or ADAM9 silencing in the drug-sensitive cells delayed the development of resistance. At T0 and T2, statistically significant differences were observed in VEGF-A serum levels between patients who responded to therapy and patients who did not. In responder patients, a significant increase of VEGF-A levels was observed at TP versus T2. Conclusions Strategies restoring miR-126-3p expression or targeting VEGF-A or ADAM9 could restrain growth and metastasis of dabrafenib-resistant melanomas and increase their drug sensitivity. Circulating VEGF-A is a promising biomarker for predicting patients’ response to BRAFi or BRAFi+MEKi and for monitoring the onset of resistance.

Com o acelerado crescimento industrial, a competitividade pela eficiência da produtividade e pela disputa de clientes, fez que com as organizações tomassem a qualidade como sinônimo de sua sobrevivência ou fracasso. Com isso, a busca por métodos que auxiliem na detecção de anomalias e melhoria dos processos produtivos. As principais ferramentas estatísticas da qualidade são muito utilizadas para o auxílio na identificação de anomalias, tal como a eliminação das mesmas e ainda proporcionam ao gerente de produção a tomar decisões para a melhoria do processo. Este artigo objetiva buscar conhecimento das ferramentas estatísticas a partir da revisão da literatura. A partir da abordagem da revisão da literatura, foi feita uma pesquisa descritiva, sendo abordado dois estudos de casos que utilizaram as ferramentas da qualidade enfatizando qual ferramenta fora utilizada, sendo estas o Diagrama de Causa e Efeito, Diagrama de Dispersão, Gráfico de Pareto, Histograma, Folha de Verificação, Gráfico de Controle e qual foi a principal função das mesmas. Por fim, de acordo com os resultados analisados é possível afirmar que as ferramentas estatísticas da qualidade foram utilizadas corretamente e ainda as mesmas foram aptas para a análise do processo, tal como indicar possíveis oportunidades de melhorias do processo.

Composite materials have been regarded as a convenient strategy in various types of engineering systems such as aeronautical and space structures, as well as architecture and light industry products due to their advantages over the traditional engineering materials, such as their high strength/stiffness relation characteristics and their anti-corrosion properties. This paper is devoted to the finite element modeling of composite laminated structures incorporating viscoelastic materials to the problem of vibration attenuation. However, the typically high dimension of large finite element models of composite structures incorporating viscoelastic materials makes the numerical processes sometimes unfeasible. Within this context, emphasis is placed on a general condensation strategy specially adapted for the case of viscoelastically damped structures, in which a constant (frequency- and temperature-independent) reduction basis to be enriched by static residues associated to the applied loads and the viscoelastic forces is used. After presenting the theoretical foundations, the numerical applications of composite plates treated by viscoelastic materials are addressed, and the main features of the methodology are discussed.

Composite materials have been regarded as a convenient strategy in various types of engineering systems such as aeronautical and space structures, as well as architecture and light industry products due to their advantages over the traditional engineering materials, such as their high strength/stiffness relation characteristics and their anti-corrosion properties. This paper is devoted to the finite element modeling of composite laminated structures incorporating viscoelastic materials to the problem of vibration attenuation. However, the typically high dimension of large finite element models of composite structures incorporating viscoelastic materials makes the numerical processes sometimes unfeasible. Within this context, emphasis is placed on a general condensation strategy specially adapted for the case of viscoelastically damped structures, in which a constant (frequency- and temperature-independent) reduction basis to be enriched by static residues associated to the applied loads and the viscoelastic forces is used. After presenting the theoretical foundations, the numerical applications of composite plates treated by viscoelastic materials are addressed, and the main features of the methodology are discussed.