295 research outputs found

    Tumor dissociation of highly viable cell suspensions for single-cell omic analyses in mouse models of breast cancer.

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    Cell preparation with a high rate of viable cells is required to obtain reliable single-cell transcriptomic and epigenomic data. This protocol describes a technique for digestion and single-cell isolation from mouse mammary tumors to achieve ∼90% of viable cells, which can be subsequently processed in a diverse array of high-throughput single-cell "omic platforms," both in an unbiased manner or after selection of a specific cell population. For complete details on the use and execution of this protocol, please refer to Valdes-Mora et al. (2021)

    Applying Data Mining and Machine Learning Techniques to Predict Powerlifting Results

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    This work was partially funded by projects PID2020-113462RB-I00 (ANIMALICOS), PID2020-115570GB-C22, and PID2020-115570GB-C21, granted by the Ministerio Español de Economía y Competitividad; project TED2021-129938B-I00, granted by the Ministerio Español de Ciencia e Innovación; projects P18-RT-4830 and A-TIC-608-UGR20, granted by Junta de Andalucía; and project B-TIC-402-UGR18 (FEDER and Junta de Andalucía).This paper presents a study on the creation of a tool to help powerlifting athletes and coaches, as well as bodybuilders and other amateur gym athletes, to analyse their data and obtain useful information regarding the athlete’s performance. The tool should also predict future personal records in lifting for both raw (non-equipped) and non-raw (equipped) attempts, and their various exercises. In order to achieve this, a dataset with entries of around 500 k lifters and more than 20 k official powerlifting competitions was used. Among those entries, biometric variables of the lifters and the weights they lift in each of the three movements of this sport discipline were included: squat, bench press, and deadlift. We applied data preprocessing and visualising as well as data splitting and scaling techniques in order to train the machine learning models that are used to make the predictions. Lastly, the best predictive models were used in the implemented tool.Ministerio Español de Economía y Competitividad ID2020-113462RB-I00, PID2020-115570GB-C22, PID2020-115570GB-C2Ministerio Español de Ciencia e Innovación TED2021-129938B-I00Junta de Andalucía P18-RT-4830, A-TIC-608-UGR20FEDER and Junta de Andalucía B-TIC-402-UGR1

    Single-Cell Transcriptomics in Cancer Immunobiology: The Future of Precision Oncology.

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    Cancer is a heterogeneous and complex disease. Tumors are formed by cancer cells and a myriad of non-cancerous cell types that together with the extracellular matrix form the tumor microenvironment. These cancer-associated cells and components contribute to shape the progression of cancer and are deeply involved in patient outcome. The immune system is an essential part of the tumor microenvironment, and induction of cancer immunotolerance is a necessary step involved in tumor formation and growth. Immune mechanisms are intimately associated with cancer progression, invasion, and metastasis; as well as to tumor dormancy and modulation of sensitivity to drug therapy. Transcriptome analyses have been extensively used to understand the heterogeneity of tumors, classifying tumors into molecular subtypes and establishing signatures that predict response to therapy and patient outcomes. However, the classification of the tumor cell diversity and specially the identification of rare populations has been limited in these transcriptomic analyses of bulk tumor cell populations. Massively-parallel single-cell RNAseq analysis has emerged as a powerful method to unravel heterogeneity and to study rare cell populations in cancer, through unsupervised sampling and modeling of transcriptional states in single cells. In this context, the study of the role of the immune system in cancer would benefit from single cell approaches, as it will enable the characterization and/or discovery of the cell types and pathways involved in cancer immunotolerance otherwise missed in bulk transcriptomic information. Thus, the analysis of gene expression patterns at single cell resolution holds the potential to provide key information to develop precise and personalized cancer treatment including immunotherapy. This review is focused on the latest single-cell RNAseq methodologies able to agnostically study thousands of tumor cells as well as targeted single-cell RNAseq to study rare populations within tumors. In particular, we will discuss methods to study the immune system in cancer. We will also discuss the current challenges to the study of cancer at the single cell level and the potential solutions to the current approaches

    Advancements in 3D Cell Culture Systems for Personalizing Anti-Cancer Therapies.

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    Over 90% of potential anti-cancer drug candidates results in translational failures in clinical trials. The main reason for this failure can be attributed to the non-accurate pre-clinical models that are being currently used for drug development and in personalised therapies. To ensure that the assessment of drug efficacy and their mechanism of action have clinical translatability, the complexity of the tumor microenvironment needs to be properly modelled. 3D culture models are emerging as a powerful research tool that recapitulates in vivo characteristics. Technological advancements in this field show promising application in improving drug discovery, pre-clinical validation, and precision medicine. In this review, we discuss the significance of the tumor microenvironment and its impact on therapy success, the current developments of 3D culture, and the opportunities that advancements that in vitro technologies can provide to improve cancer therapeutics

    Single-Cell Transcriptomics in Cancer Immunobiology: The Future of Precision Oncology

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    Cancer is a heterogeneous and complex disease. Tumors are formed by cancer cells and a myriad of non-cancerous cell types that together with the extracellular matrix form the tumor microenvironment. These cancer-associated cells and components contribute to shape the progression of cancer and are deeply involved in patient outcome. The immune system is an essential part of the tumor microenvironment, and induction of cancer immunotolerance is a necessary step involved in tumor formation and growth. Immune mechanisms are intimately associated with cancer progression, invasion, and metastasis; as well as to tumor dormancy and modulation of sensitivity to drug therapy. Transcriptome analyses have been extensively used to understand the heterogeneity of tumors, classifying tumors into molecular subtypes and establishing signatures that predict response to therapy and patient outcomes. However, the classification of the tumor cell diversity and specially the identification of rare populations has been limited in these transcriptomic analyses of bulk tumor cell populations. Massively-parallel single-cell RNAseq analysis has emerged as a powerful method to unravel heterogeneity and to study rare cell populations in cancer, through unsupervised sampling and modeling of transcriptional states in single cells. In this context, the study of the role of the immune system in cancer would benefit from single cell approaches, as it will enable the characterization and/or discovery of the cell types and pathways involved in cancer immunotolerance otherwise missed in bulk transcriptomic information. Thus, the analysis of gene expression patterns at single cell resolution holds the potential to provide key information to develop precise and personalized cancer treatment including immunotherapy. This review is focused on the latest single-cell RNAseq methodologies able to agnostically study thousands of tumor cells as well as targeted single-cell RNAseq to study rare populations within tumors. In particular, we will discuss methods to study the immune system in cancer. We will also discuss the current challenges to the study of cancer at the single cell level and the potential solutions to the current approaches

    Acetylation of H2A.Z is a key epigenetic modification associated with gene deregulation and epigenetic remodeling in cancer

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    Histone H2A.Z (H2A.Z) is an evolutionarily conserved H2A variant implicated in the regulation of gene expression; however, its role in transcriptional deregulation in cancer remains poorly understood. Using genome-wide studies, we investigated the role of promoter-associated H2A.Z and acetylated H2A.Z (acH2A.Z) in gene deregulation and its relationship with DNA methylation and H3K27me3 in prostate cancer. Our results reconcile the conflicting reports of positive and negative roles for histone H2A.Z and gene expression states. We find that H2A.Z is enriched in a bimodal distribution at nucleosomes, surrounding the transcription start sites (TSSs) of both active and poised gene promoters. In addition, H2A.Z spreads across the entire promoter of inactive genes in a deacetylated state. In contrast, acH2A.Z is only localized at the TSSs of active genes. Gene deregulation in cancer is also associated with a reorganization of acH2A.Z and H2A.Z nucleosome occupancy across the promoter region and TSS of genes. Notably, in cancer cells we find that a gain of acH2A.Z at the TSS occurs with an overall decrease of H2A.Z levels, in concert with oncogene activation. Furthermore, deacetylation of H2A.Z at TSSs is increased with silencing of tumor suppressor genes. We also demonstrate that acH2A.Z anti-correlates with promoter H3K27me3 and DNA methylation. We show for the first time, that acetylation of H2A.Z is a key modification associated with gene activity in normal cells and epigenetic gene deregulation in tumorigenesis

    Evolution of leaf-form in land plants linked to atmospheric CO2 decline in the Late Palaeozoic era

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    The widespread appearance of megaphyll leaves, with their branched veins and planate form, did not occur until the close of the Devonian period at about 360 Myr ago. This happened about 40 Myr after simple leafless vascular plants first colonized the land in the Late Silurian/Early Devonian, but the reason for the slow emergence of this common feature of present-day plants is presently unresolved. Here we show, in a series of quantitative analyses using fossil leaf characters and biophysical principles, that the delay was causally linked with a 90% drop in atmospheric pCO2 during the Late Palaeozoic era. In contrast to simulations for a typical Early Devonian land plant, possessing few stomata on leafless stems, those for a planate leaf with the same stomatal characteristics indicate that it would have suffered lethal overheating, because of greater interception of solar energy and low transpiration. When planate leaves first appeared in the Late Devonian and subsequently diversified in the Carboniferous period, they possessed substantially higher stomatal densities. This observation is consistent with the effects of the pCO2 on stomatal development and suggests that the evolution of planate leaves could only have occurred after an increase in stomatal density, allowing higher transpiration rates that were sufficient to maintain cool and viable leaf temperatures

    Adolescence, sexuality and sexual risk behaviors

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    Introducción: la adolescencia se caracteriza por la complejidad de cambios a nivel físico, psicológico y social a los que deben enfrentarse los adolescentes para poder transitar al mundo adulto. La vivencia de crisis los hace una población vulnerable sujeta a sufrir situaciones altamente significativas.Objetivo: establecer tendencias nacionales e internacionales en el abordaje de los comportamientos sexuales de riesgo en los adolescentes.Métodos se realizó una revisión bibliográfica de los principales artículos científicos de los últimos años, en revistas biomédicas nacionales e internacionales y otras fuentes bibliográficas en google académico. De los 47 artículos seleccionados, fueron utilizados 30 como referencias bibliográficas en idioma inglés y español.Desarrollo: los comportamientos sexuales de riesgo en los adolescentes favorecen la presencia de riesgos que comprometen su salud sexual y reproductiva. Se caracteriza por el inicio temprano de las relaciones sexuales, el cambio frecuente de pareja, en ocasiones se realizan presionada por su grupo de amigos o su pareja y sin ninguna protección.Conclusiones: los aspectos señalados, indican la importancia que tiene educar a los adolescentes sobre sexualidad por lo que se demanda de diseños de intervención que contribuyan a disminuir los riesgos relacionados con los grandes problemas sexuales de los adolescentes.Introduction: adolescence is characterized by the complexity of changes at the physical, psychological and social levels that adolescents must face in order to transition to the adult world. The experience of crises makes them a vulnerable population subject to suffer highly significant situations.Objective: to establish national and international trends in the approach to sexual risk behaviors in adolescents.Methods: a bibliographic review of the main scientific articles of the last few years in national and international biomedical journals and other bibliographic sources in academic google was carried out. Of the 47 articles selected, 30 were used as bibliographic references in English and Spanish.Development: risky sexual behaviors in adolescents favor the presence of risks that compromise their sexual and reproductive health. It is characterized by early initiation of sexual relations, frequent change of partners, sometimes under pressure from their group of friends or their partner and without any protection.Conclusions: the aspects mentioned above indicate the importance of educating adolescents about sexuality, and therefore intervention designs are needed to help reduce the risks related to the major sexual problems of adolescents

    Peatlands of Southern South America : a review

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    This article is an outcome of the workshop entitled “Turberas: puesta al día y desafíos” (14 Jun 2017). The workshop was supported by FONDECYT Grant N° 11150275 from the Comisión Nacional de Investigación Científica y Tecnológica (CONICYT). L.D.F. is funded by ANID (FONDECYT 11170927). We are very grateful to the reviewers and Dr Stephan Glatzel for their constructive suggestions.Peer reviewedPublisher PD
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