Manual de las construcciones rústicas, ó, Guia para los habitantes del campo y los operarios en construcciones rurales

A portada: "Obra coronada por la Real Sociedad de Agricultura de Francia"Data de publicació aproximada segons la publicació original en francè

AK2 deficiency compromises the mitochondrial energy metabolism required for differentiation of human neutrophil and lymphoid lineages

Reticular dysgenesis is a human severe combined immunodeficiency that is primarily characterized by profound neutropenia and lymphopenia. The condition is caused by mutations in the adenylate kinase 2 (AK2) gene, resulting in the loss of mitochondrial AK2 protein expression. AK2 regulates the homeostasis of mitochondrial adenine nucleotides (ADP, ATP and AMP) by catalyzing the transfer of high-energy phosphate. Our present results demonstrate that AK2-knocked-down progenitor cells have poor proliferative and survival capacities and are blocked in their differentiation toward lymphoid and granulocyte lineages. We also observed that AK2 deficiency impaired mitochondrial function in general and oxidative phosphorylation in particular - showing that AK2 is critical in the control of energy metabolism. Loss of AK2 disrupts this regulation and leads to a profound block in lymphoid and myeloid cell differentiation

Knowledge Sharing in Alliances and Alliance Portfolios

We develop a model of knowledge sharing in alliances and alliance portfolios. We show that, once the issue of encouraging effective collaboration is put center stage, many standard intuitions of the learning race view and alliance portfolio literature are overturned or qualified. Partners engage in learning races in some cases, but exhibit “altruistic” behaviors in other cases. They may reduce their own absorptive capacity or increase the transparency of their own operations to facilitate their partner’s learning. In alliance portfolios, we show that not all substitutability between alliance portfolio partners is bad. We distinguish between substitutability in implementation and substitutability in rival benefits and show that the latter is conducive to knowledge sharing. Our work contributes toward putting the literature on learning alliances on a more solid foundation by emphasizing the importance of commitments that leading firms can make to encourage collaboration

The fables of pity: Rousseau, Mandeville and the animal-fable

Copyright @ 2012 Edinburgh University PressPrompted by Derrida’s work on the animal-fable in eighteenth-century debates about political power, this article examines the role played by the fiction of the animal in thinking of pity as either a natural virtue (in Rousseau’s Second Discourse) or as a natural passion (in Mandeville’s The Fable of the Bees). The war of fables between Rousseau and Mandeville – and their hostile reception by Samuel Johnson and Adam Smith – reinforce that the animal-fable illustrates not so much the proper of man as the possibilities and limitations of a moral philosophy that is unable to address the political realities of the state

ImmunoCluster provides a computational framework for the non-specialist to profile high- dimensional cytometry data

High dimensional cytometry is an innovative tool for immune monitoring in health and disease, it has provided novel insight into the underlying biology as well as biomarkers for a variety of diseases. However, the analysis of large multiparametric datasets usually requires specialist computational knowledge. Here we describe ImmunoCluster (https://github.com/kordastilab/ImmunoCluster) an R package for immune profiling cellular heterogeneity in high dimensional liquid and imaging mass cytometry, and flow cytometry data, designed to facilitate computational analysis by a non-specialist. The analysis framework implemented within ImmunoCluster is readily scalable to millions of cells and provides a variety of visualization and analytical approaches, as well as a rich array of plotting tools that can be tailored to users' needs. The protocol consists of three core computational stages: 1, data import and quality control; 2, dimensionality reduction and unsupervised clustering; and 3, annotation and differential testing, all contained within an R-based open-source framework

Prognostic Role of Gene Mutations in Chronic Myelomonocytic Leukemia Patients Treated With Hypomethylating Agents

Somatic mutations contribute to the heterogeneous prognosis of chronic myelomonocytic leukemia (CMML). Hypomethylating agents (HMAs) are active in CMML, but analyses of small series failed to identify mutations predicting response or survival. We analyzed a retrospective multi-center cohort of 174 CMML patients treated with a median of 7 cycles of azacitidine (n = 68) or decitabine (n = 106). Sequencing data before treatment initiation were available for all patients, from Sanger (n = 68) or next generation (n = 106) sequencing. Overall response rate (ORR) was 52%, including complete response (CR) in 28 patients (17%). In multivariate analysis, ASXL1 mutations predicted a lower ORR (Odds Ratio [OR] = 0.85, p = 0.037), whereas TET2mut/ASXL1wt genotype predicted a higher CR rate (OR = 1.18, p = 0.011) independently of clinical parameters. With a median follow-up of 36.7 months, overall survival (OS) was 23.0 months. In multivariate analysis, RUNX1mut (Hazard Ratio [HR] = 2.00, p = .011), CBLmut (HR = 1.90, p = 0.03) genotypes and higher WBC (log10(WBC) HR = 2.30, p = .005) independently predicted worse OS while the TET2mut/ASXL1wt predicted better OS (HR = 0.60, p = 0.05). CMML-specific scores CPSS and GFM had limited predictive power. Our results stress the need for robust biomarkers of HMA activity in CMML and for novel treatment strategies in patients with myeloproliferative features and RUNX1 mutations. Keywords: Chronic myelomonocytic leukemia, Hypomethylating agents, Somatic mutations, Prognosi

Immune responses during COVID-19 infection

Over the past 16 years, three coronaviruses (CoVs), severe acute respiratory syndrome CoV (SARS-CoV) in 2002, Middle East respiratory syndrome CoV (MERS-CoV) in 2012 and 2015, and SARS-CoV-2 in 2020, have been causing severe and fatal human epidemics. The unpredictability of coronavirus disease-19 (COVID-19) poses a major burden on health care and economic systems across the world. This is caused by the paucity of in-depth knowledge of the risk factors for severe COVID-19, insufficient diagnostic tools for the detection of SARS-CoV-2, as well as the absence of specific and effective drug treatments. While protective humoral and cellular immune responses are usually mounted against these betacoronaviruses, immune responses to SARS-CoV2 sometimes derail towards inflammatory tissue damage, leading to rapid admissions to intensive care units. The lack of knowledge on mechanisms that tilt the balance between these two opposite outcomes poses major threats to many ongoing clinical trials dealing with immunostimulatory or immunoregulatory therapeutics. This review will discuss innate and cognate immune responses underlying protective or deleterious immune reactions against these pathogenic coronaviruses

Immunocluster provides a computational framework for the nonspecialist to profile high-dimensional cytometry data

High-dimensional cytometry is an innovative tool for immune monitoring in health and disease, and it has provided novel insight into the underlying biology as well as biomarkers for a variety of diseases. However, the analysis of large multiparametric datasets usually requires specialist computational knowledge. Here, we describe ImmunoCluster (https://github.com/ kordastilab/ImmunoCluster), an R package for immune profiling cellular heterogeneity in highdimensional liquid and imaging mass cytometry, and flow cytometry data, designed to facilitate computational analysis by a nonspecialist. The analysis framework implemented within ImmunoCluster is readily scalable to millions of cells and provides a variety of visualization and analytical approaches, as well as a rich array of plotting tools that can be tailored to users’ needs. The protocol consists of three core computational stages: (1) data import and quality control; (2) dimensionality reduction and unsupervised clustering; and (3) annotation and differential testing, all contained within an R-based open-source framework

Data submission and curation for caArray, a standard based microarray data repository system

caArray is an open-source, open development, web and programmatically accessible array data management system developed at National Cancer Institute. It was developed to support the exchange of array data across the Cancer Biomedical Informatics Grid (caBIG™), a collaborative information network that connect scientists and practitioners through a shareable and interoperable infrastructure to share data and knowledge. caArray adopts a federated model of local installations, in which data deposited are shareable across caBIG™. 

Comprehensive in annotation yet easy to use has always been a challenge to any data repository system. To alleviate this difficulty, caArray accepts data upload using the MAGE-TAB, a spreadsheet-based format for annotating and communicating microarray data in a MIAME-compliant fashion ("http://www.mged.org/mage-tab":http://www.mged.org/mage-tab). MAGE-TAB is built on community standards – MAGE, MIAME, and Ontology. The components and work flow of MAGE-TAB files are organized in such a way which is already familiar to bench scientists and thus minimize the time and frustration of reorganizing their data before submission. The MAGE-TAB files are also structured to be machine readable so that they can be easily parsed into database. Users can control public access to experiment- and sample-level data and can create collaboration groups to support data exchange among a defined set of partners. 

All data submitted to caArray at NCI will go through strict curation by a group of scientists against these standards to make sure that the data are correctly annotated using proper controlled vocabulary terms and all required information are provided. Two of mostly used ontology sources are MGED ontology ("http://mged.sourceforge.net/ontologies/MGEDontology.php":http://mged.sourceforge.net/ontologies/MGEDontology.php) and NCI thesaurus ("http://nciterms.nci.nih.gov/NCIBrowser/Dictionary.do":http://nciterms.nci.nih.gov/NCIBrowser/Dictionary.do). The purpose of data curation is to ensure easy comparison of results from different labs and unambiguous report of results. 

Data will also undergo automatic validation process before parsed into database, in which minimum information requirement and data consistency with the array designs are checked. Files with error found during validation are flagged with error message. Curators will re-examine those files and make necessary corrections before re-load the files. The iteration repeats until files are validated successfully. Data are then imported into the system and ready for access through the portal or through API. Interested parties are encouraged to review the installation package, documentation, and source code available from "http://caarray.nci.nih.gov":http://caarray.nci.nih.gov