Nueva ruralidad y dinámicas de proximidad en el desarrollo territorial de los sistemas agroalimentarios localizados

La nueva ruralidad como enfoque permite interpretar los procesos de desarrollo territorial de los Sistemas agroalimentarios localizados (SIAL), bajo las condicionantes de entorno y contexto actual. Las dinámicas de proximidad explican los procesos de interacción, cooperación y coordinación, subyacentes al desarrollo territorial. En este sentido, los objetivos del trabajo consistieron en construir un modelo de interpretación del desarrollo territorial como proceso societal, con ello analizar las dimensiones de complementariedad entre nueva ruralidad y dinámicas de proximidad, para el desarrollo territorial en los SIAL. La metodología fue un modelo construido de complementariedad conceptual entre nueva ruralidad y dinámicas de proximidad. Se analizaron seis casos SIAL documentados y se postularon seis dimensiones de sincretismo conceptual: capital humano, capital social, competitividad, institucional, gobernanza y dimensión territorial.The new rurality as an approach allows the interpretation of the processes of territorial development of localized agri-food systems (SIAL), under the conditions of environment and current context. Proximity dynamics explain the processes of interaction, cooperation and coordination, underlying the territorial development. In this sense, the objectives of the research were to build a model of interpretation of territorial development as a societal process, along with analyzing the dimensions of complementarity between new rurality and proximity dynamics related to the territorial development in the SIAL. The methodology was a built conceptual model of complementarity between new rurality and proximity. Six cases of documented SIAL were analyzed and six dimensions of conceptual syncretism were postulated: human capital, social capital, competitiveness, institutional, governance and territorial.A nova ruralidade como uma abordagem para interpretar os processos de desenvolvimento territorial de sistemas agroalimentares (SIAL), sob as condições do meio ambiente e contexto atual. dinâmica de proximidade explicar os processos de interação, cooperação e coordenação, desenvolvimento territorial subjacente. Neste sentido, os objetivos do trabalho consistiu na construção de um modelo de interpretação do ordenamento do território e do processo social, assim, analisar as dimensões da complementaridade entre as novas dinâmicas rurais e de proximidade, para o desenvolvimento territorial no SIAL. A metodologia utilizada foi um modelo conceitual construído a complementaridade entre novas dinâmicas rurais e de proximidade. SIAL documentado seis casos foram analisados e seis dimensões do sincretismo conceitual postulado: capital humano, capital social, competitividade, institucional, governança e dimensão territorial

Nueva ruralidad y dinámicas de proximidad en el desarrollo territorial de los sistemas agroalimentarios localizados

La nueva ruralidad como enfoque permite interpretar los procesos de desarrollo territorial de los Sistemas agroalimentarios localizados (SIAL), bajo las condicionantes de entorno y contexto actual. Las dinámicas de proximidad explican los procesos de interacción, cooperación y coordinación, subyacentes al desarrollo territorial. En este sentido, los objetivos del trabajo consistieron en construir un modelo de interpretación del desarrollo territorial como proceso societal, con ello analizar las dimensiones de complementariedad entre nueva ruralidad y dinámicas de proximidad, para el desarrollo territorial en los SIAL. La metodología fue un modelo construido de complementariedad conceptual entre nueva ruralidad y dinámicas de proximidad. Se analizaron seis casos SIAL documentados y se postularon seis dimensiones de sincretismo conceptual: capital humano, capital social, competitividad, institucional, gobernanza y dimensión territorial.The new rurality as an approach allows the interpretation of the processes of territorial development of localized agri-food systems (SIAL), under the conditions of environment and current context. Proximity dynamics explain the processes of interaction, cooperation and coordination, underlying the territorial development. In this sense, the objectives of the research were to build a model of interpretation of territorial development as a societal process, along with analyzing the dimensions of complementarity between new rurality and proximity dynamics related to the territorial development in the SIAL. The methodology was a built conceptual model of complementarity between new rurality and proximity. Six cases of documented SIAL were analyzed and six dimensions of conceptual syncretism were postulated: human capital, social capital, competitiveness, institutional, governance and territorial.A nova ruralidade como uma abordagem para interpretar os processos de desenvolvimento territorial de sistemas agroalimentares (SIAL), sob as condições do meio ambiente e contexto atual. dinâmica de proximidade explicar os processos de interação, cooperação e coordenação, desenvolvimento territorial subjacente. Neste sentido, os objetivos do trabalho consistiu na construção de um modelo de interpretação do ordenamento do território e do processo social, assim, analisar as dimensões da complementaridade entre as novas dinâmicas rurais e de proximidade, para o desenvolvimento territorial no SIAL. A metodologia utilizada foi um modelo conceitual construído a complementaridade entre novas dinâmicas rurais e de proximidade. SIAL documentado seis casos foram analisados e seis dimensões do sincretismo conceitual postulado: capital humano, capital social, competitividade, institucional, governança e dimensão territorial

El papel de los estudios bioarqueológicos en las interpretaciones sobre las comunidades neolíticas del noreste peninsular

Resumen del trabajo presentado al VI Congreso del Neolítico en la Península Ibérica: "Los cambios económicos y sus implicaciones sociales durante el Neolítico de la Península Ibérica", celebrado en Granada del 22 al 26 de junio de 2016.-- et al.El marco del proyecto I+D: “Aproximación a las primeras comunidades neolíticas del NE peninsular a través de sus prácticas funerarias” (2011-2015), y su continuidad para los próximos cuatro años al haber sido renovado, tiene por objetivo conocer cada día más y mejor las comunidades de agricultores y pastores que entre finales del V e inicios del IV milenio cal BC ocuparon y enterraron a sus muertos en el noreste de la Península Ibérica. El contexto de estudio es excepcional, puesto que aquellas comunidades inhumaron sistemáticamente a sus congéneres en tumbas habitualmente individuales y ocasionalmente junto a otro individuo. En esta presentación no sólo queremos mostrar los nuevos análisis y metodologías que estamos aplicando al estudio de los restos humanos, sino también el modelo de trabajo que hemos seguido. A este respecto, tres aspectos son fundamentales: 1) las dataciones absolutas son el eje que vertebra los posteriores análisis; 2) la colaboración con los distintos investigadores/as y laboratorios debe ser estrecha (no es cuestión de solicitar los resultados de un análisis a un laboratorio sino trabajar con las personas que manipulan las muestras y conocen los pros y contras de cada una de las técnicas empleadas) y 3) los estudios y análisis a realizar confluyen para responder a las hipótesis planteadas. A este respecto, en el proyecto hemos tenido la fortuna de poder colaborar con numerosos investigadores/as cuya especialidad versa alrededor de los restos funerarios y que firman la presente comunicación: análisis isotópicos, Adn, tafonomía funeraria, estudios de stress muscular y análisis de morfología dental.Peer Reviewe

Distribución histórica, actual y futura de Cedrela odorata en México

Background and Aims: Tropical forests play an indispensable role to confront and reduce environmental degradation. The objective of this work was to determine, through ecological niche simulation models, the historical and current distribution of Cedrela odorata in Mexico.Methods: A base of 1747 presence data of C. odorata was used. For the modeling 19 climatic-environmental variables were used, as well as the layers of altitude, orientation, slope and soil type. The ecological niche modeling was carried out in the program MaxEnt, with 75% of the sample for training and the Logistic, Cumulative, Raw and Cloglog models. The validation was carried out with 25% of the sample and the Crossvalidate technique.Key results: The use of the Cloglog regression is the one that most adheres to the potential distribution for the species, otherwise using the Raw type modeling, since the projection of the potential area is very restrictive and compact, followed by the Cumulative regression and the Logistic regression, being these an intermediate point for the modeling of the historical distribution of C. odorata in Mexico.Conclusions: The historical distribution obtained from this model showed that the species has very high values of probability in the southern part of the Yucatán Península, north and south of Chiapas and the coastal plain of the Gulf in the Veracruz state with respect to the current distribution reported. This suggests a reduction in the distribution of the species in the country.Antecedentes y Objetivos: Los bosques tropicales juegan un papel indispensable para enfrentar y reducir la degradación ambiental. El objetivo de este trabajo fue determinar, mediante modelos de simulación de nicho ecológico, la distribución histórica y actual de Cedrela odorata en México.Métodos: Se empleó una base de 1747 datos de presencia de C. odorata. Para la modelación se emplearon 19 variables climato-ambientales y las capas de altitud, orientación, pendiente y tipo de suelos. La modelación de nicho ecológico se realizó en el programa MaxEnt con 75% de la muestra para el entrenamiento y los modelos Logistic, Cumulative, Raw y Cloglog. La validación se realizó con 25% de la muestra y la técnica Crossvalidate.Resultados clave: El empleo de la regresión Cloglog es la que más se apega a la distribución potencial para la especie, caso contrario al emplear la modelación de tipo Raw, ya que la proyección del área potencial es muy restrictiva y compacta, seguido de la regresión Cumulative y la regresión Logistic, siendo estas un punto intermedio para la modelación de la distribución histórica de C. odorata en México.Conclusiones: La distribución histórica obtenida a partir de este modelo mostró que la especie tiene una alta probabilidad de distribuirse en la parte sur de la Península de Yucatán, norte y sur de Chiapas, y la llanura costera del Golfo en el estado de Veracruz con respecto al área actual reportada. Esto sugiere una reducción del nicho ecológico de la especie en el país

Distribución histórica, actual y futura de Cedrela odorata en México

Background and Aims: Tropical forests play an indispensable role to confront and reduce environmental degradation. The objective of this work was to determine, through ecological niche simulation models, the historical and current distribution of Cedrela odorata in Mexico.Methods: A base of 1747 presence data of C. odorata was used. For the modeling 19 climatic-environmental variables were used, as well as the layers of altitude, orientation, slope and soil type. The ecological niche modeling was carried out in the program MaxEnt, with 75% of the sample for training and the Logistic, Cumulative, Raw and Cloglog models. The validation was carried out with 25% of the sample and the Crossvalidate technique.Key results: The use of the Cloglog regression is the one that most adheres to the potential distribution for the species, otherwise using the Raw type modeling, since the projection of the potential area is very restrictive and compact, followed by the Cumulative regression and the Logistic regression, being these an intermediate point for the modeling of the historical distribution of C. odorata in Mexico.Conclusions: The historical distribution obtained from this model showed that the species has very high values of probability in the southern part of the Yucatán Península, north and south of Chiapas and the coastal plain of the Gulf in the Veracruz state with respect to the current distribution reported. This suggests a reduction in the distribution of the species in the country.Antecedentes y Objetivos: Los bosques tropicales juegan un papel indispensable para enfrentar y reducir la degradación ambiental. El objetivo de este trabajo fue determinar, mediante modelos de simulación de nicho ecológico, la distribución histórica y actual de Cedrela odorata en México.Métodos: Se empleó una base de 1747 datos de presencia de C. odorata. Para la modelación se emplearon 19 variables climato-ambientales y las capas de altitud, orientación, pendiente y tipo de suelos. La modelación de nicho ecológico se realizó en el programa MaxEnt con 75% de la muestra para el entrenamiento y los modelos Logistic, Cumulative, Raw y Cloglog. La validación se realizó con 25% de la muestra y la técnica Crossvalidate.Resultados clave: El empleo de la regresión Cloglog es la que más se apega a la distribución potencial para la especie, caso contrario al emplear la modelación de tipo Raw, ya que la proyección del área potencial es muy restrictiva y compacta, seguido de la regresión Cumulative y la regresión Logistic, siendo estas un punto intermedio para la modelación de la distribución histórica de C. odorata en México.Conclusiones: La distribución histórica obtenida a partir de este modelo mostró que la especie tiene una alta probabilidad de distribuirse en la parte sur de la Península de Yucatán, norte y sur de Chiapas, y la llanura costera del Golfo en el estado de Veracruz con respecto al área actual reportada. Esto sugiere una reducción del nicho ecológico de la especie en el país

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

Early Release Science of the exoplanet WASP-39b with JWST NIRISS

Transmission spectroscopy provides insight into the atmospheric properties and consequently the formation history, physics, and chemistry of transiting exoplanets. However, obtaining precise inferences of atmospheric properties from transmission spectra requires simultaneously measuring the strength and shape of multiple spectral absorption features from a wide range of chemical species. This has been challenging given the precision and wavelength coverage of previous observatories. Here, we present the transmission spectrum of the Saturn-mass exoplanet WASP-39b obtained using the SOSS mode of the NIRISS instrument on the JWST. This spectrum spans $0.6 - 2.8 \mu$m in wavelength and reveals multiple water absorption bands, the potassium resonance doublet, as well as signatures of clouds. The precision and broad wavelength coverage of NIRISS-SOSS allows us to break model degeneracies between cloud properties and the atmospheric composition of WASP-39b, favoring a heavy element enhancement ("metallicity") of $\sim 10 - 30 \times$ the solar value, a sub-solar carbon-to-oxygen (C/O) ratio, and a solar-to-super-solar potassium-to-oxygen (K/O) ratio. The observations are best explained by wavelength-dependent, non-gray clouds with inhomogeneous coverage of the planet's terminator.Comment: 48 pages, 12 figures, 2 tables. Under review at Natur