Una aplicación de la teoría de redes al análisis territorial : el caso de las redes del Valle del Yaqui (2006 y 2016)

The Yaqui Valley territory in the northwest of Mexico was analyzed using networks theory that determines the flows density and actors centrality among the agricultural sector. These networks were those of public, financial, commercial, technical, and social policy management. The current research has been carried out with the general objective of identifying the actors that make up the networks in the Yaqui territory and their change in densities as one of the factors that determine the effectiveness of the policy applied in the territory, comparing two samples of 2006 and 2016. Linked to this objective, it is proposed to describe the obstacles for the densification of networks that favor the agricultural producers labor in the Yaqui Valley territory. The obtained results indicate a clear disarticulation in the different networks of study that can elicit serious social problems of inequality among the actors that are active in the agricultural sector. The networks found in the territory of the Yaqui Valley have been disarticulated over time, because ten years after being analyzed for the first time, the calculation of densities has been reduced by 24% on average, and the truss of the social sector practically tends to disappear.Se analizó el territorio del Valle del Yaqui, en el noroeste de México, utilizando la teoría de redes que permiten determinar la densidad de flujos y centralidad de actores del sector agrícola. Estas redes fueron las de gestión de política pública, financiera, comercial, técnica y social. La presente investigación se ha llevado a cabo con el objetivo general de identificar los actores que conforman las redes en el territorio Yaqui y su cambio en las densidades como uno de los factores que determinan la eficacia de la política aplicada en el territorio, comparando dos muestras de 2006 y 2016. Vinculado a este objetivo se plantea describir los obstáculos para la densificación de las redes que favorezcan el trabajo de los productores agrícolas en el territorio del valle del Yaqui. Los resultados obtenidos indican una clara desarticulación en las diferentes redes, que puede provocar serios problemas sociales de desigualdad entre los actores que se encuentran activos en el sector agrícola. Las redes encontradas en el territorio del Valle del Yaqui, han ido desarticulándose a través del tiempo, debido a que, a diez años de haberse analizado por primera vez, el cálculo de las densidades se ha reducido en un 24% en promedio, y el entramado del sector social prácticamente tiende a desaparecer.Fil: Hernández Hernández, Ma. Leticia. Universidad de Córdoba (España)Fil: Gallardo Cobos, Rosa. Universidad de Córdoba (España)Fil: Dios-Palomares, Rafaela. Universidad de Córdoba (España)Fil: Martínez Pellégrini, Sárah Eva. Universidad Autónoma Chapingo (México

Synthèses de connaissances sur le genre et les systèmes ESEC

English version in the LibraryAffaires mondiales Canad

Selective Ethylene Glycol Oxidation to Formate on Nickel Selenide with Simultaneous Evolution of Hydrogen

There is an urgent need for cost-effective strategies to produce hydrogen from renewable net-zero carbon sources using renewable energies. In this context, the electrochemical hydrogen evolution reaction can be boosted by replacing the oxygen evolution reaction with the oxidation of small organic molecules, such as ethylene glycol (EG). EG is a particularly interesting organic liquid with two hydroxyl groups that can be transformed into a variety of C1 and C2 chemicals, depending on the catalyst and reaction conditions. Here, a catalyst is demonstrated for the selective EG oxidation reaction (EGOR) to formate on nickel selenide. The catalyst nanoparticle (NP) morphology and crystallographic phase are tuned to maximize its performance. The optimized NiS electrocatalyst requires just 1.395 V to drive a current density of 50 mA cm −2 in 1 potassium hydroxide (KOH) and 1 EG. A combination of in situ electrochemical infrared absorption spectroscopy (IRAS) to monitor the electrocatalytic process and ex situ analysis of the electrolyte composition shows the main EGOR product is formate, with a Faradaic efficiency above 80%. Additionally, C2 chemicals such as glycolate and oxalate are detected and quantified as minor products. Density functional theory (DFT) calculations of the reaction process show the glycol-to-oxalate pathway to be favored via the glycolate formation, where the C-C bond is broken and further electro-oxidized to formate. A combination of in situ and ex situ analysis shows the main product of the ethylene glycol (EG) oxidation reaction (EGOR) is formate with a Faradaic efficiency above 80%, and glycolate and oxalate as minor chemicals on nickel selenide nanoparticles (NPs). Further density functional theory (DFT) calculation reveals the electrooxidation mechanism to these products

From mouse to human: cellular morphometric subtype learned from mouse mammary tumors provides prognostic value in human breast cancer

Mouse models of cancer provide a powerful tool for investigating all aspects of cancer biology. In this study, we used our recently developed machine learning approach to identify the cellular morphometric biomarkers (CMB) from digital images of hematoxylin and eosin (H&E) micrographs of orthotopic Trp53-null mammary tumors (n = 154) and to discover the corresponding cellular morphometric subtypes (CMS). Of the two CMS identified, CMS-2 was significantly associated with shorter survival (p = 0.0084). We then evaluated the learned CMB and corresponding CMS model in MMTV-Erbb2 transgenic mouse mammary tumors (n = 53) in which CMS-2 was significantly correlated with the presence of metastasis (p = 0.004). We next evaluated the mouse CMB and CMS model on The Cancer Genome Atlas breast cancer (TCGA-BRCA) cohort (n = 1017). Kaplan–Meier analysis showed significantly shorter overall survival (OS) of CMS-2 patients compared to CMS-1 patients (p = 0.024) and added significant prognostic value in multi-variable analysis of clinical and molecular factors, namely, age, pathological stage, and PAM50 molecular subtype. Thus, application of CMS to digital images of routine workflow H&E preparations can provide unbiased biological stratification to inform patient care.This work was supported by the Department of Defense (DoD)BCRP: BC190820 (J-HM); and the National Cancer Institute (NCI) at the National Institutes of Health (NIH): R01CA184476 (HC). Lawrence Berkeley National Laboratory (LBNL) is a multi-program national laboratory operated by the University of California for the DOE under contract DE AC02-05CH1123

Estimating causes of death where there is no medical certification: evolution and state of the art of verbal autopsy

Over the past 70 years, significant advances have been made in determining the causes of death in populations not served by official medical certification of cause at the time of death using a technique known as Verbal Autopsy (VA). VA involves an interview of the family or caregivers of the deceased after a suitable bereavement interval about the circumstances, signs and symptoms of the deceased in the period leading to death. The VA interview data are then interpreted by physicians or, more recently, computer algorithms, to assign a probable cause of death. VA was originally developed and applied in field research settings. This paper traces the evolution of VA methods with special emphasis on the World Health Organization's (WHO)'s efforts to standardize VA instruments and methods for expanded use in routine health information and vital statistics systems in low- and middle-income countries (LMICs). These advances in VA methods are culminating this year with the release of the 2022 WHO Standard Verbal Autopsy (VA) Toolkit. This paper highlights the many contributions the late Professor Peter Byass made to the current VA standards and methods, most notably, the development of InterVA, the most commonly used automated computer algorithm for interpreting data collected in the WHO standard instruments, and the capacity building in low- and middle-income countries (LMICs) that he promoted. This paper also provides an overview of the methods used to improve the current WHO VA standards, a catalogue of the changes and improvements in the instruments, and a mapping of current applications of the WHO VA standard approach in LMICs. It also provides access to tools and guidance needed for VA implementation in Civil Registration and Vital Statistics Systems at scale

Characterization of Nkx6-2-Derived Neocortical Interneuron Lineages

Ventral telencephalic progenitors expressing the homeodomain transcription factor Nkx6-2 have been shown to give rise to a multitude of cortical interneuron subtypes usually associated with origin in either the medial ganglionic eminence or the caudal ganglionic eminence. The function of Nkx6-2 in directing the fate of those progenitors has, however, not been thoroughly analyzed. We used a combination of genetic inducible fate mapping and in vivo loss-of-function to analyze the requirement of Nkx6-2 in determining the fate of cortical interneurons. We have found that interneuron subtypes are born with a characteristic temporal pattern. Furthermore, we extend the characterization of interneurons from the Nkx6-2 lineage through the application of electrophysiological methods. Analysis of these populations in Nkx6-2 null mice suggests that there is a small and partially penetrant loss of delayed non-fast spiking somatostatin/calretinin double positive cortical interneurons in the absence of Nkx6-2 gene function

The Role of Robo3 in the Development of Cortical Interneurons

A number of studies in recent years have shown that members of the Roundabout (Robo) receptor family, Robo1 and Robo2, play significant roles in the formation of axonal tracks in the developing forebrain and in the migration and morphological differentiation of cortical interneurons. Here, we investigated the expression and function of Robo3 in the developing cortex. We found that this receptor is strongly expressed in the preplate layer and cortical hem of the early cortex where it colocalizes with markers of Cajal–Retzius cells and interneurons. Analysis of Robo3 mutant mice at early (embryonic day [E] 13.5) and late (E18.5) stages of corticogenesis revealed no significant change in the number of interneurons, but a change in their morphology at E13.5. However, preliminary analysis on a small number of mice that lacked all 3 Robo receptors indicated a marked reduction in the number of cortical interneurons, but only a limited effect on their morphology. These observations and the results of other recent studies suggest a complex interplay between the 3 Robo receptors in regulating the number, migration and morphological differentiation of cortical interneurons

Image_1_From Mouse to Human: Cellular Morphometric Subtype Learned From Mouse Mammary Tumors Provides Prognostic Value in Human Breast Cancer.pdf [Dataset]

Supplementary Figure 1. Representative examples of 256 CMB learned from Trp53-null mouse mammary tumors. Supplementary Figure 2. Consensus clustering on the Trp53-null mouse mammary tumors with different number of clusters (K) and the corresponding Kaplan–Meier curves for tumor growth. A-B. Consensus matrix with 3 and 4 clusters, respectively; C-D Kaplan–Meier curves for 3 and 4 subtypes, respectively. Supplementary Figure 3. Representative example of CMB_13 (A), CMB_249 (D), CMB_120 (G), and CMB_105 (J), and their significant and consistent difference in relative abundance between metastasis ground truth (B, E, H, and K) and low/high metastasis risk groups (i.e., LMRG and HMRG defined by CMS-1 and CMS-2, respectively) (C, F, I, and L). Supplementary Figure 4. BRCA patient subtypes in triple-negative (TNBC) and non-triplenegative (Non-TNBC) groups. A-B. KM curves for representative CMBs show consistent and significant impact on OS in Non-TNBC and TNBC groups, respectively; C. Subtype-specific patients in TCGA-BRCA cohort form distinct clusters in patient-level cellular morphometric context space in Non-TNBC and TNBC groups, respectively; D. Subtype-specific patients in TCGA-BRCA cohort show significant difference in survival in Non-TNBC and TNBC groups, respectively. Supplementary Figure 5. A. BRCA patient heatmap with mouse CMS model on the TCGABRCA cohort; B. BRCA patient heatmap with BC-CMS model on the TCGA-BRCA cohort. C. ROC curves for the prediction of 5-,10-, and 20-year overall survival of BRCA patients using all significant prognostic factors as listed in E; D. Comparison of predictive power between BC-CMS model and mouse CMS model using bootstrapping strategy with 80% sampling rate and 1000 iterations; E. Similar to patient subtype from BC-CMS model as shown in Figure 3F, patient subtype directly predicted from the mouse CMS model is also a significant and independent prognostic factor in the TCGA-BRCA cohort. Supplementary Figure 6. BC-CMS in triple-negative (TNBC) and non-triple-negative (NonTNBC) groups in the TCGA-BRCA cohort show significant difference in tumor microenvironments.Mouse models of cancer provide a powerful tool for investigating all aspects of cancer biology. In this study, we used our recently developed machine learning approach to identify the cellular morphometric biomarkers (CMB) from digital images of hematoxylin and eosin (H&E) micrographs of orthotopic Trp53-null mammary tumors (n = 154) and to discover the corresponding cellular morphometric subtypes (CMS). Of the two CMS identified, CMS-2 was significantly associated with shorter survival (p = 0.0084). We then evaluated the learned CMB and corresponding CMS model in MMTV-Erbb2 transgenic mouse mammary tumors (n = 53) in which CMS-2 was significantly correlated with the presence of metastasis (p = 0.004). We next evaluated the mouse CMB and CMS model on The Cancer Genome Atlas breast cancer (TCGA-BRCA) cohort (n = 1017). Kaplan–Meier analysis showed significantly shorter overall survival (OS) of CMS-2 patients compared to CMS-1 patients (p = 0.024) and added significant prognostic value in multi-variable analysis of clinical and molecular factors, namely, age, pathological stage, and PAM50 molecular subtype. Thus, application of CMS to digital images of routine workflow H&E preparations can provide unbiased biological stratification to inform patient care.Peer reviewe