Corrección de defectos óseos en el área de Ingeniería tisular

Correction of bone defects by tissue Engineering

ROSA ALICIA SAUCEDO ACUÑA MONICA GALICIA GARCIA JUDITH VIRGINIA RIOS ARANA SIMON YOBANNY REYES LOPEZ (2012, [Artículo])

Hoy en día, los defectos óseos representan uno de los casos de mayor impacto en la salud debido a la frecuencia con que éstos ocurren a causa de traumatismos, fracturas, enfermedades congénitas o degenerativas. En la actualidad, los implantes de tejido óseo de gran volumen se encuentran severamente restringidos a causa de las limitaciones de difusión en la interacción con el ambiente del huésped para los nutrientes, intercambio gaseoso y eliminación de desechos. Es por ello que la corrección de los defectos óseos ha cobrado gran importancia en el área de Ingeniería tisular buscando mejorar las estrategias clínicas para su tratamiento. El propósito de esta revisión es proporcionar un panorama general del desarrollo de andamios para la regeneración de tejido óseo, mostrando los avances logrados en los ensayos in vitro e in vivo en la última década

Currently, bone defects cases represent a major impact on health due to how often they occur because of trauma, fractures, congenital or degenerative diseases. Now, bone implants to large volume are severely restricted because of the diffusion limitations in the interaction

with the environment of the host for nutrients, gas exchange and waste disposal. That is why the correction of bone defects has become very important in the field of tissue engineering looking to improve clinical strategies for treatment. The purpose of this review is to provide an overview of the development of scaffolds for bone tissue regeneration, showing the progress made in the in vitro and in vivo in recent decades.

MEDICINA Y CIENCIAS DE LA SALUD Ingeniería tisular regeneración ósea Andamio Tissue engineering Bone regeneration Scaffolds

Using an incomplete block design to allocate lines to environments improves sparse genome-based prediction in plant breeding

Osval Antonio Montesinos-Lopez ABELARDO MONTESINOS LOPEZ RICARDO ACOSTA DIAZ Rajeev Varshney Jose Crossa ALISON BENTLEY (2022, [Artículo])

Genomic selection (GS) is a predictive methodology that trains statistical machine-learning models with a reference population that is used to perform genome-enabled predictions of new lines. In plant breeding, it has the potential to increase the speed and reduce the cost of selection. However, to optimize resources, sparse testing methods have been proposed. A common approach is to guarantee a proportion of nonoverlapping and overlapping lines allocated randomly in locations, that is, lines appearing in some locations but not in all. In this study we propose using incomplete block designs (IBD), principally, for the allocation of lines to locations in such a way that not all lines are observed in all locations. We compare this allocation with a random allocation of lines to locations guaranteeing that the lines are allocated to

the same number of locations as under the IBD design. We implemented this benchmarking on several crop data sets under the Bayesian genomic best linear unbiased predictor (GBLUP) model, finding that allocation under the principle of IBD outperformed random allocation by between 1.4% and 26.5% across locations, traits, and data sets in terms of mean square error. Although a wide range of performance improvements were observed, our results provide evidence that using IBD for the allocation of lines to locations can help improve predictive performance compared with random allocation. This has the potential to be applied to large-scale plant breeding programs.

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA Bayes Theorem Genome Inflammatory Bowel Diseases Models, Genetic Plant Breeding

Big data, small explanatory and predictive power: Lessons from random forest modeling of on-farm yield variability and implications for data-driven agronomy

Martin van Ittersum (2023, [Artículo])

Context: Collection and analysis of large volumes of on-farm production data are widely seen as key to understanding yield variability among farmers and improving resource-use efficiency. Objective: The aim of this study was to assess the performance of statistical and machine learning methods to explain and predict crop yield across thousands of farmers’ fields in contrasting farming systems worldwide. Methods: A large database of 10,940 field-year combinations from three countries in different stages of agricultural intensification was analyzed. Random effects models were used to partition crop yield variability and random forest models were used to explain and predict crop yield within a cross-validation scheme with data re-sampling over space and time. Results: Yield variability in relative terms was smallest for wheat and barley in the Netherlands and for wheat in Ethiopia, intermediate for rice in the Philippines, and greatest for maize in Ethiopia. Random forest models comprising a total of 87 variables explained a maximum of 65 % of cereal yield variability in the Netherlands and less than 45 % of cereal yield variability in Ethiopia and in the Philippines. Crop management related variables were important to explain and predict cereal yields in Ethiopia, while predictive (i.e., known before the growing season) climatic variables and explanatory (i.e., known during or after the growing season) climatic variables were most important to explain and predict cereal yield variability in the Philippines and in the Netherlands, respectively. Finally, model cross-validation for regions or years not seen during model training reduced the R2 considerably for most crop x country combinations, while for wheat in the Netherlands this was model dependent. Conclusion: Big data from farmers’ fields is useful to explain on-farm yield variability to some extent, but not to predict it across time and space. Significance: The results call for moderate expectations towards big data and machine learning in agronomic studies, particularly for smallholder farms in the tropics where model performance was poorest independently of the variables considered and the cross-validation scheme used.

Model Accuracy Model Precision Linear Mixed Models CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA MACHINE LEARNING SUSTAINABLE INTENSIFICATION BIG DATA YIELDS MODELS AGRONOMY

Economic inequality and the impact of cash transfers in the state of Veracruz, México, 2008 to 2020

José Alejandro Pérez-Nájera Rogelio Javier Rendón Hernández (2023, [Artículo, Artículo])

Income inequality in Mexico is extremely high and the federal states are considerably heterogeneous, which is why a regional analysis allows us to identify the fundamental characteristics, trends, and regional conditions for the implementation of redistributive policies.  We used microdata from the National Household Income and Expenditure Survey (ENIGH) to analyze the evolution of income inequality in the state of Veracruz during the 2008-2020 period; To identify its sources and investigate how it was affected by monetary transfers, the income decomposition method is used to identify the ENIGH income sources and investigate preliminary COVID-19 effects. The results show evidence of a decrease in inequality in the period; relatively and marginally, it is identified that the observed decrease can be attributed to cash transfers. In recent years, transfers represented 30% of the income of the lowest deciles (I, II, and III) and the income elasticity of the Gini coefficient indicates that their increase represents a decrease in inequality.

Desigualdad ingresos monetarios elasticidad del ingreso Políticas Sociales distribución del ingreso CIENCIAS SOCIALES CIENCIAS SOCIALES Cash transfers income elasticities inequality monetary income

Multicriteria assessment of alternative cropping systems at farm level. A case with maize on family farms of South East Asia

Santiago Lopez-Ridaura (2023, [Artículo])

CONTEXT: Integration of farms into markets with adoption of maize as a cash crop can significantly increase income of farms of the developing world. However, in some cases, the income generated may still be very low and maize production may also have strong negative environmental and social impacts. OBJECTIVE: Maize production in northern Laos is taken as a case to study how far can farms' performance be improved with improved crop management of maize with the following changes at field level: good timing and optimal soil preparation and sowing, allowing optimal crop establishment and low weed infestation. METHODS: We compared different farm types' performance on locally relevant criteria and indicators embodying the three pillars of sustainability (environmental, economic and social). An integrated assessment approach was combined with direct measurement of indicators in farmers' fields to assess eleven criteria of local farm sustainability. A bio-economic farm model was used for scenario assessment in which changes in crop management and the economic environment of farms were compared to present situation. The farm model was based on mathematical programming maximizing income under constraints related to i) household composition, initial cash and rice stocks and land type, and ii) seasonal balances of cash, labour and food. The crop management scenarios were built based on a diagnosis of the causes of variations in the agronomic and environmental performances of cropping systems, carried out in farmers' fields. RESULTS AND CONCLUSIONS: Our study showed that moderate changes in crop management on maize would improve substantially farm performance on 4 to 6 criteria out of the 11 assessed, depending on farm types. The improved crop management of maize had a high economic attractiveness for every farm type simulated (low, medium and high resource endowed farms) even at simulated production costs more than doubling current costs of farmers' practices. However, while an improvement of the systems performance was attained in terms of agricultural productivity, income generation, work and ease of work, herbicide leaching, improved soil quality and nitrogen balance, trade-offs were identified with other indicators such as erosion control and cash outflow needed at the beginning of the cropping season. SIGNIFICANCE: Using farm modelling for multicriteria assessment of current and improved maize cropping systems for contrasted farm types helped capture main opportunities and constraints on local farm sustainability, and assess the trade-offs that new options at field level may generate at farm level.

Bio-Economic Farm Model Smallholder Farms CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CASH CROPS INDICATORS SMALLHOLDERS CROPPING SYSTEMS MAIZE

Teacher training in the state of Chihuahua: Between the health challenge and teacher resilience

Evangelina Cervantes Holguín Pavel Roel Gutiérrez Sandoval Cely Celene Ronquillo Chávez (2023, [Artículo, Artículo])

The article proposes to recover the response of the Teacher Training and Updating Institutions in the state of Chihuahua regarding the various challenges imposed by the Coronavirus Disease (COVID-19). The qualitative exercise analyzes the experience of 10 institutions based on the voice of their students, teachers, and principals regarding changes in academic, administrative, and organizational processes. It is concluded that the pandemic has affected each institution in different ways and with diverse intensity. Despite the achievements, the experience analyzed reveals the relative success of the using virtual platforms in the face of three basic conditions: connectivity, technological competencies, and socio-emotional skills of the teaching staff. It highlights the importance of implementing tutoring, resilience, or awareness actions of teachers and students' needs, feelings, and sufferings. It is opportune to recover the experiences of other institutions and to question especially students, thesis students and graduates.

Acceso a la educación Aprendizaje en línea Educación a distancia Formación de docentes Tecnología educacional HUMANIDADES Y CIENCIAS DE LA CONDUCTA HUMANIDADES Y CIENCIAS DE LA CONDUCTA Access to education online learning distance education teacher education educational technology

Democracia, gobierno y administración pública en la Ciudad de México

FRANCISCO JOSE DIAZ CASILLAS (2004, [Capítulo de libro])

Capítulo de la sección: Comunicación y Sociedad Sustentable.

Hablar de democracia, gobierno y administración en la Ciudad de México, nos remite a dos momentos históricos del pasado reciente: el primero hace referencia a 1994, fecha en que aparece la Ley de Participación Ciudadana, primera normatividad político administrativa de corte ciudadano, que presenta objetivos que enlazan el quehacer gubernamental con las necesidades ciudadanas; el segundo se da en 1997 con la aparición y ascenso de un Jefe de Gobierno, que a diferencia de sus antecesores, que fungían como Jefes del Departamento del Distrito Federal, eran nombrados por el Ejecutivo Federal y actuaban con facultades delegadas, en tanto que el Jefe de Gobierno es electo de manera directa y actúa con facultades autónomas. De esta forma con un gobierno autónomo, los habitantes de la Ciudad de México dejaron de considerarse como "ciudadanos de segunda", como en algún momento se les calificó, debido a que no contaban con sus derechos jurídicos de votar por las personas que los gobernaban, con el primer Jefe de Gobierno electo en 1997, se marca un "parteaguas" en la vida del Distrito Federal en donde las formas de hacer gobierno y administración pública provocan nuevos esquemas y formas de actuación política y administrativa.

Political participation--Mexico--Mexico City. Public administration--Citizen participation. Democracy--Mexico--Mexico City. Mexico City (Mexico)--Politics and government. Administración pública -- Participación ciudadana. Democracia. JS2137.A2 CIENCIAS SOCIALES CIENCIA POLÍTICA ADMINISTRACIÓN PÚBLICA

Genetic effects of Rht-B1b and Rht-D1b dwarfing alleles on plant height and agronomic traits of bread wheat (Triticum aestivum L.) breeding lines

Zine El Abidine Fellahi Abderrahmane Hannachi Susanne Dreisigacker deepmala sehgal Hamenna Bouzerzour (2023, [Artículo])

Pleiotropic Effects Reduced Height Genes CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA PLANT HEIGHT TRITICUM AESTIVUM YIELD COMPONENTS ALLELES BREEDING LINES

The impact of 1.5 °C and 2.0 °C global warming on global maize production and trade

Wei Xiong Tariq Ali (2022, [Artículo])

Future Climate Scenario Data Yield Reduction Risk CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CLIMATE CHANGE GREENHOUSE EFFECT MAIZE MITIGATION SIMULATION ACCLIMATIZATION ADAPTATION GLOBAL WARMING

Genomic prediction of yield performance among single-cross maize hybrids using a partial diallel cross design

Junjie Fu XUECAI ZHANG (2023, [Artículo])

Genomic Prediction Prediction Model Genetic Effects Hybrid Performance CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA MAIZE GENETICS HYBRIDS PERFORMANCE ASSESSMENT