Quantifying quantitative literacy: Age heaping and the history of human capital

Age data frequently display excess frequencies at round or attractive ages, such as even numbers and multiples of five. This phenomenon of age heaping has been viewed as a problem in previous research, especially in demography and epidemiology. We see it as an opportunity and propose its use as a measure of human capital that can yield comparable estimates across a wide range of historical contexts. A simulation study yields methodological guidelines for measuring and interpreting differences in ageheaping, while analysis of contemporary and historical datasets demonstrates the existence of a robust correlation between age heaping and literacy at both the individual and aggregate level. To illustrate the method, we generate estimates of human capital in Europe over the very long run, which support the hypothesis of a major increase in human capital preceding the industrial revolution.

A dynamic analysis of human welfare in a warming planet

Climate science indicates that climate stabilization requires low GHG emissions. Is thisconsistent with nondecreasing human welfare?Our welfare or utility index emphasizes education, knowledge, and the environment. Weconstruct and calibrate a multigenerational model with intertemporal links provided by education,physical capital, knowledge and the environment.We reject discounted utilitarianism and adopt, first, the Pure Sustainability Optimization (orIntergenerational Maximin) criterion, and, second, the Sustainable Growth Optimization criterion,that maximizes the utility of the first generation subject to a given future rate of growth. We applythese criteria to our calibrated model via a novel algorithm inspired by the turnpike property.The computed paths yield levels of utility higher than the level at reference year 2000 for allgenerations. They require the doubling of the fraction of labor resources devoted to the creation ofknowledge relative to the reference level, whereas the fractions of labor allocated to consumptionand leisure are similar to the reference ones. On the other hand, higher growth rates requiresubstantial increases in the fraction of labor devoted to education, together with moderate increasesin the fractions of labor devoted to knowledge and the investment in physical capital.

Statistical analysis of maximum likelihood estimator images of human brain FDG PET studies

The work presented evaluates the statistical characteristics of regional bias and expected error in reconstructions of real positron emission tomography (PET) data of human brain fluoro-deoxiglucose (FDG) studies carried out by the maximum likelihood estimator (MLE) method with a robust stopping rule, and compares them with the results of filtered backprojection (FBP) reconstructions and with the method of sieves. The task of evaluating radioisotope uptake in regions-of-interest (ROIs) is investigated. An assessment of bias and variance in uptake measurements is carried out with simulated data. Then, by using three different transition matrices with different degrees of accuracy and a components of variance model for statistical analysis, it is shown that the characteristics obtained from real human FDG brain data are consistent with the results of the simulation studies.

Self-similar community structure in a network of human interactions

We propose a procedure for analyzing and characterizing complex networks. We apply this to the social network as constructed from email communications within a medium sized university with about 1700 employees. Email networks provide an accurate and nonintrusive description of the flow of information within human organizations. Our results reveal the self-organization of the network into a state where the distribution of community sizes is self-similar. This suggests that a universal mechanism, responsible for emergence of scaling in other self-organized complex systems, as, for instance, river networks, could also be the underlying driving force in the formation and evolution of social networks.

Characterization of human pancreatic orthotopic tumor xenografts suitable for drug screening

Background Efforts to identify novel therapeutic options for human pancreatic ductal adenocarcinoma (PDAC) have failed to result in a clear improvement in patient survival to date. Pancreatic cancer requires efficient therapies that must be designed and assayed in preclinical models with improved predictor ability. Among the available preclinical models, the orthotopic approach fits with this expectation, but its use is still occasional. Methods An in vivo platform of 11 orthotopic tumor xenografts has been generated by direct implantation of fresh surgical material. In addition, a frozen tumorgraft bank has been created, ensuring future model recovery and tumor tissue availability. Results Tissue microarray studies allow showing a high degree of original histology preservation and maintenance of protein expression patterns through passages. The models display stable growth kinetics and characteristic metastatic behavior. Moreover, the molecular diversity may facilitate the identification of tumor subtypes and comparison of drug responses that complement or confirm information obtained with other preclinical models. Conclusions This panel represents a useful preclinical tool for testing new agents and treatment protocols and for further exploration of the biological basis of drug responses.

Characterization of human pancreatic orthotopic tumor xenografts suitable for drug screening

Background Efforts to identify novel therapeutic options for human pancreatic ductal adenocarcinoma (PDAC) have failed to result in a clear improvement in patient survival to date. Pancreatic cancer requires efficient therapies that must be designed and assayed in preclinical models with improved predictor ability. Among the available preclinical models, the orthotopic approach fits with this expectation, but its use is still occasional. Methods An in vivo platform of 11 orthotopic tumor xenografts has been generated by direct implantation of fresh surgical material. In addition, a frozen tumorgraft bank has been created, ensuring future model recovery and tumor tissue availability. Results Tissue microarray studies allow showing a high degree of original histology preservation and maintenance of protein expression patterns through passages. The models display stable growth kinetics and characteristic metastatic behavior. Moreover, the molecular diversity may facilitate the identification of tumor subtypes and comparison of drug responses that complement or confirm information obtained with other preclinical models. Conclusions This panel represents a useful preclinical tool for testing new agents and treatment protocols and for further exploration of the biological basis of drug responses.

Regulation of human class I alcohol dehydrogenases by bile acids

Class I alcohol dehydrogenases (ADH1s) are the rate-limiting enzymes for ethanol and vitamin A (retinol) metabolism in the liver . Because previous studies have shown that human ADH1 enzymes may participate in bile acid metabolism, we investigated whether the bile acid-activated nuclear receptor farnesoid X receptor (FXR) regulates ADH1 genes. In human hepatocytes, both the endogenous FXR ligand chenodeoxycholic acid and synthetic FXR-specific agonist GW4064 increased ADH1 mRNA, protein, and activity. Moreover, overexpression of a constitutively active form of FXR induced ADH1A and ADH1B expression, whereas silencing of FXR abolished the effects of FXR agonists on ADH1 expression and activity. Transient transfection studies and electrophoretic mobility shift assays revealed functional FXR response elements in the ADH1A and ADH1B proximal promoters, thus indicating that both genes are direct targets of FXR. These findings provide the first evidence for direct connection of bile acid signaling and alcohol metabolism.

The complex organization of human cognitive domains and their heritability: a systematic review

Una revisión sistemática de la organización compleja de los dominios cognitivos humanos y su heredabilidad. Antecedentes: se ha propuesto que la estructura de la cognición humana respondería a un sistema jerárquico, donde las secuencias propias a una acción se organizarían desde sub-unidades de análisis hasta funciones de nivel superior relativamente complejas. Esta estructura organizacional estaría reflejada en las representaciones neurales que subyacen al comportamiento humano, así como también en sus sustratos genéticos. El objetivo del presente estudio fue explorar la posible organización jerárquica de las influencias genéticas subyacentes a los dominios cognitivos humanos. Método: se revisaron treinta y cuatro estudios de la heredabilidad de la cognición en muestras de la población general, que incluyeron medidas de inteligencia, habilidades verbales y manipulativas, memoria, memoria de trabajo y velocidad de procesamiento. Resultados: diversos dominios cognitivos mostraron distintas proporciones de influencias genéticas, con las mayores estimaciones de heredabilidad halladas para las funciones cognitivas de nivel superior y las menores estimaciones para las funciones de orden medio o inferior. Conclusiones: tomando como referencia los conocimientos actuales acerca del neurodesarrollo humano, las contribuciones genéticas de las habilidades cognitivas parecen organizarse paralelamente al crecimiento ontogénico del cerebro. Se discuten estos resultados en relación a la interacción entre el control genético de las funciones cognitivas y sus influencias ambientales.

Self-similar community structure in a network of human interactions

We propose a procedure for analyzing and characterizing complex networks. We apply this to the social network as constructed from email communications within a medium sized university with about 1700 employees. Email networks provide an accurate and nonintrusive description of the flow of information within human organizations. Our results reveal the self-organization of the network into a state where the distribution of community sizes is self-similar. This suggests that a universal mechanism, responsible for emergence of scaling in other self-organized complex systems, as, for instance, river networks, could also be the underlying driving force in the formation and evolution of social networks.