Key morphological features of human pyramidal neurons.

The basic building block of the cerebral cortex, the pyramidal cell, has been shown to be characterized by a markedly different dendritic structure among layers, cortical areas, and species. Functionally, differences in the structure of their dendrites and axons are critical in determining how neurons integrate information. However, within the human cortex, these neurons have not been quantified in detail. In the present work, we performed intracellular injections of Lucifer Yellow and 3D reconstructed over 200 pyramidal neurons, including apical and basal dendritic and local axonal arbors and dendritic spines, from human occipital primary visual area and associative temporal cortex. We found that human pyramidal neurons from temporal cortex were larger, displayed more complex apical and basal structural organization, and had more spines compared to those in primary sensory cortex. Moreover, these human neocortical neurons displayed specific shared and distinct characteristics in comparison to previously published human hippocampal pyramidal neurons. Additionally, we identified distinct morphological features in human neurons that set them apart from mouse neurons. Lastly, we observed certain consistent organizational patterns shared across species. This study emphasizes the existing diversity within pyramidal cell structures across different cortical areas and species, suggesting substantial species-specific variations in their computational properties.

Inequalities in Violent Death across Income Levels among Young Males and Females in Countries of the Americas.

BACKGROUND: Violent deaths (i.e., those due to road traffic injury, homicide, and suicide) are among the most important causes of premature and preventable mortality in young people. This study aimed at exploring inequalities in violent death across income levels between males and females aged 10 to 24 years from the Americas in 2015, the SDG baseline year. METHODS: In a cross-sectional ecological study design, eleven standard summary measures of health inequality were calculated separately for males and females and for each cause of violent death, using age-adjusted mortality rates and average income per capita for 17 countries, which accounted for 87.9% of the target population. RESULTS: Premature mortality due to road traffic injury and homicide showed a pro-poor inequality pattern, whereas premature mortality due to suicide showed a pro-rich inequality pattern. These inequalities were statistically significant (p < 0.001), particularly concentrated among young males, and dominated by homicide. The ample array of summary measures of health inequality tended to generate convergent results. CONCLUSIONS: Significant inequalities in violent death among young people seems to be in place across countries of the Americas, and they seem to be socially determined by both income and gender. These findings shed light on the epidemiology of violent death in young people and can inform priorities for regional public health action. However, further investigation is needed to confirm inequality patterns and to explore underlying mechanisms, age- and sex-specific vulnerabilities, and gender-based drivers of such inequalities.

Action on the social determinants for advancing health equity in the time of COVID-19: perspectives of actors engaged in a WHO Special Initiative.

Since the 2008 publication of the reports of the Commission on Social Determinants of Health and its nine knowledge networks, substantial research has been undertaken to document and describe health inequities. The COVID-19 pandemic has underscored the need for a deeper understanding of, and broader action on, the social determinants of health. Building on this unique and critical opportunity, the World Health Organization is steering a multi-country Initiative to reduce health inequities through an action-learning process in 'Pathfinder' countries. The Initiative aims to develop replicable and reliable models and practices that can be adopted by WHO offices and UN staff to address the social determinants of health to advance health equity. This paper provides an overview of the Initiative by describing its broad theory of change and work undertaken in three regions and six Pathfinder countries in its first year-and-a-half. Participants engaged in the Initiative describe results of early country dialogues and promising entry points for implementation that involve model, network and capacity building. The insights communicated through this note from the field will be of interest for others aiming to advance health equity through taking action on the social determinants of health, in particular as regards structural determinants.

Quantitative analysis of the GABAergic innervation of the soma and axon initial segment of pyramidal cells in the human and mouse neocortex.

Perisomatic GABAergic innervation in the cerebral cortex is carried out mostly by basket and chandelier cells, which differentially participate in the control of pyramidal cell action potential output and synchronization. These cells establish multiple synapses with the cell body (and proximal dendrites) and the axon initial segment (AIS) of pyramidal neurons, respectively. Using multiple immunofluorescence, confocal microscopy and 3D quantification techniques, we have estimated the number and density of GABAergic boutons on the cell body and AIS of pyramidal neurons located through cortical layers of the human and mouse neocortex. The results revealed, in both species, that there is clear variability across layers regarding the density and number of perisomatic GABAergic boutons. We found a positive linear correlation between the surface area of the soma, or the AIS, and the number of GABAergic terminals in apposition to these 2 neuronal domains. Furthermore, the density of perisomatic GABAergic boutons was higher in the human cortex than in the mouse. These results suggest a selectivity for the GABAergic innervation of the cell body and AIS that might be related to the different functional attributes of the microcircuits in which neurons from different layers are involved in both human and mouse.

A Deep Learning-Based Workflow for Dendritic Spine Segmentation.

The morphological analysis of dendritic spines is an important challenge for the neuroscientific community. Most state-of-the-art techniques rely on user-supervised algorithms to segment the spine surface, especially those designed for light microscopy images. Therefore, processing large dendritic branches is costly and time-consuming. Although deep learning (DL) models have become one of the most commonly used tools in image segmentation, they have not yet been successfully applied to this problem. In this article, we study the feasibility of using DL models to automatize spine segmentation from confocal microscopy images. Supervised learning is the most frequently used method for training DL models. This approach requires large data sets of high-quality segmented images (ground truth). As mentioned above, the segmentation of microscopy images is time-consuming and, therefore, in most cases, neuroanatomists only reconstruct relevant branches of the stack. Additionally, some parts of the dendritic shaft and spines are not segmented due to dyeing problems. In the context of this research, we tested the most successful architectures in the DL biomedical segmentation field. To build the ground truth, we used a large and high-quality data set, according to standards in the field. Nevertheless, this data set is not sufficient to train convolutional neural networks for accurate reconstructions. Therefore, we implemented an automatic preprocessing step and several training strategies to deal with the problems mentioned above. As shown by our results, our system produces a high-quality segmentation in most cases. Finally, we integrated several postprocessing user-supervised algorithms in a graphical user interface application to correct any possible artifacts.

Cognitive Screening Instruments for Older Adults with Low Educational and Literacy Levels: A Systematic Review.

This study presents a systematic review on existing cognitive screening tools for mild cognitive impairment and dementia in populations with low education and literacy levels. Cochrane Library, PubMed and LILACS databases were examined for studies including adults aged 50 years old or older with low educational level. 61 articles were included. Despite its frequent use, studies on Mini-Mental State Examination (MMSE) revealed that educational level biased the score obtained, regardless of other factors. Separately, the Informant Questionnaire on Cognitive Decline in the Elderly, the Fototest, or the Eurotest, appear to minimize the effect of education and literacy. MMSE is unreliable for individuals with low literacy. Tasks involving reading, writing, arithmetics, drawing, praxis, visuospatial, and visuoconstructive skills have a greater educational bias than naming, orientation, or memory. An adequate determination of educational level and validation of instruments in populations with heterogeneous levels of literacy requires further research.

Dendritic spines are lost in clusters in Alzheimer's disease.

Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by a deterioration of neuronal connectivity. The pathological accumulation of tau in neurons is one of the hallmarks of AD and has been connected to the loss of dendritic spines of pyramidal cells, which are the major targets of cortical excitatory synapses and key elements in memory storage. However, the detailed mechanisms underlying the loss of dendritic spines in individuals with AD are still unclear. Here, we used graph-theory approaches to compare the distribution of dendritic spines from neurons with and without tau pathology of AD individuals. We found that the presence of tau pathology determines the loss of dendritic spines in clusters, ruling out alternative models where spine loss occurs at random locations. Since memory storage has been associated with synaptic clusters, the present results provide a new insight into the mechanisms by which tau drives synaptic damage in AD, paving the way to memory deficits through alterations of spine organization.

Leaving no one behind: a methodology for setting health inequality reduction targets for Sustainable Development Goal 3.

OBJECTIVES: To present a methodology for the simultaneous setting of quantitative targets that reflect both an improvement in the national average of an indicator for Sustainable Development Goal 3 (SDG3), as well as a reduction in its geographic inequality. METHODS: A five-step algorithm was developed: (a) calculate the national average annual percent change (AAPC) for an SDG3 indicator; (b) normatively define geographic strata from the subnational distribution of the indicator in a baseline year; (c) apply a proportional progressivity criterion to the AAPC to project the stratum-specific indicator value for the target year; (d) set the national target as the weighted average of the indicator in the subnational territorial units for the target year; and (e) set the inequality reduction targets by calculating the absolute and relative gaps between the bottom and top strata for the target year. RESULTS: The algorithm was applied to SDG indicator 3.1.1 (maternal mortality ratio, MMR), disaggregated by Guatemala's 22 departments at the baseline year 2014 (MMR = 113 per 100,000 live births). By sustaining the AAPC rate attained from 2009 to 2014 (-4.3%) and focalizing its actions with territorial progressivity, by 2030 the country could reduce its MMR to 53 per 100,000 and its absolute and relative inequality gaps by 72% and 48%, respectively. CONCLUSIONS: The proposed methodology allows for simultaneously setting targets for overall progress and inequality reduction in health, making explicit the primacy of the equity principle contained in the SDG commitment to leave no one behind, whose urgency takes on renewed relevance in the current pandemic scenario.

Leaving no one behind: a methodology for setting health inequality reduction targets for Sustainable Development Goal 3

[ABSTRACT]. Objectives. To present a methodology for the simultaneous setting of quantitative targets that reflect both an improvement in the national average of an indicator for Sustainable Development Goal 3 (SDG3), as well as a reduction in its geographic inequality. Methods. A five-step algorithm was developed: (a) calculate the national average annual percent change (AAPC) for an SDG3 indicator; (b) normatively define geographic strata from the subnational distribution of the indicator in a baseline year; (c) apply a proportional progressivity criterion to the AAPC to project the stratum-specific indicator value for the target year; (d) set the national target as the weighted average of the indicator in the subnational territorial units for the target year; and (e) set the inequality reduction targets by calculating the absolute and relative gaps between the bottom and top strata for the target year. Results. The algorithm was applied to SDG indicator 3.1.1 (maternal mortality ratio, MMR), disaggregated by Guatemala’s 22 departments at the baseline year 2014 (MMR = 113 per 100,000 live births). By sustaining the AAPC rate attained from 2009 to 2014 (-4.3%) and focalizing its actions with territorial progressivity, by 2030 the country could reduce its MMR to 53 per 100,000 and its absolute and relative inequality gaps by 72% and 48%, respectively. Conclusions. The proposed methodology allows for simultaneously setting targets for overall progress and inequality reduction in health, making explicit the primacy of the equity principle contained in the SDG commitment to leave no one behind, whose urgency takes on renewed relevance in the current pandemic scenario.

[RESUMEN]. Objetivos. Presentar una metodología para la formulación simultánea de metas cuantitativas que reflejen tanto la mejoría del promedio nacional de un indicador del tercer Objetivo de Desarrollo Sostenible (ODS3) como la reducción de su desigualdad geográfica. Métodos. Se definió un algoritmo en cinco pasos: a) cálculo del cambio porcentual anual promedio (CPAP) nacional para un indicador del ODS3; b) definición normativa de estratos geográficos a partir de la distribución subnacional del indicador en un año base; c) aplicación de un criterio de progresividad proporcional del CPAP para proyectar el indicador estrato-específico al año meta; d) establecimiento de la meta nacional como el promedio ponderado del indicador en las unidades territoriales subnacionales al año meta; y e) formulación de metas de reducción de desigualdad mediante el cálculo de las brechas absoluta y relativa entre los estratos extremos al año meta. Resultados. Se aplicó el algoritmo al indicador ODS 3.1.1 (razón de mortalidad materna, RMM), desagregado por los 22 departamentos de Guatemala para el año base 2014 (RMM = 113 por 100 000 nacidos vivos). Sosteniendo la intensidad promedio de CPAP observada entre 2009 y 2014 (-4,3%) y focalizando sus acciones con progresividad territorial, el país reduciría al 2030 su RMM a 53 por 100 000 nacidos vivos y sus brechas absoluta y relativa en 72% y 48%, respectivamente. Conclusiones. La metodología propuesta permite formular simultáneamente metas de reducción de las desigualdades geográficas en salud y hacer explícita la primacía del principio de equidad expresado en el compromiso de no dejar a nadie atrás que identifica a los ODS, cuya urgencia cobra renovada relevancia en el escenario pospandémico actual.

[RESUMO]. Objetivos. Apresentar uma metodologia para a formulação simultânea de metas quantitativas que reflitam tanto a melhoria da média nacional de um indicador do terceiro Objetivo de Desenvolvimento Sustentável (ODS3) quanto a redução das desigualdades geográfica nesse indicador. Métodos. Estabelecemos um algoritmo em cinco etapas: (a) cálculo da variação percentual anual média (VPAM) em um país para um indicador do ODS3, (b) definição normativa de estratos geográficos a partir da distribuição subnacional do indicador em um ano base, (c) aplicação de um critério de progressividade proporcional da VPAM para projetar o indicador específico do estrato para o ano base, (d) estabelecimento da meta nacional como a média ponderada do indicador nas unidades territoriais subnacionais para o ano alvo e (e) estabelecimento de metas para a redução das desigualdades calculando a disparidade absoluta e relativa entre os estratos extremos para o ano alvo. Resultados. Aplicamos o algoritmo ao indicador ODS 3.1.1 (razão de mortalidade materna, RMM), desagregado pelos 22 departamentos da Guatemala para o ano base de 2014 (RMM = 113 por 100.000 nascidos vivos). Se mantiver a intensidade média da VPAM observada entre 2009 e 2014 (-4,3%) e concentrar as suas ações com progressividade territorial, o país reduzirá, até 2030, a sua RMM para 53 por 100.000 e sua disparidade absoluta e relativa em 72% e 48%, respectivamente. Conclusões. A metodologia proposta permite formular simultaneamente metas para a redução das desigualdades geográficas em saúde e explicitar a primazia do princípio da equidade expresso no compromisso de não deixar ninguém para trás consagrado nos ODS, cuja urgência assume uma relevância renovada no atual cenário pós-pandêmico.

Publication rate and citation counts for preprints released during the COVID-19 pandemic: the good, the bad and the ugly.

BACKGROUND: Preprints are preliminary reports that have not been peer-reviewed. In December 2019, a novel coronavirus appeared in China, and since then, scientific production, including preprints, has drastically increased. In this study, we intend to evaluate how often preprints about COVID-19 were published in scholarly journals and cited. METHODS: We searched the iSearch COVID-19 portfolio to identify all preprints related to COVID-19 posted on bioRxiv, medRxiv, and Research Square from January 1, 2020, to May 31, 2020. We used a custom-designed program to obtain metadata using the Crossref public API. After that, we determined the publication rate and made comparisons based on citation counts using non-parametric methods. Also, we compared the publication rate, citation counts, and time interval from posting on a preprint server to publication in a scholarly journal among the three different preprint servers. RESULTS: Our sample included 5,061 preprints, out of which 288 were published in scholarly journals and 4,773 remained unpublished (publication rate of 5.7%). We found that articles published in scholarly journals had a significantly higher total citation count than unpublished preprints within our sample (p < 0.001), and that preprints that were eventually published had a higher citation count as preprints when compared to unpublished preprints (p < 0.001). As well, we found that published preprints had a significantly higher citation count after publication in a scholarly journal compared to as a preprint (p < 0.001). Our results also show that medRxiv had the highest publication rate, while bioRxiv had the highest citation count and shortest time interval from posting on a preprint server to publication in a scholarly journal. CONCLUSIONS: We found a remarkably low publication rate for preprints within our sample, despite accelerated time to publication by multiple scholarly journals. These findings could be partially attributed to the unprecedented surge in scientific production observed during the COVID-19 pandemic, which might saturate reviewing and editing processes in scholarly journals. However, our findings show that preprints had a significantly lower scientific impact, which might suggest that some preprints have lower quality and will not be able to endure peer-reviewing processes to be published in a peer-reviewed journal.

A bibliometric analysis of COVID-19 research in Latin America and the Caribbean / Un análisis bibliométrico de la investigación sobre COVID-19 en Latinoamérica y el Caribe

Abstract Introduction: Latin America and the Caribbean (LAC) is one of the regions most affected by the COVID-19 pandemic. Yet, there is scarce literature addressing the research strategies developed in LAC to face COVID-19. Objective: To quantify and assess the production of scientific publications about COVID-19 in 32 countries of LAC between January 1 and July 31, 2020. Materials and methods: Bibliometric study. Scientific papers on COVID-19 conducted in LAC or reporting data pertaining to LAC and published between January 1 to July 31, 2020, were searched in the Scopus, PubMed, and LILACS databases. A subgroup analysis including only original research articles was performed to determine the contribution of LAC countries to research on COVID-19, and standardization measures (# of articles per million people) were applied to compare the country-specific production of this type of articles. Results: A total of 1 291 publications were retrieved. Overall, most of them were non-original research articles (81.72%), and the countries with the highest scientific production were Brazil (43.91%) and Mexico (9.14%). However, after applying the standardization measures, Chile was the country with the highest production of original articles (0.58 per million inhabitants). Regarding original studies (n=236), cross-sectional design was the most common (25.84%). Diagnosis and treatment of the disease was the main research focus (n=354; 27.42%). However, in the subgroup analysis (n=236), epidemiology and surveillance were the most prevalent research focus (n=57; 24.15%). Conclusions: During the study period, non-original research articles were predominant in the scientific production of the LAC region, and interventional studies were scarce among original articles, while the cross-sectional design predominated. Further research with a better quality of evidence should be performed in these countries to contribute to the making of health policies aimed at easing the burden of COVID-19 in the region and preparing for future pandemics.

Resumen Introducción. Latinoamérica y el Caribe (LAC) es una de las regiones más afectadas por la pandemia por COVID-19. Sin embargo, hay poca literatura sobre las estrategias de investigación desarrolladas en la región para confrontar esta enfermedad. Objetivo. Cuantificar y evaluar la producción de publicaciones científicas sobre COVID-19 en 32 países de LAC entre el 1 de enero y el 31 de julio del 2020. Materiales y métodos. Estudio bibliométrico. Se realizó una búsqueda de artículos científicos sobre COVID-19 realizados en LAC o con datos de LAC, y publicados entre enero 1 y julio 31 de 2020 en Scopus, PubMed y LILACS. Se realizó un análisis de subgrupos en el que se incluyeron solo artículos de investigación original para determinar la contribución de los países de la región a la investigación sobre COVID-19; además, se utilizaron medidas de estandarización (# artículos por millón de habitantes) para comparar la producción de este tipo de artículos por país. Resultados. Se identificaron 1 291 artículos. La mayoría no eran investigaciones originales (81.72%), y los países con más producción fueron Brasil (43.91%) y México (9.14%). Sin embargo, luego de aplicar las medidas de estandarización, Chile fue el país con mayor producción de artículos originales (0.58 por millón de habitantes). Respecto a los artículos originales (n = 236), el tipo de diseño de estudio más común fue el transversal (25.84%). El diagnóstico y tratamiento de COVID-19 fue el tema más investigado en todas las publicaciones (n = 354, 27.42%), pero en el análisis de subgrupo (n=236), el enfoque de investigación más frecuente fue epidemiologia y vigilancia (n = 57, 24.15%). Conclusiones. En el periodo de estudio, los artículos no originales predominaron en la producción científica de LAC, y, entre las investigaciones originales, los estudios intervencionales escasearon, mientras que los transversales predominaron. Se requiere realizar más investigación con una mejor calidad de evidencia en los países de la región para contribuir en la formulación de políticas de salud dirigidas a aliviar la carga de la COVID-19 y para prepararse para futuras pandemias.

A decade of Ecuador´s efforts to raise its health research output: a bibliometric analysis.

Background: Over the past decade, the political movement called 'Revolución Ciudadana' implemented a variety of policies and interventions (P&I) in Ecuador to improve higher education and strengthen local research capacity. We refer specifically to the 'Mandato 14' and the Higher Education Law (LOES, Spanish acronym) launched in 2008 and 2010, respectively. Objective: To assess the impact of these P&I (Mandato 14/LOES) on the production of health sciences-related articles (HSRA), and the relationship of these HSRA with the country's health priorities. Methods: A Scopus search was performed to retrieve HSRA published from 1999 to 2017. Bivariate analysis was used to assess variation between the period I (1999-2008) and period II (2009-2017). Further, we examined the association between the top 10 causes of mortality and the total HSRA output. Results: The final study sample consisted of 2784 articles. After 2008, Ecuadorian production of HSRA increased steadily from 671 to 2133 publications (p<.001). Overall (1999-2017), the most common study design was cross-sectional (32.3%), the primary research focus was in the clinical-surgical area (49.3%), and the academic institutions were the primary drivers of scientific production during period II (56.9% vs. 29.5%, p<.001). Further, we found a decrease in the production of randomized controlled trials (6.7% vs. 1.8%, p<.001). Only 9% of research production involved the primary causes of mortality, and the proportion has remained unchanged over time (8.2% vs. 9.3%, p>.05). Conclusions: Ecuadorian HSRA output increased significantly after 2008. This larger volume of scientific output could be the result to the Mandato 14/LOES implemented in the last decade. However, a low percentage of HSRA are dedicated to addressing the country's health priorities. Proper planning, execution and monitoring of national health research agendas would reduce the mismatch between health burden and the HSRA output in Ecuador and other low-and middle-income countries.

Leaving no one behind: a methodology for setting health inequality reduction targets for Sustainable Development Goal 3 / Sin dejar a nadie atrás: una metodología para establecer metas de reducción de desigualdad en salud del Objetivo de Desarrollo Sostenible 3 / Não deixar ninguém para trás: uma metodologia para estabelecer metas de redução das desigualdades em saúde sob o Objetivo de Desenvolvimento Sustentável 3

ABSTRACT Objectives. To present a methodology for the simultaneous setting of quantitative targets that reflect both an improvement in the national average of an indicator for Sustainable Development Goal 3 (SDG3), as well as a reduction in its geographic inequality. Methods. A five-step algorithm was developed: (a) calculate the national average annual percent change (AAPC) for an SDG3 indicator; (b) normatively define geographic strata from the subnational distribution of the indicator in a baseline year; (c) apply a proportional progressivity criterion to the AAPC to project the stratum-specific indicator value for the target year; (d) set the national target as the weighted average of the indicator in the subnational territorial units for the target year; and (e) set the inequality reduction targets by calculating the absolute and relative gaps between the bottom and top strata for the target year. Results. The algorithm was applied to SDG indicator 3.1.1 (maternal mortality ratio, MMR), disaggregated by Guatemala's 22 departments at the baseline year 2014 (MMR = 113 per 100,000 live births). By sustaining the AAPC rate attained from 2009 to 2014 (-4.3%) and focalizing its actions with territorial progressivity, by 2030 the country could reduce its MMR to 53 per 100,000 and its absolute and relative inequality gaps by 72% and 48%, respectively. Conclusions. The proposed methodology allows for simultaneously setting targets for overall progress and inequality reduction in health, making explicit the primacy of the equity principle contained in the SDG commitment to leave no one behind, whose urgency takes on renewed relevance in the current pandemic scenario.

RESUMEN Objetivos. Presentar una metodología para la formulación simultánea de metas cuantitativas que reflejen tanto la mejoría del promedio nacional de un indicador del tercer Objetivo de Desarrollo Sostenible (ODS3) como la reducción de su desigualdad geográfica. Métodos. Se definió un algoritmo en cinco pasos: a) cálculo del cambio porcentual anual promedio (CPAP) nacional para un indicador del ODS3; b) definición normativa de estratos geográficos a partir de la distribución subnacional del indicador en un año base; c) aplicación de un criterio de progresividad proporcional del CPAP para proyectar el indicador estrato-específico al año meta; d) establecimiento de la meta nacional como el promedio ponderado del indicador en las unidades territoriales subnacionales al año meta; y e) formulación de metas de reducción de desigualdad mediante el cálculo de las brechas absoluta y relativa entre los estratos extremos al año meta. Resultados. Se aplicó el algoritmo al indicador ODS 3.1.1 (razón de mortalidad materna, RMM), desagregado por los 22 departamentos de Guatemala para el año base 2014 (RMM = 113 por 100 000 nacidos vivos). Sosteniendo la intensidad promedio de CPAP observada entre 2009 y 2014 (-4,3%) y focalizando sus acciones con progresividad territorial, el país reduciría al 2030 su RMM a 53 por 100 000 nacidos vivos y sus brechas absoluta y relativa en 72% y 48%, respectivamente. Conclusiones. La metodología propuesta permite formular simultáneamente metas de reducción de las desigualdades geográficas en salud y hacer explícita la primacía del principio de equidad expresado en el compromiso de no dejar a nadie atrás que identifica a los ODS, cuya urgencia cobra renovada relevancia en el escenario pospandémico actual.

RESUMO Objetivos. Apresentar uma metodologia para a formulação simultânea de metas quantitativas que reflitam tanto a melhoria da média nacional de um indicador do terceiro Objetivo de Desenvolvimento Sustentável (ODS3) quanto a redução das desigualdades geográfica nesse indicador. Métodos. Estabelecemos um algoritmo em cinco etapas: (a) cálculo da variação percentual anual média (VPAM) em um país para um indicador do ODS3, (b) definição normativa de estratos geográficos a partir da distribuição subnacional do indicador em um ano base, (c) aplicação de um critério de progressividade proporcional da VPAM para projetar o indicador específico do estrato para o ano base, (d) estabelecimento da meta nacional como a média ponderada do indicador nas unidades territoriais subnacionais para o ano alvo e (e) estabelecimento de metas para a redução das desigualdades calculando a disparidade absoluta e relativa entre os estratos extremos para o ano alvo. Resultados. Aplicamos o algoritmo ao indicador ODS 3.1.1 (razão de mortalidade materna, RMM), desagregado pelos 22 departamentos da Guatemala para o ano base de 2014 (RMM = 113 por 100.000 nascidos vivos). Se mantiver a intensidade média da VPAM observada entre 2009 e 2014 (-4,3%) e concentrar as suas ações com progressividade territorial, o país reduzirá, até 2030, a sua RMM para 53 por 100.000 e sua disparidade absoluta e relativa em 72% e 48%, respectivamente. Conclusões. A metodologia proposta permite formular simultaneamente metas para a redução das desigualdades geográficas em saúde e explicitar a primazia do princípio da equidade expresso no compromisso de não deixar ninguém para trás consagrado nos ODS, cuja urgência assume uma relevância renovada no atual cenário pós-pandêmico.

[Leaving no one behind: Methodology to set health inequality reduction targets for Sustainable Development Goal 3Não deixar ninguém para trás: uma metodologia para estabelecer metas de redução das desigualdades em saúde sob o Objetivo de Desenvolvimento Sustentável 3]. / Sin dejar a nadie atrás: una metodología para establecer metas de reducción de desigualdad en salud del Objetivo de Desarrollo Sostenible 3.

OBJECTIVES: Present methodology for the concurrent development of quantitative targets that reflect improvement in the national average of an indicator for Sustainable Development Goal 3 (SDG3), as well as a reduction in geographic inequality. METHODS: A five-step algorithm was developed: a) calculate the national average annual percentage change (AAPC) for an SDG3 indicator; b) standardize the definition of geographic strata based on subnational distribution of the indicator in a base year; c) apply a criterion for proportional progress in the AAPC in order to project the stratum-specific indicator to the target year; d) set the national target as the weighted average of the indicator in the subnational territorial units for the target year; and e) develop inequality reduction targets by calculating absolute and relative gaps between the top and bottom strata for the target year. RESULTS: The algorithm was applied to SDG indicator 3.1.1 (maternal mortality ratio, MMR), disaggregated by Guatemala's 22 departments for base year 2014 (MMR = 113/100,000 live births). By sustaining the average AAPC rate attained from 2009 to 2014 (-4.3%) and targeting its actions to territorial progress, the country would reduce its MMR to 53/100,000 by 2030 and its absolute and relative gaps by 72% and 48%, respectively. CONCLUSIONS: The proposed methodology makes it possible to concurrently develop targets for the reduction of geographic inequalities in health and improvements in the national average, with explicit reference to the primacy of the principle of equity expressed in the SDGs' commitment to leaving no one behind, whose urgency is newly important in the current post-pandemic scenario.

OBJETIVOS: Apresentar uma metodologia para a formulação simultânea de metas quantitativas que reflitam tanto a melhoria da média nacional de um indicador do terceiro Objetivo de Desenvolvimento Sustentável (ODS3) quanto a redução das desigualdades geográfica nesse indicador. MÉTODOS: Estabelecemos um algoritmo em cinco etapas: (a) cálculo da variação percentual anual média (VPAM) em um país para um indicador do ODS3, (b) definição normativa de estratos geográficos a partir da distribuição subnacional do indicador em um ano base, (c) aplicação de um critério de progressividade proporcional da VPAM para projetar o indicador específico do estrato para o ano base, (d) estabelecimento da meta nacional como a média ponderada do indicador nas unidades territoriais subnacionais para o ano alvo e (e) estabelecimento de metas para a redução das desigualdades calculando a disparidade absoluta e relativa entre os estratos extremos para o ano alvo. RESULTADOS: Aplicamos o algoritmo ao indicador ODS 3.1.1 (razão de mortalidade materna, RMM), desagregado pelos 22 departamentos da Guatemala para o ano base de 2014 (RMM = 113 por 100.000 nascidos vivos). Se mantiver a intensidade média da VPAM observada entre 2009 e 2014 (-4,3%) e concentrar as suas ações com progressividade territorial, o país reduzirá, até 2030, a sua RMM para 53 por 100.000 e sua disparidade absoluta e relativa em 72% e 48%, respectivamente. CONCLUSÕES: A metodologia proposta permite formular simultaneamente metas para a redução das desigualdades geográficas em saúde e explicitar a primazia do princípio da equidade expresso no compromisso de não deixar ninguém para trás consagrado nos ODS, cuja urgência assume uma relevância renovada no atual cenário pós-pandêmico.

Neuronize v2: Bridging the Gap Between Existing Proprietary Tools to Optimize Neuroscientific Workflows.

Knowledge about neuron morphology is key to understanding brain structure and function. There are a variety of software tools that are used to segment and trace the neuron morphology. However, these tools usually utilize proprietary formats. This causes interoperability problems since the information extracted with one tool cannot be used in other tools. This article aims to improve neuronal reconstruction workflows by facilitating the interoperability between two of the most commonly used software tools-Neurolucida (NL) and Imaris (Filament Tracer). The new functionality has been included in an existing tool-Neuronize-giving rise to its second version. Neuronize v2 makes it possible to automatically use the data extracted with Imaris Filament Tracer to generate a tracing with dendritic spine information that can be read directly by NL. It also includes some other new features, such as the ability to unify and/or correct inaccurately-formed meshes (i.e., dendritic spines) and to calculate new metrics. This tool greatly facilitates the process of neuronal reconstruction, bridging the gap between existing proprietary tools to optimize neuroscientific workflows.

Bottlenecks and barriers to effective coverage of early childhood health and development interventions in Guatemala: A scoping review.

OBJECTIVES: To identify bottlenecks and barriers to effective coverage by Early Childhood Health and Development (ECHD) interventions in Guatemala. METHODS: A scoping review of more than 100 peer-reviewed articles, grey literature, and other academic publications was conducted. Articles published from 2005-2019 were considered. Results were analyzed using the Tanahashi model of effective coverage that categorizes coverage by five domains: availability, accessibility, acceptability, contact, and effective coverage. RESULTS: A total of 103 articles were identified, addressing 337 bottlenecks and barriers to effective coverage by ECHD interventions in Guatemala. Most occurred along the acceptability dimension (35.9%). The findings revealed four opportunity spaces: (i) strong political interest and commitment (opportunity for leadership); (ii) vibrant community health networks (opportunity for leverage); (iii) availability of promising evidence-based projects and interventions (opportunity for scale-up); and (iv) strong agency presence (opportunity for collaboration). CONCLUSIONS: Most bottlenecks and barriers to ECHD interventions in Guatemala occur around acceptability, followed by accessibility and availability. There is considerable potential for national leadership, leverage, scale-up, and collaboration of ongoing efforts in the country. These results may be used to inform future research and policymaking. The Tanahashi approach is an effective lens of analysis that can be applied to other countries, geographic areas, and contexts in future studies.

OBJETIVOS: Identificar los obstáculos y las barreras que impiden una cobertura efectiva de las intervenciones de salud y desarrollo en la primera infancia en Guatemala. MÉTODOS: Se llevó a cabo una revisión sistemática exploratoria de más de 100 artículos revisados por pares, literatura gris y otras publicaciones académicas. Se consideraron artículos publicados entre 2005 y 2019. Los resultados se analizaron utilizando el modelo de Tanahashi de cobertura efectiva que clasifica la cobertura en cinco dominios: disponibilidad, accesibilidad, aceptabilidad, contacto y cobertura efectiva. RESULTADOS: Se identificaron 103 artículos que abordan 337 obstáculos y barreras a la cobertura efectiva de las intervenciones de salud y desarrollo en la primera infancia en Guatemala. La mayoría de ellos se produjeron en la dimensión de la aceptabilidad (35,9%). Los resultados revelaron cuatro espacios de oportunidad para la acción: i) un fuerte interés y compromiso políticos (oportunidad de liderazgo); ii) redes de salud comunitarias dinámicas (oportunidad de apalancamiento); iii) disponibilidad de proyectos e intervenciones prometedores basados en la evidencia (oportunidad de ampliación); y iv) marcada presencia de instituciones (oportunidad de colaboración). CONCLUSIONES: La mayoría de los obstáculos y las barreras a las intervenciones de salud y desarrollo en la primera infancia en Guatemala se dan en torno a la aceptabilidad, seguida de la accesibilidad y la disponibilidad. Existe un considerable potencial para el liderazgo nacional, el apalancamiento, la ampliación y la colaboración entre los emprendimientos en curso en el país. Estos resultados pueden utilizarse para fundamentar futuras investigaciones y la formulación de políticas. El enfoque de Tanahashi es una herramienta de análisis eficaz que puede aplicarse a otros países, zonas geográficas y contextos en estudios futuros.

Bottlenecks and barriers to effective coverage of early childhood health and development interventions in Guatemala: A scoping review

[ABSTRACT]. Objectives. To identify bottlenecks and barriers to effective coverage by Early Childhood Health and Development (ECHD) interventions in Guatemala. Methods. A scoping review of more than 100 peer-reviewed articles, grey literature, and other academic publications was conducted. Articles published from 2005-2019 were considered. Results were analyzed using the Tanahashi model of effective coverage that categorizes coverage by five domains: availability, accessibility, acceptability, contact, and effective coverage. Results. A total of 103 articles were identified, addressing 337 bottlenecks and barriers to effective coverage by ECHD interventions in Guatemala. Most occurred along the acceptability dimension (35.9%). The findings revealed four opportunity spaces: (i) strong political interest and commitment (opportunity for leadership); (ii) vibrant community health networks (opportunity for leverage); (iii) availability of promising evidence-based projects and interventions (opportunity for scale-up); and (iv) strong agency presence (opportunity for collaboration). Conclusions. Most bottlenecks and barriers to ECHD interventions in Guatemala occur around acceptability, followed by accessibility and availability. There is considerable potential for national leadership, leverage, scale-up, and collaboration of ongoing efforts in the country. These results may be used to inform future research and policymaking. The Tanahashi approach is an effective lens of analysis that can be applied to other countries, geographic areas, and contexts in future studies.

[RESUMEN]. Objetivos. Identificar los obstáculos y las barreras que impiden una cobertura efectiva de las intervenciones de salud y desarrollo en la primera infancia en Guatemala. Métodos. Se llevó a cabo una revisión sistemática exploratoria de más de 100 artículos revisados por pares, literatura gris y otras publicaciones académicas. Se consideraron artículos publicados entre 2005 y 2019. Los resultados se analizaron utilizando el modelo de Tanahashi de cobertura efectiva que clasifica la cobertura en cinco dominios: disponibilidad, accesibilidad, aceptabilidad, contacto y cobertura efectiva. Resultados. Se identificaron 103 artículos que abordan 337 obstáculos y barreras a la cobertura efectiva de las intervenciones de salud y desarrollo en la primera infancia en Guatemala. La mayoría de ellos se produjeron en la dimensión de la aceptabilidad (35,9%). Los resultados revelaron cuatro espacios de oportunidad para la acción: i) un fuerte interés y compromiso políticos (oportunidad de liderazgo); ii) redes de salud comunitarias dinámicas (oportunidad de apalancamiento); iii) disponibilidad de proyectos e intervenciones prometedores basados en la evidencia (oportunidad de ampliación); y iv) marcada presencia de instituciones (oportunidad de colaboración). Conclusiones. La mayoría de los obstáculos y las barreras a las intervenciones de salud y desarrollo en la primera infancia en Guatemala se dan en torno a la aceptabilidad, seguida de la accesibilidad y la disponibilidad. Existe un considerable potencial para el liderazgo nacional, el apalancamiento, la ampliación y la colaboración entre los emprendimientos en curso en el país. Estos resultados pueden utilizarse para fundamentar futuras investigaciones y la formulación de políticas. El enfoque de Tanahashi es una herramienta de análisis eficaz que puede aplicarse a otros países, zonas geográficas y contextos en estudios futuros.

Effect of Phosphorylated Tau on Cortical Pyramidal Neuron Morphology during Hibernation.

The dendritic spines of pyramidal cells are the main postsynaptic target of excitatory glutamatergic synapses. Morphological alterations have been described in hippocampal dendritic spines during hibernation-a state of inactivity and metabolic depression that occurs via a transient neuronal tau hyperphosphorylation. Here, we have used the hibernating Syrian hamster to investigate the effect of hyperphosphorylated tau regarding neocortical neuronal structure. In particular, we examined layer Va pyramidal neurons. Our results indicate that hibernation does not promote significant changes in dendritic spine density. However, tau hyperphosphorylated neurons show a decrease in complexity, an increase in the tortuosity of the apical dendrites, and an increase in the diameter of the basal dendrites. Tau protein hyperphosphorylation and aggregation have been associated with loss or alterations of dendritic spines in neurodegenerative diseases, such as Alzheimer's disease (AD). Our results may shed light on the correlation between tau hyperphosphorylation and the neuropathological processes in AD. Moreover, we observed changes in the length and area of the apical and basal dendritic spines during hibernation regardless of tau hyperphosphorylation. The morphological changes observed here also suggest region specificity, opening up debate about a possible relationship with the differential brain activity registered in these regions in previous studies.

Differential Structure of Hippocampal CA1 Pyramidal Neurons in the Human and Mouse.

Pyramidal neurons are the most common cell type and are considered the main output neuron in most mammalian forebrain structures. In terms of function, differences in the structure of the dendrites of these neurons appear to be crucial in determining how neurons integrate information. To further shed light on the structure of the human pyramidal neurons we investigated the geometry of pyramidal cells in the human and mouse CA1 region-one of the most evolutionary conserved archicortical regions, which is critically involved in the formation, consolidation, and retrieval of memory. We aimed to assess to what extent neurons corresponding to a homologous region in different species have parallel morphologies. Over 100 intracellularly injected and 3D-reconstructed cells across both species revealed that dendritic and axonal morphologies of human cells are not only larger but also have structural differences, when compared to mouse. The results show that human CA1 pyramidal cells are not a stretched version of mouse CA1 cells. These results indicate that there are some morphological parameters of the pyramidal cells that are conserved, whereas others are species-specific.

Sin dejar a nadie atrás: una metodología para establecer metas de reducción de desigualdad en salud del Objetivo de Desarrollo Sostenible 3

[RESUMEN]. Objetivos. Presentar una metodología para la formulación simultánea de metas cuantitativas que reflejen tanto la mejoría del promedio nacional de un indicador del tercer Objetivo de Desarrollo Sostenible (ODS3) como la reducción de su desigualdad geográfica. Métodos. Se definió un algoritmo en cinco pasos: a) cálculo del cambio porcentual anual promedio (CPAP) nacional para un indicador del ODS3; b) definición normativa de estratos geográficos a partir de la distribución subnacional del indicador en un año base; c) aplicación de un criterio de progresividad proporcional del CPAP para proyectar el indicador estrato-específico al año meta; d) establecimiento de la meta nacional como el promedio ponderado del indicador en las unidades territoriales subnacionales al año meta; y e) formulación de metas de reducción de desigualdad mediante el cálculo de las brechas absoluta y relativa entre los estratos extremos al año meta. Resultados. Se aplicó el algoritmo al indicador ODS 3.1.1 (razón de mortalidad materna, RMM), desagregado por los 22 departamentos de Guatemala para el año base 2014 (RMM = 113 por 100 000 nacidos vivos). Sosteniendo la intensidad promedio de CPAP observada entre 2009 y 2014 (−4,3%) y focalizando sus acciones con progresividad territorial, el país reduciría al 2030 su RMM a 53 por 100 000 nacidos vivos y sus brechas absoluta y relativa en 72% y 48%, respectivamente. Conclusiones. La metodología propuesta permite formular simultáneamente metas de reducción de las desigualdades geográficas en salud y hacer explícita la primacía del principio de equidad expresado en el compromiso de no dejar a nadie atrás que identifica a los ODS, cuya urgencia cobra renovada relevancia en el escenario pospandémico actual.

[ABSTRACT]. Objectives. Present methodology for the concurrent development of quantitative targets that reflect improvement in the national average of an indicator for Sustainable Development Goal 3 (SDG3), as well as a reduction in geographic inequality. Methods. A five-step algorithm was developed: a) calculate the national average annual percentage change (AAPC) for an SDG3 indicator; b) standardize the definition of geographic strata based on subnational distribution of the indicator in a base year; c) apply a criterion for proportional progress in the AAPC in order to project the stratum-specific indicator to the target year; d) set the national target as the weighted average of the indicator in the subnational territorial units for the target year; and e) develop inequality reduction targets by calculating absolute and relative gaps between the top and bottom strata for the target year. Results. The algorithm was applied to SDG indicator 3.1.1 (maternal mortality ratio, MMR), disaggregated by Guatemala’s 22 departments for base year 2014 (MMR = 113/100,000 live births). By sustaining the average AAPC rate attained from 2009 to 2014 (-4.3%) and targeting its actions to territorial progress, the country would reduce its MMR to 53/100,000 by 2030 and its absolute and relative gaps by 72% and 48%, respectively. Conclusions. The proposed methodology makes it possible to concurrently develop targets for the reduction of geographic inequalities in health and improvements in the national average, with explicit reference to the primacy of the principle of equity expressed in the SDGs’ commitment to leaving no one behind, whose urgency is newly important in the current post-pandemic scenario.

[RESUMO]. Objetivos. Apresentar uma metodologia para a formulação simultânea de metas quantitativas que reflitam tanto a melhoria da média nacional de um indicador do terceiro Objetivo de Desenvolvimento Sustentável (ODS3) quanto a redução das desigualdades geográfica nesse indicador. Métodos. Estabelecemos um algoritmo em cinco etapas: (a) cálculo da variação percentual anual média (VPAM) em um país para um indicador do ODS3, (b) definição normativa de estratos geográficos a partir da distribuição subnacional do indicador em um ano base, (c) aplicação de um critério de progressividade proporcional da VPAM para projetar o indicador específico do estrato para o ano base, (d) estabelecimento da meta nacional como a média ponderada do indicador nas unidades territoriais subnacionais para o ano alvo e (e) estabelecimento de metas para a redução das desigualdades calculando a disparidade absoluta e relativa entre os estratos extremos para o ano alvo. Resultados. Aplicamos o algoritmo ao indicador ODS 3.1.1 (razão de mortalidade materna, RMM), desagregado pelos 22 departamentos da Guatemala para o ano base de 2014 (RMM = 113 por 100.000 nascidos vivos). Se mantiver a intensidade média da VPAM observada entre 2009 e 2014 (-4,3%) e concentrar as suas ações com progressividade territorial, o país reduzirá, até 2030, a sua RMM para 53 por 100.000 e sua disparidade absoluta e relativa em 72% e 48%, respectivamente. Conclusões. A metodologia proposta permite formular simultaneamente metas para a redução das desigualdades geográficas em saúde e explicitar a primazia do princípio da equidade expresso no compromisso de não deixar ninguém para trás consagrado nos ODS, cuja urgência assume uma relevância renovada no atual cenário pós-pandêmico.