Comparison of social structures within cities of very different sizes.
Ontology highlight
ABSTRACT:
SUBMITTER: Grindrod P
PROVIDER: S-EPMC4785974 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Background Appropriate social interactions influence animal fitness by impacting several processes, such as mating, territory defense, and offspring care. Many studies shedding light on the neurobiological underpinnings of social behavior have focused on nonapeptides (vasopressin, oxytocin, and homologues) and on sexual or parent-offspring interactions. Furthermore, animals have been studied under artificial laboratory conditions, where the consequences of behavioral responses may not be as critical as when expressed under natural environments, therefore obscuring certain physiological responses. We used automated recording of social interactions of wild house mice outside of the breeding season to detect individuals at both tails of a distribution of egocentric network sizes (characterized by number of different partners encountered per day). We then used RNA-seq to perform an unbiased assessment of neural differences in gene expression in the prefrontal cortex, the hippocampus and the hypothalamus between these mice with naturally occurring extreme differences in social network size. Results We found that the neurogenomic pathways associated with having extreme social network sizes differed between the sexes. In females, hundreds of genes were differentially expressed between animals with small and large social network sizes, whereas in males very few were. In males, X-chromosome inactivation pathways in the prefrontal cortex were the ones that better differentiated animals with small from those with large social network sizes animals. In females, animals with small network size showed up-regulation of dopaminergic production and transport pathways in the hypothalamus. Additionally, in females, extracellular matrix deposition on hippocampal neurons was higher in individuals with small relative to large social network size. Conclusions Studying neural substrates of natural variation in social behavior in traditional model organisms in their habitat can open new targets of research for understanding variation in social behavior in other taxa.
2020-07-06 | GSE148075 | GEO
Project description:The influence of urban structures and land use patterns of metropolitan cities on the distribution of contaminants is not well understood. In this study, two metropolitan cities [Jeddah (a typical corridor city) and Madinah (a typical compact city)], featuring different spreading patterns and urban structures, were selected to investigate the contamination level and potential risk caused by metals (i.e., Pb, Zn, Co, Fe, Al, Cr, Cu, Ni, and Mn) associated with urban dust. The findings of this study show that a metropolitan city with a limited variety of activities and a polar center (e.g., Madinah) displays a typical distribution pattern of metals, i.e., concentrations of metals increase gradually toward the center of the city. In contrast, a metropolitan city with multiple major activities (e.g., Jeddah) displays a different distribution pattern, controlled by multiple key actors (e.g., seaports, oil refineries, and desalination/power plants) able to shift the location of highest contamination away from the city center. The above findings are supported by the results of several contamination and health indices. In Jeddah, the highest Pb contamination was found near an oil refinery based on geoaccumulation index (Igeo), contamination factor (CF), enrichment factor (EF), and ecological risk (Ei) values; whereas, the highest Zn contamination was found near a seaport, based on EF, CF, and Ei values. However, in Madinah, the contamination indices indicate that the most contaminated locations are near the city center. The highest non-carcinogenic health risk in Jeddah was found near an oil refinery and in the city center; whereas in Madinah, it was found mainly in the city center. Although there is no significant risk of cancer due to metals associated with dust in the two cities, Cr, representing a health risk contribution of >24%, was the major contributor of non-carcinogenic health risk in the two metropolitan cities.
| S-EPMC6426876 | biostudies-other
Project description:BackgroundAppropriate social interactions influence animal fitness by impacting several processes, such as mating, territory defense, and offspring care. Many studies shedding light on the neurobiological underpinnings of social behavior have focused on nonapeptides (vasopressin, oxytocin, and homologues) and on sexual or parent-offspring interactions. Furthermore, animals have been studied under artificial laboratory conditions, where the consequences of behavioral responses may not be as critical as when expressed under natural environments, therefore obscuring certain physiological responses. We used automated recording of social interactions of wild house mice outside of the breeding season to detect individuals at both tails of a distribution of egocentric network sizes (characterized by number of different partners encountered per day). We then used RNA-seq to perform an unbiased assessment of neural differences in gene expression in the prefrontal cortex, the hippocampus and the hypothalamus between these mice with naturally occurring extreme differences in social network size.ResultsWe found that the neurogenomic pathways associated with having extreme social network sizes differed between the sexes. In females, hundreds of genes were differentially expressed between animals with small and large social network sizes, whereas in males very few were. In males, X-chromosome inactivation pathways in the prefrontal cortex were the ones that better differentiated animals with small from those with large social network sizes animals. In females, animals with small network size showed up-regulation of dopaminergic production and transport pathways in the hypothalamus. Additionally, in females, extracellular matrix deposition on hippocampal neurons was higher in individuals with small relative to large social network size.ConclusionsStudying neural substrates of natural variation in social behavior in traditional model organisms in their habitat can open new targets of research for understanding variation in social behavior in other taxa.
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Project description:The modeling of large-scale communicable epidemics has greatly benefited in the last years from the increasing availability of highly detailed data. Particullarly, in order to achieve quantitative descriptions of the evolution of epidemics, contact networks and mixing patterns are key. These heterogeneous patterns depend on several factors such as location, socioeconomic conditions, time, and age. This last factor has been shown to encapsulate a large fraction of the observed inter-individual variation in contact patterns, an observation validated by different measurements of age-dependent contact matrices. Recently, several works have studied how to project those matrices to areas where empirical data are not available. However, the dependence of contact matrices on demographic structures and their time evolution has been largely neglected. In this work, we tackle the problem of how to transform an empirical contact matrix that has been obtained for a given demographic structure into a different contact matrix that is compatible with a different demography. The methodology discussed here allows to extrapolate a contact structure measured in a particular area to any other whose demographic structure is known, as well as to obtain the time evolution of contact matrices as a function of the demographic dynamics of the populations they refer to. To quantify the effect of considering time-dynamics of contact patterns on disease modeling, we implemented a Susceptible-Exposed-Infected-Recovered (SEIR) model on 16 different countries and regions and evaluated the impact of neglecting the temporal evolution of mixing patterns. Our results show that simulated disease incidence rates, both at the aggregated and age-specific levels, are significantly dependent on contact structures variation driven by demographic evolution. The present work opens the path to eliminate technical biases from model-based impact evaluations of future epidemic threats and warns against the use of contact matrices to model diseases without correcting for demographic evolution or geographic variations.
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Project description:When making judgments in a group, individuals often revise their initial beliefs about the best judgment to make given what others believe. Despite the ubiquity of this phenomenon, we know little about how the brain updates beliefs when integrating personal judgments (individual information) with those of others (social information). Here, we investigated the neurocomputational mechanisms of how we adapt our judgments to those made by groups of different sizes, in the context of jury decisions for a criminal. By testing different theoretical models, we showed that a social Bayesian inference model captured changes in judgments better than 2 other models. Our results showed that participants updated their beliefs by appropriately weighting individual and social sources of information according to their respective credibility. When investigating 2 fundamental computations of Bayesian inference, belief updates and credibility estimates of social information, we found that the dorsal anterior cingulate cortex (dACC) computed the level of belief updates, while the bilateral frontopolar cortex (FPC) was more engaged in individuals who assigned a greater credibility to the judgments of a larger group. Moreover, increased functional connectivity between these 2 brain regions reflected a greater influence of group size on the relative credibility of social information. These results provide a mechanistic understanding of the computational roles of the FPC-dACC network in steering judgment adaptation to a group's opinion. Taken together, these findings provide a computational account of how the human brain integrates individual and social information for decision-making in groups.
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Project description:Soil aggregates provide spatially heterogeneous microhabitats that support the coexistence of soil microbes. However, there remains a lack of detailed assessment of the mechanism underlying aggregate-microbiome formation and impact on soil function. Here, the microbial assemblages within four different aggregate sizes and their correlation with microbial activities related to nutrient cycling were studied in rice fields in Southern China. The results show that deterministic and stochastic processes govern bacterial and fungal assemblages in agricultural soil, respectively. The contribution of determinism to bacterial assemblage improved as aggregate size decreased. In contrast, the importance of stochasticity to fungal assemblage was higher in macroaggregates (>0.25 mm in diameter) than in microaggregates (<0.25 mm). The association between microbial assemblages and nutrient cycling was aggregate-specific. Compared with microaggregates, the impacts of bacterial and fungal assemblages on carbon, nitrogen, and phosphorus cycling within macroaggregates were more easily regulated by soil properties (i.e., soil organic carbon and total phosphorus). Additionally, soil nutrient cycling was positively correlated with deterministic bacterial assemblage but negatively correlated with stochastic fungal assemblage in microaggregates, implying that bacterial community may accelerate soil functions when deterministic selection increases. Overall, our study illustrates the ecological mechanisms underlying the association between microbial assemblages and soil functions in aggregates and highlights that the assembly of aggregate microbes should be explicitly considered for revealing the ecological interactions between agricultural soil and microbial communities.
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Project description:This trial examines cancer communication within Hispanic social networks. Hispanics have the lowest colorectal cancer screening rate of any major ethnic group and health interventions are crucially needed among Hispanics. Patient decision aids are health communication interventions designed to provide patients with targeted health information and have shown to improve colorectal cancer screening rates among Hispanics. The goal of this study is to investigate, in a sample of Hispanics, how a colorectal cancer decision aid aimed at increasing individuals’ colorectal cancer screening behavior has effects on their alters’ intention to get screened for colorectal cancer.
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Project description:In early 2020, cities across China enacted strict social distancing measures to contain emerging coronavirus (COVID-19) outbreaks. We estimated the speed with which these measures contained community transmission in each of 58 Chinese cities. On average, containment was achieved 7.83 days (SD 6.79 days) after the implementation of social distancing interventions, with an average reduction in the reproduction number (Rt) of 54.3% (SD 17.6%) over that time period. A single day delay in the implementation of social distancing led to a 2.41 (95% CI: 0.97, 3.86) day delay in containment. Swift social distancing interventions may thus achieve rapid containment of newly emerging COVID-19 outbreaks.
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Project description:There is a rising concern that air pollution plays an important role in the COVID-19 pandemic. However, the results were not consistent on the association between air pollution and the spread of COVID-19. In the study, air pollution data and the confirmed cases of COVID-19 were both gathered from five severe cities across three countries in South America. Daily real-time population regeneration (Rt) was calculated to assess the spread of COVID-19. Two frequently used models, generalized additive models (GAM) and multiple linear regression, were both used to explore the impact of environmental pollutants on the epidemic. Wide ranges of all six air pollutants were detected across the five cities. Spearman's correlation analysis confirmed the positive correlation within six pollutants. Rt value showed a gradual decline in all the five cities. Further analysis showed that the association between air pollution and COVID-19 varied across five cities. According to our research results, even for the same region, varied models gave inconsistent results. For example, in Sao Paulo, both models show SO2 and O3 are significant independent variables, however, the GAM model shows that PM10 has a nonlinear negative correlation with Rt, while PM10 has no significant correlation in the multiple linear model. Moreover, in the case of multiple regions, currently used models should be selected according to local conditions. Our results indicate that there is a significant relationship between air pollution and COVID-19 infection, which will help states, health practitioners, and policy makers in combating the COVID-19 pandemic in South America.
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Project description:The experiment was conducted to compare the differences of gut microbiota and metabolic status of sows with different litter sizes on days 30 and 110 of gestation, and uncover the relationship between the composition of maternal gut microbiota during gestation and sow reproductive performance. Twenty-six Large White × Landrace crossbred multiparous sows (2nd parity) with similar back fat thickness and body weight were assigned to two groups [high-reproductive performance group (HP group) and low-reproductive performance group (LP group)] according to their litter sizes and fed a common gestation diet. Results showed that compared with LP sows, HP sows had significantly lower plasma levels of triglyceride (TG) on gestation d 30 (P < 0.05), but had significantly higher plasma levels of TG, non-esterified fatty acid, tumor necrosis factor-α, and immunoglobulin M on gestation d 110 (P < 0.05). Consistently, HP sows revealed increased alpha diversity and butyrate-producing genera, as well as fecal butyrate concentration, on gestation d 30; HP sows showed significantly different microbiota community structure with LP sows (P < 0.05) and had markedly higher abundance of Firmicutes (genera Christensenellaceae_R-7_group and Terrisporobacter) which were positively related with litter size on gestation d 110 than LP sows (P < 0.05). In addition, plasma biochemical parameters, plasma cytokines, and fecal microbiota shifted dramatically from gestation d 30 to d 110. Therefore, our findings demonstrated that microbial abundances and community structures differed significantly between sows with different litter sizes and gestation stages, which was associated with changes in plasma biochemical parameters, inflammatory factors, and immunoglobulin. Moreover, these findings revealed that there was a significant correlation between litter size and gut microbiota of sows, and provided a microbial perspective to improve sow reproductive performance in pig production.
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