Core-periphery dynamics in a plant-pollinator network

Mutualistic networks are highly dynamic, characterized by high temporal turnover of species and interactions. Yet, we have a limited understanding of how the internal structure of these networks and the roles species play in them vary through time. We used 6 years of observation data and a novel statistical method (dynamic stochastic block models) to assess how network structure and species' structural position within the network change throughout subseasons of the flowering season and across years in a quantitative plant–pollinator network from a dryland ecosystem in Argentina. Our analyses revealed a core–periphery structure persistent through subseasons and years. Yet, species structural position as core or peripheral was highly dynamic: virtually all species that were at the core in some subseasons were also peripheral in other subseasons, while many other species always remained peripheral. Our results illuminate our understanding of the dynamics of mutualistic networks and have important implications for ecosystem management and conservation.Fil: Miele, Vincent. Centre National de la Recherche Scientifique; FranciaFil: Ramos Jiliberto, Rodrigo. Universidad Mayor; ChileFil: Vazquez, Diego P.. Universidad Nacional de Cuyo. Facultad de Ciencias Exactas y Naturales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto Argentino de Investigaciones de las Zonas Áridas. Provincia de Mendoza. Instituto Argentino de Investigaciones de las Zonas Áridas. Universidad Nacional de Cuyo. Instituto Argentino de Investigaciones de las Zonas Áridas; Argentin

Frailty index in the Colonias of the Rio Grande Valley: health related quality of life and resilience

Background: Frailty is characterized by an accumulation of deficits that lead to vulnerability to adverse health outcomes. The Frailty Index (FI) quantifies frailty by measuring deficits that increase susceptibility to stressors. This study focused on a population of Mexican Americans living in vulnerable communities in the Rio Grande Valley of south Texas. We used a Frailty Index developed based on common health-related data--the Patient Health Questionnaire (PHQ-9) and a Health-related Quality of Life survey (Duke Health Profile). Quality of life, resilience, and frailty are interrelated and influenced by chronic illness, mental illness, poverty, cognitive impairment, and community support. Methods: We used Logistic regression analysis, factor component analysis, receiver operating characteristic curves, and odds ratios to identify potential associations between clinical variables and candidate predictor variables and seven physiological health variables, and two survey instruments. We analyzed data obtained from participants (894) that live in two Colonias located on the Texas-Mexico border. We calculated the FI with seven physiological variables, PHQ-9 score, and the 11 domain-specific Duke Profile scores, for a total of 19 health deficits. We then dichotomized FI (\u3e0.25) and determined ROC curves through model selection to determine best predictors of frailty. Results: Females (n = 622) had a higher starting frailty, and males (n = 272) had a significantly greater change rate with age. Women score higher in anxiety, depression, anxiety/depression, and pain. The frailty index and quality of life markers are strongly inversely related; poorer quality of life leads to greater frailty independent physiological health variables, the PHQ 9, sex, and age. Conclusion: The study highlights the importance of addressing modifiable mental health and social stressors to reduce frailty. Furthermore, it suggests that factors supporting resilience and well-being, such as physical and mental health, social support, and perceived health, play a crucial role in frailty development. The findings have implications for interventions targeting vulnerable populations and emphasize the need for further research on the relationship between health-related quality of life and frailty

Strategy and model building in the fourth dimension: a null model for genotype × age interaction as a Gaussian stationary stochastic process

BACKGROUND: Using univariate and multivariate variance components linkage analysis methods, we studied possible genotype × age interaction in cardiovascular phenotypes related to the aging process from the Framingham Heart Study. RESULTS: We found evidence for genotype × age interaction for fasting glucose and systolic blood pressure. CONCLUSIONS: There is polygenic genotype × age interaction for fasting glucose and systolic blood pressure and quantitative trait locus × age interaction for a linkage signal for systolic blood pressure phenotypes located on chromosome 17 at 67 cM

Unraveling the Mechanisms by Which Smoking and Alcohol Alter Pancreatic Cancer Pathogenesis

Pancreatic cancer is the 3rd leading cause of cancer in United States with a 5-to-7-year relative survival rate. This can be attributed to the late onset of symptoms and diagnosis of the disease, which makes it unmanageable at its later stage. Ethnic differences in pancreatic cancer incidence have been reported, especially regarding higher incidence in African Americans. African Americans are more likely than Asian, Hispanic, or whites’ people to develop pancreatic cancer. They have highest incidence rate between 28% and 59% higher than other racial groups. The mortality rate for Blacks is 13.3 per 100,000 people, while for Whites it is 11.0 per 100,000. Incidence of pancreatic cancer and increased smoking and alcohol consumption among African Americans indicates lifestyle risk rather than genetics. The purpose of this study is to identify underlying mechanisms that may contribute to this racial disparity. Herein, we have demonstrated that cigarette smoking and alcohol consumption are associated with pancreatic cancer and poor patient survival. Our results demonstrate that smoking and drinking alters tumor microenvironment and enhances bidirectional tumor-stromal cells interaction between sonic hedgehog (SHH) pathway and an oncogenic CXCR4/CXCL12 signaling axis. Our results particularly signify an aberrant overexpression of a mucin, MUC13 in the nuclear compartment of cells from the patient tissues who smoke or drink. Also, this study analyzes the association of MUC13 with effects due to smoking and alcohol consumption. This study is significant in understanding potential risk factors in pancreatic cancer. Smoking and excess drinking cessation programs can help prevent pancreatic cancer

Gene-by-Environment Expression and Calculation of the Frailty Index

Background: Frailty can be described as a phenotype (e.g., sarcopenia, reduced grip strength, decreased VO2 max) or as a ratio of deficits, i.e., a Frailty Index (FI). FI predicts survival, death, cognitive impairment, falls, and hospitalizations. Frailty is influenced by both genes and environment. We calculated the FI as the sum of measured deficits divided by the total number of items assessed in a pedigree-based sample of 1,029 Mexican Americans participants in the San Antonio Family Heart Study. We performed a novel search for genotype-by-environment interactions (GXE) influencing FI. Such interactions lead to heritable differences between individuals in their responses to the environment. Methods: We investigated a panel of 34 measured environmental factors to look for GXE influencing frailty. We employed a powerful polygenic approach to genotype-by-environment modeling, allowing for both dichotomous and continuous environmental measures. We performed likelihood-based estimation of parameters and tests for the presence of GXE. Results: GXE interactions influencing frailty were observed for the following environments: obesity (P=7.9E-10), hypertriglyceridemia (P=2.74E-09), low HDL (P=2.15E-06), impaired glucose status (P=.002), hypertension (P=0.01), and diabetes (P=0.02), Additionally, GXE interactions were detected for a number of quantitative dietary components: carbohydrates (P=5.73E-07), fats (P=2.01E-06), fiber (P=2.76E-05), dietary cholesterol (P=0.01), and protein ( P=0.006). These results document substantial statistical evidence for the interactive effects of genes and environmental factors on frailty. Conclusion: Our results support the presence of substantive gene-by-environmental interactions influencing frailty. This finding documents the presence of heritable differences between individuals that lead to differential response to environmental challenges

Non-alcoholic Fatty Liver Disease and Depression: Evidence for Genotype × Environment Interaction in Mexican Americans

This study examines the impact of G × E interaction effects on non-alcoholic fatty liver disease (NAFLD) among Mexican Americans in the Rio Grande Valley (RGV) of South Texas. We examined potential G × E interaction using variance components models and likelihood-based statistical inference in the phenotypic expression of NAFLD, including hepatic steatosis and hepatic fibrosis (identified using vibration controlled transient elastography and controlled attenuation parameter measured by the FibroScan Device). We screened for depression using the Beck Depression Inventory-II (BDI-II). We identified significant G × E interactions for hepatic fibrosis × BDI-II. These findings provide evidence that genetic factors interact with depression to influence the expression of hepatic fibrosis

Gene by Environment interaction and metabolic-associated fatty liver disease in Mexican American patients with depression

Knowledge of genetic and environmental (G x E) interaction effects on metabolic-associated fatty liver disease (MAFLD) is limited. The purpose of this study was to examine the impact of G x E interaction effects on MAFLD in Mexican Americans in the Rio Grande Valley (RGV). The environment examined was depression as measured by the Beck Depression Inventory-II (BDI-II). We examined potential G x E interaction in the phenotypic expression of MAFLD, including hepatic steatosis and hepatic fibrosis, using variance component models and likelihood-based statistical inference. Significant G x E interactions were identified for hepatic fibrosis x BDI-II. These findings provide evidence that genetic factors interact with depression to influence expression of hepatic fibrosis. A better understanding of these genetic interactions are necessary to develop strategies and interventions to reduce the bi-directional relationship of hepatic fibrosis and depression

Environmental and Genetic Correlations Between the Metabolic Syndrome (MS) and System Variables Representing Adaptive Immunity, Innate Immunity and Hemostasis

The MS is prevalent in Mexican Americans (MAs) and is projected to increase. It is important therefore to better understand its genetic and environmental determinants. We hypothesized that the MS reflects dysfunction in important biological systems. To evaluate this concept, we analyzed gene expression data for the adaptive-immune, innate-immune, and hemostasis systems in relation to the MS from a study on MAs of San Antonio and the Rio Grande Valley

Modeling methylation data as an additional genetic variance component

High-throughput platforms allow the characterization of thousands of previously known methylation sites. These platforms have great potential for investigating the epigenetic effects that are partially responsible for gene expression control. Methylation sites provide a bridge for the investigation of real-time environmental contributions on genomic events by the alteration of methylation status of those sites. Using the data provided by GAW20’s organization committee, we calculated the heritability estimates of each cytosine-phosphate-guanine (CpG) island before and after the use of fenofibrate, a lipid-control drug. Surprisingly, we detected substantially high heritability estimates before drug usage. This somewhat unexpected high sample correlation was corrected by the use of principal components and the distributions of heritability estimates before and after fenofibrate treatment, which made the distributions comparable. The methylation sites located near a gene were collected and a genetic relationship matrix estimated to represent the overall correlation between samples. We implemented a randomeffect association test to screen genes whose methylation patterns partially explain the observable high-density lipoprotein (HDL) heritability. Our leading association was observed for the TMEM52 gene that encodes a transmembrane protein, and is largely expressed in the liver, had not been previously associated with HDL until this manuscript. Using a variance component decomposition framework with the linear mixed model allows the integration of data from different sources, such as methylation, gene expression, metabolomics, and proteomics. The decomposition of the genetic variance component decomposition provides a flexible analytical approach for the challenges of this new omics era

Frailty Index in the Colonias on the US-Mexico Border: A Special Report

Frailty is the age-related decline in well-being. The Frailty index (FI) measures the accumulation of health deficits and reflects biopsychosocial and cultural determinants of well-being. Frailty is measured as a static phenotype or as a Frailty Index comprising a ratio of suffered health deficits and total deficits. We report a Frailty Index calculated from routinely measured clinical variables gathered from residents of two Colonias (neighborhoods) in South Texas. A Colonia is a predominantly Hispanic, economically distressed, unincorporated neighborhood. We analyzed retrospective data from 894 patients that live in two Colonias located on the Texas-Mexico border. We calculated the FI with seven physiological variables, PHQ-9 score, and the 11 domain-specific Duke Profile scores, for a total of 19 possible health deficits. FI against age separately in males (n = 272) and females (n = 622) was regressed. Females had a significantly higher starting frailty, and males had a significantly greater change rate with age. FI against age for Cameron Park Colonia and Indian Hills Colonia was regressed. We calculated a significantly higher starting FI in Indian Hills and a significantly greater change rate in Cameron Park residents. Frailty\u27s contributors are complex, especially in neighborhoods of poverty, immigration, low education level, and high prevalence of chronic disease. We report baseline Frailty Index data from two Colonias in South Texas and the clinical and research implications