An Analysis of the Association Between Cognitive Decline and Geographic Residence Among Women Over 65 in the Southeastern United States

Abstract Introduction: The United States is an increasingly aging nation, and aging increases the risk of cognitive decline. Information on the relationship between cognitive decline and geographic residence in the U.S. is limited. Available evidence suggests that rural residents tend to suffer persistent disadvantages in cognitive functioning when compared to sociodemographically similar urban peers. This analysis focused on women over 65 years of age living in the southeastern U.S. The primary objective of this analysis was to determine if there was a significant association between geographic residence and cognitive decline. A secondary objective was to explore variables of interest that may contribute to the relationship between geographic residence and cognitive decline. Methods: Data from the 2019 BRFSS survey were used for this research. To determine if there was a significant relationship between cognitive decline and geographic residence, the primary analysis was a Chi-square test between the geographic residence variable and the cognitive decline variable. Chi-square tests were also performed between cognitive decline/geographic residence and 5 variables of interest: education level, income level, social support, exercise, and healthcare access. An ANOVA was performed between education level/geographic residence and income level/geographic residence, to determine if the means of these variables differed between urban and rural areas. A subgroup analysis was performed including only women who reported experiencing cognitive decline. Results: A significant association was not observed between cognitive decline and geographic residence (p=0.75). Education, income, and exercise were shown to have significant associations with geographic residence. Significant associations were also observed between cognitive decline and education, income, exercise, and social support. Mean education level and mean income level were shown to significantly differ between urban and rural areas. Conclusions: Despite the null results of the primary research question, previous research indicating rural cognitive health deficits and known rural health disadvantages make this an area worthy of further study. Understanding the social determinants of health, and particularly of cognitive health, and how these factors affect urban and rural populations differently, is an important step in improving health outcomes and promoting healthier aging

An Analysis of the Association Between Cognitive Decline and Geographic Residence Among Women Over 65 in the Southeastern United States

Abstract Introduction: The United States is an increasingly aging nation, and aging increases the risk of cognitive decline. Information on the relationship between cognitive decline and geographic residence in the U.S. is limited. Available evidence suggests that rural residents tend to suffer persistent disadvantages in cognitive functioning when compared to sociodemographically similar urban peers. This analysis focused on women over 65 years of age living in the southeastern U.S. The primary objective of this analysis was to determine if there was a significant association between geographic residence and cognitive decline. A secondary objective was to explore variables of interest that may contribute to the relationship between geographic residence and cognitive decline. Methods: Data from the 2019 BRFSS survey were used for this research. To determine if there was a significant relationship between cognitive decline and geographic residence, the primary analysis was a Chi-square test between the geographic residence variable and the cognitive decline variable. Chi-square tests were also performed between cognitive decline/geographic residence and 5 variables of interest: education level, income level, social support, exercise, and healthcare access. An ANOVA was performed between education level/geographic residence and income level/geographic residence, to determine if the means of these variables differed between urban and rural areas. A subgroup analysis was performed including only women who reported experiencing cognitive decline. Results: A significant association was not observed between cognitive decline and geographic residence (p=0.75). Education, income, and exercise were shown to have significant associations with geographic residence. Significant associations were also observed between cognitive decline and education, income, exercise, and social support. Mean education level and mean income level were shown to significantly differ between urban and rural areas. Conclusions: Despite the null results of the primary research question, previous research indicating rural cognitive health deficits and known rural health disadvantages make this an area worthy of further study. Understanding the social determinants of health, and particularly of cognitive health, and how these factors affect urban and rural populations differently, is an important step in improving health outcomes and promoting healthier aging

Boredom and Psychological Time Perspective on Cognition

This study investigated psychological time with regards to a memory recognition task. The participants rated images on a 5-point scale of attractiveness. There were two different conditions, one having 40 male faces and the other containing 40 female faces. After they finished rating the faces, they made a retrospective time estimate of how long they thought they spent viewing the faces. Following this they took the Multidimensional State Boredom Scale (MSBS) to test what state of boredom they were currently experiencing. Finally they performed a memory recognition test. We noticed statistically significant differences between the two conditions based on target gender. Women who viewed the female condition made lower time estimates than women who viewed the male condition. Women also scored better on the recognition test in the female face condition. They also rated the female face condition overall higher on attractiveness than the male face condition. All in all, women who viewed the female condition seemed to be more attentionally engaged than women who viewed the male condition

Bio.Phylo: A Unified Toolkit for Processing, Analyzing and Visualizing Phylogenetic Trees in Biopython

Background: Ongoing innovation in phylogenetics and evolutionary biology has been accompanied by a proliferation of software tools, data formats, analytical techniques and web servers. This brings with it the challenge of integrating phylogenetic and other related biological data found in a wide variety of formats, and underlines the need for reusable software that can read, manipulate and transform this information into the various forms required to build computational pipelines. Results: We built a Python software library for working with phylogenetic data that is tightly integrated with Biopython, a broad-ranging toolkit for computational biology. Our library, Bio.Phylo, is highly interoperable with existing libraries, tools and standards, and is capable of parsing common file formats for phylogenetic trees, performing basic transformations and manipulations, attaching rich annotations, and visualizing trees. We unified the modules for working with the standard file formats Newick, NEXUS and phyloXML behind a consistent and simple API, providing a common set of functionality independent of the data source. Conclusions: Bio.Phylo meets a growing need in bioinformatics for working with heterogeneous types of phylogenetic data. By supporting interoperability with multiple file formats and leveraging existing Biopython features, this library simplifies the construction of phylogenetic workflows. We also provide examples of the benefits of building a community around a shared open-source project. Bio.Phylo is included with Biopython, available through the Biopython website, http://biopython.org

Prediction of Signed Protein Kinase Regulatory Circuits.

Complex networks of regulatory relationships between protein kinases comprise a major component of intracellular signaling. Although many kinase-kinase regulatory relationships have been described in detail, these tend to be limited to well-studied kinases whereas the majority of possible relationships remains unexplored. Here, we implement a data-driven, supervised machine learning method to predict human kinase-kinase regulatory relationships and whether they have activating or inhibiting effects. We incorporate high-throughput data, kinase specificity profiles, and structural information to produce our predictions. The results successfully recapitulate previously annotated regulatory relationships and can reconstruct known signaling pathways from the ground up. The full network of predictions is relatively sparse, with the vast majority of relationships assigned low probabilities. However, it nevertheless suggests denser modes of inter-kinase regulation than normally considered in intracellular signaling research. A record of this paper's transparent peer review process is included in the Supplemental Information

Ten Simple Rules for Getting Help from Online Scientific Communities

The increasing complexity of research requires scientists to work at the intersection of multiple fields and to face problems for which their formal education has not prepared them. For example, biologists with no or little background in programming are now often using complex scripts to handle the results from their experiments; vice versa, programmers wishing to enter the world of bioinformatics must know about biochemistry, genetics, and other fields. In this context, communication tools such as mailing lists, web forums, and online communities acquire increasing importance. These tools permit scientists to quickly contact people skilled in a specialized field. A question posed properly to the right online scientific community can help in solving difficult problems, often faster than screening literature or writing to publication authors. The growth of active online scientific communities, such as those listed in Table S1, demonstrates how these tools are becoming an important source of support for an increasing number of researchers. Nevertheless, making proper use of these resources is not easy. Adhering to the social norms of World Wide Web communication—loosely termed “netiquette”—is both important and non-trivial. In this article, we take inspiration from our experience on Internet-shared scientific knowledge, and from similar documents such as “Asking the Questions the Smart Way” and “Getting Answers”, to provide guidelines and suggestions on how to use online communities to solve scientific problems

Changes to the identity of EndoC-βH1 beta cells may be mediated by stress-induced depletion of HNRNPD

This is the final version. Available on open access from BMC via the DOI in this recordAvailability of data and materials: The data pertaining to this work is available from GEO under the Accession GSE173423.Background Beta cell identity changes occur in the islets of donors with diabetes, but the molecular basis of this remains unclear. Protecting residual functional beta cells from cell identity changes may be beneficial for patients with diabetes. Results A somatostatin-positive cell population was induced in stressed clonal human EndoC-βH1 beta cells and was isolated using FACS. A transcriptomic characterisation of somatostatin-positive cells was then carried out. Gain of somatostatin-positivity was associated with marked dysregulation of the non-coding genome. Very few coding genes were differentially expressed. Potential candidate effector genes were assessed by targeted gene knockdown. Targeted knockdown of the HNRNPD gene induced the emergence of a somatostatin-positive cell population in clonal EndoC-βH1 beta cells comparable with that we have previously reported in stressed cells. Conclusions We report here a role for the HNRNPD gene in determination of beta cell identity in response to cellular stress. These findings widen our understanding of the role of RNA binding proteins and RNA biology in determining cell identity and may be important for protecting remaining beta cell reserve in diabetes.Animal Free Research UK (AFRUK)Biotechnology and Biological Sciences Research Council (BBSRC)Engineering and Physical Sciences Research Council (EPSRC)Wellcome Trus

Application of the 1RM estimation formulas from the RM in bench press in a group of physically active middle-aged women

The 1RM is the standard measurement to value isotonic strength. Nevertheless, this type of test takes a lot of time, can expose evaluated individuals at a higher risk of injury, etc. Specialized literature recognizes that the use of a procedure which requires a smaller load than 1RM to estimate individuals maximal strength has, undoubted, a great attractive. Therefore, RM tests are the most commonly tool used with general population. Having the intention of proving these proposals among Spanish female population, 28 active women were evaluated in hers 1RM and RM before and after 8 training weeks. The results obtained put the predictive value of these formulas into question, especially regarding its individual predicting value

Persister Escherichia coli Cells Have a Lower Intracellular pH than Susceptible Cells but Maintain Their pH in Response to Antibiotic Treatment

This is the final version. Available from the American Society for Microbiology via the DOI in this record. Persister and viable but non-culturable (VBNC) cells are two clonal subpopulations that can survive multidrug exposure via a plethora of putative molecular mechanisms. Here, we combine microfluidics, time-lapse microscopy, and a plasmid-encoded fluorescent pH reporter to measure the dynamics of the intracellular pH of individual persister, VBNC, and susceptible Escherichia coli cells in response to ampicillin treatment. We found that even before antibiotic exposure, persisters have a lower intracellular pH than those of VBNC and susceptible cells. We then investigated the molecular mechanisms underlying the observed differential pH regulation in persister E. coli cells and found that this is linked to the activity of the enzyme tryptophanase, which is encoded by tnaA. In fact, in a ΔtnaA strain, we found no difference in intracellular pH between persister, VBNC, and susceptible E. coli cells. Whole-genome transcriptomic analysis revealed that, besides downregulating tryptophan metabolism, the ΔtnaA strain downregulated key pH homeostasis pathways, including the response to pH, oxidation reduction, and several carboxylic acid catabolism processes, compared to levels of expression in the parental strain. Our study sheds light on pH homeostasis, proving that the regulation of intracellular pH is not homogeneous within a clonal population, with a subset of cells displaying a differential pH regulation to perform dedicated functions, including survival after antibiotic treatment.Biotechnology and Biological Sciences Research Council (BBSRC)Wellcome TrustMedical Research Council (MRC)The Royal SocietyThe Gordon and Betty Moore FoundationMarie Skłodowska‐CurieLeverhulme TrustUnited Kingdom Ministry of DefenseUniversity of Exete

Nutrient and salt depletion synergistically boosts glucose metabolism in individual Escherichia coli cells

This is the final version. Available on open access from Nature Research via the DOI in this recordData availability; All RNA sequencing data and proteomics data is available in Supplementary Data 1–4. Exact p values, where shown on Figs. 1–5, are available in Supplementary Data 5. The source data underlying Figs. 1–5 are provided as Supplementary Data 6. Any other relevant data are available upon reasonable request.The interaction between a cell and its environment shapes fundamental intracellular processes such as cellular metabolism. In most cases growth rate is treated as a proximal metric for understanding the cellular metabolic status. However, changes in growth rate might not reflect metabolic variations in individuals responding to environmental fluctuations. Here we use single-cell microfluidics-microscopy combined with transcriptomics, proteomics and mathematical modelling to quantify the accumulation of glucose within Escherichia coli cells. In contrast to the current consensus, we reveal that environmental conditions which are comparatively unfavourable for growth, where both nutrients and salinity are depleted, increase glucose accumulation rates in individual bacteria and population subsets. We find that these changes in metabolic function are underpinned by variations at the translational and posttranslational level but not at the transcriptional level and are not dictated by changes in cell size. The metabolic response-characteristics identified greatly advance our fundamental understanding of the interactions between bacteria and their environment and have important ramifications when investigating cellular processes where salinity plays an important role.Biotechnology & Biological Sciences Research Council (BBSRC)Biotechnology and Biological Sciences Research Council (BBSRC)Medical Research Council (MRC)Royal SocietyQUEX Initiator grantEuropean Union Horizon 2020Gordon and Betty and Gordon Moore FoundationWellcome Trus