Designing Policy Solutions to Build a Healthier Rural America

Disparities exist in the livelihood and opportunities for people living in America’s rural communities. These differences result in a much sicker rural America compared to its urban counterpart. Rural counties have higher rates of smoking, obesity, child poverty, and teen pregnancies than urban counties. More uninsured adults live in rural areas, causing rural hospitals to close and/or cut vital services such as obstetrics care. Rural hospitals also provide fewer mental health services. The result is Americans living in rural areas are more likely to die from the five leading causes of death than those living in urban areas: heart disease, cancer, unintentional injuries, chronic lower respiratory disease, and stroke. Depending on the definition of rural, between 46-60 million people, or approximately 15-20 percent of the U.S. population, live in rural communities. Rural communities exist in nearly every state with great variability in their culture, economics, and social conditions. In fact, 97 percent of the country’s land mass is rural. This paper aims to provide a framework for policy solutions to build a healthier rural America. First, the authors describe in detail the health challenges occurring in rural communities and the great disparity that exists between rural and urban health measures. Second, they describe the varying definitions of rural and how this inconsistency in definition leads to greater difficulties in solution design. Third, the authors describe the current state of rural health policy, especially as it relates to current payment mechanisms for hospitals and providers. Finally, they describe innovative policies and practices in states addressing rural health challenges and how many of them could be a model for the country

Detection of (1,3)-β-d-Glucan in Cerebrospinal Fluid in Histoplasma Meningitis

The diagnosis of central nervous system (CNS) histoplasmosis is often difficult. Although cerebrospinal fluid (CSF) (1,3)-β-d-glucan (BDG) is available as a biological marker for the diagnosis of fungal meningitis, there are limited data on its use for the diagnosis of Histoplasma meningitis. We evaluated CSF BDG detection, using the Fungitell assay, in patients with CNS histoplasmosis and controls. A total of 47 cases and 153 controls were identified. The control group included 13 patients with a CNS fungal infection other than histoplasmosis. Forty-nine percent of patients with CNS histoplasmosis and 43.8% of controls were immunocompromised. The median CSF BDG level was 85 pg/ml for cases, compared to <31 pg/ml for all controls (P < 0.05) and 82 pg/ml for controls with other causes of fungal meningitis (P = 0.27). The sensitivity for detection of BDG in CSF was 53.2%, whereas the specificity was 86.9% versus all controls and 46% versus other CNS fungal infections. CSF BDG levels of ≥80 pg/ml are neither sensitive nor specific to support a diagnosis of Histoplasma meningitis

Detection of (1,3)-\u3cem\u3eβ\u3c/em\u3e-D-Glucan in Cerebrospinal Fluid in \u3cem\u3eHistoplasma\u3c/em\u3e Meningitis

The diagnosis of central nervous system (CNS) histoplasmosis is often difficult. Although cerebrospinal fluid (CSF) (1,3)-β-d-glucan (BDG) is available as a biological marker for the diagnosis of fungal meningitis, there are limited data on its use for the diagnosis of Histoplasma meningitis. We evaluated CSF BDG detection, using the Fungitell assay, in patients with CNS histoplasmosis and controls. A total of 47 cases and 153 controls were identified. The control group included 13 patients with a CNS fungal infection other than histoplasmosis. Forty-nine percent of patients with CNS histoplasmosis and 43.8% of controls were immunocompromised. The median CSF BDG level was 85 pg/ml for cases, compared to \u3c 31 pg/ml for all controls (P \u3c 0.05) and 82 pg/ml for controls with other causes of fungal meningitis (P = 0.27). The sensitivity for detection of BDG in CSF was 53.2%, whereas the specificity was 86.9% versus all controls and 46% versus other CNS fungal infections. CSF BDG levels of ≥ 80 pg/ml are neither sensitive nor specific to support a diagnosis of Histoplasma meningitis

Improvement in Diagnosis of \u3cem\u3eHistoplasma\u3c/em\u3e Meningitis by Combined Testing for \u3cem\u3eHistoplasma\u3c/em\u3e Antigen and Immunoglobulin G and Immunoglobulin M Anti-\u3cem\u3eHistoplasma\u3c/em\u3e Antibody in Cerebrospinal Fluid

Background. Central nervous system (CNS) histoplasmosis is a life-threatening condition and represents a diagnostic and therapeutic challenge. Isolation of Histoplasma capsulatum from cerebrospinal fluid (CSF) or brain tissue is diagnostic; however, culture is insensitive and slow growth may result in significant treatment delay. We performed a retrospective multicenter study to evaluate the sensitivity and specificity of a new anti-Histoplasma antibody enzyme immunoassay (EIA) for the detection of IgG and IgM antibody in the CSF for diagnosis of CNS histoplasmosis, the primary objective of the study. The secondary objective was to determine the effect of improvements in the Histoplasma galactomannan antigen detection EIA on the diagnosis of Histoplasma meningitis. Methods. Residual CSF specimens from patients with Histoplasma meningitis and controls were tested for Histoplasma antigen and anti-Histoplasma immunoglobulin G (IgG) and immunoglobulin M (IgM) antibody using assays developed at MiraVista Diagnostics. Results. A total of 50 cases and 157 controls were evaluated. Fifty percent of patients with CNS histoplasmosis were immunocompromised, 14% had other medical conditions, and 36% were healthy. Histoplasma antigen was detected in CSF in 78% of cases and the specificity was 97%. Anti-Histoplasma IgG or IgM antibody was detected in 82% of cases and the specificity was 93%. The sensitivity of detection of antibody by currently available serologic testing including immunodiffusion and complement fixation was 51% and the specificity was 96%. Testing for both CSF antigen and antibody by EIA was the most sensitive approach, detecting 98% of cases. Conclusions. Testing CSF for anti-Histoplasma IgG and IgM antibody complements antigen detection and improves the sensitivity for diagnosis of Histoplasma meningitis

Matrilineal behavioral and physiological changes following the death of a non-alpha matriarch in rhesus macaque

In many species, the loss of alpha matriarchs is associated with a number of negative outcomes such as troop fission, eviction, wounding, and reduced vitality. However, whether the dramatic consequences of their loss are due to their role as an old experienced figure or to their alpha status remains unclear. In a retrospective study, we tested that in a semi-free ranging colony of rhesus macaques (Macaca mulatta), the removal of a non-alpha matriarch, who had a large set of kin, led to changes in behavior and physiological stress within her matriline. Following her removal, her matriline increased in aggression, vigilance, and social grooming. Additionally, hierarchical stability, measured by levels of rank changes, decreased within her matriline, and levels of intense aggression by high-ranking animals were more frequent, as well as matrilineal wounding. Although ordinal rank was positively associated with higher chronic hair cortisol concentrations (HCCs) in the months before the matriarch’s removal, following her removal, only those who experienced large increases in rank within her matriline displayed higher HCCs. Changes in matrilineal stability, aggression, behavior, and HCCs within the other two matrilines in the troop were not evident, although caution is needed due to the small sample sizes. We conclude that the removal of the non-alpha matriarch led to matrilineal instability, characterized by higher levels of aggression and subsequent vigilance, rank changes, physiological stress, and grooming. We suggest that non-alpha matriarchs with a large number of kin and social support can be integral to the stability of matrilines.Division of Intramural Research, National Institute of Child Health and Human Development, 1ZIAHD001107- 3

Justify your alpha

Benjamin et al. proposed changing the conventional “statistical significance” threshold (i.e.,the alpha level) from p ≤ .05 to p ≤ .005 for all novel claims with relatively low prior odds. They provided two arguments for why lowering the significance threshold would “immediately improve the reproducibility of scientific research.” First, a p-value near .05provides weak evidence for the alternative hypothesis. Second, under certain assumptions, an alpha of .05 leads to high false positive report probabilities (FPRP2 ; the probability that a significant finding is a false positive

The genetic architecture of the human cerebral cortex

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder

Justify your alpha

In response to recommendations to redefine statistical significance to p ≤ .005, we propose that researchers should transparently report and justify all choices they make when designing a study, including the alpha level

Brain multiplexes reveal morphological connectional biomarkers fingerprinting late brain dementia states

Accurate diagnosis of mild cognitive impairment (MCI) before conversion to Alzheimer’s disease (AD) is invaluable for patient treatment. Many works showed that MCI and AD affect functional and structural connections between brain regions as well as the shape of cortical regions. However, ‘shape connections’ between brain regions are rarely investigated -e.g., how morphological attributes such as cortical thickness and sulcal depth of a specific brain region change in relation to morphological attributes in other regions. To fill this gap, we unprecedentedly design morphological brain multiplexes for late MCI/AD classification. Specifically, we use structural T1-w MRI to define morphological brain networks, each quantifying similarity in morphology between different cortical regions for a specific cortical attribute. Then, we define a brain multiplex where each intra-layer represents the morphological connectivity network of a specific cortical attribute, and each inter-layer encodes the similarity between two consecutive intra-layers. A significant performance gain is achieved when using the multiplex architecture in comparison to other conventional network analysis architectures. We also leverage this architecture to discover morphological connectional biomarkers fingerprinting the difference between late MCI and AD stages, which included the right entorhinal cortex and right caudal middle frontal gyrus