Testing of a Model with Latino Patients That Explains the Links Among Patient-Perceived Provider Cultural Sensitivity, Language Preference, and Patient Treatment Adherence

Introduction Disparities in treatment adherence based on race and ethnicity are well documented but poorly understood. Specifically, the causes of treatment nonadherence among Latino patients living in the USA are complex and include cultural and language barriers. Purpose The purpose of this study was to examine whether patients’ perceptions in patient-provider interactions (i.e., trust in provider, patient satisfaction, and patient sense of interpersonal control in patient-provider interactions) mediate any found association between patient-perceived provider cultural sensitivity (PCS) and treatment adherence among English-preferred Latino (EPL) and Spanish-preferred Latino (SPL) patients. Methods Data from 194 EPL patients and 361 SPL patients were obtained using questionnaires. A series of language-specific structural equation models were conducted to test the relationship between patient-perceived PCS and patient treatment adherence and the examined mediators of this relationship among the Latino patients. Results No significant direct effects of patient-perceived PCS on general treatment adherence were found. However, as hypothesized, several significant indirect effects emerged. Preferred language appeared to have moderating effects on the relationships between patient-perceived PCS and general treatment adherence. Conclusion These results suggest that interventions to promote treatment adherence among Latino patients should likely include provider training to foster patient-defined PCS, trust in provider, and patient satisfaction with care. Furthermore, this training needs to be customized to be suitable for providing care to Latino patients who prefer speaking Spanish and Latino patients who prefer speaking English

Mid-infrared optical parametric amplifier using silicon nanophotonic waveguides

All-optical signal processing is envisioned as an approach to dramatically decrease power consumption and speed up performance of next-generation optical telecommunications networks. Nonlinear optical effects, such as four-wave mixing (FWM) and parametric gain, have long been explored to realize all-optical functions in glass fibers. An alternative approach is to employ nanoscale engineering of silicon waveguides to enhance the optical nonlinearities by up to five orders of magnitude, enabling integrated chip-scale all-optical signal processing. Previously, strong two-photon absorption (TPA) of the telecom-band pump has been a fundamental and unavoidable obstacle, limiting parametric gain to values on the order of a few dB. Here we demonstrate a silicon nanophotonic optical parametric amplifier exhibiting gain as large as 25.4 dB, by operating the pump in the mid-IR near one-half the band-gap energy (E~0.55eV, lambda~2200nm), at which parasitic TPA-related absorption vanishes. This gain is high enough to compensate all insertion losses, resulting in 13 dB net off-chip amplification. Furthermore, dispersion engineering dramatically increases the gain bandwidth to more than 220 nm, all realized using an ultra-compact 4 mm silicon chip. Beyond its significant relevance to all-optical signal processing, the broadband parametric gain also facilitates the simultaneous generation of multiple on-chip mid-IR sources through cascaded FWM, covering a 500 nm spectral range. Together, these results provide a foundation for the construction of silicon-based room-temperature mid-IR light sources including tunable chip-scale parametric oscillators, optical frequency combs, and supercontinuum generators

Screening for Alcoholism Among Medical Inpatients: How Important Is Corroboration of Patient Self-Report?

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/65580/1/j.1530-0277.1998.tb03925.x.pd

Phylogenetic relationships of cone snails endemic to Cabo Verde based on mitochondrial genomes

Background: Due to their great species and ecological diversity as well as their capacity to produce hundreds of different toxins, cone snails are of interest to evolutionary biologists, pharmacologists and amateur naturalists alike. Taxonomic identification of cone snails still relies mostly on the shape, color, and banding patterns of the shell. However, these phenotypic traits are prone to homoplasy. Therefore, the consistent use of genetic data for species delimitation and phylogenetic inference in this apparently hyperdiverse group is largely wanting. Here, we reconstruct the phylogeny of the cones endemic to Cabo Verde archipelago, a well-known radiation of the group, using mitochondrial (mt) genomes. Results: The reconstructed phylogeny grouped the analyzed species into two main clades, one including Kalloconus from West Africa sister to Trovaoconus from Cabo Verde and the other with a paraphyletic Lautoconus due to the sister group relationship of Africonus from Cabo Verde and Lautoconus ventricosus from Mediterranean Sea and neighboring Atlantic Ocean to the exclusion of Lautoconus endemic to Senegal (plus Lautoconus guanche from Mauritania, Morocco, and Canary Islands). Within Trovaoconus, up to three main lineages could be distinguished. The clade of Africonus included four main lineages (named I to IV), each further subdivided into two monophyletic groups. The reconstructed phylogeny allowed inferring the evolution of the radula in the studied lineages as well as biogeographic patterns. The number of cone species endemic to Cabo Verde was revised under the light of sequence divergence data and the inferred phylogenetic relationships. Conclusions: The sequence divergence between continental members of the genus Kalloconus and island endemics ascribed to the genus Trovaoconus is low, prompting for synonymization of the latter. The genus Lautoconus is paraphyletic. Lautoconus ventricosus is the closest living sister group of genus Africonus. Diversification of Africonus was in allopatry due to the direct development nature of their larvae and mainly triggered by eustatic sea level changes during the Miocene-Pliocene. Our study confirms the diversity of cone endemic to Cabo Verde but significantly reduces the number of valid species. Applying a sequence divergence threshold, the number of valid species within the sampled Africonus is reduced to half.Spanish Ministry of Science and Innovation [CGL2013-45211-C2-2-P, CGL2016-75255-C2-1-P, BES-2011-051469, BES-2014-069575, Doctorado Nacional-567]info:eu-repo/semantics/publishedVersio

The Cosmology of Composite Inelastic Dark Matter

Composite dark matter is a natural setting for implementing inelastic dark matter - the O(100 keV) mass splitting arises from spin-spin interactions of constituent fermions. In models where the constituents are charged under an axial U(1) gauge symmetry that also couples to the Standard Model quarks, dark matter scatters inelastically off Standard Model nuclei and can explain the DAMA/LIBRA annual modulation signal. This article describes the early Universe cosmology of a minimal implementation of a composite inelastic dark matter model where the dark matter is a meson composed of a light and a heavy quark. The synthesis of the constituent quarks into dark mesons and baryons results in several qualitatively different configurations of the resulting dark matter hadrons depending on the relative mass scales in the system.Comment: 31 pages, 4 figures; references added, typos correcte

Multiway modeling and analysis in stem cell systems biology

<p>Abstract</p> <p>Background</p> <p>Systems biology refers to multidisciplinary approaches designed to uncover emergent properties of biological systems. Stem cells are an attractive target for this analysis, due to their broad therapeutic potential. A central theme of systems biology is the use of computational modeling to reconstruct complex systems from a wealth of reductionist, molecular data (e.g., gene/protein expression, signal transduction activity, metabolic activity, etc.). A number of deterministic, probabilistic, and statistical learning models are used to understand sophisticated cellular behaviors such as protein expression during cellular differentiation and the activity of signaling networks. However, many of these models are bimodal i.e., they only consider row-column relationships. In contrast, multiway modeling techniques (also known as tensor models) can analyze multimodal data, which capture much more information about complex behaviors such as cell differentiation. In particular, tensors can be very powerful tools for modeling the dynamic activity of biological networks over time. Here, we review the application of systems biology to stem cells and illustrate application of tensor analysis to model collagen-induced osteogenic differentiation of human mesenchymal stem cells.</p> <p>Results</p> <p>We applied Tucker1, Tucker3, and Parallel Factor Analysis (PARAFAC) models to identify protein/gene expression patterns during extracellular matrix-induced osteogenic differentiation of human mesenchymal stem cells. In one case, we organized our data into a tensor of type protein/gene locus link × gene ontology category × osteogenic stimulant, and found that our cells expressed two distinct, stimulus-dependent sets of functionally related genes as they underwent osteogenic differentiation. In a second case, we organized DNA microarray data in a three-way tensor of gene IDs × osteogenic stimulus × replicates, and found that application of tensile strain to a collagen I substrate accelerated the osteogenic differentiation induced by a static collagen I substrate.</p> <p>Conclusion</p> <p>Our results suggest gene- and protein-level models whereby stem cells undergo transdifferentiation to osteoblasts, and lay the foundation for mechanistic, hypothesis-driven studies. Our analysis methods are applicable to a wide range of stem cell differentiation models.</p

Living in rural New England amplifies the risk of depression in patients with HIV

<p>Abstract</p> <p>Background</p> <p>The importance of depression as a complication of HIV infection is increasingly understood, and people living in rural areas are at increased risk for depression. However, it is not known whether living in rural areas amplifies the risk of depression in patients with HIV.</p> <p>Methods</p> <p>We compared the prevalence of depression between rural and metropolitan HIV patients seen at the Dartmouth-Hitchcock HIV Program in a retrospective cohort study. Using the validated Rural-Urban Commuting Area Score, we categorized patients as living in small town/rural areas, micropolitan or metropolitan towns. Then, using a multivariate logistic regression model to adjust for demographic factors that differed between rural and metropolitan patients, we estimated the impact of living in rural areas on the odds of depression.</p> <p>Results</p> <p>Among 646 patients with HIV (185 small town/rural, 145 micropolitan, 316 metropolitan), rural patients were older, white, male, and men who have sex with men (ANOVA, F-statistic < 0.05). The prevalence of depression was highest in rural patients (59.5 vs. 51.7 vs. 41.2%, F statistic < 0.001), particularly rural patients on antiretroviral therapy (72.4 vs. 53.5 vs. 38.2%, F-statistic < 0.001. A multivariate logistic regression model showed that the odds of depression in rural patients with HIV were 1.34 (P < 0.001).</p> <p>Conclusion</p> <p>HIV-infected patients living in rural areas, particularly those on antiretroviral therapy, are highly vulnerable to depression.</p