Cost-of-illness in psoriasis: Comparing inpatient and outpatient therapy

Treatment modalities of chronic plaque psoriasis have dramatically changed over the past ten years with a still continuing shift from inpatient to outpatient treatment. This development is mainly caused by outpatient availability of highly efficient and relatively well-tolerated systemic treatments, in particular BioLogicals. In addition, inpatient treatment is time- and cost-intense, conflicting with the actual burst of health expenses and with patient preferences. Nevertheless, inpatient treatment with dithranol and UV light still is a major mainstay of psoriasis treatment in Germany. The current study aims at comparing the total costs of inpatient treatment and outpatient follow-up to mere outpatient therapy with different modalities (topical treatment, phototherapy, classic systemic therapy or BioLogicals) over a period of 12 months. To this end, a retrospective cost-of-illness study was conducted on 120 patients treated at the University Medical Centre Mannheim between 2005 and 2006. Inpatient therapy caused significantly higher direct medical, indirect and total annual costs than outpatient treatment (13,042 € versus 2,984 €). Its strong influence on cost levels was confirmed by regression analysis, with total costs rising by 104.3% in case of inpatient treatment. Patients receiving BioLogicals produced the overall highest costs, whereas outpatient treatment with classic systemic antipsoriatic medications was less cost-intense than other alternatives

Substantiating harm reduction and supporting tobacco regulatory science

A framework for the assessment of novel next-generation tobacco and nicotine products with the potential to reduce health risks compared with cigarettes should integrate scientific studies incorpor..

Cellulose acetate phthalate, a common pharmaceutical excipient, inactivates HIV-1 and blocks the coreceptor binding site on the virus envelope glycoprotein gp120

BACKGROUND: Cellulose acetate phthalate (CAP), a pharmaceutical excipient used for enteric film coating of capsules and tablets, was shown to inhibit infection by the human immunodeficiency virus type 1 (HIV-1) and several herpesviruses. CAP formulations inactivated HIV-1, herpesvirus types 1 (HSV-1) and 2 (HSV-2) and the major nonviral sexually transmitted disease (STD) pathogens and were effective in animal models for vaginal infection by HSV-2 and simian immunodeficiency virus. METHODS: Enzyme-linked immunoassays and flow cytometry were used to demonstrate CAP binding to HIV-1 and to define the binding site on the virus envelope. RESULTS: 1) CAP binds to HIV-1 virus particles and to the envelope glycoprotein gp120; 2) this leads to blockade of the gp120 V3 loop and other gp120 sites resulting in diminished reactivity with HIV-1 coreceptors CXCR4 and CCR5; 3) CAP binding to HIV-1 virions impairs their infectivity; 4) these findings apply to both HIV-1 IIIB, an X4 virus, and HIV-1 BaL, an R5 virus. CONCLUSIONS: These results provide support for consideration of CAP as a topical microbicide of choice for prevention of STDs, including HIV-1 infection

Systems toxicology: real world applications and opportunities

Systems Toxicology aims to change the basis of how adverse biological effects of xenobiotics are characterized from empirical end points to describing modes of action as adverse outcome pathways and perturbed networks. Toward this aim, Systems Toxicology entails the integration of in vitro and in vivo toxicity data with computational modeling. This evolving approach depends critically on data reliability and relevance, which in turn depends on the quality of experimental models and bioanalysis techniques used to generate toxicological data. Systems Toxicology involves the use of large-scale data streams ("big data"), such as those derived from omics measurements that require computational means for obtaining informative results. Thus, integrative analysis of multiple molecular measurements, particularly acquired by omics strategies, is a key approach in Systems Toxicology. In recent years, there have been significant advances centered on in vitro test systems and bioanalytical strategies, yet a frontier challenge concerns linking observed network perturbations to phenotypes, which will require understanding pathways and networks that give rise to adverse responses. This summary perspective from a 2016 Systems Toxicology meeting, an international conference held in the Alps of Switzerland, describes the limitations and opportunities of selected emerging applications in this rapidly advancing field. Systems Toxicology aims to change the basis of how adverse biological effects of xenobiotics are characterized, from empirical end points to pathways of toxicity. This requires the integration of in vitro and in vivo data with computational modeling. Test systems and bioanalytical technologies have made significant advances, but ensuring data reliability and relevance is an ongoing concern. The major challenge facing the new pathway approach is determining how to link observed network perturbations to phenotypic toxicity

Construction of a computable cell proliferation network focused on non-diseased lung cells

<p>Abstract</p> <p>Background</p> <p>Critical to advancing the systems-level evaluation of complex biological processes is the development of comprehensive networks and computational methods to apply to the analysis of systems biology data (transcriptomics, proteomics/phosphoproteomics, metabolomics, etc.). Ideally, these networks will be specifically designed to capture the normal, non-diseased biology of the tissue or cell types under investigation, and can be used with experimentally generated systems biology data to assess the biological impact of perturbations like xenobiotics and other cellular stresses. Lung cell proliferation is a key biological process to capture in such a network model, given the pivotal role that proliferation plays in lung diseases including cancer, chronic obstructive pulmonary disease (COPD), and fibrosis. Unfortunately, no such network has been available prior to this work.</p> <p>Results</p> <p>To further a systems-level assessment of the biological impact of perturbations on non-diseased mammalian lung cells, we constructed a lung-focused network for cell proliferation. The network encompasses diverse biological areas that lead to the regulation of normal lung cell proliferation (Cell Cycle, Growth Factors, Cell Interaction, Intra- and Extracellular Signaling, and Epigenetics), and contains a total of 848 nodes (biological entities) and 1597 edges (relationships between biological entities). The network was verified using four published gene expression profiling data sets associated with measured cell proliferation endpoints in lung and lung-related cell types. Predicted changes in the activity of core machinery involved in cell cycle regulation (RB1, CDKN1A, and MYC/MYCN) are statistically supported across multiple data sets, underscoring the general applicability of this approach for a network-wide biological impact assessment using systems biology data.</p> <p>Conclusions</p> <p>To the best of our knowledge, this lung-focused Cell Proliferation Network provides the most comprehensive connectivity map in existence of the molecular mechanisms regulating cell proliferation in the lung. The network is based on fully referenced causal relationships obtained from extensive evaluation of the literature. The computable structure of the network enables its application to the qualitative and quantitative evaluation of cell proliferation using systems biology data sets. The network is available for public use.</p

Regioselective glucosidation of trans-resveratrol in Escherichia coli expressing glucosyltransferase from Phytolacca americana

A glucosyltransferase (GT) of Phytolacca americana (PaGT3) was expressed in Escherichia coli and purified for the synthesis of two O-β-glucoside products of trans-resveratrol. The reaction was moderately regioselective with a ratio of 4′-O-β-glucoside: 3-O-β-glucoside at 10:3. We used not only the purified enzyme but also the E. coli cells containing the PaGT3 gene for the synthesis of glycoconjugates. E. coli cell cultures also have other advantages, such as a shorter incubation time compared with cultured plant cells, no need for the addition of exogenous glucosyl donor compounds such as UDP-glucose, and almost complete conversion of the aglycone to the glucoside products. Furthermore, a homology model of PaGT3 and mutagenesis studies suggested that His-20 would be a catalytically important residue

Photoreceptor Spectral Sensitivity in the Bumblebee, Bombus impatiens (Hymenoptera: Apidae)

The bumblebee Bombus impatiens is increasingly used as a model in comparative studies of colour vision, or in behavioural studies relying on perceptual discrimination of colour. However, full spectral sensitivity data on the photoreceptor inputs underlying colour vision are not available for B. impatiens. Since most known bee species are trichromatic, with photoreceptor spectral sensitivity peaks in the UV, blue and green regions of the spectrum, data from a related species, where spectral sensitivity measurements have been made, are often applied to B impatiens. Nevertheless, species differences in spectral tuning of equivalent photoreceptor classes may result in peaks that differ by several nm, which may have small but significant effects on colour discrimination ability. We therefore used intracellular recording to measure photoreceptor spectral sensitivity in B. impatiens. Spectral peaks were estimated at 347, 424 and 539 nm for UV, blue and green receptors, respectively, suggesting that this species is a UV-blue-green trichromat. Photoreceptor spectral sensitivity peaks are similar to previous measurements from Bombus terrestris, although there is a significant difference in the peak sensitivity of the blue receptor, which is shifted in the short wave direction by 12–13 nm in B. impatiens compared to B. terrestris

Outcomes associated with matching patients' treatment preferences to physicians' recommendations: study methodology

<p>Abstract</p> <p>Background</p> <p>Patients often express strong preferences for the forms of treatment available for their disease. Incorporating these preferences into the process of treatment decision-making might improve patients' adherence to treatment, contributing to better outcomes. We describe the methodology used in a study aiming to assess treatment outcomes when patients' preferences for treatment are closely matched to recommended treatments.</p> <p>Method</p> <p>Participants included patients with moderate and severe psoriasis attending outpatient dermatology clinics at the University Medical Centre Mannheim, University of Heidelberg, Germany. A self-administered online survey used conjoint analysis to measure participants' preferences for psoriasis treatment options at the initial study visit. Physicians' treatment recommendations were abstracted from each participant's medical records. The Preference Matching Index (PMI), a measure of concordance between the participant's preferences for treatment and the physician's recommended treatment, was determined for each participant at t₁(initial study visit). A clinical outcome measure, the Psoriasis Area and Severity Index, and two participant-derived outcomes assessing treatment satisfaction and health related quality of life were employed at t₁, t₂(twelve weeks post-t₁) and t₃(twelve weeks post-t₂). Change in outcomes was assessed using repeated measures analysis of variance. The association between participants' PMI scores at t₁and outcomes at t₂and t₃was evaluated using multivariate regressions analysis.</p> <p>Discussion</p> <p>We describe methods for capturing concordance between patients' treatment preferences and recommended treatment and for assessing its association with specific treatment outcomes. The methods are intended to promote the incorporation of patients' preferences in treatment decision-making, enhance treatment satisfaction, and improve treatment effectiveness through greater adherence.</p

Industrial methodology for process verification in research (IMPROVER): toward systems biology verification

Motivation: Analyses and algorithmic predictions based on high-throughput data are essential for the success of systems biology in academic and industrial settings. Organizations, such as companies and academic consortia, conduct large multi-year scientific studies that entail the collection and analysis of thousands of individual experiments, often over many physical sites and with internal and outsourced components. To extract maximum value, the interested parties need to verify the accuracy and reproducibility of data and methods before the initiation of such large multi-year studies. However, systematic and well-established verification procedures do not exist for automated collection and analysis workflows in systems biology which could lead to inaccurate conclusions