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Background: Routine human papillomavirus (HPV) testing is performed in cervival cancer and is required for classification of some head and neck cancers. In penile cancer a statement on HPV association of the carcinoma is required. In most cases p16 immunohistochemistry as a surrogate marker is applied in this setting. Since differing clinical outcomes for HPV positive and HPV negative tumors are described we await HPV testing to be requested more frequently by clinicians, also in the context of HPV vaccination, where other HPV subtypes are expected to emerge.
Method: Therefore, a cohort of archived, formalin-fixed paraffin embedded (FFPE) penile neoplasias was stained for p16 and thereafter tested for HPV infection status via PCR based methods. Additionally to Sanger sequencing, we chose LCD-Array technique (HPV 3.5 LCD-Array Kit, Chipron; LCD-Array) for the detection of HPV in our probes expecting a less time consuming and sensitive HPV test for our probes.
Results: We found that LCD-Array is a sensitive and feasible method for HPV testing in routine diagnostics applicable to FFPE material in our cohort. Our cohort of penile carcinomas and carcinomas in situ was associated with HPV infection in 61% of cases. We detected no significant association between HPV infection status and histomorphological tumor characteristics as well as overall survival.
Conclusions: We showed usability of molecular HPV testing on a cohort of archived penile carcinomas. To the best of our knowledge, this is the first study investigating LCD-Array technique on a cohort of penile neoplasias.
Purpose: Suicidality and suicidal ideation (SI) in oncology has long been an underestimated danger. Although there are cancer-specific distress screening tools available, none of these specifically incorporates items for SI. We examined the prevalence of SI in cancer patients, investigated the relation between SI and distress, and tried to identify additional associated factors. Methods: A cross-sectional study with patients treated for cancer in a primary care hospital was conducted. Psychosocial distress and SI in 226 patients was assessed. An expert rating scale (PO-Bado-SF) and a self-assessment instrument (QSC-R23) were used to measure distress. SI was assessed with item 9 of the PHQ-9. Data was descriptively analyzed, and correlations and group comparisons between clinically distressed and non-distressed patients were calculated. Results: SI was reported by 15% of patients. Classified as clinically distressed were 24.8% (QSC-R23) to 36.7% (PO-Bado-SF). SI was correlated with externally (rτ = 0.19, p < 0.001) and self-rated distress (rτ = 0.31, p < 0.001). Symptoms sufficiently severe for at least a medium major depressive episode were recorded in 23.5% of patients (PHQ-9). Factors associated with SI were feeling bad about oneself, feeling down, depressed, and hopeless, deficits in activities of daily life, psycho-somatic afflictions, social restrictions, and restrictions in daily life. Being in a steady relationship seemed to have a protective effect. Conclusions: SI is common in cancer patients. Distress and associated factors are increased in patients with SI. A distress screening with the ability to assess SI could be an important step in prevention, but more research is necessary.
Supersaturating formulations are widely used to improve the oral bioavailability of poorly soluble drugs. However, supersaturated solutions are thermodynamically unstable and such formulations often must include a precipitation inhibitor (PI) to sustain the increased concentrations to ensure that sufficient absorption will take place from the gastrointestinal tract. Recent advances in understanding the importance of drug-polymer interaction for successful precipitation inhibition have been encouraging. However, there still exists a gap in how this newfound understanding can be applied to improve the efficiency of PI screening and selection, which is still largely carried out with trial and error-based approaches. The aim of this study was to demonstrate how drug-polymer mixing enthalpy, calculated with the Conductor like Screening Model for Real Solvents (COSMO-RS), can be used as a parameter to select the most efficient precipitation inhibitors, and thus realise the most successful supersaturating formulations. This approach was tested for three different Biopharmaceutical Classification System (BCS) II compounds: dipyridamole, fenofibrate and glibenclamide, formulated with the supersaturating formulation, mesoporous silica. For all three compounds, precipitation was evident in mesoporous silica formulations without a precipitation inhibitor. Of the nine precipitation inhibitors studied, there was a strong positive correlation between the drug-polymer mixing enthalpy and the overall formulation performance, as measured by the area under the concentration-time curve in in vitro dissolution experiments. The data suggest that a rank-order based approach using calculated drug-polymer mixing enthalpy can be reliably used to select precipitation inhibitors for a more focused screening. Such an approach improves efficiency of precipitation inhibitor selection, whilst also improving the likelihood that the most optimal formulation will be realised.
Background: Chronic hepatitis C is a major public health burden. With new interferon-free direct-acting agents (showing sustained viral response rates of more than 98%), elimination of HCV seems feasible for the first time. However, as HCV infection often remains undiagnosed, screening is crucial for improving health outcomes of HCV-patients. Our aim was to assess the long-term cost-effectiveness of a nationwide screening strategy in Germany.
Methods: We used a Markov cohort model to simulate disease progression and examine long-term population outcomes, HCV associated costs and cost-effectiveness of HCV screening. The model divides the total population into three subpopulations: general population (GEP), people who inject drugs (PWID) and HIV-infected men who have sex with men (MSM), with total infection numbers being highest in GEP, but new infections occurring only in PWIDs and MSM. The model compares four alternative screening strategies (no/basic/advanced/total screening) differing in participation and treatment rates.
Results: Total number of HCV-infected patients declined from 275,000 in 2015 to between 125,000 (no screening) and 14,000 (total screening) in 2040. Similarly, lost quality adjusted life years (QALYs) were 320,000 QALYs lower, while costs were 2.4 billion EUR higher in total screening compared to no screening. While incremental cost-effectiveness ratio (ICER) increased sharply in GEP and MSM with more comprehensive strategies (30,000 EUR per QALY for total vs. advanced screening), ICER decreased in PWIDs (30 EUR per QALY for total vs. advanced screening).
Conclusions: Screening is key to have an efficient decline of the HCV-infected population in Germany. Recommendation for an overall population screening is to screen the total PWID subpopulation, and to apply less comprehensive advanced screening for MSM and GEP.
Telemonitoring devices can be used to screen consumer characteristics and mitigate information asymmetries that lead to adverse selection in insurance markets. Nevertheless, some consumers value their privacy and dislike sharing private information with insurers. In a secondbest efficient Miyazaki-Wilson-Spence (MWS) framework, we allow consumers to reveal their risk type for an individual subjective cost and show analytically how this affects insurance market equilibria as well as social welfare. We find that information disclosure can substitute deductibles for consumers whose transparency aversion is sufficiently low. This can lead to a Pareto improvement of social welfare. Yet, if all consumers are offered cross-subsidizing contracts, the introduction of a screening contract decreases or even eliminates cross-subsidies. Given the prior existence of a cross-subsidizing MWS equilibrium, utility is shifted from individuals who do not reveal their private information to those who choose to reveal. Our analysis informs the discussion on consumer protection in the context of digitalization. It shows that new technologies challenge cross-subsidization in insurance markets, and it stresses the negative externalities that digitalization has on consumers who are unwilling to take part in this development.
Bargaining with a bank
(2018)
This paper examines bargaining as a mechanism to resolve information problems. To guide the analysis, I develop a parsimonious model of a credit negotiation between a bank and firms with varying levels of impatience. In equilibrium, impatient firms accept the bank’s offer immediately, while patient firms wait and negotiate price adjustments. I test the empirical predictions using a hand-collected dataset on credit line negotiations. Firms signing the bank’s offer right away draw down their line of credit after origination and default more than late signers. Late signers negotiate price adjustments more frequently, and, consistent with the model, these adjustments predict better ex post performance.
Telemonitoring devices can be used to screen consumer characteristics and mitigate information asymmetries that lead to adverse selection in insurance markets. Nevertheless, some consumers value their privacy and dislike sharing private information with insurers. In a secondbest efficient Miyazaki-Wilson-Spence (MWS) framework, we allow consumers to reveal their risk type for an individual subjective cost and show analytically how this affects insurance market equilibria as well as social welfare. We find that information disclosure can substitute deductibles for consumers whose transparency aversion is sufficiently low. This can lead to a Pareto improvement of social welfare. Yet, if all consumers are offered cross-subsidizing contracts, the introduction of a screening contract decreases or even eliminates cross-subsidies. Given the prior existence of a cross-subsidizing MWS equilibrium, utility is shifted from individuals who do not reveal their private information to those who choose to reveal. Our analysis informs the discussion on consumer protection in the context of digitalization. It shows that new technologies challenge cross-subsidization in insurance markets, and it stresses the negative externalities that digitalization has on consumers who are unwilling to take part in this
development
Telemonitoring devices can be used to screen consumers' characteristics and mitigate information asymmetries that lead to adverse selection in insurance markets. However, some consumers value their privacy and dislike sharing private information with insurers. In the second-best efficient Wilson-Miyazaki-Spence framework, we allow for consumers to reveal their risk type for an individual subjective cost and show analytically how this affects insurance market equilibria as well as utilitarian social welfare. Our analysis shows that the choice of information disclosure with respect to revelation of their risk type can substitute deductibles for consumers whose transparency aversion is sufficiently low. This can lead to a Pareto improvement of social welfare and a Pareto efficient market allocation. However, if all consumers are offered cross-subsidizing contracts, the introduction of a transparency contract decreases or even eliminates cross-subsidies. Given the prior existence of a WMS equilibrium, utility is shifted from individuals who do not reveal their private information to those who choose to reveal. Our analysis provides a theoretical foundation for the discussion on consumer protection in the context of digitalization. It shows that new technologies bring new ways to challenge crosssubsidization in insurance markets and stresses the negative externalities that digitalization has on consumers who are not willing to take part in this development.
Kurz vor Silvester sah sich der designierte Vorsitzende des deutschen Flughafenverbandes (ADV) Christoph Blume einer heftigen öffentlichen Kritik ausgesetzt. Grund war sein Vorschlag die zukünftigen Flughafenkontrollen nicht auf technisches Screening zu beschränken, sondern durch aktives Profiling deren Effizienz zu optimieren http://www.rp-online.de/politik/deutschland/Flughafenchef-will-Kontrollen-nach-Herkunft_aid_946638.html. Die öffentlichen Proteste waren heftig...
We investigate the utility of modern kernel-based machine learning methods for ligand-based virtual screening. In particular, we introduce a new graph kernel based on iterative graph similarity and optimal assignments, apply kernel principle component analysis to projection error-based novelty detection, and discover a new selective agonist of the peroxisome proliferator-activated receptor gamma using Gaussian process regression. Virtual screening, the computational ranking of compounds with respect to a predicted property, is a cheminformatics problem relevant to the hit generation phase of drug development. Its ligand-based variant relies on the similarity principle, which states that (structurally) similar compounds tend to have similar properties. We describe the kernel-based machine learning approach to ligand-based virtual screening; in this, we stress the role of molecular representations, including the (dis)similarity measures defined on them, investigate effects in high-dimensional chemical descriptor spaces and their consequences for similarity-based approaches, review literature recommendations on retrospective virtual screening, and present an example workflow. Graph kernels are formal similarity measures that are defined directly on graphs, such as the annotated molecular structure graph, and correspond to inner products. We review graph kernels, in particular those based on random walks, subgraphs, and optimal vertex assignments. Combining the latter with an iterative graph similarity scheme, we develop the iterative similarity optimal assignment graph kernel, give an iterative algorithm for its computation, prove convergence of the algorithm and the uniqueness of the solution, and provide an upper bound on the number of iterations necessary to achieve a desired precision. In a retrospective virtual screening study, our kernel consistently improved performance over chemical descriptors as well as other optimal assignment graph kernels. Chemical data sets often lie on manifolds of lower dimensionality than the embedding chemical descriptor space. Dimensionality reduction methods try to identify these manifolds, effectively providing descriptive models of the data. For spectral methods based on kernel principle component analysis, the projection error is a quantitative measure of how well new samples are described by such models. This can be used for the identification of compounds structurally dissimilar to the training samples, leading to projection error-based novelty detection for virtual screening using only positive samples. We provide proof of principle by using principle component analysis to learn the concept of fatty acids. The peroxisome proliferator-activated receptor (PPAR) is a nuclear transcription factor that regulates lipid and glucose metabolism, playing a crucial role in the development of type 2 diabetes and dyslipidemia. We establish a Gaussian process regression model for PPAR gamma agonists using a combination of chemical descriptors and the iterative similarity optimal assignment kernel via multiple kernel learning. Screening of a vendor library and subsequent testing of 15 selected compounds in a cell-based transactivation assay resulted in 4 active compounds. One compound, a natural product with cyclobutane scaffold, is a full selective PPAR gamma agonist (EC50 = 10 +/- 0.2 muM, inactive on PPAR alpha and PPAR beta/delta at 10 muM). The study delivered a novel PPAR gamma agonist, de-orphanized a natural bioactive product, and, hints at the natural product origins of pharmacophore patterns in synthetic ligands.