USE OF DRUG ELUTING STENTS AS A FUNCTION OF PREDICTED BENEFIT: CLINICAL AND ECONOMIC IMPLICATIONS OF CURRENT PRACTICE

Background: Benefits of drug-eluting stents (DES) in percutaneous coronary intervention (PCI) are greatest in those at the highest risk of target vessel revascularization (TVR). While DES reduce restenosis, they cost more than bare metal stents (BMS), and necessitate prolonged dual antiplatelet therapy (DAPT) that increases costs, bleeding risk, and risk of complications if DAPT is prematurely discontinued. Our objectives were to assess if DES are preferentially used in those with higher predicted TVR risk, and to estimate whether lower use of DES (50% less DES use among patients with low predicted TVR risk) would be more cost-effective as compared with the existing pattern of DES use. Methods: We analyzed ~1.5 million PCI procedures in the NCDR CathPCI registry from Apr 2003 - Sept 2010. We estimated 1-year TVR risk assuming PCI with BMS using a previously validated prediction model. The main outcome measures were the rate of DES use and projected annual US societal costs at one year after PCI. We assessed the association between TVR risk with BMS DES use, and performed cost-effectiveness analysis of a lower use of DES (50% less DES use among patients with low predicted TVR risk) vs. existing DES use. Results: There was marked variation in physicians' use of DES (range = 2-100%). DES use was relatively high across all categories of predicted TVR risk (73.9% in patients with TVR risk 20%), with a modest correlation between predicted TVR risk and DES use (RR 1.005/1% increase in predicted TVR risk [95% CI = 1.005, 1.006]). Reducing DES use by 50% among the lowest risk patients was projected to lower US healthcare costs by $205 million/year while increasing the overall TVR event rate by 0.5% (95% CI= 0.49%, 0.51%) in absolute terms. Conclusions: DES use in the U.S. varies widely among physicians, with only modest correlation to patients' risk of restenosis. Less DES use among patients with low risk of restenosis has the potential for significant cost savings for the US healthcare system, while minimally increasing restenosis events

Microscopic force for aerosol transport

A key ingredient for single particle diffractive imaging experiments is the successful and efficient delivery of sample. Current sample-delivery methods are based on aerosol injectors in which the samples are driven by fluid-dynamic forces. These are typically simulated using Stokes' drag forces and for micrometer-size or smaller particles, the Cunningham correction factor is applied. This is not only unsatisfactory, but even using a temperature dependent formulation it fails at cryogenic temperatures. Here we propose the use of a direct computation of the force, based on Epstein's formulation, that allows for high relative velocities of the particles to the gas and also for internal particle temperatures that differ from the gas temperature. The new force reproduces Stokes' drag force for conditions known to be well described by Stokes' drag. Furthermore, it shows excellent agreement to experiments at 4 K, confirming the improved descriptive power of simulations over a wide temperature range

Microscopic force for aerosol transport

A key ingredient for single particle diffractive imaging experiments is the successful and efficient delivery of sample. Current sample-delivery methods are based on aerosol injectors in which the samples are driven by fluid-dynamic forces. These are typically simulated using Stokes' drag forces and for micrometer-size or smaller particles, the Cunningham correction factor is applied. This is not only unsatisfactory, but even using a temperature dependent formulation it fails at cryogenic temperatures. Here we propose the use of a direct computation of the force, based on Epstein's formulation, that allows for high relative velocities of the particles to the gas and also for internal particle temperatures that differ from the gas temperature. The new force reproduces Stokes' drag force for conditions known to be well described by Stokes' drag. Furthermore, it shows excellent agreement to experiments at 4 K, confirming the improved descriptive power of simulations over a wide temperature range

Laser-induced alignment of nanoparticles and macromolecules for single-particle-imaging applications

Laser-induced alignment of particles and molecules was long envisioned to support three-dimensional structure determination using single-particle imaging with x-ray free-electron lasers [PRL 92, 198102 (2004)]. However, geometric alignment of isolated macromolecules has not yet been demonstrated. Using molecular modeling, we analyzed and demonstrated how the alignment of large nanorods and proteins is possible with standard laser technology, and performed a comprehensive analysis on the dependence of the degree of alignment on molecular properties and experimental details. Calculations of the polarizability anisotropy of about 150,000 proteins yielded a skew-normal distribution with a location of 1.2, which reveals that most of these proteins can be aligned using appropriate, realistic experimental parameters. Moreover, we explored the dependence of the degree of alignment on experimental parameters such as particle temperature and laser-pulse energy

A simple method to combine multiple molecular biomarkers for dichotomous diagnostic classification

BACKGROUND: In spite of the recognized diagnostic potential of biomarkers, the quest for squelching noise and wringing in information from a given set of biomarkers continues. Here, we suggest a statistical algorithm that – assuming each molecular biomarker to be a diagnostic test – enriches the diagnostic performance of an optimized set of independent biomarkers employing established statistical techniques. We validated the proposed algorithm using several simulation datasets in addition to four publicly available real datasets that compared i) subjects having cancer with those without; ii) subjects with two different cancers; iii) subjects with two different types of one cancer; and iv) subjects with same cancer resulting in differential time to metastasis. RESULTS: Our algorithm comprises of three steps: estimating the area under the receiver operating characteristic curve for each biomarker, identifying a subset of biomarkers using linear regression and combining the chosen biomarkers using linear discriminant function analysis. Combining these established statistical methods that are available in most statistical packages, we observed that the diagnostic accuracy of our approach was 100%, 99.94%, 96.67% and 93.92% for the real datasets used in the study. These estimates were comparable to or better than the ones previously reported using alternative methods. In a synthetic dataset, we also observed that all the biomarkers chosen by our algorithm were indeed truly differentially expressed. CONCLUSION: The proposed algorithm can be used for accurate diagnosis in the setting of dichotomous classification of disease states

The Roles of the Saccharomyces cerevisiae RecQ Helicase SGS1 in Meiotic Genome Surveillance

leads to an increase in synapsis initiation complexes and axial associations leading to the proposal that it has an early role in unwinding surplus strand invasion events. Physical studies of recombination intermediates implicate it in the dissolution of double Holliday junctions between sister chromatids. chromosomes may sometimes remain entangled at the end of pre-meiotic replication. This, combined with reciprocal crossing over, could lead to physical destruction of the recombined and entangled chromosomes. We hypothesise that Sgs1, acting in concert with the topoisomerase Top2, resolves these structures.This work provides evidence that Sgs1 interacts with various partner proteins to maintain genome stability throughout meiosis