A Uniform Method for Proving Lower Bounds of the Computational Complexity of Logical Theories

https://deepblue.lib.umich.edu/bitstream/2027.42/154178/1/39015100081655.pd

Architecture of the Short External Rotator Muscles of the Hip.

BackgroundMuscle architecture, or the arrangement of sarcomeres and fibers within muscles, defines functional capacity. There are limited data that provide an understanding of hip short external rotator muscle architecture. The purpose of this study was thus to characterize the architecture of these small hip muscles.MethodsEight muscles from 10 independent human cadaver hips were used in this study (n = 80 muscles). Architectural measurements were made on pectineus, piriformis, gemelli, obturators, quadratus femoris, and gluteus minimus. Muscle mass, fiber length, sarcomere length, and pennation angle were used to calculate the normalized muscle fiber length, which defines excursion, and physiological cross-sectional area (PCSA), which defines force-producing capacity.ResultsGluteus minimus had the largest PCSA (8.29 cm2) followed by obturator externus (4.54 cm2), whereas superior gemellus had the smallest PCSA (0.68 cm2). Fiber lengths clustered into long (pectineus - 10.38 cm and gluteus minimus - 10.30 cm), moderate (obturator internus - 8.77 cm and externus - 8.04 cm), or short (inferior gemellus - 5.64 and superior gemellus - 4.85). There were no significant differences among muscles in pennation angle which were all nearly zero. When the gemelli and obturators were considered as a single functional unit, their collective PCSA (10.00 cm2) exceeded that of gluteus minimus as a substantial force-producing group.ConclusionsThe key findings are that these muscles have relatively small individual PCSAs, short fiber lengths, and low pennation angles. The large collective PCSA and short fiber lengths of the gemelli and obturators suggest that they primarily play a stabilizing role rather than a joint rotating role

Nonconvergence, Undecidability, and Intractability in Asymptotic Problems

https://deepblue.lib.umich.edu/bitstream/2027.42/154144/1/39015099114582.pd

Integration of Attributes from Non-Linear Characterization of Cardiovascular Time-Series for Prediction of Defibrillation Outcomes

Objective The timing of defibrillation is mostly at arbitrary intervals during cardio-pulmonary resuscitation (CPR), rather than during intervals when the out-of-hospital cardiac arrest (OOH-CA) patient is physiologically primed for successful countershock. Interruptions to CPR may negatively impact defibrillation success. Multiple defibrillations can be associated with decreased post-resuscitation myocardial function. We hypothesize that a more complete picture of the cardiovascular system can be gained through non-linear dynamics and integration of multiple physiologic measures from biomedical signals. Materials and Methods Retrospective analysis of 153 anonymized OOH-CA patients who received at least one defibrillation for ventricular fibrillation (VF) was undertaken. A machine learning model, termed Multiple Domain Integrative (MDI) model, was developed to predict defibrillation success. We explore the rationale for non-linear dynamics and statistically validate heuristics involved in feature extraction for model development. Performance of MDI is then compared to the amplitude spectrum area (AMSA) technique. Results 358 defibrillations were evaluated (218 unsuccessful and 140 successful). Non-linear properties (Lyapunov exponent \u3e 0) of the ECG signals indicate a chaotic nature and validate the use of novel non-linear dynamic methods for feature extraction. Classification using MDI yielded ROC-AUC of 83.2% and accuracy of 78.8%, for the model built with ECG data only. Utilizing 10-fold cross-validation, at 80% specificity level, MDI (74% sensitivity) outperformed AMSA (53.6% sensitivity). At 90% specificity level, MDI had 68.4% sensitivity while AMSA had 43.3% sensitivity. Integrating available end-tidal carbon dioxide features into MDI, for the available 48 defibrillations, boosted ROC-AUC to 93.8% and accuracy to 83.3% at 80% sensitivity. Conclusion At clinically relevant sensitivity thresholds, the MDI provides improved performance as compared to AMSA, yielding fewer unsuccessful defibrillations. Addition of partial end-tidal carbon dioxide (PetCO2) signal improves accuracy and sensitivity of the MDI prediction model

On the physical origins of the negative index of refraction

The physical origins of negative refractive index are derived from a dilute microscopic model, producing a result that is generalized to the dense condensed phase limit. In particular, scattering from a thin sheet of electric and magnetic dipoles driven above resonance is used to form a fundamental description for negative refraction. Of practical significance, loss and dispersion are implicit in the microscopic model. While naturally occurring negative index materials are unavailable, ferromagnetic and ferroelectric materials provide device design opportunities.Comment: 4 pages, 1 figur

Hydrogen peroxide filled poly(methyl methacrylate) microcapsules: potential oxygen delivery materials

This paper describes the synthesis of H2O2–H2O filled poly(methyl methacrylate) (PMMA) microcapsules as potential candidates for controlled O2 delivery. The microcapsules are prepared by a water-in-oil solvent emulsion and evaporation method. The results of this study describe the effect of process parameters on the characteristics of the microcapsules and on their in vitro performance. The size of the microcapsules, as determined from scanning electron microscopy, ranges from ∼5 to 30 μm and the size distribution is narrow. The microcapsules exhibit an internal morphology with entrapped H2O2–H2O droplets randomly distributed in the PMMA continuous phase. In vitro release studies of 4.5 wt% H2O2-loaded microcapsules show that ∼70% of the H2O2 releases in 24 h. This corresponds to a total O2 production of ∼12 cc/gram of dry microcapsules. Shelf-life studies show that the microcapsules retain ∼84 wt% of the initially loaded H2O2 after nine months storage at 2–8 °C, which is an attractive feature for clinical applications

Chronic nitrite treatment activates adenosine monophosphate-activated protein kinase-endothelial nitric oxide synthase pathway in human aortic endothelial cells

Endothelial dysfunction, with impaired bioavailability and/or bioactivity of the vasoprotective molecule, nitric oxide, appears to be a vital step in the initiation of atherosclerosis. Several studies have shown that dietary nitrate/nitrite can have significant benefits on human cardiovascular homeostasis. Although serum nitrite concentrations can reach micromolar levels, the physiological significance of nitrate/nitrite in normal tissues has not been fully elucidated. We investigated in vitro the chronic effects of nitrate/nitrite on endothelial nitric oxide synthase (eNOS) to determine the potential vasoprotective effects of nitrate/nitrite and the underlying molecular mechanisms. Our results demonstrate the expression of phosphorylated eNOS at Ser1177 and phosphorylated adenosine monophosphate activated protein kinase (AMPK) at Thr172 in human aortic endothelial cells were increased after nitrite treatment. We suggest that nitrite stimulation may enhance eNOS activation, which is due, in part, to AMPK activation. The AMPK–eNOS activation by nitrite may be a possible molecular mechanism underlying the vascular protective effects of dietary nitrate

Tailoring Capture-Recapture Methods to Estimate Registry-Based Case Counts Based on Error-Prone Diagnostic Signals

Surveillance research is of great importance for effective and efficient epidemiological monitoring of case counts and disease prevalence. Taking specific motivation from ongoing efforts to identify recurrent cases based on the Georgia Cancer Registry, we extend recently proposed "anchor stream" sampling design and estimation methodology. Our approach offers a more efficient and defensible alternative to traditional capture-recapture (CRC) methods by leveraging a relatively small random sample of participants whose recurrence status is obtained through a principled application of medical records abstraction. This sample is combined with one or more existing signaling data streams, which may yield data based on arbitrarily non-representative subsets of the full registry population. The key extension developed here accounts for the common problem of false positive or negative diagnostic signals from the existing data stream(s). In particular, we show that the design only requires documentation of positive signals in these non-anchor surveillance streams, and permits valid estimation of the true case count based on an estimable positive predictive value (PPV) parameter. We borrow ideas from the multiple imputation paradigm to provide accompanying standard errors, and develop an adapted Bayesian credible interval approach that yields favorable frequentist coverage properties. We demonstrate the benefits of the proposed methods through simulation studies, and provide a data example targeting estimation of the breast cancer recurrence case count among Metro Atlanta area patients from the Georgia Cancer Registry-based Cancer Recurrence Information and Surveillance Program (CRISP) database

Breast Cancer Screening in Patients With Newly Diagnosed Lung and Colorectal Cancer: A Population-Based Study of Utilization

Purpose—To assess breast cancer screening utilization in Medicare beneficiaries with colorectal and lung cancer versus cancer-free controls. Methods—Female fee-for-service Medicare beneficiaries who were ≥ 67 years old and diagnosed with lung or colorectal cancer between 2000 and 2011 and who reported to a Surveillance, Epidemiology, and End Results (SEER) registry (case group) were followed for 2 years after their diagnoses, unless death, a diagnosis of breast cancer, or the end of 2013 came first. A similar number of cancer-free controls were individually matched to cases by age, race, registry region, and follow-up time. Screening utilization was defined as the percentage of women with ≥1 screening mammogram during follow-up. Results—Overall, 104,164 cases (48% colorectal, 52% lung; 30% advanced cancer) and 104,164 controls were included. Among women with lung or colorectal cancer, 22% underwent ≥ 1 screening mammogram versus 26% of controls (odds ratio [OR] 0.80; 95% confidence interval [CI] 0.78–0.82). Stratified by cancer type, 28% of colorectal cancer cases versus 29% of controls (OR 0.98; 95% CI 0.95–1.01) and 17% of lung cancer cases versus 23% of controls (OR 0.63; 95% CI 0.60–0.65) received ≥ 1 mammogram. When stratified by stage, 8% with advanced cancer versus 18% of controls (OR 0.33; 95% CI 0.31–0.35) and 30% with early-stage cancer versus 30% of controls (OR 1; 95% CI 0.97–1.02) underwent ≥ 1 mammogram. Conclusion—Screening mammography utilization rates are similar between Medicare beneficiaries with early-stage cancer versus controls. Although the majority of patients with advanced-stage cancer appropriately do not pursue screening mammography, a small number (8%) continue with screening