Free-living inferential modeling of blood glucose level using only noninvasive inputs

The goal of this work is to present a causation modeling methodology with the ability to accurately infer blood glucose levels using a large set of highly correlated noninvasive input variables over an extended period of time. These models can provide insight to improve glucose monitoring, and glucose regulation through advanced model-based control technologies. The efficacy of this approach is demonstrated using real data from a type 2 diabetic (T2D) subject collected under free-living conditions over a period of 25 consecutive days. The model was identified and tested using eleven variables that included three food variables as well as several activity and stress variables. The model was trained using 20 days of data and validated using 5 days of data. This gave a fitted correlation coefficient of 0.70 and an average absolute error (AAE) (i.e., the average of the absolute values for the measured glucose concentration minus modeled glucose concentration) of 13.3 mg/dL for the validation data. This AAE result was significantly better than the subject’s personal glucose meter AAE of 15.3 mg/dL for replicated measurements.     

Mode conversion in rectangular-core optical fibers

Mode conversion from the fundamental to a higher-order mode in a rectangular-core optical fiber is accomplished by applying pressure with the edge of a flat plate. Modal analysis of the near and far field images of the fiber's transmitted beam determines the purity of the converted mode. Mode conversion reaching 75% of the targeted higher-order mode is achieved using this technique. Conversion from a higher-order mode back to the fundamental mode is also demonstrated with comparable efficiency. Propagation of a higher-order mode in a rectangular-core fiber allows for better thermal management and bend-loss immunity than conventional circular-core fibers, extending the power-handling capabilities of optical fibers.     

Screening and treatment of distress.

The screening and treatment of psychological distress is an increasingly important aspect of providing comprehensive care to medical patients. The importance of this within oncology was illustrated most recently by the publication of the National Comprehensive Cancer Network's Distress Guidelines (Holland, 1997). Given that measures of general distress assess for symptoms across diagnostic categories, it is not unusual to have a combination of symptoms indicating distress without meeting diagnostic criteria (Derogatis, Morrow, & Petting, 1983). We would suggest that general measures of distress and psychiatric diagnoses not assessed by Coyne et al. (e.g., somatoform or adjustment disorders) may reflect better the distress (health anxiety and somatic preoccupation) of women at increased risk for cancer and be more informative than assessing selectively for mood disorders, anxiety disorders, and alcohol abuse. The authors additionally concluded that if there is not psychiatric disorder, then there is no impairment. We believe it premature at best to reify the DSM in a nonpsychiatric population. Distress exists on a continuum. To wait until patients meet psychiatric criteria before they are seen is not in the spirit of comprehensive medical care. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Do citations and impact factors relate to the real numbers in publications? A case study of citation rates, impact, and effect sizes in ecology and evolutionary biology

Metrics of success or impact in academia may do more harm than good. To explore the value of citations, the reported efficacy of treatments in ecology and evolution from close to 1,500 publications was examined. If citation behavior is rationale, i.e. studies that successfully applied a treatment and detected greater biological effects are cited more frequently, then we predict that larger effect sizes increases study relative citation rates. This prediction was not supported. Citations are likely thus a poor proxy for the quantitative merit of a given treatment in ecology and evolutionary biology—unlike evidence-based medicine wherein the success of a drug or treatment on human health is one of the critical attributes. Impact factor of the journal is a broader metric, as one would expect, but it also unrelated to the mean effect sizes for the respective populations of publications. The interpretation by the authors of the treatment effects within each study differed depending on whether the hypothesis was supported or rejected. Significantly larger effect sizes were associated with rejection of a hypothesis. This suggests that only the most rigorous studies reporting negative results are published or that authors set a higher burden of proof in rejecting a hypothesis. The former is likely true to a major extent since only 29 % of the studies rejected the hypotheses tested. These findings indicate that the use of citations to identify important papers in this specific discipline—at least in terms of designing a new experiment or contrasting treatments—is of limited value.     

Spatial and temporal variation in indicator microbe sampling is influential in beach management decisions

Fecal indicator microbes, such as enterococci, are often used to assess potential health risks caused by pathogens at recreational beaches. Microbe levels often vary based on collection time and sampling location. The primary goal of this study was to assess how spatial and temporal variations in sample collection, which are driven by environmental parameters, impact enterococci measurements and beach management decisions. A secondary goal was to assess whether enterococci levels can be predictive of the presence of Staphylococcus aureus, a skin pathogen. Over a ten-day period, hydrometeorologic data, hydrodynamic data, bather densities, enterococci levels, and S. aureus levels including methicillin-resistant S. aureus (MRSA) were measured in both water and sand. Samples were collected hourly for both water and sediment at knee-depth, and every 6 h for water at waist-depth, supratidal sand, intertidal sand, and waterline sand. Results showed that solar radiation, tides, and rainfall events were major environmental factors that impacted enterococci levels. S. aureus levels were associated with bathing load, but did not correlate with enterococci levels or any other measured parameters. The results imply that frequencies of advisories depend heavily upon sample collection policies due to spatial and temporal variation of enterococci levels in response to environmental parameters. Thus, sampling at different times of the day and at different depths can significantly impact beach management decisions. Additionally, the lack of correlation between S. aureus and enterococci suggests that use of fecal indicators may not accurately assess risk for some pathogens.     

Housing quality and resilience in New Zealand

There is extensive research on the negative health impacts of poor housing quality. However, little is known about the potential health benefits of high-quality housing in poor neighbourhoods. Neighbourhoods with unexpectedly good health outcomes despite high levels of deprivation have been deemed resilient places and housing quality in these areas may be a contributor to this resilience. This study aimed to evaluate whether an indicator of neighbourhood housing quality was associated with a previously quantified resilience index (RINZ) in New Zealand. It was found that areas with high housing quality tended to have higher median income, greater proportions of partnered people and shorter-term residents, and very low proportions of Māori. A positive association was found between housing quality and resilience, after adjustment for deprivation. There was no indication of differences by heterogeneity in housing quality within the aggregate unit of analysis. These findings pose the hypothesis that improving housing quality in similarly deprived areas that have poor health outcomes could potentially boost health. To extend this understanding, further development of a more sophisticated housing quality indicator is recommended.     

Nanoparticle Accumulation in Angiogenic Tissues: Towards Predictable Pharmacokinetics

Nanoparticles are increasingly used in medical applications such as drug delivery, imaging, and biodiagnostics, particularly for cancer. The design of nanoparticles for tumor delivery has been largely empirical, owing to a lack of quantitative data on angiogenic tissue sequestration. Using fluorescence correlation spectroscopy, the deposition rate constants of nanoparticles into angiogenic blood vessel tissue are determined. It is shown that deposition is dependent on surface charge. Moreover, the size dependency strongly suggests that nanoparticles are taken up by a passive mechanism that depends largely on geometry. These findings imply that it is possible to tune nanoparticle pharmacokinetics simply by adjusting nanoparticle size.     

Multifractal signatures of infectious diseases

Incidence of infection time-series data for the childhood diseases measles, chicken pox, rubella and whooping cough are described in the language of multifractals. We explore the potential of using the wavelet transform maximum modulus (WTMM) method to characterize the multiscale structure of the observed time series and of simulated data generated by the stochastic susceptible-exposed-infectious-recovered (SEIR) epidemic model. The singularity spectra of the observed time series suggest that each disease is characterized by a unique multifractal signature, which distinguishes that particular disease from the others. The wavelet scaling functions confirm that the time series of measles, rubella and whooping cough are clearly multifractal, while chicken pox has a more monofractal structure in time. The stochastic SEIR epidemic model is unable to reproduce the qualitative singularity structure of the reported incidence data: it is too smooth and does not appear to have a multifractal singularity structure. The precise reasons for the failure of the SEIR epidemic model to reproduce the correct multiscale structure of the reported incidence data remain unclear.