A Novel Method for Reducing the Effect of Tonic Muscle Activity on the Gamma Band of the Scalp EEG

Neural oscillations in the gamma band are of increasing interest, but separating them from myogenic electrical activity has proved difficult. A novel algorithm has been developed to reduce the effect of tonic scalp and neck muscle activity on the gamma band of the EEG. This uses mathematical modelling to fit individual muscle spikes and then subtracts them from the data. The method was applied to the detection of motor associated gamma in two separate groups of eight subjects using different sampling rates. A reproducible increase in high gamma (65–85 Hz) magnitude occurred immediately after the motor action in the left central area (p = 0.02 and p = 0.0002 for the two cohorts with individually optimized algorithm parameters, compared to p = 0.03 and p = 0.16 before correction). Whilst the magnitude of this event-related gamma synchronisation was not reduced by the application of the EMG reduction algorithm, the baseline left central gamma magnitude was significantly reduced by an average of 23 % with a faster sampling rate (p < 0.05). In comparison, at left and right temporo-parietal locations the gamma amplitude was reduced by 60 and 54 % respectively (p < 0.05). The reduction of EMG contamination by fitting and subtraction of individual spikes shows promise as a method of improving the signal to noise ratio of high frequency neural oscillations in scalp EEG

Open-front Systems

Dave Serfling and his family live in Preston, Minnesota, which is just north across the border from Decorah. Dave graduated from ISU in 1981 in farm operations. Serflings have a 50 sow farrow-to-finish operation and 80 cows they feed out. They also have sheep, and they own about 350 acres. They love Iowa so much, Dave\u27s wife even works in Iowa, so thanks for helping the economy. (laughter) Steve Williams and his wife live in Villisca, in Page County. Steve is a 1988 ISU business graduate. He has a total livestock operation with beef and a farrow-tofeeder pig operation. He feeds out a few. There are some interesting family ties and partnerships in Page County, and now his operation\u27s up to about 300 sows in a very productive and unique arrangement, which we\u27ll hear more about. Greg Vogel represents the ISU AG 450 Farm, which is located southwest of Ames , about a mile. This is actually a student-managed farm, and many of you are familiar with that concept that the students really manage it, for better or for worse. And they suffer all the advantages and perils of pure agriculture. Greg is the farm operator. He\u27s also an ISU grad (ag business, 1978) and finished a master\u27s in ag business in 1994. The farm is about 950 acres, and they have 200 sows out there. They run both outdoor and confmement operations. Last we\u27ll hear from my good friend, Dick Thompson. Dick and Sharon, of course, farm in Boone County. Dick and Sharon recently were recognized as the 1996 Farm Agricultural Leaders of The Year by the Des Moines Register, which was a tremendous honor for them. There farm is a little under 400 acres, they have been the driving force behind and the inspiration behind Practical Farmers of Iowa. Dick and Sharon have served as mentors for many, many farm families, not only in Iowa but nationwide. I know Dick and Sharon now have a cow-calf operation, and with their son, Rex, they have some of the facilities we\u27re talking about today, and they\u27re trying some new things in agriculture, so we\u27re pleased to have Dick here

Discovery of Novel Materials with Broad Resistance to Bacterial Attachment Using Combinatorial Polymer Microarrays

A new class of bacteria-attachment-resistant materials is discovered using a multi-generation polymer microarray methodology that reduces bacterial attachment by up to 99.3% compared with a leading commercially available silver hydrogel anti-bacterial material. The coverage of three bacterial species, Pseudomonas aeruginosa, Staphylococcus aureus, and uropathogenic Escherichia coli is assessed.National Institutes of Health (U.S.) (Grant R01 DE016516

CD4 intragenic SNPs associate with HIV-2 plasma viral load and CD4 count in a community-based study from Guinea-Bissau, West Africa.

OBJECTIVES: The human genetics of HIV-2 infection and disease progression is understudied. Therefore, we studied the effect of variation in 2 genes that encode products critical to HIV pathogenesis and disease progression: CD4 and CD209. DESIGN: This cross-sectional study consisted of 143 HIV-2, 30 HIV-1 + HIV-2 and 29 HIV-1-infected subjects and 194 uninfected controls recruited from rural Guinea-Bissau. METHODS: We genotyped 14 CD4 and 4 CD209 single nucleotide polymorphisms (SNPs) that were tested for association with HIV infection, HIV-2 plasma viral load (high vs. low), and CD4 T-cell count (high vs. low). RESULTS: The most significant association was between a CD4 haplotype rs11575097-rs10849523 and high viral load [odds ratio (OR): = 2.37, 95% confidence interval (CI): 1.35 to 4.19, P = 0.001, corrected for multiple testing], suggesting increased genetic susceptibility to HIV-2 disease progression for individuals carrying the high-risk haplotype. Significant associations were also observed at a CD4 SNP (rs2255301) with HIV-2 infection (OR: = 2.36, 95% CI: 1.19 to 4.65, P = 0.01) and any HIV infection (OR: = 2.50, 95% CI: 1.34 to 4.69, P = 0.004). CONCLUSIONS: Our results support a role of CD4 polymorphisms in HIV-2 infection, in agreement with recent data showing that CD4 gene variants increase risk to HIV-1 in Kenyan female sex workers. These findings indicate at least some commonality in HIV-1 and HIV-2 susceptibility

Estimating multivariate similarity between neuroimaging datasets with sparse canonical correlation analysis:an application to perfusion imaging

An increasing number of neuroimaging studies are based on either combining more than one data modality (inter-modal) or combining more than one measurement from the same modality (intra-modal). To date, most intra-modal studies using multivariate statistics have focused on differences between datasets, for instance relying on classifiers to differentiate between effects in the data. However, to fully characterize these effects, multivariate methods able to measure similarities between datasets are needed. One classical technique for estimating the relationship between two datasets is canonical correlation analysis (CCA). However, in the context of high-dimensional data the application of CCA is extremely challenging. A recent extension of CCA, sparse CCA (SCCA), overcomes this limitation, by regularizing the model parameters while yielding a sparse solution. In this work, we modify SCCA with the aim of facilitating its application to high-dimensional neuroimaging data and finding meaningful multivariate image-to-image correspondences in intra-modal studies. In particular, we show how the optimal subset of variables can be estimated independently and we look at the information encoded in more than one set of SCCA transformations. We illustrate our framework using Arterial Spin Labeling data to investigate multivariate similarities between the effects of two antipsychotic drugs on cerebral blood flow

A Preliminary Observational Search for Circumbinary Disks Around Cataclysmic Variables

Circumbinary (CB) disks have been proposed as a mechanism to extract orbital angular momentum from cataclysmic variables (CVs) during their evolution. As proposed by Taam & Spruit, these disks extend outwards to several a.u. and should be detected observationally via their infrared flux or by absorption lines in the ultraviolet spectra of the CV. We have made use of archival HST/STIS spectra as well as our own near-IR imaging to search for observational evidence of such CB disks in seven CVs. Based on the null result, we place an upper limit on the column density of the disk of N_H~10^17 cm^-2.Comment: accepted for publication in the Astronomical Journal (July 2004

How to make epidemiological training infectious

CITATION: Bellan, S. E. et al. 2012. How to make epidemiological training infectious. PLoS Biology, 10(4): e1001295, doi:10.1371/journal.pbio.1001295.The original publication is available at http://journals.plos.org/plosbiologyModern infectious disease epidemiology builds on two independently developed fields: classical epidemiology and dynamical epidemiology. Over the past decade, integration of the two fields has increased in research practice, but training options within the fields remain distinct with few opportunities for integration in the classroom. The annual Clinic on the Meaningful Modeling of Epidemiological Data (MMED) at the African Institute for Mathematical Sciences has begun to address this gap. MMED offers participants exposure to a broad range of concepts and techniques from both epidemiological traditions. During MMED 2010 we developed a pedagogical approach that bridges the traditional distinction between classical and dynamical epidemiology and can be used at multiple educational levels, from high school to graduate level courses. The approach is hands-on, consisting of a real-time simulation of a stochastic outbreak in course participants, including realistic data reporting, followed by a variety of mathematical and statistical analyses, stemming from both epidemiological traditions. During the exercise, dynamical epidemiologists developed empirical skills such as study design and learned concepts of bias while classical epidemiologists were trained in systems thinking and began to understand epidemics as dynamic nonlinear processes. We believe this type of integrated educational tool will prove extremely valuable in the training of future infectious disease epidemiologists. We also believe that such interdisciplinary training will be critical for local capacity building in analytical epidemiology as Africa continues to produce new cohorts of well-trained mathematicians, statisticians, and scientists. And because the lessons draw on skills and concepts from many fields in biology—from pathogen biology, evolutionary dynamics of host–pathogen interactions, and the ecology of infectious disease to bioinformatics, computational biology, and statistics—this exercise can be incorporated into a broad array of life sciences courses.http://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.1001295Publisher's versio

Association of cannabis with glutamatergic levels in patients with early psychosis: Evidence for altered volume striatal glutamate relationships in patients with a history of cannabis use in early psychosis

The associative striatum, an established substrate in psychosis, receives widespread glutamatergic projections. We sought to see if glutamatergic indices are altered between early psychosis patients with and without a history of cannabis use and characterise the relationship to grey matter. 92 participants were scanned: Early Psychosis with a history of cannabis use (EPC\u2009=\u200929); Early Psychosis with minimal cannabis use (EPMC\u2009=\u200925); Controls with a history of cannabis use (HCC\u2009=\u200916) and Controls with minimal use (HCMC\u2009=\u200922). Whole brain T1 weighted MR images and localised proton MR spectra were acquired from head of caudate, anterior cingulate and hippocampus. We examined relationships in regions with known high cannabinoid 1 receptor (CB1R) expression (grey matter, cortex, hippocampus, amygdala) and low expression (white matter, ventricles, brainstem) to caudate Glutamine+Glutamate (Glx). Patients were well matched in symptoms, function and medication. There was no significant group difference in Glx in any region. In EPC grey matter volume explained 31.9% of the variance of caudate Glx (p\u2009=\u20090.003) and amygdala volume explained 36.9% (p\u2009=\u20090.001) of caudate Glx. There was no significant relationship in EPMC. The EPC vs EPMC interaction was significant (p\u2009=\u20090.042). There was no such relationship in control regions. These results are the first to demonstrate association of grey matter volume and striatal glutamate in the EPC group. This may suggest a history of cannabis use leads to a conformational change in distal CB1 rich grey matter regions to influence striatal glutamatergic levels or that such connectivity predisposes to heavy cannabis use

Development and implementation of a nurse-based remote patient monitoring program for ambulatory disease management

IntroductionNumerous factors are intersecting in healthcare resulting in an increased focus on new tools and methods for managing care in patients' homes. Remote patient monitoring (RPM) is an option to provide care at home and maintain a connection between patients and providers to address ongoing medical issues.MethodsMayo Clinic developed a nurse-led RPM program for disease and post-procedural management to improve patient experience, clinical outcomes, and reduce health care utilization by more directly engaging patients in their health care. Enrolled patients are sent a technology package that includes a digital tablet and peripheral devices for the collection of symptoms and vital signs. The data are transmitted from to a hub integrated within the electronic health record. Care team members coordinate patient needs, respond to vital sign alerts, and utilize the data to inform and provide individualized patient assessment, patient education, medication management, goal setting, and clinical care planning.ResultsSince its inception, the RPM program has supported nearly 22,000 patients across 17 programs. Patients who engaged in the COVID-19 RPM program experienced a significantly lower rate of 30-day, all-cause hospitalization (13.7% vs. 18.0%, P = 0.01), prolonged hospitalization &gt;7 days (3.5% vs. 6.7%, P = 0.001), intensive care unit (ICU) admission (2.3% vs. 4.2%, P = 0.01), and mortality (0.5% vs. 1.7%, P = 0.01) when compared with those enrolled and unengaged with the technology. Patients with chronic conditions who were monitored with RPM upon hospital discharge were significantly less likely to experience 30-day readmissions (18.2% vs. 23.7%, P = 0.03) compared with those unmonitored. Ninety-five percent of patients strongly agreed or agreed they were likely to recommend RPM to a friend or family member.ConclusionsThe Mayo Clinic RPM program has generated positive clinical outcomes and is satisfying for patients. As technology advances, there are greater opportunities to enhance this clinical care model and it should be extended and expanded to support patients across a broader spectrum of needs. This report can serve as a framework for health care organizations to implement and enhance their RPM programs in addition to identifying areas for further evolution and exploration in developing RPM programs of the future