4,448 research outputs found

    Non-Operative Management of a Common Bile Duct Injury Sustained During Cholecystectomy in a Morbidly Obese Patient. (Non-Operative Repair of CBD Injury)

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    A 29 year old morbidly obese patient suffered injury to his common bile duct during cholecystectomy. Subsequent access to the biliary tree was obtained by using a long heavy gauge needle after first opacifying the system with contrast injection through a nasobiliary tube. It is now twenty six months after initial percutaneous biliary drainage placement and eighteen months after removal of all biliary access. The patient is asymptomatic and has normal liver function tests. This technique can be useful in morbidly obese patients who are at increased risk from surgical repair of biliary duct injuries

    Coherence-based approaches for estimating the composition of the seismic wavefield

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    As new techniques exploiting the Earth's ambient seismic noise field are developed and applied, such as for the observation of temporal changes in seismic velocity structure, it is crucial to quantify the precision with which wave‐type measurements can be made. This work uses array data at the Homestake mine in Lead, South Dakota, and an array at Sweetwater, Texas, to consider two aspects that control this precision: the types of seismic wave contributing to the ambient noise field at microseism frequencies and the effect of array geometry. Both are quantified using measurements of wavefield coherence between stations in combination with Wiener filters. We find a strong seasonal change between body‐wave and surface‐wave content. Regarding the inclusion of underground stations, we quantify the lower limit to which the ambient noise field can be characterized and reproduced; the applications of the Wiener filters are about 4 times more successful in reproducing ambient noise waveforms when underground stations are included in the array, resulting in predictions of seismic time series with less than a 1% residual, and are ultimately limited by the geometry and aperture of the array, as well as by temporal variations in the seismic field. We discuss the implications of these results for the geophysics community performing ambient seismic noise studies, as well as for the cancellation of seismic Newtonian gravity noise in ground‐based, sub‐Hertz, gravitational‐wave detectors

    Unfolding Rates for the Diffusion-Collision Model

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    In the diffusion-collision model, the unfolding rates are given by the likelihood of secondary structural cluster dissociation. In this work, we introduce an unfolding rate calculation for proteins whose secondary structural elements are α\alpha-helices, modeled from thermal escape over a barrier which arises from the free energy in buried hydrophobic residues. Our results are in good agreement with currently accepted values for the attempt rate.Comment: Shorter version of cond-mat/0011024 accepted for publication in PR

    [Phe4]somatostatin: a potent, selective inhibitor of growth hormone release.

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    [Phe4]Somatostatin was twice as active as somatostatin (SS) in suppressing rat growth hormone release in vitro but had only weak activity toward inhibition of insulin and glucagon release in vivo. The ability of this analogue to inhibit growth hormone release more actively than SS was confirmed in vivo by two separately designed bioassays. Further structure/activity studies of position 4 were carried out with [Glu4]SS, [Thr4]SS, and des-Lys4-SS, all of which had negligible inhibiting activity in the pituitary and pancreas. In this context the strikingly selective activity of [Phe4]SS suggests a fundamental difference in the SS receptors of pituitary and pancreas and the normal side-chain basicity of position 4 appears to be more important for action in pancreas than in pituitary. [Phe4]SS has properties that may be useful in the development of agents for the treatment of acromegaly or other disorders associated with increased growth hormone levels

    The Relationship Between CO2 Levels and CO2 Related Symptoms Reported on the ISS

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    Medical Operations, Toxicology, and the Lifetime Surveillance of Astronaut Health collaborated to assess the association of CO2 levels on board the International Space Station and USOS crew reported symptoms inflight, i.e. headache and vision changes. Private Medical Conference (PMC) documents and the weekly Space Medicine Operations Team (SMOT) Notes were used to provide a robust data set of inflight medical events. All events and nonevents were documented independent of CO2 levels and other potential contributors. Average (arithmetic mean) and single point maximum ppCO2 was calculated for the 24 hours and 7 days prior to the PMC or SMOT date and time provided by LSAH. Observations falling within the first 7 days of flight (147) were removed from the datasets analyzed to avoid confounding with Space Adaptation Syndrome. The final analysis was based on 1716 observations. For headache, 46 headaches were observed. CO2 level, age at launch, time inflight, and data source were all significantly associated with headache. In particular, for each 1 mmHg increase in CO2, the odds of a crewmember reporting a headache doubled. For vision changes, 29 reports of vision changes were observed. These observations were not found to be statistically associated with CO2 levels as analyzed. While the incidence of headache has was not high (~3%), headaches may be an indicator of underlying increases in intracranial pressure, which may result likely from the synergy between CO2induced cerebral vasodilatation and decreased venous drainage in microgravity. Vision changes were inconsistently reported and as a result did not align appropriately with the CO2 levels. Further analysis is needed. Our results support ongoing efforts to lower the CO2 exposure limits in spacecraft

    Missing Data and Multiple Imputation: An Unbiased Approach

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    The default method of dealing with missing data in statistical analyses is to only use the complete observations (complete case analysis), which can lead to unexpected bias when data do not meet the assumption of missing completely at random (MCAR). For the assumption of MCAR to be met, missingness cannot be related to either the observed or unobserved variables. A less stringent assumption, missing at random (MAR), requires that missingness not be associated with the value of the missing variable itself, but can be associated with the other observed variables. When data are truly MAR as opposed to MCAR, the default complete case analysis method can lead to biased results. There are statistical options available to adjust for data that are MAR, including multiple imputation (MI) which is consistent and efficient at estimating effects. Multiple imputation uses informing variables to determine statistical distributions for each piece of missing data. Then multiple datasets are created by randomly drawing on the distributions for each piece of missing data. Since MI is efficient, only a limited number, usually less than 20, of imputed datasets are required to get stable estimates. Each imputed dataset is analyzed using standard statistical techniques, and then results are combined to get overall estimates of effect. A simulation study will be demonstrated to show the results of using the default complete case analysis, and MI in a linear regression of MCAR and MAR simulated data. Further, MI was successfully applied to the association study of CO2 levels and headaches when initial analysis showed there may be an underlying association between missing CO2 levels and reported headaches. Through MI, we were able to show that there is a strong association between average CO2 levels and the risk of headaches. Each unit increase in CO2 (mmHg) resulted in a doubling in the odds of reported headaches

    Sibling comparisons elucidate the associations between educational attainment polygenic scores and alcohol, nicotine and cannabis.

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    Background and aimsThe associations between low educational attainment and substance use disorders (SUDs) may be related to a common genetic vulnerability. We aimed to elucidate the associations between polygenic scores for educational attainment and clinical criterion counts for three SUDs (alcohol, nicotine and cannabis).DesignPolygenic association and sibling comparison methods. The latter strengthens inferences in observational research by controlling for confounding factors that differ between families.SettingSix sites in the United States.ParticipantsEuropean ancestry participants aged 25 years and older from the Collaborative Study on the Genetics of Alcoholism (COGA). Polygenic association analyses included 5582 (54% female) participants. Sibling comparisons included 3098 (52% female) participants from 1226 sibling groups nested within the overall sample.MeasurementsOutcomes included criterion counts for DSM-5 alcohol use disorder (AUDSX), Fagerström nicotine dependence (NDSX) and DSM-5 cannabis use disorder (CUDSX). We derived polygenic scores for educational attainment (EduYears-GPS) using summary statistics from a large (> 1 million) genome-wide association study of educational attainment.FindingsIn polygenic association analyses, higher EduYears-GPS predicted lower AUDSX, NDSX and CUDSX [P < 0.01, effect sizes (R2 ) ranging from 0.30 to 1.84%]. These effects were robust in sibling comparisons, where sibling differences in EduYears-GPS predicted all three SUDs (P < 0.05, R2 0.13-0.20%).ConclusionsIndividuals who carry more alleles associated with educational attainment tend to meet fewer clinical criteria for alcohol, nicotine and cannabis use disorders, and these effects are robust to rigorous controls for potentially confounding factors that differ between families (e.g. socio-economic status, urban-rural residency and parental education)

    Challenges in Evaluating Relationships Between Quantitative Data (Carbon Dioxide) and Qualitative Data (Self-Reported Visual Changes)

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    Understanding the nuances in clinical data is critical in developing a successful data analysis plan. Carbon dioxide (CO2) data are collected on board the International Space Station (ISS) in a continuous stream. Clinical data on ISS are primarily collected via conversations between individual crewmembers and NASA Flight Surgeons during weekly Private Medical Conferences (PMC). Law, et.al, 20141 demonstrated a statistically significant association between weekly average CO2 levels on ISS and self-reported headaches over the reporting period from March 14, 2001 to May 31, 2012. The purpose of this analysis is to describe the evaluation of a possible association between visual changes and CO2 levels on ISS and to discuss challenges in developing an appropriate analysis plan. METHODS & PRELIMINARY RESULTS: A first analysis was conducted following the same study design as the published work on CO2 and self-reported headaches1; substituting self-reported changes in visual acuity in place of self-reported headaches. The analysis demonstrated no statistically significant association between visual impairment characterized by vision symptoms self-reported during PMCs and ISS average CO2 levels over ISS missions. Closer review of the PMC records showed that vision outcomes are not well-documented in terms of clinical severity, timing of onset, or timing of resolution, perhaps due to the incipient nature of vision changes. Vision has been monitored in ISS crewmembers, pre- and post-flight, using standard optometry evaluations. In-flight visual assessments were limited early in the ISS program, primarily consisting of self-perceived changes reported by crewmembers. Recently, on-orbit capabilities have greatly improved. Vision data ranges from self-reported post-flight changes in visual acuity, pre- to postflight changes identified during fundoscopic examination, and in-flight progression measured by advanced on-orbit clinical imaging capabilities at predetermined testing intervals. In contrast, CO2 data are recorded in a continuous stream over time; however, for the initial analysis this data was categorized into weekly averages
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