An Educational Program for Primary Nursing

To increase continuity of care and reduce clinical errors, management in an inpatient rehabilitation unit of a private, nonprofit hospital chose to change the care delivery model to primary nursing; unit nurses had inadequate understanding of primary nursing, creating a gap in practice. The purpose of this project was to develop an educational program on primary nursing to address the question of how education on primary nursing would impact the understanding of the model among the nurses in the patient rehabilitation unit of the project site. Rogers\u27s diffusion of innovation model provided a framework for developing the educational program. The educational program was supported by research and literature in addition to input from a project team comprising five participants, the unit manager, associate manager, and three charge nurses from the unit. The project evaluation process included an evaluation questionnaire that included 10 questions using a Likert-type scale. All team members scored outcomes as strongly agree and agree. Descriptive statistics indicated that all team members agreed the project goal was appropriate, the project objective was met, and that leadership was demonstrated throughout the project process. The implications of these findings for positive social change include improved nursing competencies and capabilities, tailored care and continuity to care, as well as improved organizational outcomes

Electron microscopic measurement of the size of the optical focus in laser scanning microscopy

We describe a method for measuring the lateral focal spot size of a multiphoton laser scanning microscope (LSM) with unprecedented accuracy. A specimen consisting of an aluminum film deposited on a glass coverslip was brought into focus in a LSM and the laser intensity was then increased enough to perform nanoablation of the metal film. This process leaves a permanent trace of the raster path usually taken by the beam during the acquisition of an optical image. A scanning electron microscope (SEM) was then used to determine the nanoablated line width to high accuracy, from which the lateral spot size and hence resolution of the LSM can be determined. To demonstrate our method, we performed analysis of a multiphoton LSM at various infrared wavelengths, and we report measurements of optical lateral spot size with an accuracy of 20 nm, limited only by the resolution of the SEM

Femtosecond synchronously in-well pumped vertical-external-cavity surface-emitting laser

We demonstrate the first synchronously in-well pumped vertical-external-cavity surface-emitting laser (VECSEL). Depending on the cavity mismatch, laser pulses with a duration from 1 ps to 7 ps at a repetition rate of 76 MHz were generated directly from the laser at 860 nm. The application of extra-cavity pulse compression further shortened the pulse to a duration of 210 fs providing a peak power of 226 W

redbiom: a Rapid Sample Discovery and Feature Characterization System.

Meta-analyses at the whole-community level have been important in microbiome studies, revealing profound features that structure Earth's microbial communities, such as the unique differentiation of microbes from the mammalian gut relative to free-living microbial communities, the separation of microbiomes in saline and nonsaline environments, and the role of pH in driving soil microbial compositions. However, our ability to identify the specific features of a microbiome that differentiate these community-level patterns have lagged behind, especially as ever-cheaper DNA sequencing has yielded increasingly large data sets. One critical gap is the ability to search for samples that contain specific features (for example, sub-operational taxonomic units [sOTUs] identified by high-resolution statistical methods for removing amplicon sequencing errors). Here we introduce redbiom, a microbiome caching layer, which allows users to rapidly query samples that contain a given feature, retrieve sample data and metadata, and search for samples that match specified metadata values or ranges (e.g., all samples with a pH of >7), implemented using an in-memory NoSQL database called Redis. By default, redbiom allows public anonymous sample access for over 100,000 publicly available samples in the Qiita database. At over 100,000 samples, the caching server requires only 35 GB of resident memory. We highlight how redbiom enables a new type of characterization of microbiome samples and provide tutorials for using redbiom with QIIME 2. redbiom is open source under the BSD license, hosted on GitHub, and can be deployed independently of Qiita to enable search of proprietary or clinically restricted microbiome databases.IMPORTANCE Although analyses that combine many microbiomes at the whole-community level have become routine, searching rapidly for microbiomes that contain a particular sequence has remained difficult. The software we present here, redbiom, dramatically accelerates this process, allowing samples that contain microbiome features to be rapidly identified. This is especially useful when taxonomic annotation is limited, allowing users to identify environments in which unannotated microbes of interest were previously observed. This approach also allows environmental or clinical factors that correlate with specific features, or vice versa, to be identified rapidly, even at a scale of billions of sequences in hundreds of thousands of samples. The software is integrated with existing analysis tools to enable fast, large-scale microbiome searches and discovery of new microbiome relationships

The Iowa Homemaker vol.39, no.3

Dean LeBaron, Diane Rasmussen, page 5 Your Faculty’s Favorite Home-Work, Jill Gaylord, page 6 Why the Slouch?, Jane Gibson, page 8 My Trip Around the World, Jane Gibson, page 9 Off-Campus Commentary, Elizabeth McDonald, page 10 How Do You Rate As A Roomie?, Gail Devens, page 11 What’s Going On, page 1

RUNX-mediated growth arrest and senescence are attenuated by diverse mechanisms in cells expressing RUNX1 fusion oncoproteins

RUNX gene over-expression inhibits growth of primary cells but transforms cells with tumor suppressor defects, consistent with reported associations with tumor progression. In contrast, chromosomal translocations involving RUNX1 are detectable in utero, suggesting an initiating role in leukemias. How do cells expressing RUNX1 fusion oncoproteins evade RUNX-mediated growth suppression? Previous studies showed that the TEL-RUNX1 fusion from t(12;21) B-ALLs is unable to induce senescence-like growth arrest (SLGA) in primary fibroblasts while potent activity is displayed by the RUNX1-ETO fusion found in t(8;21) AMLs. We now show that SLGA potential is suppressed in TEL-RUNX1 but reactivated by deletion of the TEL HLH domain or mutation of a key residue (K99R). Attenuation of SLGA activity is also a feature of RUNX1-ETO9a, a minor product of t(8;21) translocations with increased leukemogenicity. Finally, while RUNX1-ETO induces SLGA it also drives a potent senescence-associated secretory phenotype (SASP), and promotes the immortalisation of rare cells that escape SLGA. Moreover, the RUNX1-ETO SASP is not strictly linked to growth arrest as it is largely suppressed by RUNX1 and partially activated by RUNX1-ETO9a. These findings underline the heterogeneous nature of premature senescence and the multiple mechanisms by which this failsafe process is subverted in cells expressing RUNX1 oncoproteins

Exploring wind-driving dust species in cool luminous giants I. Basic criteria and dynamical models of M-type AGB stars

This work is part of an ongoing effort aiming at identifying the actual wind-drivers among the dust species observed in circumstellar envelopes. In particular, we focus on the interplay between a strong stellar radiation field and the dust formation process. To identify critical properties of potential wind-driving dust species we use detailed radiation-hydrodynamical models which include a parameterized dust description, complemented by simple analytical estimates to help with the physical interpretation of the numerical results. The adopted dust description is constructed to mimic different chemical and optical dust properties in order to systematically study the effects of a realistic radiation field on the second stage of the mass loss mechanism. We see distinct trends in which combinations of optical and chemical dust properties are needed to trigger an outflow. Dust species with a low condensation temperature and a NIR absorption coefficient that decreases strongly with wavelength will not condense close enough to the stellar surface to be considered as potential wind-drivers. Our models confirm that metallic iron and Fe-bearing silicates are not viable as wind-drivers due to their near-infrared optical properties and resulting large condensation distances. TiO2 is also excluded as a wind-driver due to the low abundance of Ti. Other species, such a SiO2 and Al2O3, are less clear-cut cases due to uncertainties in the optical and chemical data and further work is needed. A strong candidate is Mg2SiO4 with grain sizes of 0.1-1 micron, where scattering contributes significantly to the radiative acceleration, as suggested by earlier theoretical work and supported by recent observations.Comment: 15 pages, 12 figure

Extreme Dysbiosis of the Microbiome in Critical Illness.

Critical illness is hypothesized to associate with loss of "health-promoting" commensal microbes and overgrowth of pathogenic bacteria (dysbiosis). This dysbiosis is believed to increase susceptibility to nosocomial infections, sepsis, and organ failure. A trial with prospective monitoring of the intensive care unit (ICU) patient microbiome using culture-independent techniques to confirm and characterize this dysbiosis is thus urgently needed. Characterizing ICU patient microbiome changes may provide first steps toward the development of diagnostic and therapeutic interventions using microbiome signatures. To characterize the ICU patient microbiome, we collected fecal, oral, and skin samples from 115 mixed ICU patients across four centers in the United States and Canada. Samples were collected at two time points: within 48 h of ICU admission, and at ICU discharge or on ICU day 10. Sample collection and processing were performed according to Earth Microbiome Project protocols. We applied SourceTracker to assess the source composition of ICU patient samples by using Qiita, including samples from the American Gut Project (AGP), mammalian corpse decomposition samples, childhood (Global Gut study), and house surfaces. Our results demonstrate that critical illness leads to significant and rapid dysbiosis. Many taxons significantly depleted from ICU patients versus AGP healthy controls are key "health-promoting" organisms, and overgrowth of known pathogens was frequent. Source compositions of ICU patient samples are largely uncharacteristic of the expected community type. Between time points and within a patient, the source composition changed dramatically. Our initial results show great promise for microbiome signatures as diagnostic markers and guides to therapeutic interventions in the ICU to repopulate the normal, "health-promoting" microbiome and thereby improve patient outcomes. IMPORTANCE Critical illness may be associated with the loss of normal, "health promoting" bacteria, allowing overgrowth of disease-promoting pathogenic bacteria (dysbiosis), which, in turn, makes patients susceptible to hospital-acquired infections, sepsis, and organ failure. This has significant world health implications, because sepsis is becoming a leading cause of death worldwide, and hospital-acquired infections contribute to significant illness and increased costs. Thus, a trial that monitors the ICU patient microbiome to confirm and characterize this hypothesis is urgently needed. Our study analyzed the microbiomes of 115 critically ill subjects and demonstrated rapid dysbiosis from unexpected environmental sources after ICU admission. These data may provide the first steps toward defining targeted therapies that correct potentially "illness-promoting" dysbiosis with probiotics or with targeted, multimicrobe synthetic "stool pills" that restore a healthy microbiome in the ICU setting to improve patient outcomes

redbiom: a Rapid Sample Discovery and Feature Characterization System

Meta-analyses at the whole-community level have been important in microbiome studies, revealing profound features that structure Earth’s microbial communities, such as the unique differentiation of microbes from the mammalian gut relative to free-living microbial communities, the separation of microbiomes in saline and nonsaline environments, and the role of pH in driving soil microbial compositions. However, our ability to identify the specific features of a microbiome that differentiate these community-level patterns have lagged behind, especially as ever-cheaper DNA sequencing has yielded increasingly large data sets. One critical gap is the ability to search for samples that contain specific features (for example, sub-operational taxonomic units [sOTUs] identified by high-resolution statistical methods for removing amplicon sequencing errors). Here we introduce redbiom, a microbiome caching layer, which allows users to rapidly query samples that contain a given feature, retrieve sample data and metadata, and search for samples that match specified metadata values or ranges (e.g., all samples with a pH of >7), implemented using an in-memory NoSQL database called Redis. By default, redbiom allows public anonymous sample access for over 100,000 publicly available samples in the Qiita database. At over 100,000 samples, the caching server requires only 35 GB of resident memory. We highlight how redbiom enables a new type of characterization of microbiome samples and provide tutorials for using redbiom with QIIME 2. redbiom is open source under the BSD license, hosted on GitHub, and can be deployed independently of Qiita to enable search of proprietary or clinically restricted microbiome databases