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Solid state gas sensors are a core enabling technology to a range of measurement applications including industrial, safety, and environmental monitoring. The technology associated with solid-state gas sensors has evolved in recent years with advances in materials, and improvements in processing and miniaturization. In this review, we examine the state-of-the-art of solid state gas sensors with the goal of understanding the core technology and approaches, various sensor design methods to provide targeted functionality, and future prospects in the field. The structure, detection mechanism, and sensing properties of several types of solid state gas sensors will be discussed. In particular, electrochemical cells (solid and liquid), impedance/resistance based sensors (metal oxide, polymer, and carbon based structures), and mechanical sensing structures (resonators, cantilevers, and acoustic wave devices) as well as sensor arrays and supporting technologies, are described. Development areas for this field includes increased control of material properties for improved sensor response and durability, increased integration and miniaturization, and new material systems, including nano-materials and nano-structures, to address shortcomings of existing solid state gas sensors.

BCL6 is a transcriptional repressor that recognizes DNA target sequences similar to those recognized by signal transducer and activator of transcriptions 5 (Stat5). BCL6 disrupts differentiation of breast epithelia, is downregulated during lactation, and is upregulated in poorly differentiated breast cancer. In contrast, Stat5a mediates prolactin-induced differentiation of mammary epithelia, and loss of Stat5 signaling in human breast cancer is associated with undifferentiated histology and poor prognosis. Here, we identify the mammary cell growth factor prolactin as a potent suppressor of BCL6 protein expression in human breast cancer through a mechanism that requires Stat5a, but not prolactin-activated Stat5b, MEK-ERK, or PI3K-AKT pathways. Prolactin rapidly suppressed BCL6 mRNA in T47D, MCF7, ZR75.1, and SKBr3 breast cancer cell lines, followed by prolonged reduction of BCL6 protein levels within 3 hours. Prolactin suppression of BCL6 was enhanced by overexpression of Stat5a but not Stat5b, was mimicked by constitutively active Stat5a, but did not require the transactivation domain of Stat5a. Stat5 chromatin immunoprecipitation demonstrated physical interaction with a BCL6 gene regulatory region, and BCL6 transcript repression required histone deacetylase activity based on sensitivity to trichostatin A. Functionally, BCL6 overexpression disrupted prolactin induction of Stat5 reporter genes. Prolactin suppression of BCL6 was extended to xenotransplant tumors in nude mice in vivo and to freshly isolated human breast cancer explants ex vivo. Quantitative immunohistochemistry revealed elevated BCL6 in high-grade and metastatic breast cancer compared with ductal carcinoma in situ and nonmalignant breast, and cellular BCL6 protein levels correlated negatively with nuclear Stat5a (r = −0.52; P < 0.001) but not with Stat5b. Loss of prolactin-Stat5a signaling and concomitant upregulation of BCL6 may represent a regulatory switch facilitating undifferentiated histology and poor prognosis of breast cancer.

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PURPOSE In-vivo assessment of spinal cord gray matter (GM) and white matter (WM) could become pivotal to study various neurological diseases, but it is challenging because of insufficient GM/WM contrast provided by conventional MRI. Here we present and assess a procedure for measurement of spinal cord total cross-sectional area (TCA) and GM areas based on phase sensitive inversion recovery imaging (PSIR). MATERIALS AND METHODS We acquired 2D PSIR images at 3T at each disc level of the spinal axis on 10 healthy subjects and measured TCA, cord diameters, WM and GM area, and GM area/TCA ratio. We secondly investigated 32 healthy subjects at 4 selected levels (C2–C3, C3–C4, T8–T9, T9–T10, total acquisition time <8 minutes) and generated normative reference values of TCA and GM areas. We assessed test-retest, intra- and inter-operator reliability of the acquisition strategy and measurement steps. RESULTS The measurement procedure based on 2D PSIR imaging allowed TCA and GM area assessments along the entire spinal cord axis. The tests we performed revealed high test-retest/intra-operator reliability (mean coefficient of variation (COV) at C2–C3: TCA=0.41%, GM area=2.75%) and inter-operator reliability of the measurements (mean COV on the 4 levels: TCA=0.44%, GM area= 4.20%; mean intra-class correlation coefficient: TCA=0.998, GM area=0.906). CONCLUSION 2D PSIR allows reliable in-vivo assessment of spinal cord TCA, GM and WM areas in clinically feasible acquisition times. The area measurements presented here are in agreement with previous MRI and post-mortem studies.

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Approximately 2-6% of total iron in commonly used IV iron compounds is available for in vitro iron donation to Tf. This fraction may contribute to evidence of bioactive iron in patients after IV iron administration.

Do teams with motivation to learn actually engage in the behaviors that produce learning? Though team learning orientation has been found to be positively related to team learning, we know little about how and when it actually fosters team learning. It is obviously not the only factor that may impact learning in teams. Team psychological safety, or the way team members feel about taking interpersonal risks, is another important factor associated with team learning. Team open-mindedness, or the degree of curiosity that teams have for new ideas, is also likely to impact team learning. So far, these factors have been investigated independently of each other. In this article, we draw from theory on team development and goal achievement to develop a model of team learning that includes them. We report the results from a time-lagged, survey-based study designed to test our model. We found that the relationship between team learning orientation and team learning is mediated by team psychological safety. Yet, this is only true when team open-mindedness is low, not when it is high. We thus reveal initial patterns of interaction and discrimination among key factors that are related to team learning in ways that contribute to both theory and practice.