Characterization of a putative mutant for iron homeostasis

Abstract only availableLittle is known about the genetics of iron homeostasis in plants. A novel genetic screen was used to identify mutants with alterations in iron homeostasis. Because Ferritin (Fer1) mRNA expression is upregulated by intracellular iron concentration in leaves, this gene can be used to predict intercellular iron concentrations in leaves. To identify mutants that over- or under-accumulate leaf iron, Arabidopsis was transformed with the reporter gene Green Fluorescent Protein (GFP) driven by the Fer1 promoter. Seed from this transgenic plant were mutagenized with EMS. The resulting M2 seed were screened for high or low GFP fluorescence relative to transgenic controls grown on iron-sufficient medium. A putative Over-Accumulator of Fe, pOAF40, was identified that expressed high levels of GFP fluorescence. Our objective was to characterize this mutant for alterations in iron homeostasis. Seed of pOAF40 and the non-mutagenized transgenic control were germinated and plants grown on iron-sufficient medium for 14 days before transferring to iron-sufficient or -deficient media for four days. Fer1 mRNA levels, chlorophyll content, and ferric-chelate reductase activity (an enzyme whose activity increases during iron deficiency) were determined at the point of transfer and again four days after transfer. Fer1 mRNA expression was the same at the time of transfer, but greater relative to transgenic controls regardless of iron concentration 4 days later. The average concentration of chlorophyll in pOAF40 was less than the control regardless of sampling time or iron concentration. pOAF40 exhibited lower reductase activity than control on the day of transfer, however this difference in activity was not detected four days after transfer within iron-sufficient or -deficient treatments. Furthermore, ferric-chelatate reductase activity was greater in iron-deficient than -sufficient media for both mutant and control suggesting normal response to iron-deficiency by pOAF40. Further characterization of this mutant is being performed to determine whether the mutation deregulates ferritin expression or leads to over-accumulation of iron in leaves.MU Monsanto Undergraduate Research Fellowshi

Charlson Comorbidity Index: A Critical Review of Clinimetric Properties

The present critical review was conducted to evaluate the clinimetric properties of the Charlson Comorbidity Index (CCI), an assessment tool designed specifically to predict long-term mortality, with regard to its reliability, concurrent validity, sensitivity, incremental and predictive validity. The original version of the CCI has been adapted for use with different sources of data, ICD-9 and ICD-10 codes. The inter-rater reliability of the CCI was found to be excellent, with extremely high agreement between self-report and medical charts. The CCI has also been shown either to have concurrent validity with a number of other prognostic scales or to result in concordant predictions. Importantly, the clinimetric sensitivity of the CCI has been demonstrated in a variety of medical conditions, with stepwise increases in the CCI associated with stepwise increases in mortality. The CCI is also characterized by the clinimetric property of incremental validity, whereby adding the CCI to other measures increases the overall predictive accuracy. It has been shown to predict long-term mortality in different clinical populations, including medical, surgical, intensive care unit (ICU), trauma, and cancer patients. It may also predict in-hospital mortality, although in some instances, such as ICU or trauma patients, the CCI did not perform as well as other instruments designed specifically for that purpose. The CCI thus appears to be clinically useful not only to provide a valid assessment of the patient’s unique clinical situation, but also to demarcate major diagnostic and prognostic differences among subgroups of patients sharing the same medical diagnosis

Scientific Objectives, Measurement Needs, and Challenges Motivating the PARAGON Aerosol Initiative

Aerosols are involved in a complex set of processes that operate across many spatial and temporal scales. Understanding these processes, and ensuring their accurate representation in models of transport, radiation transfer, and climate, requires knowledge of aerosol physical, chemical, and optical properties and the distributions of these properties in space and time. To derive aerosol climate forcing, aerosol optical and microphysical properties and their spatial and temporal distributions, and aerosol interactions with clouds, need to be understood. Such data are also required in conjunction with size-resolved chemical composition in order to evaluate chemical transport models and to distinguish natural and anthropogenic forcing. Other basic parameters needed for modeling the radiative influences of aerosols are surface reflectivity and three-dimensional cloud fields. This large suite of parameters mandates an integrated observing and modeling system of commensurate scope. The Progressive Aerosol Retrieval and Assimilation Global Observing Network (PARAGON) concept, designed to meet this requirement, is motivated by the need to understand climate system sensitivity to changes in atmospheric constituents, to reduce climate model uncertainties, and to analyze diverse collections of data pertaining to aerosols. This paper highlights several challenges resulting from the complexity of the problem. Approaches for dealing with them are offered in the set of companion papers

Electrically Variable Resistive Memory Devices

Nonvolatile electronic memory devices that store data in the form of electrical- resistance values, and memory circuits based on such devices, have been invented. These devices and circuits exploit an electrically-variable-resistance phenomenon that occurs in thin films of certain oxides that exhibit the colossal magnetoresistive (CMR) effect. It is worth emphasizing that, as stated in the immediately preceding article, these devices function at room temperature and do not depend on externally applied magnetic fields. A device of this type is basically a thin film resistor: it consists of a thin film of a CMR material located between, and in contact with, two electrical conductors. The application of a short-duration, low-voltage current pulse via the terminals changes the electrical resistance of the film. The amount of the change in resistance depends on the size of the pulse. The direction of change (increase or decrease of resistance) depends on the polarity of the pulse. Hence, a datum can be written (or a prior datum overwritten) in the memory device by applying a pulse of size and polarity tailored to set the resistance at a value that represents a specific numerical value. To read the datum, one applies a smaller pulse - one that is large enough to enable accurate measurement of resistance, but small enough so as not to change the resistance. In writing, the resistance can be set to any value within the dynamic range of the CMR film. Typically, the value would be one of several discrete resistance values that represent logic levels or digits. Because the number of levels can exceed 2, a memory device of this type is not limited to binary data. Like other memory devices, devices of this type can be incorporated into a memory integrated circuit by laying them out on a substrate in rows and columns, along with row and column conductors for electrically addressing them individually or collectively

On clinical trial fragility due to patients lost to follow up

Wells ′ research was partially supported by NIH grant U19 AI111143, PCORI IHS-2017C3-8923, and Cornell’s Center for the Social Sciences project on Algorithms, Big Data, and Inequality.Background Clinical trials routinely have patients lost to follow up. We propose a methodology to understand their possible effect on the results of statistical tests by altering the concept of the fragility index to treat the outcomes of observed patients as fixed but incorporate the potential outcomes of patients lost to follow up as random and subject to modification. Methods We reanalyse the statistical results of three clinical trials on coronary artery bypass grafting (CABG) to study the possible effect of patients lost to follow up on the treatment effect statistical significance. To do so, we introduce the LTFU-aware fragility indices as a measure of the robustness of a clinical trial’s statistical results with respect to patients lost to follow up. Results The analyses illustrate that clinical trials can either be completely robust to the outcomes of patients lost to follow up, extremely sensitive to the outcomes of patients lost to follow up, or in an intermediate state. When a clinical trial is in an intermediate state, the LTFU-aware fragility indices provide an interpretable measure to quantify the degree of fragility or robustness. Conclusions The LTFU-aware fragility indices allow researchers to rigorously explore the outcomes of patients who are lost to follow up, when their data is the appropriate kind. The LTFU-aware fragility indices are sensitivity measures in a way that the original fragility index is not.Peer reviewe

Reply to ''Comments on 'Why Hasn't Earth Warmed as much as Expected?'''

In response to our article, Why Hasnt Earth Warmed as Much as Expected? (2010), Knutti and Plattner (2012) wrote a rebuttal. The term climate sensitivity is usually defined as the change in global mean surface temperature that is produced by a specified change in forcing, such as a change in solar heating or greenhouse gas concentrations. We had argued in the 2010 paper that although climate models can reproduce the global mean surface temperature history over the past century, the uncertainties in these models, due primarily to the uncertainty in climate forcing by airborne particles, mean that the models lack the confidence to actually constrain the climate sensitivity within useful limits for climate prediction. Knutti and Plattner are climate modelers, and they argued essentially that because the models could reproduce the surface temperature history, the issue we raised was moot. Our response amounts to straightening out this confusion; for the models to be constraining, they must be able to reproduce the surface temperature history with sufficient confidence, not just to match the measurements, but to exclude alternative histories. As before, we concluded that if we can actually make the aerosol measurements using currently available, state-of-the-art techniques, we can determine the aerosol climate forcing to the degree required to constrain that aspect of model climate sensitivity. A technical issue relating to the timescale over which a change in CO2 emissions would be equilibrated in the environmental energy balance was also discussed, again, a matter of differences in terminology

The stochastic resonance mechanism in the Aerosol Index dynamics

We consider Aerosol Index (AI) time-series extracted from TOMS archive for an area covering Italy $(7-18^o E ; 36-47^o N)$. The missing of convergence in estimating the embedding dimension of the system and the inability of the Independent Component Analysis (ICA) in separating the fluctuations from deterministic component of the signals are evidences of an intrinsic link between the periodic behavior of AI and its fluctuations. We prove that these time series are well described by a stochastic dynamical model. Moreover, the principal peak in the power spectrum of these signals can be explained whereby a stochastic resonance, linking variable external factors, such as Sun-Earth radiation budget and local insolation, and fluctuations on smaller spatial and temporal scale due to internal weather and antrophic components

Characteristics and outcome of patients with newly diagnosed advanced or metastatic lung cancer admitted to intensive care units (ICUs)

BACKGROUND: Although patients with advanced or metastatic lung cancer have poor prognosis, admission to the ICU for management of life-threatening complications has increased over the years. Patients with newly diagnosed lung cancer appear as good candidates for ICU admission, but more robust information to assist decisions is lacking. The aim of our study was to evaluate the prognosis of newly diagnosed unresectable lung cancer patients. METHODS: A retrospective multicentric study analyzed the outcome of patients admitted to the ICU with a newly diagnosed lung cancer (diagnosis within the month) between 2010 and 2013. RESULTS: Out of the 100 patients, 30 had small cell lung cancer (SCLC) and 70 had non-small cell lung cancer. (Thirty patients had already been treated with oncologic treatments.) Mechanical ventilation (MV) was performed for 81 patients. Seventeen patients received emergency chemotherapy during their ICU stay. ICU, hospital, 3- and 6-month mortality were, respectively, 47, 60, 67 and 71%. Hospital mortality was 60% when invasive MV was used alone, 71% when MV and vasopressors were needed and 83% when MV, vasopressors and hemodialysis were required. In multivariate analysis, hospital mortality was associated with metastatic disease (OR 4.22 [1.4-12.4]; p = 0.008), need for invasive MV (OR 4.20 [1.11-16.2]; p = 0.030), while chemotherapy in ICU was associated with survival (OR 0.23, [0.07-0.81]; p = 0.020). CONCLUSION: This study shows that ICU management can be appropriate for selected newly diagnosed patients with advanced lung cancer, and chemotherapy might improve outcome for patients with SCLC admitted for cancer-related complications. Nevertheless, tumors' characteristics, numbers and types of organ dysfunction should be taken into account in the decisional process before admitting these patients in ICU.Peer reviewe

An Integrated Approach for Characterizing Aerosol Climate Impacts and Environmental Interactions

Aerosols exert myriad influences on the earth's environment and climate, and on human health. The complexity of aerosol-related processes requires that information gathered to improve our understanding of climate change must originate from multiple sources, and that effective strategies for data integration need to be established. While a vast array of observed and modeled data are becoming available, the aerosol research community currently lacks the necessary tools and infrastructure to reap maximum scientific benefit from these data. Spatial and temporal sampling differences among a diverse set of sensors, nonuniform data qualities, aerosol mesoscale variabilities, and difficulties in separating cloud effects are some of the challenges that need to be addressed. Maximizing the long-term benefit from these data also requires maintaining consistently well-understood accuracies as measurement approaches evolve and improve. Achieving a comprehensive understanding of how aerosol physical, chemical, and radiative processes impact the earth system can be achieved only through a multidisciplinary, inter-agency, and international initiative capable of dealing with these issues. A systematic approach, capitalizing on modern measurement and modeling techniques, geospatial statistics methodologies, and high-performance information technologies, can provide the necessary machinery to support this objective. We outline a framework for integrating and interpreting observations and models, and establishing an accurate, consistent, and cohesive long-term record, following a strategy whereby information and tools of progressively greater sophistication are incorporated as problems of increasing complexity are tackled. This concept is named the Progressive Aerosol Retrieval and Assimilation Global Observing Network (PARAGON). To encompass the breadth of the effort required, we present a set of recommendations dealing with data interoperability; measurement and model integration; multisensor synergy; data summarization and mining; model evaluation; calibration and validation; augmentation of surface and in situ measurements; advances in passive and active remote sensing; and design of satellite missions. Without an initiative of this nature, the scientific and policy communities will continue to struggle with understanding the quantitative impact of complex aerosol processes on regional and global climate change and air quality