Method for RNA extraction and transcriptomic analysis of single fungal spores

Transcriptomic analysis of single cells has been increasingly in demand in recent years, thanks to technological and methodological advances as well as growing recognition of the importance of individuals in biological systems. However, the majority of these studies have been performed in mammalian cells, due to their ease of lysis and high RNA content. No single cell transcriptomic analysis has yet been applied to microbial spores, even though it is known that heterogeneity at the phenotype level exists among individual spores. Transcriptomic analysis of single spores is challenging, in part due to the physically robust nature of the spore wall. This precludes the use of methods commonly used for mammalian cells. Here, we describe a simple method for extraction and amplification of transcripts from single fungal conidia (asexual spores), and its application in single-cell transcriptomics studies. The method can also be used for studies of small numbers of fungal conidia, which may be necessary in the case of limited sample availability, low-abundance transcripts or interest in small subpopulations of conidia.• The method allows detection of transcripts from single conidia of Aspergillus niger• The method allows detection of genomic DNA from single conidia of Aspergillus nige

Leadership on Trial: A Manifesto for Leadership Development

Recent books and articles have analyzed the causes of the global financial and economic crisis of 2007-09. Yet little attention has been paid to the quality of leadership in organizations that were at the epicentre of the storm, were victims of it, avoided it or even prospered from it. In the summer of 2009 a multi-disciplinary group of Ivey faculty decided to look at the leadership dimensions of the recent financial and economic crisis. We started by writing a working paper that laid out our preliminary views. We then engaged more than 300 business, public sector and not-for-profit leaders in small and large groups, as individuals and collectives, to get their reaction to this paper and, more generally, to discuss the role that organizational leadership played before, during and after the crisis. We examined leadership not just in the financial sector but also in many other public and private sector organizations that were affected by the crisis. In a sense, we were putting leadership on trial. Our aim in doing this was not to identify and assign blame. Rather, we examined leadership during this critical period in recent history to learn what we could, and use the learning to improve the practice of leadership today and the development of next generation leaders. As we analyzed the role of leadership in this crisis we were faced with one major question: “Would better leadership have made a difference?” Our answer is unequivocal: “Yes!” We recognize that many people could argue it is unfair to criticize leaders whose decisions were based on their knowledge of the situation at the time and which only eventually, with the aid of 20/20 hindsight, proved bad. We respect this view but we disagree with it. Some business and public sector leaders predicted better than others the bursting of the housing bubble and financial markets turmoil, positioned their organizations to avoid problems, and coped with them skillfully. Their organizations were not badly damaged by the crisis and some even prospered. Some governments and regulatory agencies’ control and monitoring systems were superior to those in the U.S., the U.K., Ireland, Spain, Iceland and other countries that had to bail out their banks and other industries. Our evidence supports the conclusion that these companies, these agencies, these governments and these countries had better leadership. Good leadership mattered then and good leadership will matter in the future. We are presenting our conclusions about what good leadership involves in the form of a public statement of principles—a manifesto that addresses what good leaders do, who they are, and how they can be developed in organizations

The Nutritional Status of Individuals Adopted Internationally as Children: A Systematic Review.

Since 1955, international adoption has been a way of finding homes for children who have been orphaned or abandoned. We aimed to describe the nutritional status of individuals adopted internationally and their long-term nutritional and health outcomes. We searched four databases for articles published from January 1995 to June 2020, which included information on anthropometric or micronutrient status of children adopted internationally (CAI). Mean Z-scores on arrival to adoptive country ranged from -2.04 to -0.31 for weight for age; -0.94 to 0.39 for weight for height; -0.7 to 0 for body mass index; -1.89 to -0.03 for height for age; -1.43 to 0.80 for head circumference for age. Older children, those adopted from institutionalized care or with underlying disability, were more likely to be malnourished. Though long-term data was scarce, mean Z-scores post-adoption ranged from -0.59 to 0.53 for weight for age; -0.31 to 1.04 for weight for height; 0.39 to 1.04 for body mass index; -1.09 to 0.58 for height for age; -0.06 to 1.23 for head circumference for age. We conclude that though CAI are at high risk of malnutrition at baseline, marked catch-up growth is possible, including for those older than two years of age on arrival. This has implications not only for CAI but for the wider population of malnourished children worldwide. Research on how to optimize catch-up growth is a priority

Enhancing Quality in Psychiatry with Psychiatrists (EQUIPP)—Results from a Pilot Study

To pilot a pharmacist-led, patient centered medication management program

An Experimental Investigation of Applying Mica2 Motes in Pavement Condition Monitoring

Pavement maintenance is vital for travel safety, thus detecting dangerous road conditions in a real-time fashion is desirable. Using an off-the-shelf wireless sensor network to detect such conditions at a low cost poses many challenges. In order to meet these challenges, a Mica2 Mote sensor network is adopted in this study to process and transmit data collected from three external analog sensors. Consequentially, several hardware and software interfaces are developed to complete a pavement monitoring system that uses temperature and moisture presence to detect hazardous road conditions. Surge Time Synchronization is explored in this specific application to enable the wireless sensor network to operate in a low power consumption mode. A fairly simplistic pattern classification algorithm is embedded into the motes to create the smart wireless sensing application. A series of outdoor tests are conducted in this study paying special attention to the survivability of fragile analog sensors in harsh roadway conditions. In this regard, a novel solution called the ``Sensor-Road Button''(SRB) is developed and validated experimentally. This is one of several exercises made in this study to enable the application of sensor technologies in intelligent transportation systems (ITS). The size of the wireless sensor network in this study is relatively small, utilizing a total of five motes in order to fully exploit the transmitting range of each mote. Long testing periods (i.e., uninterrupted 12-hour time frames for each period of data collection) add an additional advantage, allowing for the evaluation of the selected wireless sensor network for long-term monitoring using the low power consumption mode under Surge Time Synchronization. Many performance metrics of the adopted small-size, large-interval Mica2 Motes wireless sensor network are revealed in this study through a series of data processing efforts. Results are presented to examine (i) inter-node connectivity and transmitting range, (ii) battery life, (iii) the length of the initial network connection time as affected by methods of setting up tests under practical conditions, (iv) error rate and analysis of different error types (showing the importance of the subsequent data cleansing step), and (v) other network routing properties including the parent time histories for each mote. The results and analysis form a database for future efforts to better understand, appreciate, and improve the performance of Mica2 Motes. This study will thus benefit robust real-world implementation of off-the-shelf sensor network products such as Mica2 Motes in terms of hardware development and data processing.Yeshttps://us.sagepub.com/en-us/nam/manuscript-submission-guideline

Automated Track Change Detection Technology for Enhanced Railroad Safety Assessment

693JJ619C000004The Rail Transportation and Engineering Center at the University of Illinois at Urbana-Champaign and Railmetrics, Inc. evaluated the use of 3D laser scanning, Deep Convolutional Neural Networks (DCNNs), and change detection technology for railway track safety inspections. Researchers evaluated the potential use of these combined technologies to provide value-added inspection data to traditional track inspection methods. The project was conducted between April 2019 and October 2020. Field testing was completed on the High Tonnage Loop at the Transportation Technology Center in Pueblo, Colorado

Preliminary systems engineering evaluations for the National Ecological Observatory Network.

The National Ecological Observatory Network (NEON) is an ambitious National Science Foundation sponsored project intended to accumulate and disseminate ecologically informative sensor data from sites among 20 distinct biomes found within the United States and Puerto Rico over a period of at least 30 years. These data are expected to provide valuable insights into the ecological impacts of climate change, land-use change, and invasive species in these various biomes, and thereby provide a scientific foundation for the decisions of future national, regional, and local policy makers. NEON's objectives are of substantial national and international importance, yet they must be achieved with limited resources. Sandia National Laboratories was therefore contracted to examine four areas of significant systems engineering concern; specifically, alternatives to commercial electrical utility power for remote operations, approaches to data acquisition and local data handling, protocols for secure long-distance data transmission, and processes and procedures for the introduction of new instruments and continuous improvement of the sensor network. The results of these preliminary systems engineering evaluations are presented, with a series of recommendations intended to optimize the efficiency and probability of long-term success for the NEON enterprise