Prediction of geomagnetic storm strength from inner heliospheric in situ observations

Prediction of the effects of coronal mass ejections (CMEs) on Earth strongly depends on knowledge of the interplanetary magnetic field southward component, B z . Predicting the strength and duration of B z inside a CME with sufficient accuracy is currently impossible, forming the so-called B z problem. Here, we provide a proof-of-concept of a new method for predicting the CME arrival time, speed, B z , and resulting disturbance storm time (Dst) index on Earth based only on magnetic field data, measured in situ in the inner heliosphere (<1 au). On 2012 June 12–16, three approximately Earthward-directed and interacting CMEs were observed by the Solar Terrestrial Relations Observatory imagers and Venus Express (VEX) in situ at 0.72 au, 6° away from the Sun–Earth line. The CME kinematics are calculated using the drag-based and WSA–Enlil models, constrained by the arrival time at VEX, resulting in the CME arrival time and speed on Earth. The CME magnetic field strength is scaled with a power law from VEX to Wind. Our investigation shows promising results for the Dst forecast (predicted: −96 and −114 nT (from 2 Dst models); observed: −71 nT), for the arrival speed (predicted: 531 ± 23 km s−1; observed: 488 ± 30 km s−1), and for the timing (6 ± 1 hr after the actual arrival time). The prediction lead time is 21 hr. The method may be applied to vector magnetic field data from a spacecraft at an artificial Lagrange point between the Sun and Earth or to data taken by any spacecraft temporarily crossing the Sun–Earth line

Modeling observations of solar coronal mass ejections with heliospheric imagers verified with the Heliophysics System Observatory

We present an advance toward accurately predicting the arrivals of coronal mass ejections (CMEs) at the terrestrial planets, including Earth. For the first time, we are able to assess a CME prediction model using data over two thirds of a solar cycle of observations with the Heliophysics System Observatory. We validate modeling results of 1337 CMEs observed with the Solar Terrestrial Relations Observatory (STEREO) heliospheric imagers (HI) (science data) from 8 years of observations by five in situ observing spacecraft. We use the self-similar expansion model for CME fronts assuming 60 degrees longitudinal width, constant speed, and constant propagation direction. With these assumptions we find that 23%-35% of all CMEs that were predicted to hit a certain spacecraft lead to clear in situ signatures, so that for one correct prediction, two to three false alarms would have been issued. In addition, we find that the prediction accuracy does not degrade with the HI longitudinal separation from Earth. Predicted arrival times are on average within 2.6 +/- 16.6 h difference of the in situ arrival time, similar to analytical and numerical modeling, and a true skill statistic of 0.21. We also discuss various factors that may improve the accuracy of space weather forecasting using wide-angle heliospheric imager observations. These results form a first-order approximated baseline of the prediction accuracy that is possible with HI and other methods used for data by an operational space weather mission at the Sun-Earth L5 point. Plain Language Summary Solar storms are formed by incredibly powerful explosions on the Sun and travel as clouds of plasma threaded by magnetic fields through the solar system. Depending on their propagation direction, they may impact planets such as Earth, where they elicit colorful aurorae or, in very seldom cases, can lead to power failures with potentially tremendous economical and societal effects, thus posing a serious natural hazard. In this work, we have shown how well the solar storm impact can be forecasted when using a special type of instrument that can actually image the solar storms as they propagate toward the planets and even as they sweep over them. Our analysis includes two thirds of a solar cycle with 8 years of data, and spacecraft at Mercury, Venus, Earth, and in the solar wind to check on the correctness of our predictions. We could forecast the arrival time within +/- 16 h, and for one correct impact there are two to three false alarms. This forms a new baseline for the science of space weather prediction. Clearly, the modeling should be further improved to be used on a daily basis for a space weather mission to the Sun-Earth L5 point.Peer reviewe

Cryptic Polyketide Synthase Genes in Non-Pathogenic Clostridium SPP

Modular type I polyketide synthases (PKS) produce a vast array of bacterial metabolites with highly diverse biological functions. Notably, all known polyketides were isolated from aerobic bacteria, and yet no example has been reported for strict anaerobes. In this study we explored the diversity and distribution of PKS genes in the genus Clostridium. In addition to comparative genomic analyses combined with predictions of modular type I polyketide synthase (PKS) gene clusters in sequenced genomes of Clostridium spp., a representative selection of other species inhabiting a variety of ecological niches was investigated by PCR screening for PKS genes. Our data reveal that all studied pathogenic Clostridium spp. are devoid of putative PKS genes. In stark contrast, cryptic PKS genes are widespread in genomes of non-pathogenic Clostridium species. According to phylogenetic analyses, the Clostridium PKS genes have unusual and diverse origins. However, reverse transcription quantitative PCR demonstrates that these genes are silent under standard cultivation conditions, explaining why the related metabolites have been overlooked until now. This study presents clostridia as a putative source for novel bioactive polyketides

Data-driven learning of narcosis mode of action identifies a CNS transcriptional signature shared between whole organism Caenorhabditis elegans and a fish gill cell line

Supplementary data related to this article: Supplementary material, available at https://ars.els-cdn.com/content/image/1-s2.0-S0048969722047647-mmc1.docx (Word document35, 5KB)); Supplementary Data 1. These are the chemicals along with their properties and the calculated doses given for the C. elegans (Caenorhabditis elegans), available at https://ars.els-cdn.com/content/image/1-s2.0-S0048969722047647-mmc2.xls (spreadsheet, 68KB); Supplementary Data 2. These are the chemicals and the doses given for the trout gill cell line (Rtgill-WT1). The codes here relate to the same codes on the microarray data, available at https://ars.els-cdn.com/content/image/1-s2.0-S0048969722047647-mmc3.xlsx (spreadsheet; 11KB); Supplementary Data 3. These are the probes found to be significantly different between exposed and unexposed C. elegans for each of the narcotic chemicals tested, available at https://ars.els-cdn.com/content/image/1-s2.0-S0048969722047647-mmc4.xlsx (spreadsheet, 363KB); Supplementary Data 4. The file provide the metabolite composition of the three clusters identified by running a metabolic-based predictive model, available at https://ars.els-cdn.com/content/image/1-s2.0-S0048969722047647-mmc5.xlsx (spreadsheet, 10KB).Copyright © 2022 The Authors. With the large numbers of man-made chemicals produced and released in the environment, there is a need to provide assessments on their potential effects on environmental safety and human health. Current regulatory frameworks rely on a mix of both hazard and risk-based approaches to make safety decisions, but the large number of chemicals in commerce combined with an increased need to conduct assessments in the absence of animal testing makes this increasingly challenging. This challenge is catalysing the use of more mechanistic knowledge in safety assessment from both in silico and in vitro approaches in the hope that this will increase confidence in being able to identify modes of action (MoA) for the chemicals in question. Here we approach this challenge by testing whether a functional genomics approach in C. elegans and in a fish cell line can identify molecular mechanisms underlying the effects of narcotics, and the effects of more specific acting toxicants. We show that narcosis affects the expression of neuronal genes associated with CNS function in C. elegans and in a fish cell line. Overall, we believe that our study provides an important step in developing mechanistically relevant biomarkers which can be used to screen for hazards, and which prevent the need for repeated animal or cross-species comparisons for each new chemical.Unilever Ltd

Distorted Views of Biodiversity: Spatial and Temporal Bias in Species Occurrence Data

Boakes et al. compile and analyze a historical dataset of 170,000 bird sightings over two centuries and show how changing trends in data gathering may confound a true picture of biodiversity change

Changes in the geographical distribution of plant species and climatic variables on the West Cornwall peninsula (South West UK)

Recent climate change has had a major impact on biodiversity and has altered the geographical distribution of vascular plant species. This trend is visible globally; however, more local and regional scale research is needed to improve understanding of the patterns of change and to develop appropriate conservation strategies that can minimise cultural, health, and economic losses at finer scales. Here we describe a method to manually geo-reference botanical records from a historical herbarium to track changes in the geographical distributions of plant species in West Cornwall (South West England) using both historical (pre-1900) and contemporary (post-1900) distribution records. We also assess the use of Ellenberg and climate indicator values as markers of responses to climate and environmental change. Using these techniques we detect a loss in 19 plant species, with 6 species losing more than 50% of their previous range. Statistical analysis showed that Ellenberg (light, moisture, nitrogen) and climate indicator values (mean January temperature, mean July temperature and mean precipitation) could be used as environmental change indicators. Significantly higher percentages of area lost were detected in species with lower January temperatures, July temperatures, light, and nitrogen values, as well as higher annual precipitation and moisture values. This study highlights the importance of historical records in examining the changes in plant species’ geographical distributions. We present a method for manual geo-referencing of such records, and demonstrate how using Ellenberg and climate indicator values as environmental and climate change indicators can contribute towards directing appropriate conservation strategies

Altering the Motivational Function of Nicotine through Conditioning Processes

The collection of chapters in this 55th Nebraska Symposium on Motivation Volume clearly highlights that effective strategies for reducing compulsive tobacco use will require a multifaceted approach in which genetic, neurobiological, individual, and cultural factors are considered. It is difficult, if not impossible, to predict where the next important breakthrough will come from (Bevins & Bardo, 2004; Dethier, 1966; Laidler, 1998). Accordingly, further research that extends and challenges current theory and practice at each of these levels of analysis is needed. The continuing focus of our research program, and the topic of the present chapter, is on the role of Pavlovian conditioning processes involving nicotine. Theoretical and empirical approaches to nicotine dependence that include Pavlovian conditioning processes have lead to important advances in our understanding and treatment of chronic tobacco use (e.g., see Rose, Chapter 8 and Tiffany, Warthen, & Goedecker, Chapter 10 in current Volume). These approaches conceptualize the drug as an unconditioned stimulus (US) or reinforcer. That is, the pharmacological effects of the drug (e.g., reward, analgesia, psychomotor stimulation) enter into an association with stimuli that reliably co-occur with these effects (e.g., paraphernalia, situational cues). Later exposure to these conditioned stimuli (CSs) can evoke conditioned responses (CRs) that increase the chances an individual will seek drug. More recently, we have suggested that the interoceptive stimulus effects of nicotine might also serve as a CS for other appetitive non-drug outcomes (i.e., USs) and/or a stimulus that occasions whether other CS-US associations will or will not occur (i.e., an occasion setter or facilitator; see Bevins & Palmatier, 2004). We have further suggested that such an associative learning history could impact the tenacity of nicotine addiction—e.g., shorten the time between experimentation and dependence, increase the difficulty of quitting, make sustaining abstinence more difficult, etc. At the current time these suggestions are speculative. With this in mind, the present chapter will review the research in this area, as well as highlight some of its historical precursors and suggest some possible future directions for research. In doing so, hopefully the reader will gain an appreciation for how this approach might lead to further insight into how Pavlovian conditioning processes can alter the motivational function of nicotine in a manner that contributes to chronic tobacco use