Perturbation Events Research Articles

Biocrusts Mediate the Niche Distribution and Diversity of Ammonia-Oxidizing Microorganisms in the Gurbantunggut Desert, Northwestern China

Biological soil crusts (biocrusts) play pivotal ecological roles in regulating nitrogen cycling within desert ecosystems. While acknowledging the essential role played by ammonia-oxidizing microorganisms in nitrogen transformation, there remains a paucity of understanding concerning how disturbances to biocrusts impact the diversity and spatial distribution patterns among ammonia oxidizer communities within temperate deserts. This investigation delved into assessing how 4 years’ worth of removing biocrust influenced niche differentiation between nitrifying archaea and bacteria while also examining its effects on shaping community structures of predominant ammonia-oxidizing archaea (AOA) within the Gurbantunggut Desert soils. Despite notable variations in abundance of ammonia-oxidizing microbes across distinct soil depths throughout different seasons, it became apparent that removing biocrust significantly altered both the abundance and niche pattern for AOA alongside their bacterial counterparts during winter and summer periods. Notably dominating over their bacterial counterparts within desert soils, AOA displayed their highest archaeal to bacterial amoA gene copy ratio (6549-fold higher) at a soil depth of 5–10 cm during summer. Moreover, substantial impacts were observed upon AOA diversity along with compositional changes following such perturbation events. The aftermath saw an emergence of more diffuse yet dynamic AOA communities, especially noticeable amidst winter when nitrogen and water limitations were relatively alleviated. In summary, our findings underscore how interactions between biocrust coverages alongside factors like soil temperature, total carbon content, or NO3−_N concentrations govern niches occupied by ammoxidation communities whilst influencing assemblage processes too. The sensitivity shown by dominant AOAs towards biocrust removal further underscores how biocrust coverage influences nitrogen transformation processes while potentially involving other communities and functions in desert ecosystems.

Hector’s dolphin distribution at Kaikōura before and after a major earthquake

Catastrophic natural events can have major impacts on marine ecosystems, but effects on mobile predators, such as cetaceans, remain poorly understood. This study investigated whether the coastal distribution patterns of Hector’s dolphins Cephalorhynchus hectori hectori off Kaikōura, New Zealand, changed after the powerful Kaikōura earthquake in November 2016. Dolphin sightings from boat-based surveys conducted before (2013-2016) and after (2016-2020) the earthquake were binned into 18 sectors of 4 km length each. The dolphins’ occurrence across sectors was then compared during pre- and post-earthquake periods using generalised linear models. Areas of high and low occurrence probability were temporally stable for Hector’s dolphins from before to 1.5 yr post-quake. Historic sighting data (from the 1990s) matched with the observed high-occurrence areas, indicating decadal stability in distribution patterns. An increase in dolphin occurrence was noted in the final 2-4 yr post-quake period across most nearshore sectors. This was particularly noticeable in the historically low-use areas along the narrow shelf at the head of the deep Kaikōura Canyon. This observation could indicate increased population connectivity between dolphins using the northern and southern sections of the Kaikōura Peninsula. The dolphins’ occurrence patterns pre-quake at the sector level were broadly explained by water depth, distance to rivers, sea surface temperature and chlorophyll when explored with generalised additive models. We discuss scenarios that may explain the species’ persistent distribution patterns during natural perturbation events as well as synergies with other conservation measures.

Long-term (2010–2021) lidar observations of stratospheric aerosols in Wuhan, China

Abstract. This study analyzes the vertical distribution, optical properties, radiative forcing, and several perturbation events of stratospheric aerosols using observations from a ground-based polarization lidar in Wuhan (30.5° N, 114.4° E) from 2010 to 2021. The background stratospheric aerosol optical depth (sAOD) was 0.0044 ± 0.0019 at 532 nm, as calculated during a stratosphere-quiescent period from January 2013 to August 2017. In addition, several cases of volcanic aerosol and wildfire-induced smoke were observed. Volcanic aerosols from the Nabro (2011) and Raikoke (2019) eruptions (both in boreal summer) increased the sAOD to 2.9 times the background level. Tracers of smoke from the Canadian wildfire in the summer of 2017 were observed twice, at 19–21 km on 14–17 September and at 20–23 km on 28–31 October, with a plume-isolated aerosol optical depth (AOD) of 0.002–0.010 and a particle linear depolarization ratio δp of 0.14–0.18, indicating the dominance of non-aged smoke particles. During these summertime events, the injected stratospheric aerosols were captured by the large-scale Asian monsoon anticyclone (AMA), confining the transport pathway to mid-latitude Asia. On 8–9 November 2020, smoke plumes originating from the California wildfire in October 2020 appeared at 16–17 km, with a mean δp of 0.13. Regarding seasonal variation, the sAOD in the cold half-year (0.0054) is 69 % larger than in the warm half-year (0.0032) due to stronger meridional transport of stratospheric aerosols from the tropics to middle latitudes. The stratospheric radiative forcing was −0.11 W m−2 during the stratosphere-quiescent period and increased to −0.31 W m−2 when volcanic aerosols were largely injected. These findings contribute to our understanding of the sources and transport patterns of stratospheric aerosols over mid-latitude Asia and serve as an important database for the validation of model outputs.

Redox-sensitive metals and δ238U in red and grey shales: Exploring a new archive for palaeo-redox studies

Reconstructions of past oceanic redox conditions, based on the measurement of metal distributions and their stable-isotope ratios in marine sediments, have now become more commonplace, providing new constraints on past environmental change. Almost all of these records, however, are based on organic-rich black-shale and carbonate sedimentary archives, which have formed primarily in low-latitude regions. This limitation leads to incomplete geographic coverage that complicates the global-scale interpretation of the results. In this study, the potential of oceanic ‘red beds’ and grey shales as new archives of past environmental conditions are explored to complement the datasets derived from other lithologies and extend reconstruction efforts to mid- to high-latitude regions. Our records originate from open-marine red and grey shales from two sedimentary sections spanning the Late Cretaceous Oceanic Anoxic Event 2 (OAE 2) in New Zealand, formerly deposited at high southern latitudes in the palaeo-Pacific Ocean at c. 94 Ma and where contemporaneous black-shale and/or carbonate successions do not exist. Access to the seawater-derived, authigenic fraction of the bulk sediment is essential for reconstructing past marine redox state at these mid- to high-latitude locations. Therefore, a series of leaching experiments using reagents of progressively increasing concentration were conducted to determine the best method for isolating the authigenic Fe- and Mn-(oxyhydr)oxide fraction from the red and grey shale lithologies. Chemostratigraphic records for the concentrations of a suite of redox-sensitive metals (Fe, Mn, Co, Ni, Mo, Cr, V and U), as well as the U-isotope palaeo-redox tracer (238U/235U; reformulated as δ238U), were obtained. These records imply that leaching with 6 M HCl at room temperature is the best of the tested methods for the selective extraction of the Fe- and Mn-(oxyhydr)oxide phase, whilst minimising the contribution from older inherited detrital material that potentially could confound the interpretation of the chemostratigraphic records. This method offers potential for reliably constraining the authigenic distributions of redox-sensitive elements in red and grey shales, provided Fe- and Mn-(oxyhydr)oxides are predominantly of authigenic origin and constitute at least 5 % of the mineralogy. By contrast, for the investigation of the U-isotope system, a larger Fe- and Mn-(oxyhydr)oxide proportion in the sediment for an ocean–atmosphere perturbation event recording more severe changes in ocean redox conditions and bigger U-isotope shifts than observed for OAE 2 are both necessary to obtain reliable results.

Social behaviour mediates the microbiome response to antibiotic treatment in a wild mammal.

High levels of social connectivity among group-living animals have been hypothesized to benefit individuals by creating opportunities to rapidly reseed the microbiome and maintain stability against disruption. We tested this hypothesis by perturbing the microbiome of a wild population of Grant's gazelles with an antibiotic and asking whether microbiome recovery differs between individuals with high versus low levels of social connectivity. We found that after treatment, individuals with high social connectivity experienced a faster increase in microbiome richness than less socially connected individuals. Unexpectedly, the rapid increase in microbiome richness of highly connected individuals that received treatment led to their microbiomes becoming more distinct relative to the background population. Our results suggest that the microbiome of individuals with high social connectivity can be rapidly recolonized after a perturbation event, but this leads to a microbiome that is more distinct from, rather than more similar to the unperturbed state. This work provides new insight into the role of social interactions in shaping the microbiome.

Life history strategies predict responses of lacustrine fish communities to eutrophication

The demographic traits of an organism are key components of its fitness and life history theory aims at identifying the environmental drivers underlying the evolution of life history strategies. For fishes, the equilibrium species, those investing into larval survival (large eggs, parental care) rather than into absolute fecundity, are hypothesized to have evolved in stable and predictable environments with high biotic pressure. Human induced nutrient enrichment in many lakes around the world makes them increasingly subjected to perturbations such as anoxia and toxic algal blooms. We hypothesized that eutrophication results in lakes becoming more unstable, unpredictable and less resource-limited, in turn less favorable to equilibrium species. Another hypothesis states that lacustrine environment stability increases with ecosystem size. This study presents the first attempt to compare the two hypotheses in a group of 26 lakes. We found that the population abundance of equilibrium species was negatively related to increasing eutrophication. Long-lived and highly fecund periodic species responded more positively to eutrophication than short lived opportunistic species, with no parental care. This result could be demonstrated by seasonality in primary productivity which favors periodic species, disconnection from the river which prevents good colonist (i.e., opportunistic) species to (re)-establish after perturbation events, and predation by periodic species on opportunistic species. In contrast, we found no support for the ecosystem size hypothesis. Overall, we showed that human driven eutrophication affected species according to their life history strategies, reinforcing the usefulness of life history theory as a framework for assessing fish community response to a large array of human perturbations. More generally, our study emphasizes the importance of species traits to assess, explain, and predict community responses to human and natural perturbations.

Process stability in anaerobic Digestion: Unveiling microbial signatures of full-scale reactor performance

Anaerobic digestion is responding to the growing demand for sustainability by exploring alternatives for methane production through renewable processes. The target is to implement stable production systems at industrial scale that can accommodate heterogeneous feedstocks with seasonal or intermittent availability. In this study, we investigated the microbiomes of six full-scale biogas plant digesters, operated under continuous production with distinct feedstock and varying operating parameters, by monitoring multiple time points over an 18-month period. This time-course experiment analyzed 114 Metagenome-Assembled Genomes alongside physico-chemical assessments to identify common and plant-specific indicators for operational management. Results identify a Limnochordia and a Dysgonomonadaceae bacteria, as well as Candidatus Methanoculleus thermohydrogenotrophicum, as widespread and potentially desirable components of the microbiota for resilient digestion of varying waste, including the peculiar olive pomace. The abundance of individual taxonomic groups and their reconstructed metabolic pathways aligned with the availability of their fermentation substrates, finding a prevalence of beta-oxidizing bacteria with lipid-rich olive pomace. Monitoring through perturbation events revealed possible causative and remediative microbiological factors, in particular Methanosarcina flavescens and Candidatus Syntrophosphaera thermopropionivorans could contribute to restoration of reactor performance. This work showcases relationships between digester operation and its microbiome, supporting microbial monitoring as a tool to increase biogas production efficiency.

Norian (Upper Triassic) carbon isotopic perturbations and conodont biostratigraphy from the Simao terrane, eastern Tethys

The Norian “chaotic carbon episode” stands out as a compelling carbon cycle perturbation event within the Late Triassic period. This episode has been documented in marine stratigraphic sections across North America, Italy, Japan, and China. However, limited Norian chronostratigraphy available in the eastern Tethys inhibited the identification of this event in this broad area, and thus the possible global response to this carbon cycle perturbation. To address this issue, we analyzed the conodonts and carbon-isotope of the Norian Sanhedong (SHD) section in the Simao terrane, Southwest China. The identification of the Alaunian Epigondolella spiculata Zone has well documented the base of the Alaunian stage. Moreover, a conodont faunal turnover can be recognized at the base of the Alaunian, with the evolution of Mockina from Ancyrogondolella and Epigondolella, and it is characterized by a gradual decrease in specimen size. The E. spiculata conodont Zone from the SHD section correlates well with the homonymous conodont Zones documented in both the Tethys and the Panthalassa Oceans. Two carbon-isotope negative excursions (CIE1 and CIE2) have also been recorded in the Lacian to Alaunian of the SHD section that can be compared with coeval global sections.

Addressing chemically-induced obesogenic metabolic disruption: selection of chemicals for in vitro human PPARα, PPARγ transactivation, and adipogenesis test methods.

Whilst western diet and sedentary lifestyles heavily contribute to the global obesity epidemic, it is likely that chemical exposure may also contribute. A substantial body of literature implicates a variety of suspected environmental chemicals in metabolic disruption and obesogenic mechanisms. Chemically induced obesogenic metabolic disruption is not yet considered in regulatory testing paradigms or regulations, but this is an internationally recognised human health regulatory development need. An early step in the development of relevant regulatory test methods is to derive appropriate minimum chemical selection lists for the target endpoint and its key mechanisms, such that the test method can be suitably optimised and validated. Independently collated and reviewed reference and proficiency chemicals relevant for the regulatory chemical universe that they are intended to serve, assist regulatory test method development and validation, particularly in relation to the OECD Test Guidelines Programme. To address obesogenic mechanisms and modes of action for chemical hazard assessment, key initiating mechanisms include molecular-level Peroxisome Proliferator-Activated Receptor (PPAR) α and γ agonism and the tissue/organ-level key event of perturbation of the adipogenesis process that may lead to excess white adipose tissue. Here we present a critical literature review, analysis and evaluation of chemicals suitable for the development, optimisation and validation of human PPARα and PPARγ agonism and human white adipose tissue adipogenesis test methods. The chemical lists have been derived with consideration of essential criteria needed for understanding the strengths and limitations of the test methods. With a weight of evidence approach, this has been combined with practical and applied aspects required for the integration and combination of relevant candidate test methods into test batteries, as part of an Integrated Approach to Testing and Assessment for metabolic disruption. The proposed proficiency and reference chemical list includes a long list of negatives and positives (20 chemicals for PPARα, 21 for PPARγ, and 11 for adipogenesis) from which a (pre-)validation proficiency chemicals list has been derived.

A robust defense for spiking neural networks against adversarial examples via input filtering

Spiking Neural Networks (SNNs) are increasingly deployed in applications on resource constraint embedding systems due to their low power. Unfortunately, SNNs are vulnerable to adversarial examples which threaten the application security. Existing denoising filters can protect SNNs from adversarial examples. However, the reason why filters can defend against adversarial examples remains unclear and thus it cannot ensure a trusty defense. In this work, we aim to explain the reason and provide a more robust filter against different adversarial examples. First, we propose two new norms l0 and l∞ to describe the spatial and temporal features of adversarial events for understanding the working principles of filters. Second, we propose to combine filters to provide a robust defense against different perturbation events. To make up the gap between the goal and the ability of existing filters, we propose a new filter that can defend against both spatially and temporally dense perturbation events. We conduct the experiments on two widely used neuromorphic datasets, NMNIST and IBM DVSGesture. Experimental results show that the combined defense can restore the accuracy to over 80% of the original SNN accuracy.

Robust control strategies applicable to DC–DC converter with reliability assessment: A review

AbstractThis paper provides an overview of various control strategies for DC–DC converters along with a brief discussion on various performance indices for evaluating the reliability of designed controller. DC–DC converters are emerging as the fastest‐growing interfacing devices in the world because of their emergent applications in almost all domains of engineering. Notably, the non‐linear behavior of DC–DC converters offers a perplexing problem in designing a robust controller. A robust controller must ensure proper closed‐loop stability with desired performance and reliable control for output voltage regulation in the event of various possible perturbations. This creates the requirement for practically implementable non‐linear controllers that can effectively overlook the drawbacks of linear controllers. The prominence of this composition is based on the expansion in tuning techniques of proportional‐integral‐derivative controller gain parameters using linear strategies and heading towards non‐linear strategies by reviewing 196 research papers. The modification in non‐linear control strategies in terms of their fundamental features associated with key benefits and limitations are comprehensively reviewed. This study mostly revolves around non‐linear internal model control (IMC) strategies for parameter tuning of IMC‐based controllers for various order of plants with an improved degree of freedom.

An Extreme Auroral Electrojet Spike During 2023 April 24th Storm

AbstractAbrupt variations of auroral electrojets can induce geomagnetically induced currents, and the ability to model and forecast them is a pressing goal of space weather research. We report an auroral electrojet spike event that is extreme in magnitude, explosive in nature, and global in spatial extent that occurred on 24 April 2023. The event serves as a fundamental test of our understanding of the response of the geospace system to solar wind dynamics. Our results illustrate new and important characteristics that are drastically different from existing knowledge. Most important findings include (a) the event was only of ∼5‐min duration and was limited to a narrow (2°–3°) band of diffuse aurora; (b) the longitudinal span covered the entire nightside sector, possibly extending to the dayside; (c) the trigger seems to be a transient solar wind dynamic pressure pulse. In comparison, substorms usually last 1–2 hr and span almost the entire latitudinal width of the auroral oval. Magnetic perturbation events (MPEs) span hundreds km in radius. Both substorms and MPEs are mainly driven by disturbances in the magnetotail. A possible explanation is that the pressure pulse compresses the magnetosphere and enhances diffuse precipitation of electrons and protons from the inner plasma sheet, which elevates the ionospheric conductivity and intensifies the auroral electrojet. Therefore, the event exhibits a potentially new type of geomagnetic disturbance and highlights a solar wind driver that is enormously influential in driving extreme space weather events.

Mapping the Chemodynamics of the Galactic Disk Using the LAMOST and APOGEE Red Clump Stars

A detailed measurement is made of the metallicity distributions, kinematics, and dynamics of the thin and thick disks across a large disk volume (5.0 ≤ R ≤ 15.0 kpc and ∣Z∣ ≤ 3.0 kpc) by using the LAMOST–APOGEE red clump stars. The metallicity distribution results show that the radial metallicity gradient Δ[Fe/H]/ΔR of the thin disk weakens with ∣Z∣ from −0.06 dex kpc−1 at around ∣Z∣ < 0.25 kpc to −0.02 dex kpc−1 at around ∣Z∣ > 2.75 kpc, while the thick disk displays a global weak positive Δ[Fe/H]/ΔR that is generally weaker than 0.01 dex kpc−1. The vertical metallicity gradient Δ[Fe/H]/Δ∣Z∣ steadily weakened from −0.36 dex kpc−1 at R ∼ 5.5 kpc to −0.05 dex kpc−1 at around R > 11.5 kpc for the thin disk, while the thick disk presents an almost constant value (nearly −0.06∼−0.08 dex kpc−1) for all the R bins. These results indicate the contribution of the radial migration to the disk evolution, and the obvious north–south asymmetry in [Fe/H] may be linked to disk warp and/or disk perturbation events. The oscillations in the corrected Δ[Fe/H]/Δ∣Z∣ with R likely arise from the resonances with the Galactic bar. Our detailed measurements of ΔV ϕ /Δ[Fe/H] indicate an inside-out and upside-down star formation scenario for the thick disk. The results of eccentricity distributions and [α/Fe]–velocity dispersion relations are likely to suggest that thick-disk stars require an obvious contribution from other heating mechanisms, such as mergers and accretion, or are born in the chaotic mergers of gas-rich systems and/or the turbulent interstellar medium.

ILOSCAR: interactive Long-term Ocean-atmosphere-Sediment CArbon cycle Reservoir model v1.0

Computationally inexpensive carbon cycle models serve as critical and efficient tools for illuminating the complex dynamics of the carbon cycle and its interplay with the climate system, offering insights into how our planet has responded to climate perturbations throughout its history. During geologic hyperthermal events, carbon cycle models are employed to trace the trajectory of carbon emissions and establish a connection between the emission trajectory and changes in the Earth's surface environment. To date, the prevalent method to estimate the carbon emission rate relies on coupling the carbon cycle modeling and proxy reconstructions. Most previous studies employ a forward methodology, i.e., they force the model with an array of predefined carbon injection scenarios and select the one that produces the best fit to one or more specific proxy-derived records (e.g., atmospheric pCO2, sea surface pH, and calcite compensation depth) as the optimal solution. However, this forward method has two potential disadvantages. First, it can be computationally expensive, particularly when tens of thousands of scenarios need to be conducted to find the best solution. Second, it might not yield the best injection trajectory if none of the predefined carbon emission curves represents the realistic emission curve. Hence, an inverse model that can reconstruct the carbon emission trajectory directly from the record/records is urgently needed. In this study, building upon the Long-term Ocean-atmosphere-Sediment CArbon cycle Reservoir (LOSCAR) Model (Zeebe, 2012), we develop an interactive carbon cycle model (named iLOSCAR) using the open-source Python language and include two options, a forward model and an inverse model. The forward model replicates the original LOSCAR model, while the inverse model calculates the emission trajectory constrained by the proxy records in a single run. Both models are accessible via a web-based interface, which allows users to interactively tune model parameters and conduct experiments. In this paper, we present the details of iLOSCAR, including model structure and derivation of key equations. We then validate iLOSCAR's performance through an identical twin test and model intercomparison. We also apply it to a climatic perturbation event to diagnose features of the emission pattern that were overlooked in previous studies. Finally, we discuss the possible directions for model's future development.

Inferring attracting basins of power system with machine learning

Power systems dominated by renewable energy encounter frequently large, random disturbances, and a critical challenge faced in power-system management is how to anticipate accurately whether the perturbed systems will return to the functional state after the transient or collapse. Whereas model-based studies show that the key to addressing the challenge lies in the attracting basins of the functional and dysfunctional states in the phase space, the finding of the attracting basins for realistic power systems remains a challenge, as accurate models describing the system dynamics are generally unavailable. Here we propose a new machine-learning technique, namely balanced reservoir computing, to infer the attracting basins of a typical power system based on measured data. Specifically, trained by the time series of a handful of perturbation events, we demonstrate that the trained machine can predict accurately whether the system will return to the functional state in response to a large, random perturbation, thereby reconstructing the attracting basin of the functional state. The working mechanism of the new machine is analyzed, and it is revealed that the success of the new machine is attributed to the new objective function adopted in optimizing the machine hyperparameters, which keeps a good balance between the echo and fading properties of the reservoir network; the effect of noisy signals on the prediction performance is also investigated, and it is found that the machine performance is improved by introducing a certain amount of noise. Finally, we demonstrate that the new technique can also be utilized to infer the attracting basins of coexisting attractors in typical chaotic systems. Published by the American Physical Society 2024

Mapping the Galactic Disk with the LAMOST and Gaia Red Clump Sample. VIII. Mapping the Kinematics of the Galactic Disk Using Mono-age and Mono-abundance Stellar Populations

We present a comprehensive study of the kinematic properties of the different Galactic disk populations, as defined by the chemical abundance ratios and stellar ages, across a large disk volume (4.5 ≤ R ≤ 15.0 kpc and ∣Z∣ ≤ 3.0 kpc), by using the LAMOST-Gaia red clump sample stars. We determine the median velocities for various spatial and population bins, finding large-scale bulk motions; for example, the wave-like behavior in radial velocity, the north–south discrepancy in azimuthal velocity and the warp signal in vertical velocity, and the amplitudes and spatial dependences of these bulk motions show significant variations for different mono-age and mono-abundance populations. The global spatial behaviors of the velocity dispersions clearly show a signal of spiral arms and a signal of the disk perturbation event within 4 Gyr, as well as disk flaring in the outer region (i.e., R ≥ 12 kpc), mostly for young or alpha-poor stellar populations. Our detailed measurements of age/[α/Fe]-velocity dispersion relations for different disk volumes indicate that young/α-poor populations are likely to originate from dynamic heating by both giant molecular clouds and spiral arms, while old/α-enhanced populations require an obvious contribution from other heating mechanisms, such as merger and accretion, or are born in the chaotic mergers of gas-rich systems and/or turbulent interstellar medium.

Extreme Geomagnetic Disturbances (GMDs) Observed in Eastern Arctic Canada: Occurrence Characteristics and Solar Cycle Dependence

AbstractExtreme (&gt;20 nT/s) geomagnetic disturbances (GMDs, also denoted as MPEs—magnetic perturbation events)—impulsive nighttime disturbances with time scale ∼5–10 min, have sufficient amplitude to cause bursts of geomagnetically induced currents (GICs) that can damage technical infrastructure. In this study, we present occurrence statistics for extreme GMD events from five stations in the MACCS and AUTUMNX magnetometer arrays in Arctic Canada at magnetic latitudes ranging from 65° to 75°. We report all large (≥6 nT/s) and extreme GMDs from these stations from 2011 through 2022 to analyze variations of GMD activity over a full solar cycle and compare them to those found in three earlier studies. GMD activity between 2011 and 2022 did not closely follow the sunspot cycle, but instead was lowest during its rising phase and maximum (2011–2014) and highest during the early declining phase (2015–2017). Most of these GMDs, especially the most extreme, were associated with high‐speed solar wind streams (Vsw &gt;600 km/s) and steady solar wind pressure. All extreme GMDs occurred within 80 min after substorm onsets, but few within 5 min. Multistation data often revealed a poleward progression of GMDs, consistent with a tailward retreat of the magnetotail reconnection region. These observations indicate that extreme GIC hazard conditions can occur for a variety of solar wind drivers and geomagnetic conditions, not only for fast‐coronal mass ejection driven storms.

A comprehensive analysis of mRNA expression profiles of Esophageal Squamous Cell Carcinoma reveals downregulation of Desmoglein 1and crucial genomic targets.

Esophageal Squamous Cell Carcinoma (ESCC) is a histological subtype of esophageal cancer that begins in the squamous cells in the esophagus. In only 19% of the ESCC-diagnosed patients, a five-year survival rate has been seen. This necessitates the identification of high-confidence biomarkers for early diagnosis, prognosis, and potential therapeutic targets for the mitigation of ESCC. We performed a meta-analysis of 10 mRNA datasets and identified consistently perturbed genes across the studies. Then, integrated with ESCC ATLAS to segregate 'core' genes to identify consequences of primary gene perturbation events leading to gene-gene interactions and dysregulated molecular signaling pathways. Further, by integrating with toxicogenomics data, inferences were drawn for gene interaction with environmental exposures, trace elements, chemical carcinogens, and drug chemicals. We also deduce the clinical outcomes of candidate genes based on survival analysis using the ESCC related dataset in The Cancer Genome Atlas. We identified 237 known and 18 novel perturbed candidate genes. Desmoglein 1 (DSG1) is one such gene that we found significantly downregulated (Fold Change =-1.89, p-value = 8.2e-06) in ESCC across six different datasets. Further, we identified 31 'core' genes (that either harbor genetic variants or are regulated by epigenetic modifications) and found regulating key biological pathways via adjoining genes in gene-gene interaction networks. Functional enrichment analysis showed dysregulated biological processes and pathways including "Extracellular matrix", "Collagen trimmer" and "HPV infection" are significantly overrepresented in our candidate genes. Based on the toxicogenomic inferences from Comparative Toxicogenomics Database we report the key genes that interacted with risk factors such as tobacco smoking, zinc, nitroso benzylmethylamine, and drug chemicals such as cisplatin, Fluorouracil, and Mitomycin in relation to ESCC. We also point to the STC2 gene that shows a high risk for mortality in ESCC patients. We identified novel perturbed genes in relation to ESCC and explored their interaction network. DSG1 is one such gene, its association with microbiota and a clinical presentation seen commonly with ESCC hints that it is a good candidate for early diagnostic marker. Besides, in this study we highlight candidate genes and their molecular connections to risk factors, biological pathways, drug chemicals, and the survival probability of ESCC patients.

Risk Assessment of Industrial Microbes Using a Terrestrial Mesocosm Platform

Industrial microbes and bio-derived products have emerged as an integral component of the bioeconomy, with an array of agricultural, bioenergy, and biomedical applications. However, the rapid development of microbial biotechnology raises concerns related to environmental escape of laboratory microbes, detection and tracking thereof, and resultant impact upon native ecosystems. Indeed, though wild-type and genetically modified microbes are actively deployed in industrial bioprocesses, an understanding of microbial interactivity and impact upon the environment is severely lacking. In particular, the persistence and sustained ecosystem impact of industrial microbes following laboratory release or unintentional laboratory escape remains largely unexplored. Herein, we investigate the applicability of soil-sorghum mesocosms for the ecological risk assessment of the industrial microbe, Saccharomyces cerevisiae. We developed and applied a suite of diagnostic and bioinformatic analyses, including digital droplet PCR, microscopy, and phylogenomic analyses to assess the impacts of a terrestrial ecosystem perturbation event over a 30-day time course. The platform enables reproducible, high-sensitivity tracking of S. cerevisiae in a complex soil microbiome and analysis of the impact upon abiotic soil characteristics and soil microbiome population dynamics and diversity. The resultant data indicate that even though S. cerevisiae is relatively short-lived in the soil, a single perturbation event can have sustained impact upon mesocosm soil composition and underlying microbial populations in our system, underscoring the necessity for more comprehensive risk assessment and development of mitigation and biocontainment strategies in industrial bioprocesses.

Retinoic acid regulation of homoeostatic synaptic plasticity and its relationship to cognitive disorders.

There is increasing interest in retinoic acid (RA) as a regulator of the complex biological processes underlying the cognitive functions performed by the brain. The importance of RA in brain function is underlined by the brain's high efficiency in converting vitamin A into RA. One crucial action of RA in the brain is dependent on RA receptor α (RARα) transport out of the nucleus, where it no longer regulates transcription but carries out non-genomic functions. RARα, when localised in the cytoplasm, particularly in neuronal dendrites, acts as a translational suppressor. It regulates protein translation as a crucial part of the mechanism maintaining homoeostatic synaptic plasticity, which is characterised by neuronal changes necessary to restore and balance the excitability of neuronal networks after perturbation events. Under normal conditions of neurotransmission, RARα without ligand suppresses the translation of proteins. When neural activity is reduced, RA synthesis is stimulated, and RA signalling via RARα derepresses the translation of proteins and synergistically with the fragile X mental retardation protein allows the synthesis of Ca2+ permeable α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptors that re-establish normal levels of synaptic activity. Homoeostatic synaptic plasticity underlies many cognitive processes, so its impairment due to dysregulation of RA signalling may be involved in neurodevelopmental disorders such as autism, which is also associated with FMRP. A full understanding of RA signalling control of homoeostatic synaptic plasticity may point to treatments.