Potato Plant Gene Expression and Physiology During Three-Way Interactions with Mycorrhizal Fungi and Lepidopteran Larvae

Arbuscular mycorrhizal fungi (AMF) are integral components of ecosystems and form root associations with the majority of land plants (\u3e80%). In these relationships, AMF provide essential nutrients to their hosts, primarily phosphorus, in exchange for photosynthates, which enhance plant growth and help plants overcome environmental stress. The below-ground interaction between plants and AMF can indirectly alter aboveground plant interactions with insect herbivores. Potatoes (Solanum tuberosum) which are considered one of the most important vegetable crops worldwide, naturally form symbioses with AMF. However, it is not well understood how the association between potatoes and AMF can potentially affect leaf-chewing insect herbivory. This study examined the interactions between potatoes, the generalist Lepidopteran larvae of the cabbage looper (Trichoplusia ni), and a generalist AM fungus (Glomus intraradices). The research objectives were to: a) determine the impact of the tripartite interaction involving an AM fungus, potatoes, and cabbage loopers on each organism involved, b) examine gene expression of a group of defense-related plant genes during a tripartite interaction, and c) assess changes in potato physiology during the tripartite cabbage looper-potatoAM fungus interaction. The results indicate that larval growth was negatively impacted after feeding on mycorrhizal potato plants at the low level of G. intraradices root colonization (20-40% colonized at time of insect exposure) in the first experiment. Larvae gained significantly less weight after seven days of feeding on mycorrhizal plants at the low level of G. intraradices colonization compared to those that fed on highly colonized plants. Mycorrhizal plants at high levels of G. intraradices root colonization accumulated more shoot biomass, however, root biomass was not altered by the AM symbiosis. While defense-related genes were upregulated in shoots of mycorrhizal plants, their expression levels were not significantly different compared to non-mycorrhizal plants. The second and third experiments were designed using the low level of G. intraradices root colonization. Similarly, cabbage looper larvae gained less mass after eight days of feeding on mycorrhizal plants compared to those that fed on nonmycorrhizal plants. In this case, increased levels of transcripts of defense-related genes were detected in above-ground tissues. Interestingly, cabbage looper herbivory caused an ‘apparent’ stimulation of the AM fungus root colonization. Results from the third experiment revealed that while insects were negatively affected by the AM symbiosis, there were not substantial changes in potato plant physiology. Overall, this research showed that potato root colonization by G. intraradices indirectly altered cabbage looper growth (measured as weight), but the effect is dependent on the mycorrhizal stage. At the low level of G. intraradices colonization, the physiology of potato plants was not altered, but again, insects gained less mass after feeding on mycorrhizal plants. At the high levels of G. intraradices colonization, potato shoots accumulated more mass, but also insects gained more mass after feeding on mycorrhizal plants. Taken together, these data suggest that potatoes may transition from insect resistance to tolerance when progressing from low to high levels of G. intraradices root colonization

Local dynamics of topological magnetic defects in the itinerant helimagnet FeGe

Chiral magnetic interactions induce complex spin textures including helical and conical spin waves, as well as particle-like objects such as magnetic skyrmions and merons. These spin textures are the basis for innovative device paradigms and give rise to exotic topological phenomena, thus being of interest for both applied and fundamental sciences. Present key questions address the dynamics of the spin system and emergent topological defects. Here we analyze the micromagnetic dynamics in the helimagnetic phase of FeGe. By combining magnetic force microscopy, single-spin magnetometry, and Landau-Lifschitz-Gilbert simulations we show that the nanoscale dynamics are governed by the depinning and subsequent motion of magnetic edge dislocations. The motion of these topologically stable objects triggers perturbations that can propagate over mesoscopic length scales. The observation of stochastic instabilities in the micromagnetic structure provides new insight to the spatio-temporal dynamics of itinerant helimagnets and topological defects, and discloses novel challenges regarding their technological usage

A 0535+26 in the August/September 2005 outburst observed by RXTE and INTEGRAL

In this Letter we present results from INTEGRAL and RXTE observations of the spectral and timing behavior of the High Mass X-ray Binary A 0535+26 during its August/September 2005 normal (type I) outburst with an average flux F(5-100keV)~400mCrab. The search for cyclotron resonance scattering features (fundamental and harmonic) is one major focus of the paper. Our analysis is based on data from INTEGRAL and RXTE Target of Opportunity Observations performed during the outburst. The pulse period is determined. X-ray pulse profiles in different energy ranges are analyzed. The broad band INTEGRAL and RXTE pulse phase averaged X-ray spectra are studied. The evolution of the fundamental cyclotron line at different luminosities is analyzed. The pulse period P is measured to be 103.39315(5)s at MJD 53614.5137. Two absorption features are detected in the phase averaged spectra at E_1~45keV and E_2~100keV. These can be interpreted as the fundamental cyclotron resonance scattering feature and its first harmonic and therefore the magnetic field can be estimated to be B~4x10^12G.Comment: 4 pages, 5 figures, accepted for publication in A&A Letter

Assessing Supply Chain Resilience During the Pandemic Using Network Analysis

Disruptions induced by the COVID-19 pandemic have wreaked havoc in supply chain networks. To gain an understanding of the dynamics that had been at play, we construct a real supply chain network (scale-free) based on a seed firm (Apple), its customers, and its first- and second-tier suppliers, yielding a network of a total of 883 firms. We then use visualization to derive insight into various network characteristics and develop an agent-based model to capture the disruption of the network over a period of 400 days from the onset of the pandemic. The disruptions experienced by firms depend on the stringency of measures taken to curb the pandemic in their respective countries and the severity of disruptions experienced by suppliers in a specific region. We specifically find that spatial complexity, degree centrality, betweenness centrality, and closeness centrality have changed significantly throughout our observation period. We thus subsequently theorize on the influence of some of these characteristics on supply chain resilience (SCRes), and through our empirical tests, we find that, at the network level, Average degree and spatial complexity significantly influence SCRes. At the firm-level, we find that powerful firms within the network influence SCRes based on their betweenness centrality and closeness Centrality. Implications for managerial practice and academic research are discussed

Detection of Topological Spin Textures via Nonlinear Magnetic Responses

Topologically nontrivial spin textures, such as skyrmions and dislocations, display emergent electrodynamics and can be moved by spin currents over macroscopic distances. These unique properties and their nanoscale size make them excellent candidates for the development of next-generation race-track memory and unconventional computing. A major challenge for these applications and the investigation of nanoscale magnetic structures in general is the realization of suitable detection schemes. We study magnetic disclinations, dislocations, and domain walls in FeGe and reveal pronounced responses that distinguish them from the helimagnetic background. A combination of magnetic force microscopy (MFM) and micromagnetic simulations links the response to the local magnetic susceptibility, that is, characteristic changes in the spin texture driven by the MFM tip. On the basis of the findings, which we explain using nonlinear response theory, we propose a read-out scheme using superconducting microcoils, presenting an innovative approach for detecting topological spin textures and domain walls in device-relevant geometries

Resonant Spin Excitation in an Overdoped High Temperature Superconductor

An inelastic neutron scattering study of overdoped Bi_2Sr_2CaCu_2O_{8+\delta} $ (T_c = 83 K) has revealed a resonant spin excitation in the superconducting state. The mode energy is E_res=38 meV, significantly lower than in optimally doped Bi_2Sr_2CaCu_2O_{8+\delta} (T_c = 91 K, E_ res =43 meV). This observation, which indicates a constant ratio E_res /k_B T_c \sim 5.4, helps resolve a long-standing controversy about the origin of the resonant spin excitation in high-temperature superconductors.Comment: final version: PRL 86, 1610 (2001

Transcriptomic analysis of cutaneous squamous cell carcinoma reveals a multi-gene prognostic signature associated with metastasis.

BackgroundMetastasis of cutaneous squamous cell carcinoma (cSCC) is uncommon. Current staging methods are reported to have sub-optimal performances in metastasis prediction. Accurate identification of patients with tumours at high risk of metastasis would have a significant impact on management.ObjectiveTo develop a robust and validated gene expression profile (GEP) signature for predicting primary cSCC metastatic risk using an unbiased whole transcriptome discovery-driven approach.MethodsArchival formalin-fixed paraffin-embedded primary cSCC with perilesional normal tissue from 237 immunocompetent patients (151 non-metastasising and 86 metastasising) were collected retrospectively from four centres. TempO-seq was used to probe the whole transcriptome and machine learning algorithms were applied to derive predictive signatures, with a 3:1 split for training and testing datasets.ResultsA 20-gene prognostic model was developed and validated, with an accuracy of 86.0%, sensitivity of 85.7%, specificity of 86.1%, and positive predictive value of 78.3% in the testing set, providing more stable, accurate prediction than pathological staging systems. A linear predictor was also developed, significantly correlating with metastatic risk.LimitationsThis was a retrospective 4-centre study and larger prospective multicentre studies are now required.ConclusionThe 20-gene signature prediction is accurate, with the potential to be incorporated into clinical workflows for cSCC

Transcriptomic analysis of cutaneous squamous cell carcinoma reveals a multi-gene prognostic signature associated with metastasis.

BACKGROUND: Metastasis of cutaneous squamous cell carcinoma (cSCC) is uncommon. Current staging methods are reported to have sub-optimal performances in metastasis prediction. Accurate identification of patients with tumours at high risk of metastasis would have a significant impact on management. OBJECTIVE: To develop a robust and validated gene expression profile (GEP) signature for predicting primary cSCC metastatic risk using an unbiased whole transcriptome discovery-driven approach. METHODS: Archival formalin-fixed paraffin-embedded primary cSCC with perilesional normal tissue from 237 immunocompetent patients (151 non-metastasising and 86 metastasising) were collected retrospectively from four centres. TempO-seq was used to probe the whole transcriptome and machine learning algorithms were applied to derive predictive signatures, with a 3:1 split for training and testing datasets. RESULTS: A 20-gene prognostic model was developed and validated, with an accuracy of 86.0%, sensitivity of 85.7%, specificity of 86.1%, and positive predictive value of 78.3% in the testing set, providing more stable, accurate prediction than pathological staging systems. A linear predictor was also developed, significantly correlating with metastatic risk. LIMITATIONS: This was a retrospective 4-centre study and larger prospective multicentre studies are now required. CONCLUSION: The 20-gene signature prediction is accurate, with the potential to be incorporated into clinical workflows for cSCC

Search for the Magnetic Monopole at a Magnetoelectric Surface

We show, by solving Maxwell’s equations, that an electric charge on the surface of a slab of a linear magnetoelectric material generates an image magnetic monopole below the surface provided that the magnetoelectric has a diagonal component in its magnetoelectric response. The image monopole, in turn, generates an ideal monopolar magnetic field outside of the slab. Using realistic values of the electric and magnetic field susceptibilities, we calculate the magnitude of the effect for the prototypical magnetoelectric material Cr2O3. We use low-energy muon spin rotation to measure the strength of the magnetic field generated by charged muons as a function of their distance from the surface of a Cr2O3 film and show that the results are consistent with the existence of the monopole. We discuss other possible routes to detecting the monopolar field, and show that, while the predicted monopolar field generated by Cr2O3 is above the detection limit for standard magnetic force microscopy, the detection of the field using this technique is prevented by surface charging effects