Transciptome Analysis Illuminates the Nature of the Intracellular Interaction in a Vertebrate-Algal Symbiosis

During embryonic development, cells of the green alga Oophila amblystomatis enter cells of the salamander Ambystoma maculatum forming an endosymbiosis. Here, using de novo dual-RNA seq, we compared the host salamander cells that harbored intracellular algae to those without algae and the algae inside the animal cells to those in the egg capsule. This two-by-two-way analysis revealed that intracellular algae exhibit hallmarks of cellular stress and undergo a striking metabolic shift from oxidative metabolism to fermentation. Culturing experiments with the alga showed that host glutamine may be utilized by the algal endosymbiont as a primary nitrogen source. Transcriptional changes in salamander cells suggest an innate immune response to the alga, with potential attenuation of NF-κB, and metabolic alterations indicative of modulation of insulin sensitivity. In stark contrast to its algal endosymbiont, the salamander cells did not exhibit major stress responses, suggesting that the host cell experience is neutral or beneficial

Screening of Irish Fruit and Vegetable Germplasm for Novel Anti-tumour and Pesticidal Compounds

Conference paperPhytochemicals are a rich source of novel therapeutic and insecticidal agents (McLaughlin and Chang, 1999). Considerable research effort has been directed at screening exotic and medicinal plants in the search for novel products. However, plants which have traditional food uses have been little explored. In addition the range, type and level of individual bioactive compounds can vary significantly between different species, different cultivars of the same species and different tissue types of the plant (Reilly, in press) Therefore, the objective of this study was to screen a range of fruits and vegetables which can be grown in Ireland for novel bioactive compounds for use in food production and as bio-pesticides.The author wishes to acknowledge the financial support from the Dublin Institute of Technology through an ABBEST fellowshi

Emergence of a Dynamic Super-Structural Order Integrating Antiferroelectric and Antiferrodistortive Competing Instabilities in EuTiO3

Microscopic structural instabilities of EuTiO3 single crystal were investigated by synchrotron x-ray diffraction. Antiferrodistortive (AFD) oxygen octahedral rotational order was observed alongside Ti derived antiferroelectric (AFE) distortions. The competition between the two instabilities is reconciled through a cooperatively modulated structure allowing both to coexist. The electric and magnetic field effect on the modulated AFD order shows that the origin of large magnetoelectric coupling is based upon the dynamic equilibrium between the AFD - antiferromagnetic interactions versus the electric polarization - ferromagnetic interactions

The Thermal Properties of Solar Flares Over Three Solar Cycles Using GOES X-ray Observations

Solar flare X-ray emission results from rapidly increasing temperatures and emission measures in flaring active region loops. To date, observations from the X-Ray Sensor (XRS) onboard the Geostationary Operational Environmental Satellite (GOES) have been used to derive these properties, but have been limited by a number of factors, including the lack of a consistent background subtraction method capable of being automatically applied to large numbers of flares. In this paper, we describe an automated temperature and emission measure-based background subtraction method (TEBBS), which builds on the methods of Bornmann (1990). Our algorithm ensures that the derived temperature is always greater than the instrumental limit and the pre-flare background temperature, and that the temperature and emission measure are increasing during the flare rise phase. Additionally, TEBBS utilizes the improved estimates of GOES temperatures and emission measures from White et al. (2005). TEBBS was successfully applied to over 50,000 solar flares occurring over nearly three solar cycles (1980-2007), and used to create an extensive catalog of the solar flare thermal properties. We confirm that the peak emission measure and total radiative losses scale with background subtracted GOES X-ray flux as power-laws, while the peak temperature scales logarithmically. As expected, the peak emission measure shows an increasing trend with peak temperature, although the total radiative losses do not. While these results are comparable to previous studies, we find that flares of a given GOES class have lower peak temperatures and higher peak emission measures than previously reported. The resulting TEBBS database of thermal flare plasma properties is publicly available on Solar Monitor (www.solarmonitor.org/TEBBS/) and will be available on Heliophysics Integrated Observatory (www.helio-vo.eu)

Verification of the Socio-Technical Aspects of Voting: The Case of the Polish Postal Vote 2020

Voting procedures are designed and implemented by people, for people, and with significant human involvement. Thus, one should take into account the human factors in order to comprehensively analyze properties of an election and detect threats. In particular, it is essential to assess how actions and strategies of the involved agents (voters, municipal office employees, mail clerks) can influence the outcome of other agents' actions as well as the overall outcome of the election. In this paper, we present our first attempt to capture those aspects in a formal multi-agent model of the Polish presidential election 2020. The election marked the first time when postal vote was universally available in Poland. Unfortunately, the voting scheme was prepared under time pressure and political pressure, and without the involvement of experts. This might have opened up possibilities for various kinds of ballot fraud, in-house coercion, etc. We propose a preliminary scalable model of the procedure in the form of a Multi-Agent Graph, and formalize selected integrity and security properties by formulas of agent logics. Then, we transform the models and formulas so that they can be input to the state-of-art model checker Uppaal. The first series of experiments demonstrates that verification scales rather badly due to the state-space explosion. However, we show that a recently developed technique of user-friendly model reduction by variable abstraction allows us to verify more complex scenarios

One-Component Order Parameter in URu2_2Si2_2 Uncovered by Resonant Ultrasound Spectroscopy and Machine Learning

The unusual correlated state that emerges in URu$_2$Si$_2$ below T$_{HO}$ = 17.5 K is known as "hidden order" because even basic characteristics of the order parameter, such as its dimensionality (whether it has one component or two), are "hidden". We use resonant ultrasound spectroscopy to measure the symmetry-resolved elastic anomalies across T$_{HO}$. We observe no anomalies in the shear elastic moduli, providing strong thermodynamic evidence for a one-component order parameter. We develop a machine learning framework that reaches this conclusion directly from the raw data, even in a crystal that is too small for traditional resonant ultrasound. Our result rules out a broad class of theories of hidden order based on two-component order parameters, and constrains the nature of the fluctuations from which unconventional superconductivity emerges at lower temperature. Our machine learning framework is a powerful new tool for classifying the ubiquitous competing orders in correlated electron systems