The Hottest Spot on Campus

This book presents the result of an innovative challenge, to create a systematic literature overview driven by machine-generated content. Questions and related keywords were prepared for the machine to query, discover, collate and structure by Artificial Intelligence (AI) clustering. The AI-based approach seemed especially suitable to provide an innovative perspective as the topics are indeed both complex, interdisciplinary and multidisciplinary, for example, climate, planetary and evolution sciences. Springer Nature has published much on these topics in its journals over the years, so the challenge was for the machine to identify the most relevant content and present it in a structured way that the reader would find useful. The automatically generated literature summaries in this book are intended as a springboard to further discoverability. They are particularly useful to readers with limited time, looking to learn more about the subject quickly and especially if they are new to the topics. Springer Nature seeks to support anyone who needs a fast and effective start in their content discovery journey, from the undergraduate student exploring interdisciplinary content to Master- or PhD-thesis developing research questions, to the practitioner seeking support materials, this book can serve as an inspiration, to name a few examples. 

It is important to us as a publisher to make the advances in technology easily accessible to our authors and find new ways of AI-based author services that allow human-machine interaction to generate readable, usable, collated, research content.

Context. Blazars are beamed active galactic nuclei (AGNs) known for their strong multi-wavelength variability on timescales ranging from years down to minutes. Many different models have been proposed to explain this variability.

Aims. We aim to investigate the suitability of the twisting jet model presented in previous works to explain the multi-wavelength behaviour of BL Lacertae, the prototype of one of the blazar classes. According to this model, the jet is inhomogeneous, curved, and twisting, and the long-term variability is due to changes in the Doppler factor due to variations in the orientation of the jet-emitting regions.

Methods. We analysed optical data of the source obtained during monitoring campaigns organised by the Whole Earth Blazar Telescope (WEBT) in 2019–2022, together with radio data from the WEBT and other teams, and γ-ray data from the Fermi satellite. In this period, BL Lacertae underwent an extraordinary activity phase, reaching its historical optical and γ-ray brightness maxima.

Results. The application of the twisting jet model to the source light curves allows us to infer the wiggling motion of the optical, radio, and γ-ray jet-emitting regions. The optical-radio correlation shows that the changes in the radio viewing angle follow those in the optical viewing angle by about 120 days, and it suggests that the jet is composed of plasma filaments, which is in agreement with some radio high-resolution observations of other sources. The γ-ray emitting region is found to be co-spatial with the optical one, and the analysis of the γ-optical correlation is consistent with both the geometric interpretation and a synchrotron self-Compton (SSC) origin of the high-energy photons.

Conclusions. We propose a geometric scenario where the jet is made up of a pair of emitting plasma filaments in a sort of double-helix curved rotating structure, whose wiggling motion produces changes in the Doppler beaming and can thus explain the observed multi-wavelength long-term variability.

Purpose

To examine the associations and substitutions of dietary sugars [extrinsic (free) or intrinsic (non-free)] as well as dietary starch and fiber intakes for indices of body fat and cardiometabolic health.

Methods

Dietary intake was assessed at multiple times using multi-day 24-hour recalls over 18-months for indices of body fat (body fat %, waist circumference, BMI, and weight change) (n = 1066) and at baseline and 12 months for cardiometabolic outcomes (LDL, HDL, HbA1c) (n = 736). Bayesian modeling was applied to analyze the probabilistic impact of dietary carbohydrate components using credible intervals for association and substitution analyses with repeated measures random effects modeling.

Results

A higher starch intake significantly associated with higher body fat %, BMI and waist circumference (WC) (all CrI > 0). Conversely, intrinsic sugar and fiber intakes were significantly linked to lower body fat indices, while free sugar showed no association. A 20 g substitution of free sugars with intrinsic sugars significantly associated with lower body fat (CrI: -4.2; -1.0%), BMI (CrI: -1.8; -0.4) and WC (CrI: -4.2; -1.0 cm), while substituting intrinsic sugars with starch resulted in significantly higher body fat, BMI, WC and weight change. Replacing starch with fiber associated with higher HDL-C (CrI: -0.0; 0.3) and lower LDL-C (CrI: -0.6; 0.1). Replacing free sugars with starch associated with a higher HbA1c level (CrI: 0.0;0.2).

Conclusion

These results underscore the importance of distinguishing between intrinsic versus extrinsic sugars and highlight the potential benefits of increasing intrinsic sugars and fiber while reducing starch for better body fat management and cardiometabolic health.

Obtaining microscopic structure-property relationships for grain boundaries is challenging due to their complex atomic structures. Recent efforts use machine learning to derive these relationships, but the way the atomic grain boundary structure is represented can have a significant impact on the predictions. Key steps for property prediction common to grain boundaries and other variable-sized atom clustered structures include: (1) describing the atomic structure as a feature matrix, (2) transforming the variable-sized feature matrix to a fixed length common to all structures, and (3) applying a machine learning algorithm to predict properties from the transformed matrices. We examine how these steps and different combinations of engineered features impact the accuracy of grain boundary energy predictions using a database of over 7000 grain boundaries. Additionally, we assess how different engineered features support interpretability, offering insights into the physics of the structure-property relationships.

Context. The BL Lac object 3C 371 is one of the targets regularly monitored by the Whole-Earth Blazar Telescope (WEBT), a collaboration of observers studying blazar variability on both short and long timescales.

Aims. We aim to evaluate the long-term multi-wavelength (MWL) behaviour of 3C 371, comparing it with results derived from its optical emission in our previous study. For this, we make use of the multi-band campaigns organised by the WEBT collaboration in optical and radio between January 2018 and December 2020, and of public data from Swift and Fermi satellites and the MOJAVE Very Large Interferometry programme.

Methods. We evaluated the variability shown by the source in each band by quantifying the amplitude variability parameter, and also looked for a possible inter-band correlation using the z-discrete correlation function. We also present a deep analysis of the optical-UV, X-ray, and γ-ray spectral variability. With the MOJAVE data, we performed a kinematics analysis, looking for components propagating along the jet and calculating its kinematics parameters. We then used this set of parameters to interpret the source MWL behaviour, modelling its broadband spectral energy distribution (SED) with theoretical blazar emission scenarios.

Results. The MWL variability of the source in the UV, X-ray, and γ-ray bands is comparable to that in optical, especially considering the lower coverage of the first two wavebands. On the other hand, the radio bands show variability of much lower magnitude. Moreover, this MWL emission shows a high degree of correlation, which is compatible with zero lag, again with the exception of the radio emission. The radio VLBI images reveal super-luminal motion of one of the identified components, which we used to set constraints on the jet kinematics and parameters, and to estimate a viewing angle of θ = (9.6 ± 1.6)°, a Doppler factor of δ = 6.0 ± 1.1, and a Lorentz factor of Γ = 6.0 ± 1.8. The polarised radio emission was found to be anti-correlated with the total flux, and to follow the same behaviour as the polarised optical radiation. The optical-UV spectral behaviour shows a mild harder-when-brighter trend on long timescales, and other trends such as redder-when-brighter on shorter timescales. We successfully modelled the broadband emission with a leptonic scenario, where we compared the low and high emission states during the period of complete MWL coverage. The difference between these two states can be ascribed mainly to a hardening of the distribution of particles. The derived features of the source confirm that 3C 371 is a BL Lac whose jet is not well aligned with the line of sight.

Apolipoprotein E (ApoE) polymorphisms modify the risk of Alzheimer’s disease with ApoE4 strongly increasing and ApoE2 modestly decreasing risk relative to the control ApoE3. To investigate how ApoE isoforms alter risk, we measured changes in proteome homeostasis in transgenic mice expressing a human ApoE gene (isoform 2, 3, or 4). The regulation of each protein’s homeostasis is observed by measuring turnover rate and abundance for that protein. We identified 4849 proteins and tested for ApoE isoform-dependent changes in the homeostatic regulation of ~2700 ontologies. In the brain, we found that ApoE4 and ApoE2 both lead to modified regulation of mitochondrial membrane proteins relative to the wild-type control ApoE3. In ApoE4 mice, lack of cohesion between mitochondrial membrane and matrix proteins suggests that dysregulation of proteasome and autophagy is reducing protein quality. In ApoE2, proteins of the mitochondrial matrix and the membrane, including oxidative phosphorylation complexes, had a similar increase in degradation which suggests coordinated replacement of the entire organelle. In the liver we did not observe these changes suggesting that the ApoE-effect on proteostasis is amplified in the brain relative to other tissues. Our findings underscore the utility of combining protein abundance and turnover rates to decipher proteome regulatory mechanisms and their potential role in biology.