Background-deflection Brillouin microscopy reveals altered biomechanics of intracellular stress granules by ALS protein FUS

Altered cellular biomechanics have been implicated as key photogenic triggers in age-related diseases. An aberrant liquid-to-solid phase transition, observed in in vitro reconstituted droplets of FUS protein, has been recently proposed as a possible pathogenic mechanism for amyotrophic lateral sclerosis (ALS). Whether such transition occurs in cell environments is currently unknown as a consequence of the limited measuring capability of the existing techniques, which are invasive or lack of subcellular resolution. Here we developed a non-contact and label-free imaging method, named background-deflection Brillouin microscopy, to investigate the three-dimensional intracellular biomechanics at a sub-micron resolution. Our method exploits diffraction to achieve an unprecedented 10,000-fold enhancement in the spectral contrast of single-stage spectrometers, enabling, to the best of our knowledge, the first direct biomechanical analysis on intracellular stress granules containing ALS mutant FUS protein in fixed cells. Our findings provide fundamental insights on the critical aggregation step underlying the neurodegenerative ALS disease

Insight on Hole-Hole Interaction and Magnetic Order from Dichroic Auger-Photoelectron Coincidence Spectra

The absence of sharp structures in the core-valence-valence Auger line shapes of partially filled bands has severely limited the use of electron spectroscopy in magnetic crystals and other correlated materials. Here by a novel interplay of experimental and theoretical techniques we achieve a combined understanding of the Photoelectron, Auger %$M_{23}M_{45}M_{45}$ and Auger-Photoelectron Coincidence Spectra (APECS) of CoO. This is a prototype antiferromagnetic material in which the recently discovered Dichroic Effect in Angle Resolved (DEAR) APECS reveals a complex pattern in the strongly correlated Auger line shape. A calculation of the \textit{unrelaxed} spectral features explains the pattern in detail, labeling the final states by the total spin. The present theoretical analysis shows that the dichroic effect arises from a spin-dependence of the angular distribution of the photoelectron-Auger electron pair detected in coincidence, and from the selective power of the dichroic technique in assigning different weights to the various spin components. Since the spin-dependence of the angular distribution exists in the antiferromagnetic state but vanishes at the N\'eel temperature, the DEAR-APECS technique detects the phase transition from its local effects, thus providing a unique tool to observe and understand magnetic correlations in such circumstances, where the usual methods (neutron diffraction, specific heat measurements) are not applicable.Comment: Accepted by: Physical Review Letter

Global Transformer Architecture for Indoor Room Temperature Forecasting

A thorough regulation of building energy systems translates in relevant energy savings and in a better comfort for the occupants. Algorithms to predict the thermal state of a building on a certain time horizon with a good confidence are essential for the implementation of effective control systems. This work presents a global Transformer architecture for indoor temperature forecasting in multi-room buildings, aiming at optimizing energy consumption and reducing greenhouse gas emissions associated with HVAC systems. Recent advancements in deep learning have enabled the development of more sophisticated forecasting models compared to traditional feedback control systems. The proposed global Transformer architecture can be trained on the entire dataset encompassing all rooms, eliminating the need for multiple room-specific models, significantly improving predictive performance, and simplifying deployment and maintenance. Notably, this study is the first to apply a Transformer architecture for indoor temperature forecasting in multi-room buildings. The proposed approach provides a novel solution to enhance the accuracy and efficiency of temperature forecasting, serving as a valuable tool to optimize energy consumption and decrease greenhouse gas emissions in the building sector.publishedVersio

Global Transformer Architecture for Indoor Room Temperature Forecasting

A thorough regulation of building energy systems translates in relevant energy savings and in a better comfort for the occupants. Algorithms to predict the thermal state of a building on a certain time horizon with a good confidence are essential for the implementation of effective control systems. This work presents a global Transformer architecture for indoor temperature forecasting in multi-room buildings, aiming at optimizing energy consumption and reducing greenhouse gas emissions associated with HVAC systems. Recent advancements in deep learning have enabled the development of more sophisticated forecasting models compared to traditional feedback control systems. The proposed global Transformer architecture can be trained on the entire dataset encompassing all rooms, eliminating the need for multiple room-specific models, significantly improving predictive performance, and simplifying deployment and maintenance. Notably, this study is the first to apply a Transformer architecture for indoor temperature forecasting in multi-room buildings. The proposed approach provides a novel solution to enhance the accuracy and efficiency of temperature forecasting, serving as a valuable tool to optimize energy consumption and decrease greenhouse gas emissions in the building sector

Electronic structure of copper phthalocyanine:An experimental and theoretical study of occupied and unoccupied levels

An experimental and theoretical study of the electronic structure of copper phthalocyanine (CuPc) molecule is presented. We performed x-ray photoemission spectroscopy (XPS) and photoabsorption [x-ray absorption near-edge structure (XANES)] gas phase experiments and we compared the results with self-consistent field, density functional theory (DFT), and static-exchange theoretical calculations. In addition, ultraviolet photoelectron spectra (UPS) allowed disentangling several outer molecular orbitals. A detailed study of the two highest occupied orbitals (having a(1u) and b(1g) symmetries) is presented: the high energy resolution available for UPS measurements allowed resolving an extra feature assigned to vibrational stretching in the pyrrole rings. This observation, together with the computed DFT electron density distributions of the outer valence orbitals, suggests that the a(1u) orbital (the highest occupied molecular orbital) is mainly localized on the carbon atoms of pyrrole rings and it is doubly occupied, while the b(1g) orbital, singly occupied, is mainly localized on the Cu atom. Ab initio calculations of XPS and XANES spectra at carbon K-edge of CuPc are also presented. The comparison between experiment and theory revealed that, in spite of being formally not equivalent, carbon atoms of the benzene rings experience a similar electronic environment. Carbon K-edge absorption spectra were interpreted in terms of different contributions coming from chemically shifted C 1s orbitals of the nonequivalent carbon atoms on the inner ring of the molecule formed by the sequence of CN bonds and on the benzene rings, respectively, and also in terms of different electronic distributions of the excited lowest unoccupied molecular orbital (LUMO) and LUMO+1. In particular, the degenerate LUMO appears to be mostly localized on the inner pyrrole ring

Carbon nanostructures for directional light dark matter detection

Carbon nanostructures offer exciting new possibilities in the detection of light dark matter. A darkmatter particle with mass between 1 MeV and 1 GeV scattering off an electron in the carbon wouldtransfer sufficient energy to extract the electron from the lattice. In 2D materials, such as grapheneor carbon nanotubes, these electrons would be released directly into the vacuum, avoiding theirre-absorption in the medium. We present two novel detector concepts: a ’Graphene-FET’ design,based on graphene sheets, developed at Princeton University; and a ’Dark-PMT’ based on alignedcarbon nanotubes, developed in University of Rome Sapienza. We discuss their light dark matterdiscovery potential, the status of the RD, and the recent commissioning of a state-of-the-art carbonnanotube growing facility in Rome

Metabolic Reprogramming of Cancer Associated Fibroblasts: The Slavery of Stromal Fibroblasts

Cancer associated fibroblasts (CAFs) are the main stromal cell type of solid tumour microenvironment and undergo an activation process associated with secretion of growth factors, cytokines, and paracrine interactions. One of the important features of solid tumours is the metabolic reprogramming that leads to changes of bioenergetics and biosynthesis in both tumour cells and CAFs. In particular, CAFs follow the evolution of tumour disease and acquire a catabolic phenotype: in tumour tissues, cancer cells and tumour microenvironment form a network where the crosstalk between cancer cells and CAFs is associated with cell metabolic reprogramming that contributes to CAFs activation, cancer growth, and progression and evasion from cancer therapies. In this regard, the study of CAFs metabolic reprogramming could contribute to better understand their activation process, the interaction between stroma, and cancer cells and could offer innovative tools for the development of new therapeutic strategies able to eradicate the protumorigenic activity of CAFs. Therefore, this review focuses on CAFs metabolic reprogramming associated with both differentiation process and cancer and stromal cells crosstalk. Finally, therapeutic responses and potential anticancer strategies targeting CAFs metabolic reprogramming are reviewed