Swiss Federal Institute of Technology in Lausanne

Amyloid self‐assembly of α‐synuclein (αSyn) is linked to the pathogenesis of Parkinson’s disease (PD). Type 2 diabetes (T2D) has recently emerged as a risk factor for PD. Cross‐interactions between their amyloidogenic proteins may act as molecular links. In fact, fibrils of islet amyloid polypeptide (IAPP) (T2D) can cross‐seed αSyn amyloidogenesis and αSyn and IAPP colocalize in PD brains. Inhibition of both self‐ and IAPP‐cross‐seeded αSyn amyloidogenesis could thus interfere with PD pathogenesis. Here we show that macrocyclic peptides, designed to mimic IAPP self‐/cross‐interaction sites and previously found to inhibit amyloidogenesis of IAPP and/or Alzheimer’s disease (AD) amyloid‐β peptide Aβ40(42), are nanomolar inhibitors of both self‐ and IAPP‐cross‐seeded amyloid self‐assembly of αSyn. Anti‐amyloid function is mediated by nanomolar affinity interactions with αSyn via three αSyn regions which are identified as key sites of both αSyn self‐assembly and its cross‐interactions with IAPP. We also show that the peptides block Aβ42‐mediated cross‐seeding of αSyn as well. Based on their broad spectrum anti‐amyloid function and additional drug‐like features, these peptides are leads for multifunctional anti‐amyloid drugs in PD, T2D, AD, and their comorbidities, while the identified αSyn key segments are valuable targets for novel, multi‐site targeting amyloid inhibitors in PD and related synucleinopathies.

Amyloid self‐assembly of α‐synuclein (αSyn) is linked to the pathogenesis of Parkinson’s disease (PD). Type 2 diabetes (T2D) has recently emerged as a risk factor for PD. Cross‐interactions between their amyloidogenic proteins may act as molecular links. In fact, fibrils of islet amyloid polypeptide (IAPP) (T2D) can cross‐seed αSyn amyloidogenesis and αSyn and IAPP colocalize in PD brains. Inhibition of both self‐ and IAPP‐cross‐seeded αSyn amyloidogenesis could thus interfere with PD pathogenesis. Here we show that macrocyclic peptides, designed to mimic IAPP self‐/cross‐interaction sites and previously found to inhibit amyloidogenesis of IAPP and/or Alzheimer’s disease (AD) amyloid‐β peptide Aβ40(42), are nanomolar inhibitors of both self‐ and IAPP‐cross‐seeded amyloid self‐assembly of αSyn. Anti‐amyloid function is mediated by nanomolar affinity interactions with αSyn via three αSyn regions which are identified as key sites of both αSyn self‐assembly and its cross‐interactions with IAPP. We also show that the peptides block Aβ42‐mediated cross‐seeding of αSyn as well. Based on their broad spectrum anti‐amyloid function and additional drug‐like features, these peptides are leads for multifunctional anti‐amyloid drugs in PD, T2D, AD, and their comorbidities, while the identified αSyn key segments are valuable targets for novel, multi‐site targeting amyloid inhibitors in PD and related synucleinopathies.

Li‐TFSI/t‐BP is the most widely utilized p‐dopant for hole‐transporting materials (HTMs) in state‐of‐the‐art perovskite solar cells (PSCs). However, its nonuniformity of doping, along with the hygroscopicity and migration of dopants, results in the devices exhibiting limited stability and performance. This study reports on the utilization of a spherical anion derived from the p‐dopant, regulated by its radius and shape, as an alternative to the linear TFSI⁻ anion. The theoretical and experimental results reveal that the spherical anion significantly increases the doping effect of HTMs due to an enhanced electron transfer from larger dipole moments. The enhanced transfer leads to a shift in the Pb‐6p defect orbitals, resulting in shallower trap states. Moreover, compared to the linear structure of the TFSI⁻ anion, the anion of sodium tetrakis[3,5‐bis(trifluoro methyl)phenyl]borate (Na‐TFPB) with a larger van der Waals radius and spherical shape offers increased hydrophobicity and migration barriers, which can protect the perovskite crystal and facilitate stable p‐doping of HTMs. The use of Na‐TFPB results in enhanced thermal and ambient stability of PSCs. The devices fabricated with the shape‐ and radius‐regulated p‐dopant achieve remarkable efficiencies of 24.49 % and 24.31 % for CJ‐01 and spiro‐OMeTAD, respectively, representing the highest efficiency values for organic dopants to date. This study underscores the ingenious design of spherical anions of p‐dopants in contrast to the conventional linear anions.

Heat transfer differs in the regions where the flow is developed and developing thermally. These regions can be differentiated by using the thermal entry length. Many researchers have presented correlations to determine the thermal entry length for natural and forced convection. In this study, heat transfer in the entrance region of a concentric annuli is investigated. It is accepted that beginning from the inlet of annuli the flow is developed hydrodynamically and it is developing thermally. Heat transfer is investigated where the internal or external surfaces of the annuli are at constant but different heat fluxes. The fluid velocity is assumed to be constant or radially variable. Due to thermal boundary conditions, one thermal boundary layer appears on the outer cylinder surface, another on the inner cylinder surface. The edge of two boundary layers will be adiabatic and naturally, the temperature of fluid between the two edges will be equal to free stream temperature. Transformation, Separation of Variables method, eigenvalue problem, Sturm‐Liouville system, Bessel differential equation and properties of orthogonal functions are used in solution of the problem. Exact and analytical solutions of the momentum and energy equations are presented. Velocity and temperature distributions, local Nusselt numbers and convection heat transfer coefficients are calculated for the internal and external surfaces of annuli.

Our motivation in this paper is twofold. First, we study the geometry of a class of exploration sets, called exit sets, which are naturally associated with a 2D vector-valued Gaussian Free Field : $\phi : \mathbb {Z}^2 \rightarrow \mathbb {R}^N, N\ge 1$. We prove that, somewhat surprisingly, these sets are a.s. degenerate as long as $N\ge 2$, while they are conjectured to be macroscopic and fractal when N=1. This analysis allows us, when $N\ge 2$, to understand the percolation properties of the level sets of $\{ \Vert \phi (x)\Vert _{{2}}, x\in \mathbb {Z}^2\}$ and leads us to our second main motivation in this work: if one projects a spin O(N+1) model (the case N=2 corresponds to the classical Heisenberg model) down to a spin O(N) model, we end up with a spin O(N) in a quenched disorder given by random conductances on $\mathbb {Z}^2$. Using the exit sets of the N-vector-valued GFF, we obtain a local and geometric description of this random disorder in the limit $\beta \rightarrow \infty$. This allows us in particular to revisit a series of celebrated works by Patrascioiu and Seiler (J Stat Phys 69(3):573–595, 1992, Nucl Phys B Proc Suppl 30:184–191, 1993, J Stat Phys 106(3):811–826, 2002) which argued against Polyakov’s prediction that spin O(N+1) model is massive at all temperatures as long as $N\ge 2$ (Polyakov in Phys Lett B 59(1):79–81, 1975). We make part of their arguments rigorous and more importantly we provide the following counter-example: we build ergodic environments of (arbitrary) high conductances with (arbitrary) small and disconnected regions of low conductances in which, despite the predominance of high conductances, the XY model remains massive. Of independent interest, we prove that at high $\beta$, the fluctuations of a classical Heisenberg model near a north pointing spin are given by a N=2 vectorial GFF. This is implicit for example in Polyakov (1975) but we give here the first (non-trivial) rigorous proof. Also, independently of the recent work Dubédat and Falconet (Random clusters in the villain and xy models, arXiv preprint arXiv:2210.03620, 2022), we show that two-point correlation functions of the spin O(N) model can be given in terms of certain percolation events in the cable graph for any $N\ge 1$.

We formulate a connection between a topological and a geometric category. The former is the idempotent completion of the (horizontal) trace of the affine Hecke category, while the latter is the equivariant derived category of the (semi-nilpotent) commuting stack. This provides a more precise and improved version of our proposal in Gorsky and Neguț (Proc Lond Math Soc (3) 126(6): 2013–2056, 2023).

Background Bronchiolitis Obliterans Syndrome (BOS), a fibrotic airway disease that may develop after lung transplantation, conventionally relies on pulmonary function tests (PFTs) for diagnosis due to limitations of CT imaging. Deep neural networks (DNNs) have not previously been used for BOS detection. This study aims to train a DNN to detect BOS in CT scans using an approach tailored for low-data scenarios. Methods We trained a DNN to detect BOS in CT scans using a co-training method designed to enhance performance in low-data environments. Our method employs an auxiliary task that makes the DNN more sensitive to disease manifestations and less sensitive to the patient’s anatomical features. The DNN was tasked with predicting the sequence of two CT scans taken from the same BOS patient at least six months apart. We evaluated this approach on CT scans from 75 post-transplant patients, including 26 with BOS, and used a ROC-AUC metric to assess performance. Results We show that our DNN method achieves a ROC-AUC of 0.90 (95% CI: 0.840–0.953) in distinguishing BOS from non-BOS in CT scans. Performance correlates with BOS progression, with ROC-AUC values of 0.88 for stage I, 0.91 for stage II, and 0.94 for stage III BOS. Notably, the DNN shows comparable performance on standard- and high-resolution CT scans. It also demonstrates the ability to predict BOS in at-risk patients (FEV1 between 80% and 90% of best FEV1) with a ROC-AUC of 0.87 (95% CI: 0.735–0.974). Using visual interpretation techniques for DNNs, we reveal sensitivity to hyperlucent/hypoattenuated areas indicative of air-trapping or bronchiectasis. Conclusions Our approach shows potential for improving BOS diagnosis by enabling early detection and management. The ability to detect BOS from standard-resolution scans at any stage of respiration makes this method more accessible than previous approaches. Additionally, our findings highlight that techniques to limit overfitting are crucial for unlocking the potential of DNNs in low-data settings, which could assist clinicians in BOS studies with limited patient data.

Confined single metal atoms in graphene‐based materials have proven to be excellent catalysts for several reactions and promising gas sensing systems. However, whether the chemical activity arises from the specific type of metal atom or is a direct consequence of the confinement itself remains unclear. In this work, through a combined density functional theory and experimental surface science study, we address this question by investigating Co and Ni single atoms embedded in graphene (Gr) on a Ni(111) support. These two single atom catalysts (SACs) exhibit opposite behavior toward carbon monoxide (CO) gas molecules: at RT, CO binds stably to Co, whereas it does not to Ni. We rationalize this difference by the energy position of trapped metal dxz and dyz states involved in π backdonation to CO: while for Co, these states lie at the Fermi level, for Ni are located deep below it. This conclusion is corroborated by a proof‐of‐concept experiment, where a Gr/Ni(111) sample containing both stable Ni and Co single atoms was exposed to a CO partial pressure of 5 ‧ 10‐7 mbar. Scanning tunnelling microscopy (STM), X‐ray photoelectron spectroscopy (XPS), and temperature programmed desorption (TPD) measurements confirm the selective adsorption of CO on Co at RT.

Confined single metal atoms in graphene‐based materials have proven to be excellent catalysts for several reactions and promising gas sensing systems. However, whether the chemical activity arises from the specific type of metal atom or is a direct consequence of the confinement itself remains unclear. In this work, through a combined density functional theory and experimental surface science study, we address this question by investigating Co and Ni single atoms embedded in graphene (Gr) on a Ni(111) support. These two single atom catalysts (SACs) exhibit opposite behavior toward carbon monoxide (CO) gas molecules: at RT, CO binds stably to Co, whereas it does not to Ni. We rationalize this difference by the energy position of trapped metal dxz and dyz states involved in π backdonation to CO: while for Co, these states lie at the Fermi level, for Ni are located deep below it. This conclusion is corroborated by a proof‐of‐concept experiment, where a Gr/Ni(111) sample containing both stable Ni and Co single atoms was exposed to a CO partial pressure of 5 ‧ 10‐7 mbar. Scanning tunnelling microscopy (STM), X‐ray photoelectron spectroscopy (XPS), and temperature programmed desorption (TPD) measurements confirm the selective adsorption of CO on Co at RT.

This study investigates the stability and UV-blocking properties of cellulose nanofibril (CNF) and TEMPO-oxidized cellulose nanofibril (TOCNF) films, with and without lignin, under 1000 h of artificial sunlight. The literature to date provides no quantitative analysis of such films’ stability, however such insight is critical for optoelectronic applications for instance solar cells. This contribution examines the films from practical perspectives, considering aging with respect to their optical performance and retention of UV protective qualities. Films containing residual lignin (LignoCNF and LignoTOCNF), and lignin nanoparticles (CNF-LNP and TOCNF-LNP) demonstrated remarkable UV-blocking stability; even after the aging transmittance of LignoCNF and CNF-LNP films remained lower than 1% below 390 nm. Most lignin-containing films exhibited increased transmittance between 400 and 600 nm after aging, except for LignoTOCNF, which showed a decrease in transmittance that was comparable to that displayed by non-lignin films. Nevertheless, long-term light exposure induced a decrease in their mechanical properties. Tensile tests revealed increased brittleness in CNF and LignoCNF, while LNP-containing films showed reduced strain at the break. The observed changes were linked to the potential oxidation of COO- groups and structural modifications in both cellulose and lignin. Overall, the incorporation of lignin into nanocellulose films enhances their durability, UV protection, and mechanical stability, making them promising candidates for sustainable optoelectronic applications.

Increasing soil salinity causes significant crop losses globally; therefore, understanding plant responses to salt (sodium) stress is of high importance. Plants avoid sodium toxicity through subcellular compartmentation by intricate processes involving a high level of elemental interdependence. Current technologies to visualize sodium, in particular, together with other elements, are either indirect or lack in resolution. Here we used the newly developed cryo nanoscale secondary ion mass spectrometry ion microprobe¹, which allows high-resolution elemental imaging of cryo-preserved samples and reveals the subcellular distributions of key macronutrients and micronutrients in root meristem cells of Arabidopsis and rice. We found an unexpected, concentration-dependent change in sodium distribution, switching from sodium accumulation in the cell walls at low external sodium concentrations to vacuolar accumulation at stressful concentrations. We conclude that, in root meristems, a key function of the NHX family sodium/proton antiporter SALT OVERLY SENSITIVE 1 (also known as Na⁺/H⁺ exchanger 7; SOS1/NHX7) is to sequester sodium into vacuoles, rather than extrusion of sodium into the extracellular space. This is corroborated by the use of new genomic, complementing fluorescently tagged SOS1 variants. We show that, in addition to the plasma membrane, SOS1 strongly accumulates at late endosome/prevacuoles as well as vacuoles, supporting a role of SOS1 in vacuolar sodium sequestration.

Molecular recognition events between proteins drive biological processes in living systems¹. However, higher levels of mechanistic regulation have emerged, in which protein–protein interactions are conditioned to small molecules2, 3, 4–5. Despite recent advances, computational tools for the design of new chemically induced protein interactions have remained a challenging task for the field6,7. Here we present a computational strategy for the design of proteins that target neosurfaces, that is, surfaces arising from protein–ligand complexes. To develop this strategy, we leveraged a geometric deep learning approach based on learned molecular surface representations8,9 and experimentally validated binders against three drug-bound protein complexes: Bcl2–venetoclax, DB3–progesterone and PDF1–actinonin. All binders demonstrated high affinities and accurate specificities, as assessed by mutational and structural characterization. Remarkably, surface fingerprints previously trained only on proteins could be applied to neosurfaces induced by interactions with small molecules, providing a powerful demonstration of generalizability that is uncommon in other deep learning approaches. We anticipate that such designed chemically induced protein interactions will have the potential to expand the sensing repertoire and the assembly of new synthetic pathways in engineered cells for innovative drug-controlled cell-based therapies¹⁰.

Understanding thermodynamical measurement noise is of central importance for electrical and optical precision measurements. These range from semiconductor sensors, in which the Brownian motion of charge carriers poses limits, to optical reference cavities for atomic clocks or gravitational wave detection, which are limited by thermo-refractive and thermo-elastic noise. Here we find that charge-carrier density fluctuations give rise to a noise process in electro-optic photonic integrated circuits. We show that the noise exhibited by lithium niobate and lithium tantalate photonic integrated microresonators feature a frequency scaling to the power of −1.2, deviating from thermo-refractive noise theory. This noise is consistent with thermodynamical charge noise, which leads to electrical field fluctuations that are transduced via the strong Pockels effects of electro-optic materials. Our results establish electrical Johnson–Nyquist noise as the fundamental limitation for electro-optic integrated photonics, crucial for determining performance limits for both classical and quantum devices.

Degrowth‐oriented climate change mitigation policies offer inspiring possibilities for future societies. However, they require radical change to individual and collective behaviours; and research has not yet fully addressed how people may anticipate future loss and threat when confronted with such policies. This study proposes a twofold examination of anticipated reactions to pro‐environmental degrowth‐oriented minority influence. First, we conducted a qualitative study of 21 semi‐structured interviews. Both thematic analysis and consensual approach methodologies were adopted to explore emerging trends in the perception of a minority call to reduce human overpopulation, consumption of natural resources, and infrastructural incursions into nature. Results revealed three recurring themes: loss of individual freedom, fear of extremism, and loss of comfort. Second, a quantitative study ( N = 488) followed up these results by testing the hypothesis that anticipated loss would be associated to a gendered perception of threat. In line with our conjecture regarding the relationship between policy change, status quo preservation, and gender, moderation analysis showed that men reported more threat than women, the more perceptions of degrowth‐oriented policies were anticipated as a loss. Implications for a future‐forming approach of research and policy making are discussed considering perceiving radical pro‐environmental change as a threatening loss.

The alteration of neurovascular coupling (NVC), where acute localized blood flow increases following neural activity, plays a key role in several neurovascular processes including aging and neurodegeneration. While not equivalent to NVC, the coupling between simultaneously measured cerebral blood flow (CBF) with arterial spin labeling (ASL) and blood oxygenation dependent (BOLD) signals, can also be affected. Moreover, the acquisition of BOLD data allows the assessment of resting state (RS) fMRI metrics. In this study a multiband, multi-echo (MBME) pseudo-continuous ASL (pCASL) sequence was used to collect simultaneous BOLD and ASL data in a group of healthy control subjects, and the patterns of BOLD-CBF coupling were evaluated. Coupling was also correlated with the BOLD RS measures. The variability, reproducibility, and reliability of the metrics were also computed in a multi-session subgroup. Areas of higher coupling were observed in the visual, motor, parietal, and frontal cortices and corresponded to major brain networks. Areas of significant correlation between coupling and BOLD RS measures corresponded to areas of heightened coupling. Higher variability and lower reliability were found for coupling metrics compared to BOLD RS metrics. These results indicate BOLD-CBF coupling metrics may be useful for studying neurovascular physiology.

Artificial metalloenzymes (ArMs) enable the integration of abiotic cofactors within a native protein scaffold, allowing for non‐natural catalytic activities. Previous ArMs, however, have primarily relied on single cofactor systems, limiting them to only one catalytic function. Here we present an approach to construct ArMs embedding two catalytic cofactors based on the biotin‐streptavidin technology. By incorporating multiple catalytic cofactors into the four binding sites of streptavidin, we engineered programmable ArMs for tandem abiotic transformations including an enantioselective formal C−H hydroxylation and a photooxidation‐Michael addition. This work thus outlines a promising strategy for the development of ArMs embedding multiple cofactors.

One of the hypothesized functions of biomolecular condensates is to act as chemical reactors, where chemical reactions can be modulated, i.e., accelerated or slowed down, while substrate molecules enter and products exit from the condensate. Similarly, the components themselves that take part in the architectural integrity of condensates might be modified by active (energy consuming, non-equilibrium) processes, e.g., by ATPase chaperones or by kinases and phosphatases. In this work, we study how the presence of spatial inhomogeneities, such as in the case of liquid–liquid phase separation, affects active chemical reactions and results in the presence of directional flows of matter, which are one of the hallmarks of non-equilibrium processes. We establish the minimal conditions for the existence of such spatial currents, and we furthermore find that these fluxes are maximal at the condensate interface. These results propose that some condensates might be most efficient as chemical factories due to their interfaces rather than their volumes and could suggest a possible biological reason for the observed abundance of small non-fusing condensates inside the cell, thus maximizing their surface and the associated fluxes.

Background Lower respiratory tract infections (LRTIs) are among the most frequent infections and a significant contributor to inappropriate antibiotic prescription. Currently, no single diagnostic tool can reliably identify bacterial pneumonia. We thus evaluate a multimodal approach based on a clinical score, lung ultrasound (LUS), and the inflammatory biomarker, procalcitonin (PCT) to guide prescription of antibiotics. LUS outperforms chest X-ray in the identification of pneumonia, while PCT is known to be elevated in bacterial and/or severe infections. We propose a trial to test their synergistic potential in reducing antibiotic prescription while preserving patient safety in emergency departments (ED). Methods The PLUS-IS-LESS study is a pragmatic, stepped-wedge cluster-randomized, clinical trial conducted in 10 Swiss EDs. It assesses the PLUS algorithm, which combines a clinical prediction score, LUS, PCT, and a clinical severity score to guide antibiotics among adults with LRTIs, compared with usual care. The co-primary endpoints are the proportion of patients prescribed antibiotics and the proportion of patients with clinical failure by day 28. Secondary endpoints include measurement of change in quality of life, length of hospital stay, antibiotic-related side effects, barriers and facilitators to the implementation of the algorithm, cost-effectiveness of the intervention, and identification of patterns of pneumonia in LUS using machine learning. Discussion The PLUS algorithm aims to optimize prescription of antibiotics through improved diagnostic performance and maximization of physician adherence, while ensuring safety. It is based on previously validated tests and does therefore not expose participants to unforeseeable risks. Cluster randomization prevents cross-contamination between study groups, as physicians are not exposed to the intervention during or before the control period. The stepped-wedge implementation of the intervention allows effect calculation from both between- and within-cluster comparisons, which enhances statistical power and allows smaller sample size than a parallel cluster design. Moreover, it enables the training of all centers for the intervention, simplifying implementation if the results prove successful. The PLUS algorithm has the potential to improve the identification of LRTIs that would benefit from antibiotics. When scaled, the expected reduction in the proportion of antibiotics prescribed has the potential to not only decrease side effects and costs but also mitigate antibiotic resistance. Trial registration This study was registered on July 19, 2022, on the ClinicalTrials.gov registry using reference number: NCT05463406. Trial status Recruitment started on December 5, 2022, and will be completed on November 3, 2024. Current protocol version is version 3.0, dated April 3, 2023.