bluuebunny/crossref_metadata_2025_split huggingface dataset:
Tomography of memory engrams in self-organizing nanowire connectomes
Authors: Milano Gianluca , Cultrera Alessandro , Boarino Luca , Callegaro Luca , Ricciardi Carlo 
Published: September 2023

AbstractSelf-organizing memristive nanowire connectomes have been exploited for physical (in materia) implementation of brain-inspired computing paradigms. Despite having been shown that the emergent behavior relies on weight plasticity at single junction/synapse level and on wiring plasticity involving topological changes, a shift to multiterminal paradigms is needed to unveil dynamics at the network level. Here, we report on tomographical evidence of memory engrams (or memory traces) in nanowire connectomes, i.e., physicochemical changes in biological neural substrates supposed to endow the representation of experience stored in the brain. An experimental/modeling approach shows that spatially correlated short-term plasticity effects can turn into long-lasting engram memory patterns inherently related to network topology inhomogeneities. The ability to exploit both encoding and consolidation of information on the same physical substrate would open radically new perspectives for in materia computing, while offering to neuroscientists an alternative platform to understand the role of memory in learning and knowledge.
An all 2D bio-inspired gustatory circuit for mimicking physiology and psychology of feeding behavior
Authors: Ghosh Subir , Pannone Andrew , Sen Dipanjan , Wali Akshay , Ravichandran Harikrishnan , Das Saptarshi 
Published: September 2023

AbstractAnimal behavior involves complex interactions between physiology and psychology. However, most AI systems neglect psychological factors in decision-making due to a limited understanding of the physiological-psychological connection at the neuronal level. Recent advancements in brain imaging and genetics have uncovered specific neural circuits that regulate behaviors like feeding. By developing neuro-mimetic circuits that incorporate both physiology and psychology, a new emotional-AI paradigm can be established that bridges the gap between humans and machines. This study presents a bio-inspired gustatory circuit that mimics adaptive feeding behavior in humans, considering both physiological states (hunger) and psychological states (appetite). Graphene-based chemitransistors serve as artificial gustatory taste receptors, forming an electronic tongue, while 1L-MoS2 memtransistors construct an electronic-gustatory-cortex comprising a hunger neuron, appetite neuron, and feeding circuit. This work proposes a novel paradigm for emotional neuromorphic systems with broad implications for human health. The concept of gustatory emotional intelligence can extend to other sensory systems, benefiting future humanoid AI.
Social isolation shortens lifespan through oxidative stress in ants
Authors: Koto Akiko , Tamura Makoto , Wong Pui Shan , Aburatani Sachiyo , Privman Eyal , Stoffel Céline , Crespi Alessandro , McKenzie Sean Keane , La Mendola Christine , Kay Tomas , Keller Laurent 
Published: September 2023

AbstractSocial isolation negatively affects health, induces detrimental behaviors, and shortens lifespan in social species. Little is known about the mechanisms underpinning these effects because model species are typically short-lived and non-social. Using colonies of the carpenter ant Camponotus fellah, we show that social isolation induces hyperactivity, alters space-use, and reduces lifespan via changes in the expression of genes with key roles in oxidation-reduction and an associated accumulation of reactive oxygen species. These physiological effects are localized to the fat body and oenocytes, which perform liver-like functions in insects. We use pharmacological manipulations to demonstrate that the oxidation-reduction pathway causally underpins the detrimental effects of social isolation on behavior and lifespan. These findings have important implications for our understanding of how social isolation affects behavior and lifespan in general.
Proteomic and genetic analyses of influenza A viruses identify pan-viral host targets
Authors: Haas Kelsey M. , McGregor Michael J. , Bouhaddou Mehdi , Polacco Benjamin J. , Kim Eun-Young , Nguyen Thong T. , Newton Billy W. , Urbanowski Matthew , Kim Heejin , Williams Michael A. P. , Rezelj Veronica V. , Hardy Alexandra , Fossati Andrea , Stevenson Erica J. , Sukerman Ellie , Kim Tiffany , Penugonda Sudhir , Moreno Elena , Braberg Hannes , Zhou Yuan , Metreveli Giorgi , Harjai Bhavya , Tummino Tia A. , Melnyk James E. , Soucheray Margaret , Batra Jyoti , Pache Lars , Martin-Sancho Laura , Carlson-Stevermer Jared , Jureka Alexander S. , Basler Christopher F. , Shokat Kevan M. , Shoichet Brian K. , Shriver Leah P. , Johnson Jeffrey R. , Shaw Megan L. , Chanda Sumit K. , Roden Dan M. , Carter Tonia C. , Kottyan Leah C. , Chisholm Rex L. , Pacheco Jennifer A. , Smith Maureen E. , Schrodi Steven J. , Albrecht Randy A. , Vignuzzi Marco , Zuliani-Alvarez Lorena , Swaney Danielle L. , Eckhardt Manon , Wolinsky Steven M. , White Kris M. , Hultquist Judd F. , Kaake Robyn M. , García-Sastre Adolfo , Krogan Nevan J. 
Published: September 2023

AbstractInfluenza A Virus (IAV) is a recurring respiratory virus with limited availability of antiviral therapies. Understanding host proteins essential for IAV infection can identify targets for alternative host-directed therapies (HDTs). Using affinity purification-mass spectrometry and global phosphoproteomic and protein abundance analyses using three IAV strains (pH1N1, H3N2, H5N1) in three human cell types (A549, NHBE, THP-1), we map 332 IAV-human protein-protein interactions and identify 13 IAV-modulated kinases. Whole exome sequencing of patients who experienced severe influenza reveals several genes, including scaffold protein AHNAK, with predicted loss-of-function variants that are also identified in our proteomic analyses. Of our identified host factors, 54 significantly alter IAV infection upon siRNA knockdown, and two factors, AHNAK and coatomer subunit COPB1, are also essential for productive infection by SARS-CoV-2. Finally, 16 compounds targeting our identified host factors suppress IAV replication, with two targeting CDK2 and FLT3 showing pan-antiviral activity across influenza and coronavirus families. This study provides a comprehensive network model of IAV infection in human cells, identifying functional host targets for pan-viral HDT.
Terahertz Néel spin-orbit torques drive nonlinear magnon dynamics in antiferromagnetic Mn2Au
Authors: Behovits Y. , Chekhov A. L. , Bodnar S. Yu. , Gueckstock O. , Reimers S. , Lytvynenko Y. , Skourski Y. , Wolf M. , Seifert T. S. , Gomonay O. , Kläui M. , Jourdan M. , Kampfrath T. 
Published: September 2023

AbstractAntiferromagnets have large potential for ultrafast coherent switching of magnetic order with minimum heat dissipation. In materials such as Mn2Au and CuMnAs, electric rather than magnetic fields may control antiferromagnetic order by Néel spin-orbit torques (NSOTs). However, these torques have not yet been observed on ultrafast time scales. Here, we excite Mn2Au thin films with phase-locked single-cycle terahertz electromagnetic pulses and monitor the spin response with femtosecond magneto-optic probes. We observe signals whose symmetry, dynamics, terahertz-field scaling and dependence on sample structure are fully consistent with a uniform in-plane antiferromagnetic magnon driven by field-like terahertz NSOTs with a torkance of (150 ± 50) cm2 A−1 s−1. At incident terahertz electric fields above 500 kV cm−1, we find pronounced nonlinear dynamics with massive Néel-vector deflections by as much as 30°. Our data are in excellent agreement with a micromagnetic model. It indicates that fully coherent Néel-vector switching by 90° within 1 ps is within close reach.
Time-dependent memory transformation in hippocampus and neocortex is semantic in nature
Authors: Krenz Valentina , Alink Arjen , Sommer Tobias , Roozendaal Benno , Schwabe Lars 
Published: September 2023

AbstractMemories undergo a time-dependent neural reorganization, which is assumed to be accompanied by a transformation from detailed to more gist-like memory. However, the nature of this transformation and its underlying neural mechanisms are largely unknown. Here, we report that the time-dependent transformation of memory is semantic in nature, while we find no credible evidence for a perceptual transformation. Model-based MRI analyses reveal time-dependent increases in semantically transformed representations of events in prefrontal and parietal cortices, while specific pattern representations in the anterior hippocampus decline over time. Posterior hippocampal memory reinstatement, in turn, increases over time and is linked to the semantic gist of the original memory, without a statistically significant link to perceptual details. These findings indicate that qualitative changes in memory over time, associated with distinct representational changes in the neocortex and within the hippocampus, reflect a semantic transformation, which may promote the integration of memories into abstract knowledge structures.
Activating lattice oxygen in high-entropy LDH for robust and durable water oxidation
Authors: Wang Fangqing , Zou Peichao , Zhang Yangyang , Pan Wenli , Li Ying , Liang Limin , Chen Cong , Liu Hui , Zheng Shijian 
Published: September 2023

AbstractThe oxygen evolution reaction is known to be a kinetic bottleneck for water splitting. Triggering the lattice oxygen oxidation mechanism (LOM) can break the theoretical limit of the conventional adsorbate evolution mechanism and enhance the oxygen evolution reaction kinetics, yet the unsatisfied stability remains a grand challenge. Here, we report a high-entropy MnFeCoNiCu layered double hydroxide decorated with Au single atoms and O vacancies (AuSA-MnFeCoNiCu LDH), which not only displays a low overpotential of 213 mV at 10 mA cm−2 and high mass activity of 732.925 A g−1 at 250 mV overpotential in 1.0 M KOH, but also delivers good stability with 700 h of continuous operation at ~100 mA cm−2. Combining the advanced spectroscopic techniques and density functional theory calculations, it is demonstrated that the synergistic interaction between the incorporated Au single atoms and O vacancies leads to an upshift in the O 2p band and weakens the metal-O bond, thus triggering the LOM, reducing the energy barrier, and boosting the intrinsic activity.
Sucrose substitution in cake systems is not a piece of cake
Authors: Godefroidt Thibault , Riley Isabella M. , Ooms Nand , Bosmans Geertrui M. , Brijs Kristof , Delcour Jan A. 
Published: September 2023

AbstractSuccessful sucrose replacement in cake systems requires thorough understanding of its functionality. Time-domain 1H NMR showed that water in the viscous aqueous phase isolated from cake batter by ultracentrifugation [i.e. the batter liquor (BL)] exhibits low mobility by its low T2 relaxation time (T2,D RT). This is due to its interactions with sucrose or sucrose replacers. The T2,D RT itself is positively related with the effective volumetric hydrogen bond density of sucrose or sucrose replacers. Sucrose additionally co-determines the quantity and viscosity of cake BL and thereby how much air the batter contains at the end of mixing. Like sucrose, maltitol and oligofructose provide adequate volumes of BL with low water mobility and thus sufficient air in the batter, while the rather insoluble mannitol and inulin do not. Differential scanning calorimetry and rapid viscosity analysis revealed, however, that, in contrast to sucrose and maltitol, oligofructose fails to provide appropriate timings of starch gelatinisation and protein denaturation, resulting in poor cake texture. The shortcomings of mannitol and oligofructose in terms of respectively ensuring appropriate gas content in batter and biopolymer transitions during baking can be overcome by using mixtures thereof. This work shows that successful sucrose substitutes or substitute mixtures must provide sufficient BL with low water mobility and ensure appropriate timings of starch and protein biopolymer transitions during baking.
Duration of SARS-CoV-2 mRNA vaccine persistence and factors associated with cardiac involvement in recently vaccinated patients
Authors: Krauson Aram J. , Casimero Faye Victoria C. , Siddiquee Zakir , Stone James R. 
Published: September 2023

AbstractAt the start of the COVID-19 pandemic, the BNT162b2 (BioNTech-Pfizer) and mRNA-1273 (Moderna) mRNA vaccines were expediently designed and mass produced. Both vaccines produce the full-length SARS-CoV-2 spike protein for gain of immunity and have greatly reduced mortality and morbidity from SARS-CoV-2 infection. The distribution and duration of SARS-CoV-2 mRNA vaccine persistence in human tissues is unclear. Here, we developed specific RT-qPCR-based assays to detect each mRNA vaccine and screened lymph nodes, liver, spleen, and myocardium from recently vaccinated deceased patients. Vaccine was detected in the axillary lymph nodes in the majority of patients dying within 30 days of vaccination, but not in patients dying more than 30 days from vaccination. Vaccine was not detected in the mediastinal lymph nodes, spleen, or liver. Vaccine was detected in the myocardium in a subset of patients vaccinated within 30 days of death. Cardiac ventricles in which vaccine was detected had healing myocardial injury at the time of vaccination and had more myocardial macrophages than the cardiac ventricles in which vaccine was not detected. These results suggest that SARS-CoV-2 mRNA vaccines routinely persist up to 30 days from vaccination and can be detected in the heart.
Few-shot out-of-distribution detection for automated screening in retinal OCT images using deep learning
Authors: Araújo Teresa , Aresta Guilherme , Schmidt-Erfurth Ursula , Bogunović Hrvoje 
Published: September 2023

AbstractDeep neural networks have been increasingly proposed for automated screening and diagnosis of retinal diseases from optical coherence tomography (OCT), but often provide high-confidence predictions on out-of-distribution (OOD) cases, compromising their clinical usage. With this in mind, we performed an in-depth comparative analysis of the state-of-the-art uncertainty estimation methods for OOD detection in retinal OCT imaging. The analysis was performed within the use-case of automated screening and staging of age-related macular degeneration (AMD), one of the leading causes of blindness worldwide, where we achieved a macro-average area under the curve (AUC) of 0.981 for AMD classification. We focus on a few-shot Outlier Exposure (OE) method and the detection of near-OOD cases that share pathomorphological characteristics with the inlier AMD classes. Scoring the OOD case based on the Cosine distance in the feature space from the penultimate network layer proved to be a robust approach for OOD detection, especially in combination with the OE. Using Cosine distance and only 8 outliers exposed per class, we were able to improve the near-OOD detection performance of the OE with Reject Bucket method by $$\approx$$
≈
10% compared to without OE, reaching an AUC of 0.937. The Cosine distance served as a robust metric for OOD detection of both known and unknown classes and should thus be considered as an alternative to the reject bucket class probability in OE approaches, especially in the few-shot scenario. The inclusion of these methodologies did not come at the expense of classification performance, and can substantially improve the reliability and trustworthiness of the resulting deep learning-based diagnostic systems in the context of retinal OCT.
Physicochemical properties of the vacuolar membrane and cellular factors determine formation of vacuolar invaginations
Authors: Kimura Yoko , Tsuji Takuma , Shimizu Yosuke , Watanabe Yuki , Kimura Masafumi , Fujimoto Toyoshi , Higuchi Miyuki 
Published: September 2023

AbstractVacuoles change their morphology in response to stress. In yeast exposed to chronically high temperatures, vacuolar membranes get deformed and invaginations are formed. We show that phase-separation of vacuolar membrane occurred after heat stress leading to the formation of the invagination. In addition, Hfl1, a vacuolar membrane-localized Atg8-binding protein, was found to suppress the excess vacuolar invaginations after heat stress. At that time, Hfl1 formed foci at the neck of the invaginations in wild-type cells, whereas it was efficiently degraded in the vacuole in the atg8Δ mutant. Genetic analysis showed that the endosomal sorting complex required for transport machinery was necessary to form the invaginations irrespective of Atg8 or Hfl1. In contrast, a combined mutation with the vacuole BAR domain protein Ivy1 led to vacuoles in hfl1Δivy1Δ and atg8Δivy1Δ mutants having constitutively invaginated structures; moreover, these mutants showed stress-sensitive phenotypes. Our findings suggest that vacuolar invaginations result from the combination of changes in the physiochemical properties of the vacuolar membrane and other cellular factors.
High-volume hybridoma sequencing on the NeuroMabSeq platform enables efficient generation of recombinant monoclonal antibodies and scFvs for neuroscience research
Authors: Mitchell Keith G. , Gong Belvin , Hunter Samuel S. , Burkart-Waco Diana , Gavira-O’Neill Clara E. , Templeton Kayla M. , Goethel Madeline E. , Bzymek Malgorzata , MacNiven Leah M. , Murray Karl D. , Settles Matthew L. , Froenicke Lutz , Trimmer James S. 
Published: September 2023

AbstractThe Neuroscience Monoclonal Antibody Sequencing Initiative (NeuroMabSeq) is a concerted effort to determine and make publicly available hybridoma-derived sequences of monoclonal antibodies (mAbs) valuable to neuroscience research. Over 30 years of research and development efforts including those at the UC Davis/NIH NeuroMab Facility have resulted in the generation of a large collection of mouse mAbs validated for neuroscience research. To enhance dissemination and increase the utility of this valuable resource, we applied a high-throughput DNA sequencing approach to determine immunoglobulin heavy and light chain variable domain sequences from source hybridoma cells. The resultant set of sequences was made publicly available as a searchable DNA sequence database (neuromabseq.ucdavis.edu) for sharing, analysis and use in downstream applications. We enhanced the utility, transparency, and reproducibility of the existing mAb collection by using these sequences to develop recombinant mAbs. This enabled their subsequent engineering into alternate forms with distinct utility, including alternate modes of detection in multiplexed labeling, and as miniaturized single chain variable fragments or scFvs. The NeuroMabSeq website and database and the corresponding recombinant antibody collection together serve as a public DNA sequence repository of mouse mAb heavy and light chain variable domain sequences and as an open resource for enhancing dissemination and utility of this valuable collection of validated mAbs.
Optimal degrees of freedom of the lower extremities for human walking and running
Authors: Kudo Shoma , Fujimoto Masahiro , Sato Takahiko , Nagano Akinori 
Published: September 2023

AbstractDetermining the degrees of freedom (DOF) of the linked rigid-body model, representing a multi-body motion of the human lower extremity, is one of the most important procedures in locomotion analysis. However, a trade-off exists between the quality of data fitting and the generalizability of the model. This study aimed to determine the optimal DOF of the model for the lower extremities that balance the goodness-of-fit and generalizability of the model during walking and running using Akaike’s information criterion (AIC). Empirically obtained kinematic data for the lower extremities during walking and running were fitted by models with 9, 18, or 22 DOF. The relative quality of these models was assessed using their bias-corrected AIC (cAIC) value. A significant simple main effect of the model was found on the cAIC value for both walking and running conditions. Pairwise comparisons revealed that the cAIC value of the 18-DOF model was significantly smaller than that of the 9-DOF (walking: p < 0.001, running: p = 0.010) and 22-DOF (walking: p < 0.001, running: p < 0.001) models. These findings suggest that the 18-DOF model is optimal for representing the lower extremities during walking and running, in terms of goodness-of-fit and generalizability.
Using Differential Evolution to avoid local minima in Variational Quantum Algorithms
Authors: Faílde Daniel , Viqueira José Daniel , Mussa Juane Mariamo , Gómez Andrés 
Published: September 2023

AbstractVariational Quantum Algorithms (VQAs) are among the most promising NISQ-era algorithms for harnessing quantum computing in diverse fields. However, the underlying optimization processes within these algorithms usually deal with local minima and barren plateau problems, preventing them from scaling efficiently. Our goal in this paper is to study alternative optimization methods that can avoid or reduce the effect of these problems. To this end, we propose to apply the Differential Evolution (DE) algorithm to VQAs optimizations. Our hypothesis is that DE is resilient to vanishing gradients and local minima for two main reasons: (1) it does not depend on gradients, and (2) its mutation and recombination schemes allow DE to continue evolving even in these cases. To demonstrate the performance of our approach, first, we use a robust local minima problem to compare state-of-the-art local optimizers (SLSQP, COBYLA, L-BFGS-B and SPSA) against DE using the Variational Quantum Eigensolver algorithm. Our results show that DE always outperforms local optimizers. In particular, in exact simulations of a 1D Ising chain with 14 qubits, DE achieves the ground state with a 100% success rate, while local optimizers only exhibit around 40%. We also show that combining DE with local optimizers increases the accuracy of the energy estimation once avoiding local minima. Finally, we demonstrate how our results can be extended to more complex problems by studying DE performance in a 1D Hubbard model.
Development of a dynamical statistical analog ensemble forecast model for landfalling typhoon disasters
Authors: Wu Caiming , Ren Fumin , Zhang Da-Lin , Zhu Jing , McBride John Leonard , Chen Yuxu 
Published: September 2023

AbstractIn this report, the development of a Dynamical Statistical Analog Ensemble Forecast model for landfalling typhoon disasters (LTDs) and some applications over coastal China are described. This model consists of the following four elements: (i) obtaining the forecast track of a target landfalling typhoon, (ii) constructing its generalized initial value (GIV), (iii) identifying its analogs based on the GIV, and (iv) assembling typhoon disasters of the analogs. Typhoon track, intensity, and landfall date are introduced in GIV at this early development stage. The pre-assessment results show that the mean threat scores of two important damage levels of LTDs reach 0.48 and 0.55, respectively. Of significance is that most of the damage occurs near the typhoon centers around the time of landfall. These results indicate the promising performance of the model in capturing the main damage characteristics of typhoon disasters, which would help coastal community mitigate damage from destructive typhoons.