bluuebunny/crossref_metadata_2025 huggingface dataset:
Key gut microbiota components and functions in an aquatic keystone species across diets assessed by metaproteomics
Authors: Dumas Thibaut , Pible Olivier , Grenga Lucia , Esposti Davide Degli , Delorme Nicolas , Geffard Olivier , Chaumot Arnaud , Armengaud Jean
Published: November 2024

The gut microbiota plays a crucial role in maintaining host fitness and modulating contaminant toxicity-related responses. However, information on how the gut microbiota of sentinel species responds to environmental factors is limited. In this study, we characterized the gut microbial community and its functions under normal, contaminant-free conditions by examining the effects of different diets over a 10-day period (alder leaf, carrot, spinach, and protein-rich granules) on the amphipodGammarus fossarum, commonly used in bioassays for ecotoxicity assessment of contaminated rivers. Metaproteomic analysis of intestine samples enabled taxonomic characterization of the gut microbiota from this millimetric animal, assignment of biological functions to each microbial entity, and functional analysis of host proteins. The most abundant microbes detected in the gut belong to 37 bacterial and 5 fungal genera. Functional analyses of host and microbial proteins revealed complementary metabolic activities, allowing the degradation of complex polysaccharides such as cellulose and chitin. Diet was found to shape microbial community structure, with foodborne microorganisms strongly influencing structural changes during short-term feeding in amphipods. These microorganisms remained viable post-ingestion and contributed to food digestion. Functional stability was maintained across different diets, although the protein-rich granules diet induced functional shifts in both the host and its microbiota, reflecting their adaptation to a novel nutrient source. Finally, we identified a core microbiota driving key gut functions, less affected by dietary variations. These findings are significant for future ecotoxicological and biomonitoring investigations, leveraging the microbiomes of these sentinel animals as pivotal targets.
Inhibition and Updating Share Common Resources: Evidence from Drift Diffusion Model
Authors: Sun Yuhong , Lin Yaohui , Han Shangfeng
Published: November 2024

Inhibition and updating are fundamental cognitive functions in humans, yet the nature of their relationship—whether shared or distinct—remains ambiguous. This study investigates the relationship between inhibition and updating and examines whether this relationship is altered in individuals with trait anxiety. A novel paradigm that combines N-back and congruent/incongruent Stroop tasks were utilized to explore these issues by employing Signal Detection Theory (SDT) and the hierarchical drift diffusion model (HDDM) methods. The results revealed that participants exhibited longer response times and higher error rates in conditions requiring both inhibition and updating compared to those requiring updating alone. SDT analysis indicated lower discriminability, while HDDM analysis showed slower drift rates and longer non-decision times. These findings suggest that inhibition consumes cognitive resources, leading to worse updating performance, implying that both functions may rely on shared resources. In the anxiety group, higher trait anxiety scores correlated with increased response times and decreased accuracy. The drift rate fully mediated the effect of trait anxiety on accuracy, suggesting that the speed of effective information accumulation is a key mechanism underlying the abnormal functioning of inhibition and updating in individuals with anxiety. Overall, the results elucidate the relationship between these fundamental cognitive functions, supporting the notion that inhibition and updating share cognitive resources. Furthermore, this study provides evidence and insights into the cognitive abnormalities observed in individuals with anxiety.
Are resting-state networks the brain’s cognitive atoms? Differential dynamic reconfiguration of functional brain networks across tasks and at rest
Authors: Jung JeYoung , Lambon Ralph Matthew A.
Published: November 2024

It is increasingly popular to utilise functional connectivity (FC) analyses of resting-state functional magnetic resonance imaging (fMRI) to characterize human functional brain networks and to use the emergent resting-state networks (RSNs) in basic and clinical neuroscience. Often, they are treated as ‘atomic’ building blocks that underpin human cognition. However, the true function of these RSNs, as well as the relationship between intrinsic and task-evoked functional brain networks, are complex and incompletely characterized. Here, we investigated the functional characteristics of the intrinsic and extrinsic networks using resting-state and task fMRI. Independent component analysis (ICA) was used to estimate spatiotemporal functional networks during tasks and at rest, and to compare the spatiotemporal properties of each network. While there was some spatial correspondence between the RSNs and task-evoked networks, our results demonstrated that the task-evoked functional networks were different from the RSNs in task-relatedness as well as spatial topology. Furthermore, the degree of topological differences between the RSNs and task-evoked networks was modulated by a given task. Comparison between the RSNs and task-evoked networks showed that tasks reconfigure the RSNs by changing FC with various brain regions specific to the task condition. Our findings indicate that the brain does not maintain an “invariant intrinsic” network architecture when it engages in a task. Instead, the tasks reconfigure the network architectures, thereby accommodating specific computational/representational task requirements through flexible interactions between demand-specific regions. Thus, the results suggest that task fMRI is required to understand the full repertoire of the brain’s functional architecture.

Significant Statement

Resting-state networks (RSNs) could offer a critical foundation for understanding the brain’s intrinsic organization. However, the functional nature of these intrinsic networks, and their relationship to those activated during specific tasks, are complex and not fully understood. We undertook a comprehensive examination of the functional attributes of intrinsic and extrinsic networks. Although we observed some spatial congruence between RSNs and task-evoked networks, we found fundamental differences in their task-relatedness and spatial topology. These findings highlight the dynamic nature of the brain’s functional networks, which adapt to specific task demands through flexible interactions among task-specific regions. Thus, task fMRI is essential for a comprehensive understanding of how the human brain dynamically reconfigures its functional architecture in response to external demands, providing valuable insights into the cognition and behaviour.
Differentiating hallucination proneness dimensions through resting state alpha dynamics
Authors: Honcamp Hanna , O'Donnell Philip , Pinheiro Ana P. , Trujillo-Barreto Nelson J. , Schwartze Michael , El-Deredy Wael , Kotz Sonja A.
Published: November 2024

Background: Hallucination-like experiences (HLEs) are untriggered sensory perceptions linked to externalizing bias - the misattribution of self-generated sensory experiences to an external source. The vulnerability to HLEs, i.e., hallucination proneness (HP), is typically assessed by the Launay-Slade Hallucination Scale (LSHS). A recent LSHS factor analysis revealed four distinct HP dimensions: Multisensory HLEs, Auditory daydreaming, Vivid thoughts and inner speech, and Personified HLEs. The current study assesses whether these HP dimensions map onto distinct patterns of resting state brain dynamics in the alpha frequency band due to its modulatory role in attention and perception. Methods: We used a Hidden semi-Markov Model to segment continuous RS alpha activity into nine recurrent brain states and extracted the total number of transitions (TT) and the number of visits per state (SV). We assessed how the HP dimensions relate to these metrics, calculated across the entire 3-minute recording and within shorter sliding windows to capture finer temporal changes. Results: All HP dimensions and increased RS time correlated with increased TT. Increased Personified HLEs scores linked to different time-dependent changes of SV in two states (SV to state 5 decreased over time, while visits to state 9 increased), highlighting distinct alpha dynamics in high- and low-hallucination prone individuals. Conclusions: Increased TT could indicate frequent attentional switches between internal and external states. Different SV patterns related to higher Personified HLEs scores suggest unstable source monitoring, potentially inducing an externalizing bias. These findings provide novel predictors of HP dimensions, revealing distinct neural profiles associated with different vulnerability profiles.
Astrocytic modulation of population encoding in mouse visual cortex via GABA transporter 3 revealed by multiplexed CRISPR/Cas9 gene editing
Authors: Park Jiho , Sipe Grayson O. , Tang Xin , Ojha Prachi , Fernandes Giselle , Leow Yi Ning , Zhang Caroline , Osako Yuma , Natesan Arundhati , Drummond Gabrielle T. , Jaenisch Rudolf , Sur Mriganka
Published: November 2024

Astrocytes, which are increasingly recognized as pivotal constituents of brain circuits governing a wide range of functions, express GABA transporter 3 (Gat3), an astrocyte-specific GABA transporter responsible for maintenance of extra-synaptic GABA levels. Here, we examined the functional role of Gat3 in astrocyte-mediated modulation of neuronal activity and information encoding. First, we developed a multiplexed CRISPR construct applicable for effective genetic ablation of Gat3 in the visual cortex of adult mice. Usingin vivotwo-photon calcium imaging of visual cortex neurons in Gat3 knockout mice, we observed changes in spontaneous and visually driven single neuronal response properties such as response magnitudes and trial-to-trial variability. Gat3 knockout exerted a pronounced influence on population-level neuronal activity, altering the response dynamics of neuronal populations and impairing their ability to accurately represent stimulus information. These findings demonstrate that Gat3 in astrocytes profoundly shapes the sensory information encoding capacity of neurons and networks within the visual cortex.
Archaic Adaptive Introgression in Modern Human Reproductive Genes
Authors: Kendall Christopher , Nooranikhojasteh Amin , Parra Esteban , Schillaci Michael A. , Viola Bence
Published: November 2024

Modern humans and archaic hominins, namely Denisovans and Neanderthals, have been demonstrated to have a long history of admixture. Specifically, some of these admixture events have been adaptive and allowed modern humans to adapt to their new environments outside of Africa. Little research has been done on the impact of archaic introgression on genes associated with reproduction. In this study we report evidence of putative adaptive introgression of 118 genes within modern humans that have been previously associated with reproduction in mice or modern humans. From these genes we identified 11 archaic core haplotypes, three that have been positively selected. Additionally, we found that 327 archaic alleles have genome-wide significance for a variety of traits and 308 of these variants were discovered to be eQTLs regulating 176 genes. We highlight that 81% of the archaic eQTLs overlapping a core haplotype region regulate genes expressed in ovaries, prostate, testes, and vagina compared to other tissues. We also found that several of the putatively adaptively introgressed genes in our results are enriched in developmental and cancer pathways. Further, some of these genes have been associated with embryo development and reproductive-inhibiting phenotypes like preeclampsia. Lastly, we found that archaic alleles overlapping an introgressed segment on chromosome 2 are protective against prostate cancer. Taken together, our results describe how archaic haplotypes, when introduced into a modern human background, may be important in regulating development across the lifespan of an individual.
Modulation of learning-dependent plasticity in the attention network
Authors: Contò F. , Ellena G. , Edwards G. , Battelli L.
Published: November 2024

Neuromodulatory interventions are gaining interest for their potential to enhance key cognitive functions, including attention and learning. However, their effects on cortical activity during training remains limited. Our previous work demonstrated that bilateral transcranial random noise stimulation (tRNS) over the intraparietal sulcus (IPS), coupled with a multi-session attention-based perceptual learning increased functional connectivity within the dorsal-ventral attention network at rest (DVAN, Contò et al., 2021). In this follow-up study we examined how the same multi-session stimulation protocol modulates BOLD signal in the DVAN during two attention tasks. Our findings show that tRNS targeting the IPS selectively enhanced BOLD responses during a spatial, but not a temporal task, indicating task-specific neural effects. Conversely, BOLD responses in the DVAN significantly decreased after sham. Control analyses within the default mode network (DMN) showed no significant changes, indicating the network specific effects of tRNS. The region-specific nature of these effects suggests that tRNS-induced modulation is constrained to key network nodes, enhancing the DVAN’s cortical response in spatial tasks, a response that instead decreases after sham and has no benefit on behavior. This selectivity of the cortical response aligns with theories of neural efficiency, indicating that tRNS may prevent natural downregulation in task-relevant areas and promotes sustained plasticity. Our results highlight the potential of tRNS in augmenting cognitive training, providing a powerful tool for the precise modulation of attention networks in both healthy individuals and clinical population.
Expression variability following gene duplication facilitates gene retention
Authors: Cai Haoran , Des Marais David L.
Published: November 2024

Genome analyses reveal that gene duplication in eukaryotes is pervasive, providing a primary source for the emergence of new genes. The mechanisms governing the retention of duplicated genes, particularly in the early stages post-duplication, remain ambiguous. Patterns of divergence between duplicated genes vary, leading to biases in the functions of genes retained following duplication. For example, genes that arise from tandem duplication tend to be involved in envi- ronmental responses. However, the mechanisms that cause such functional biases remain elusive. Here, to better understand the mechanisms and factors determining gene retention, we study a frequently overlooked molecular feature —expression variability—as measured by within-line expression variation, termed variability. We find that, on average, genes with duplicates exhibit higher expression variability than singletons. We further find that such elevated expression variability for small-scale duplications (SSDs) is likely driven by the immediate increase in expression variability following duplication events. These findings suggest a potential overarch- ing mechanism that facilitates gene expression divergence, functional gains of environmental responses, and duplicate retention following SSDs.
Modelling the Complex Smoking Exposure History in Assessment of Pan-Cancer Risk
Authors: Liu Wei , Chen Ya-Ting , Tao Baiwenrui , Lv Ying , Zhang Yan-Xi , Ren Hui-Ying , Zhang Yu-Ting , Fan Yu-Ping , Li Meng-Han , Shi Ya-Xin , Wang Shi-Yuan , Chen Bing-Wei , van Osch Frits , Zeegers Maurice P. , Qin Qi-Rong , Wesselius Anke , Yu Evan Yi-Wen
Published: November 2024

Modelling complex smoking histories, with more comprehensive and flexible methods, to show what profile of smoking behavior is associated with the risk of different cancers remains poorly understood. This study aims to provide insight into the association between complex smoking exposure history and pan-cancer risk by modelling both smoking intensity and duration in a large-scale prospective cohort. Here, we used data including a total of 0.5 million with cancer incidences of 12 smoking-related cancers. To jointly interpret the effects of intensity and duration of smoking, we modelled excess relative risks (ERRs)/pack-year isolating the intensity effects for fixed total pack-years, thus enabling the smoking risk comparison for total exposure delivered at low intensity (for long duration) and at a high intensity (for short duration). The pattern observed from the ERR model indicated that for a fixed number of pack-years, low intensity/long duration or high intensity/short duration is associated with a different greater increase in cancer risk. Those findings were extended to an increase of time since smoking cessation (TSC) showing a reduction of ERR/pack-year for most cancers. Moreover, individuals with favorable lifestyle behaviors, such as regular physical activity and healthy dietary intakes, were shown to have lower ERRs/pack-year, compared to those with unfavorable lifestyle behaviors. Overall, this study systematically evaluates and demonstrates that for pan-cancer risks, smoking patterns are varied, while reducing exposure history to a single metric such as pack-years was too restrictive. Therefore, cancer screening guidelines should consider detailed smoking patterns, including intensity, duration, and cessation, for more precise prevention strategies.

Highlights (Key context and significance)

Distinct cancer risk patterns emerge based on smoking exposure beyond equal pack-years: smoking duration is a stronger risk factor for some cancers, while smoking intensity dominates for others.

Time since smoking cessation (TSC) significantly lowers cancer risk: former smokers experience substantial reductions in risk for most cancers within the first 20 years after quitting.

Favorable lifestyle behaviors mitigate cancer risks: individuals with regular physical activity and healthy diets show lower excess relative risks (ERRs) for most cancers, compared to those with unhealthy habits.

Tailored cancer screening based on smoking behavior: cancer screening guidelines should consider detailed smoking patterns, including intensity, duration, and cessation, for more precise prevention strategies.
AI coupled to pharmacometric modelling to tailor malaria and tuberculosis treatment in Africa
Authors: Turon Gemma , Mulubwa Mwila , Montaner Anna , Njoroge Mathew , Chibale Kelly , Duran-Frigola Miquel
Published: November 2024

Africa’s vast genetic diversity poses challenges for optimising drug treatments in the continent, which is exacerbated by the fact that drug discovery and development efforts have historically been performed outside Africa. This has led to suboptimal therapeutic outcomes in African populations and overall scarcity of relevant pharmacogenetic data, including characteristic genotypes as well as drugs prescribed in the continent to treat infectious diseases. Here, we propose a general approach to identify drug-gene pairs with potential pharmacogenetic interest. Furthermore, we delve deeper into the analysis of malaria and tuberculosis therapies, many of which remain uncharacterised from a pharmacogenetic perspective. Our pipeline leverages artificial intelligence and the latest advances in knowledge embedding techniques to exploit currently available biomedical data and subsequently prioritise pharmacogenes for each drug. Predicted pharmacogenes are then incorporated into pharmacometric modelling to hypothesise which ones might be of clinical interest, and which dose adjustments could be made to provide better treatment outcomes for the African population.
A chill brain-music interface for enhancing music chills with personalized playlists
Authors: Kondoh Sotaro , Etani Takahide , Sakakibara Yuna , Naruse Yasushi , Imamura Yasuhiko , Ibaraki Takuya , Fujii Shinya
Published: November 2024

Music chills are pleasurable experiences while listening to music, often accompanied by physical responses, such as goosebumps1,2. Enjoying music that induces chills is central to music appreciation, and engages the reward system in the brain3–5. However, the specific songs that trigger chills vary with individual preferences6, and the neural substrates associated with musical rewards differ among individuals7–9, making it challenging to establish a standard method for enhancing music chills. In this study, we developed the Chill Brain-Music Interface (C-BMI), a closed-loop neurofeedback system that uses in-ear electroencephalogram (EEG) for song selection. The C-BMI generates personalized playlists aimed at evoking chills by integrating individual song preferences and neural activity related to music reward processing. Twenty-four participants listened to both self-selected and other-selected songs, reporting higher pleasure levels and experiencing more chills in their self-selected songs. We constructed two LASSO regression models to support the C-BMI. Model 1 predicted pleasure based on the acoustic features of the self-selected songs. Model 2 classified the EEG responses when participants listened to self-selected versus other-selected songs. Model 1 was applied to over 7,000 candidate songs, predicting pleasure scores. We used these predicted scores and acoustic similarity to the self-selected songs to rank songs that were likely to induce pleasure. Using this ranking, four tailored playlists were generated. Two playlists were designed to augment pleasure by selecting top-ranked songs, one of which incorporated real-time pleasure estimates from Model 2 to continuously update Model 1 and refine song rankings. Additionally, two playlists aimed to diminish pleasure, with one updated using Model 2. We found that the pleasure-augmenting playlist with EEG-based updates elicited more chills and higher pleasure levels than pleasure-diminishing playlists. Our results indicate that C-BMI using in-ear EEG data can enhance music-induced chills.
Gut Microbiota Regulates Exercise-induced Hormetic Modulation of Cognitive Function
Authors: Cintado Elisa , Muela Pablo , Martin-Rodriguez Lucia , Alcaide Ignacio , Tezanos Patricia , Vlckova Klara , Valderrama Benjamin , Bastiaanssen Thomaz FS , Rodríguez-Muñoz María , de Ceballos María L. , Aburto María R , Cryan John F , Trejo José Luis
Published: November 2024

Lifestyle factors, particularly physical exercise, significantly influence brain structure and cognitive function through a hormetic effect dependent on exercise intensity and duration. The underlying mechanisms of this profile remain largely unexplored. Recently, the gut microbiota, has emerged a potent modulator of lifestyle-induced changes on brain and behavior. Here, we demonstrate that a 40-minute protocol of moderate exercise enhances cognitive abilities related to object recognition and memory, and increases hippocampal neurogenesis in adult mice compared to sedentary controls, but these cognitive and neurogenic benefits vanish when the exercise intensity or duration is increased. Furthermore, we identified significant alpha- and beta-diversity changes and distinct bacteria composition profiles of gut microbiota associated with different exercise regimens. Specific bacterial families showed altered relative abundances depending on exercise intensity and duration, with certain families’ quantities significantly correlating with cognitive performance (Angelakisella, Acetatifactor, Erysipelatoclostridium, andCoriobacteriaceaeUCG-002.). To parse causal mechanisms, fecal microbiota transplantation from exercised to sedentary mice replicated the cognitive and brain structural improvements observed in the donor animals. These findings suggest that the hormetic effects of physical exercise on cognitive function and neurogenesis are mediated by corresponding changes in the gut microbiota, indicating a novel mechanistic link between exercise, brain, and gut microbiota composition.
Opposing effects of rewarding and aversive stimuli on D1 and D2 types of dopamine-sensitive neurons in the central amygdala
Authors: Bijoch Łukasz , Szczypkowski Paweł , Wiśniewska Justyna , Pawłowska Monika , Hajdukiewicz Karolina , Łapkiewicz Radek , Beroun Anna
Published: November 2024

Dopamine-sensitive neurons are organized in two classes of cells, expressing D1- or D2- types of dopamine receptors, and are often mediating opposing aspects of reward-oriented behaviors. Here, we focused on dopamine-sensitive neurons in the central amygdala – a brain structure critically involved in processing emotion-related stimuli. We discovered that both dopamine receptor types are present in the central medial nucleus, while the lateral part is populated predominantly with DRD2 cells. Exposing mice to rewarding and aversive stimuli we studied DRD1 and DRD2 cells activity usingin vivotwo-photon calcium imaging in the CeM. We showed that cocaine and sugar predominantly increase the activity of DRD1(+) neurons and decrease DRD2(+) cells. Repeated exposure to cocaine, however, had the opposite effect on spontaneous excitatory synaptic transmission in the CeM than exposure to sugar. Quinine, an aversive stimulus, primarily engaged DRD2(+) neurons, activating predominantly those cells that were previously inhibited by sugar exposure. Our results show that though DRD1 and DRD2 populations are differentially engaged and regulated by appetitive/aversive stimuli, both participate in sugar, cocaine, and quinine processing.
Single-nuclei transcriptomes in the hypothalamus and POA of a highly social cichlid
Authors: Miller-Crews Isaac , Hofmann Hans A.
Published: November 2024

How does complex behavior arise from the genome across biological levels? Specific cell types have evolutionarily conserved functional roles in regulating and maintaining various aspects of social behavior. There is a long history of research demonstrating how specific cells in the hypothalamus and POA are critical in regulating social status and reproductive behavior. This cell function is dependent not just on one gene, but the entire gene expression network working within each cell. The brain is a heterogenous tissue made up of a broad diversity of cells. Targeting the cellular-level transcriptomes in socially relevant brain regions enables the identification of social status mediators. Single-nuclei RNA-sequencing (snRNA-seq) provides the resolution to identify cell-specific transcriptomes, with more practical benefits compared to single-cell approaches. Single-nucleus sequencing of neuronal tissue has remained fairly limited to model mammalian organisms. Here we performed snRNA-seq in the hypothalamus and POA ofAstatotilapia burtoni, a fish system ideal for social neuroscience. MaleA. burtoniare characterized by plastic phenotypes associated with social status, dominant and subordinate, with well-established differences in neural gene expression patterns and specific neuron morphology. This provides a novel opportunity to apply snRNA-seq in a complex tissue of a non-model system using hypothesis driven approaches. We show how changes in social status are linked to distinct transcriptomic profiles at the cellular level.
Plug-and-Play Myoelectric Control via a Self-Calibrating Random Forest Common Model
Authors: Jiang Xinyu , Ma Chenfei , Nazarpour Kianoush
Published: November 2024

Electromyographic (EMG) signals show large variabilities over time due to factors such as electrode shifting, user behaviour variations, etc., substantially degrading the performance of myoelectric control models in long-term use. Previously one-time model calibration was usually required each time before usage. However, the EMG characteristics could change even within a short period of time. Our objective is to develop a self-calibrating model, with an automatic and unsupervised self-calibration mechanism. Approach: We developed a computationally efficient random forest (RF) common model, which can (1) be pre-trained and easily adapt to a new user via one-shot calibration, and (2) keep calibrating itself once in a while by boosting the RF with new decision trees trained on pseudo-labels of testing samples in a data buffer. Main results: Our model has been validated in both offline and real-time, both open and closed-loop, both intra-day and long-term (up to 5 weeks) experiments. We tested this approach with data from 66 able-bodied participants. We also explored the effects of bidirectional user-model co-adaption in closed-loop experiments. We found that the self-calibrating model could gradually improve its performance in long-term use. With visual feedback, users will also adapt to the dynamic model meanwhile learn to perform hand gestures with significantly lower EMG amplitudes (less muscle effort). Significance: Our random forest-approach provides a new alternative built on simple decision tree for myoelectric control, which is explainable, computationally efficient, and requires minimal data for model calibration. Source codes are available at: https://github.com/MoveR-Digital-Health-and-Care-Hub/self-calibrating-rf.
Experimental end-to-end demonstration of intersatellite absolute ranging for the Laser Interferometer Space Antenna
Authors: Yamamoto Kohei , Bykov Iouri , Reinhardt Jan Niklas , Bode Christoph , Grafe Pascal , Staab Martin , Messied Narjiss , Clark Myles , Barranco Germán Fernández , Schwarze Thomas S. , Hartwig Olaf , Delgado Juan José Esteban , Heinzel Gerhard
Published: November 2024

The Laser Interferometer Space Antenna (LISA) is a gravitational wave detector in space. It relies on a postprocessing technique named time-delay interferometry to suppress the overwhelming laser frequency noise by several orders of magnitude. This algorithm requires intersatellite-ranging monitors to provide information on spacecraft separations. To fulfill this requirement, we use on-ground observatories, optical sideband-sideband beatnotes, pseudorandom noise ranging (PRNR), and time-delay interferometric ranging (TDIR). This article reports on the experimental end-to-end demonstration of a hexagonal optical testbed used to extract absolute ranges via the optical sidebands, PRNR, and TDIR. These were applied for clock synchronization of optical beatnote signals sampled at independent phasemeters. We set up two possible PRNR processing schemes: Scheme 1 extracts pseudoranges from PRNR via a calibration relying on TDIR; Scheme 2 synchronizes all beatnote signals without TDIR calibration. The schemes rely on newly implemented monitors of local-PRNR biases. After the necessary PRNR treatments (unwrapping, ambiguity resolution, bias correction, in-band jitter reduction, and/or calibration), Schemes 1 and 2 achieved ranging accuracies of 2.0–8.1 cm and 5.8–41.1 cm, respectively, below the classical 1-m mark with margins.

Published by the American Physical Society
2024
Dilatonic dynamics of baryonic crystals, branes, and spheres
Authors: Bersini Jahmall , D’Alise Alessandra , Sannino Francesco , Torres Matías
Published: November 2024

We systematically analyze the impact of dilatonic dynamics on Skyrme spheres, crystals, and branes. The effects of the dilatonic model parameters, encompassing different underlying near-conformal dynamics, on the macroscopic properties of skyrmions such as their mass and radius are discussed. For spheres and crystals we identify special values of the ratio of the decay constants for which the second order differential equations reduce to a solvable first order system. Additionally, in the case of the crystals, the dilaton presence spatially separates the baryon and isospin charge distributions. For branes, we show how the dilaton smooths out their configurations. Our results are expected to have wide implications from the study of near-conformal dynamics stemming from QCD-like theories to phenomenological investigations of nuclear matter in extreme regimes.

Published by the American Physical Society
2024
Learning new physics from data: A symmetrized approach
Authors: Bressler Shikma , Savoray Inbar , Zurgil Yuval
Published: November 2024

Thousands of person years have been invested in searches for new physics (NP), the majority of them motivated by theoretical considerations. Yet, no evidence of beyond the Standard Model physics has been found. This suggests that model-agnostic searches might be an important key to explore NP, and help discover unexpected phenomena which can inspire future theoretical developments. A possible strategy for such searches is identifying asymmetries between data samples that are expected to be symmetric within the Standard Model. We propose exploiting neural networks (NNs) to quickly fit and statistically test the differences between two samples. Our method is based on an earlier work, originally designed for inferring the deviations of an observed dataset from that of a much larger reference dataset. We present a symmetric formalism, generalizing the original one, avoiding fine-tuning of the NN parameters and any constraints on the relative sizes of the samples. Our formalism could be used to detect small symmetry violations, extending the discovery potential of current and future particle physics experiments.

Published by the American Physical Society
2024
Measuring the circular polarization of gravitational waves with pulsar timing arrays
Authors: Jiménez Cruz N. M. , Malhotra Ameek , Tasinato Gianmassimo , Zavala Ivonne
Published: November 2024

The circular polarization of the stochastic gravitational wave background (SGWB) is a key observable for characterizing the origin of the signal detected by Pulsar Timing Array (PTA) collaborations. Both the astrophysical and the cosmological SGWB can have a sizeable amount of circular polarization, due to Poisson fluctuations in the source properties for the former, and to parity violating processes in the early universe for the latter. Its measurement is challenging since PTA are blind to the circular polarization monopole, forcing us to turn to anisotropies for detection. We study the sensitivity of current and future PTA datasets to circular polarization anisotropies, focusing on realistic modelling of intrinsic and kinematic anisotropies for astrophysical and cosmological scenarios respectively. Our results indicate that the expected level of circular polarization for the astrophysical SGWB should be within the reach of near future datasets, while for cosmological SGWB circular polarization is a viable target for more advanced SKA-type experiments.

Published by the American Physical Society
2024
Specific heats for quantum BTZ black holes in extended thermodynamics
Authors: Johnson Clifford V. , Nazario Roberto
Published: November 2024

It was shown recently that extended black hole thermodynamics, where the cosmological constant is a dynamical variable, giving rise to a pressure p and its conjugate volume V, can be given a natural setting in the context of braneworld models. We study the specific heat capacities Cp(T) and CV(T) of the quantum version of the Bañados, Teitelboim, and Zanelli (BTZ) black hole that lives in the induced gravity theory on the brane. There are multiple branches of solutions, and we explore and characterize key features of the possible behavior. We identify and study a critical point in the space of solutions where both specific heats diverge. In the regime of weak backreaction where we are close to an ordinary theory of gravity, the black hole is “subentropic,” but as backreaction is increased we note that there are parts of parameter space that has regions where it is “superentropic.” While a study of the sign of the specific heats does not always show a corresponding instability (conjectured in the literature), the presence of strong backreaction makes interpretation unclear.

Published by the American Physical Society
2024
Probability density functions for photon propagation in a binary (isotropic-Poisson) statistical mixture with unmatched positive and negative refractive indexes
Authors: Binzoni Tiziano , Mazzolo Alain
Published: November 2024

The exact homogenized probability density function, for a photon making a step of length s has been analytically derived for a binary (isotropic-Poisson) statistical mixture with unmatched refractive indexes. The companions, exact, homogenized probability density functions for a photon to change direction (“scatter”), with polar ϑ and azimuthal φ angles, and the homogenized albedo, have also been obtained analytically. These functions also apply to negative refractive indexes and can reduce the number of Monte Carlo simulations needed for photon propagation in complex binary (isotropic-Poisson) statistical mixtures from hundreds to just one, for an equivalent homogeneous medium. Note, that this is not an approximate approach, but a mathematically equivalent and exact result. Additionally, some tutorial examples of homogenized Monte Carlo simulations are also given.

Published by the American Physical Society
2024
Importance of accounting for student identities and intersectionality for creating equitable and inclusive physics learning environments
Authors: Santana Lisabeth Marie , Singh Chandralekha
Published: November 2024

This research focuses on the experiences of seven undergraduate women who were majoring in physics in a medium-size physics department at a small liberal arts college. In the semistructured, empathetic interviews we conducted, the women discussed how they decided to major in physics, their interactions with their peers and instructors, and who supported them during their physics trajectory. We used Standpoint Theory and focused on the experiences of undergraduate women to get a holistic perspective of how they became interested in physics, how they have been supported in their physics journey, as well as identify any challenges that they faced in their undergraduate physics program due to their identity. Using the Domains of Power framework, we analyzed how those in the position of power, e.g., instructors, can play important roles in establishing and maintaining safe, equitable, and inclusive environments for students, which is especially important for historically marginalized students such as women and ethnic and racial minority students in physics.

Published by the American Physical Society
2024
Competition of vortex core structures in superfluid
He3−B
Authors: Rantanen Riku , Eltsov Vladimir
Published: November 2024

Among vortex structures identified so far in superfluid He3−B, the most common are the A-phase-core and double-core vortices. According to earlier numerical calculations, the double-core vortex is energetically favored nearly everywhere in the p−T phase diagram. Nevertheless, in experiments, the A-phase-core vortex has been observed down to temperatures of 0.6Tc at high pressures. We use the Ginzburg-Landau formalism to calculate the energies of the two vortex structures in the experimentally relevant magnetic field as well as the energy barrier for the transition between the two structures. Assigning vanishing barrier as the boundary of the metastability region of the A-phase-core vortex, we reproduce the experimentally measured vortex phase diagram and provide an explanation for the reappearance of the double-core vortex near the critical temperature Tc at low pressures: the difference in Zeeman energy between the two vortex structures becomes relatively more important close to Tc, and the A-phase-core vortex becomes unstable. In contrast to the equilibrium vortex structures, we suggest that the vortex nucleation process favors the A-phase-core vortex over the double-core vortex. Our approach can be used to analyze competition between different vortex structures in other unconventional superfluids and superconductors.

Published by the American Physical Society
2024
Triplet supercurrents in lateral Josephson junctions with a half-metallic ferromagnet
Authors: Junxiang Yao , Fermin Remko , Cabero Mariona , Lahabi Kaveh , Aarts Jan
Published: November 2024

In the area of superconducting spintronics, spin-triplet supercurrents in half-metallic ferromagnets (HMFs) could yield dissipationless spin transport over large distances and high current density. Promising among the HMFs is the perovskite oxide La0.7Sr0.3MnO3 (LSMO), and recent studies in combination with the high-Tc superconductor YBa2Cu3O7, or the conventional superconductor NbTi, showed long-range effects. Here we focus on two issues that as yet have received less attention: the value of the critical current in the HMF in the limit of a very small electrode distance (20 nm) and the nature of the spin-triplet generator. We use lateral junctions shaped as a bar, square, and disk, and find high supercurrent densities of the order of 1011 A/m2, pointing to an efficient triplet generation mechanism. This is surprising in the sense that no magnetic inhomogeneity is purposely built in, as is done in conventional metal triplet junctions. Furthermore, from the magnetic field dependence of the critical current interference patterns, we find a uniform supercurrent distribution in bar-shaped devices, but one more constricted to the rim in disk devices, which is an expected consequence of the geometry. We also analyze the temperature dependence of the critical current and find the quadratic dependence that was predicted in the limit of small junction lengths. From studying the NbTi/LSMO interface with scanning electron transmission microscopy, we conclude that the magnetic inhomogeneity required for triplet generation resides in the LSMO layer adjacent to the interface.

Published by the American Physical Society
2024
Learning Collective Cell Migratory Dynamics from a Static Snapshot with Graph Neural Networks
Authors: Yang Haiqian , Meyer Florian , Huang Shaoxun , Yang Liu , Lungu Cristiana , Olayioye Monilola A. , Buehler Markus J. , Guo Ming
Published: November 2024

Multicellular self-assembly into functional structures is a dynamic process that is critical in the development of biological structures and diseases, including embryo development, organ formation, tumor invasion, and other processes. Being able to infer collective cell migratory dynamics from their static configuration is valuable for both understanding and predicting these complex behaviors. However, the identification of structural features that can indicate multicellular motion has been difficult, and existing metrics largely rely on physical instincts. Here we show that, through the use of a graph neural network, the motion of multicellular collectives can be inferred from a static snapshot of cell positions, in both experimental and synthetic datasets.

Published by the American Physical Society
2024
Hybrid III-V/Silicon Quantum Photonic Device Generating Broadband Entangled Photon Pairs
Authors: Schuhmann J. , Lazzari L. , Morassi M. , Lemaître A. , Sagnes I. , Beaudoin G. , Amanti M.I. , Boeuf F. , Raineri F. , Baboux F. , Ducci S.
Published: November 2024

The demand for integrated photonic chips combining the generation and manipulation of quantum states of light is steadily increasing, driven by the need for compact and scalable platforms for quantum information technologies. While photonic circuits with diverse functionalities are being developed in different single material platforms, it has become crucial to realize hybrid photonic circuits that harness the advantages of multiple materials while mitigating their respective weaknesses, resulting in enhanced capabilities. Here, we demonstrate a hybrid III-V/silicon quantum photonic device combining the strong second-order nonlinearity and direct band gap of the III-V semiconductor platform with the high maturity and CMOS compatibility of the silicon photonic platform. Our device embeds the spontaneous parametric down-conversion (SPDC) of photon pairs into an AlGaAs source and their vertical routing to an adhesively bonded silicon-on-insulator circuitry, within an evanescent coupling scheme managing both polarization states. This enables the on-chip generation of broadband (>40 nm) telecom photons by type-0 and type-2 SPDC from the hybrid device, at room temperature and with internal pair generation rates exceeding 105s−1 for both types, while the pump beam is strongly rejected. Two-photon interference with 92% visibility (and up to 99% upon 5-nm spectral filtering) proves the high energy-time entanglement quality of the produced quantum state, thereby enabling a wide range of quantum information applications on chip, within a hybrid architecture compliant with electrical pumping and merging the assets of two mature and highly complementary platforms in view of out-of-the-lab deployment of quantum technologies.

Published by the American Physical Society
2024
Morphological control for hollow rod crystals of a photochromic diarylethene on spherulites by surface properties of substrates
Authors: Isobe Mami , Kitagawa Daichi , Kobatake Seiya
Published: November 2024

Sublimation methods utilizing the surface properties of substrates can address the challenge of controlling hollow morphologies in rod crystals. Spherulites were formed on the hydrophilic surface of the (0001) planes of α-quartz and sapphire substrates by sublimation of 1,2-bis(3,5-dimethyl-2-thienyl)perfluorocyclopentene (1a). Various types of hollow morphologies, distinguished by the size and shape of their cross sections and by the presence or absence of branching structures, were formed separately on α-quartz and sapphire substrates. Such precise control of the hollow morphologies was attributed to the wettability of each substrate, leading to the formation of spherulites of 1a. In addition, it was indicated that the formation process of the surface morphologies of spherulites was associated with the hollow morphologies of rod crystals of 1a.
The impact of improving element quality on the comprehensive production capacity of grain: evidence from high-standard farmland construction
Authors: Sun Xuetao , Zhao Yu , Zhang Guangsheng
Published: November 2024

Purpose

China’s overall grain production efficiency is currently relatively low, and how to improve it is key to high-quality grain development. High-standard farmland construction fills the gaps in grain production, providing a path for improving comprehensive grain production capacity.

Design/methodology/approach

This paper analyzes grain production data from 281 Chinese cities and uses the meta-Malmquist index to calculate total factor productivity (TFP) of grain and the spatial autoregressive model with spatial error (SARAR) model to analyze the impact of high-standard farmland construction on TFP of grain. Finally, it tests the model for robustness and heterogeneity.

Findings

TFP of grain has room for improvement, and technological efficiency has a greater impact on it than technological progress. TFP of grain in the eastern region is significantly higher than that in central and western regions. High-standard farmland construction can significantly improve TFP and technology efficiency of grain, and its economic benefits are directly affected by the differences in regional grain economic development. High-standard farmland construction improves TFP of grain through agricultural mechanization, and its impact is heterogeneous; TFP of grain in the (poor, plain) eastern region is more likely to share its benefits.

Originality/value

This paper evaluates whether high-standard farmland construction has achieved its purpose of enhancing comprehensive grain production capacity. It offers novel insights into elevating element quality and comprehensive grain production capacity, provides a theoretical reference from the perspective of element quality and draws corresponding policy implications for high-standard farmland.