bluuebunny/crossref_metadata_2025_split huggingface dataset:
Modulation of pedunculopontine input to the basal ganglia relieves motor symptoms in Parkinsonian mice
Authors: Lin Caixia , Ridder Margreet , Zhong Jinhao , Albornoz Eduardo A. , Sedlak Petra , Xu Li , Woodruff Trent M. , Chen Fangyi , Sah Pankaj 
Published: March 2024

AbstractLocomotion, the ability to move, is driven by central pattern generators in the spinal cord. However, its initiation, selection of gait and arrest are controlled by command centers in the brain stem of which the best understood is the mesencephalic locomotor region (MLR). Stimulation of the MLR can initiate or arrest movement, but its neural projections and the neural circuits that mediate these actions are poorly understood. Here we show that glutamatergic neurons in the pedunculopontine nucleus (PPN), a major part of the MLR, project to the substantial nigra pars reticulata (SNr) where they innervate neurons that send afferents to the ventro medial motor thalamus (VM). Stimulation of this input to the SNr in mice slows voluntary and driven movement by modifying gait, with higher frequencies arresting gait. In Parkinsons disease (PD), a neurodegenerative disorder, the cardinal symptoms are bradykinesia, tremor and rigidity. Using an mouse model of PD, we show that inhibition of PPN input to the SNr rescues bradykinesia. This is the first description of a circuit in the mammalian brain that regulates movement and gait selection. Targeting of this circuit may be a more effective modality for treating the motor symptoms of PD.
A subtle modification of modafinil-based DAT inhibitors changes conformational preference
Authors: Lee Kuo Hao , Camacho-Hernandez Gisela A. , Newman Amy Hauck , Shi Lei 
Published: March 2024

AbstractModafinil analogs with either a sulfoxide or sulfide moiety have improved binding affinities at the human dopamine transporter (hDAT) compared to modafinil, with lead sulfoxide-substituted analogs showing characteristics of atypical inhibition (e.g., JJC8-091). Interestingly, the only distinction between sulfoxide and sulfide substitution is the presence of one additional oxygen atom. To elucidate why such a subtle difference in ligand structure can result in different typical or atypical profiles, we investigated two pairs of analogs. Our quantum mechanical calculations revealed a more negatively charged distribution of electrostatic potential surface of the sulfoxide substitution. Using molecular dynamics simulations, we demonstrated that sulfoxide-substituted modafinil analogs have a propensity to attract more water into the binding pocket. They also exhibited a tendency to dissociate from Asp79 and form a new interaction with Asp421, consequently promoting an inward-facing conformation of DAT. In contrast, sulfide-substituted analogs did not display these effects. These findings deepen our understanding of the functionally relevant conformational spectrum of DAT.
Deletion of Robo4 worsens neuroinflammation and motor coordination in a mouse model of Alzheimer’s disease
Authors: Cullen Abigail E , Winder Nick R , Lee Byron , Krishna Kumaran Sahana , Arora Nayantara , Wolf Julia R , Henson Grant D , Woltjer Randy L , Walker Ashley E 
Published: March 2024

AbstractDeclines in vascular integrity are potential contributors to Alzheimer’s disease (AD) as these result in increased blood-brain barrier permeability and, as a consequence, accelerate neuroinflammation and cognitive impairment. Roundabout guidance receptor 4 (Robo4) is primarily expressed in endothelial cells and stabilizes the vasculature, and thus, has the potential to protect the brain in AD. To study the effect of Robo4 on neuroinflammation and cognitive function in the context of AD, we compared Robo4 knockout and wildtype mice crossed with mice with and without AD mutations (APP/tau). We found that the knockout of Robo4 led to greater astrocyte activation, as demonstrated by GFAP content, but this was dependent on the brain region studied. The knockout of Robo4 also led to greater activated microglia, as assessed by Iba1 content, but only in the presence of AD-related mutations. We found that AD mutations, but not Robo4, were associated with cognitive dysfunction measured by a nest-building test. In contrast, Robo4 deletion, but not AD mutations, was associated with impaired motor coordination. Lastly, Robo4 deletion was associated with greater arterial stiffness, but this trend did not reach statistical significance. In summary, these results demonstrate that Robo4 impacts neuroinflammation, motor coordination, and arterial stiffness, however, the impact on neuroinflammation is dependent on the presence/absence of AD-related mutations and the brain region examined.
The Ramp protocol: Uncovering individual differences in walking to an auditory beat using TeensyStep
Authors: Zagala Agnès , Foster Nicholas E.V. , van Vugt Floris T. , Dal Maso Fabien , Dalla Bella Simone 
Published: March 2024

AbstractIntentionally walking to the beat of an auditory stimulus seems effortless for most humans. However, studies have revealed significant individual differences in the spontaneous tendency to synchronize. Some individuals tend to adapt their walking pace to the beat, while others show little or no adjustment. To fill this gap we introduce the Ramp protocol, which measures spontaneous adaptation to a change in an auditory rhythmic stimulus in a gait task. First, participants walk at their preferred cadence without stimulation. After several steps, a metronome is presented, timed to match the participant’s heel-strike. Then, the metronome tempo progressively departs from the participant’s cadence by either accelerating or decelerating. The implementation of the Ramp protocol required real-time detection of heel-strike and auditory stimuli aligned with participants’ preferred cadence. To achieve this, we developed the TeensyStep device, which we validated compared to a gold standard for step detection. We also demonstrated the sensitivity of the Ramp protocol to individual differences in the spontaneous response to a tempo-changing rhythmic stimulus by introducing a new measure: the Response Score. This new method and quantification of spontaneous response to rhythmic stimuli holds promise for highlighting and distinguishing different profiles of adaptation in a gait task.
An engineered human cardiac tissue model reveals contributions of systemic lupus erythematosus autoantibodies to myocardial injury
Authors: Fleischer Sharon , Nash Trevor R. , Tamargo Manuel A. , Lock Roberta I. , Venturini Gabriela , Morsink Margaretha , Li Vanessa , Lamberti Morgan J. , Graney Pamela L. , Liberman Martin , Kim Youngbin , Zhuang Richard Z. , Whitehead Jaron , Friedman Richard A. , Soni Rajesh K. , Seidman Jonathan G. , Seidman Christine E. , Geraldino-Pardilla Laura , Winchester Robert , Vunjak-Novakovic Gordana 
Published: March 2024

ABSTRACTSystemic lupus erythematosus (SLE) is a highly heterogenous autoimmune disease that affects multiple organs, including the heart. The mechanisms by which myocardial injury develops in SLE, however, remain poorly understood. Here we engineered human cardiac tissues and cultured them with IgG fractions containing autoantibodies from SLE patients with and without myocardial involvement. We observed unique binding patterns of IgG from two patient subgroups: (i) patients with severe myocardial inflammation exhibited enhanced binding to apoptotic cells within cardiac tissues subjected to stress, and (ii) patients with systolic dysfunction exhibited enhanced binding to the surfaces of viable cardiomyocytes. Functional assays and RNA sequencing (RNA-seq) revealed that IgGs from patients with systolic dysfunction exerted direct effects on engineered tissues in the absence of immune cells, altering tissue cellular composition, respiration and calcium handling. Autoantibody target characterization by phage immunoprecipitation sequencing (PhIP-seq) confirmed distinctive IgG profiles between patient subgroups. By coupling IgG profiling with cell surface protein analyses, we identified four pathogenic autoantibody candidates that may directly alter the function of cells within the myocardium. Taken together, these observations provide insights into the cellular processes of myocardial injury in SLE that have the potential to improve patient risk stratification and inform the development of novel therapeutic strategies.
Differential predictive value of resident memory CD8+T cell subpopulations in non-small-cell lung cancer patients treated by immunotherapy
Authors: Paolini Léa , Tran Thi , Corgnac Stéphanie , Villemin Jean-Philippe , Wislez Marie , Arrondeau Jennifer , Johannes Ludger , Ulmer Jonathan , Vieillard Louis-Victorien , Pineau Joséphine , Gey Alain , Quiniou Valentin , Barennes Pierre , Pham Hang Phuong , Gruel Nadège , Hasan Milena , Libri Valentina , Mella Sébastien , De Percin Sixtine , Boudou-Rouquette Pascaline , Cremer Isabelle , Blons Hélène , Leroy Karen , Laurent-Puig Pierre , De Saint Basile Hortense , Gibault Laure , Ravel Patrice , Chouaib Fathia Mami- , Goldwasser François , Fabre Elizabeth , Damotte Diane , Tartour Eric 
Published: March 2024

AbstractA high density of resident memory T cells (TRM) in tumors correlates with improved clinical outcomes in immunotherapy-treated patients. However, in preclinical models, only some subpopulations of TRMare associated with cancer vaccine efficacy.We identified two main TRMsubpopulations in tumor-infiltrating lymphocytes derived from non-small cell lung cancer (NSCLC) patients: one co-expressing CD103 and CD49a (DP), and the other expressing only CD49a (MP); both exhibiting additional TRMsurface markers like CD69. DP TRMexhibited greater functionality compared to MP TRM. Analysis of T-cell receptor (TCR) repertoire and of the stemness marker TCF-1 revealed shared TCRs between populations, with the MP subset appearing more progenitor-like phenotype. In two NSCLC patient cohorts, only DP TRMpredicted PD-1 blockade response. Multivariate analysis, including various biomarkers (CD8, TCF1+CD8+T cells, and PD-L1) associated with responses to anti-PD(L)1, showed that only intra-tumoral infiltration by DP TRMremained significant. This study highlights the non-equivalence of TRMpopulations and emphasizes the importance of distinguishing between them to better define their role in antitumor immunity and as a biomarker of response to immunotherapy.
High-resolution perfusion imaging in rodents using pCASL at 9.4 T
Authors: Pires Monteiro Sara , Hirschler Lydiane , Barbier Emmanuel L. , Figueiredo Patricia , Shemesh Noam 
Published: March 2024

AbstractAdequate perfusion is critical for maintaining normal brain function and aberrations thereof are hallmarks of many diseases. Pseudo-Continuous Arterial Spin Labeling (pCASL) MRI enables noninvasive perfusion mapping without contrast agent injection and with higher signal-to-noise ratio (SNR) than alternative methods. Despite its great potential, pCASL remains challenging, unstable, and relatively low-resolution in rodents – especially in mice – thereby limiting the investigation of perfusion properties in many transgenic or other relevant rodent models of disease. Here, we address this gap by developing a novel experimental setup for high-resolution pCASL imaging in mice and combining it with the enhanced SNR of cryogenic probes. We show that our new experimental setup allows for optimal positioning of the carotids within the cryogenic coil, rendering labelling reproducible. With the proposed methodology, we managed to increase the spatial resolution of pCASL perfusion images by a factor of 15 in mice; a factor of 6 in rats is gained compared to the state of the art just by virtue of the cryogenic coil. We also show that the improved pCASL perfusion imaging allows much better delineation of specific brain areas, both in healthy animals as well as in rat and mouse models of stroke. Our results bode well for future high-definition pCASL perfusion imaging in rodents.Data availabilityData will be freely made available upon request.
Microsaccadic suppression of peripheral perceptual detection performance as a function of foveated visual image appearance
Authors: Greilich Julia , Hafed Ziad M. 
Published: March 2024

AbstractMicrosaccades are known to be associated with a deficit in perceptual detection performance for brief probe flashes presented in their temporal vicinity. However, it is still not clear how such a deficit might depend on the visual environment across which microsaccades are generated. Here, and motivated by studies demonstrating an interaction between visual background image appearance and perceptual suppression strength associated with large saccades, we probed peripheral perceptual detection performance of human subjects while they generated microsaccades over three different visual backgrounds. Subjects fixated near the center of a low spatial frequency grating, a high spatial frequency grating, or a small white fixation spot over an otherwise gray background. When a computer process detected a microsaccade, it presented a brief peripheral probe flash at one of four locations (over a uniform gray background), and at different times. After collecting full psychometric curves, we found that both perceptual detection thresholds and slopes of psychometric curves were impaired for peripheral flashes in the immediate temporal vicinity of microsaccades, and they recovered with later flash times. Importantly, the threshold elevations, but not the psychometric slope reductions, were stronger for the white fixation spot than for either of the two gratings. Thus, like with larger saccades, microsaccadic suppression strength can show a certain degree of image-dependence. However, unlike with larger saccades, stronger microsaccadic suppression did not occur with low spatial frequency textures. This observation might reflect the different spatio-temporal retinal transients associated with the small microsaccades in our study versus larger saccades.
WITHDRAWN: DiDBiT-TMT: A novel method to quantify changes in the proteomic landscape induced by neural plasticity
Authors: Gamaleldin Mariam , Yu Nam-Kyung , Diedrich Jolene K , Ma Yuanhui , Wienand Anne , McClatchy Daniel B. , Nykjaer Anders , Nabavi Sadegh , Yates John R. 
Published: March 2024

Withdrawal StatementThe authors have withdrawn this manuscript because during the peer review process in the journal, it was discovered that one of the processed proteomic data groups (the chemical LTP group) was mistakenly processed from the raw data for the norepinephrine group, resulting in an apparent complete overlap between the two conditions.For a correct analysis, please refer to the currently published peer-reviewed publication through the following DOI:https://doi.org/10.1021/acs.jproteome.4c00180Therefore, the authors do not wish this preprint to be cited as reference for the project. If you have any questions, please contact the corresponding author.
Inter-modality source coupling: a fully-automated whole-brain data-driven structure-function fingerprint shows replicable links to reading in a large-scale (N∼8K) analysis
Authors: Kotoski Aline , Liu Jingyu , Morris Robin , Calhoun Vince 
Published: March 2024

AbstractObjectiveBoth structural and functional brain changes have been individually associated with developing cognitive processes such as reading. However, there is limited research about the combined influence of resting-state functional and structural magnetic resonance imaging (rs-fMRI and sMRI) features in reading development, which could provide insights into the interplay between brain structure and function in shaping cognitive growth. We propose a method called inter-modality source coupling (IMSC) to study the coupling between the rs-fMRI and sMRI and its relationship to reading ability in school-age children.MethodsThis approach is applied to baseline data from four thousand participants (9-11 years) and replicated in a second group. Our analysis focused on the relationship of IMSC to overall reading score.ResultsOur findings indicate that higher reading ability was linked with increased function-structure coupling among higher-level cortical regions, particularly those links between the inferior parietal lobule and inferior frontal areas, and conversely, lower reading ability was associated with enhanced function-structure coupling among the fusiform and lingual gyrus. Our study found evidence of spatial correspondence between the data indicating an interplay between brain structure and function in our participants.ConclusionOur approach revealed a linked pattern of whole brain structure to the corresponding functional connectivity pattern that correlated with reading ability. This novel IMSC analysis method provides a new approach to study the multimodal relationship between brain function and structure.SignificanceThese findings have interesting implications for understanding the multimodal complexity underlying the development of the neural basis for reading ability in school-aged children.
Protein language models are biased by unequal sequence sampling across the tree of life
Authors: Ding Frances , Steinhardt Jacob 
Published: March 2024

AbstractProtein language models (pLMs) trained on large protein sequence databases have been used to understand disease and design novel proteins. In design tasks, the likelihood of a protein sequence under a pLM is often used as a proxy for protein fitness, so it is critical to understand what signals likelihoods capture. In this work we find that pLM likelihoods unintentionally encode a species bias: likelihoods of protein sequences from certain species are systematically higher, independent of the protein in question. We quantify this bias and show that it arises in large part because of unequal species representation in popular protein sequence databases. We further show that the bias can be detrimental for some protein design applications, such as enhancing thermostability. These results highlight the importance of understanding and curating pLM training data to mitigate biases and improve protein design capabilities in under-explored parts of sequence space.
CLCluster: a redundancy-reduction contrastive learning-based clustering method of cancer subtype based on multi-omics data
Authors: Wang Hong , Zhang Yi , Li Wen , Wang Zhenlong , Wei Zhen , Yang Mengyuan 
Published: March 2024

AbstractAlternative splicing (AS) enables the regulated generation of multiple mRNA and protein products from a single gene. Cancer cells have general, cancer type-specific, and subtype-specific alterations in the splicing process that can have predictive value and contribute to cancer diagnosis, prognosis, and treatment. Currently, multi-omics data have been used to identify the molecular subtype of cancer. However, alternative splicing is rarely used to identify the cancer subtypes. Here, we propose a redundancy-reduction contrastive learning-based method (CLCluster) based on copy number variation, DNA methylation, gene expression, miRNA expression, and alternative splicing for cancer subtype clustering of 33 cancer types. Experimental results demonstrate the superior performance of the proposed CLCluster model in identifying cancer subtypes over the currently available state-of-the-art clustering methods. Moreover, ablation experiments demonstrate the advantages of alternative splicing data for cancer subtyping tasks. We performed multiple analyses for cancer subtype-related AS events, including open reading frame annotation, and RNA binding protein-associated alternative splicing regulation. From our analysis, we identified 2,930 AS events that were associated with patient survival, and ORF analysis showed that 417 of them could cause in-frame and 420 could cause frameshift. we also identified 1,752 RBP-AS regulatory pairs that could be associated with patient survival. Accurate classification of the cancer type using CLCluster, and effective annotation of cancer subtype related AS events can effectively facilitate the identification of patient’s therapeutically targetable AS events.
Are ChatGPT and Copilot Reliable for Health Education on Statistical Testing?
Authors: Rovetta Alessandro , Mansournia Mohammad Ali 
Published: March 2024

AbstractThe introduction of Artificial Intelligence (AI) has revolutionized daily life and scientific research, with applications ranging from writing scientific articles to clinical assistance. However, the effectiveness of AI models like ChatGPT 3.5 by Open AI and Bing Copilot GPT-4 by Microsoft in explaining complex concepts such as statistical testing is a cause for concern. This study investigates the ability of these AI models to explain fundamental statistical concepts, such as P-values, confidence intervals, and surprisals, crucial to properly inform conclusions in scientific research and public health. Our results highlight significant misconceptions in both AI models’ understanding and teaching of inferential statistics. These deficiencies include the mixing of incompatible statistical approaches, the nullism fallacy, the dichotomization of (statistical) significance, the incorrect interpretation of statistical measures and concepts, and an overestimation of the role of p-values and confidence intervals. Additionally, both models lack knowledge of recent alternative statistical methods like S-values and S-intervals, showing biases similar to those present in traditional statistical approaches. Given the importance of accurate statistical understanding in various sectors and the widespread integration of AI in decision-making processes, urgent intervention by OpenAI and Microsoft is necessary to update their platform databases. It is essential to align AI knowledge with the latest developments in scientific research to ensure the reliability of generated results. Collaboration with organizations such as the American Statistical Association is recommended to facilitate this process. In conclusion, this scenario underscores the need for immediate corrective action by the developing companies of such platforms. Indeed, only through continuous updates and improvements can we ensure that AI can contribute positively to scientific and technological progress.
Directional swimming patterns in jellyfish aggregations
Authors: Malul Dror , Berman Hadar , Solodoch Aviv , Tal Omri , Barak Noga , Mizrahi Gur , Berenshtein Igal , Toledo Yaron , Lotan Tamar , Sher Daniel , Shavit Uri , Lehahn Yoav 
Published: March 2024

AbstractHaving a profound influence on marine and coastal environments worldwide, jellyfish hold significant scientific, economic, and public interest. The predictability of outbreaks and dispersion of jellyfish is limited by a fundamental gap in our understanding of their movement. Although there is evidence that jellyfish may actively affect their position, the role of active swimming in controlling jellyfish movement, and the characteristics of jellyfish swimming behavior, are not well understood. Consequently, jellyfish are often regarded as passively drifting or randomly moving organisms, both conceptually and in process studies. Here we show that the movement of jellyfish is controlled by distinctly directional swimming patterns, which are oriented against the direction of surface gravity waves. Taking a Lagrangian viewpoint from drone videos that allows the tracking of multiple adjacent jellyfish, and focusing the scyphozoan jellyfishRhopilema nomadicaas a model organism, we show that the behavior of individual jellyfish translates into a synchronized directional swimming of the aggregation as a whole. Numerical simulations show that this counter-wave swimming behavior results in biased correlated random-walk movement patterns that reduce the risk of stranding, thus providing jellyfish with an adaptive advantage critical to their survival. Our results emphasize the importance of active swimming in regulating jellyfish movement, and open the way for a more accurate representation in model studies, thus improving the predictability of jellyfish outbreaks and their dispersion, and contributing to our ability to mitigate their possible impact on coastal infrastructure and populations.