bluuebunny/crossref_metadata_2025 huggingface dataset:
Device placement using Laplacian PCA and graph attention networks
Authors: Han Meng , Zeng Yan , Shu Hao , Yue Lupeng , Zhang Jilin , Wan Jian , Ren Yongjian
Published: October 2024

The exponential growth in data and parameters in modern neural networks has created the need to distribute these models across multiple devices for efficient training, resulting in the device placement problem. Existing graph encoding approaches for device placement suffer from low efficiency when searching for optimal parallel strategies, primarily due to suboptimal positional information retrieval. To address these challenges, we propose the Laplacian Principal Component Analysis-graph attention networks (LPCA-GAT) model. Firstly, we employ GAT to capture complex relationships between nodes and generate node encodings. Secondly, we leverage LPCA on the graph Laplacian matrix to extract crucial low-dimensional positional information. Finally, by integrating these two components, we obtain the final node encodings. This enhances the representation capability of nodes within the graph, enabling efficient device placement. The experimental results demonstrate that LPCA-GAT achieves superior device placement results, specifically accelerating execution and computation time by 13.24% and 96.38%, respectively, leading to significant improvements in both operational efficiency and performance.
Convergence of an adaptive C0-interior penalty Galerkin method for the biharmonic problem
Authors: Dominicus Alexander , Gaspoz Fernando D , Kreuzer Christian
Published: October 2024

We develop a basic convergence analysis for an adaptive ${C}^{0}\mathsf{IPG}$ method for the biharmonic problem that provides convergence without rates for all practically relevant marking strategies and all penalty parameters assuring coercivity of the method. The analysis hinges on embedding properties of (broken) Sobolev and BV spaces, and the construction of a suitable limit space. In contrast to the previous convergence result of adaptive discontinuous Galerkin methods for elliptic PDEs, here we have to deal with the fact that the Lagrange finite element spaces may possibly contain no proper $C^{1}$-conforming subspace. This prevents from a straight forward generalization and requires the development of some new key technical tools.
Large language model uncertainty proxies: discrimination and calibration for medical diagnosis and treatment
Authors: Savage Thomas , Wang John , Gallo Robert , Boukil Abdessalem , Patel Vishwesh , Safavi-Naini Seyed Amir Ahmad , Soroush Ali , Chen Jonathan H
Published: October 2024

Introduction

The inability of large language models (LLMs) to communicate uncertainty is a significant barrier to their use in medicine. Before LLMs can be integrated into patient care, the field must assess methods to estimate uncertainty in ways that are useful to physician-users.

Objective

Evaluate the ability for uncertainty proxies to quantify LLM confidence when performing diagnosis and treatment selection tasks by assessing the properties of discrimination and calibration.

Methods

We examined confidence elicitation (CE), token-level probability (TLP), and sample consistency (SC) proxies across GPT3.5, GPT4, Llama2, and Llama3. Uncertainty proxies were evaluated against 3 datasets of open-ended patient scenarios.

Results

SC discrimination outperformed TLP and CE methods. SC by sentence embedding achieved the highest discriminative performance (ROC AUC 0.68-0.79), yet with poor calibration. SC by GPT annotation achieved the second-best discrimination (ROC AUC 0.66-0.74) with accurate calibration. Verbalized confidence (CE) was found to consistently overestimate model confidence.

Discussion and Conclusions

SC is the most effective method for estimating LLM uncertainty of the proxies evaluated. SC by sentence embedding can effectively estimate uncertainty if the user has a set of reference cases with which to re-calibrate their results, while SC by GPT annotation is the more effective method if the user does not have reference cases and requires accurate raw calibration. Our results confirm LLMs are consistently over-confident when verbalizing their confidence (CE).
Enhancing photosynthetic phosphorus use efficiency through coordination of leaf phosphorus fractions, allocation, and anatomy during soybean domestication
Authors: Chen Geng , Ran Qiu-Xia , Wang Cai , Pang Jiayin , Ren Ming-Jian , Wang Zheng-Yu , He Jin , Lambers Hans
Published: October 2024

Soybean domestication has significantly changed key agronomic traits, yet its impact on leaf photosynthetic phosphorus use efficiency (PPUE) and its underlying traits remains poorly known. Further information on this would be important to increase soybean P use efficiency. To address this gap, 48 soybean accessions (16 wild relatives, 16 landraces, and 16 cultivars) were used to compare leaf anatomical traits, foliar chemical P fractions, P allocation, and PPUE under two P levels. The results showed that the cultivars had higher area-based and mass-based photosynthesis rates, PPUE, metabolite P concentration, and its percentage of leaf total P, as well as a greater percentage of lipid P, nucleic acid P, and residual P. Conversely, wild relatives tended to have higher leaf P concentration, palisade:spongy thickness ratio, and concentrations of inorganic P, nucleic acid P, lipid P, and residual P. PPUE was negatively correlated with leaf inorganic P concentration and its percentage relative to leaf total P, while it was positively correlated with the concentration and percentage of metabolite P. We concluded that soybean domestication increased PPUE, as a result of both increased photosynthesis rate and decreased leaf P concentration; domestication reduced the palisade:spongy thickness ratio coupled with increased allocation of P to P-containing metabolites, thereby contributing to faster photosynthesis and higher PPUE. This study sheds light on the significance of leaf P allocation and anatomical traits affecting PPUE during soybean domestication, offering a mechanistic understanding to further enhance soybean P use efficiency.
Trade literature provides a path from research to practice
Authors: Dobre Silvia , Herbert Rachel , Hicks Diana
Published: October 2024

The work of professionals practicing in the community provides a pathway for knowledge advances to reach practice. Yet outside of medicine, little attention has been paid to this phenomenon. Similarly, professions are defined by bodies of knowledge yet studies of professions do not attend to the dynamic relationship between professionals and the ever advancing frontiers of knowledge. In this paper, we delineate the pathway from research to practice as evidenced in trade literature. Our analysis is based on bibliometric and survey data. We find evidence that trade literature is informed by research in references to research papers found in trade periodicals, and trade press articles authored by researchers. Professionals feed back their advances in practice to the community by writing articles for trade publications, and sometimes these are articles are cited by scholarly journal articles, thus the exchange of knowledge is bi-directional to a certain extent. Our survey established that many professionals read trade literature because the contents are relevant to their practice. They trust, with caveats, the material they read but trust more in material with an obvious connection to public sector research. Professionals can often point to ways their practice has improved due to something they read in a trade periodical. Thus the trade literature has institutionalized a mechanism of indirect linkage between research and practice. Indexing trade periodicals could provide a valuable resource for those wishing to make visible the connection between research and practice.
Assessment of radiological contamination due to gold mining in soil and food crops of Babban Tsauni, Gwagwalada, Nigeria
Authors: Odelami Kafayat Abdulrasheed , Oladipo Mark Omotola Afolayan , Onoja Michael Akor , Musa Yahaya , Aremu Saudat Olabisi
Published: October 2024

This work assessed the activity concentrations of 238U(226Ra), 232Th, and 40K and their associated radiological risks due to exposure to soil and consumption of food crops in Babban Tsauni artisanal gold mine, Gwagwalada, Nigeria, using the gamma spectrometry technique. The mean activity concentrations of 226Ra, 232Th, and 40K in the mine soil were 60.2 ± 9.9, 161.4 ± 16.2, and 664.6 ± 138.2, while they were 46.4 ± 4.9, 79.9 ± 39.3, 266.4 ± 185.4 for tubers and 46.9 ± 15.7, 100.5 ± 35.8, 311.4 ± 132.7 (Bq/kg) for grains, respectively. The results reveal that the activity concentrations of radionuclides in all samples exceeded the recommended values set by United Nations Scientific Committee on the Effects of Atomic Radiation (33, 45, and 420 Bq/kg) except 40K, which fell within the acceptable limit in all food crop sample types. Estimated results for radiological hazard parameters, radium equivalent, annual effective dose due to ingestion, and excess life cancer risk were within safe limits, while the annual effective dose due to external gamma radiation in soil and annual gonadal equivalent dose were significantly high in all investigated samples; these call for constant radiological monitoring.
“The Damage is Permanent”: Law, Women’s “Honor,” and the Psychiatrization of Sexual Violence in Post-reform Turkey
Authors: Ellialtı-Köse Tuğçe
Published: October 2024

Existing literature is deeply divided on the effectiveness of rape law reforms. Intervening in this literature, this article examines the workings and consequences of ostensibly gender-neutral and victim-friendly reforms in Turkey. Through court observations, document analysis, and interviews with legal actors, I show how complex—and gendered—notions of victimization, harm, and trauma are embedded in sexual assault laws. I argue that the law defines sexual violence as inherently and invariably traumatizing, causing symptoms that can be identified and evidenced through the examination of the mental states of survivors, thus psychiatrizing it. This psychiatrization rests on the idea that rape primarily, and unequivocally, damages women’s “honor.” Consequently, the category of “legitimate victimhood” does not disappear; rather, it is reinvented by medico-legal logics that invoke gendered norms of honor and morality, which infuse and shape deliberations of justice in cases of sexual violence.
PRC2 facilitates the transition from heterotrophy to photoautotrophy during seedling emergence
Authors: Samo Naseem , Trejo-Arellano María Guadalupe , Gahurová Lenka , Erban Alexander , Ebert Alina , Rivière Quentin , Kubásek Jiří , Aflaki Fatemeh , Hönig Mondeková Helena , Schlereth Armin , Dubois Annick , Zhou Mingxi , Novák Ondřej , Šantrůček Jiří , Bouyer Daniel , Roudier Franҫois , Kopka Joachim , Mozgová Iva
Published: October 2024

Seed-to-seedling transition represents a key developmental and metabolic switch in plants. Catabolism of seed storage reserves fuels germination and early seedling emergence until photosynthesis is established. The developmental transition is controlled by Polycomb repressive complex 2 (PRC2). However, the coordination of PRC2 activity and its contribution to transcriptional reprogramming during seedling establishment is unknown. By analysing the re-distribution of H3K27me3 and changes in gene transcription in shoot and root tissues of heterotrophic and photoautotrophic seedlings, we reveal two phases of PRC2-mediated gene repression. The first phase is independent of light and photosynthesis and results in irreversible repression of the embryo maturation programme, marked by heterotrophy and biosynthesis of reserve storage molecules. The second phase is associated with the repression of metabolic pathways related to germination and early seedling emergence, and H3K27me3 deposition in this phase is sensitive to photosynthesis inhibition. We show that preventing transcription of the PRC2-repressed glyoxylate cycle geneISOCITRATE LYASEis sufficient to drive the vegetative phase transition in PRC2-depleted plants. This underscores a key role of PRC2 repression in the coordinated metabolic and developmental switches during seedling emergence and emphasizes the close connection between metabolic and developmental identities.
Selection, Design and Immunogenicity Studies of ASFV Antigens for Subunit mRNA Cocktail Vaccines with Specific Immune Response Profiles
Authors: Yuan Fangfeng , Cui Junru , Wang Tianlei , Qin Jane , Jeon Ju Hyeong , Ding Huiming , Whittaker Charles A. , Xu Renhuan , Cao Helen , Chen Jianzhu
Published: October 2024

Development of safe and effective subunit vaccines for controlling African Swine Fever Virus (ASFV) infection has been hampered by a lack of protective viral antigens, complex virion structures, and multiple mechanisms of infection. Here, we selected ASFV antigens based on their localization on the virion, known functions, and homologies to the subunits of the protective vaccinia virus vaccine. We also engineered viral capsid proteins for inducing optimal antibody responses and designed T cell-directed antigen for inducing broad and robust cellular immunity. The selected antigens in lipid nanoparticle-mRNA formulations were evaluated for immunogenicity in both mice and pigs with concordant results. Different antigens induced divergent immune response profiles, including the levels of IgG and T cell responses and effector functions of anti-sera. We further developed a computational approach to combine antigens into cocktails for inducing specific immune response profiles and validated candidate cocktail vaccines in mice. Our results provide a basis for further evaluating candidate subunit mRNA vaccines in challenge studies.

Teaser

Novel strategies to develop subunit vaccines for ASFV and other complex large DNA viruses.
The Role of Semantic Inhibition in Aesthetic Appreciation: fNIRS Evidence from Poetry Reading
Authors: Liu Huishu , Xu Xiaomeng , Sun Wanyan , Zhang Dan , Zhang Yu
Published: October 2024

Background

Aesthetic education is pivotal in shaping a comprehensive and harmonious humanity. However, the transition from semantic comprehension to aesthetic appreciation remains poorly understood. This study, informed by transactional theory, sought to elucidate the cognitive mechanisms of aesthetic reading by examining its neural dynamics through functional Near-Infrared Spectroscopy.

Methods

Participants were tasked with reading Tang poetry aesthetically, with fNIRS monitoring brain activity in frontal and temporal regions.

Results

Compared to an efferent reading task, the aesthetic reading task revealed a distinct three-stage neural dynamic pattern. Initially, aesthetic reading showed similar HbO activation in all regions, likely indicating the semantic processing phase. This was followed by a divergence, with a decrease in HbO over the left primary somatosensory cortex and the left superior, inferior, and middle temporal gyri, suggesting inhibition of semantic processing. Finally, a resurgence of activity in these areas was observed, along with an increase in HbO over the left dorsolateral prefrontal cortex, which could be associated with memory, imagination, and empathy. This reactivation correlated with participants’ self-reported aesthetic appreciation scores.

Contribution

The findings reveal the temporal and spatial dynamics of brain activity during aesthetic reading, enhancing our comprehension of underlying cognitive processes.
Time-dependent computational model of post-traumatic osteoarthritis to estimate how mechanoinflammatory mechanisms impact cartilage aggrecan content
Authors: Eskelinen ASA , Kosonen JP , Hamada M , Esrafilian A , Florea C , Grodzinsky AJ , Tanska P , Korhonen RK
Published: October 2024

Degenerative musculoskeletal diseases like osteoarthritis can be initiated by joint injury. Injurious overloading-induced mechanical straining of articular cartilage and subsequent biological responses may trigger cartilage degradation. One early sign of degradation is loss of aggrecan content which is potentially accelerated near chondral lesions under physiological loading. Yet, the mechanoinflammatory mechanisms explaining time-dependent degradation in regions with disparate mechanical loading are unclear and challenging to assess with experiments alone. Here, we developed computational models unraveling potential mechanisms behind aggrecan content adaptation. Incorporating mechanical strain-driven cell damage and downstream proteolytic enzyme release, fluid flow-driven aggrecan depletion, and fluid pressure-stimulated regulation of aggrecan biosynthesis, the models agreed with experiments and exhibited 14%-points greater near-lesion aggrecan loss after 12 days of physiological loading compared to without loading. This significant advancement in mechanistic understanding incorporated into cartilage adaptation model can help in development and guidance of personalized therapies, such as rehabilitation protocols and tissue- engineered constructs.
Accelerated multi-shell diffusion MRI with Gaussian process estimated reconstruction of multi-band imaging
Authors: Ye Xinyu , Miller Karla , Wu Wenchuan
Published: October 2024

Purpose

This work aims to propose a robust reconstruction method exploiting shared information across shells to increase the acquisition speed of multi-shell diffusion MRI, enabling rapid tissue microstructure mapping.

Theory and Methods

Local q-space points share similar information. Gaussian Process can exploit the q-space smoothness in a data-driven way and provide q-space signal estimation based on the signals from a q-space neighborhood. The Diffusion Acceleration with Gaussian process Estimated Reconstruction (DAGER) method uses the signal estimation from Gaussian process as a prior in a joint k-q reconstruction and improves image quality under high acceleration factors compared to conventional (k-only) reconstruction. In this work, we extend the DAGER method by introducing a multi-shell covariance function and correcting for Rician noise distribution in magnitude data when fitting the Gaussian process model. The method was evaluated with both simulation and in vivo data.

Results

Simulated and in-vivo results demonstrate that the proposed method can significantly improve the image quality of reconstructed dMRI data with high acceleration both in-plane and slice-wise, achieving a total acceleration factor of 12. The improvement of image quality allows more robust diffusion model fitting compared to conventional reconstruction methods, enabling advanced multi-shell diffusion analysis within much shorter scan time.

Conclusion

The proposed method enables highly accelerated dMRI which can shorten the scan time of multi-shell dMRI without sacrificing quality compared to conventional practice. This may facilitate a wider application of advanced dMRI models in basic and clinical neuroscience.
DeepPaint: A deep-learning package for Cell Painting Image Classification
Authors: Luna Diego , Johnson Erik C. , Dunphy Laura J. , McQuillen Ryan
Published: October 2024

Recent developments in the high-content imaging (HCI) space have allowed for the production of large Cell Painting datasets. These datasets are typically derived from cells exposed to a set of biological perturbants including proteins, small molecules, or even pathogens. While the method of Cell Painting has shown utility for drug discovery and hazard evaluation purposes, traditional analyses pipelines applied Cell Painting datasets typically require the segmentation of single cells from thousands to millions of images, a process that is time-consuming and subject to noise and experimental variability. Here we present DeepPaint, a Python package that uses a deep learning framework to perform image analysis of cell painting images including treatment classification and latent space analysis, circumventing the need for image segmentation. DeepPaint is easily tunable to different HCI setups and datasets and can be applied to classify broad types of biological perturbations. Here we demonstrate that DeepPaint can generate highly accurate neural networks for binary and multiclass classification of cell painting images. The DeepPaint package and example notebooks are freely available athttps://github.com/jhuapl-bio/DeepPaint.
Overcoming ploidy barriers: the role of triploid bridges in the genetic introgression ofCardamine amara
Authors: Bartolić P , Voltrová A , Macková L , Šrámková G , Šlenker M , Mandáková T , García N Padilla , Marhold K , Kolář F
Published: October 2024

Polyploidisation is a significant reproductive barrier, yet genetic evidence indicates that interploidy admixture is more common than previously thought. Theoretical models and controlled crosses support the ‘triploid bridge’ hypothesis supposing that hybrids of intermediate ploidy facilitate gene flow. However, comprehensive evidence combining experimental and genetic data is missing.

In this study, we investigated the rates and directions of gene flow within a diploid– autotetraploid contact zone ofCardamine amara, a species with abundant natural triploids. We cytotyped over 400 wild individuals, conducted reciprocal interploidy crosses and inferred gene flow based on genome-wide sequencing of 84 individuals.

Triploids represent a conspicuous entity in mixed-ploidy populations (5%), yet only part of them arose through interploidy hybridisation. Despite being rarely formed, triploid hybrids can backcross with their parental cytotypes, producing viable offspring that are often euploid (in 42% of cases). In correspondence, we found a significant genome-wide signal of gene flow for sympatric, but not allopatric, diploids and tetraploids. Coalescent simulations demonstrated significant bidirectional introgression which is stronger in the direction towards the tetraploid cytotype.

Triploids, though rare, play a key role in overcoming polyploidy-related reproductive barriers. We present integrative evidence for bidirectional interploidy gene flow mediated by a triploid bridge in natural populations.
Regulating Human T Lymphocytes Through Magnetogenetic Tools
Authors: Helalat Seyed Hossein , Téllez Rodrigo C. , Kristinsdóttir Helga Thora , Petersen Astrid Dolinger , Islam Seder Fayyad , Pardo Carlos Rodriguez , Sun Yi
Published: October 2024

The field of synthetic biology has expanded the possibilities for controlling cellular functions, particularly in the development of mammalian cells for therapeutic applications. This study explored the application of magnetogenetic tools to regulate T cell activity, a crucial aspect of developing advanced immunotherapies. Magnetogenetic tools use magnetic fields to remotely control engineered ion channels and protein domains, providing non-invasive, deep-tissue stimulation that overcomes the limitations of traditional methods. We investigated the effects of three magnetogenetic tools - engineered TRPV1 (TRP1-Fer) and TRPV4 (TRP4-Fer) channels, and Electromagnetic Perceptive Gene (EPG) - in Jurkat cells. First, calcium concentration measurements confirmed the activity of these tools within the cells. Using qPCR and proteomics analysis, we then analyzed their impact on T cell activation, calcium signaling, mitochondrial function, membrane integrity, and gene expression under both stimulated (with antigens) and non-stimulated conditions. Our results revealed significant upregulation of activation and calcium-handling proteins in stimulated cells, indicating enhanced activation and cytoskeletal dynamics compared to controls. However, in non-stimulated cells, the magnetogenetic tools unexpectedly led to deactivation of T cells. This investigation showed that while magnetic induction alone deactivated the cells, antigen stimulation in conjunction with magnetic induction amplified cell activation.

This study highlights the potential of magnetogenetics to precisely modulate T cell functions, presenting promising avenues for more effective and controlled immunotherapies. However, the findings also underscore the need for careful optimization to mitigate potential adverse effects on cellular integrity and function.
A novel epigenetic clock for rhesus macaques unveils an association between early life adversity and epigenetic age acceleration
Authors: Bronk Gabriel , Lardenoije Roy , Koolman Laura , Klengel Claudia , Dan Shu , Howell Brittany R. , Morin Elyse L. , Meyer Jerrold S. , Wilson Mark E. , Ethun Kelly F. , Alvarado Maria C. , Raper Jessica , Bravo-Rivera Hector , Kenwood Margaux M. , Roseboom Patrick H. , Quirk Gregory J. , Kalin Ned H. , Binder Elisabeth B. , Sanchez Mar M. , Klengel Torsten
Published: October 2024

Because DNA methylation changes reliably with age, machine learning models called epigenetic clocks can estimate an individual’s age based on their DNA methylation profile. This epigenetic measure of age can deviate from one’s true age, and the difference between the epigenetic age and true age, known as epigenetic age acceleration (EAA), has been found to directly correlate with morbidity and mortality in adults. Emerging evidence suggests that EAA is also associated with aberrant health outcomes in children, making epigenetic clocks useful tools for studying aging and development. We developed two highly accurate epigenetic clocks for the rhesus macaque, utilizing 1,008 blood samples from 690 macaques between 2 days and 23.4 years of age with diverse genetic backgrounds and exposure to environmental conditions. The first clock, which is trained on all samples, achieves a Pearson correlation between true age and predicted age of 0.983 and median absolute error of 0.210 years. To study phenotypes during development, the second clock is optimized for macaques younger than 6 years and achieves a Pearson correlation of 0.974 and a median absolute error of 0.148 years. Using the latter clock, we investigated whether epigenetic aging is affected by early life adversity in the form of infant maltreatment. Our data suggests that maltreatment and increased hair cortisol levels are associated with epigenetic age acceleration right after the period of maltreatment.
HEMIBIOTROPHIC INFECTION OF SUNFLOWER ROOT CELLS BY THE PARASITEOROBANCHE CUMANAWALLR
Authors: Khablak S.H. , Spychak V.M. , Abdullaieva Y A. , Blume Ya.B.
Published: October 2024

The process of infection of different sunflower hybrids by Orobanche cumana was studied according to the way the pathogen interacts with the components of root cells. The study of the behavior of sunflower root cells during the penetration of Gaustoria showed not biotrophic, but hemibiotrophic process of infection of hybrids with the pathogen. In the hemibiotrophic mixed type of sunflower infection, broomrape initially develops as a biotrophic pathogen and, with the help of effectors, suppresses the course of immune reactions and forms multicellular haustoria, which at a certain stage of growth break the membrane bags of cells, leading to cytoplasmic leakage and causing the death of root cells as a necrotrophic pathogen. The discovery of the hemibiotrophic process of sunflower broomrape infection opens a new promising direction in reducing the infection of hybrids with the parasite through the induction of systemic acquired resistance (SAR) by drugs that cause the formation of reactive oxygen species and trigger plant defense responses through programmed cell death at the sites of infection and cause pathogen necrosis. The process of infection of cells and the emergence of reverse immune responses in plants when infected with pathogens has similar features and a similar course of protective responses. In the interaction between broomrape and sunflower, resistance mechanisms may act to stop the pathogen in the root cortex, in the entodermis, or after reaching the central cylinder. The cell wall is the first obstacle that pathogens have to overcome. The cell membranes of growing cells have a “primary” structure. Cell walls are composed of cellulose and matrix substances (hemicelluloses, pectins, and proteins). In cells that have already formed, the cell walls are reinforced with lignin, suberin, and kalose. Sunflower’s defense reactions against broomrape consist of strengthening the cell wall through the deposition of lignin, suberin, accumulation of callose, protective proteins and cross-linking of proteins that prevent the parasite from penetrating and communicating with the host vascular system. Lignin, suberin and callose polymers strengthen the cell wall structure by increasing its stiffness at the site of infection to limit the penetration of the parasite.
Leveraging Transfer Learning for Predicting Protein-Small Molecule Interactions
Authors: Wang Jian , Dokholyan Nikolay V.
Published: October 2024

A complex web of intermolecular interactions defines and regulates biological processes. Understanding this web has been particularly challenging because of the sheer number of actors in biological systems: ∼104proteins in a typical human cell offer a plausible 108interactions. This number grows rapidly if we consider metabolites, drugs, nutrients, and other biological molecules. The relative strength of interactions also critically affects these biological processes. However, the small and often incomplete datasets (103-104protein-ligand interactions) traditionally used for binding affinity predictions limit the ability to capture the full complexity of these interactions. To overcome this challenge, we developed Yuel 2, a novel neural network-based approach that leverages transfer learning to address the limitations of small datasets. Yuel 2 is pre-trained on a large-scale dataset to learn intricate structural features and then fine-tuned on specialized datasets like PDBbind to enhance the predictive accuracy and robustness. We show that Yuel 2 predicts multiple binding affinity metrics – Kd, Ki, and IC50 – between proteins and small molecules, offering a comprehensive representation of molecular interactions crucial for drug design and development.
Compulsive coping behaviour, which goal trackers do not develop, is exacerbated by chronic atomoxetine
Authors: Chernoff Chloe S , Belin-Rauscent Aude , Puaud Mickael , Torrisi Sebastiano A , Fouyssac Maxime S , Nemeth Bence , Yu Charlotte , Higuera-Matas Alejandro , Jones Susan , Belin David
Published: October 2024

Loss of control over coping strategies can result in the development of impulsive/compulsive spectrum disorders (ICSDs) such as obsessive-compulsive disorder or trichotillomania. Rats, like humans, show individual differences in their tendency to engage in and maintain control over coping behaviours. While most rats exposed to a schedule-induced polydipsia (SIP) procedure develop a controlled, moderate, coping polydipsic drinking response, some vulnerable individuals engage in excessive, compulsive drinking, or hyperdipsia. The development of hyperdipsia depends in part on noradrenergic mechanisms, as it is prevented by the noradrenaline reuptake inhibitor, atomoxetine in highly impulsive vulnerable individuals. However, whether noradrenergic mechanisms also underlie the expression of well-established hyperdipsia, or if other traits confer vulnerability to its development, are unknown. In two longitudinal studies in male Sprague Dawley rats, we investigated whether well-established hyperdipsia is influenced by atomoxetine and if its development is predicted by the ICSD-relevant sign-tracking trait. Sign-tracking predicted faster acquisition of adjunctive drinking but not the transition to hyperdipsia, while goal-tracking protected against the latter. Chronic atomoxetine exacerbated well-established hyperdipsia; post-mortem qPCR assays revealed that this was associated with increased cFos and zif268 mRNA, markers of cellular activity and plasticity, across the dorsal striatum. Atomoxetine also altered the transcriptomic landscape of the nucleus accumbens shell and the pattern of cFos and zif268 expression in the amygdalo-striatal system. These results provide new insights into the biobehavioural basis of compulsive behaviours, revealing a differential noradrenergic control of the development and the expression of compulsive coping.
Simulations reveal how touchdown kinematic variables affect top sprinting speed: implications for coaching
Authors: Haralabidis Nicos , Eaton Ashton J. , Delp Scott L. , Hicks Jennifer L.
Published: October 2024

Sprint performance is a priority for coaches and athletes. Several kinematic variables, including horizontal touchdown distance (HTD) and inter-knee touchdown distance (IKTD), are targeted by coaches to increase top sprinting speed. However, the results of past research are conflicting, potentially due to the use of experimental inter-athlete study designs where it is not possible to establish cause-effect relationships. In this study, we used a predictive simulation approach to assess cause-effect relationships between HTD and IKTD and sprinting speed. We scaled a three-dimensional musculoskeletal model to match the anthropometry of an international caliber male sprinter, and generated predictive simulations of a single symmetric step of top-speed sprinting using a direct collocation optimal control framework. We first used our simulation framework to establish the model’s top speed with minimal constraints on touchdown kinematics (the optimal simulation). Then, in additional simulations we enforced specific HTD or IKTD values (± 2, 4 and 6 cm compared to optimal). The model achieved a top speed of 11.85 m/s in the optimal simulation. Shortening HTD by 6 cm reduced speed by 7.3%, while lengthening HTD by 6 cm had a smaller impact on speed, with a 1.6% reduction. Speed in the simulation was insensitive to the IKTD changes we tested. The results of our simulations indicate there is an optimal HTD to maximize sprinting speed, providing support for coaches and athletes to adjust this technique variable. Conversely, our results do not provide evidence to support utilizing IKTD as a key technique variable for speed enhancement. We share the simulation framework so researchers can explore the effects of additional modifications on sprinting performance (https://github.com/nicos1993/Pred_Sim_Sprinting).
Decoding Spatial Tissue Architecture: A Scalable Bayesian Topic Model for Multiplexed Imaging Analysis
Authors: Peng Xiyu , Smithy James W. , Yosofvand Mohammad , Kostrzewa Caroline E. , Bleile MaryLena , Ehrich Fiona D. , Lee Jasme , Postow Michael A. , Callahan Margaret K. , Panageas Katherine S. , Shen Ronglai
Published: October 2024

Recent progress in multiplexed tissue imaging is advancing the study of tumor microenvironments to enhance our understanding of treatment response and disease progression. Cellular neighborhood analysis is a popular computational approach for these complex image data. Despite its popularity, there are significant challenges, including high computational demands that limit feasibility for largescale applications and the lack of a principled strategy for integrative analysis across images. This absence hampers the precise and consistent identification of spatial features and tracking of their dynamics over disease progression. To overcome these challenges, we introduceSpatialTopic, a spatial topic model designed to decode high-level spatial architecture across multiplexed tissue images.SpatialTopicintegrates both cell type and spatial information within a topic modelling framework, originally developed for natural language processing and adapted for computer vision. Spatial information is incorporated into the flexible design of documents, representing densely overlapping regions in images. We employ an efficient collapsed Gibbs sampling algorithm for model inference. We benchmarked the performance against five state-of-the-art algorithms through various case studies using different single-cell spatial transcriptomic and proteomic imaging platforms across different tissue types. We show thatSpatialTopicis highly scalable on large-scale image datasets with millions of cells, along with high precision and interpretability. Our findings demonstrate thatSpatialTopicconsistently identifies biologically and clinically significant spatial “topics” such as tertiary lymphoid structures (TLSs) and tracks dynamic changes in spatial features over disease progression. Its computational efficiency and broad applicability across various molecular imaging platforms will enhance the analysis of large-scale tissue imaging datasets.
Dissecting Regulatory Non-Coding Heart Disease GWAS Loci with High-Resolution 3D Chromatin Interactions Reveals Causal Genes with Pathophysiological Relevance to Heart Failure
Authors: Gill Richard , Lu Daniel R. , Eres Ittai , Lu Jiamiao , Cui Jixin , Yu Zhongsheng , Yamawaki Tracy , Zhou Hong , Pei Baikang , Amrute Junedh M. , Ang Yen-Sin , Wang Songli , Lavine Kory J. , Ason Brandon , Li Chi-Ming , Hsu Yi-Hsiang
Published: October 2024

Heart failure is caused in part by cardiac remodeling processes that include the death of cardiac myocytes and their replacement by cardiac fibroblasts. We hypothesized that these two cell types may harbor epigenetic contexts in which heart disease-associated non-coding SNPs perturb gene expression relevant to disease. Accordingly, we generated high-resolution Hi-C data layered with chromatin accessibility and transcriptomic information to annotate and link putative distal regulatory elements in heart disease-associated loci to gene promoters. Our analysis identified several target genes with established roles in cardiac fibrosis and/or heart disease (GJA1,TBC1D32, CXCL12,IL6R, andFURIN). Perturb-seq in cardiac fibroblasts to knock out putative regulatory elements confirmed regulatory relationships involvingGJA1,CXCL12, andFURIN, as gene editing led to changes in transcriptomic signatures associated with fibroblasts in heart failure. Our results demonstrate how integrative multi-omic approaches can delineate pathophysiologically relevant regulatory circuits that connect protein-coding genes to non-coding genetic variants associated with disease.
Influence of Cognitive Demand and auditory noise on Postural Dynamics
Authors: Carey Sam , Balasubramaniam Ramesh
Published: October 2024

The control of human balance involves an interaction between the human motor, cognitive, and sensory systems. The dynamics of this interaction are yet to be fully understood, however, work has shown the performance of cognitive tasks to have a hampering effect on motor performance, while additive sensory noise to have a beneficial effect. The current study aims to examine whether postural control will be impacted by a concurrent working memory task, and similarly, if additive noise can counteract the expected negative influence of the added cognitive demand. Postural sway of healthy young adults was collected during the performance of a modified N-back task with varying difficulty, in the presence and absence of auditory noise. Our results show a reduction in postural stability scaled to the difficulty of the cognitive task, but this effect is less prominent in the presence of additive noise. Additionally, by separating postural sway into different frequency bands, typically used to assess the exploratory vs feedback-driven stabilizing dynamics of sway, we found a differential effect between the cognitive task and additive noise, thus demonstrating that both frequency regimes of postural sway are sensitive to high cognitive load and increased sensory information.
Essential Yet Dispensable: The Role of CINNAMATE 4-HYDROXYLASE in Rice Cell Wall Lignification
Authors: Supatmi  , Lam Lydia Pui Ying , Yamamoto Senri , Afifi Osama A. , Ji Pingping , Osakabe Yuriko , Osakabe Keishi , Umezawa Toshiaki , Tobimatsu Yuki
Published: October 2024

A comprehensive understanding of the intricate lignin biosynthesis in grasses could contribute to enhancing our ability to utilize grass biomass. CINNAMATE 4-HYDROXYLASE (C4H), in conjunction with PHENYLALANINE AMMONIA-LYASE (PAL), initiates the entry of phenylalanine into the cinnamate/monolignol pathway, leading to the production of diverse phenylpropanoids, including lignin monomers. Despite extensive research on C4H in eudicots, genetic studies of C4H in grasses remain considerably limited. Notably, the role of C4H in the presence of PHENYLALANINE/TYROSINE AMMONIA-LYASE (PTAL), a grass-specific ammonia-lyase that can bypass the conserved PAL-C4H pathway by recruiting tyrosine into the cinnamate/monolignol pathway, remains unclear. To address this gap, a set of genome-edited rice mutants harboring knockout mutations in riceC4Hgenes were generated and subjected to the analysis of growth phenotype and cell wall chemotype, alongside isotopic feeding and chemical inhibitor assays to test the contributions of the PAL-C4H and PTAL pathways. The phenotype and chemotype characterizations ofC4H-knockout rice mutants demonstrated that class I (OsC4H1/CYP73A38) and class II (OsC4H2a/CYP73A39 and OsC4H2b/CYP73A40) C4Hs cooperatively contribute to lignin biosynthesis in rice. Nevertheless, the impacts ofC4H-deficiency on plant development and lignin formation in rice appeared to be less prominent compared to those reported in eudicots. The13C-labeled phenylalanine and tyrosine feeding experiments demonstrated that even with the phenylalanine-derived PAL-C4H pathway completely blocked, theC4H-knockout rice can still produce significant levels of lignin and maintain sound cell walls by utilizing the tyrosine-derived PTAL pathway. Overall, this study demonstrates the essential but dispensable role of C4H in grass cell wall lignification.
Inferring post-transcriptional regulation within and across cell types in human testis
Authors: Khan Saad , Elcheikhali Megan , Leduc Andrew , Huffman R Gray , Derks Jason , Franks Alexander , Slavov Nikolai
Published: October 2024

Single-cell tissue atlases commonly use RNA abundances as surrogates for protein abundances. Yet, protein abundance also depends on the regulation of protein synthesis and degradation rates. To estimate the contributions of such post transcriptional regulation, we quantified the proteomes of 5,883 single cells from human testis using 3 distinct mass spectrometry methods (SCoPE2, pSCoPE, and plexDIA). To distinguish between biological and technical factors contributing to differences between protein and RNA levels, we developedBayesPG, a Bayesian model of transcript and protein abundance that systematically accounts for technical variation and infers biological differences. We useBayesPGto jointly model RNA and protein data collected from 29,709 single cells across different methods and datasets.BayesPGestimated consensus mRNA and protein levels for 3,861 gene products and quantified the relative protein-to-mRNA ratio (rPTR) for each gene across six distinct cell types in samples from human testis. About 28% of the gene products exhibited significant differences at protein and RNA levels and contributed to about 1, 500 significant GO groups. We observe that specialized and context specific functions, such as those related to spermatogenesis are regulated after transcription. Among hundreds of detected post translationally modified peptides, many show significant abundance differences across cell types. Furthermore, some phosphorylated peptides covary with kinases in a cell-type dependent manner, suggesting cell-type specific regulation. Our results demonstrate the potential of inferring protein regulation in from single-cell proteogenomic data and provide a generalizable model,BayesPG, for performing such analyses.
Mouth-attaching copepodSalmincola markewitschireduces the body condition and growth of juvenile salmonidSalvelinus leucomaenisby decreasing host feeding activity: evidence from parasite removal experiment
Authors: Murakami Leo , Hasegawa Ryota , Aruga Nozomi , Sato Nobuhiro , Nakamura Shingo , Kajihara Hiroshi , Koizumi Itsuro
Published: October 2024

Ectoparasitic copepods in the genusSalmincolaWilson, 1915 are considered harmful to host salmonids, yet experimental studies on whether and how these copepods affect hosts are critically limited. We evaluated the effects of the mouth-attachingSalmincola markewitschiShedko and Shedko, 2002 on juvenile white-spotted charrSalvelinus leucomaenis(Pallas, 1814) using a parasite removal experiment where all individuals were artificially infected, and then parasites were removed in one group (i.e., treatment), while the copepods were left in another group (i.e., control). We hypothesized that the copepods reduce host feeding, thereby reducing host body condition and growth. The alternative hypothesis is that parasites do not change host feeding, or even increase because of the compensation for the negative effect. In this case, host condition and growth would not be reduced. The control group (parasite remained) had lower food consumption, body condition, and growth compared to the treatment (parasite removed). Thus,S. markewitschinegatively affected hosts by reducing host feeding, and no behavioral compensation was observed. It remains unknown, however, whether reduced feeding was due to impaired swallowing or physiological stresses caused by infections. Further experiments on gill- and body-surface-attachingSalmincolaspecies could provide deeper insights into how these parasites influence host health.
Big Data, Small Bias: Harmonizing Diffusion MRI-Based Structural Connectomes to Mitigate Site-Related Bias in Data Integration
Authors: Shen Rui Sherry , Parker Drew , Chen Andrew An , Yerys Benjamin E. , Tunç Birkan , Roberts Timothy P.L. , Shinohara Russell T. , Verma Ragini
Published: October 2024

Diffusion MRI-based structural connectomes are increasingly used to investigate brain connectivity changes associated with various disorders. However, small sample sizes in individual studies, along with highly heterogeneous disorder-related manifestations, underscore the need to pool datasets across multiple studies to be able to identify coherent and generalizable connectivity patterns linked to these disorders. Yet, combining datasets introduces site-related differences due to variations in scanner hardware or acquisition protocols. These differences highlight the necessity for statistical data harmonization to mitigate site-related effects on structural connectomes while preserving the biological information associated with participant demographics and the disorders. While several paradigms exist for harmonizing normally distributed neuroimaging measures, this paper represents the first effort to establish a harmonization framework specifically tailored for the structural connectome. We conduct a thorough investigation of various statistical harmonization methods, adapting them to accommodate the unique distributional characteristics and graph-based properties of structural connectomes. Through rigorous evaluation, we demonstrate that the generalized linear model with a log-linked gamma model (gamma-GLM) outperforms other approaches in modeling structural connectomes, enabling the effective removal of site-related biases in both edge-based and downstream graph analyses while preserving biological variability. Two real-world applications further highlight the utility of our harmonization framework in addressing challenges in multi-site structural connectome analysis. Specifically, harmonization with gamma-GLM enhances the generalizability of connectome-based machine learning predictors to new datasets and increases statistical power for detecting group-level differences. Our work provides essential guidelines for harmonizing multi-site structural connectomes, paving the way for more robust discoveries through collaborative research in the era of team science and big data.