bluuebunny/crossref_metadata_2025_split huggingface dataset:
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

AbstractA 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.
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

AbstractEctoparasitic 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

AbstractDiffusion 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.
Deep Prediction of Human Essential Genes using Weighted Protein-Protein Interaction Networks
Authors: Mehrpou Soroush , Mansoori Eghbal G. 
Published: October 2024

AbstractEssential proteins are group of proteins that are indispensable to survival and development of cells. Prediction and analysis of essential genes/proteins are crucial for uncovering the mechanisms of cells. Using bioinformatics and high-throughput technologies, forecasting essential genes/proteins by protein–protein interaction (PPI) networks have become more efficient than traditional approaches which use expensive and time-consuming experimental methods. Previous studies have found that the essentiality of genes closely relates to their properties in PPI network. In this work, we propose a supervised deep model for predicting human essential genes using neighboring details of genes/proteins in the PPI network. Our approach implements a weight-biased random walk on PPI network to get the node network context. Then, some different measures are used to get some feature vectors for each node (gene/protein) that preserve the network structure as well as the gene’s properties in the PPI network. These feature vectors are then fed to a Relational AutoEncoder to embed the genes’ features into latent space. At last, these embedded features are put into a trained classifier to predict the human essential genes. The prediction results on two human PPI networks show that our model achieves better performance than those that only refer to genes’ centrality properties in the network.
A multi-omics and cell type-specific characterization of the ventral striatum in human cocaine use disorder
Authors: Zillich Eric , Artioli Annasara , Rossetti Andrea C. , Avetyan Diana , Belschner Hanna , Frank Josef , Stein Frank , Schwarz Jennifer J. , Mechawar Naguib , Turecki Gustavo , Nöthen Markus M. , Hansson Anita C. , Witt Christian C. , Rietschel Marcella , Koch Philipp , Spanagel Rainer , Zillich Lea , Witt Stephanie H. 
Published: October 2024

AbstractEpigenome, transcriptome, and proteome analyses of postmortem brains have revealed initial molecular insights into cocaine use disorder (CUD). However, the inter-relationship between these –omics and the contribution of individual cell types remain largely unknown. We present an in-depth analysis of molecular changes in the ventral striatum in CUD at multi-omics and single-cell resolution. Integrative multi-omics analyses of microRNA-seq, RNA-seq, and proteomics datasets in 41 individuals and single-nuclei RNA-seq in a subset of 16 individuals revealed conserved deregulation of metabolic pathways, oxidative phosphorylation, and glutamatergic signaling. Cell type-specific analyses identified inverse metabolic pathway deregulation patterns in glial and neuronal cells, notably in astrocytes and medium spiny neurons (MSNs). Characterizing astrocyte-neuron crosstalk revealed altered glutamatergic and cell adhesion signaling in CUD. By applying a comprehensive multi-omics analytical framework, our study provides novel insights into CUD-associated molecular changes in the ventral striatum, suggesting astrocytes, MSNs, and their crosstalk as particularly perturbed in CUD.
Hand Position Fields of Neurons in the Premotor Cortex of Macaques during Natural Reaching
Authors: Cao Sheng-Hao , Han Xin-Yong , Zhao Zhi-Ping , Gu Jian-Wen , Jiang Tian-Zi , Yu Shan 
Published: October 2024

SummaryPlanning and execution for goal-directed movements requires the integration of the current position of body or body parts with various kinematic parameters of the movement itself. In the hippocampus, the field-based representation of spatial information plays an essential role in this process during navigation. However, if a similar, field-based encoding framework is also utilized by the motor areas during hand reaching remains unclear. In this study, we investigated the hand position tuning in the dorsal premotor cortex (PMd) neurons (n= 601) when four monkeys performing a naturalistic reach-and-grasp task. We show that 132/601 (22%) of PMd neurons increased their firing rates when the monkey’s hand occupied specific positions in the space, forming the “position fields” in their spatial firing maps that can be well described by 2D Gaussian functions/kernels. We further analyzed how the field-tuning of hand position is co-represented with other task-related parameters including the hand moving direction, speed, and reward location in the same population of PMd neurons, revealing a mixed-selective framework also similar to that discovered in the hippocampus. These position-tuned cells demonstrated high efficiency in encoding hand position, with ~10% of overall recorded neurons contributing >80% of accuracy in decoding instantaneous hand moving trajectories. These results suggest that a field-based encoding framework of position may be a common component to representing spatial information and integrating it with kinematic parameters for guiding goal-directed movements of the body or body parts.
Medieval genomes from eastern Iberia illuminate the role of Morisco mass deportations in dismantling a long-standing genetic bridge with North Africa
Authors: Oteo-García Gonzalo , Silva Marina , Foody M. George B. , Yau Bobby , Fichera Alessandro , Alapont Llorenç , Justeau Pierre , Rodrigues Simão , Monteiro Rita , Gandini Francesca , Rovira Marisa , Ribera i Lacomba Albert , Beneyto Josep Pascual , Mattiangeli Valeria , Bradley Daniel G. , Edwards Ceiridwen J. , Pala Maria , Richards Martin B. 
Published: October 2024

ABSTRACTBackgroundThe Islamic influence on the Iberian Peninsula left an enduring legacy culturally and linguistically, however the demographic impact is less well understood. This study aims to explore the dynamics of gene flow and population structure in eastern Iberia from the early to late Medieval period through ancient DNA.ResultsOur comprehensive genomic analysis uncovered gene flow from various Mediterranean regions into Iberia before the Islamic period, supporting a pre-existing pan-Mediterranean homogenization phenomenon during the Roman Empire. North African ancestry is present but sporadic in late antiquity genomes but becomes consolidated during the Islamic period. We uncovered one of the earliest dated Islamic burials in Spain, which showed high levels of inbreeding. For the first time we also prove the persistence of North African ancestry in a Christian cemetery until the 17th century, in addition to evidence of slave traffick from the Maghreb.ConclusionsThis study reveals the complex interaction between political events and cultural shifts that influenced the population of eastern Iberia. It highlights the existence of a slave trade and underscores the lasting impact of historical events, such as the Expulsion of the Moriscos in 1609 CE, on the region’s genetic and cultural landscape through mass population displacement and replacement.
A Graph Neural Network Approach to Investigate Brain Critical States Over Neurodevelopment
Authors: Cabral-Carvalho Rodrigo M. , Pinaya Walter H. L. , Sato João R. 
Published: October 2024

AbstractRecent studies show that functional resting-state dynamics may be modelled by lattice models near criticality, such as the 2D Ising model. The Ising temperature, which is the control parameter dictating the phase transitions of the model, can provide insight into the large-scale dynamics and is being used to better understand different brain states and neurodevelopment. This period is categorized by intricated changes in the microcircuits to consolidate networks. These changes influence the macroscopic brain dynamics and also its functional relations, which can be observed in functional Magnetic Resonance Imaging (fMRI). Therefore, this work investigates neurodevelopment through a novel method to estimate the Ising temperature of the brain from fMRI data using functional connectivity and Graph Neural Networks (GNNs) trained on Ising model networks. The main finding indicates a statistically significant negative correlation between age and temperature for typically developing children (𝑟 =− 0. 48, 𝑝 < 0. 0001)and also children with Attention deficit/hyperactivity disorder (ADHD) (𝑟 =− 0. 49, 𝑝 < 0. 0001). This study suggests that the brain gets distant from criticality as age increases, leading to a more ordered state.Author SummaryIn this study, we employed Graph Neural Networks to investigate functional connectivity patterns of resting-state fMRI data using the 2D Ising model as a theoretical framework to access critical dynamics. Our key finding is the significant decrease in Ising temperature with age in both typically developing children and those with ADHD, indicating a developmental transition from a high-entropy, disordered state to a more ordered, decreasing the availability of dynamical states that the system can occupy and transit in different conditions. Moreover, this decrease in temperature is crucial as it implies that the brain is moving away from criticality, leading the system to a more sub-critical regime. The correlation coefficients across the groups showed no significant differences, indicating the same developmental trajectory.
Genomic prediction in insects: a case study on wing morphology traits in the jewel waspNasonia vitripennis
Authors: Xia Shuwen , Kiss Gabriella Bukovinszkine , Megens Hendrik-Jan , Groenen Martien A.M. , Zwaan Bas J. , Bijma Piter , Pannebakker Bart A. 
Published: October 2024

AbstractBackgroundBiological control is a sustainable strategy to combat agricultural pests. Yet, due to legislation, importing non-native biocontrol agents is increasingly restricted. Thus, selective breeding of biocontrol traits of native species is suggested to enhance performance of existing biocontrol agents. Genomic prediction is a new alternative to exploit genetic variation for improving biocontrol efficacy. This study aims to establish proof-of-principle for genomic prediction in insect biocontrol agents, using wing morphology traits in the parasitoidNasonia vitripennisWalker (Pteromalidae) as a model.MethodsWe performed genomic prediction using a Genomic Best Linear Unbiased Prediction (GBLUP) model, using a total of 1,230 individuals with 8,639 SNPs generated by genotyping-by-sequencing (GBS). We used individuals from two generations from the outbred HVRx population, 717 individuals from generation G169 and 513 from generation G172. To assess genomic prediction accuracy, we used across- generation validation: forward validation for G172 from G169, backward in time validation for G169 from G172, and also 5-fold cross-validation, randomly using one fifth of the population as validiation and the others as training groups.ResultsFor size-related traits, including tibia length, wing length, width, and second moment wing area, the accuracy of genomic prediction was close to zero in both across-generation validations, but much higher in 5-fold cross-validation (ranging 0.54-0.68). For the shape-related trait wing aspect ratio, a high accuracy was found for all three validation strategies, with 0.47 for across-generation forward validation, 0.65 for across-generation backward validation, and 0.54 for 5-fold cross-validation.ConclusionPromising accuracies were observed for all traits in 5-fold cross-validation, but not in the across-generation validations. Overall, applying genomic selection in insect biocontrol agents with a relative small effective population size seems promising. However, factors such as the biology of insects, the techniques of phenotyping, and costs of large-scale genotyping still challenge the application of genomic selection to biocontrol agents.
Proximity to Visual Stimuli Reduces Post-Saccadic Alpha Lateralisation
Authors: Turner Christopher , Vuckovic Aleksandra , Learmonth Gemma , Fracasso Alessio 
Published: October 2024

AbstractPosterior alpha lateralisation is a well-established marker of visual spatial attention, with growing evidence suggesting that it may also be linked to oculomotor planning and execution. However, saccades also result in a change in visual input to the fovea, which could be linked to lateralised posterior alpha. In this study, we investigate the interplay between saccade-induced foveal input changes and lateralised posterior alpha by analysing saccades from the cue period of a Posner task and the active feedback period of a neurofeedback task, where visual stimuli were present on screen. Specifically, we examine the impact of saccade landing proximity to visual stimuli and saccade amplitude on post-saccade alpha lateralisation. Consistent with previous research, we observe a general post-saccade alpha lateralisation across both tasks. Importantly, we find that alpha lateralisation is reduced in the neurofeedback task when saccades land close to visual stimuli compared to those landing further away, while saccade amplitude has no significant effect. This investigation highlights the importance of controlling for both eye movements and visual stimuli when investigating alpha lateralisation in fixational tasks. Moreover, it shows how both oculomotor and afferent processing mechanisms affect posterior alpha lateralisation.
Thalamo-frontal connectivity patterns in Tourette Syndrome: Insights from combined intracranial DBS and EEG recordings
Authors: Wehmeyer Laura , Baldermann Juan C. , Pogosyan Alek , Plazas Fernando Rodriguez , Loehrer Philipp Alexander , Bonetti Leonardo , Yassine Sahar , Mühlen Katharina Zur , Schüller Thomas , Kuhn Jens , Visser-Vandewalle Veerle , Tan Huiling , Andrade Pablo 
Published: October 2024

AbstractThalamic deep brain stimulation (DBS) has shown clinical improvement for patients with treatment-refractory Tourette Syndrome (TS). Advancing DBS for TS requires identifying reliable electrophysiological markers. Recognising TS as a network disorder, we investigated thalamo-cortical oscillatory connectivity by combining local field potential (LFP) recordings from the DBS thalamic target region using the PerceptTMPC neurostimulator with high-density EEG in eight male TS patients (aged 27 to 38) while stimulation was off. We identified a spatially and spectrally distinct oscillatory network connecting the medial thalamus and frontal regions in the alpha band (8–12 Hz), with connectivity strength negatively correlated with TS symptom severity. Moreover, reduced thalamo-frontal alpha connectivity before tic onset, localised in sensorimotor regions and the inferior parietal cortex, suggests its direct role in tic generation. Importantly, associations with symptoms and pre-tic dynamics were specific to connectivity patterns and not evident in the pure power spectra. These findings underscore the importance of investigating electrophysiological oscillatory connectivity to characterise pathological network connections in TS, potentially guiding stimulation-based interventions and future research on closed-loop DBS for TS.
RIPK2 is crucial for the microglial inflammatory response to bacterial muramyl dipeptide but not to lipopolysaccharide
Authors: Yang Changjun , Machado da Silva Maria Carolina , Howell John A. , Larochelle Jonathan , Liu Lei , Gunraj Rachel E. , Pinheiro de Oliveira Antônio Carlos , Candelario-Jalil Eduardo 
Published: October 2024

AbstractReceptor-interacting serine/threonine protein kinase 2 (RIPK2) is a kinase that plays an essential role in the modulation of innate and adaptive immune responses. As a downstream signaling molecule for nucleotide-binding oligomerization domain 1 (NOD1), NOD2, and Toll-like receptors (TLRs), it is implicated in the signaling triggered by recognition of microbe-associated molecular patterns by NOD1/2 and TLRs. Upon activation of these innate immune receptors, RIPK2 mediates the release of pro-inflammatory factors by activating mitogen-activated protein kinases (MAPKs) and nuclear factor-kappa B (NF-κB). However, whether RIPK2 is essential for downstream inflammatory signaling following the activation of NOD1/2, TLRs, or both remains controversial. In this study, we examined the role of RIPK2 in NOD2- and TLR4-dependent signaling cascades following stimulation of microglial cells with bacterial muramyl dipeptide (MDP), a NOD2 agonist, or lipopolysaccharide (LPS), a TLR4 agonist. We utilized a highly specific proteolysis targeting chimera (PROTAC) molecule, GSK3728857A, and found dramatic degradation of RIPK2 in a concentration- and time-dependent manner. Importantly, the PROTAC completely abolished MDP-induced increases in iNOS and COX-2 protein levels and pro-inflammatory gene transcription ofNos2,Ptgs2,Il-1β,Tnfα,Il6,Ccl2, andMmp9. However, increases in iNOS and COX-2 proteins and pro-inflammatory gene transcription induced by the TLR4 agonist, LPS, were only slightly attenuated with the GSK3728857A pretreatment. Further findings revealed that the RIPK2 PROTAC completely blocked the phosphorylation and activation of p65 NF-κB and p38 MAPK induced by MDP, but it had no effects on the phosphorylation of these two mediators triggered by LPS. Collectively, our findings strongly suggest that RIPK2 plays an essential role in the inflammatory responses of microglia to bacterial MDP but not to LPS.