bluuebunny/crossref_metadata_2025_split huggingface dataset:
Novel verbal instructions recruit abstract neural patterns of time-variable information dimensionality
Authors: Pena Paula , Palenciano Ana F. , González-García Carlos , Ruz María 
Published: July 2024

AbstractHuman performance is endowed by neural representations of information that is relevant for behavior, some of which are also activated in a preparatory fashion to optimize later execution. Most studies to date have focused on highly practiced actions, leaving largely unaddressed the novel re-configuration of information to generate unique whole task-sets. Using electroencephalography (EEG), this study investigated the dynamics of the content and geometry reflected on the neural patterns of control representations during re-configuration of information. We designed a verbal instruction paradigm where each trial involved novel combinations of multi-component task information. By manipulating three task-relevant factors in a sample of 40 participants (26 females, 14 males), we observed complex coding schemes throughout the trial, during both preparation and implementation stages. The temporal profiles were consistent with a hierarchical structure: whereas task information was active in a sustained manner, the coding of more concrete stimulus features was more transient. Data showed both high dimensionality and abstraction, particularly during instruction encoding and target processing. Our results suggest that whenever task content could be recovered from neural patterns of activity, there was evidence of abstract coding, with an underlying geometry that favored generalization. During target processing, where potential interference across stimulus and response factors increased, orthogonal configurations also appeared. Overall, our findings uncover the dynamic manner with which control representations operate during novel recombination unique scenarios, with changes in dimensionality and abstraction adjusting along processing stages.Significance StatementThe neural mechanisms that support task performance in novel contexts have been largely overlooked. Cognitive control is thought to enable complex behavior through the active maintenance of task sets, containing essential information for execution. However, how novel whole combinations of information are organized in neural patterns and their temporal dependencies remain unknown. Here, using a novel complex instruction paradigm, we observed that coding of informational content and its underlying geometry followed a dynamic temporal pattern. Our results reveal varying dimensionality and abstraction throughout the trial, with neural codes generally structured in a geometry favoring generalization of relevant information across task demands. These findings provide a first glimpse into the temporal computations engaged by the brain when encountering novel recombination settings.
Modelling genetic risk of β-cell dysfunction in human induced pluripotent stem cells from patients carrying theMTNR1Brisk variant
Authors: Singh T. , Kalamajski S. , Cunha J.P.M.C.M. , Hladkou S. , Roberts F. , Gheibi S. , Soltanian A. , Yektay Farahmand K. , Ekström O. , Mamidi A. , Franks P.W. , Rosengren A. , Semb H. , Mulder H. , Fex M. 
Published: July 2024

AbstractDisruptions in circadian rhythm, partly controlled by the hormone melatonin, increase the risk of type 2 diabetes (T2D). Accordingly, a variant of the gene encoding the melatonin receptor 1B (MTNR1B) is robustly associated with increased risk of T2D. This single nucleotide polymorphism (SNP; rs10830963; G-allele) is an expression quantitative trait locus (eQTL) in human pancreatic islets, conferring increased expression ofMTNR1B, which is thought to perturb pancreatic β-cell function. To understand this pathogenic mechanism in detail, we utilized human induced pluripotent stem cells (hiPSC), derived from individuals with T2D carrying theMTNR1BG-allele. Patient-derived fibroblasts were reprogrammed to hiPSC and single-base genome editing by CRISPR/Cas9 was employed to create isogenic lines of either the C/C or G/G genotypes (non-risk and risk, respectively). In addition, the human embryonic stem cell (hESC) line (HUES4) was subjected to genome editing to create isogenic lines of either the C/C or G/G genotypes. hiPSC and hESC were differentiated into β-cells, using a 50-day 2D protocol. Single-base genome editing generated cells with the desired genotype at a success rate of >90%. Expression of stage-specific markers confirmed differentiation of both hiPSC and hESC into β-cells.MTNR1BmRNA levels were consistently low in differentiated β-cells, precluding quantitative analysis of gene expression. However, Western blot analysis showed higher levels of MTNR1B in differentiated β-cells carrying the risk allele, consistent with rs10830963 (G-allele) being an eQTL in β-cells. Insulin secretion in response to glucose and IBMX was similar between the genotypes, whereas addition of melatonin reduced secretion in G-allele carriers. We conclude that the stem cell-derived β-cells are not sufficiently mature to allow determination of eQTL status at the mRNA level. However, we did observe increased MTNR1B protein and increased sensitivity of β-cells from risk allele carriers (G-allele) to melatonin with regard to insulin secretion, thus supporting a functional role for the rs10830963 SNP in β-cell dysfunction.
Adaptive Safety Coding in the Prefrontal Cortex
Authors: Tashjian Sarah M. , Cussen Joseph , Deng Wenning , Zhang Bo , Mobbs Dean 
Published: July 2024

AbstractPivotal to self-preservation is the ability to identify when we are safe and when we are in danger. Previous studies have focused on safety estimations based on the features of external threats and do not consider how the brain integrates other key factors, including estimates about our ability to protect ourselves. Here we examine the neural systems underlying the online dynamic encoding of safety. The current preregistered study used two novel tasks to test four facets of safety estimation:Safety Prediction,Meta-representation,Recognition, andValue Updating. We experimentally manipulated safety estimation changing both levels of external threats and self-protection. Data were collected in two independent samples (behavioralN=100; fMRIN=30). We found consistent evidence of subjective changes in the sensitivity to safety conferred through protection. Neural responses in the ventromedial prefrontal cortex (vmPFC) tracked increases in safety during all safety estimation facets, with specific tuning to protection. Further, informational connectivity analyses revealed distinct hubs of safety coding in the posterior and anterior vmPFC for external threats and protection, respectively. These findings reveal a central role of the vmPFC for coding safety.
Hysteresis and noise floor in gene expression optimised for persistence against lethal events
Authors: Bokes Pavol , Singh Abhyudai 
Published: July 2024

AbstractBacterial cell persistence, crucial for survival under adverse conditions like antibiotic exposure, is intrinsically linked to stochastic fluctuations in gene expression. Certain genes, while inhibiting growth under normal circumstances, confer tolerance to antibiotics at elevated expression levels. The occurrence of antibiotic events lead to instantaneous cellular responses with varied survival probabilities correlated with gene expression levels. Notably, cells with lower protein concentrations face higher mortality rates. This study aims to elucidate an optimal strategy for protein expression conducive to cellular survival. Through comprehensive mathematical analysis, we determine the optimal burst size and frequency that maximise cell proliferation. Furthermore, we explore how the optimal expression distribution changes as the cost of protein expression to growth escalates. Our model reveals a hysteresis phenomenon, characterised by discontinuous transitions between deterministic and stochastic optima. Intriguingly, stochastic optima possess a noise floor, representing the minimal level of fluctuations essential for optimal cellular resilience.
Interactions between weather, ungulates and geese create opportunities for wood-pasture cycles
Authors: Kramer Koen , Cornelissen Perry , Groot Bruinderink Geert W.T.A. , Kuiters Loek , Lammertsma Dennis , Vulink J. Theo , van Wieren Sip E. , Prins Herbert H.T. 
Published: July 2024

AbstractManaging nature reserves to achieve coexistence of ungulate species and vegetation heterogeneity is challenging in small reserves. A central question is whether spatial heterogeneity is maintained or restored through occasional natural disturbances. This is the premise of the wood-pasture hypothesis, which asserts that natural disturbances, such as winter severity, are sufficiently significant to sustain the long-term coexistence of ungulate species and provide opportunities for the establishment of shrubs and trees, thereby enhancing vegetation heterogeneity. Testing the wood-pasture hypothesis under field conditions necessitates long-term time series of both vegetation and herbivore dynamics. Therefore, we employed a modeling approach to test this hypothesis.The study area was the Oostvaardersplassen, a nature reserve in the Netherlands characterized by rich and productive clay soil. This area hosts an assemblage of Heck cattle, Konik horses, and red deer. Additionally, large numbers of geese frequent this reserve, competing for the same food resources. The Oostvaardersplassen is one of the few areas in Europe where neither the populations of coexisting herbivore species nor the vegetation have been managed and its development was monitored for several decades. This provides unique insights into natural herbivore-vegetation interactions that can be applied to the management of other nature reserves.The results indicate that weather variability and the presence of both geese and large ungulates are essential factors in creating a heterogeneous landscape. The general pattern is that weather variability induces fluctuations in ungulate numbers, and geese reduce the numbers of ungulates. Coexistence of the three ungulate species remains possible regardless of weather variability and the presence of geese. However, the presence of the largest ungulate, cattle, is threatened when weather is highly variable and geese numbers are high. The vegetation is likely evolving towards a predominantly open landscape with occasional opportunities for the establishment of spiny shrub species. Nature reserves managed with an assemblage of ungulate species, which numbers are controlled by food supply, winter severity and competition, should thus focus on the substantial presence of a few species (“biomassality,” e.g., for migratory birds) rather than achieving the highest species diversity in a small area (“biodiversity”).
Olfactory cortical outputs recruit and shape distinct brain-wide spatiotemporal networks
Authors: Ma Teng , Wang Xunda , Lin Xuehong , Wen Junjian , Xie Linshan , Khong Pek-Lan , Cao Peng , Wu Ed X. , Leong Alex T. L. 
Published: July 2024

AbstractOdor information is transmitted from the olfactory bulb to several primary olfactory cortical regions in parallel, including the anterior olfactory nucleus (AON) and piriform cortex (Pir). However, the specific roles of the olfactory bulb and cortical outputs in wider interactions with other interconnected regions throughout the brain remain unclear due to the lack of suitable in vivo techniques. Furthermore, emerging associations between olfactory-related dysfunctions and neurological disorders underscore the need for examining olfactory networks at the systems level. Using optogenetics, fMRI, and computational modeling, we interrogated the spatiotemporal properties of brain-wide neural interactions in olfactory networks. We observed distinct downstream recruitment patterns. Specifically, stimulation of excitatory projection neurons in OB predominantly activates primary olfactory network regions, while stimulation of OB afferents in AON and Pir primarily orthodromically activates hippocampal/striatal and limbic networks, respectively. Temporally, repeated OB or AON stimulation diminishes neural activity propagation brain-wide in contrast to Pir stimulation. Dynamic causal modeling analysis reveals a robust inhibitory effect of AON outputs on striatal and limbic network regions. In addition, experiments in aged rat models show decreased brain-wide activation following OB stimulation, particularly in the primary olfactory and limbic networks. Modeling analysis identifies a dysfunctional AON to Pir connection, indicating the impairment of this primary olfactory cortical circuit that disrupts the downstream long-range propagation. Our study for the first time delineates the spatiotemporal properties of olfactory neural activity propagation in brain-wide networks and uncovers the roles of primary olfactory cortical, AON and Pir, outputs in shaping neural interactions at the systems level.
Programmable Editing of Primary MicroRNA Switches Stem Cell Differentiation and Improves Tissue Regeneration
Authors: Truong Vu Anh , Chang Yu-Han , Tu Yi , Nguyen Thi Kieu Nuong , Pham Ngoc Nam , Chang Chin-Wei , Chang Yi-Hao , Ngo Thi Kim Dung , Pham Huu Dang , Tu Jui , Dang Thuc Quyen , Truong Anh Vy , Hu Yu-Chen 
Published: July 2024

AbstractProgrammable RNA editing is harnessed for modifying mRNA. Besides mRNA, miRNA also regulates numerous biological activities, but current RNA editors have yet to be exploited for miRNA manipulation. To engineer primary miRNA (pri-miRNA), the miRNA precursor, we present a customizable editor REPRESS (RNA Editing of Pri-miRNA for Efficient Suppression of miRNA) and characterize critical parameters. The optimized REPRESS is distinct from other mRNA editing tools in design rationale, hence enabling editing of pri-miRNAs that are not editable by other RNA editing systems. We edited various pri-miRNAs in different cells including adipose-derived stem cells (ASCs), hence attenuating mature miRNA levels without disturbing host gene expression. We further developed an improved REPRESS (iREPRESS) that enhances and prolongs pri-miR-21 editing for at least 10 days, with minimal perturbation of transcriptome and miRNAome. iREPRESS reprograms ASCs differentiation, promotes in vitro cartilage formation and augments calvarial bone regeneration in rats, thus implicating its potentials for engineering miRNA for many applications such as stem cell engineering and tissue regeneration.
The kinesin Kip2 promotes microtubule growth using a bipartite polymerase module to deliver tubulin to microtubule plus-ends
Authors: Nadalis Simos , Neyret Aymeric , Abrieu Ariane , Drechsler Hauke , Liakopoulos Dimitris , Portran Didier 
Published: July 2024

SUMMARYKinesin molecular motors are essential for fundamental cellular processes such as chromosome segregation or vesicular transport. To fulfil their function, some kinesins promote microtubule growth, but the molecular mechanism underlying this activity remains unclear. One of the motors with the strongest microtubule growth-promoting activity is Kip2, a kinesin that is required for astral microtubule integrity and spindle positioning in yeast. Here we show that the ability of Kip2 to polymerize microtubules is coupled to binding and transport of free tubulin. We report that the Kip2 N-terminus is required to promote microtubule elongationin vitroandin vivo. Kip2 binds free tubulin through this unstructured, basic domain and delivers it to microtubule plus-ends. In addition to the N-terminus, we find that ATP hydrolysis and motor activity is also required for microtubule polymerisation. Finally, transfer of the Kip2 N-terminus to kinesin-1, a kinesin that lacks polymerase activity, transforms kinesin-1 into a tubulin-transporting microtubule polymerase. We propose that motor-driven tubulin delivery to microtubule plus-ends is an efficient mechanism used by kinesins to promote microtubule polymerization.
Robust and Memoryless Median Estimation for Real-Time Spike Detection
Authors: Burman Ariel , Solé-Casals Jordi , Lew Sergio E. 
Published: July 2024

AbstractWe propose a novel moving median estimator specifically designed for online detection of threshold crossings in multi-channel signals, such as extracellular neural recordings. This estimator offers two key advantages: a reduced sensitivity to outliers and the elimination of memory requirements for storing arrival times. Furthermore, its design facilitates parallel implementation on FPGAs, making it ideal for real-time processing of multi-channel recordings.
Return of intracranial beta oscillations and traveling waves with recovery from traumatic brain injury
Authors: Vaz Alex , Wathen Connor , Miranda Stephen , Thomas Rachel , Darlington Timothy , Jabarkheel Rashad , Tomlinson Samuel , Arena John , Bond Kamila , Salwi Sanjana , Ajmera Sonia , Bachschmid-Romano Ludovica , Gugger James , Sandsmark Danielle , Diaz-Arrastia Ramon , Schuster James , Ramayya Ashwin G. , Cajigas Iahn , Pesaran Bijan , Chen H. Isaac , Petrov Dmitriy 
Published: July 2024

AbstractTraumatic brain injury (TBI) remains a pervasive clinical problem associated with significant morbidity and mortality. However, TBI remains clinically and biophysically ill-defined, and prognosis remains difficult even with the standardization of clinical guidelines and advent of multimodality monitoring. Here we leverage a unique data set from TBI patients implanted with either intracranial strip electrodes during craniotomy or quad-lumen intracranial bolts with depth electrodes as part of routine clinical practice. By extracting spectral profiles of this data, we found that the presence of narrow-band oscillatory activity in the beta band (12-30 Hz) closely corresponds with the neurological exam as quantified with the standard Glasgow Coma Scale (GCS). Further, beta oscillations were distributed over the cortical surface as traveling waves, and the evolution of these waves corresponded to recovery from coma, consistent with the putative role of waves in perception and cognitive activity. We consequently propose that beta oscillations and traveling waves are potential biomarkers of recovery from TBI. In a broader sense, our findings suggest that emergence from coma results from recovery of thalamo-cortical interactions that coordinate cortical beta rhythms.
Using deep learning predictions reveals a large number of register errors in PDB deposits
Authors: Rodríguez Filomeno Sánchez , Simpkin Adam J. , Chojnowski Grzegorz , Keegan Ronan M. , Rigden Daniel J. 
Published: July 2024

AbstractThe accuracy of the information in the Protein Data Bank (PDB) is of great importance for the myriad downstream applications that make use of protein structural information. Despite best efforts, the occasional introduction of errors is inevitable, especially where the experimental data are of limited resolution. We have previously established a novel protein structure validation approach based on spotting inconsistencies between the residue contacts and distances observed in a structural model and those computationally predicted by methods such as AlphaFold 2. It is particularly well-suited to the detection of register errors. Importantly, the new approach is orthogonal to traditional methods based on stereochemistry or map-model agreement, and is resolution-independent. Here we identify thousands of likely register errors by scanning 3-5Å resolution structures in the PDB. Unlike most methods, application of our approach yields suggested corrections to the register of affected regions which we show, even by limited implementation, lead to improved refinement statistics in the vast majority of cases. A few limitations and confounding factors such as fold-switching proteins are characterised, but we expect our approach to have broad application in spotting potential issues in current accessions and, through its implementation and distribution in CCP4, helping ensure the accuracy of future deposits.
A Burst-Dependent Algorithm for Neuromorphic On-Chip Learning of Spiking Neural Networks
Authors: Stuck Michael , Wang Xingyun , Naud Richard 
Published: July 2024

AbstractThe field of neuromorphic engineering addresses the high energy demands of neural networks through brain-inspired hardware for efficient neural network computing. For on-chip learning with spiking neural networks, neuromorphic hardware requires a local learning algorithm able to solve complex tasks. Approaches based on burst-dependent plasticity have been proposed to address this requirement, but their ability to learn complex tasks has remained unproven. Specifically, previous burst-dependent learning was demonstrated on a spiking version of the XOR problem using a network of thousands of neurons. Here, we extend burst-dependent learning, termed ‘Burstprop’, to address more complex tasks with hundreds of neurons. We evaluate Burstprop on a rate-encoded spiking version of the MNIST dataset, achieving low test classification errors, comparable to those obtained using backpropagation through time on the same architecture. Going further, we develop another burst-dependent algorithm based on the communication of two types of error-encoding events for the communication of positive and negative errors. We find that this new algorithm performs better on the image classification benchmark. We also tested our algorithms under various types of feedback connectivity, establishing that the capabilities of fixed random feedback connectivity is preserved in spiking neural networks. Lastly, we tested the robustness of the algorithm to weight discretization. Together, these results suggest that spiking Burstprop can scale to more complex learning tasks and can thus be considered for self-supervised algorithms while maintaining efficiency, potentially providing a viable method for learning with neuromorphic hardware.
Bone mineral density affects tumor growth by shaping microenvironmental heterogeneity
Authors: Whitman Matthew A. , Mantri Madhav , Spanos Emmanuel , Estroff Lara A. , De Vlaminck Iwijn , Fischbach Claudia 
Published: July 2024

ABSTRACTBreast cancer bone metastasis is the leading cause of mortality in patients with advanced breast cancer. Although decreased mineral density is a known risk factor for bone metastasis, the underlying mechanisms remain poorly understood because studying the isolated effect of bone mineral density on tumor heterogeneity is challenging with conventional approaches. Here, we investigate how bone mineral content affects tumor growth and microenvironmental complexityin vivoby combining single-cell RNA-sequencing with mineral-containing or mineral-free decellularized bone matrices. We discover that the absence of bone mineral significantly influences fibroblast and immune cell heterogeneity, promoting phenotypes that increase tumor growth and alter the response to injury or disease. Importantly, we observe that the stromal response to matrix mineral content depends on host immunocompetence and the murine tumor model used. Collectively, our findings suggest that bone mineral density affects tumor growth by altering microenvironmental complexity in an organism-dependent manner.