bluuebunny/crossref_metadata_2025_split huggingface dataset:
Histone deacetylases regulate organ-specific growth in a horned beetle
Authors: Hu Yonggang , Crabtree Jordan R. , Macagno Anna L. M. , Moczek Armin P. 
Published: December 2023

ABSTRACTBackgroundNutrient availability is among the most widespread means by which environmental variability affects developmental outcomes. Because almost all cells within an individual organism share the same genome, structure-specific growth responses must result from changes in gene regulation. Earlier work suggested thathistone deacetylases(HDACs) may serve as epigenetic regulators linking nutritional conditions to trait-specific development. Here we expand on this work by assessing the function of diverseHDACsin the structure-specific growth of both sex-shared and sex-specific traits including evolutionarily novel structures in the horned dung beetleOnthophagus taurus.ResultsWe identified fiveHDACmembers whose down-regulation yielded highly variable mortality depending on whichHDACmember was targeted. We then show thatHDAC1,3, and4operate in both a gene- and trait-specific manner in the regulation of nutrition-responsiveness of appendage size and shape. Specifically,HDAC 1, 3,or4knockdown diminished wing size similarly while leg development was differentially affected by RNAi targetingHDAC3andHDAC4. In addition, depletion ofHDAC3transcript resulted in a more rounded shape of genitalia at the pupal stage and decreased the length of adult aedeagus across all body sizes. Most importantly, we find thatHDAC3and4pattern the morphology and regulate the scaling of evolutionarily novel head and thoracic horns as a function of nutritional variation.ConclusionCollectively, our results suggest that both functional overlap and division of labor amongHDACmembers contribute to morphological diversification of both conventional and recently evolved appendages. More generally, our work raises the possibility thatHDAC-mediated scaling relationships and their evolution may underpin morphological diversification within and across insect species broadly.
Do nocturnal pollinators carry a more conspecific pollen load than diurnal ones?
Authors: Razanajatovo Mialy , Schurr Frank M. , Muhthassim Nadia , Troesch Sandra , Knop Eva 
Published: December 2023

AbstractPlant-pollinator interactions are key for the reproduction of wild plants and for food security. However, the role nocturnal pollinators play in wild plant communities is not yet clear. Specifically, it has rarely been studied whether nocturnal pollinators are comparable to diurnal ones in the pollination services they deliver in plant communities. We tested whether nocturnal pollinators have the potential to provide higher pollination services than diurnal ones by carrying a more conspecific pollen load. We compared pollen loads carried by nocturnal and diurnal pollinators captured over 24-hour cycles in co-flowering plant communities in European ruderal meadows. Pollen load was less diverse at night, and the proportion of conspecific pollen carried by nocturnal pollinators was similar to or higher than that of diurnal ones. Thus, nocturnal pollinators do not only carry pollen but can remove and deposit conspecific pollen with a comparable or even superior performance to diurnal ones. Therefore, nocturnal pollinators can be more efficient pollination vectors than diurnal ones, which might compensate their lower pollen load.
Exploring Discrete Space-Time Models for Information Transfer: Analogies from Mycelial Networks to the Cosmic Web
Authors: Wood Tommy , Sorakivi Tuomas , Ayres Phil , Adamatzky Andrew 
Published: December 2023

AbstractFungal mycelium networks are large scale biological networks along which nutrients, metabolites flow. Recently, we discovered a rich spectrum of electrical activity in mycelium networks, including action-potential spikes and trains of spikes. Reasoning by analogy with animals and plants, where travelling patterns of electrical activity perform integrative and communicative mechanisms, we speculated that waves of electrical activity transfer information in mycelium networks. Using a new discrete space-time model with emergent radial spanning-tree topology, hypothetically comparable mycelial morphology and physically comparable information transfer, we provide physical arguments for the use of such a model, and by considering growing mycelium network by analogy with growing network of matter in the cosmic web, we develop mathematical models and theoretical concepts to characterise the parameters of the information transfer.
Deciphering the Biosynthetic Potential of Microbial Genomes Using a BGC Language Processing Neural Network Model
Authors: Lai Qilong , Yao Shuai , Zha Yuguo , Zhang Haobo , Ye Ying , Zhang Yonghui , Bai Hong , Ning Kang 
Published: December 2023

AbstractMicrobial secondary metabolites are usually synthesized by colocalized genes termed biosynthetic gene clusters (BGCs). A large portion of BGCs remain undiscovered in microbial genomes and metagenomes, representing a pressing challenge in unlocking the full potential of natural product diversity. In this work, we propose BGC-Prophet, a language model based on the transformer encoder that captures the distant location-dependent relationships among biosynthetic genes, allows accurately and efficiently identifies known BGCs and extrapolates novel BGCs among the microbial universe. BGC-Prophet is the first ultrahigh-throughput (UHT) method that is several orders of magnitude faster than existing tools such as DeepBGC, enabling pan-phylogenetic screening and whole-metagenome screening of BGCs. By analyzing 85,203 genomes and 9,428 metagenomes, new insights have been obtained about the diversity of BGCs on genomes from the majority of bacterial and archaeal lineages. The profound enrichment of BGCs in microbes after important geological events have been revealed: Both the Great Oxidation and Cambrian Explosion events led to a surge in BGC diversity and abundance, particularly in polyketides. These findings suggest that it is a general but constantly evolving approach for microbes to produce secondary metabolites for their adaptation in the changing environment. Taken together, BGC-Prophet enables accurate and fast detection of BGCs on a large scale, holds great promise for expanding BGC knowledge, and sheds light on the evolutionary patterns of BGCs for possible applications in synthetic biology.HighlightsBGC-Prophet shows superior performance to existing tools in terms of accuracy and speed.BGC-Prophet is the first ultrahigh-throughput (UHT) method that enables pan-phylogenetic screening and whole-metagenome screening of BGCs.BGC-Prophet builds the comprehensive profile of BGCs on 85,203 genomes and 9,428 metagenomes from the majority of bacterial and archaeal lineages.BGC-Prophet reveals the profound enrichment pattern of BGCs after important geological events.
Learning spatio-temporal V1 cells from diverse LGN inputs
Authors: Ruslim Marko A. , Burkitt Anthony N. , Lian Yanbo 
Published: December 2023

AbstractSince the Nobel-winning discovery of simple cells and complex cells in cat’s primary visual cortex (V1) by Hubel and Wiesel, many experimental studies of the visual system of the brain have been conducted. Experimental data of V1 cells from animal recordings show spatio-temporal properties, namely that they display both spatial and temporal response properties. For spatial properties, each V1 cell responds to a specific feature (such as bars, blobs, etc.) in the visual space, which is called the receptive field of this cell. The receptive fields of different V1 cells are typically different in size, orientation, spatial frequencies, etc. Furthermore, V1 cells also display temporal properties, namely that the receptive fields of V1 cells can change over time, and there is a great variety of ways in which they change over time. For example, the population of V1 cells show a great diversity from monophasic response to biphasic response, and some V1 cells are selective to a preferred direction. However, given many computational learning models that explain how spatial properties of V1 cells can be learnt, how temporal properties emerge is still not well understood. In this paper, we use a simple learning model based on sparse coding to show that spatio-temporal V1 cells, such as biphasic and direction selective cell, can emerge via synaptic plasticity when diverse spatio-temporal LGN cells are used as upstream input to V1 cells. This work suggests that temporal along with spatial properties of V1 cells may simply come from a learning process that aims to encode upstream input with spatio-temporal properties, which greatly enhances our understanding of V1 cells.
Maternofetal transfer of human NMDAR antibodies leads to cortical network defect in the adult
Authors: Altahini Saleh , Doering Jan , Kuchling Joseph , Backhaus Hendrik , Kreye Jakob , Guimaraes-Backhaus Roberta , Finke Carsten , Prüss Harald , Stroh Albrecht 
Published: December 2023

AbstractIgG antibodies that bind to the N-methyl-D-aspartate receptors (NMDAR-Ab) can be detected in up to 1 % of healthy individuals. This suggests that a considerable subgroup of pregnant women is at risk of transferring NMDAR-antibodies to the fetus. We ask whether a transientin uteroexposure to human NMDAR-Ab can lead to neural network defects in adulthood. In mouse model of maternofetally transferred human NMDAR-Ab, at P51, corresponding to early adulthood in humans, we conducted two-photon calcium imaging in awake behaving mice. We found that microcircuits in NMDAR-Ab exposed mice exhibited a lower spontaneous activity and increased bursty firing. Upon visual stimulation, neurons in NMDAR-Ab exposed mice had a higher orientation selectivity. In NMDAR-Ab exposed mice, a large fraction of neurons active upon visual stimulation did not fire spontaneously, andvice versa. This dissociation is in sharp contrast to the operational principles in healthy networks, in which the majority of all neurons were co-active. These findings suggest that transientin uteroexposure to NMDAR-Ab shifts cortical microcircuits to a maladaptive state persisting into adulthood, characterized by a dissociation between spontaneous and visually evoked activity. Such dissociation has long been hypothesized to play a role in the development of psychosis.
Imprecise perception of hand position during early motor adaptation
Authors: Will Matthias , Stenner Max-Philipp 
Published: December 2023

ABSTRACTLocalizing one’s body parts is important for movement control and motor learning. Recent studies have shown that the precision with which people localize their hand places constraints on motor adaptation. While these studies have assumed that hand localization remains equally precise across learning, we show that precision decreases rapidly during early motor learning. In three experiments, healthy young participants (n=92) repeatedly adapted to a 45° visuomotor rotation for a cycle of two to four reaches, followed by a cycle of two to four reaches with veridical feedback. Participants either used an aiming strategy that fully compensated for the rotation (experiment 1), or always aimed directly at the target, so that adaptation was implicit (experiment 2). We omitted visual feedback for the last reach of each cycle, after which participants localized their unseen hand. We observed an increase in the variability of angular localization errors when subjects used a strategy to counter the visuomotor rotation (experiment 1). This decrease in precision was less pronounced in the absence of re-aiming (experiment 2), and when subjects knew that they would have to localize their hand on the upcoming trial, and could thus fully allocate attention to hand position (experiment 3). We propose that attention to vision during strategic re-aiming decreases the precision of perceived hand position. We discuss how these dynamics in precision during early motor learning could impact on motor control, and shape the interplay between implicit and strategy-based motor adaptation.NEW & NOTEWORTHYRecent studies indicate that the precision with which people localize their hand limits implicit visuomotor learning. We found that localization precision is not static, but decreases early during learning. This decrease is pronounced when people apply a re-aiming strategy to compensate for a visuomotor perturbation, and diminishes when the hand is fully attended. We propose that these attention-dependent dynamics in position sense during learning may influence how implicit and strategy-based motor adaption interact.
Time-of-day effects of cancer drugs revealed by high-throughput deep phenotyping
Authors: Ector Carolin , Schmal Christoph , Didier Jeff , De Landtsheer Sébastien , Finger Anna-Marie , Müller-Marquardt Francesca , Schulte Johannes , Sauter Thomas , Keilholz Ulrich , Herzel Hanspeter , Kramer Achim , Granada Adrián E. 
Published: December 2023

AbstractThe circadian clock, a fundamental biological regulator, governs essential cellular processes in health and disease. Circadian-based therapeutic strategies are increasingly gaining recognition as promising avenues. Aligning drug administration with the circadian rhythm can enhance treatment efficacy and minimize side effects. Yet, uncovering the optimal treatment timings remains challenging, limiting their widespread adoption. In this work, we introduce a novel high-throughput approach integrating live-imaging and data analysis techniques to deep-phenotype cancer cell models, evaluating their circadian rhythms, growth, and drug responses. We devised a streamlined process for profiling drug sensitivities across different times of the day, identifying optimal treatment windows and responsive cell types and drug combinations. Finally, we implement multiple computational tools to uncover cellular and genetic factors shaping time-of-day drug sensitivity. Our versatile approach is adaptable to various biological models, facilitating its broad application and relevance. Ultimately, this research leverages circadian rhythms to optimize anti-cancer drug treatments, promising improved outcomes and transformative treatment strategies.
CIA: a Cluster Independent Annotation method to investigate cell identities in scRNA-seq data
Authors: Ferrari Ivan , Battistella Mattia , Vincenti Francesca , Gobbini Andrea , Marini Federico , Notarbartolo Samuele , Costanza Jole , Biffo Stefano , Grifantini Renata , Abrignani Sergio , Galeota Eugenia 
Published: December 2023

AbstractSingle-cell RNA sequencing (scRNA-seq) has revolutionized our understanding of the transcriptional landscape of complex tissues, enabling the discovery of novel cell types and biological functions. However, the identification and classification of cells from scRNA-seq datasets remain significant challenges. To address this, we developed a new computational tool called CIA (Cluster Independent Annotation), which accurately identifies cell types across different datasets without requiring a fully annotated reference dataset or complex machine learning processes. Based on predefined cell type signatures, CIA provides a highly user-friendly and practical solution to functional annotation of single cells. Our results demonstrate that CIA outperforms other state-of-the-art approaches, while also having significantly lower computational running time. Overall, CIA simplifies the process of obtaining reproducible signature-based cell assignments that can be easily interpreted through graphical summaries providing researchers with a powerful tool to explore the complex transcriptional landscape of single cells.The CIA framework is implemented in both the Python and R programming languages, making it applicable to all main single-cell analysis frameworks, and it is available under the MIT license with its documentation at the following links:Python package:https://pypi.org/project/cia-python/Python tutorial:https://cia-python.readthedocs.io/en/latest/tutorial/Cluster_Independent_Annotation.htmlR package and tutorial:https://github.com/ingmbioinfo/CIA_R
Cortical responses to looming sources are explained away by the auditory periphery
Authors: Benghanem Sarah , Guha Rudradeep , Pruvost-Robieux Estelle , Lévi-Strauss Julie , Joucla Coralie , Cariou Alain , Gavaret Martine , Aucouturier Jean-Julien 
Published: December 2023

AbstractA wealth of behavioral evidence indicate that sounds with increasing intensity (i.e. appear to be looming towards the listener) are processed with increased attentional and physiological resources compared to receding sounds. However, the neurophysiological mechanism responsible for such cognitive amplification remains elusive. Here, we show that the large differences seen between cortical responses to looming and receding sounds are in fact almost entirely explained away by nonlinear encoding at the level of the auditory periphery. We collected EEG mismatch negativity (MMN) data in response to deviant stimuli with both dynamic (looming and receding) and constant level (flat) differences to the standard in the same participants. We then combined a computational model of the auditory periphery with generative EEG methods (temporal response functions, TRFs) to model the single-participant MMN responses to flat deviants, and used them to predict the effect of the same mechanism on looming and receding stimuli. The flat model explained a remarkable 45% variance of the looming response, and 33% of the receding response. This provide striking evidence that MMN responses to looming and receding sounds result from the same cortical mechanism that generate MMN to constant-level deviants: all such differences are the sole consequence of their particular physical morphology getting amplified and integrated by peripheral auditory mechanisms. Thus, not all effects seen cortically proceed from top-down modulations by high-level decision variables, but can rather be performed early and efficiently by feed-forward peripheral mechanisms that evolved precisely to sparing subsequent networks with the necessity to implement such mechanisms.
Engagement for Alcohol Escalates in the 5-Choice Serial Reaction Time Task After Intermittent Access
Authors: Starski Phillip , Siegle Addyson , Hopf Frederic 
Published: December 2023

ABSTRACTUncontrollable binge drinking is becoming an increasingly prevalent issue in our society. This is a factor that plays a role in the development of alcohol use disorder (AUD). AUD impacts 15 million Americans annually, with approximately 88,000 dying from alcohol related deaths. There are several aspects of AUD that encourage a strong dependence on alcohol. Impulsivity, motivation, and attention are the primary behavioral facets we contribute to AUD. Many past studies have used the 5-Choice Serial Reaction Time Task (5-Choice) to analyze these types of behaviors using sugar as the reward. We have recently published a study where alcohol was used as a reward in the 5-Choice. 48 mice were trained to respond for alcohol in the 5-Choice, and the analyses for these animals were originally categorized by their alcohol preference and consumption. Upon looking at the data, we became more interested in a new way to classify these mice into groups. High engaged (HE) and low engaged (LE) mice were classified based on their number of correct responses in the last five late-stage sessions. During early-stage training, mice began to separate themselves into two groups based on their interaction with the task. The high-engaged (HE) mice were much more engaged with the task by having a high number of trials and correct responses, as well as a much lower percentage of omissions. The low engaged (LE) mice were not as engaged, this was apparent because of their lower number of trials and correct responses. They also had a much higher percentage of omissions in comparison to HE mice. LE mice presented no significant changes in late-stage training, while HE mice began responding and engaging more. These mice went through a period of intermittent access (IA), where they were allowed to drink alcohol in their cage for 3 weeks. After intermittent access, LE mice increased their responding which suggests an increase in motivation for alcohol as a reward. Engagement analysis presents two clearly different groups, one being motivated to work for alcohol and the other not wanting to work for this reward. These two distinct phenotypes in the 5-Choice could be used to model alcohol motivated behavior, which could help us further understand AUD.
Tradeoff Between Speed and Robustness in Primordium Initiation Mediated by Auxin-CUC1 Interaction
Authors: Kong Shuyao , Zhu Mingyuan , Pan David , Lane Brendan , Smith Richard S. , Roeder Adrienne H. K. 
Published: December 2023

ABSTRACTRobustness is the reproducible development of a phenotype despite stochastic noise. It often involves tradeoffs with other performance metrics, but the mechanisms underlying such tradeoffs were largely unknown. AnArabidopsisflower robustly develops four sepals from four precisely positioned auxin maxima. Thedevelopment related myb-like 1(drmy1)mutant generates noise in auxin signaling that disrupts robustness in sepal initiation. Here, we found that increased expression ofCUP-SHAPED COTYLEDON1(CUC1), a boundary specification transcription factor, indrmy1underlies this loss of robustness. CUC1 surrounds and amplifies stochastic auxin noise indrmy1to form variably positioned auxin maxima and sepal primordia. RemovingCUC1fromdrmy1provides time for noisy auxin signaling to resolve into four precisely positioned auxin maxima, restoring robust sepal initiation. However, removing CUC1 decreases auxin maxima intensity and slows down sepal initiation. Thus, CUC1 increases morphogenesis speed but impairs robustness against auxin noise. Further, using a computational model, we found that the observed phenotype can be explained by the effect of CUC1 in repolarizing PIN FORMED1 (PIN1), a polar auxin transporter. Lastly, our model predicts that reducing global growth rate improves developmental robustness, which we validated experimentally. Thus, our study illustrates a tradeoff between speed and robustness during development.
Protected areas enhance avian food webs
Authors: Thompson Lucie , Galiana Núria , Wells Konstans , Lurgi Miguel 
Published: December 2023

AbstractRestoring and conserving habitat and the species they shelter has become a primary focus to mitigate the current extinction crisis. Setting aside land designated as protected areas (PAs) is an efficient way of achieving these aims. This strategy has been proven to enhance different aspects of species richness and abundance across ecosystems1–4. However, to truly understand the effects of global environmental change on biodiversity, and the efficiency of our mitigation measures, we must account for one of its fundamental dimensions: species interactions. Here we show that PAs enhance avian food webs across Europe by protecting key network and species traits. Using 376,556 observational records of 509 bird species from citizen science databases distributed across 45 networks of PAs, we found beneficial effects of protection on 10 out of 13 food web properties on an average of 25.9% of sites. PAs enhance food webs by harbouring large top predators, in turn increasing the length of biomass flow paths from basal to top species. Furthermore, we link these beneficial effects to environmental drivers and PA designations. PA benefits were augmented by specific protection goals such as European Directives for conservation. This study provides evidence for the effectiveness of PAs as a strategy to preserve fundamental aspects of biodiversity beyond species richness. We anticipate our study to be a starting point for the development of comprehensive frameworks to assess the critical role of PAs in safeguarding biodiversity worldwide. Improving the mapping of species occurrences and ecological interactions across the globe will is fundamental to develop optimal strategies for establishing networks of PAs aimed at protecting all aspects of ecosystem diversity.