bluuebunny/crossref_metadata_2025_split huggingface dataset:
Api-TRACE: A System for Honey Bee Tracking in a Constrained Environment to Study Bee Learning Process and the Effect of Lithium on Learning
Authors: Erdem Babur , Ince Ayben , Sevin Sedat , Arslan Okan Can , Gozen Ayse Gul , Giray Tugrul , Alemdar Hande 
Published: September 2024

AbstractLearning is an adaptive behavior that improves the performance of bees in foraging, dance communication, predator avoidance, and other tasks. Any deficiencies in learning could be detrimental to the long-term survival of the bee colony. Passive avoidance task is a fundamental procedure for investigating learning. We introduce Api-TRACE, a computer vision-aided system to analyze the avoidance assays. Api-TRACE tracks individual bees from the video footage of the assay and detects the moments when they were exposed to a stimulus. The algorithm provides stimulus exposure duration and learning profiles of each individual bee, enabling fast and detailed analysis of the results. Electric shock avoidance assay is one of the most common experimental methods to assess learning. We designed an apparatus for the electric shock avoidance experiments using within-reach hardware and 3D-printed components. We used Api-TRACE and experimental apparatus to investigate the effect of lithium on bee learning success in passive avoidance and reversal learning paradigms through an electric shock avoidance assay. Lithium is a potential chemical for combatingVarroa, a bee (Apis) parasite, and a well-known medication for treating bipolar disorder. It has been known that lithium alters learning in humans and other animals. Before the experiment, we treated the bees with a sucrose solution with 0, 5, 25, and 125 mM LiClad libitum. Our results indicated that a decrement in learning performance emerged with increasing lithium doses in the reversal phase but not in the acquisition of the electric shock avoidance assay.
Dual transposon sequencing (Dual Tn-seq) to probe genome-wide genetic interactions
Authors: Zik Justin J. , Price Morgan N. , Arkin Adam P. , Deutschbauer Adam M. , Sham Lok-To 
Published: September 2024

ABSTRACTUnderstanding gene function on a genome-wide scale is a fundamental goal in biology. With the advent of next-generation sequencing, high-throughput methods such as transposon sequencing (Tn- seq) were developed to measure fitness of single deletion mutants en masse. Nevertheless, gene redundancy complicates these approaches, as inactivating genes individually may not produce discernable phenotypes. Here, we report Dual Tn-seq, a technique for simultaneously assaying fitness of a comprehensive pool of double mutants. Dual Tn-seq couples random barcode transposon-site sequencing (RB Tn-seq) with the Cre-loxsystem, allowing us to determine the fitness of ≈68% of all possible double mutant combinations in the human pathogenStreptococcus pneumoniae. Genetic interactions identified from ≈1.4 billion double mutants uncovered new avenues in widely conserved biochemical pathways, exemplified by the discovery of a new CTP synthase and a regulator of peptidoglycan biosynthesis. Since Dual Tn-seq has very few requirements, it can be readily adapted to diverse organisms.
Which perceptual categories do observers experience during multistable perception?
Authors: Skerswetat Jan , Bex Peter J. 
Published: September 2024

AbstractMultistable perceptual phenomena provide insights into the mind’s dynamic states within a stable external environment and the neural underpinnings of these consciousness changes are often studied with binocular rivalry. Conventional methods to study binocular rivalry suffer from biases and assumptions that limit their ability to describe the continuous nature of this perceptual transitions and to discover what kind of percept was perceived across time. In this study, we propose a novel way to avoid those shortcomings by combining a continuous psychophysical method that estimates introspection during binocular rivalry with machine learning clustering and transition probability analysis. This combination of techniques reveals individual variability and complexity of perceptual experience in 28 normally sighted participants. Also, the analysis of transition probabilities between perceptual categories, i.e., exclusive and different kinds of mixed percepts, suggest that interocular perceptual competition, triggered by low-level stimuli, involves conflict between monocular and binocular neural processing sites rather than mutual inhibition of monocular sites.Layman abstractWhen our brain receives ambiguous information about the world, it changes its interpretation between different alternatives and thereby provides insight into how the mind works. Scientists often use a technique called binocular rivalry, where each eye sees a different image, to provoke an ambiguous visual world that is perceived as ongoing competition among interpretations of the two eyes inputs. Traditional methods for studying binocular rivalry struggle to describe the continuous nature of this fluctuation and to estimate the range of different perceived experiences. We have created a new approach in which participants reproduce their ongoing perceptual experiences combined machine learning analyses of these states. We found that individuals visual experience is more varied and complex than previously thought. Our results suggest that when our eyes see conflicting images, the brain’s effort to make sense of what is seen involves syntheses among both monocular and binocular brain areas, not just competition between monocular areas.
Unsupervised Neural Network-Based Image Stitching Method for Bladder Endoscopy
Authors: Ye Zixing , Shao Chenyu , Zhu Kelei 
Published: September 2024

AbstractBladder endoscopy enables the observation of intravesical lesion characteristics, making it an essential tool in urology. Image stitching techniques are commonly employed to expand the field of view of bladder endoscopy. Traditional image stitching methods rely on feature matching. In recent years, deep-learning techniques have garnered significant attention in the field of computer vision. However, the commonly employed supervised learning approaches often require a substantial amount of labeled data, which can be challenging to acquire, especially in the context of medical data. Both feature-based and unreliable supervised methods for cystoscopy image stitching are limited by their quality and the robustness of image stitching. This study proposes an unsupervised neural network-based image stitching method for bladder endoscopy that comprises two modules: an unsupervised alignment network and an unsupervised fusion network. In the unsupervised alignment network, we employed feature convolution, regression networks, and linear transformations to align images. In the unsupervised fusion network, we achieved image fusion from features to pixel by simultaneously eliminating artifacts and enhancing the resolution. Experiments demonstrated our method’s consistent stitching success rate of 98.11% and robust image stitching accuracy at various resolutions. Our method eliminates sutures and flocculent debris from cystoscopy images, presenting good image smoothness while preserving rich textural features. Moreover, our method could successfully stitch challenging scenes such as dim and blurry scenes. Our application of unsupervised deep learning methods in the field of cystoscopy image stitching was successfully validated, laying the foundation for real-time panoramic stitching of bladder endoscopic video images. This advancement provides opportunities for the future development of computer-vision-assisted diagnostic systems for bladder cavities.
Bacterial cell size modulation along the growth curve across nutrient conditions
Authors: Nieto César , Igler Claudia , Singh Abhyudai 
Published: September 2024

AbstractUnder stable growth conditions, bacteria maintain cell size homeostasis through coordinated elongation and division. However, fluctuations in nutrient availability result in dynamic regulation of the target cell size. Using microscopy imaging and mathematical modelling, we examine how bacterial cell volume changes over the growth curve in response to nutrient conditions. We find that two rod-shaped bacteria,Escherichia coliandSalmonella enterica, exhibit similar cell volume distributions in stationary phase cultures irrespective of growth media. Cell resuspension in rich media results in a transient peak with a five-fold increase in cell volume ≈ 2h after resuspension. This maximum cell volume, which depends on nutrient composition, subsequently decreases to the stationary phase cell size. Continuous nutrient supply sustains the maximum volume. In poor nutrient conditions, cell volume shows minimal changes over the growth curve, but a markedly decreased cell width compared to other conditions. The observed cell volume dynamics translate into non-monotonic dynamics in the ratio between biomass (optical density) and cell number (colony-forming units), highlighting their non-linear relationship. Our findings support a heuristic model comparing modulation of cell division relative to growth across nutrient conditions and providing novel insight into the mechanisms of cell size control under dynamic environmental conditions.
Adipocyte metabolic state regulates glial phagocytic function
Authors: Alassaf Mroj , Rajan Akhila 
Published: September 2024

SummaryObesity and type 2 diabetes are well-established risk factors for neurodegenerative disorders1–4, yet the underlying mechanisms remain poorly understood. The adipocyte-brain axis is crucial for brain function, as adipocytes secrete signaling molecules, including lipids and adipokines, that impinge on neural circuits to regulate feeding and energy expenditure5. Disruptions in the adipocyte-brain axis are associated with neurodegenerative conditions6, but the causal links are not fully understood. Neural debris accumulates with age and injury, and glial phagocytic function is crucial for clearing this debris and maintaining a healthy brain microenvironment7–9. Using adultDrosophila,we investigate how adipocyte metabolism influences glial phagocytic activity in the brain. We demonstrate that a prolonged obesogenic diet increases adipocyte fatty acid oxidation and ketogenesis. Genetic manipulations that mimic obesogenic diet-induced changes in adipocyte lipid and mitochondrial metabolism unexpectedly reduce the expression of the phagocytic receptor Draper inDrosophilamicroglia-like cells in the brain. We identifyApolpp—theDrosophilaequivalent of human apolipoprotein B (ApoB)—as a critical adipocyte-derived signal that regulates glial phagocytosis. Additionally, we show that Lipoprotein Receptor 1 (LpR1), the LDL receptor on phagocytic glia, is required for glial capacity to clear injury-induced neuronal debris. Our findings establish that adipocyte-brain lipoprotein signaling regulates glial phagocytic function, revealing a novel pathway that links adipocyte metabolic disorders with neurodegeneration.HighlightsProlonged exposure to an obesogenic diet result in a starvation-like metabolic response in adipose tissue.Obesogenic diet-induced mitochondrial lipid catabolism in adipose tissue impacts glial phagocytic function.Adipocyte ApoB is a novel regulator of glial phagocytic function.LpR1, on ensheathing glia, is required for glial response to axonal injury.Graphical abstract
MedGraphNet: Leveraging Multi-Relational Graph Neural Networks and Text Knowledge for Biomedical Predictions
Authors: Macaulay Oladimeji , Servilla Michael , Arredondo David , Virupakshappa Kushal , Hu Yue , Tafoya Luis , Zhang Yanfu , Sahu Avinash 
Published: September 2024

AbstractGenetic, molecular, and environmental factors influence diseases through complex interactions with genes, phenotypes, and drugs. Current methods often fail to integrate diverse multi-relational biological data meaningfully, limiting the discovery of novel risk genes and drugs. To address this, we presentMedGraphNet, a multi-relational Graph Neural Network (GNN) model designed to infer relationships among drugs, genes, diseases, and phenotypes.MedGraphNetinitializes nodes using informative embeddings from existing text knowledge, allowing for robust integration of various data types and improved generalizability. Our results demonstrate thatMedGraphNetmatches and often outperforms traditional single-relation approaches, particularly in scenarios with isolated or sparsely connected nodes. The model shows generalizability to external datasets, achieving high accuracy in identifying disease-gene associations and drug-phenotype relationships. Notably,MedGraphNetaccurately inferred drug side effects without direct training on such data. Using Alzheimer’s disease as a case study,MedGraphNetsuccessfully identified relevant phenotypes, genes, and drugs, corroborated by existing literature. These findings demonstrate the potential of integrating multi-relational data with text knowledge to enhance biomedical predictions and drug repurposing for diseases.MedGraphNetcode is available athttps://github.com/vinash85/MedGraphNet
The evolution and functional significance of the programmed ribosomal frameshift inprfB
Authors: Prince Cassidy R. , Lin Isabella N. , Feaga Heather A. 
Published: September 2024

AbstractRelease Factor 2 (RF2) is one of two peptide release factors that terminate translation in bacteria. InEscherichia coli, the gene encoding RF2,prfB, contains an in-frame premature RF2-specific stop codon. Therefore, a programmed ribosomal frameshift is required to translate full-length RF2. Here, we investigate the diversity ofprfBframeshifting through bioinformatic analyses of >12,000 genomes. We present evidence thatprfBframeshifting autoregulates RF2 levels throughout the bacterial domain since (i) theprfBin-frame stop codon is always TGA or TAA, both of which are recognized by RF2, and never the RF1-specific TAG stop codon, and (ii) species that lack the autoregulatory programmed frameshift likely need higher RF2 levels since, on average, they have significantly higher RF2-specific stop codon usage. Overexpression ofprfBwithout the autoregulatory frameshift motif is toxic toBacillus subtilis, an organism with intermediate RF2-specific stop codon usage. We did not detect the programmed frameshift in any Actinobacteriota. Consistent with this finding, we observed very low frameshift efficiency at theprfBframeshift motif in the ActinobacteriumMycobacterium smegmatis. Our work provides a more complete picture of the evolution of the RF2 programmed frameshifting motif, and its usage to prevent toxic overexpression of RF2.
Dynamic BMP signaling regulates sclerotome induction and lineage diversification in zebrafish
Authors: Xie Linjun , Ma Roger C. , Kocha Katrinka M. , Méndez-Olivos Emilio E. , Huang Peng 
Published: September 2024

ABSTRACTThe sclerotome is an embryonic structure that gives rise to various supportive tissues, including the axial skeleton and connective tissues. Despite its significance, the mechanisms underlying sclerotome induction and diversification during embryonic development remain poorly understood. Sclerotome progenitors exhibit transientbmp4expression and an active response to BMP signaling. Using BMP gain- and loss-of-function tools, we demonstrate that BMP signaling is both necessary and sufficient for sclerotome induction. Furthermore, through mosaic expression of a dominant-negative tool, we show that BMP signaling induces sclerotome fate in a cell-autonomous manner. Interestingly, different populations of sclerotome-derived cells have distinct BMP signaling requirements. Sclerotome-derived notochord-associated cells in the trunk lack BMP response, and sustained BMP signaling inhibits their differentiation into tenocytes. By contrast, sclerotome-derived fin mesenchymal cells in the fin fold require high levels of BMP signaling for proper morphogenesis. Our findings suggest that dynamic regulation of BMP signaling is crucial for the induction of the sclerotome and the subsequent diversification of sclerotome-derived lineages in zebrafish.
From Homogeneity to Heterogeneity: Refining Stochastic Simulations of Gene Regulation
Authors: Chae Seok Joo , Shin Seolah , Lee Seunggyu , Kim Jae Kyoung 
Published: September 2024

AbstractCellular processes are intricately controlled through gene regulation, which is significantly influenced by intrinsic noise due to the small number of molecules involved. The Gillespie algorithm, a widely used stochastic simulation method, is pervasively employed to model these systems. However, this algorithm typically assumes that DNA is homogeneously distributed through- out the nucleus, which is not realistic. In this study, we evaluated whether stochastic simulations based on the assumption of spatial homogeneity can accurately capture the dynamics of gene regulation. Our findings indicate that when transcription factors diffuse slowly, these simulations fail to accurately capture gene expression, highlighting the necessity to account for spatial heterogeneity. However, incorporating spatial heterogeneity considerably increases computational time. To address this, we explored various stochastic quasi-steady-state approximations (QSSAs) that simplify the model and reduce simulation time. While both the stochastic total quasi-steady state approximation (stQSSA) and the stochastic low-state quasi-steady-state approximation (slQSSA) reduced simulation time, only the slQSSA provided an accurate model reduction. Our study underscores the importance of utilizing appropriate methods for efficient and accurate stochastic simulations of gene regulatory dynamics, especially when incorporating spatial heterogeneity.
Hebbian induction adds AMPA-labile signaling units to CA3-CA1 synapses in the developing hippocampus
Authors: Abrahamsson Therése , Gustafsson Bengt , Hanse Eric 
Published: September 2024

AbstractIn the 2ndpostnatal week hippocampus, Hebbian-induced long-term potentiation (LTP) of AMPA receptor-mediated transmission in CA3-CA1 synapses is not a genuine potentiation. Instead, it is a de-depression (unsilencing) and temporary stabilization of postsynaptically AMPA-labile synapses silenced by a prior test pulse (0.03 - 0.2 Hz) stimulation. In addition to such an LTP, Hebbian induction at these synapses also results in a labile potentiation that becomes depotentiated by test pulse stimulation, thus appearing as an Hebbian-induced short- term potentiation (STP). Although the induction of this labile potentiation was blocked in the combined presence of N-methyl-D-aspartate (NMDA) and metabotropic glutamate (mGlu) receptor antagonists, the depotentiation was not affected by these drugs. The labile potentiation was not associated with a change in paired-pulse ratio and was, after a depotentiation, fully re-established by a 20 min interruption of test pulse stimulation. These properties are shared with the silencing of previously non-stimulated (naïve) AMPA-labile synapses by such test pulse stimulation. However, the depotentiation following an Hebbian induction is not a re-silencing of naïve AMPA labile synapses since there is no correlation between the magnitudes of depotentiation and preceding silencing of naïve synapses. The present results suggest that Hebbian induction at these neonatal CA3-CA1 synapses, in addition to unsilencing and temporary stabilization of AMPA-labile transmission, creates a labile potentiation based on the insertion/activation of an additional AMPA-labile signaling unit to a pre-existing synapse.
Quantitative in toto live imaging analysis of apical nuclear migration in the mouse telencephalic neuroepithelium
Authors: Shimamura Tsukasa , Miyata Takaki 
Published: September 2024

AbstractIn the embryonic neuroepithelium (NE), neural progenitor cells undergo cell cycle-dependent interkinetic nuclear migration (IKNM) along the apicobasal axis. Extensive IKNM supports increasing cell production rates per unit apical surface, as typically observed in the mammalian telencephalic NE. Apical nucleokinesis during the G2 phase is an essential premitotic event, but its occurrence has not yet been quantitatively analyzed at a large 3D scale with sufficient spatiotemporal resolution. Here, we comprehensively analyzed apically migrating nuclei/somata in reference to their surroundings from embryonic day (E)11 to E13 in the mouse telencephalon. The velocity of apical nucleokinesis decreased, with more frequent nuclear pausing occurring at E12 and E13, whereas the nuclear density in the middle NE zone (20-40 μm deep) increased. This result, together with the results of Shh-mediated overproliferation experiments in which the nuclear density was increased in vivo at E11, suggests that apical nucleokinesis is physically influenced by the surrounding nuclei. Mean square displacement analysis for nuclei being passed by the apically migrating nuclei via horizontal sectioning in toto-recorded movies revealed that the “tissue fluidity” or physical permissiveness of the NE to apical nucleokinesis gradually decreased (E11 > E12 > E13). To further investigate the spatial relationship between preexisting mitoses and subsequent premitotic apical nucleokinesis, the horizontal distribution of mitoses was cumulatively (∼3 hours) analyzed under in toto monitoring. The four-dimensional cumulative apical mitoses presented a “random”, not “clustered” or “regular”, distribution pattern throughout the period examined. These methodologies provide a basis for future comparative studies of interspecies differences.
High
Q
and high gradient performance of the first medium-temperature baking 1.3 GHz cryomodule
Authors: Pan Weimin , Zhai Jiyuan , He Feisi , Ge Rui , Mi Zhenghui , Sha Peng , Jin Song , Han Ruixiong , Wang Qunyao , Lin Haiying , Wang Guangwei , Dai Xuwen , Zhang Zhanjun , Li Mei , Sang Minjing , Sun Liangrui , Ye Rui , Zhao Tongxian , Li Shaopeng , Zhu Keyu , Liu Baiqi , Wang Xiaolong , Yang Xiangchen , Bian Xiaojuan , Zhang Xiangzhen , Ma Huizhou , Zhao Jianbing , Zhang Liang , Zhao Hui , Guo Runbing , Mu Zhihui , Yang Conglai , Zheng Xiaobing , Dong Chao , Zheng Hongjuan , Chang Zhengze , Yang Xiaochen , Huang Tongming , Ma Qiang , Wang Zihan , Liu Ming , Zhou Wenzhong , Chen Senyu 
Published: September 2024

The world’s first 1.3 GHz cryomodule containing eight 9-cell superconducting radio-frequency (rf) cavities treated by medium-temperature furnace baking (mid-T bake) was developed at the Institute of High Energy Physics, Chinese Academy of Sciences. The 9-cell cavities in the cryomodule achieved an unprecedented high average intrinsic quality factor (Q0) of 3.8×1010 at 16  MV/m and 3.6×1010 at 21  MV/m in the horizontal test. The cryomodule can operate stably up to a total continuous wave rf voltage greater than 193 MV, with an average cavity usable accelerating gradient of more than 23  MV/m. The results significantly exceed the specifications of Circular Electron Positron Collider and Dalian advanced light source and the other high repetition rate free electron laser facilities [Linac Coherent Light Source II (LCLS-II), LCLS-II-high energy, Shanghai High Repetition Rate X-ray FEL and Extreme Light Facility, Shenzhen Superconducting Soft X-Ray Free Electron Laser, etc.]. There is evidence that the mid-T bake cavity may not require fast cooldown or long processing time in the cryomodule. This paper reviews the cryomodule performance and discusses some important issues in cryomodule assembly and testing.

Published by the American Physical Society
2024