bluuebunny/crossref_metadata_2025_split huggingface dataset:
Novel function ofHox13in regulating outgrowth of the newt hindlimb bud through interaction withFgf10andTbx4
Authors: Tozawa Sayo , Matsubara Haruka , Minamitani Fumina , Kamei Yasuhiro , Saida Misako , Asao Momoko , Suzuki Ken-ichi T. , Matsunami Masatoshi , Shigenobu Shuji , Hayashi Toshinori , Abe Gembu , Takeuchi Takashi 
Published: November 2024

Abstract5’Hoxgenes regulate pattern formation along the axes of the limb. Previously, we showed thatHoxa13/Hoxd13double mutant newts lacked all digits of the forelimbs during development and regeneration, showing that newtHox13is necessary for digit formation in development and regeneration. In addition, we found another unique phenotype. A part of theHox13crispant newts showed hindlimb defects, in which whole or almost whole hindlimbs were lost, suggesting a novel function ofHox13in limb development. Using germline mutants, we showed that mutation inHox13led to hindlimb defects. The limb buds ofHox13crispants formed, however, did not show outgrowth. Expression ofFgf10andTbx4, which are involved in limb outgrowth, decreased in the hindlimb buds ofHox13crispants. In addition, hindlimb defects were observed in bothFgf10andTbx4crispant newts. Finally,Fgf10andTbx4interacted withHox13genetically. Our results revealed a novel function ofHox13in regulating the outgrowth of the newt hindlimb bud through interaction withFgf10andTbx4.
YORU: social behavior detection based on user-defined animal appearance using deep learning
Authors: Yamanouchi Hayato M , Takeuchi Ryosuke F , Chiba Naoya , Hashimoto Koichi , Shimizu Takashi , Tanaka Ryoya , Kamikouchi Azusa 
Published: November 2024

AbstractThe creation of tools using deep learning methodologies for animal behavior analysis has revolutionized neuroethology. They allow researchers to analyze animal behaviors and reveal causal relationships between specific neural circuits and behaviors. However, the application of such annotation/manipulation systems to social behaviors, in which multiple individuals interact dynamically, remains challenging. Here, we applied an object detection algorithm to classify animal social behaviors. Our system, packaged as “YORU” (Your Optimal Recognition Utility), classifies animal behaviors, including social behaviors, based on the shape of the animal as a “behavior object”. It successfully classified several types of social behaviors ranging from vertebrates to insects. We also integrated a closed-loop control system for operating optogenetic devices into the YORU package. YORU enables real-time delivery of photostimulation feedback to specific individuals during specific behaviors, even when multiple individuals are close together. We hope that the YORU system will accelerate the understanding of the neural basis of social behaviors.
Bidirectional Impact of miR-29a modulation on Memory Stability in the Adult Brain
Authors: Viglione Aurelia , Giannuzzi Chiara , Putignano Elena , Mazziotti Raffaele , Cellerino Alessandro , Pizzorusso Tommaso 
Published: November 2024

SummaryMicroRNAs are key regulators of brain gene expression, with miR-29a notably upregulated from development to adulthood and in aging, and showing links to cognitive decline. However, the extent to which miR-29 levels influence learning and memory processes, and its molecular mediators, remains to be determined. Here, we down- and up-regulated miR-29a levels in the dorsal hippocampus of adult mice to reveal miR-29 role in memory. Inhibiting miR-29a enhanced trace fear memory stability, increased Dnmt3a levels, and affected CpG methylation in gene regulation regions. In contrast, increasing miR-29a impaired memory performances and decreased Dnmt3a levels, suggesting a destabilization of memory processes. Proteomic and transcriptomic analysis demonstrated that miR-29a antagonism upregulated RNA-binding and synaptic proteins and downregulated inflammation and myelin associated proteins. These results underscore miR-29a’s pivotal role in memory persistence, plasticity, and cognitive aging, suggesting that miR-29a modulation could offer potential strategies for cognitive enhancement and age-related memory decline.
Transmission dynamics of COVID-19 in the outbreak among healthcare workers at a university hospital in Rio de Janeiro, Brazil
Authors: Braga José Ueleres , Rocco Suassuna José Hérmogennes , Semeão de Souza Ana Sara 
Published: November 2024

AbstractObjectiveThe objective of this study was to investigate an outbreak of COVID-19 among HCWs in the nephrology service of a university hospital in Rio de Janeiro in March 2020.MethodsThe study population consisted of a team of 59 HCWs, and surveys were conducted through digital interviews. Signs and symptoms, existence of comorbidities, hospitalization, and the network of contacts among the professionals during the period from March 1 to 23, 2020 were evaluated. The analysis consisted of: (i) describe epidemic curve, (ii) transmission chains, (iii) estimate the effective reproduction number (Rt), and (iv) identification of factors related to infectious cases.ResultsOf the 59 professionals in the nephrology service, 43 (73%) participated in the study. The first case occurred on March 1 and the last case occurred on March 23, 2020. The outbreak peaked on March 12–13. 31 participants were probable or confirmed cases COVID-19. These were mostly women (71%), with an average age of 37 years, and were predominantly doctors (45%). Only one participant was hospitalized. The risk factors for contracting COVID-19 were being a medical doctor, working at another hospital, and being female.ConclusionWe concluded that there was an outbreak of COVID-19 among health professionals in the nephrology service at HUPE from March 1 to 23, 2020. The transmission chain network had large clusters showing intense transmission.
Lipid flippases ATP9A and ATP9B form a complex and contribute to the secretory pathway from the Golgi apparatus
Authors: Yagi Tsukasa , Nakabuchi Riki , Muranaka Yumeka , Tanaka Gaku , Nakayama Kazuhisa , Takatsu Hiroyuki , Shin Hye-Won 
Published: November 2024

ABSTRACTType IV P-type ATPases (P4-ATPases) serve as lipid flippases, translocating membrane lipids from the exoplasmic (or luminal) leaflet to the cytoplasmic leaflet of lipid bilayers. In mammals, these P4-ATPases are localized to distinct subcellular compartments. ATP8A1 and ATP9A, both members of the P4-ATPase family, are involved in endosome-mediated membrane trafficking, although the roles of P4-ATPases in the secretory pathway remain to be clarified. ATP9A and ATP9B are located in thetrans-Golgi network, with ATP9A also present in endosomal compartments. This study unveiled the overlapping roles of ATP9A and ATP9B in transporting VSVG from the Golgi to the plasma membrane within the secretory pathway. Furthermore, we demonstrated that the flippase activities of ATP9A and ATP9B were crucial for transport process. Notably, we discovered the formation of homomeric and/or heteromeric complexes between ATP9A and ATP9B. The existence of the heteromeric complex notably contributed to the retention of ATP9A in the Golgi. Therefore, ATP9A and ATP9B play a role in the secretory pathway from the Golgi to the plasma membrane, forming either homomeric or heteromeric complexes.
Confirming the Impact of Climate Change on Biodiversity: Results from a Global Survey
Authors: Alshehab Eyab A. 
Published: November 2024

AbstractThe escalating impacts of climate change on global biodiversity constitute one of the most pressing environmental challenges of our time. This study employs a global survey to gather empirical evidence from a broad spectrum of biologists and ecologists, aiming to confirm the predicted impacts of climate change on biodiversity as theorized in foundational studies. Building upon the seminal work of Parmesan and Yohe (2003) and Root et al. (2003), who documented early evidence of biotic responses to climate change, our research seeks to validate these findings through contemporary observations from professionals actively engaged in the field.The survey, distributed to over 500 experts worldwide, focused on gathering data on observed shifts in species distributions, alterations in phenological events, and increased frequency of ecosystem disturbances. Our analysis employs advanced statistical techniques to correlate these observations with historical climate data, thereby examining the direct and indirect effects of climatic variations on biological diversity.Results from this study confirm significant correlations between climate change and various forms of biodiversity disruption, echoing the predictions of Walther et al. (2002) regarding the northward and upward shifts in species distributions. Furthermore, changes in the timing of reproductive events, as detailed by Visser and Both (2005), and increased disturbances such as wildfires and pest outbreaks, support the hypothesis of a climate-driven perturbation in natural systems.This paper not only substantiates earlier projections but also enhances our understanding of the intricate dynamics between climate change and biodiversity. It emphasizes the urgent need for comprehensive global conservation strategies, as echoed by Hughes et al. (2003), to mitigate these profound impacts. The findings serve as a critical update to the ongoing scientific dialogue, urging for immediate and coordinated policy action.
Biophysical network modeling of temporal and stereotyped sequence propagation of neural activity in the premotor nucleus HVC
Authors: Diab Zeina Bou , Chammas Marc , Daou Arij 
Published: November 2024

AbstractStereotyped neural sequences are often exhibited in the brain, yet the neurophysiological mechanisms underlying their generation are not fully understood. Birdsong is a prominent model to study such behavior particularly because juvenile songbirds progressively learn from their tutors and by adulthood are able to sing stereotyped song patterns. The songbird premotor nucleus HVC coordinate motor and auditory activity responsible for learned vocalizations. The HVC comprises three neural populations that has distinctin vitroandin vivoelectrophysiological responses. Typically, models that explain HVC’s network either rely on intrinsic HVC circuitry to propagate sequential activity, rely on extrinsic feedback to advance the sequence or rely on both. Here, we developed a physiologically realistic neural network model incorporating the three classes of HVC neurons based on the ion channels and the synaptic currents that had been pharmacologically identified. Our model is based on a feedforward chain of microcircuits that encode for the different sub-syllabic segments (SSSs) and that interact with each other through structured feedback inhibition. The network reproduced thein vivoactivity patterns of each class of HVC neurons, and unveiled key intrinsic and synaptic mechanisms that govern the sequential propagation of neural activity by highlighting important roles for the T-type Ca2+current, Ca2+-dependent K+current, A-type K+current, hyperpolarization activated inward current, as well as excitatory and inhibitory synaptic currents. The result is a biophysically realistic model that suggests an improved characterization of the HVC network responsible for song production in the songbird.
Gestation length drives brain size and litter size variation in eutherian mammals
Authors: Danis Thodoris , Lin Dana , Caetano Daniel S. , Funston Gregory F. , Rokas Antonis 
Published: November 2024

AbstractThe length of gestation in eutherian mammals, which is key to their reproductive success, is closely connected to other life history traits and with body mass and brain mass, but causal relationships between these variables are unclear. Here, we used an integrative analytical framework to evaluate the evolutionary relationships between gestation length and eight other traits on a dataset of 3,258 eutherian mammals and infer causality. We identify variation in generation length and litter size as the primary predictors of eutherian gestation length variation, whereas additional traits, such as brain mass, significantly predict gestation length only in specific mammalian orders. Using a structural equation modeling approach known as phylogenetic path analysis to infer causality, we find that gestation length variation positively influences brain mass variation and negatively influences litter size variation. Furthermore, body mass causally influences gestation length variation only in certain orders. Consistent with these causal inferences, examination of trait-trait coevolution reinforces that gestation length is strongly positively associated with brain mass, strongly negatively associated with litter size, and only moderately correlated with body mass. These findings reveal how gestation length directly and indirectly influences, and is influenced by, other key eutherian traits. Our study establishes a robust framework for identifying causal relationships within suites of correlated and co-evolving traits.
Lethal Plague Outbreaks in Lake Baikal Hunter–gatherers 5500 Years Ago
Authors: Macleod Ruairidh , Seersholm Frederik , de Sanctis Bianca , Lieverse Angela , Timpson Adrian , Stenderup Jesper T. , Gaunitz Charleen , Vinner Lasse , Schulting Rick , Goriunova Olga Ivanovna , Bazaliiskii Vladimir Ivanovich , Vasiliev Sergei V. , Jessup Erin , Wang Yucheng , Thomas Mark G. , Corbett-Detig Russell , Iversen Astrid K.N. , Weber Andrzej W. , Sikora Martin , Willerslev Eske 
Published: November 2024

AbstractThe rise of zoonotic diseases in prehistory is often associated with the Neolithic agricultural transition1,2. In particular, plague has been linked to population declines in Late Neolithic Europe3,4. Although plague is amongst the most devastating diseases in human history, early strains ofYersinia pestis,the causal agent of plague, lack virulence factors required for the bubonic form5, and their severity remains unclear. Here, we describe the oldest strains of plague reported so far, associated with two early phases of outbreaks among prehistoric hunter–gatherers in the Lake Baikal region in East Siberia, beginning from ∼5600–5400 years ago (cal. BP). These outbreaks occur across four hunter–gatherer cemeteries; the largest of these (Ust’-Ida I) has a 38.7% detection rate for plague infection (39% detection across all sites). By reconstructing kinship pedigrees, we show that small familial groups are affected, consistent with human-to-human spread of the disease, and the first outbreak occurred within a single generation. Intriguingly, the infections appear to have resulted in acute mortality events, especially among children. Zoonotic transmission is separately indicated by aBrucellainfection in one of the children. Interestingly, we see differences in functional genomic variants in the prehistoric plague strains, including in theypmsuperantigen known fromY. pseudotuberculosistoday. The new strains diverge ancestrally to all knownY. pestisdiversity and push back theY. pestisdivergence fromY. pseudotuberculosisby some 2000 years6. Our results show that plague outbreaks happen earlier than previously thought and that these early outbreaks were indeed lethal. The findings challenge the common notion that high population densities and lifestyle changes during the Neolithic transition were prerequisites for plague epidemics.
Computational Design of Metallohydrolases
Authors: Kim Donghyo , Woodbury Seth M. , Ahern Woody , Kalvet Indrek , Hanikel Nikita , Salike Saman , Pellock Samuel J. , Lauko Anna , Hilvert Donald , Baker David 
Published: November 2024

AbstractNew enzymes can be designed by starting from a description of an ideal active site composed of catalytic residues surrounding the reaction transition state(s) and identifying or generating a protein scaffold that supports the site1–7, but there are a few current limitations. First, the catalytic efficiencies achieved by such efforts have generally been quite low, and considerable optimization by directed evolution has been required to reach activities typical of native enzymes.8–10Second, generative AI methods such as RFdiffusion11,12now enable the direct generation of proteins around active sites, but to date, such scaffolding has required specification of both the position in the sequence and the backbone coordinates of the catalytic residue, which complicates sampling. Here we introduce a generative AI method called RFam that overcomes these limitations and use it to design zinc metallohydrolases starting from a density functional theory description of active site geometry. Of 96 designs tested experimentally, the most active has akcat/KMof 23,000 M-1s-1, orders of magnitude higher than previously designed metallohydrolases.6,7,13,14This 148 amino acid protein has a novel fold with an enclosed chamber which positions the reaction substrate nearly perfectly for attack by a catalytic water molecule activated by the bound metal and is predicted by ChemNet15to have a highly preorganized active site. The ability to generate high activity catalysts starting from quantum chemistry calculated active site geometries without experimental optimization should open the door to a new generation of potent designer enzymes.16,17
Decomposing Cognitive Processes in the mPFC During Self-Thinking
Authors: Levorsen Marie , Aoki Ryuta , Sedikides Constantine , Izuma Keise 
Published: November 2024

AbstractPast cognitive neuroscience research has demonstrated that thinking about both the self and other activate the medial prefrontal cortex (mPFC), a central hub of the default mode network. The mPFC is also implicated in other cognitive processes, such as introspection and autobiographical memory, rendering elusive its exact role during thinking about the self. Specifically, it is unclear whether the same cognitive process explains the common mPFC involvement or distinct processes are responsible for the mPFC activation overlap. In this preregistered functional magnetic resonance imaging study, we investigated whether and to what extent mPFC activation patterns during self-reference judgment could be explained by activation patterns during the tasks of other-reference judgment, introspection, and autobiographical memory. Multi-voxel pattern analysis showed that only in the mPFC were neural responses both concurrently different and similar across tasks. Furthermore, multiple regression and variance partitioning analyses indicated that each task (i.e., other-reference, introspection, memory) uniquely and jointly explained significant variance in mPFC activation during self-reference. These findings suggest that the self-reference task involves multiple cognitive processes shared with other tasks, and the mPFC is the unique place where necessary information is gathered and integrated for judgments based on internally constructed representations.
From naïve pluripotency to human neural organoids through a three-dimensional morphogenetic continuum
Authors: Laterza Cecilia , Cesare Elisa , Stuart Hannah T. , D’Ercole Martina , Gesualdo Alessia , La Barbera Maria Grazia , Brignani Sara , Ribecco Carmela , Polli Roberta , Frison Roberta , Angiolillo Silvia , Maset Andrea , Gagliano Onelia , Cacchiarelli Davide , Briscoe James , Tanaka Elly M. , Murgia Alessandra , Elvassore Nicola 
Published: November 2024

SummaryHuman central nervous system (CNS) development involves complex transitions from pluripotency to regionalised neural tissues. The early phases of this process are inaccessible in humans but can potentially be modelledin vitrousing brain organoids, including to study neurodevelopmental disorders. However, current methods are based on post-implantation-like human pluripotent stem cells (hPSCs), which exhibit a hypermethylated state and show epigenetic memory retention. Here we developed a 3D model of human CNS development, starting from naïve human induced PSCs (hiPSCs), which exhibit a hypomethylated pre-implantation-like state of pluripotency and develop into 3D neuroepithelial cysts in a timely morphogenetic continuum. Upon treatment with appropriate signalling cues, naïve-derived neuroepithelial cysts can be specified toward different axial identities. Extended culture of anterior-specified organoids results in forebrain-like structures containing both dorsal and ventral neural precursors as well as mature neurons, exhibiting appropriate cellular diversity and functional properties. We applied this system to model Fragile X Syndrome (FXS), an epigenetically regulated neurodevelopmental disorder. We found that FXS patient-derived naïve hiPSCs, initially demethylated at theFmr1locus, gradually underwent remethylation during organoid development. In addition,Fmr1silencing started much earlier than can be detected by pre-natal analysis, and is concomitant with the development of mosaicisms. Our approach provides a new platform for studying human CNS development, including early epigenetic events and regional patterning, demonstrating the potential of naïve hiPSC-derived organoids for modelling neurodevelopmental disorders with complex epigenetic regulation.Highlights- single naïve hiPSCs differentiate into 3D neuroepithelial cysts in a timely morphogenetic continuum- signalling cues at appropriate developmental transitions can direct naïve hiPSC- derived organoids to different regional identities of the human CNS- naïve hiPSC-derived forebrain organoids display cellular complexity representing both dorsal and ventral identities- forebrain organoids from Fragile X Syndrome patients recapitulate the genetic instability and epigenetic dysregulation ofFmr1locus.
Computational analysis of morphological changes inLactiplantibacillus plantarumunder acidic stress
Authors: Venugopal Athira , Steinberg Doron , Moyal Ora , Yonnasi Shira , Glaicher Noga , Gitelman Eliraz , Shemesh Moshe , Amitay Moshe 
Published: November 2024

AbstractCell shape and size often define characteristics of individual or communities of microorganisms in changing environments. Hence, characterizing cell morphology using computational image analysis can aid in the accurate identification of bacterial responses to these changes. Modifications in cell morphology ofLactiplantibacillus plantarumwere determined in response to acidic stress, specifically during growth stage of the cells at pH 3.5 compared to pH 6.5.Consequently, we developed a computational method to sort, detect, analyze, and measure bacterial size in a single-species culture. We applied a deep learning methodology composed of object detection followed by image classification to measure the bacterial cell dimensions of the pre-identified cells.The results of our computational analysis show a significant change in cell morphology in response to alteration of environmental pH. Specifically, we found that the cell was dramatically elongated at low pH, while the width was not altered. Those changes could be attributed to modifications in membrane properties, for instance increased cell membrane fluidity in acidic pH.Integration of deep learning with microbial microscopic imaging is an advanced methodology for studying cellular structures. These trained models and scripts can be applied to other microbes and cells and are publicly available at:https://github.com/OraMoyal26/bacteria_dimensions/tree/main