bluuebunny/crossref_metadata_2025_split huggingface dataset:
Haplotype-aware multiomics unveils the regulatory basis of haplodiplontic life-cycle differentiation in a cosmopolitan marine alga
Authors: Kao Tzu-Tong , Lai Ming-Wei , Wang Tzu-Haw , Yang Chia-Ling , Frada Miguel J. , Ku Chuan 
Published: May 2024

AbstractGephyrocapsa huxleyi(formerlyEmiliania huxleyi), a key coccolithophore alga influencing the global carbon cycle through photosynthesis and calcification, undergoes a haplodiplontic sexual life cycle with a calcifying non-flagellate diploid and a non-calcifying biflagellate haploid stage. To reveal the molecular basis of their morpho-physiological distinctions, we generated chromosome-level genome assemblies and compared the transcriptomes, proteomes, and methylomes for a pair of isogenic haploid and diploid model strains and conducted haplotype-aware analyses of their multiomic features. In addition to calcification and flagella, transcriptomes and proteomes of haploid and diploid cells modulate their differentiation in photosynthesis, sulfatases, DMSP degradation, DNA replication, and endomembrane system and transport. Haploid-diploid differential gene expression can be partially attributable to allelic imbalance (allele-specific expression) in diploid cells. Gene transcript abundance is positively associated with both CG and CHG gene-body DNA methylation, which can be inheritable, allele-specific, and differentiated between life-cycle phases. This multiomic study unravels the regulatory basis of unicellular algal life-cycle differentiation and provides valuable resources for investigating the ecologically important coccolithophore algae.
Deep Learning Models Can Predict Violence and Threats Against Healthcare Providers Using Clinical Notes
Authors: Dobbins Nicholas J , Chipkin Jacqueline , Byrne Tim , Ghabra Omar , Siar Julia , Sauder Mitchell , Huijon R Michael , Black Taylor M 
Published: May 2024

AbstractViolence, verbal abuse, threats, and sexual harassment of healthcare providers by patients is a major challenge for healthcare organizations around the world, contributing to staff turnover, distress, absenteeism, and reduced job satisfaction and overall mental and physical health. To enable interventions prior to possible violent episodes, we trained two deep learning models to predict violence against healthcare workers 3 days prior to violent events for case and control patients. The first model is a document classification model using clinical notes, and the second a baseline regression model using largely structured data. Our document classification model achieved an F1 score of 0.75 while our model using structured data achieved an F1 of 0.72, both exceeding predictive performance of a psychia-try team who reviewed the same documents (0.5 F1). To aid in explainability and understanding of risk factors for violent events, we additionally trained a named entity recognition classifier on annotations of the same corpus, which achieved an overall F1 of 0.7. This study demonstrates the first deep learning model capable of predicting violent events within healthcare settings using clinical notes, sur-passing the first published baseline of human experts. We anticipate our methods can be generalized and extended to enable intervention at other hospital systems.
Genetically Encoded FRET Biosensor for Live-cell Visualization of Lamin A Phosphorylation at Serine 22
Authors: Liu Jian , Li Qianqian , Wang Jinfeng , Qiu Juhui , Zhou Jing , Peng Qin 
Published: May 2024

AbstractExtensive phosphorylation at Serine 22 (pSer22) on lamin A is the hallmark of cell mitosis, which contributes to the breakdown of nuclear envelope. In the interphase, the pSer22 lamin A exists in low abundance and involves in mechanotransduction, virus infection and gene expression. Numerous evidence emerges to support lamin A regulation on cell function and fate by phosphorylation. However, live-cell imaging tools for visualizing the dynamics of pSer22 lamin A is yet to be established. Herein, we developed a novel lamin A phosphorylation sensor (LAPS) based on fluorescence resonance energy transfer (FRET) with high sensitivity and specificity. We observed the dynamic lamin A phosphorylation during cell cycle progression in single living cells: the increase of pSer22 modification when cells enter the mitosis and recovered upon the mitosis exit. Our biosensor also showed the gradual reduction of pSer22 modification during cell adhesion and in response to hypotonic environment. By applying LAPS, we captured the propagation of pSer22 modification from inside to outside of the inner nuclear membrane, which further led to the breakdown of nuclear envelope. Meanwhile, we found the synchronous phosphorylation of lamin A and H3S10 at mitosis entry. Inhibition of Aurora B, the responsible kinase for H3S10ph, could shorten the mitotic period without obvious effect on the pSer22 modification level of lamin A. Thus, LAPS allows the spatiotemporal visualization of lamin A phosphorylation at Serine 22 site, which will be useful for elucidating the molecular mechanisms underlying cell mitosis and mechanoresponsive processes.
The contribution of small protected areas to the big picture of forest conservation and restoration in Sweden
Authors: Svensson Johan , Lopez-Peinado Andres , Jonsson Bengt Gunnar , Singh Navinder J 
Published: May 2024

AbstractIn forest regions worldwide, industrial forestry has left fragments of natural forests behind. This challenges biodiversity conservation and calls for ecological restoration for sustainable forest management and conservation. The functionality of protected areas need to be improved and forest ecosystems set in a state that better favors biodiversity, resilience and provisioning of ecosystem services. Sweden contributes a substantial share of the European forests, with dominance of non-industrial forest ownership and extensive forestry footprint, and hence with immediate need for advanced conservation and restoration. Protection through voluntary nature conservation agreements and regulated biotope protection areas exists since the 1990s, with schemes involving economic compensation to landowners to facilitate conservation and restoration. Across entire Sweden and all ecoregions, we assessed their accumulated capacity over a 30-year period, including forest types protected, type of restoration management, rotation intervals, and selection of tree species. These nearly 14,000 different areas covering over 70,000ha are small, ranging in size from 5ha but rarely larger than 20ha. Their contribution is important, particularly in south Sweden with low and fragmented forest cover among many different owners. Active restoration dominates over passive set asides, coniferous forest types are less represented than more rare forest types, many different tree species are favored, and different restoration types occur but with few types dominating. In recognizing their critical importance, we find that the practices are narrow and repetitive, and that a greater restoration diversification is needed. The decreasing trend in protection is alarming since these contribute key forest type representativeness and functionality.
Plant genotype-specific modulation ofClonostachys rosea-mediated biocontrol of septoria tritici blotch disease on wheat
Authors: Chaudhary Sidhant , Zakieh Mustafa , Dubey Mukesh , Jensen Dan Funck , Grenville-Briggs Laura , Chawade Aakash , Karlsson Magnus 
Published: May 2024

AbstractBackgroundBeneficial microorganisms can act as biological control agents (BCAs) by directly targeting pathogens or indirectly by enhancing the plant’s defense mechanisms against pathogens. However, efficiencies with which plants benefit from BCAs vary, potentially because of genetic variation in plants for plant-BCA compatibility. The aim of this study was to explore the genetic variation in winter wheat for modulation ofClonostachys rosea-mediated biocontrol of septoria tritici blotch disease caused by the fungal pathogenZymoseptoria tritici.ResultsIn total, 202 winter wheat genotypes, including landraces and old cultivars grown from 1900 onwards in the Scandinavian countries, were tested under greenhouse-controlled conditions. Foliar spray applications of the pathogen and the fungal BCA in two treatments, i.e.,Z. tritici(Zt) alone andZ. triticialong withC. rosea(ZtCr) were used to assess the disease progress over time. The absence and presence ofC. roseain Zt and ZtCr, respectively, allowed the dissection of variation for plant disease resistance and biocontrol efficacy. The study showed significant phenotypic variation among plant genotypes for disease progression in both Zt and ZtCr treatments. Moreover, disease progress for individual plant genotypes differed significantly between the two treatments, indicating a plant genotype-dependent variation in biocontrol efficacy. For the phenotypic variation in disease progress and biocontrol efficacy, a genome-wide association study using a 20K single-nucleotide polymorphism (SNP) marker array was also performed. In total, five distinct SNP markers associated with disease resistance and four SNP markers associated withC. roseabiocontrol efficacy were identified.ConclusionsThis work serves as a foundation to further characterize the genetic basis of plant-BCA interactions, facilitating opportunities for concurrent breeding for disease resistance and biocontrol efficacy.
Impact of rotavirus vaccination in Malawi from 2012 to 2022 compared to model predictions before, during, and after the COVID-19 pandemic
Authors: Pitzer Virginia E. , Ndeketa Latif , Asare Ernest O. , Hungerford Daniel , Jere Khuzwayo C. , Cunliffe Nigel A. 
Published: May 2024

AbstractBackgroundRotarix® rotavirus vaccine was introduced into the Malawi national immunization program in October 2012. We used a previously developed mathematical models to estimate overall vaccine effectiveness over a 10-year period following rotavirus vaccine introduction.MethodsWe analyzed data on children <5 years old hospitalized with acute gastroenteritis in Blantyre, Malawi from January 2012 to June 2022, compared to pre-vaccination data. We estimated vaccine coverage before, during, and after the COVID-19 pandemic using data from rotavirus-negative children. We compared model predictions for the weekly number of rotavirus-associated gastroenteritis (RVGE) cases to the observed number by age to validate model predictions and estimate overall vaccine effectiveness.ResultsThe number of RVGE and rotavirus-negative acute gastroenteritis cases declined substantially following vaccine introduction. Vaccine coverage among rotavirus-negative controls was >90% with two doses by July 2014, and declined to a low of ∼80% in October 2020, before returning to pre-pandemic levels by July 2021. Our models captured the post-vaccination trends in RVGE incidence, with 5.4% to 19.4% of observed weekly RVGE cases falling outside of the 95% prediction intervals. Comparing observed RVGE cases to the model-predicted incidence without vaccination, overall vaccine effectiveness was estimated to be 36.0% (95% prediction interval: 33.6%, 39.9%) peaking in 2014 and was highest in infants (52.5%; 95% prediction interval: 50.1%, 54.9%).ConclusionsOverall effectiveness of rotavirus vaccination in Malawi is modest despite high vaccine coverage and has plateaued since 2016. Our mathematical models provide a validated platform for assessing strategies to improve rotavirus vaccine impact.
Ultra-Rapid Droplet Digital PCR Enables Intraoperative Tumor Quantification
Authors: Murphy Zachary R. , Bianchini Emilia C. , Smith Andrew , Körner Lisa I. , Russell Teresa , Reinecke David , Wang Yuxiu , Snuderl Matija , Orringer Daniel A. , Evrony Gilad D. 
Published: May 2024

AbstractThe diagnosis and treatment of tumors often depends on molecular-genetic data. However, rapid and iterative access to molecular data is not currently feasible during surgery, complicating intraoperative diagnosis and precluding measurement of tumor cell burdens at surgical margins to guide resections. To address this gap, we developed Ultra-Rapid droplet digital PCR (UR-ddPCR), which can be completed in 15 minutes from tissue to result with an accuracy comparable to standard ddPCR. We demonstrate UR-ddPCR assays for the IDH1 R132H and BRAF V600E clonal mutations that are present in many low-grade gliomas and melanomas, respectively. We illustrate the clinical feasibility of UR-ddPCR by performing it intraoperatively for 13 glioma cases. We further combine UR-ddPCR measurements with UR-stimulated Raman histology intraoperatively to estimate tumor cell densities in addition to tumor cell percentages. We anticipate that UR-ddPCR, along with future refinements in assay instrumentation, will enable novel point-of-care diagnostics and the development of molecularly-guided surgeries that improve clinical outcomes.
Artificial Intelligence in Periodontology: Performance Evaluation of ChatGPT, Claude, and Gemini on the In-service Examination
Authors: Ahmad Bushra , Saleh Khaled , Alharbi Saleh , Alqaderi Hend , Jeong Y. Natalie 
Published: May 2024

ABSTRACTBackgroundArtificial intelligence (AI) language models have shown potential as educational tools in healthcare, but their accuracy and reliability in periodontology education require further evaluation. In this study we aimed to assess and compare the performance of three prominent AI language models—ChatGPT-4o, Claude 3 Opus, and Gemini Advanced—with second-year periodontics residents across the United States on the American Academy of Periodontology 2024 in-service examination.MethodsWe conducted a cross-sectional study using 331 multiple-choice questions from the 2024 periodontology in-service examination. We evaluated and compared the performances of ChatGPT-4o, Claude 3 Opus, and Gemini Advanced across various question domains. The results of second-year periodontics residents served as a benchmark.ResultsChatGPT-4o, Gemini Advanced, and Claude 3 Opus significantly outperformed second-year periodontics residents across the United States, with accuracy rates of 92.7 percent, 81.6 percent, and 78.5 percent, respectively, compared to the residents’ 61.9 percent. The differences in performance among the AI models were statistically significant (p< 0.001). Percentile rankings underscored the superior performance of the AI models, with ChatGPT-4o, Gemini Advanced, and Claude 3 Opus placing in the 99.95th, 98th, and 95th percentiles, respectively.ConclusionChatGPT-4o displayed superior performance compared to Claude 3 Opus and Gemini Advanced. The results highlight the potential of AI large language models (LLMs) as educational tools in periodontology and emphasize the need for ongoing evaluation and validation as these technologies evolve. Researchers should explore both the integration of AI language models into periodontal education and their impact on learning outcomes and clinical decision-making.
Genetic ablation of GABABreceptors from oligodendrocyte precursor cells protects against demyelination in the mouse spinal cord
Authors: Gobbo D , Rieder P , Fang LP , Buttigieg E , Schablowski M , Damo E , Bosche N , Dallorto E , May P , Bai X , Kirchhoff F , Scheller A 
Published: May 2024

AbstractGABAergic signaling and GABABreceptors play crucial roles in regulating the physiology of oligodendrocyte-lineage cells, including their proliferation, differentiation, and myelination. Therefore, they are promising targets for studying how spinal oligodendrocyte precursor cells (OPCs) respond to injuries and neurodegenerative diseases like multiple sclerosis. Taking advantage of the temporally controlled and cell-specific genetic removal of GABABreceptors from OPCs, our investigation addresses their specific influence on OPC behavior in the gray and white matter of the mouse spinal cord. Our results show that while GABABreceptors do not significantly alter OPC cell proliferation and differentiation under physiological conditions, they distinctly regulate the Ca2+signaling of OPCs. In addition, we investigate the impact of OPC-GABABreceptors in two models of toxic demyelination, namely the cuprizone and the lysolecithin models. The genetic removal of OPC-GABABreceptors protects against demyelination and oligodendrocyte loss. Additionally, we observe enhanced resilience to cuprizone-induced pathological alterations in OPC Ca2+signaling. Our results provide valuable insights into the potential therapeutic implications of manipulating GABABreceptors in spinal cord OPCs and deepen our understanding of the interplay between GABAergic signaling and spinal cord OPCs, providing a basis for future research.
Light and substrate composition control root exudation rates at the initial stages of soilless lettuce cultivation
Authors: de Haas Brechtje R. , Oburger Eva , Van Labeke Marie-Christine , Dhooghe Emmy , Geelen Danny 
Published: May 2024

ABSTRACTPlant root exudation is an inherent metabolic process that enhances various functions of the root system like the mobilization of nutrients and interactions with surrounding microbial communities. The role and extent of root exudation in soilless crop production is poorly investigated. Here, we analyzed soilless lettuce and show that the root exudation rate declines with plant age. Furthermore, the impact of light quality and substrate was assessed by growing soilless lettuce in 100% red light (660 nm), 100% blue light (450 nm), and white light (full-light spectrum) and in 100% perlite, 100% potting soil, or mixtures of both materials. Root exudates were collected at 10, 17 and 24 days after transplanting. The total carbon root exudation rate was influenced by light conditions and substrate composition at the earliest timepoint of the culture but not at later growth stages. The total carbohydrate exudation rate was significantly higher under pure blue and red light compared to white light. The impact of light depended on the presence of perlite in the substrate. The total phenolic compound exudation rate was most strongly influenced by the substrate composition and reached the highest level in either pure potting soil or pure perlite. These findings underscore the importance of root exudation during the initial stages of development. Light and growing media influence the exudation rate at this early stage, suggesting that exudation is an adaptive process of the soilless lettuce culture.HIGHLIGHTAt an initial stage of development, soilless lettuce exudation rates are high and modulated by light and substrate composition, whereas older plants show lower rates that are not influenced by these environmental conditions.
Reduced temporal and spatial stability of neural activity patterns predict cognitive control deficits in children with ADHD
Authors: Gao Zhiyao , Duberg Katherine , Warren Stacie L , Zheng Li , Hinshaw Stephen P. , Menon Vinod , Cai Weidong 
Published: May 2024

AbstractThis study explores the neural underpinnings of cognitive control deficits in ADHD, focusing on overlooked aspects of trial-level variability of neural coding. We employed a novel computational approach to neural decoding on a single-trial basis alongside a cued stop-signal task which allowed us to distinctly probe both proactive and reactive cognitive control. Typically developing (TD) children exhibited stable neural response patterns for efficient proactive and reactive dual control mechanisms. However, neural coding was compromised in children with ADHD. Children with ADHD showed increased temporal variability and diminished spatial stability in neural responses in salience and frontal-parietal network regions, indicating disrupted neural coding during both proactive and reactive control. Moreover, this variability correlated with fluctuating task performance and with more severe symptoms of ADHD. These findings underscore the significance of modeling single-trial variability and representational similarity in understanding distinct components of cognitive control in ADHD, highlighting new perspectives on neurocognitive dysfunction in psychiatric disorders.
The diversity ofSNCAtranscripts in neurons, and its impact on antisense oligonucleotide therapeutics
Authors: Evans James R. , Gustavsson Emil K. , Doykov Ivan , Murphy David , Virdi Gurvir S. , Lachica Joanne , Röntgen Alexander , Murtada Mhd Hussein , Pang Chun Wei , Macpherson Hannah , Wernick Anna I. , Toomey Christina E. , Athauda Dilan , Choi Minee L. , Hardy John , Wood Nicholas W. , Vendruscolo Michele , Mills Kevin , Heywood Wendy , Ryten Mina , Gandhi Sonia 
Published: May 2024

SummaryThe role of theSNCAgene locus in driving Parkinson’s disease (PD) through rare and common genetic variation is well-recognized, but the transcriptional diversity ofSNCAin vulnerable cell types remains unclear. We performedSNCAlong-read RNA sequencing in human dopaminergic neurons and show that annotatedSNCAtranscripts account for only 5% of expression. Rather, the majority of expression (75%) at theSNCAlocus originates from transcripts with alternative 5’ and 3’ untranslated regions. Importantly, 10% originates from transcripts encoding open reading frames not previously annotated, which are translated and detectable in human postmortem brain. Defining the 3’ untranslated regions enabled the rational design of antisense oligonucleotides targeting the majority ofSNCAtranscripts, leading to the effective reversal of PD pathology, including protein aggregation, mitochondrial dysfunction, and toxicity. Resolving the complexity of theSNCAtranscriptional landscape impacts RNA therapies and highlights differences in protein isoforms and their contribution to disease.
Self-Supervised Grid Cells Without Path Integration
Authors: Pettersen Markus , Schøyen Vemund Sigmundson , Østby Mattis Dalsætra , Malthe-Sørenssen Anders , Lepperød Mikkel Elle 
Published: May 2024

AbstractGrid cells, found in the medial Entorhinal Cortex, are known for their regular spatial firing patterns. These cells have been proposed as the neural solution to a range of computational tasks, from performing path integration, to serving as a metric for space. Their exact function, however, remains fiercely debated. In this work, we explore the consequences of demanding distance preservation over small spatial scales in networks subject to a capacity constraint. We consider two distinct self-supervised models, a feedforward network that learns to solve a purely spatial encoding task, and a recurrent network that solves the same problem during path integration. We find that this task leads to the emergence of highly grid cell-like representations in both networks. However, the recurrent network also features units with band-like representations. We subsequently prune velocity inputs to subsets of recurrent units, and find that their grid score is negatively correlated with path integration contribution. Thus, grid cells emerge without path integration in the feedforward network, and they appear substantially less important than band cells for path integration in the recurrent network. Our work provides a minimal model for learning grid-like spatial representations, and questions the role of grid cells as neural path integrators. Instead, it seems that distance preservation and high population capacity is a more likely candidate task for learning grid cells in artificial neural networks.