bluuebunny/crossref_metadata_2025_split huggingface dataset:
Identification of PTGR2 inhibitors as a new therapy for diabetes and obesity
Authors: Chang Yi-Cheng , Hsieh Meng-Lun , Lee Hsiao-Lin , Hee Siow-Wey , Chang Chi-Fon , Yen Hsin-Yung , Chen Yi-An , Chen Yet-Ran , Chou Ya-Wen , Li Fu-An , Ke Yi-Yu , Chen Shih-Yi , Hung Ming-Shiu , Hung Alfur Fu-Hsin , Huang Jing-Yong , Chiu Chu-Hsuan , Lin Shih-Yao , Shih Sheue-Fang , Hsu Chih-Neng , Hwang Juey-Jen , Yeh Teng-Kuang , Rachel Cheng Ting-Jen , Liao Karen Chia-Wen , Laio Daniel , Lin Shu-Wha , Chen Tzu-Yu , Hu Chun-Mei , Vogel Ulla , Saar Daniel , Kragelund Birthe B. , Tsou Lun Kelvin , Tseng Yu-Hua , Chuang Lee-Ming 
Published: December 2024

AbstractPeroxisome proliferator-activated receptor γ (PPARγ) is a master transcriptional regulator of systemic insulin sensitivity and energy balance. The anti-diabetic drug thiazolidinediones (TZDs) are potent synthetic PPARγ ligands with undesirable side effects, including obesity, fluid retention, and osteoporosis. 15-keto prostaglandin E2 (15-keto-PGE2) is an endogenous PPARγ ligand metabolized by prostaglandin reductase 2 (PTGR2). Here, we confirmed that 15-keto-PGE2 binds and activates PPARγ via covalent binding. In patients with type 2 diabetes and obese mice, serum 15-keto-PGE2 levels were decreased. Administration of 15-keto-PGE2 improves glucose homeostasis and prevented diet-induced obesity in mice. Either genetic inhibition of PTGR2 or PTGR2 inhibitor BPRPT0245 protected mice from diet-induced obesity, insulin resistance, and hepatic steatosis without fluid retention and osteoporosis. In conclusion, inhibition of PTGR2 is a new therapeutic approach to treat diabetes and obesity through increasing endogenous PPARγ ligands without side effects of synthetic PPARγ ligands TZDs.
Transmissibility of a newPlasmodium falciparum3D7 bank for use in malaria volunteer infection studies evaluating transmission blocking interventions
Authors: Lynch Sean A. , Abd-Rahman Azrin N. , Peters Jenny M. , Heunis Juanita M. , Gower Jeremy , Potter Adam J. , Webster Rebecca , Jennings Helen , Mathison Susan , Sahai Nischal , Amante Fiona H. , Barber Bridget E. 
Published: December 2024

ABSTRACTTransmission blocking activity is an important characteristic of antimalarial drugs, and can be evaluated in malaria volunteer infection studies (VIS). We undertook a pilot VIS to evaluate the suitability of a recently manufacturedP. falciparum3D7 bank (3D7-MBE-008) for evaluating transmission blocking interventions. Four adults were inoculated withP. falciparum3D7-MBE-008 infected erythrocytes and administered piperaquine on days 8 and 10 to clear asexual parasitemia while allowing gametocyte development. On day 25, participants were randomised (1:1) to receive either 0.25 mg/kg primaquine (primaquine group) or no intervention (control group). Transmissibility was assessed by enriched membrane feeding assays on days 25, 29, 32, and 39, with transmission intensity (proportion of mosquitoes infected) determined by 18S qPCR. All participants were infective on day 25, with a median 94% (range, 12%–100%) of mosquitoes positive for oocysts, and 76% (range, 8%–94%) positive for sporozoites. In the primaquine group, mosquito infectivity decreased substantially between days 25 and 29. In the control group, mosquito infectivity remained high up to day 32, and persisted to day 39 in one participant. TheP. falciparum3D7-MBE-008 parasite bank induced blood-stage infections that were highly transmissible to mosquitoes and is therefore suitable for evaluating transmission blocking interventions.Trial registrationanzctr.org.au (registration number: ACTRN12622001097730), registered 08/08/2022.
Cluefish: mining the dark matter of transcriptional data series with over-representation analysis enhanced by aggregated biological prior knowledge
Authors: Franklin Ellis , Billoir Elise , Veber Philippe , Ohanessian Jérémie , Delignette-Muller Marie Laure , Prud’homme Sophie Martine 
Published: December 2024

ABSTRACTInterpreting transcriptomic data presents significant challenges, particularly in non-targeted approaches. While modern functional enrichment methods are well-suited for experimental designs involving two conditions, they are less applicable to data series. In this context, we developed Cluefish, a free and open-source, semi-automated R workflow designed for untargeted, comprehensive biological interpretation of transcriptomic data series. Cluefish applies over-representation analysis on pre-clustered protein-protein interaction networks, using clusters as anchors to identify smaller, more specific biological functions. Innovative features, including cluster merging and recovery of isolated genes through shared biological contexts, enable a more complete exploration of the data. In our case study with zebrafish embryos exposed to a dose-gradient of dibutyl phthalate, Cluefish—combined with DRomics, a tool for dose-response analysis—identified gene clusters deregulated at low doses and linked to biological functions overlooked by the standard approach. Notably, it revealed that retinoid signalling disruption may be the most sensitive pathway affected by dibutyl phthalate during zebrafish development, potentially leading to morphological changes. The Cluefish workflow aims to provide valuable clues for biological hypothesis generation and experimental validation. It is freely available athttps://github.com/ellfran-7/cluefish.GRAPHICAL ABSTRACTA graphical abstract will be provided at revision.
The impact of human agents on spatial navigation and knowledge acquisition in a Virtual Environment
Authors: Sánchez-Pacheco T. , Sarría-Mosquera M. , Gärtner K. , Schmidt V. , Nolte D. , König S.U. , Pipa G. , König P. 
Published: December 2024

ABSTRACTConcepts of spatial navigation rest on the idea of landmarks, which are immobile features or objects in the environment. However, behaviorally relevant objects or fellow humans are often mobile. This raises the question of how the presence of human agents influences spatial exploration and knowledge acquisition. Here, we investigate exploration and performance in subsequent spatial tasks within a virtual environment containing numerous human avatars. In the exploration phase, agents had a locally limited effect on navigation. They prompted participants to revisit locations with agents during their initial exploration without significantly altering overall exploration patterns or the extent of the area covered. However, agents and buildings competed for visual attention. When spatial recall was tested, pointing accuracy toward buildings improved when participants directed their attention to the buildings and nearby agents. In contrast, pointing accuracy for agents showed weaker performance and did not benefit from visual attention directed toward the adjacent building. Active agents and incongruent agent-environment pairings further enhanced pointing accuracy, revealing that violations of expectations by agents can significantly shape navigational knowledge acquisition. Overall, agents influenced spatial exploration by directing attention locally, with the interaction between agent salience and environmental features playing a key role in shaping navigational knowledge acquisition.
Cleavage of the TrkB-FL Receptor During Epileptogenesis: Insights from a Kainic Acid-Induced Model of Epilepsy and Human Samples
Authors: Ribeiro-Rodrigues Leonor , Fonseca-Gomes João , Paulo Sara L. , Viais Ricardo , Ribeiro Filipa F. , Miranda-Lourenço Catarina , Mouro Francisco M. , Belo Rita F. , Ferreira Catarina B. , Tanqueiro Sara R. , Ferreira-Manso Mafalda , Umemori Juzoh , Castrén Eero , Paiva Vítor H. , Sebastião Ana M. , Aronica Eleonora , Rainha Campos Alexandre , Bentes Carla , Xapelli Sara , Diógenes Maria José 
Published: December 2024

AbstractBrain-derived neurotrophic factor (BDNF) is essential for neuronal survival, differentiation, and plasticity. In epilepsy, BDNF exhibits a dual role, exerting both antiepileptic and pro-epileptic effects. The cleavage of its main receptor, full-length tropomyosin-related kinase B (TrkB-FL), was suggested to occur in status epilepticus (SE) in vitro. Moreover, under excitotoxic conditions, TrkB-FL was found to be cleaved, resulting in the formation of a new intracellular fragment, TrkB-ICD. Thus, we hypothesized that TrkB-FL cleavage and TrkB-ICD formation could represent an uncovered mechanism in epilepsy.We used a rat model of mesial temporal lobe epilepsy (mTLE) induced by kainic acid (KA) to investigate TrkB-FL cleavage and TrkB-ICD formation during SE and established epilepsy (EE). Animals treated with 10 mg/kg of KA exhibited TrkB-FL cleavage during SE, with hippocampal levels of TrkB-FL and TrkB-ICD correlating with seizure severity. Notably, TrkB-FL cleavage and TrkB-ICD formation were also detected in animals with EE, which exhibited spontaneous recurrent convulsive seizures, neuronal death, mossy fiber sprouting, and long-term memory impairment. Importantly, hippocampal samples from patients with refractory epilepsy also showed TrkB-FL cleavage with increased TrkB-ICD levels. Additionally, overexpression of TrkB-ICD in the hippocampus of healthy rodents resulted in long-term memory impairment.Our findings suggest that TrkB-FL cleavage and the subsequent TrkB-ICD production occur throughout epileptogenesis, with the extent of cleavage correlating positively with seizure occurrence. Moreover, we found that TrkB-ICD impairs memory. This work uncovers a novel mechanism in epileptogenesis that could serve as a potential therapeutic target in mTLE, with implications for preserving cognitive function.
GRN_modeler: An Intuitive Tool for Constructing and Evaluating Gene Regulatory Networks and its Applications to Oscillators and a Light Biosensor
Authors: Holló Gábor , Park Jung Hun , Boni Emanuele , Schaerli Yolanda 
Published: December 2024

AbstractModeling and simulating gene regulatory networks (GRNs) is crucial for understanding biological processes, predicting system behavior, guiding the design of synthetic biological systems, and interpreting experimental data. In synthetic biology, GRNs play a pivotal role in enabling the design and control of complex systems for a wide range of applications. However, GRN simulations can be time-consuming and often require specialized expertise. To make this process more accessible, we developed a user-friendly application with a graphical user interface (GUI), allowing users to create simple phenomenological models without requiring prior programming experience. We demonstrate the versatility of our tool through several examples, including the design of novel oscillator families capable of robust oscillation with an even number of nodes. These complement the well-known repressilator family, which only oscillates with odd-numbered nodes. Furthermore, we showcase how GRN modeler allowed us to develop a light-detecting biosensor inEscherichia colithat can track light intensity over several days, leaving a record in the form of ring patterns in bacterial colonies. In summary, our work empowers biologists to model their systems of interest even without programming expertise.
Spatial-DC: a robust deep learning-based method for deconvolution of spatial proteomics
Authors: Li Yuan , Kong Qian , Wu Zihan , Xu Yanfen , Mao Yiheng , Gu Yunjie , Wang Xi , Gao Weina , Tian Ruijun , Yao Jianhua 
Published: December 2024

AbstractSpatial proteomics studies the spatial distribution of proteins within cells or tissues, providing a new perspective for comprehending cellular processes and disease mechanisms. One important challenge of current spatial proteomics technologies is low resolution, resulting in multiple cells in each spatial proteomics spot. While methods have been proposed to infer the composition of potential cell types in such spots for spatial transcriptomics, the depressed correlation and divergent quantification between transcriptome and proteome limits their capability in spatial proteomics.To enhance the utility of spatial proteomics data, we propose Spatial-DC (Spatial Digital Cytometry), a deep learning-based framework that infers cell-type composition in each spot and reconstructs spatially and cell-type resolved proteomic profiles. We achieve this by utilizing transfer learning and self-supervised learning with graph convolutional networks (GCN), which enables the incorporation of target spatial proteomics with reference single-cell or single-cell-type proteomics data.Through extensive simulations of spatial proteomics data, we demonstrate that Spatial-DC outperforms eight state-of-the-art methods in estimating cell-type composition and provides meaningful reconstructions of proteomic profiles for individual cell types. We apply Spatial-DC to different tissues measured using both multiplexed antibody-based and mass spectrometry (MS)-based spatial proteomics technologies. The results showcase Spatial-DC’s superior sensitivity in providing more refined cell-type distribution maps compared to cell-type-specific marker-based distributions and its feasibility in reconstructing spatially and cell-type resolved proteomic profiles from real-world spatial proteomics data. Moreover, we validate Spatial-DC with a newly self-collected pancreatic cancer spatial proteomics data characterized by complex tumor microenvironment (TME) and identify the signaling direction and strength at both spatial and cell-type levels within the TME, suggesting cell-type-specific and spatially-resolved interactions linked to tumor outcomes.Our results highlight Spatial-DC as a versatile tool for the deconvolution of spatial proteomics data across various tissue slices, providing a reliable foundation for downstream analysis.
The effect of an increasing elephant population on the allometry of trees
Authors: Thel Lucie , Stols Dietre , Orth Sarah , Lagendijk D.D. Georgette , Slotow Rob , Venter Jan A. , Fritz Herve 
Published: December 2024

AbstractAfrican savannas, which support a diverse range of plant species, from evergreen trees to deciduous shrubs, are regulated by complex interactions between climatic, fire, soil and herbivory processes. African elephants (Loxodonta africana) exert substantial top-down control over vegetation dynamics by utilising large amounts of plant biomass, as well as through various forms of non-consumptive effects. However, how much elephants affect the pattern of proportional growth between different tree components such as roots, stems or branches (known as allometry), remains understudied. Using vegetation data collected in 2000-2001 and 2019 for more than 3500 individual trees inside and outside Madikwe Game Reserve, South Africa, we determined the long-term effects of an increasing elephant population on allometric relationships in 13 tree species. The presence of elephants reduced logged canopy volume, and increasing elephant population in Madikwe reduced logged tree height and logged initial growth rate of the allometric relationship between tree height and tree diameter, without modifying asymptotic change in growth rate. Although not significantly, elephants seemed to increase asymptotic change in growth rate of canopy volume according to tree diameter, suggesting that compensatory mechanisms for the loss of height might happen in the longer-term. Although the species-specific elephant use index increased over the 20 years of the study, no consistent effect on allometric coefficients was detectable. Our study emphasises the necessity of long-term, species-specific studies to improve our understanding of how elephants affect allometric relationships in trees, which will ultimately guide management of savanna systems with increasing elephant numbers.
A High-Throughput Platform for Assessing Single Fly Learning and Memory: IndividualDrosophilaOlfactory Conditioner (iDOC)
Authors: Ortega Antonio , Tedre Erik , Baz El-Sayed , Tsao Chang-Hui , Chen Chien-Chun , Liu Sha 
Published: December 2024

SummaryOlfactory conditioning inDrosophila melanogasteris a widely used behavioral paradigm for uncovering the neural basis of learning and memory. The traditional T-maze assay, however, relies on group-level assessments and cannot examine individual flies’ learning and memory abilities. To address this limitation, we developed the IndividualDrosophilaOlfactory Conditioner (iDOC), an apparatus for single-fly conditioning and memory assessment. Using iDOC, we demonstrated aversive olfactory learning, short-term memory (STM), anesthesia-resistant memory (ARM), and protein synthesis-dependent long-term memory (LTM) in individual flies, consistent with previous experiments conducted using the T-maze. As an individual memory assessment method, iDOC can be integrated with other behavioral assays at the single animal level, such as sleep monitoring. Notably, we found that spaced training, which induces LTM, also promotes post-learning sleep, while massed training, which induces ARM, did not. iDOC thus provides a powerful platform for investigating learning and memory and its interplay with other behavioral processes at the individual animal level.HighlightsDeveloped iDOC for high-throughput, single-fly aversive olfactory training and memory assessmentDemonstrated aversive learning, STM, ARM, and LTM in individual flies using iDOCSpaced conditioning, and not massed conditioning, promotes sleep
Syn-tasiR-VIGS: Virus-Based Targeted RNAi in Plants By Synthetic Trans Acting Small Interfering RNAs Derived from Minimal Precursors
Authors: Cisneros Adriana E. , Alarcia Ana , Llorens-Gámez Juan José , Puertes Ana , Juárez-Molina María , Primc Anamarija , Carbonell Alberto 
Published: December 2024

AbstractSynthetic trans-acting small interfering RNAs (syn-tasiRNAs) are 21-nucleotide (nt) small RNAs designed to silence plant transcripts with high specificity. Their use as biotechnological tools for functional genomics and crop improvement is limited by the need to transgenically express longTASprecursors to produce syn-tasiRNAsin vivo. Here, we show that authentic and highly effective syn-tasiRNAs can be produced from minimal, non-TASprecursors consisting of a 22-nt endogenous microRNA target site, an 11-nt spacer and the 21 nt syn-tasiRNA sequence(s). These minimal precursors, when transgenically expressed inArabidopsis thalianaandNicotiana benthamiana, generated highly phased syn-tasiRNAs that silenced one or multiple plant genes with high efficacy. Remarkably, minimal but not full-lengthTASprecursors produced authentic syn-tasiRNAs and induced widespread gene silencing inN. benthamianawhen expressed from an RNA virus, which can be applied by spraying infectious crude extracts onto leaves in a GMO-free manner. This strategy, named syn-tasiRNA-based virus-induced gene silencing (syn-tasiR-VIGS), was further used to vaccinate plants against a pathogenic virus, resulting in complete plant immunization. Our results reveal that syn-tasiRNA precursors can be significantly shortened without compromising silencing efficacy, and that syn-tasiR-VIGS represents a versatile, scalable and non-transgenic platform for precision RNAi and antiviral vaccination in plants.Graphical abstract
GeneSetCluster 2.0: a comprehensive toolset for summarizing and integrating gene-sets analysis
Authors: Ortega-Legarreta Asier , Maillo Alberto , Mouzo Daniel , López-Pérez Ana Rosa , Kular Lara , Kakhki Majid Pahlevan , Jagodic Maja , Tegner Jesper , Lagani Vincenzo , Ewing Ewoud , Gomez-Cabrero David 
Published: December 2024

BackgroundGene-Set Analysis (GSA) is commonly used to analyze high-throughput experiments. However, GSA cannot readily disentangle clusters or pathways due to redundancies in upstream knowledge bases, which hinders comprehensive exploration and interpretation of biological findings. To address this challenge, we developed GeneSetCluster, an R package designed to summarize and integrate GSA results. Over time, we and users as well identified limitations in the original version, such as difficulties in managing redundancies across multiple gene-sets, large computational times, and its lack of accessibility for users without programming expertise.ResultsWe present GeneSetCluster 2.0, a comprehensive upgrade that delivers methodological, computational, interpretative, and user-experience enhancements. Methodologically, GeneSetCluster 2.0 introduces a novel approach to address duplicated gene-sets and implements a seriation-based clustering algorithm that reorders results, aiding pattern identification. Computationally, the package is optimized for parallel processing, significantly reducing execution time. GeneSetCluster 2.0 enhances cluster annotations by associating clusters with relevant tissues and biological processes to improve biological interpretation, particularly for human and mouse data. To broaden accessibility, we have developed a user-friendly web application enabling non-programmers to use it. This version also ensures seamless integration between the R package, catering to users with programming expertise, and the web application for broader audiences. We evaluated the updates in a single-cell RNA public dataset.ConclusionGeneSetCluster 2.0 offers substantial improvements over its predecessor. Furthermore, by bridging the gap between bioinformaticians and clinicians in multidisciplinary teams, GeneSetCluster 2.0 facilitates collaborative research. The R package and web application, along with detailed installation and usage guides, are available on GitHub (https://github.com/TranslationalBioinformaticsUnit/GeneSetCluster2.0), and the web application can be accessed athttps://translationalbio.shinyapps.io/genesetcluster/.
Bacteria-powered living materials enable coral larval settlement
Authors: Levy Natalie , Kundu Samapti , Freckelton Marnie , Dinasquet Julie , Flores Isabel , Galindo-Martínez Claudia T. , Tresguerres Martin , La Garza Vanessa De , Sun Yazhi , Karimi Zahra , Drury Crawford , Jury Christopher P. , Hancock Josh , Chen Shaochen , Hadfield Michael , Wangpraseurt Daniel 
Published: December 2024

AbstractThe global decline of coral reefs calls for new strategies to rapidly restock coral populations and maintain ecosystem functions and services. Low recruitment success on degraded reefs hampers coral sexual propagation and contributes to limited genetic diversity and reef resilience. Here, we introduce a living bacteria-powered reef ink (Brink) for assisted coral recruitment. Brink can be rapidly applied to restoration substrates via photopolymerization, and it has been formulated to cultivate two settlement-inducing bacterial strains (Cellulophaga lyticaandThalassotalea euphylliae). Settlement assays performed with broadcast spawning (Montipora capitata) and brooding (Pocillopora acuta) Indo-Pacific corals showed that Brink-coated substrates increased settlement >5-fold compared to uncoated control substrates. Brink can be applied as a coating or 3D bioprinted, leading to various potential applications for integration with reef engineering. Our approach underscores the potential of using functional living materials for augmented ecosystem engineering and reef rehabilitation.SynopsisThis study introduces a functional and sustainable bacteria-powered living material that enhances coral settlement, promoting coral reef rehabilitation and ecosystem resilience.