bluuebunny/crossref_metadata_2025_split huggingface dataset:
Regulation of Ferroptosis in Obesity: Muscle Type-Specific Effects of Dietary Restriction and Exercise
Authors: Ji Fujue , Lee Haesung , Kim Jong-Hee 
Published: August 2024

BackgroundObesity is a significant global health issue and a risk factor for numerous diseases. Ferroptosis, an iron-dependent regulated cell death, is triggered by iron overload and the excessive accumulation of lipid peroxidation mediated by reactive oxygen species. Studies has identified a strong association between ferroptosis and obesity. Additionally, dietary restriction (DR) and DR combined with exercise (DR+Ex) are effective strategies for managing obesity and ferroptosis. However, the regulation of ferroptosis and its signaling pathways in skeletal muscle under conditions of obesity, DR, and DR+Ex remains poorly understood.MethodsMice were divided into four groups: normal diet, high-fat diet, high-fat DR, and high-fat DR+Ex. All mice were fed ad libitum with either a normal or high-fat diet for the first 14 weeks, followed by the respective interventions for the subsequent 8 weeks. Mice muscle ferroptosis were examined by immunohistochemistry, Hematoxylin & Eosin, Masson’s trichrome, Prussian blue staining, and Western-Immunoblot.ResultsThe high-fat diet resulted in increased inflammatory cell infiltration, fibrosis, and iron accumulation. Red and white muscle showed increased expression of 4-HNE, regulated by GPX4 and NCAO4, respectively. DR and DR+Ex reduced downstream 4-HNE expression by regulating GPX4 in red muscle.ConclusionDue to metabolic differences, obesity-induced ferroptosis in skeletal muscle and the regulation by DR+Ex exhibiting fiber type-specificity. Specifically, red and white muscle respond to obesity-induced ferroptosis through different pathways; red muscle can inhibit obesity-induced ferroptosis through DR+Ex by GPX4. This deepens the understanding of mechanisms related to skeletal muscle cell death and provides scientific data support for the personalized treatment of related diseases.
A humanized yeast model for studying TRAPP complex mutations; proof-of-concept using variants from an individual with aTRAPPC1-associated neurodevelopmental syndrome
Authors: Zykaj Erta , Abboud Chelsea , Asadi Paria , Warsame Simane , Greco Brittany , López-Sánchez Marcos , Bratkovic Drago , Kachroo Aashiq , Pérez-Jurado Luis Alberto , Sacher Michael 
Published: August 2024

AbstractVariants in membrane trafficking proteins are known to cause rare disorders with severe symptoms. The highly conserved transport protein particle (TRAPP) complexes are key membrane trafficking regulators that are also involved in autophagy. Pathogenic genetic variants in specific TRAPP subunits are linked to neurological disorders, muscular dystrophies, and skeletal dysplasias. Characterizing these variants and their phenotypes is important for understanding general and specialized roles of TRAPP subunits as well as for patient diagnosis. Patient-derived cells are not always available, which poses a limitation for the study of these diseases. Therefore, other systems, like the yeastSaccharomyces cerevisiae, can be used to dissect the mechanisms at the intracellular level underlying these disorders. The development of CRISPR/Cas9 technology in yeast has enabled a scar-less editing method that creates an efficient humanized yeast model. In this study, core yeast subunits were humanized by replacing their human orthologs, and TRAPPC1, TRAPPC2, TRAPPC2L, TRAPPC6A, and TRAPPC6B were found to successfully replace their yeast counterparts. This system was used for studying the first reported individual with an autosomal recessive disorder caused by biallelicTRAPPC1variants, a girl with a severe neurodevelopmental disorder and myopathy. We show that the maternal variant (TRAPPC1 p.(Val121Alafs*3)) is non-functional while the paternal variant (TRAPPC1 p.(His22_Lys24del)) is conditional-lethal and affects secretion and non-selective autophagy in yeast. This parallels defects seen in fibroblasts derived from this individual which also showed membrane trafficking defects and altered Golgi morphology, all of which were rescued in the human system by wild typeTRAPPC1. This study suggests that humanized yeast can be an efficient means to study TRAPP subunit variants in the absence of human cells, and can assign significance to variants of unknown significance (VUS). This study lays the foundation for characterizing further TRAPP variants through this system, rapidly contributing to disease diagnosis.
What works to improve species conservation state? An analysis of species whose state has improved and the actions responsible
Authors: Simkins Ashley T. , Sutherland William J. , Dicks Lynn V. , Hilton-Taylor Craig , Grace Molly K. , Butchart Stuart H.M. , Senior Rebecca A. , Petrovan Silviu O. 
Published: August 2024

AbstractUnderstanding the consequences of past conservation efforts is essential to inform the means of maintaining and restoring species. Data from the IUCN Red List for 67,217 comprehensively assessed animal species were reviewed and analysed to determine (i) which conservation actions have been implemented for different species, (ii) which types of species have improved in state and (iii) which actions are likely to have driven the improvements. At least 51.8% (34,847) of assessed species have actions reported, mostly comprising protected areas (82.7%), with more actions reported for both terrestrial tetrapods and warm-water reef-building corals and fewer for fish, dragonflies and damselflies and crustaceans. Species at greater risk of extinction have a wider range of species-targeted actions reported compared to less threatened species, reflecting differences in documentation and conservation efforts. Six times more species have deteriorated rather than improved in their Red List category. Almost all species that improved have conservation actions in place; species that improved in state typically were historically at high risk of extinction, have smaller ranges and lacked a range of reported threats, particularly hunting and habitat loss or degradation. All types of conservation action were associated with improvements in state, especially reintroductions and invasive species control, alongside, for amphibians and birds, area management. This suggests a range of conservation interventions have successfully conserved some species at greatest risk but have rarely recovered populations to resilient levels. Scaling up the extent and intensity of conservation interventions, particularly landscape-scale actions that benefit broadly distributed species, is urgently needed to assist the recovery of biodiversity.
Two types of regeneration mechanism in acute liver injury
Authors: Aoyagi Tomomi , Goya Takeshi , Imoto Koji , Azuma Yuki , Hioki Tomonobu , Kohjima Motoyuki , Tanaka Masatake , Oda Yoshinao , Ogawa Yoshihiro 
Published: August 2024

AbstractThe liver has a strong regenerative capacity, but the mechanisms of liver regeneration are not well understood. Furthermore, many previous studies on liver regeneration have been conducted in partial hepatectomy models, which may differ from acute liver injury with inflammation and necrosis, as observed in many clinical cases. In this study, we conducted a single-cell RNA-seq analysis (scRNA-seq) of liver regeneration in mice treated with acetaminophen (APAP) using publicly available data. We discovered that two cell proliferation populations appeared simultaneously during a single regenerative process. The two populations differed significantly in terms of differentiation, localization, proliferation rate, and signal response. Furthermore, one of the populations was induced by contact with necrotic tissue and exhibited a higher proliferative capacity with a dedifferentiated feature. These findings can shed new light on liver regeneration and aid in the development of therapeutic strategies for liver failure.
Identifying Differential Spatial Expression Patterns across Different Slices, Conditions and Developmental Stages with Interpretable Deep Learning
Authors: Cui Yan , Yuan Zhiyuan 
Published: August 2024

AbstractSpatially resolved transcriptomics technologies enable the mapping of multiplexed gene expression profiles within tissue contexts. To explore the gene spatial patterns in complex tissues, computational methods have been developed to identify spatially variable genes within single tissue slices. However, there is a lack of methods designed to identify genes with differential spatial expression patterns (DSEPs) across multiple slices or conditions, which becomes increasingly common in complex experimental designs. The challenges include the complexity of cross-slice gene expression and spatial information modeling, scalability issues in constructing large-scale cell graphs, and mixed factors of inter-slice heterogeneity. We propose DSEP gene identification as a new task and develop River, an interpretable deep learning-based method, to solve this task. River comprises a two-branch prediction model architecture and a post-hoc attribution method to prioritize DSEP genes that explain condition differences. River’s special design for modeling spatial-informed gene expression makes it scalable to large-scale spatial omics datasets. We proposed strategies to decouple the spatial and non-spatial components of River’s outcomes. We validated River’s performance using simulated datasets and applied it to identify DSEP genes/proteins in diverse biological contexts, including embryo development, diabetes-induced alterations in spermatogenesis, and lupus-induced splenic changes. In a human triple-negative breast cancer dataset, River identified generalizable survival-related DSEPs, validated across unseen patient groups. River does not rely on specific data distribution assumptions and is compatible with various spatial omics data types, making it a versatile method for analyzing complex tissue architectures across multiple biological conditions.
Single component CRISPR-mediated base- editors forAgrobacteriumand their use to develop an improved suite of strains
Authors: Pennetti Vincent J. , LaFayette Peter R. , Parrott Wayne Allen 
Published: August 2024

AbstractAgrobacterium mediated plant transformation largely depends on two distinct strain lineages – C58 and Ach5. To better serve the plant transformation community, we have created a suite of auxotrophic and auxotrophic recombinant deficient mutants of C58 derivatives EHA105, GV3101::pMP90, and Ach5 derivative LBA4404. While these derivatives are useful, having additional strain backgrounds available would help expand the repertoire for plant transformation even further. Toward that end, two underutilized hypervirulent strains are K599 (NCPPB 2659), and Chry5—but disarmed variants are not easily accessible. To improve availability, we produced disarmed versions ofA. rhizogenesstrain K599 andA. tumefaciensstrain Chry5 and introduced the same desirable mutations as with the other lineages. Each thymidine auxotrophy and recombination deficiency were introduced to existing and newly disarmed Agrobacterium strains via loss of function mutations conferred tothyAandrecA, respectively, through CRISPR-mediated base-editing of codons amenable to nonsense mutation. To streamline the editing process, we created a series of visually marked single component base-editor vectors and a corresponding guide-filtering Geneious Prime wrapper plugin for expedited guide filtering. These new strains, the simplified CRISPR-mediated base-editor plasmids, and streamlined workflow will improve the ease with which futureAgrobacteriumstrain derivatives are created while also supporting plant transformation at large.
Discovery of ICOS-targeted small molecules using affinity selection mass spectrometry screening
Authors: Zhang Longfei , Calvo-Barreiro Laura , de Sousa Batista Victor , Świderek Katarzyna , Gabr Moustafa T. 
Published: August 2024

AbstractInducible T cell co-stimulator (ICOS) is a positive immune checkpoint receptor expressed on the surface of activated T cells, which could promote cell function after being stimulated with ICOS ligand (ICOS-L). Although clinical benefits have been reported in the ICOS modulation-based treatment for cancer and autoimmune disease, current modulators are restricted in biologics, whereas ICOS-targeted small molecules are lacking. To fill this gap, we performed an affinity selection mass spectrometry (ASMS) screening for ICOS binding using a library of 15,600 molecules. To the best of our knowledge, this is the first study that utilizes ASMS screening to discover small molecules targeting immune checkpoints. Compound9with a promising ICOS/ICOS-L inhibitory profile (IC50= 29.38 ± 3.41 µM) was selected as the template for the modification. Following preliminary structure-activity relationship (SAR) study and molecular dynamic (MD) simulation revealed the critical role of the ortho-hydroxy group on compound9in the ICOS binding, as it could stabilize the interaction via the hydrogen bond formation with residuals on the glycan, and the depletion could lead to an activity lost. This work validates a promising inhibitor for the ICOS/ICOS-L interaction, and we anticipate future modifications could provide more potent modulators for this interaction.
Large scale serum proteomics identifies proteins associated with performance decline and clinical milestones in Duchenne muscular dystrophy
Authors: Ikelaar N.A. , Barnard A.M. , Eng S.W.M. , Vajargah S. Hosseini , Ha K.C.H. , Kan H.E. , Vandenborne K. , Niks E.H. , Walter G.A. , Spitali P. 
Published: August 2024

AbstractSerum biomarkers are promising minimally invasive outcome measures in clinical studies in Duchenne muscular dystrophy (DMD). However, biomarkers strongly associated with clinical progression and predicting performance decline are lacking. In this study we aimed to identify serum biomarkers associated with clinical performance and able to predict clinical milestones in DMD. Towards this aim we present a retrospective multi-center cohort study including serum samples and clinical data collected in research participants with DMD as part of a natural history study at the University of Florida (UF) and real-world observations at Leiden University Medical Center (LUMC) between 2009-2022. The 7K SomaScan® assay was used to analyse protein levels in in individual serum samples. Serum biomarkers predicted age at loss of ambulation (LoA), age at loss of overhead reach (OHR) and age at loss of hand to mouth function (HTM). Secondary outcomes were the association of biomarkers with age, corticosteroid (CS) usage, and clinical performance based on the North Star Ambulatory Assessment (NSAA), 10 meter run velocity (10mrv), 6 minute walk (6MWT) and Performance of the Upper Limb (PUL2.0). A total of 716 serum samples were collected in 79 participants at UF and 74 at LUMC (mean[SD] age; 10.9[3.2] vs 8.4[3.4]). 244 serum proteins showed an association with CS usage in both cohorts independent of CS type and regimen, including MMP3 and IGLL1. 318 probes (corresponding to 294 proteins) showed significant associations with NSAA, 10mrv, 6MWT and/or PUL2.0 across both cohorts. The expression of 38 probes corresponding to 36 proteins such as RGMA, EHMT2, ART3, ANTXR2 and DLK1 was associated with risk of both lower and upper limb clinical milestones in both the LUMC and UF cohort. In conclusion, multiple biomarkers were associated with CS use, motor function and upper lower and upper limb disease milestones in DMD. These biomarkers were validated across two independent cohorts, increasing their likelihood of translation for use within the broader DMD population.
Towards an automated protocol for wildlife density estimation using camera-traps
Authors: Zampetti Andrea , Mirante Davide , Palencia Pablo , Santini Luca 
Published: August 2024

AbstractCamera-traps are valuable tools for estimating wildlife population density, and recently developed models enable density estimation without the need for individual recognition. Still, processing and analysis of camera-trap data are extremely time-consuming. While algorithms for automated species classification are becoming more common, they have only served as supporting tools, limiting their true potential in being implemented in ecological analyses without human supervision. Here, we assessed the capability of two camera-trap based models to provide robust density estimates when image classification is carried out by machine learning algorithms.We simulated density estimation with Camera-Traps Distance Sampling (CT-DS) and Random Encounter Model (REM) under different scenarios of automated image classification. We then applied the two models to obtain density estimates of three focal species (roe deerCapreolus capreolus, red foxVulpes vulpes, and Eurasian badgerMeles meles) in a reserve in central Italy. Species detection and classification was carried out both by the user and machine learning algorithms (respectively, MegaDetector and Wildlife Insights), and all outputs were used to estimate density and ultimately compared. Simulation results suggested that the CT-DS model could provide robust density estimates even at poor algorithm performances (down to 50% of correctly classified images), while the REM model is more unpredictable and depends on multiple factors. Density estimates obtained from the MegaDetector output were highly consistent for both models with the manually labelled images. While Wildlife Insights’ performance differed greatly between species (recall: badger = 0.15; roe deer = 0.56; fox = 0.75), CT-DS estimates did not vary significantly; on the contrary, REM systematically overestimated density, with little overlap in standard errors.We conclude that CT-DS and REM models can be robust to the loss of images when machine learning algorithms are used to identify animals, with the CT-DS being an ideal candidate for applications in a fully unsupervised framework. We propose guidelines to evaluate when and how to integrate machine learning in the analysis of camera-trap data for density estimation, further strengthening the applicability of camera traps as a cost-effective method for density estimation in (spatially and temporally) extensive multi-species monitoring programs.
Rare earth elements extraction from Idaho-sourced surface soil by phytomining
Authors: Richardson Kathryn , Mirkouei Amin , Duellman Kasia , Aylward Anthony , Zirker David , Schwarz Eliezer , Sun Ying 
Published: August 2024

AbstractEnvironmentally-friendly and low emission extraction methods are needed to meet worldwide rare earth element (REE) demand. Within a greenhouse setting, we assessed the REE hyperaccumulation ability of four plant species (e.g.,Phalaris arundinacea, Solanum nigrum, Phytolacca americana, andBrassica juncea) and the impact of amending REE-rich soil with biochar or fertilizer and watering with citric acid solution. Harvested samples were pyrolyzed, and the resulting bio-ores were acid-digested and underwent elemental analysis to determine REE content. Amending soil with fertilizer and biochar increased bio-ore production, while plant species explained most variation in bioaccumulation factor.Phalaris arundinaceaachieved the highest average REE concentration of 27,940 ppm for targeted REEs (i.e., cerium, lanthanum, neodymium, praseodymium, and yttrium) and 37,844 ppm for total REEs. We successfully extracted REE-rich bio-ore from plant biomass and determined that soil amendment and plant species will be critical parameters in design and implementation of Idaho-based REE phytomining operations.Graphical Abstract
GBA1mutations alter neuronal firing and structure, regulating VGLUT2 and CRYAB in dopamine neurons
Authors: Rodríguez-Traver Eva , Suárez Luz M. , Crespo Carlos , González-Burgos Irene , Vecino Rebeca , Jurado-Coronel Juan C. , Galán María , González-González Marta , Moratalla Rosario , Vicario Carlos 
Published: August 2024

AbstractMutations in theGBA1gene are major risk factors for Parkinsońs disease (PD), but their role in PD pathology is not fully understood. The impact ofGBA1mutations was investigated in dopamine (DA) neurons obtained from induced pluripotent stem cells (iPSCs) derived from PD patients carrying the N370S or L444PGBA1mutation. DA neurons co-expressing TH and VGLUT2 were detected in the cultures, and their number and/or expression ofVGLUT2/SLC17A6mRNA was markedly reduced in both N370S and L444P cultures compared to controls. A significant increase in the firing rate of N370S neurons was found, whereas evoked dopamine release was stronger from neurons carrying either mutation. Furthermore, mutant neurons accumulated abundant degenerative structures, and there was a significant accumulation of α-synuclein aggregates in N370S neurons. Notably, a significant upregulation of the chaperoneCRYAB/HSPB5/alpha-crystallin-Bwas found early in DA neuron differentiation and in the substantia nigra of PD patients. Our findings indicate that N370S and L444PGBA1mutations impair midbrain DA neurons expressing VGLUT2, and provoke molecular, functional and structural changes, possibly involved in PD pathology.
Multimodal electrical impedance tomography and electroencephalography imaging: Does higher skull conductivity resolution in EIT imaging improve accuracy of EEG source localization?
Authors: Rimpiläinen Ville , Koulouri Alexandra 
Published: August 2024

AbstractObjectiveUnknown conductivities of the head tissues, particularly the skull, is a major factor of uncertainty in electroencephalography (EEG) source imaging. Here, we develop a personalized skull conductivity framework aiming to improve the head models used in the EEG source imaging and to reduce localization errors.MethodsWe employ Electrical Impedance Tomography (EIT) and convex optimization to produce high resolution skull conductivity maps that are subsequently embedded in the EEG modeling.ResultsFirst, we demonstrate through simulations that locally varying conductivity values of the skull can be estimated from EIT measurements. Second, we show how the choice of the skull conductivity resolution of the EIT imaging affects the EEG source reconstructions.ConclusionsEIT estimated conductivities can signicantly improve the source reconstructions, particularly in cortical areas under bones that exhibit high conductivity variations.SignificanceThis work acts as a steppingstone in defining a protocol for the preparation of patient-specic head conductivity models that are essential for accurate examination and systematic monitoring of the brain activity via EEG.
Connectivity loss in experimental pond networks leads to biodiversity loss in microbial communities
Authors: Szabó Beáta , Váczy-Földi Máté , Vad Csaba F. , Pálffy Károly , Huỳnh Thu-Hương , Dobosy Péter , Fierpasz Ádám , Márton Zsuzsanna , Felföldi Tamás , Horváth Zsófia 
Published: August 2024

AbstractHabitat fragmentation is among the most important global threats to biodiversity, however, the direct effects of its components including connectivity loss are still lesser known. Our understanding of these drivers is especially limited in microbial communities. Here, by conducting a four-month outdoor experiment with artificial pond (mesocosm) metacommunities, we studied the effects of connectivity loss on planktonic prokaryote and microeukaryote communities. Connectivity loss was simulated by stopping the dispersal among local habitats while keeping the habitat amount constant and the abiotic environment homogeneous. We found that connectivity loss led to higher levels of extinction and a decrease in both local and regional diversity in microeukaryotes. In contrast, diversity patterns of prokaryotes remained largely unaffected, with some indications of extinction debt. Connectivity loss also led to lower evenness in microeukaryotes, likely through changes in biotic interactions with zooplankton grazers. Our results imply that connectivity loss can directly translate into species losses in communities and highlight the importance of conserving habitat networks with sufficient dispersal among local habitats.