bluuebunny/crossref_metadata_2025_split huggingface dataset:
Proteomic profiling of IDH-wildtype Glioblastoma Tissue and Serum uncovers prognostic Subtypes and Marker Candidates
Authors: Werner Tilman , Schäfer Agnes , Hennes Michael , Cosenza Contreras Miguel , Espadas Guadalupe , Sabido Eduard , Cook Lena , Pagenstecher Axel , Pinter Niko , Feilen Tobias , Grote Alexander , Nimsky Christopher , Bartsch Jörg Walter , Schilling Oliver 
Published: March 2024

AbstractBackgroundIDH-wildtype glioblastoma (GBM) is the most prevalent primary brain cancer with a 5-year survival rate below 10%. Despite combined treatment through extensive resection and radiochemotherapy, nine out of ten patients develop recurrences. The lack of targeted treatment options and reliable diagnostic markers for recurrent tumors remain major challenges.Methods & AimsIn this study, we present the proteomic characterization of tissue and serum from 55 initial GBM tumors and five matching recurrences, which we investigated for proteomic tumor subtypes and proteomic signatures associated with recurrence.ResultsPrimary tumors revealed four distinct subgroups through hierarchical clustering: a neuronal cluster with elevated mature neuron markers, an innate immunity cluster with increased protease expression, a mixed cluster, and a stem-cell cluster. Neurodevelopmental and inflammatory processes were identified as key factors influencing clustering, with proteolytic activity increasing relative to the degree of inflammation. An analysis comprising proteins with lower coverage confirmed and expanded this pattern. Patients in the neuronal cluster exhibited significantly longer survival compared to those in the stem-cell cluster. In a patient-matched differential expression analysis, five recurrent tumors displayed significantly altered protein expression compared to their primary counterparts, emphasizing the proteomic plasticity of recurrent tumors. Investigation of serum proteomes before and after surgery, using a depletion-based protocol, revealed highly patient-specific and stable proteome compositions, despite a notable increase in inflammation markers post-surgery. However, the levels of circulating proteolytic products matched to the proteolytic activity within the tissue and one fragment of proteolysis activated receptor 2 (PAR2) consistently dropped in abundance after removal of inflamed tumors.ConclusionOverall, we describe a large proteomic GBM cohort. We identified distinct tumor subgroups, molecular patterns of recurrence, and matching proteomic patterns in the bloodstream, which may improve risk prediction for recurrent GBM.
TabHLH27 orchestrates root growth and drought tolerance to enhance water use efficiency in wheat
Authors: Wang Dongzhi , Zhang Xiuxiu , Cao Yuan , Batool Aamana , Xu Yongxin , Qiao Yunzhou , Li Yongpeng , Wang Hao , Lin Xuelei , Bie Xiaomin , Zhang Xiansheng , Jing Ruilian , Dong Baodi , Tong Yiping , Teng Wan , Liu Xigang , Xiao Jun 
Published: March 2024

ABSTRACTCultivating high-yield wheat under limited water resources is essential for sustainable agriculture in semiarid regions. Amid water scarcity, plants activate drought response signaling, yet the delicate balance between drought tolerance and development remains unclear. Through genome-wide-association study (GWAS) and transcriptome profiling, we identified a wheat atypical basic helix-loop-helix (bHLH) transcription factor (TF), TabHLH27-A1, as a promising quantitative trait locus (QTL) candidate for both relative root dry weight (DW.R%) and spikelet number per spike (SPS) in wheat. TabHLH27-A1/B1/D1 knockout reduced wheat drought tolerance, yield, and water use efficiency (WUE).TabHLH27-A1exhibited rapid induction with PEG treatment, gradually declining over days. It activated stress response genes such asTaCBL8-B1andTaCPI2-A1while inhibiting root growth genes likeTaSH15-B1andTaWRKY70-B1under short-term PEG stimulus. The distinct transcriptional regulation of TabHLH27-A1 involved diverse interacting factors such as TaABI3-D1 and TabZIP62-D1. Natural variations ofTabHLH27-A1influences its transcriptional responses to drought stress, withTabHLH27-A1Hap-IIassociated with stronger drought tolerance, larger root system, more spikelets, and higher WUE in wheat. Significantly, the eliteTabHLH27-A1Hap-IIwas selected during the breeding process in China, and introgression ofTabHLH27-A1Hap-IIallele improves drought tolerance and grain yield, especially under water-limited conditions. Our study highlights TabHLH27-A1’s role in balancing root growth and drought tolerance, providing a genetic manipulation locus for enhancing WUE in wheat.
Preclinical assessment of MAGMAS inhibitor as a potential therapy for pediatric medulloblastoma
Authors: Motahari Zahra , Lepe Javier J. , Bautista Malia R. , Hoerig Clay , Plant-Fox Ashley S. , Das Bhaskar , Fowler Christie D. , Magge Suresh N. , Bota Daniela A. 
Published: March 2024

AbstractMedulloblastoma, the most common pediatric brain malignancy, has Sonic Hedgehog (SHH) and non-SHH group3 subtypes. MAGMAS (Mitochondrial Associated Granulocyte Macrophage colony-stimulating factor Signaling molecules) encode for mitochondrial import inner membrane translocase subunit and is responsible for translocation of matrix proteins across the inner membrane. We previously reported that a small molecule MAGMAS inhibitor, BT9, decreases cell proliferation, migration, and oxidative phosphorylation in adult glioblastoma cell lines. The aim of our study was to investigate whether the chemotherapeutic effect of BT9 can be extended to pediatric medulloblastoma.MethodsMultiple in vitro assays were performed using human DAOY (SHH activated tp53 mutant) and D425 (non-SHH group 3) cells. The impact of BT9 on cellular growth, death, migration, invasion, and metabolic activity were quantified using MTT assay, TUNEL staining, scratch wound assay, Matrigel invasion chambers, and seahorse assay, respectively. Survival following 50mg/kg BT9 treatment was assessedin vivoin immunodeficient mice intracranially implanted with D425 cells.ResultsCompared to control, BT9 treatment led to a significant reduction in medulloblastoma cell growth (DAOY, 24hrs IC50: 3.6uM, 48hrs IC50: 2.3uM, 72hrs IC50: 2.1uM; D425 24hrs IC50: 3.4uM, 48hrs IC50: 2.2uM, 72hrs IC50: 2.1uM) and a significant increase in cell death (DAOY, 24hrs p=0.0004, 48hrs p<0.0001; D425, 24hrs p=0.0001, 48hrs p=0.02). In DAOY cells, 3uM BT9 delayed migration, and significantly decreased DAOY and D425 cells invasion (p < 0.0001). Ourin vivostudy, however, did not extend survival in xenograft mouse model of group3 medulloblastoma compared to vehicle-treated controls.ConclusionsOurin vitrodata showed BT9 antitumor efficacy in DAOY and D425 cell lines suggesting that BT9 may represent a promising targeted therapeutic in pediatric medulloblastoma. These data, however, need to be further validated in animal models.
Measuring instability in chronic human intracortical neural recordings towards stable, long-term brain-computer interfaces
Authors: Pun Tsam Kiu , Khoshnevis Mona , Hosman Thomas , Wilson Guy H. , Kapitonava Anastasia , Kamdar Foram , Henderson Jaimie M. , Simeral John D. , Vargas-Irwin Carlos E. , Harrison Matthew T. , Hochberg Leigh R. 
Published: March 2024

AbstractIntracortical brain-computer interfaces (iBCIs) enable people with tetraplegia to gain intuitive cursor control from movement intentions. To translate to practical use, iBCIs should provide reliable performance for extended periods of time. However, performance begins to degrade as the relationship between kinematic intention and recorded neural activity shifts compared to when the decoder was initially trained. In addition to developing decoders to better handle long-term instability, identifying when to recalibrate will also optimize performance. We propose a method to measure instability in neural data without needing to label user intentions. Longitudinal data were analyzed from two BrainGate2 participants with tetraplegia as they used fixed decoders to control a computer cursor spanning 142 days and 28 days, respectively. We demonstrate a measure of instability that correlates with changes in closed-loop cursor performance solely based on the recorded neural activity (Pearsonr= 0.93 and 0.72, respectively). This result suggests a strategy to infer online iBCI performance from neural data alone and to determine when recalibration should take place for practical long-term use.
Specifying precision in visual-orthographic prediction error representations for a better understanding of efficient reading
Authors: Fu Wanlu , Gagl Benjamin 
Published: March 2024

AbstractEfficient visual word recognition presumably relies on orthographic prediction error (oPE) representations. Based on a transparent neurocognitive computational model rooted in the principles of the predictive coding framework, we postulated that readers optimize their percept by removing redundant visual signals, allowing them to focus on the informative aspects of the sensory input (i.e., the oPE). Here, we explore alternative oPE implementations, testing whether increased precision by assuming all-or-nothing signaling and more realistic word lexicons results in adequate representations underlying efficient word recognition. We used behavioral and electrophysiological data (i.e., EEG) for model evaluation. More precise oPE representations (i.e., implementing a binary signaling and a frequency-sorted lexicon with the 500 most common five-letter words) explained variance in behavioral responses and electrophysiological data 300 ms after stimulus onset best. The original less-precise oPE representation still best explains early brain activation. This pattern suggests a dynamic adaption of represented visual-orthographic information, where initial graded prediction errors convert into binary representations, allowing accurate retrieval of word meaning. These results offer a neuro-cognitive plausible account of efficient word recognition, emphasizing visual-orthographic information in the form of prediction error representations central to the transition from perceptual processing to the access of word meaning.
Sex differences in the distribution and density of regulatory interneurons in the striatum
Authors: Van Zandt Meghan , Flanagan Deirdre , Pittenger Christopher 
Published: March 2024

AbstractDysfunction of the cortico-basal circuitry – including its primary input nucleus, the striatum – contributes to neuropsychiatric disorders, including autism and Tourette Syndrome (TS). These conditions show marked sex differences, occurring more often in males than in females. Regulatory interneurons, including cholinergic interneurons (CINs) and parvalbumin-expressing GABAergic fast spiking interneurons (FSIs), are implicated in human neuropsychiatric disorders such as TS, and ablation of these interneurons produces relevant behavioral pathology in male mice, but not in females. Here we investigate sex differences in the density and distribution of striatal interneurons, using stereological quantification of CINs, FSIs, and somatostatin-expressing (SOM) GABAergic interneurons in the dorsal striatum (caudate-putamen) and the ventral striatum (nucleus accumbens) in male and female mice. Males have a higher density of CINs than females, especially in the dorsal striatum; females have equal distribution between dorsal and ventral striatum. FSIs showed similar effects, with a greater dorsal-ventral density gradient in males than in females. SOM interneurons were denser in the ventral than in the dorsal striatum, with no sex differences. These sex differences in the density and distribution of FSIs and CINs may contribute to sex differences in basal ganglia function, including in the context of psychopathology.
Reduction Midpoint Potential of a Paradigm Light-Oxygen-Voltage Receptor and its Modulation by Methionine Residues
Authors: García de Fuentes Andrés , Möglich Andreas 
Published: March 2024

AbstractLight-dependent adaptations of organismal physiology, development, and behavior abound in nature and depend on sensory photoreceptors. As one class, light-oxygen-voltage (LOV) photoreceptors harness flavin-nucleotide chromophores to sense blue light. Photon absorption drives the LOV receptor to its signaling state, characterized by a metastable thioadduct between the flavin and a conserved cysteine residue. With this cysteine absent, LOV receptors instead undergo photoreduction to the flavin semiquinone which however can still elicit downstream physiological responses. Irrespective of the cysteine presence, the LOV photochemical response thus entails a formal reduction of the flavin. Against this backdrop, we here investigate the reduction midpoint potentialE0in the paradigm LOV2 domain fromAvena sativaphototropin 1 (AsLOV2), and how it can be deliberately varied. Replacements of residues at different sites near the flavin by methionine consistently increaseE0from its value of around –280 mV by up to 40 mV. Moreover, methionine introduction invariably impairs photoactivation efficiency and thus renders the resultantAsLOV2 variants less light-sensitive. Although individual methionine substitutions also affect the stability of the signaling state and downstream allosteric responses, no clear-cut correlation with the redox properties emerges. With a reduction midpoint potential near –280 mV,AsLOV2 and, by inference, other LOV receptors may be partially reduced inside cells which directly affects their light responsiveness. The targeted modification of the chromophore environment, as presently demonstrated, may mitigate this effect and enables the design of LOV receptors with stratified redox sensitivities.
A Combination of Environmental and Landscape Variables Drive Movement and Habitat use in TwoAnaxyrussp. in the Eastern Coastal Plain
Authors: Ferentinos Alexander M. , Check Courtney E. , Windorf Olivia , Leu Matthias 
Published: March 2024

ABSTRACTAmphibians are one of the most endangered taxa and are largely threatened by habitat loss. Little work has been conducted on the movement and habitat use of amphibians outside of the breeding season. In this study, we examined the movement patterns of two species of toads inhabiting the Eastern Coastal Plain of Virginia: the Eastern American Toad (Anaxyrus americanus americanus) and the Fowler’s Toad (Anaxyrus fowleri). Based on three years of movement data, we estimated the median migration distance of toads from their breeding location and the propensity for site fidelity, related variation in distance traveled to environmental (e.g., rain, temperature, humidity) and landscape variables (e.g., coniferous forests, distance to trails, terrain ruggedness index), and compared microhabitat selection for daytime refugia between the two species. We found the median distance from breeding grounds to be similar between the two species, 63 m for the Eastern American Toad and 64 m for the Fowler’s Toad, but Eastern American Toads had a greater range of moved distances (3rdquartiles were 122 m for Eastern American and 73 m for Fowler’s Toads). We also found that both species exhibit site fidelity. Distance to trails, proportion of conifer forest, minimum temperature, and 3-day cumulative rainfall related positively with increased movements. Compared to Fowler’s Toads, Eastern American Toads favored woody structures and leaf litter for daytime refugia. Our research provides crucial information for two toad species about the extent of their movements and habitat use during the nonbreeding season. To lessen the decline of amphibians, habitat occupied during the nonbreeding season needs to be included in conservation strategies at biologically relevant distances.
Segmentation aware probabilistic phenotyping of single-cell spatial protein expression data
Authors: Lee Yuju , Chen Edward L. Y. , Chan Darren C. H. , Dinesh Anuroopa , Afiuni-Zadeh Somaieh , Klamann Conor , Selega Alina , Mrkonjic Miralem , Jackson Hartland W. , Campbell Kieran R. 
Published: March 2024

AbstractSpatial protein expression technologies can map cellular content and organization by simultaneously quantifying the expression of >40 proteins at subcellular resolution within intact tissue sections and cell lines. However, necessary image segmentation to single cells is challenging and error prone, easily confounding the interpretation of cellular phenotypes and cell clusters. To address these limitations, we present STARLING, a novel probabilistic machine learning model designed to quantify cell populations from spatial protein expression data while accounting for segmentation errors. To evaluate performance we developed a comprehensive benchmarking workflow by generating highly multiplexed imaging data of cell line pellet standards with controlled cell content and marker expression and additionally established a novel score to quantify the biological plausibility of discovered cellular phenotypes on patient derived tissue sections. Moreover, we generate spatial expression data of the human tonsil – a densely packed tissue prone to segmentation errors – and demonstrate cellular states captured by STARLING identify known cell types not visible with other methods and enable quantification of intra- and inter- individual heterogeneity. STARLING is available athttps://github.com/camlab-bioml/starling.
Leukemia aggressiveness is driven by chromatin remodeling and expression changes of core regulators
Authors: Bonilla Gracia , Morris Alexander , Kundu Sharmistha , DuCasse Anthony , Kirkpatrick Grace , Jeffries Nathan E. , Chetal Kashish , Yvanovich Emma E. , Milosevic Jelena , Zhao Ting , Xia Jun , Barghout Rana , Scadden David , Mansour Michael K. , Kingston Robert E. , Sykes David B. , Mercier Francois E. , Sadreyev Ruslan I. 
Published: March 2024

ABSTRACTMolecular mechanisms driving clonal aggressiveness in leukemia are not fully understood. We tracked and analyzed MLL-rearranged leukemic clones independently evolving towards higher aggressiveness. More aggressive subclones lost their growth differential ex vivo but restored it upon secondary transplantation, suggesting molecular memory of aggressiveness. Development of aggressiveness was associated with clone-specific gradual modulation of chromatin states and expression levels across the genome, with a surprising preferential trend of reversing the earlier changes between normal and leukemic progenitors. To focus on the core aggressiveness program, we identified genes with consistent changes of expression and chromatin marks that were maintained in vivo and ex vivo in both clones. Overexpressing selected core genes (Smad1 as aggressiveness driver, Irx5 and Plag1 as suppressors) affected leukemic progenitor growth in the predicted way and had convergent downstream effects on central transcription factors and repressive epigenetic modifiers, suggesting a broader regulatory network of leukemic aggressiveness.
Activation of locus coeruleus noradrenergic neurons rapidly drives homeostatic sleep pressure
Authors: Silverman Daniel , Chen Changwan , Chang Shuang , Bui Lillie , Zhang Yufan , Raghavan Rishi , Jiang Anna , Darmohray Dana , Sima Jiao , Ding Xinlu , Li Bing , Ma Chenyan , Dan Yang 
Published: March 2024

AbstractHomeostatic sleep regulation is essential for optimizing the amount and timing of sleep, but the underlying mechanism remains unclear. Optogenetic activation of locus coeruleus noradrenergic neurons immediately increased sleep propensity following transient wakefulness. Fiber photometry showed that repeated optogenetic or sensory stimulation caused rapid declines of locus coeruleus calcium activity and noradrenaline release. This suggests that functional fatigue of noradrenergic neurons, which reduces their wake-promoting capacity, contributes to sleep pressure.
Low protein diet protects liver function upon Salmonella infection by metabolic reprogramming of macrophages
Authors: Wojtowicz Edyta E , Hampton Katherine , Moreno-Gonzalez Mar , Utting Charlotte L , Lan Yuxuan , Ruiz Paula , Beasy Gemma , Bone Caitlin , Hellmich Charlotte , Maynard Rebecca , Acton Luke , Telatin Andrea , Kingsley Robert A , Macaulay Iain C , Rushworth Stuart A , Beraza Naiara 
Published: March 2024

ABSTRACTBackground & AimsWestern diets are the underlying cause of metabolic and liver diseases. Recent trend to limit the consumption of protein-rich animal products has become more prominent. This dietary change entails decreased protein consumption; however, it is still unknown how this affects innate immunity. Here, we studied the influence of a low protein diet (LPD) on the liver response to bacterial infection.MethodsMice were fed a LPD and exposed toSalmonella entericaserotype Typhimurium infection. Mechanistic studies were donein vitrowhere bone marrow derived macrophages were cultured in a low-aa media to mimicin vivoreduction of protein availability and challenged with bacterial endotoxin.ResultsWe found that a LPD protects fromSTyphimurium-induced liver damage. Bulk- and 10xsingle cell-RNA sequencing of liver tissues and isolated immune cells showed reduced activation of myeloid cells in mice fed with LPD afterSTyphimurium infection. Mechanistically, we found reduced activation of the mammalian target of rapamycin (mTOR) pathway whilst increased phagocytosis and activation of autophagy in LPD-programmed macrophages. Dietary restoration of leucine reverted the protective effects of a LPD and restored the damaging effects of Salmonella on liver parenchyma in mice.ConclusionsLow protein diet protects the liver formSTyphimurium-induced tissue damage via modulating macrophage autophagy and phagocytosis. Our result support the causal role of dietary components on the fitness of the immune system.SYNOPSISLow protein diet protects the liver from Salmonella-mediated liver injury that associates with reduced mTOR activation and increased autophagy in macrophages. Restoration of the mTOR pathway with aminoacid supplementation reverses the protection of a low protein diet from Salmonella-liver damage.
Effects of input image size on the accuracy of fish identification using deep learning
Authors: Iwahara Yuka , Shibata Yasutoki , Manano Masahiro , Nishino Tomoya , Kariya Ryosuke , Yaemori Hiroki 
Published: March 2024

AbstractThe length composition of catches by species is important for stock assessment. However, length measurement is performed manually, jeopardizing the future of continuous measurement because of likely labor shortages. We focused on applying deep learning to estimate length composition by species from images of fish caught for sustainable management. In this study, input image sizes were varied to evaluate the effect of input image size on detection and classification accuracy, as a method for improving the accuracy. The images (43,226 fish of 85 classes) were captured on conveyor belts to sort set-net catches. Fish detection and classification were performed using Mask R-CNN. The effect of input image size on accuracy was examined using three image sizes of 1333×888, 2000×1333, and 2666×1777 pixels, achieving an mAP50-95 of 0.580 or higher. The accuracy improved with increasing image size, attaining a maximum improvement of 4.3% compared to the smallest size. However, increasing the image size too far from the default size may not improve the accuracy of models with fine-tuning. Improvements in accuracy were primarily observed for the species with low accuracy at the smallest image size. Increasing image size would be a useful and simple way to improve accuracy for these species.