bluuebunny/crossref_metadata_2025_split huggingface dataset:
Exploring the Landscape of Spatial Transcriptome Analysis: Introducing STASH, a Database of Spatial Transcriptome Tools
Authors: Chu Han , Wang Kun , Cheng Hansen , Ma Wenhao , Dong Liting , Gou Yixiong , Yang Jian , Cai Haoyang 
Published: April 2023

AbstractSpatial transcriptomics (ST) has emerged as a powerful tool for unravelling tissue structure and function. However, the continuous development of ST has made it challenging to select and effectively use appropriate analysis tools. To address this issue, we have developed the Spatial Transcriptome Analysis Hub (STASH,http://cailab.labshare.cn:7004), a comprehensive, systematic, and user-friendly database of ST analysis tools. STASH collects and categorizes most of the tools currently available and provides insight into their current status and trends. This can help researchers quickly locate the appropriate tool for their needs, or even guide researchers in the development of better tools.
Efficient multiple gene knock-out inColletotrichum higginsianumvia CRISPR-Cas9 ribonucleoprotein andURA3-based marker recycling
Authors: Yonehara Katsuma , Kumakura Naoyoshi , Motoyama Takayuki , Ishihama Nobuaki , Dallery Jean-Félix , O’Connell Richard , Shirasu Ken 
Published: April 2023

AbstractColletotrichum higginsianum is a hemibiotrophic pathogen that causes anthracnose disease on crucifer hosts, including Arabidopsis thaliana. Despite the availability of genomic and transcriptomic information and the ability to transform both organisms, identifying C. higginsianum genes involved in virulence has been challenging due to their recalcitrance to gene targeting and redundancy of virulence factors. To overcome these obstacles, we developed an efficient method for multiple gene disruption in C. higginsianum by combining CRISPR-Cas9 and URA3-based marker recycling systems. Our method significantly increased the efficiency of gene knock-out via homologous recombination by introducing genomic DNA double-strand breaks. We demonstrated the applicability of the URA3-based marker recycling system for multiple gene targeting in the same strain. Using our technology, we successfully targeted two melanin biosynthetic genes, SCD1 and PKS1, which resulted in deficiency in melanisation and pathogenicity in the mutants. Our findings demonstrate the effectiveness of our developments in analysing virulence factors in C. higginsianum, thus accelerating research on plant-fungus interactions.
A novel injectable radiopaque hydrogel with potent properties for multicolor CT imaging in the context of brain and cartilage regenerative therapy
Authors: Said Moustoifa , Tavakoli Clément , Dumot Chloé , Toupet Karine , Dong Yuxi Clara , Collomb Nora , Auxenfans Céline , Moisan Anaïck , Favier Bertrand , Chovelon Benoit , Barbier Emmanuel Luc , Jorgensen Christian , Cormode David Peter , Noël Danièle , Brun Emmanuel , Elleaume Hélène , Wiart Marlène , Detante Olivier , Rome Claire , Auzély-Velty Rachel 
Published: April 2023

AbstractCell therapy is promising to treat many conditions, including neurological and osteoarticular diseases. Encapsulation of cells within hydrogels facilitates cell delivery and can improve therapeutic effects. However, much work remains to be done to align treatment strategies with specific diseases. The development of imaging tools that enable monitoring cells and hydrogel independently is key to achieving this goal. Our objective herein is to longitudinally study an iodine-labeled hydrogel, incorporating gold-labeled stem cells, by bicolor CT imaging afterin vivoinjection in rodent brains or knees. To this aim, an injectable self-healing hyaluronic acid (HA) hydrogel with long-persistent radiopacity was formed by the covalent grafting of a clinical contrast agent on HA. The labeling conditions were tuned to achieve sufficient X-ray signal and to maintain the mechanical and self-healing properties as well as injectability of the original HA scaffold. The efficient delivery of both cells and hydrogel at the targeted sites was demonstrated by synchrotron K-edge subtraction-CT. The iodine labeling enabled to monitor the hydrogel biodistributionin vivoup to 3 days post-administration, which represents a technological first in the field of molecular CT imaging agents. This tool may foster the translation of combined cell-hydrogel therapies into the clinics.
Genistein enhances NAD+biosynthesis by binding to Prohibitin 1 and upregulating nicotinamide phosphoribosyltransferase in adipocytes
Authors: Watanabe Shun , Haruyama Riki , Umezawa Koji , Tomioka Ikuo , Nakamura Soichiro , Katayama Shigeru , Mitani Takakazu 
Published: April 2023

AbstractDecreased NAD+levels in adipocytes cause adipose-tissue dysfunction, leading to systemic glucose and lipid metabolism failure. Therefore, developing small molecules and nutraceuticals that can increase NAD+levels in adipocytes is necessary. Genistein, a nutraceutical derived from soybeans, has various physiological activities and improves glucose and lipid metabolism. In this study, we aimed to unravel the effects of genistein on the intracellular NAD+levels in adipocytes and the underlying molecular mechanisms. We showed that genistein enhanced NAD+biosynthesis by increasing the expression of nicotinamide phosphoribosyltransferase (NAMPT), the rate-limiting enzyme in NAD+biosynthesis. A pull-down assay using genistein-immobilized beads identified prohibitin 1 (PHB1) as a target protein of genistein. The knockdown of PHB1 suppressed the genistein-induced increase in NAMPT expression and NAD+levels in adipocytes. Genistein-bound PHB1 contributed to the stabilization of the transcription factor CCAAT/enhancer-binding protein β through activation of extracellular signal-regulated kinase, resulting in increased NAMPT expression at the transcriptional level. Genistein induced dephosphorylation of peroxisome proliferator-activated receptor at serine 273 and increased the insulin-sensitizing adipokine, adiponectin, in adipocytes, whereas the knockdown of NAMPT and PHB1 abolished these genistein-mediated effects. Our results proved the potential efficacy of nutraceuticals in promoting NAD+levels and restoring metabolic function in adipocytes. Furthermore, we identified PHB1, localized to the plasma membrane, as a candidate target protein for increased expression of NAMPT in adipocytes. Overall, these findings will assist in developing NAD+boosting strategies to alleviate the metabolic dysfunctions in adipose tissues.Significance StatementIncreasing NAD+levels is an important preventive strategy for maintaining metabolic function. Here, we showed that genistein, a nutraceutical, which increases NAD+levels in adipocytes, increased NAD+biosynthesis by upregulating nicotinamide phosphoribosyltransferase (NAMPT), a rate-limiting enzyme in the NAD+biosynthesis pathway. Our findings also showed that genistein increased NAMPT expression by binding to prohibitin 1 in the plasma membrane. Genistein-induced increase in NAD+levels promoted adiponectin expression, an insulin-sensitizing adipokine, in adipocytes. This study provides evidence that nutraceuticals, such as genistein, are effective in enhancing NAD+biosynthesis in adipocytes and that PHB1 is a candidate target protein for increased expression of NAMPT to maintain metabolic functions in adipose tissues.
AbFold -- an AlphaFold Based Transfer Learning Model for Accurate Antibody Structure Prediction
Authors: Peng Chao , Wang Zelong , Zhao Peize , Ge Weifeng , Huang Charles 
Published: April 2023

AbstractMotivationAntibodies are a group of proteins generated by B cells, which are crucial for the immune system. The importance of antibodies is ever-growing in pharmaceutics and biotherapeutics. Despite recent advancements pioneered by AlphaFold in general protein 3D structure prediction, accurate structure prediction of antibodies still lags behind, primarily due to the difficulty in modeling the Complementarity-determining regions (CDRs), especially the most variable CDR-H3 loop.ResultsThis paper presents AbFold, a transfer learning antibody structure prediction model with 3D point cloud refinement and unsupervised learning techniques. AbFold consistently produces state-of-the-art results on the prediction accuracy of the six CDR loops. The predictions of AbFold achieve an average RMSD of 1.51 Å for both heavy and light chains and an average RMSD of 3.04 Å for CDR-H3, bettering current models AlphaFold and IgFold. AbFold will contribute to antibody structure prediction and design processes.
Pathfinder: protein folding pathway prediction based on conformational sampling
Authors: Huang Zhaohong , Cui Xinyue , Xia Yuhao , Zhao Kailong , Zhang Guijun 
Published: April 2023

AbstractThe study of protein folding mechanism is a challenge in molecular biology, which is of great significance for revealing the movement rules of biological macromolecules, understanding the pathogenic mechanism of folding diseases, and designing protein engineering materials. Based on the hypothesis that the conformational sampling trajectory contain the information of folding pathway, we propose a protein folding pathway prediction algorithm named Pathfinder. Firstly, Pathfinder performs large-scale sampling of the conformational space and clusters the decoys obtained in the sampling. The heterogeneous conformations obtained by clustering are named seed states. Then, a resampling algorithm that is not constrained by the local energy basin is designed to obtain the transition probabilities of seed states. Finally, protein folding pathways are inferred from the maximum transition probabilities of seed states. The proposed Pathfinder is tested on our developed test set (34 proteins). For 5 widely studied proteins, we correctly predicted their folding pathways. For 25 partial biological experiments proteins, we predicted folding pathways could be further verified. For the other 4 proteins without biological experiment results, potential folding pathways were predicted to provide new insights into protein folding mechanism. The results reveal that structural analogs may have different folding pathways to express different biological functions, homologous proteins may contain common folding pathways, and α-helices may be more prone to early protein folding than β-strands.
Endogenous epitope tagging of eEF1A2 in mice reveals early embryonic expression of eEF1A2 and subcellular compartmentalisation of neuronal eEF1A1 and eEF1A2
Authors: Davies Faith C.J. , Marshall Grant F. , Gadd Danni , Abbott Catherine M. 
Published: April 2023

AbstractAll vertebrate species express two independently-encoded forms of translation elongation factor eEF1A. In humans and mice eEF1A1 and eEF1A2 are 92% identical at the amino acid level, but the well conserved developmental switch between the two variants in specific tissues suggests the existence of important functional differences. Heterozygous mutations in eEF1A2 result in neurodevelopmental disorders in humans; the mechanism of pathogenicity is unclear, but one hypothesis is that there is a dominant negative effect on eEF1A1 during development. The high degree of similarity between the eEF1A proteins has complicated expression analysis in the past; here we describe a gene edited mouse line in which we have introduced a V5 tag in the gene encoding eEF1A2. Expression analysis using anti-V5 and anti-eEF1A1 antibodies demonstrates that, in contrast to the prevailing view that eEF1A2 is only expressed postnatally, it is expressed from as early as E11.5 in the developing neural tube. Two colour immunofluorescence also reveals coordinated switching between eEF1A1 and eEF1A2 in different regions of postnatal brain. Completely reciprocal expression of the two variants is seen in post-weaning mouse brain with eEF1A1 expressed in oligodendrocytes and astrocytes and eEF1A2 in neuronal soma. Although eEF1A1 is absent from neuronal cell bodies after development, it is widely expressed in axons. This expression does not appear to coincide with myelin sheaths originating from oligodendrocytes but rather results from localised translation within the axon, suggesting that both variants are transcribed in neurons but show completely distinct subcellular localisation at the protein level. These findings will form an underlying framework for understanding how missense mutations in eEF1A2 result in neurodevelopmental disorders.
Epidermal tyrosine catabolism is critical for metabolic homeostasis and survival against high-protein diets inDrosophila
Authors: Kosakamoto Hina , Miura Masayuki , Obata Fumiaki 
Published: April 2023

AbstractThe insect epidermis that forms the exoskeleton and determines the body size of an organism has the potential to respond and adapt to the changing nutritional environment. However, the extent to which the tissue contributes to adaptation to varying dietary protein availability, as well as its role as a metabolic regulator, remains incompletely understood. Here, we show that theDrosophilaepidermis promptly reacts to dietary protein intake, promoting tyrosine (Tyr) catabolism. Among the enzymes involved in Tyr degradation, 4- hydroxyphenylpyruvate dioxygenase (Hpd) is particularly induced under high-protein regimens. We found that AMP-activated protein kinase (AMPK) pathway and forkhead box O subfamily (FoxO) induce Hpd expression. Impaired Hpd function in the epidermis leads to aberrant increases in internal Tyr levels and its metabolites, disrupting larval development under high-protein diets. Taken together, our findings uncover the critical role of epidermal metabolism in adapting to imbalanced protein environments and hence in promoting animal survival.Summary statementTyrosine degradation is upregulated inDrosophilaepidermal tissue via the AMPK-FoxO axis upon dietary high-protein stress.
Regression models for partially localized fMRI connectivity analyses
Authors: Smith Bonnie B. , Zhao Yi , Lindquist Martin A. , Caffo Brian 
Published: April 2023

AbstractBrain functional connectivity analysis of resting-state functional magnetic resonance imaging (fMRI) data is typically performed in a standardized template space assuming consistency of connections across subjects. This can come in the form of one-edge-at-a-time analyses or dimension reduction/decomposition methods. Common to these approaches is the assumption of complete localization (or spatial alignment) of brain regions across subjects. Alternative approaches completely eschew localization assumptions by treating connections as statistically exchangeable (for example, using the density of connectivity between nodes). Yet other approaches, such as hyperalignment, attempt to align subjects on function as well as structure, thereby achieving a different sort of template-based localization. In this paper, we propose the use of simple regression models to characterize connectivity. To that end, we build regression models on subject-level Fisher transformed regional connection matrices using geographic distance, homotopic distance, network labels, and region indicators as covariates to explain variation in connections. While we perform our analysis in template-space in this paper, we envision the method being useful in multi-atlas registration settings, where subject data remains in its own geometry and templates are warped instead. A byproduct of this style of analysis is the ability to characterize the fraction of variation in subject-level connections explained by each type of covariate. Using Human Connectome Project data, we found that network labels and regional characteristics contribute far more than geographic or homotopic relationships (considered non-parametrically). In addition, visual regions had the highest explanatory power (i.e., largest regression coefficients). We also considered subject repeatability and found that the degree of repeatability seen in fully localized models is largely recovered using our proposed subject-level regression models. Further, even fully exchangeable models retain a sizeable amount of repeatability information, despite discarding all localization information. These results suggest the tantalizing possibility that fMRI connectivity analysis can be performed in subject-space, using less aggressive registration, such as simple affine transformations, multi-atlas subject-space registration, or perhaps even no registration whatsoever.
Unisensory visual and auditory objects are processed in olfactory cortex, independently of odor association
Authors: Thunell Evelina , Peter Moa , Iravani Behzad , Porada Danja K. , Prenner Katharina , Darki Fahimeh , Lundström Johan N. 
Published: April 2023

AbstractPrimary sensory cortices have been demonstrated to process sensory input from non-preferred sensory modalities, e.g. primary visual cortex reacting to auditory stimulation, bringing their presumed sensory specificity into question. Whether this reflects processing of the non-preferred stimulus per se or originates from cross-modal associations is debated. Visual/auditory objects typically have strong reciprocal associations; hence, it is difficult to address this question in these modalities. Here, we attempt to dissociate between the two competing hypotheses of whether this form of activation in primary cortices is caused by unisensory processing or cross-modal associations by turning to the olfactory system where cross-modal associations are generally weaker. Using unisensory visual and auditory objects with odor associations ranging from none to strong, we show that the posterior piriform cortex, an area known to process odor objects, is activated by both sounds and pictures of objects. Critically, this activation is independent of the objects’ odor associations, thereby demonstrating that the activity is not due to cross-modal associations. Using a Floyd–Warshall algorithm, we further show that the amygdala mediate condition-relevant information between the posterior piriform cortex and both the auditory and visual object-oriented cortices. Importantly, we replicate past findings of clear crossmodal processing in the visual and auditory systems. Our study demonstrates processing of non-olfactory input in olfactory cortices that is independent of cross-modal associations and contributes to a more nuanced view of modality specificity in olfactory, auditory, and visual cortices.
Alterations in cortical excitability during pain: A combined TMS-EEG Study
Authors: Chowdhury Nahian S , Chiang Alan KI , Millard Samantha K , Skippen Patrick , Chang Wei-Ju , Seminowicz David A , Schabrun Siobhan M 
Published: April 2023

AbstractTranscranial magnetic stimulation (TMS) has been used to examine inhibitory and facilitatory circuits during experimental pain and in chronic pain populations. However, current applications of TMS to pain have been restricted to measurements of motor evoked potentials (MEPs) from peripheral muscles. Here, TMS was combined with electroencephalography (EEG) to determine whether experimental pain could induce alterations in cortical inhibitory/facilitatory activity observed in TMS-evoked potentials (TEPs). In Experiment 1 (n = 29), multiple sustained thermal stimuli were administered to the forearm, with the first, second and third block of thermal stimuli consisting of warm but non-painful (pre-pain block), painful (pain block) and warm but non-painful (post-pain block) temperatures respectively. During each stimulus, TMS pulses were delivered while EEG (64 channels) was simultaneously recorded. Verbal pain ratings were collected between TMS pulses. Relative to pre-pain warm stimuli, painful stimuli led to an increase in the amplitude of the frontocentral negative peak ∼45ms post-TMS (N45), with a larger increase associated with higher pain ratings. Experiments 2 and 3 (n = 10 in each) showed that the increase in the N45 in response to pain was not due to changes in sensory potentials associated with TMS, or a result of stronger reafferent muscle feedback during pain. This is the first study to use combined TMS-EEG to examine alterations in cortical excitability in response to pain. These results suggest that the N45 TEP peak, which indexes GABAergic neurotransmission, is implicated in pain perception and is a potential marker of individual differences in pain sensitivity.
A quasi-analytic solution for real-time multi-exposure speckle imaging of tissue perfusion
Authors: Rivera Daniel A. , Schaffer Chris B. 
Published: April 2023

AbstractLaser speckle contrast imaging (LSCI) is a widefield imaging technique that enables high spatiotemporal resolution measurement of blood flow. Laser coherence, optical aberrations, and static scattering effects restrict LSCI to relative and qualitative measurements. Multi-exposure speckle imaging (MESI) is a quantitative extension of LSCI that accounts for these factors but has been limited to post-acquisition analysis due to long data processing times. Here we propose and test a real-time quasi-analytic solution to fitting MESI data, using both simulated and real-world data from a mouse model of photothrombotic stroke. This rapid estimation of multi-exposure imaging (REMI) enables processing of full-frame MESI images at up to 8 Hz with negligible errors relative to time-intensive least-squares methods. REMI opens the door to real-time, quantitative measures of perfusion change using simple optical systems.
Complex Conformational Space of RNA Polymerase II C-Terminal Domain upon Phosphorylation
Authors: Amith Weththasinghage D. , Dutagaci Bercem 
Published: April 2023

ABSTRACTIntrinsically disordered proteins (IDPs) have been closely studied during the past decade due to their importance for many biological processes. The disordered nature of this group of proteins makes it difficult to observe its full span of the conformational space either using experimental or computational studies. In this article, we explored the conformational space of the C-terminal domain (CTD) of RNA polymerase II (Pol II), which is also an intrinsically disordered low complexity domain, using enhanced sampling methods. We provided a detailed conformational analysis of model systems of CTD with different lengths; first with the last 44 residues of the human CTD sequence and finally the CTD model with two heptapeptide repeating units. We then investigated the effects of phosphorylation on CTD conformations by performing simulations at different phosphorylated states. We obtained broad conformational spaces in non-phosphorylated CTD models and phosphorylation has complex effects on the conformations of the CTD. These complex effects depend on the length of the CTD, spacing between the multiple phosphorylation sites, ion coordination and interactions with the nearby residues.