bluuebunny/crossref_metadata_2025_split huggingface dataset:
Citalopram exhibits immune-dependent anti-tumor effects by modulating C5aR1+TAMs and CD8+T cells
Authors: Dong Fangyuan , Zhang Shan , Song Kaiyuan , Jiang Luju , Hu Li-Peng , Li Qing , Zhang Xue-Li , Li Jun , Feng Mingxuan , Cai Zhi-Wei , Yao Hong-Fei , Li Rong-Kun , Li Hui , Chen Jie , Hu Xiaona , Wang Jiaofeng , Jiang Chongyi , Zhu Helen He , Wang Cun , Da Lin-Tai , Zhang Zhi-Gang , Bao Zhijun , Wang Xu , Jiang Shu-Heng 
Published: October 2024

AbstractAdministration of selective serotonin reuptake inhibitors (SSRIs) is associated with a reduced cancer risk and shows significant anti-tumor effects across multiple tumor types, suggesting the potential for repurposing SSRIs in cancer therapy. Nonetheless, the specific molecular target and mechanism of action of SSRIs remain to be fully elucidated. Here, we reveal that citalopram exerts an immune-dependent anti-tumor effects in hepatocellular carcinoma (HCC). Interestingly, the anti-HCC effects of citalopram are not reliant on its conventional target, the serotonin transporter. Through various drug repurposing approaches, including global reverse gene expression profiling, drug affinity responsive target stability assay, and molecular docking, the complement component 5a receptor 1 (C5aR1) is identified as a new target of citalopram. C5aR1 is predominantly expressed by tumor-associated macrophages (TAMs), and citalopram treatment enhances local macrophage phagocytosis and elicits CD8+T anti-tumor immunity. At a systemic level, citalopram treatment results in decreased serum 5-HT levels, which correlates with increased activation of CD8+T cells. Additionally, citalopram promotes αCD3/αCD28-stimulated CD8+T cell activation, expansion, and cytotoxicity. Depletion of CD8+T cells partially hinders the anti-HCC effects of citalopram. Collectively, our study reveals multiple immunomodulatory roles of citalopram in inducing anti-tumor immunity, and provides a basis for considering the repurposing of SSRIs as promising anticancer agents for HCC treatment.
Niclosamide Prodrug Enhances Oral Bioavailability and Targets Vasorin-TGFβ Signaling in Hepatocellular Carcinoma
Authors: Tan Mingdian , Ye Wei , Liu Yi , Chen Xiaowu , Huttad Lakshmi , Chua Mei-Sze , So Samuel 
Published: October 2024

AbstractBackgroundHepatocellular carcinoma (HCC) ranks third in cancer-related deaths worldwide, with limited therapeutic options. While niclosamide (NIC) has shown potential for repurposing in HCC, its poor water solubility and low bioavailability limit its efficacy, and its mechanisms of action are not yet fully elucidated.MethodsWe designed a water-soluble NIC prodrug (NIC-PS) and evaluated its efficacy throughin vitroandin vivostudies, including pharmacokinetic (PK) and pharmacodynamic (PD) assays, HCC patient-derived xenograft (PDX) models were applied in two independent experiments, vasorin (VASN) knockout models, and combination treatments with NIC-PS and sorafenib or anti-PD-L1 antibody. Bioinformatic analyses and western blotting were used to investigate NIC-PS’s target, VASN, and related signaling pathways.ResultsNIC-PS exhibited aten-fold increase in oral bioavailabilityand reduced tumor volume by over75%in HCC PDX models. NIC-PS directly binds and suppresses VASN, suppressing TGFβ signaling and reducing SMAD2/3 phosphorylation. VASN inhibition led to a50% tumor reduction, and NIC-PS enhanced responses to sorafenib and anti-PD-L1 therapy.ConclusionsNIC-PS, equal to 36% of NIC in molecular weight, offers improved bioavailability, efficacy, and anovel mechanism of action in targeting VASN, showing promise for HCC treatment alone or in combination therapy.
The Infralimbic, but not the Prelimbic Cortex is needed for a Complex Olfactory Memory Task
Authors: Jun Dahae J. , Shannon Rebecca , Tschida Katherine , Smith David M. 
Published: October 2024

AbstractThe medial prefrontal cortex (mPFC) plays a key role in memory and behavioral flexibility, and a growing body of evidence suggests that the prelimbic (PL) and infralimbic (IL) subregions contribute differently to these processes. Studies of fear conditioning and goal-directed learning suggest that the PL promotes behavioral responses and memory retrieval, while the IL inhibits them. Other studies have shown that the mPFC is engaged under conditions of high interference. This raises the possibility that the PL and IL play differing roles in resolving interference. To examine this, we first used chemogenetics (DREADDs) to suppress mPFC neuronal activity and tested subjects on a conditional discrimination task known to be sensitive to muscimol inactivation. After confirming the effectiveness of the DREADD procedures, we conducted a second experiment to examine the PL and IL roles in a high interference memory task. We trained rats on two consecutive sets of conflicting odor discrimination problems, A and B, followed by test sessions involving a mid-session switch between the problem sets. Controls repeatedly performed worse on Set A, suggesting that learning Set B inhibited the rats’ ability to retrieve Set A memories (i.e. retroactive interference). PL inactivation rats performed similarly to controls. However, IL inactivation rats did not show this effect, suggesting that the IL plays a critical role in suppressing the retrieval of previously acquired memories that may interfere with retrieval of more recent memories. These results suggest that the IL plays a critical role in memory control processes needed for resolving interference.
Branched-chain amino acid catabolism promotes ovarian cancer cell proliferation via phosphorylation of mTOR
Authors: Lusk Hannah J. , Haughan Monica A. , Bergsten Tova M. , Burdette Joanna E. , Sanchez Laura M. 
Published: October 2024

ABSTRACTOvarian cancer is the sixth leading cause of cancer-related mortality among individuals with ovaries, and high-grade serous ovarian cancer (HGSOC) is the most common and lethal subtype. Characterized by a distinct and aggressive metastatic pattern, HGSOC can originate in the fallopian tube with the transformation of fallopian tube epithelial (FTE) cells, which metastasize to the ovary and subsequently to the omentum and peritoneal cavity. The omentum is a privileged metastatic site, and the metabolic exchange underlying omental metastasis could provide enzyme or receptor targets to block spread. In this study, we adapted a mass spectrometry imaging (MSI) protocol to investigate spatial location of 3D cocultures of tumorigenic FTE cells when grown in proximity to murine omental explants as a model of early metastatic colonization. Our analysis revealed several altered metabolites in tumorigenic FTE/omentum cocultures, namely changes in branched-chain amino acids (BCAA), including valine. We quantified the heightened consumption of valine, other BCAAs, and other amino acid-derived metabolites in omental cocultures using LC-MS assays. Our analysis revealed that metabolite concentrations when monitored with MSI from cell culture media in living culture systems have notable considerations for how MSI data may produce signatures that induce ionization suppression. Supplementation with valine enhanced proliferation and mTOR signaling in tumorigenic FTE cells, suggesting the potential of BCAA’s as a nutrient utilized by tumor cells during omental colonization and a possible target for metastasis.SIGNIFICANCEThis study uncovers altered amino acid metabolism, specifically increased BCAA catabolism, at the interface of ovarian cancer cells and omental tissue in a coculture model of HGSOC secondary metastasis. Enhanced BCAA catabolism may promote cancer cell proliferation through mTOR signaling, presenting potential therapeutic value. These findings deepen our understanding of HGSOC pathogenesis and the metastatic tumor microenvironment, offering insights for developing new treatment strategies.
An integrative spatial multi-omic workflow for unified analysis of tumor tissue
Authors: Kriel Jurgen , Moffet Joel J.D. , Lu Tianyao , Fatunla Oluwaseun E. , Narayana Vinod K. , Valkovic Adam , Maluenda Ana , McConville Malcolm J. , Tsui Ellen , Whittle James R. , Best Sarah A. , Freytag Saskia 
Published: October 2024

AbstractCombining molecular profiling with imaging techniques has advanced the field of spatial biology, offering new insights into complex biological processes. Focusing on diffuseIDH-mutated low-grade glioma, this study presents a workflow for Spatial Multi-omics Integration, SMINT, specifically combining spatial transcriptomics and spatial metabolomics. Our workflow incorporates both existing and custom-developed computational tools to enable cell segmentation and registration of spatial coordinates from both modalities to a common coordinate framework. During our investigation of cell segmentation strategies, we found that nuclei-only segmentation, while containing only 40% of segmented cell transcripts, enables accurate cell type annotation, but does not account for multinucleated cells. Our integrative workflow including cell-morphology segmentation identified distinct cellular neighborhoods at the infiltrating edge of gliomas, which were enriched in multinucleated and oligodendrocyte-lineage tumor cells, that may drive tumor invasion into the normal cortical layers of the brain.HighlightsAlignment and integrated analysis of spatial transcriptomic and metabolomic dataNuclei-only and cell-morphology segmentations are concordant for cell annotationSpatially distinct regions are conserved in transcriptomic and metabolomic datasetsMulti-omic exploration of glioma leading edge identifies novel biological features
CELL-Diff: Unified Diffusion Modeling for Protein Sequences and Microscopy Images
Authors: Dihan Zheng , Huang Bo 
Published: October 2024

AbstractFluorescence microscopy is ubiquitously used in cell biology research to characterize the cellular role of a protein. To help elucidate the relationship between the amino acid sequence of a protein and its cellular function, we introduce CELL-Diff, a unified diffusion model facilitating bidirectional transformations between protein sequences and their corresponding microscopy images. Utilizing reference cell morphology images and a protein sequence, CELL-Diff efficiently generates corresponding protein images. Conversely, given a protein image, the model out-puts protein sequences. CELL-Diff integrates continuous and diffusion models within a unified framework and is implemented using a transformer-based network. We train CELL-Diff on the Human Protein Atlas (HPA) dataset and finetune it on the OpenCell dataset. Experimental results demonstrate that CELL-Diff outperforms existing methods in generating high-fidelity protein images, making it a practical tool for investigating subcellular protein localization and interactions.
Generation of cultured beef from bovine embryonic stem cells
Authors: Rui Xue , Li Zehan , Xu Jiehuan , Dai Jianjun , Zhang Xiaohui , Jin Xiao , Liu Yang 
Published: October 2024

AbstractBovine embryonic stem cells (bESCs) serve as an optimal source for generating muscle and fat tissues. However, systematic methodologies for creating cultured beef from bESCs have not yet been reported. Here, we successfully established a bESC line and formulated a specialized culture medium that supports cell pluripotency in both two-dimensional (2D) and three-dimensional (3D) cultures. Additionally, we have also developed serum-free and transgene-free protocols that efficiently differentiate bESCs into muscle and fat cells. These differentiated cells were validated at the transcriptional and protein levels. Furthermore, we devised a method using high moisture stretched plant-based protein scaffolds for incorporating differentiated muscle and fat cells derived from bESCs, producing an innovative plant-cell hybrid cultured beef. These advancements provide a solid foundation for future cultured beef production using pluripotent stem cells.
Speed amplitude and period affect gait variability and step followability under sinusoidal speed changing conditions
Authors: Motoyama Kiyotaka , Tashiro Takehiro , Saito Akira , Horiuchi Masahiro , Sakaki Taisuke , Abe Daijiro 
Published: October 2024

AbstractBackgroundThe time courses of the joint elevation angles of the thigh, shank, and foot in one stride during walking can be well approximated by a “plane” in a triaxial space. This intersegmental coordination (IC) of the lower limb elevation angles is called planar covariation law. Thickness of the ICplaneis associated with gait variability. This study aimed to examine how anteroposterior and lateral gait variabilities are influenced by sinusoidal speed changes with different amplitudes (±0.33 vs. ±0.67 m·s-1) and periods (30 vs. 60 s). We also questioned which limbs are responsible for the step variabilities in these conditions.MethodsEighteen young adults walked on a treadmill under sinusoidal speed-changing conditions with different amplitudes (±0.33 vs. ±0.67 m·s-1) and periods (30-vs. 60-s). Using 3D motion analysis system, we quantified the ICplanethickness, coefficient of variance of step width (CVSW), time delay of step length (TDSL), and step frequency (TDSF). We applied 2-way statistical parametric mapping for the time courses of each limb angle during the acceleration and deceleration phases.ResultsThe ICplanethickness was greater in the ±0.67 m·s-1condition than in the ±0.33 m·s-1condition. Periods and amplitudes did not affect CVSW, TDSL, and TDSF. In the middle gait cycle, the thigh and shank were delayed in the greater amplitude condition during the acceleration phase but proceeded in the same condition during the deceleration phase.DiscussionSinusoidal speed amplitude influenced anteroposterior gait variability, but not lateral gait variability, regardless of period, even in healthy young adults. More distal limbs were delayed in the greater speed amplitude condition during the acceleration phase, whereas more proximal limbs proceeded in that condition during the deceleration phase, indicating that these different behaviors of the lower limb segments could be related to step variabilities.
Nonparametric serial interval estimation
Authors: Gressani Oswaldo , Hens Niel 
Published: October 2024

AbstractThe serial interval of an infectious disease is a key instrument to understand transmission dynamics. Estimation of the serial interval distribution from illness onset data extracted from transmission pairs is challenging due to the presence of censoring and state-of-the-art frequentist or Bayesian methods mostly rely on parametric models. We present a fully data-driven methodology to estimate the serial interval distribution based on (coarse) serial interval data. The proposal combines a nonparametric estimator of the cumulative distribution function with the bootstrap and yields point and interval estimates of any desired feature of the serial interval distribution. Algorithms underlying our approach are simple, fast and stable, and are thus easily implementable in any programming language most desired by modelers from the infectious disease community. The nonparametric routines are included in the EpiLPS package for ease of implementation. Our method complements existing parametric approaches for serial interval estimation and permits to straightforwardly analyze past, current, or future illness onset data streams.
Partial Correlation as a Tool for Mapping Functional-Structural Correspondence in Human Brain Connectivity
Authors: Santucci Francesca , Jimenez-Marin Antonio , Gabrielli Andrea , Bonifazi Paolo , Ibáñez-Berganza Miguel , Gili Tommaso , Cortes Jesus M. 
Published: October 2024

AbstractBrain structure-function coupling has been studied in health and disease by many different researchers in recent years. Most of the studies have addressed functional connectivity matrices by estimating correlation coefficients between different brain areas, despite well-known disadvantages compared to partial correlation connectivity matrices. Indeed, partial correlation represents a more sensible model for structural connectivity since, under a Gaussian approximation, it accounts only for direct dependencies between brain areas. Motivated by this and following previous results by different authors, we investigate structure-function coupling using partial correlation matrices of functional magnetic resonance imaging (fMRI) brain activity time series under different regularization (a.k.a. noise-cleaning) algorithms. We find that, across different algorithms and conditions, partial correlation provides a higher match with structural connectivity retrieved from Density Weighted Imaging data than standard correlation, and this occurs at both subject and population levels. Importantly, we also show that the precise regularization and thresholding strategy are crucial for this match to emerge. Finally, we assess neuro-genetic associations in relation to structure-function coupling, which presents promising opportunities to further advance research in the field of network neuroscience, particularly concerning brain disorders.
Identification of new targets for the diagnosis of cysts (four) and trophozoites (one) of the eye pathogenAcanthamoeba
Authors: Sundararaj Bharath Kanakapura , Goyal Manish , Samuelson John 
Published: October 2024

AbstractAcanthamoebae, which are free-living amoebae, cause corneal inflammation (keratitis) and blindness, if not diagnosed and effectively treated. While trophozoites adhere to and damage the cornea,Acanthamoebacysts, the walls of which contain cellulose and have two layers connected by conical ostioles, are the diagnostic form by microscopy of the eye or of corneal scrapings. We recently used structural and experimental methods to characterize cellulose-binding domains of Luke and Leo lectins, which are abundant in the inner layer and ostioles. However, no antibodies have been made to these lectins or to a Jonah lectin and a laccase, which are abundant in the outer layer. Here we used confocal microscopy to show that rabbit antibodies to recombinant Luke, Leo, Jonah, and laccase generally support localizations of GFP-tagged proteins in walls of transfectedAcanthamoebae.Rabbit antibodies to all four wall proteins efficiently detected calcofluor white-labeled cysts of 10 of 11Acanthamoebaisolates obtained from the ATCC, including five T4 genotypes that cause most cases of keratitis. Laccase shed into the medium during encystation was detected by an enzyme-linked immunoassay. We also used structural and experimental methods to characterize the mannose-binding domain of anAcanthamoebamannose-binding protein and showed that rabbit antibodies to the mannose-binding domain efficiently detected trophozoites of all 11Acanthamoebaisolates. We conclude that four wall proteins are all excellent targets for diagnosingAcanthamoebacysts in the eye or corneal scrapings, while the mannose-binding domain is an excellent target for identifying trophozoites in cultures of corneal scrapings.ImportanceFree-living amoeba in the soil or water causeAcanthamoebakeratitis, which is diagnosed by identification of cysts by microscopy of the eye or of corneal scrapings, using calcofluor-white that unfortunately cross-reacts with fungi and plants. Alternatively,Acanthamoebainfections are diagnosed by identification of trophozoites in cultures of scrapings. Here we showed that rabbit antibodies to four abundant cyst wall proteins (Jonah, Luke, Leo, and laccase) each efficiently detect calcofluor-white-labeled cysts of 10 of 11Acanthamoebaisolates obtained from the ATCC. Further, laccase released into the medium by encystingAcanthamoebaewas detected by an enzyme-linked immunoassay. We also showed that rabbit antibodies to the mannose-binding domain of theAcanthamoebamannose-binding protein, which mediates adherence of trophozoites to keratinocytes, efficiently identifies trophozoites of all 11 ATCC isolates. In summary, four wall proteins and the ManBD appear to be excellent targets for diagnosis ofAcanthamoebacysts and trophozoites, respectively.
Plant phenotypic differentiation outweighs genetic variation in shaping the lettuce leaf microbiota
Authors: Capparotto Arianna , Chesneau Guillaume , Tondello Alessandra , Stevanato Piergiorgio , Bonato Tiziano , Squartini Andrea , Hacquard Stéphane , Giovannetti Marco 
Published: October 2024

SummaryLettuce is a widely consumed raw vegetable, making it crucial to understand and predict its leaf-associated microbial communities for the benefit of both plant and human health. While environmental factors are known to strongly influence plant leaf microbiomes, the role of plant-specific determinants in shaping microbial diversity remains unclear. In this study, we investigated the impact of three key plant factors -genetic distance, morphology and leaf micro- and macronutrient content- on the composition and diversity of lettuce leaf bacterial communities.Using 131 fully-sequencedLactuca sativagenotypes, we analyzed their leaf-associated bacterial communities via 16S rRNA amplicon sequencing. Our findings revealed that morphological classification, as defined by breeders, exerts a greater influence on bacterial community diversity than genetic distance or variations in leaf nutrient levels. Together with shoot traits they explained 13.9% of the observed bacterial diversity. Further analysis of 10 specific leaf morphological traits showed that heart formation, head height, and venation types significantly shaped bacterial richness and evenness, mainly acting on non-hub members.The strong association between leaf morphology and bacterial community structure suggests that phenotypic traits play a disproportionately large, yet understudied, role in leaf microbiota establishment offering new potential for manipulation by breeders.
EEG markers of vigilance, task-induced fatigue and motivation during sustained attention: Evidence for decoupled alpha- and beta-signatures
Authors: Hanzal Simon , Learmonth Gemma , Thut Gregor , Harvey Monika 
Published: October 2024

AbstractReduced vigilance can be captured in measures of attentional lapses in sustained attention tasks, but just how these lapses relate to task-induced fatigue and motivation to maintain optimal performance is unclear. We used the sustained attention to response task (SART) to induce fatigue, and manipulated motivation levels for the last block of the task in young and older participants (N = 34), while recording EEG to track electrophysiological markers of vigilance change, fatigue and motivation. Despite significant increases in subjective fatigue and mind wandering over 45 minutes, no vigilance decline was observed. However, the age groups differed markedly in their response strategies from the outset (adopting distinct speed-accuracy trade-off strategies) with faster/more erroneous responses in the younger and slower/more accurate responses in the older participants. The subjective rises in fatigue/mind wandering were coupled with an increase in pre-stimulus alpha-power, whereas the post-stimulus activity revealed two distinguishable beta signatures: a fronto-central topography as a marker of response strategy and a fronto-parietal distribution modulated by motivationper se. Our results thus show three distinct neural patterns underpinning the effects of fatigue, response strategy and motivation and suggest a (motivational) cognitive control mechanism behind resetting of performance decrement, independent of persistent fatigue.