bluuebunny/crossref_metadata_2025_split huggingface dataset:
Generating human parvalbumin interneurons through 3D glia reprogramming
Authors: Stamouli Christina-Anastasia , Degener Alexander , Cepeda-Prado Efrain , Bruzelius Andreas , Andersson Emil , Giacomoni Jessica , Vorgeat Aurélie Delphine , Kidnapillai Srisaiyini , Klementieva Oxana , Parmar Malin , Olariu Victor , Ottosson Daniella Rylander 
Published: September 2024

SummaryParvalbumin (PV) interneurons are crucial for synaptic plasticity, and their damage or loss is linked to various neurological disorders. Yet, generating these cells of human sourcein vitrois challenging, limiting advancements in cell repair and disease modelling. We introduce a novel approach to derive human PV neurons through direct reprogramming of glial precursor cells (GPCs). Using ectopic expression of GABAergic neuronal genes, GPCs efficiently convert into GABAergic interneurons in 3D culture environment within weeks and achieve functional neuronal maturity. Single-nuclei RNA sequencing identified a distinct PV neuronal cluster with high maturity and characteristics of PV chandelier subclass that are equivalent to bona fide human interneurons. Trajectory analysis revealed a distinct glia-to-PV interneuron conversion pathway, involving several new transitory genes, with potential for functional importance for PV derivation. Our data introduces a new strategy for generating human PV interneurons, promising significant implications for future generation of patient-specific PV neurons bothin vitroandin vivo.HighlightsA novel approach to derive human PV interneurons by direct glia reprogramming.First comprehensive transcriptomic profiling of induced human PV interneurons.Induced PV interneurons are of chandelier subtype with transcriptional similarity tobona fideinterneurons.Successful glia-to-PV interneuron conversion passes through a specific reprogramming trajectory and involves key genes with functional potential.
Single cell genome and epigenome co-profiling reveals hardwiring and plasticity in breast cancer
Authors: Wang Kaile , Yan Yun , Elgamal Heba , Li Jianzhuo , Tang Chenling , Bai Shanshan , Xiao Zhenna , Sei Emi , Lin Yiyun , Wang Junke , Montalvan Jessica , Nagi Changandeep , Thompson Alastair M. , Navin Nicholas 
Published: September 2024

AbstractUnderstanding the impact of genetic alterations on epigenomic phenotypes during breast cancer progression is challenging with unimodal measurements. Here, we report wellDA-seq, the first high-genomic resolution, high-throughput method that can simultaneously measure the whole genome and chromatin accessibility profiles of thousands of single cells. Using wellDA-seq, we profiled 22,123 single cells from 2 normal and 9 tumors breast tissues. By directly mapping the epigenomic phenotypes to genetic lineages across cancer subclones, we found evidence of both genetic hardwiring and epigenetic plasticity. In 6 estrogen-receptor positive breast cancers, we directly identified the ancestral cancer cells, and found that their epithelial cell-of-origin was Luminal Hormone Responsive cells. We also identified cell types with copy number aberrations (CNA) in normal breast tissues and discovered non-epithelial cell types in the microenvironment with CNAs in breast cancers. These data provide insights into the complex relationship between genetic alterations and epigenomic phenotypes during breast tumor evolution.
Systemic injection of scopolamine increased the variability of temporal prediction in head-fixed mice
Authors: Ujihara Yusuke , Yamada Kota , Yamamoto Mizuki , Toda Koji 
Published: September 2024

AbstractSeveral theories propose a close relationship between interval timing and the temporal properties of memory. Systemic administration of scopolamine, a muscarinic acetylcholine receptor antagonist, is known to induce memory deficits and impair temporal prediction. However, existing studies on timing using free-moving animals are challenging to interpret due to the confounding effects of movement on interval timing. In this study, we examined the effects of scopolamine on timing behavior in mice using a head-fixed experimental setup. Mice were trained on a fixed-time schedule task with a peak procedure, where a 10% sucrose solution was delivered every 10 seconds through a spout placed within the licking distance of the mice. Following training, the mice exhibited anticipatory licking behavior in response to the timing of sucrose delivery, indicating that they could predict the reward timing. Systemic administration of scopolamine increased the variability of temporal prediction in a dose-dependent manner but did not affect the mean temporal prediction. Single-trial bout analysis revealed that scopolamine impaired the duration of licking bouts without affecting the total number of licks in peak trials, suggesting that the mice were unable to sustain licking at the spout. Additionally, we assessed the effects of scopolamine on spontaneous locomotor activity and excretion in a free-moving open-field task. Scopolamine injections increased locomotor activity and decreased fecal output. Taken together, these findings suggest that the increased variability in timing behavior induced by scopolamine may be attributed to changes in transitions between behavioral states.
EyaHOST, a modular genetic system for investigation of intercellular and tumor-host interactionsin Drosophila melanogaster
Authors: Teles-Reis José , Jain Ashish , Liu Dan , Khezri Rojyar , Micheli Sofia , Gomez Alicia Alfonso , Dillard Caroline , Rusten Tor Erik 
Published: September 2024

AbstractCell biology and genetic analysis of intracellular, intercellular and inter-organ interaction studies in animal models are key for understanding development, physiology, and disease. The MARCM technique can emulate tumor development by simultaneous clonal tumor suppressor loss-of-function generation coupled with GAL4-UAS-driven oncogene and marker expression, but the utility is limited for studying tumor-host interactions due to genetic constraints. To overcome this, we introduce EyaHOST, a novel system that replaces MARCM with the QF2-QUAS binary gene expression system under theeyapromoter control, unleashing the fly community genome-wide GAL4-UAS driven tools to manipulate any host cells or tissue at scale. EyaHOST generates epithelial clones in the eye epithelium similar to MARCM. EyaHOST-driven RasV12oncogene overexpression coupled with scribble tumor suppressor knockdown recapitulates key cancer features, including systemic catabolic switching and organ wasting. We demonstrate effective tissue-specific manipulation of host compartments such as neighbouring epithelial cells, immune cells, fat body, and muscle using fly avatars with tissue-specific GAL4 drivers. Organ-specific inhibition of autophagy or stimulation of growth-signaling through PTEN knockdown in fat body or muscle prevents cachexia-like wasting. Additionally, we show thatRasV12, scribRNAitumors induce caspase-driven apoptosis in the epithelial microenvironment. Inhibition of apoptosis by p35 expression in the microenvironment promotes tumor growth. EyaHOST offers a versatile modular platform for dissecting tumor-host interactions and other mechanisms involving intercellular and inter-organ communication inDrosophila.Highlights*eyes absent, eye disc-specific enhancer drives clonal KD recombinase flip-out activated QF2 expression in the larval eye epithelium for simultaneous QUAS-driven gain and loss-of-function analysis of gene function.*Clones are visualized by QUAS-tagBFP or QUAS-eGFP facilitating analysis of existing fluorescent reporters.*The GAL4-UAS system and existing genome-wide genetic tools are released to independently manipulate any cell population in the animal for cell biology, intercellular or inter-organ analysis for developmental, physiological, or disease model analysis.*Fly avatars for tumor-host interaction studies with multiple organs allow live monitoring and manipulation of tumors and organs in translucent larva.
Targeting CXCR4 with [212Pb/203Pb]-Pentixather Significantly Increases Overall Survival in Small Cell Lung Cancer
Authors: Christensen Keegan A. , Fath Melissa A. , Ewald Jordan T. , Robles-Planells Claudia , Graves Stephen A. , Johnson Spenser S. , Zacharias Zeb R. , Houtman Jon C.D. , O’Dorisio M Sue , Schultz Michael K. , Allen Bryan G. , Furqan Muhammad , Menda Yusuf , Liu Dijie , Spitz Douglas R. 
Published: September 2024

ABSTRACTIntroductionSmall cell lung cancer (SCLC) has a 7% 5-year overall survival. C-X-C chemokine receptor 4 (CXCR4), an attractive target for theranostic agents, is highly expressed in SCLCs, and can be targeted with pentixather using the theranostic pair212Pb/203Pb. The hypothesis that [212Pb/203Pb]-pentixather can be used safely and effectively for imaging and therapy in SCLC in xenograft models was tested.ResultsSPECT/CT imaging and biodistribution studies of tumor bearing mice injected with [203Pb]-pentixather demonstrated CXCR4-dependent uptake in tumors and accumulation of radioligand in kidneys and livers. Dosimetry calculations estimated [212Pb]-pentixather uptake in tumor and normal tissue. [212Pb]-pentixather treatment (37-111 kBq/g) of SCLC xenografts (DMS273 and H69AR) significantly prolonged survival and delayed tumor growth. When NSG mice grafted with human hCD34+ bone marrow were treated with [212Pb]-pentixather (37-111 kBq/g), significant cytopenias were observed in peripheral blood complete blood counts (CBCs) at 13-18 days post treatment which resolved by day 28-31. Flow cytometry of bone marrow hematopeotic stem cells in these animals at day 28-31 demonstrated a significantly reduced frequency of the human hematopoietic marker CD45 (hCD45+) and reconstitution of the bone marrow with murine CD45+ (mCD45+) lineages.Conclusions[203Pb]-pentixather can be used to image CXCR4 expressing SCLC xenografts and treatment with alpha emitter [212Pb]-pentixather significantly prolongs SCLC xenograft median overall survival. Significantly greater mCD45+ bone marrow repopulation was detected in NSG mice engrafted with human bone marrow 28-31 days following [212Pb]-pentixather treatment, relative to hCD45+ bone marrow.
EpipwR: Efficient Power Analysis for EWAS with Continuous Outcomes
Authors: Barth Jackson , Reynolds Austin W. 
Published: September 2024

AbstractMotivationEpigenome-wide association studies (EWAS) have emerged as a popular way to investigate the pathophysiology of complex diseases and to assist in bridging the gap between genotypes and phenotypes. Despite the increasing popularity of EWAS, very few tools exist to aid researchers in power estimation and those are limited to case-control studies. The existence of user-friendly tools, expanding power calculation functionality to additional study designs would be a significant aid to researchers planning EWAS.ResultsWe introduce EpipwR, an open-source R package that can efficiently estimate power for EWAS with continuous outcomes. EpipwR uses a quasi-simulated approach, meaning that data is generated only for CpG sites with methylation associated with the outcome, while p-values are generated directly for those with no association (when necessary). Like existing EWAS power calculators, reference datasets of empirical EWAS are used to guide the data generation process. Two simulation studies show the effect of the selected empirical dataset on the generated correlations and the relative speed of EpipwR compared to similar approaches.Availability and ImplementationThe EpipwR R-package is currently available for download atgithub.com/jbarth216/EpipwR.
Multi-epitope immunocapture of huntingtin reveals striatum-selective molecular signatures
Authors: Justice Joshua L. , Greco Todd M. , Hutton Josiah E. , Reed Tavis J. , Mair Megan L. , Botas Juan , Cristea Ileana M. 
Published: September 2024

AbstractHuntington’s disease (HD) is a debilitating neurodegenerative disorder affecting an individual’s cognitive and motor abilities. HD is caused by mutation in the huntingtin gene producing a toxic polyglutamine-expanded protein (mHTT) and leading to degeneration in the striatum and cortex. Yet, the molecular signatures that underlie tissue-specific vulnerabilities remain unclear. Here, we investigate this aspect by leveraging multi-epitope protein interaction assays, subcellular fractionation, thermal proteome profiling, and genetic modifier assays. Use of human cell, mouse, and fly models afforded capture of distinct subcellular pools of epitope-enriched and tissue-dependent interactions linked to dysregulated cellular pathways and disease relevance. We established an HTT association with nearly all subunits of the transcriptional regulatory Mediator complex (20/26), with preferential enrichment of MED15 in the tail domain. Using HD and KO models, we find HTT modulates the subcellular localization and assembly of Mediator. We demonstrated striatal enriched and functional interactions with regulators of calcium homeostasis and chromatin remodeling, whose disease relevance was supported by HD fly genetic modifiers assays. Altogether, we offer insights into tissue- and localization-dependent (m)HTT functions and pathobiology.
Progress in Developing a Bark Beetle Identification Tool
Authors: Marais G. Christopher , Stratton Isabelle C. , Johnson Andrew J. , Hulcr Jiri 
Published: September 2024

AbstractThis study presents an initial model for bark beetle identification, serving as a foundational step toward developing a fully functional and practical identification tool. Bark beetles are known for extensive damage to forests globally, as well as for uniform and homoplastic morphology which poses identification challenges. Utilizing a MaxViT-based deep learning backbone which utilizes blocked local and dilated global attention to classify bark beetles down to the genus level from images containing multiple beetles. The methodology involves a comprehensive process of image collection, preparation, and model training, leveraging pre-classified beetle species to ensure accuracy and reliability. The model’s F1 score estimates of 0.99 and 1.0 indicates a strong ability to accurately classify genera in the collected data, including those previously unknown to the model. This makes it a valuable first step towards building a tool for applications in forest management and ecological research. While the current model distinguishes among 12 genera, further refinement and additional data will be necessary to achieve reliable species-level identification, which is particularly important for detecting new invasive species. Despite the controlled conditions of image collection and potential challenges in real-world application, this study provides the first model capable of identifying the bark beetle genera, and by far the largest training set of images for any comparable insect group. We also designed a function that reports if a species appears to be unknown. Further research is suggested to enhance the model’s generalization capabilities and scalability, emphasizing the integration of advanced machine learning techniques for improved species classification and the detection of invasive or undescribed species.
Characterising global risk profiles of Mpox clade Ib importation
Authors: Asakura Toshiaki R. , Jung Sung-mok , Jin Shihui , Hu Gang , Endo Akira , Dickens Borame Lee 
Published: September 2024

AbstractThe novel mpox clade Ib initially identified in the Domestic Republic of Congo has spread to its multiple neighbouring countries as well as countries beyond the African continent. We characterised the global risk of importation of mpox clade Ib, highlighting the need to ramp up surveillance capacity for early detection.
Plasma proteome-based test (PROphetNSCLC) predicts response to immune checkpoint inhibitors (ICI) independent of tumor programmed death-ligand 1(PD-L1) expression and tumor mutational burden (TMB)
Authors: Brody Yehuda , Yellin Ben , Sela Itamar , Elon Yehonatan , Puzanov Igor , Nechushtan Hovav , Zerkuch Alona , Gottfried Maya , Katzenelson Rivka , Moskovitz Mor , Levy-Barda Adva , Lotem Michal , Leibowitz Raya , Lou Yanyan , Dicker Adam P. , Gandara David R. , McGregor Kimberly 
Published: September 2024

AbstractDespite the approval of PD-(L)1 inhibitors for the first-line treatment of all metastatic, driver-negative, non-small cell lung cancer patients (mNSCLC) in the United States since 2018, there still is a lack discerning biomarkers to predict which patients will derive significant benefit. Tumor expression of programmed-death ligand 1 (PD-L1), measured as the tumor proportion score (TPS), is a standard biomarker approved for the selection of initial therapy. Tumor mutational burden (TMB), a promising biomarker, thought to represent the tumors’ ability to engage the host’s immune system, has demonstrated clinical utility primarily in the context of immunotherapy monotherapy. PROphetNSCLC, a test developed through proteomic analysis and machine learning, provides a novel approach by capturing biological processes from both tumor and host. In a previously published study, PROphetNSCLC, was validated to correlate with the probability of clinical benefit, independent of but also complementary to PD-L1 expression levels predicting specific treatment-related survival outcomes. Utilizing available tumor TMB measurements from this investigation, we sought to assess the correlation between the PROphetNSCLC clinical benefit probability score and TMB measurement. PROphetNSCLC demonstrated a correlation with various outcomes from PD-(L)1 inhibitor treatment independent of TMB status, whereas TMB did not exhibit an association with outcomes. This finding emphasizes the significance in of novel systemic biomarkers in refining personalized treatment strategies for mNSCLC.
Reconciling heterogeneous dengue virus infection risk estimates from different study designs
Authors: Huang Angkana T. , Buddhari Darunee , Kaewhiran Surachai , Iamsirithaworn Sopon , Khampaen Direk , Farmer Aaron , Fernandez Stefan , Thomas Stephen J. , Rodriguez Barraquer Isabel , Hunsawong Taweewun , Srikiatkhachorn Anon , Ribeiro dos Santos Gabriel , O’Driscoll Megan , Hamins-Puertolas Marco , Endy Timothy , Rothman Alan L. , Cummings Derek A. T. , Anderson Kathryn , Salje Henrik 
Published: September 2024

AbstractUncovering rates at which susceptible individuals become infected with a pathogen, i.e. the force of infection (FOI), is essential for assessing transmission risk and reconstructing distribution of immunity in a population. For dengue, reconstructing exposure and susceptibility statuses from the measured FOI is of particular significance as prior exposure is a strong risk factor for severe disease. FOI can be measured via many study designs. Longitudinal serology are considered gold standard measurements, as they directly track the transition of seronegative individuals to seropositive due to incident infections (seroincidence). Cross-sectional serology can provide estimates of FOI by contrasting seroprevalence across ages. Age of reported cases can also be used to infer FOI. Agreement of these measurements, however, have not been assessed. Using 26 years of data from cohort studies and hospital-attended cases from Kamphaeng Phet province, Thailand, we found FOI estimates from the three sources to be highly inconsistent. Annual FOI estimates from seroincidence was 2.46 to 4.33-times higher than case-derived FOI. Correlation between seroprevalence-derived and case-derived FOI was moderate (correlation coefficient=0.46) and no systematic bias. Through extensive simulations and theoretical analysis, we show that incongruences between methods can result from failing to account for dengue antibody kinetics, assay noise, and heterogeneity in FOI across ages. Extending standard inference models to include these processes reconciled the FOI and susceptibility estimates. Our results highlight the importance of comparing inferences across multiple data types to uncover additional insights not attainable through a single data type/analysis.Significance statementDengue virus infections are surging globally. Knowing who, where, and how many people are at risk of infection is crucial in determining means to protect them. Here, we compare three current approaches in measuring risk (two involving blood samples and one involving case counts) to estimate the risk of infection. Estimates derived from each method differed greatly. By accounting for rise and falls of antibodies following infections, noise in the antibody titer measurements, and heterogeneity in infection risk across ages, we reconciled the measurements. As measurements from blood samples and case counts are pillars in uncovering risk of most infectious diseases, our results signifies integrating these processes into risk measurements of pathogens beyond dengue virus.
Investigation of hemodynamic bulk flow patterns caused by aortic stenosis using a combined 4D Flow MRI-CFD framework
Authors: Wang Tianai , Quast Christine , Bönner Florian , Kelm Malte , Zeus Tobias , Lemainque Teresa , Steinseifer Ulrich , Neidlin Michael 
Published: September 2024

AbstractAortic stenosis (AS) leads to alterations of supra-valvular flow patterns. These patterns might lead to, inter alia, increased damage of red blood cell (RBC) membranes. We investigated these patient specific patterns of a severe AS patient and their reversal in healthy flow through a 4D Flow MRI-based CFD methodology. Computational models of subject-specific aortic geometries were created using in-vivo medical imaging data. Temporally and spatially resolved boundary conditions derived from 4D Flow MRI were implemented for an AS patient and a healthy subject. After validation of the in-silico results with in-vivo data, a healthy inflow profile was set for the AS patient in the CFD model. Pathological versus healthy flow fields were compared regarding their blood flow characteristics, i.e. shear stresses on RBCs and helicity. The accuracy of the 4D Flow MRI-based CFD model was proven with excellent agreement between in-vivo and in-silico velocity fields and R² = 0.9. A pathological high shear stress region in the bulk flow was present during late systole with an increase of 125 % compared to both healthy flow. The physiological bihelical structure with predominantly right-handed helices vanished for the pathological state. Instead, a left-handed helix appeared, accompanied by an overall increase in turbulent kinetic energy in areas of accumulated left-handed helicity.The validated 4D Flow MRI-based CFD model identified marked differences between AS and healthy flow. It suggests that altered turbulent and helical structures in the bulk flow are the cause for increased, potentially damaging forces acting upon RBCs in AS.Author SummaryAortic stenosis (AS) is a condition that alters the flow of blood through the aorta, potentially increasing damage to red blood cells (RBCs). It is therefore crucial to understand the precise nature of these changes, especially in the bulk region where the RBCs are mainly circulating. To investigate this, we developed a computational model based on patient-specific 4D Flow MRI data to simulate blood flow in a patient with severe AS and a healthy individual. Our high-fidelity models show high agreement with real-world data. We then imposed synthetically generated healthy flow conditions in the AS patient to eliminate age- and geometry-related uncertainties. Our results revealed significantly higher shear stresses and changes in helical flow patterns in the AS patient compared to healthy flow, suggesting that these alterations could increase the risk of RBC membrane damage. These findings underscore the importance of deepening our understanding about the interplay between bulk flow alterations and their impact on RBCs, as previous studies were mostly focused on near wall regions. This methodology could also be extended to other cardiovascular conditions, aiding in the development of patient-specific treatment strategies.