bluuebunny/crossref_metadata_2025_split huggingface dataset:
Topology-dependent DNA binding
Authors: Kolbeck Pauline J. , Tišma Miloš , Analikwu Brian T. , Vanderlinden Willem , Dekker Cees , Lipfert Jan 
Published: July 2023

ABSTRACTDNA stores our genetic information and is ubiquitous in biological and biotechnological applications, where it interacts with binding partners ranging from small molecules to large macromolecular complexes. Binding is modulated by mechanical strains in the molecule and, in turn, can change the local DNA structure. Frequently, DNA occurs in closed topological forms where topology and supercoiling add a global constraint to the interplay of binding-induced deformations and strain-modulated binding. Here, we present a quantitative model of how the global constraints introduced by DNA topology modulate binding and create a complex interplay between topology and affinity. We focus on fluorescent intercalators, which unwind DNA and enable direct quantification via fluorescence detection. Using bulk measurements, we show that DNA supercoiling can increase or decrease intercalation relative to an open topology depending on ligand concentration and the initial topology. Our model quantitatively accounts for observations obtained using psoralen for UV-induced DNA crosslinking, which is frequently used to quantify supercoilingin vivo. Finally, we observe topology-dependent binding in a single-molecule assay, which provides direct access to binding kinetics and DNA supercoil dynamics. Our results have broad implications for the detection and quantification of DNA and for the modulation of DNA binding in cellular contexts.
Reverse engineering of a pathogenic antibody reveals the molecular mechanism of vaccine-induced immune thrombotic thrombocytopenia
Authors: Ivanov Daniil G. , Ivetic Nikola , Du Yi , Nguyen Son N. , Le S. Hung , Favre Daniel , Nazy Ishac , Kaltashov Igor A. 
Published: July 2023

AbstractThe massive COVID-19 vaccine roll-out campaign illuminated a range of rare side effects, the most dangerous of which – vaccine-induced immune thrombotic thrombocytopenia (VITT) – is caused by adenoviral (Ad)-vectored vaccines. VITT occurrence had been linked to production of pathogenic antibodies that recognize an endogenous chemokine, platelet factor 4 (PF4). Mass spectrometry (MS)-based evaluation of the ensemble of anti-PF4 antibodies obtained from a VITT patient’s blood indicates that its major component is a monoclonal antibody. Structural characterization of this antibody reveals several unusual characteristics, such as the presence of anN-glycan in the Fab segment and high density of acidic amino acid residues in the CDR regions. A recombinant version of this antibody (RVT1) was generated by transient expression in mammalian cells based on the newly determined sequence. It captures the key properties of VITT antibodies, such as their ability to activate platelets in a PF4-dependent fashion. Homology modeling of the Fab segment reveals a well-defined polyanionic paratope, and the docking studies indicate that the polycationic segment of PF4 readily accommodates two Fab segments, cross-linking the antibodies to yield polymerized immune complexes. Their existence was verified with native MS by detecting assemblies as large as (RVT1)3(PF4)2, pointing out at FcγRIIa-mediated platelet activation as the molecular mechanism underlying VITT clinical manifestations. In addition to high PF4 affinity, RVT1 readily binds other polycationic targets, indicating a polyreactive nature of this antibody. This surprising polyspecificity not only sheds light on VITT etiology, but also opens up a range of opportunities to manage this pathology.Significance StatementVaccine-induced immune thrombotic thrombocytopenia (VITT) is a dangerous side effect of adenoviral-vectored vaccines that is linked to the emergence of autoantibodies recognizing platelet factor 4 (PF4). We have engineered a recombinant VITT antibody by sequencing a VITT patient-derived anti-PF4 monoclonal antibody that causes platelet activation and triggers thrombosis. This antibody was used to characterize architecture of the pathogenic immune complexes with a combination of biophysical and computational approaches, revealing the molecular mechanism of VITT. The results of this work demonstrate the critical role of electrostatics in PF4 recognition by the pathogenic antibody and the polyspecificity of the latter. Availability of the engineered VITT antibody will be invaluable for future studies aiming at understanding the general mechanistic features of autoimmune pathologies.
Inclusion Criteria for Extracorporeal Membrane Oxygenation (ECMO) in Patients with Acute Respiratory Distress Syndrome (ARDS) Due to COVID-19: A Systematic Review
Authors: Triantafyllaki Panagiota , Charalampopoulos Marios , Sampani Christina-Athanasia , Triantafyllou Christos , Papageorgiou Dimitrios 
Published: July 2023

AbstractIntroductionAt the end of 2019, in the city of Wuhan, China, a virus of the family of coronaviruses first appeared, mainly affecting the respiratory system, which was called SARS-COV-2 and causes COVID-19. Although in most patients, it occurs with mild symptomatology, however, a significant percentage (15-30%) will develop acute respiratory distress syndrome (ARDS) with increased chances of intubation and mechanical ventilation. In special cases of severe disease, where the oxygenation of the patient is not improved by the use of the ventilator, extracorporeal membrane oxygenation (ECMO) can be applied, a technique that has been used in previous pandemics that affected the respiratory system.AimTo investigate the evidence of the appliance of the ECMO, based on international literature, of the extracorporeal membrane oxygenator in patients with severe respiratory failure due to Covid-19 disease.MethodArticles were searched on the international bases of scientific studies PubMed, Cochrane Library, and Google Scholar. This review was carried out using meta-analysis and international guidelines.ResultsFour articles were included where there was an agreement on the basic characteristics of patients, which can be considered as selection criteria. The primary criteria indicate the age, where the patient must be under 65 years old, and the body mass index (BMI) should be below 40. In addition, it is very important that there is no serious underlying pathology such as multi-organ failure syndrome. Also, the mechanical ventilation should not exceed seven (7) days until the placement of the ECMO, while all the other therapeutic methods, such as the prone position, neuromuscular blockers, and the appropriate positive end-expiratory pressure of the airways (Positive end-expiratory pressure - PEEP) should be already applied.ConclusionsThe application of ECMO is widely used as a treatment for patients with severe COVID-19 disease. However, in order to have the best therapeutic results while reducing hospitalization costs, it is necessary to follow the guidelines regarding the selection of patients who will benefit substantially.
Assessing Radiotherapy Responses in Low-Risk Prostate Cancer: A Longitudinal Analysis of T2 Relaxation Times
Authors: Hanzlikova Pavla , Vilimek Dominik , Vilimkova Kahankova Radana , Ladrova Martina , Skopelidou Valeria , Ruzickova Zuzana , Martinek Radek , Cvek Jakub 
Published: July 2023

AbstractRationale and ObjectivesTo evaluate short and long-term changes inT2relaxation as a response to radiotherapy in patients with low and intermediate risk localized prostate cancer.Materials and MethodsA total of 24 patients were selected for this retrospective study. Each participant underwent 1.5T magnetic resonance imaging on seven separate occasions: initially after the implantation of gold fiducials, the required step for Cyberknife therapy guidance, followed by MRI scans two weeks post-therapy and monthly thereafter. As part of each MRI scan, the prostate region was manually delineated, and theT2relaxation times were calculated for quantitative analysis. TheT2relaxation times between individual follow-ups were analyzed using Repeated Measures Analysis of Variance.ResultsRepeated Measures Analysis of Variance (RM-ANOVA) revealed a significant difference across all measurements (F (6, 120) = 0.611, p<<0.001). A Bonferroni post hoc test revealed significant differences in medianT2values between the baseline and subsequent measurements, particularly between pre-therapy (M0) and two weeks post-therapy (M1), as well as during the monthly interval checks (M2-M6). Some cases showed a delayed decrease in relaxation times, indicating the prolonged effects of therapy.ConclusionThe changes inT2values during the course of radiotherapy can help in monitoring radiotherapy response in unconfirmed patients, quantifying the scarring process, and recognizing the therapy failure.
A quantitative systems pharmacology workflow towards optimal design and biomarker stratification of atopic dermatitis clinical trials
Authors: Go Natacha , Arsène Simon , Faddeenkov Igor , Galland Théo , Martis B. Shiny , Lefaudeux Diane , Wang Yishu , Etheve Loic , Jacob Evgueni , Monteiro Claudio , Bosley Jim , Sansone Caterina , Pasquali Christian , Lehr Lorenz , Kulesza Alexander 
Published: July 2023

AbstractBackgroundThe development of atopic dermatitis (AD) drugs is confronted by many disease phenotypes and trial design options, which are hard to explore experimentally.ObjectiveOptimize AD trial design using simulations.MethodsWe constructed a quantitative systems pharmacology (QSP) model of AD and standard of care (SoC) treatments and generated a phenotypically diverse virtual population whose parameter distribution is derived from known relationships between AD biomarkers and disease severity and b) calibrated using disease severity evolution under SoC regimens.ResultsWe applied this workflow to the immunomodulator OM-85, currently being investigated for its potential use in AD, and calibrated investigational treatment model with the efficacy profile of an existing trial (thereby enriching it with plausible marker levels and dynamics). We assessed the sensitivity of trial outcomes to trial protocol and found that for this particular example, a) the choice of endpoint is more important than the choice of dosing-regimen and b) patient selection by model-based responder enrichment could increase the expected effect size. A global sensitivity analysis reveals that only a limited subset of baseline biomarkers is needed to predict the drug response of the full virtual populationConclusionThis AD QSP workflow built around knowledge of marker-severity relationships as well as SoC efficacy can be tailored to specific development cases so as to optimize several trial protocol parameters and biomarker-stratificaiton and therefore holds promise to become a powerful model-informed drug development tool.Key MessagesDisease and treatment models can quantify pre-existing knowledge about complex immune diseases such as atopic dermatitis and drug’s efficacy data under one common umbrella.Embedding QSP models into trial simulation setup can give insight into clinical trial optimization.Complex QSP models can help with patient selection and biomarker identification.Capsule SummaryThis study shows the relevance of QSP model and computer simulations in assisting clinical development in the field of atopic dermatitis by assessing the impact of trial protocol on treatment effect and guiding biomarker programs.
Assessing above and belowground recovery from ammonium sulfate addition and wildfire in a lowland heath: mycorrhizal fungi as potential indicators
Authors: Kowal Jill , Pino-Bodas Raquel , Arrigoni Elena , Delhaye Guillaume , Suz Laura M. , Duckett Jeffrey G. , Bidartondo Martin I. , Pressel Silvia 
Published: July 2023

ABSTRACTAtmospheric pollution containing soil-nitrifying ammonium sulphate is affecting semi-natural ecosystems worldwide. Long-term additions of ammonium sulphate on nitrogen (N)-limited habitats such as heathlands increase climate stress affecting recovery from wildfires. Yet although heathland vegetation largely depends on ericoid mycorrhizal fungi (ErM) to access soil N, we lack a detailed understanding of how prolonged exposure to ammonium sulphate may alter ErM community composition and host plants’ reliance on fungal partners following wildfire and substantial reductions in ammonium sulphate pollution. Effects on ecosystem processes, particularly carbon stores, also remain uncertain. Ammonium sulphate additions occurred bi-weekly for five years after a 2006 wildfire burnt a UK heathland. Ten years after the treatments ceased (2021), we measured vegetation structure, lichen and lichen photobiont composition, soil characteristics, ErM colonisation, ErM diversity in roots and soil, and assessed their potential as recovery indicators. We found heather height and density, and moss groundcover, were greater in N-enriched plots. Lichen community indices showed significant treatment effects without photobiont differences. Soil pH and Mg, and the proportion of putative ErM fungi in soil were significantly lower in treated plots while soil cation exchange capacity was significantly higher. Increases in soil pH were positively correlated to soil ErM abundance. Soil carbon stock measures were variable and negatively related with soil ErM. Our results indicate that atmospheric pollution following fire can have significant lingering effects and mycorrhizal fungi diversity are a novel and effective ecological tool to assess ecosystem recovery on heathlands.IMPLICATIONS FOR PRACTICERecovery of heathlands from wildfire and atmospheric pollution may require decadal scales. Conventional restoration assessment tools lack critical understanding of belowground soil and mycorrhizal fungi interactions and nutritional feedback loops with aboveground hosts.Given that ericoid mycorrhizal fungi (ErM) communities are key nutrient regulators of resilient heathlands, we recommend baseline measurements of ErM diversity and abundance in both soil and dominant plant roots be added to the recovery assessment toolkit prior to commencing restoration or management plans.What defines ErM recovery, and disentangling effects of ammonium sulphate pollution and fire, remain open questions which only long-term field experiments across pollution gradients will address.
Uncovering the regulatory landscape of early human B-cell lymphopoiesis and its implications in the pathogenesis of B-cell acute lymphoblastic leukemia
Authors: Planell Núria , Martínez-de-Morentin Xabier , Mouzo Daniel , Lara-Astiaso David , Vilas-Zornoza Amaia , Martín-Uriz Patxi San , Alignani Diego , Paiva Bruno , Maillo Alberto , Kurowska Aleksandra , Berastegui Nerea , Garcia-Olloqui Paula , Urdangarin Arantxa , Noori Peri , Ortega-Legarreta Asier , Hernaez Mikel , Lagani Vincenzo , Kiani Narsis , Merkenschlager Matthias , Ezponda Teresa , Martín-Subero José I. , Ramírez Ricardo N. , Tegner Jesper , Prosper Felipe , Gomez-Cabrero David 
Published: July 2023

ABSTRACTDysregulation of the early stages of B-cell lymphopoiesis, orchestrating the development of cellular immunity, may induce malignant transformations. Therefore, it is essential to characterize the gene regulatory network (GRN) driving B-cell lymphopoiesis in healthy individuals to uncover malignancy mechanisms. To this end, we generated a dataset that included paired human data for chromatin accessibility and gene expression in eight B-cell precursor stages, providing the first deep characterization of early B-cell lymphopoiesis, including the identification of regulatory elements and the reconstruction of the GRN. Using this data, we recapitulated well-known regulatory elements and revealed new regulons, such as ELK3, enriched in pro-B cells with a putative role in cell cycle progression. Moreover, a single-cell multi-omics analysis validated and enhanced the resolution of the regulatory landscape recovered by bulk data, revealing MYBL2 and ZNF367 as specific regulons of cycling cell states, and CEBPA associated with lymphoid multipotent progenitors (LMPPs). Importantly, this dataset enabled us to uncover B-cell acute lymphoblastic leukemia (B-ALL) triggers. We identified different cellular origins of malignant transformation depending on the B-ALL subtype, including the association of the ETV6-RUNX1 with pro-B cells and the increased expression ofELK3in this ALL subtype. Overall, our dataset provides the most comprehensive atlas to date of early human B-cell regulation (B-rex;https://translationalbio.shinyapps.io/brex/), facilitating further understanding of B-cell differentiation in health and disease.
KRAS-mediated upregulation of CIP2A promotes suppression of PP2A-B56α to initiate pancreatic cancer development
Authors: Tinsley Samantha L. , Shelley Rebecca A. , Mall Gaganpreet K. , Chianis Ella Rose D. , Dhiman Alisha , Baral Garima , Kothandaraman Harish , Thoma Mary C. , Daniel Colin J. , Lanman Nadia Atallah , Pasca di Magliano Marina , Narla Goutham , Solorio Luis , Dykhuizen Emily C. , Sears Rosalie C. , Allen-Petersen Brittany L. 
Published: July 2023

ABSTRACTOncogenic mutations in KRAS are present in approximately 95% of patients diagnosed with pancreatic ductal adenocarcinoma (PDAC) and are considered the initiating event of pancreatic intraepithelial neoplasia (PanIN) precursor lesions. While it is well established that KRAS mutations drive the activation of oncogenic kinase cascades during pancreatic oncogenesis, the effects of oncogenic KRAS signaling on regulation of phosphatases during this process is not fully appreciated. Protein Phosphatase 2A (PP2A) has been implicated in suppressing KRAS-driven cellular transformation. However, low PP2A activity is observed in PDAC cells compared to non-transformed cells, suggesting that suppression of PP2A activity is an important step in the overall development of PDAC. In the current study, we demonstrate that KRASG12Dinduces the expression of both an endogenous inhibitor of PP2A activity, Cancerous Inhibitor of PP2A (CIP2A), and the PP2A substrate, c-MYC. Consistent with these findings, KRASG12Dsequestered the specific PP2A subunit responsible for c-MYC degradation, B56α, away from the active PP2A holoenzyme in a CIP2A-dependent manner. During PDAC initiationin vivo, knockout of B56α promoted KRASG12Dtumorigenesis by accelerating acinar-to-ductal metaplasia (ADM) and the formation of PanIN lesions. The process of ADM was attenuatedex vivoin response to pharmacological re-activation of PP2A utilizing direct small molecule activators of PP2A (SMAPs). Together, our results suggest that suppression of PP2A-B56α through KRAS signaling can promote the MYC-driven initiation of pancreatic tumorigenesis.
Imaging proteins sensitive to direct fusions using transient peptide-peptide interactions
Authors: Gidden Zoe , Oi Curran , Johnston Emily , Bhaskar Haresh , Rosser Susan , Mochrie Simon G. J. , Horrocks Mathew H. , Regan Lynne 
Published: July 2023

ABSTRACTFluorescence microscopy enables specific visualization of proteins in living cells and has played an important role in our understanding of protein subcellular location and function. Some proteins, however, show altered localization and/or function when labeled using direct fusions to fluorescent proteins, making them difficult to study in live cells. Additionally, the resolution of fluorescence microscopy is limited to ∼200 nm, which is two orders of magnitude larger than the size of most proteins. To circumvent these challenges, we previously developed LIVE-PAINT, a live-cell super-resolution approach that takes advantage of short interacting peptides to transiently bind a fluorescent protein to the protein-of-interest. Here, we successfully use LIVE-PAINT to image yeast membrane proteins that do not tolerate the direct fusion of a fluorescent protein by using peptide tags as short as 5-residues. We also demonstrate that it is possible to resolve multiple proteins at the nanoscale concurrently using orthogonal peptide interaction pairs.FOR TABLE OF CONTENTS ONLY
A Serum- and Feeder-Free System to Generate CD4 and Regulatory T Cells from Human iPSCs
Authors: Fong Helen , Mendel Matthew , Jascur John , Najmi Laeya , Kim Ken , Lew Garrett , Garimalla Swetha , Schock Suruchi , Hu Jing , Villegas Andres , Conway Anthony , Fontenot Jason D. , Zompi Simona 
Published: July 2023

AbstractiPSCs can serve as a renewable source of a consistent edited cell product, overcoming limitations of primary cells. While feeder-free generation of clinical grade iPSC-derived CD8 T cells has been achieved, differentiation of iPSC-derived CD4sp and regulatory T cells requires mouse stromal cells in an artificial thymic organoid. Here we report a serum- and feeder-free differentiation process suitable for large-scale production. Using an optimized concentration of PMA/Ionomycin, we generated iPSC-CD4sp T cells at high efficiency and converted them to Tregs using TGFβ and ATRA. Using genetic engineering, we demonstrated high, non-viral, targeted integration of an HLA-A2 CAR in iPSCs. iPSC-Tregs +/- HLA-A2-targeted CAR phenotypically, transcriptionally and functionally resemble primary Tregs and suppress T cell proliferationin vitro. Our work is the first to demonstrate an iPSC-based platform amenable to manufacturing CD4 T cells to complement iPSC-CD8 oncology products and functional iPSC-Tregs to deliver Treg cell therapies at scale.
Fusion of Electronic Health Records and Radiographic Images for a Multimodal Deep Learning Prediction Model of Atypical Femur Fractures
Authors: Schilcher Jörg , Nilsson Alva , Andlid Oliver , Eklund Anders 
Published: July 2023

AbstractAtypical femur fractures (AFF) represent a very rare type of fracture that can be difficult to discriminate radiologically from normal femur fractures (NFF). AFFs are associated with drugs that are administered to prevent osteoporosis-related fragility fractures, which are highly prevalent in the elderly population. Given that these fractures are rare and the radiologic changes are subtle currently only 7% of AFFs are correctly identified, which hinders adequate treatment for most patients with AFF. Deep learning models could be trained to classify automatically a fracture as AFF or NFF, thereby assisting radiologists in detecting these rare fractures. Historically, for this classification task, only imaging data have been used, using convolutional neural networks (CNN) or vision transformers applied to radiographs. However, to mimic situations in which all available data are used to arrive at a diagnosis, we adopted an approach of deep learning that is based on the integration of image data and tabular data (from electronic health records) for 159 patients with AFF and 914 patients with NFF. We hypothesized that the combinatorial data, compiled from all the radiology departments of 72 hospitals in Sweden and the Swedish National Patient Register, would improve classification accuracy, as compared to using only one modality. At the patient level, the area under the ROC curve (AUC) increased from 0.966 to 0.987 when using the integrated set of imaging data and seven pre-selected variables, as compared to only using imaging data. More importantly, the sensitivity increased from 0.796 to 0.903. We found a greater impact of data fusion when only a randomly selected subset of available images was used to make the image and tabular data more balanced for each patient. The AUC then increased from 0.949 to 0.984, and the sensitivity increased from 0.727 to 0.849. These AUC improvements are not large, mainly because of the already excellent performance of the CNN (AUC of 0.966) when only images are used. However, the improvement is clinically highly relevant considering the importance of accuracy in medical diagnostics. We expect an even greater effect when imaging data from a clinical workflow, comprising a more diverse set of diagnostic images, are used.