bluuebunny/crossref_metadata_2025_split huggingface dataset:
Alpha Cell Theory: Modeling Self-Assembly and Dynamic Processes in Living Systems
Authors: Gruhlke Martin C.H. 
Published: November 2024

AbstractUnderstanding and describing the dynamic processes within living systems is a complex and fundamental challenge. This article presents a novel mathematical model that explores the self-assembly and dynamic behaviors observed in living systems. The model integrates complex chemical reactions, self-organization, and energy transfer processes. Key features of the model include the interaction of various molecular species (A, B, C, D, E, F, G, H, I, and K) and the self-assembly of G-structures within a dynamic environment. Furthermore, the model introduces the concept of Alpha Cell decay when a certain threshold is reached, enhancing the dynamic nature of the system. This research provides insights into the potential underlying mechanisms of life processes and their mathematical representations. It opens the door to a deeper understanding of complex, dynamic, and self-organizing systems in the context of living organisms. The model presented here serves as a valuable tool for further exploration of emergent behaviors and complex dynamics in living systems.
EEMtoolbox: A user-friendly R package for flexible ensemble ecosystem modeling
Authors: Pascal Luz Valerie , Vollert Sarah A. , Bimler Malyon D. , Baker Christopher M. , Vernet Maude , Canessa Stefano , Drovandi Christopher , Adams Matthew P. 
Published: November 2024

AbstractForecasting ecosystem changes due to disturbances or conservation interventions is essential to improve ecosystem management and anticipate unintended consequences of conservation decisions. Mathematical models allow practitioners to understand the potential effects and unintended consequences via simulation. However, calibrating these models is often challenging due to a paucity of appropriate ecological data.Ensemble ecosystem modelling (EEM) is a quantitative method used to parameterize models from theoretical ecosystem features rather than data. Two approaches have been considered to find parameter values satisfying those features: a standard accept-reject algorithm, appropriate for small ecosystem networks; and a sequential Monte Carlo (SMC) algorithm, that is more computationally efficient for larger networks. In practice, using SMC for EEM generation requires advanced statistical and mathematical knowledge, as well as strong programming skills, which might limit its uptake. In addition, current EEM approaches have been developed for only one model structure (generalized Lotka-Volterra).To facilitate the usage of EEM methods we introduce EEMtoolbox, an R package for calibrating quantitative ecosystem models. Our package allows the generation of parameter sets satisfying ecosystem features, by using either the standard accept-reject algorithm or the novel SMC procedure. Our package extends the existing EEM methodology, originally developed for the generalized Lotka-Volterra model, to two additional model structures (the multi-species Gompertz, and the Bimler-Baker model), and additionally allows users to define their own model structures.We demonstrate the usage of EEMtoolbox by modelling the introduction of sihek (extinct-in-the-wild) on Palmyra Atoll in the Pacific Ocean. With its simple interface, our package facilitates straightforward generation of EEM parameter sets, thus unlocks advanced statistical methods supporting conservation decisions using ecosystem network models.
AistSeq: An In-House Tn5-Based Plasmid Sequencing Platform Using A Compact Benchtop Sequencer
Authors: Suzuki Hayato , Romsuk Jutapat , Nakamura Akiyoshi , Moriwaki Kosuke , Sugano Shigeo S. 
Published: November 2024

AbstractSequence verification of plasmids is a fundamental process in synthetic biology. For plasmid sequence verification using next-generation sequencing (NGS) library preparation, Tn5 transposase is widely used. Streamlined sequencing workflow for laboratory-scale applications is important; however, recombinant Tn5 productionin-housecan be laborious. In this study, we demonstrated that the addition of a large soluble tag was not essential for purification and that the fusion of a His10 tag and protein A was sufficient to purify sufficient amounts of active Tn5 transposase. In addition, we evaluated exonuclease-based genomic DNA digestion for plasmid sequencing from anE. colilysate and the data analysis pipeline of sequences derived from the Illumina iSeq100 platform forde novoassembly, reference mapping, and annotation. This study proposes a simple workflow ofan in-houseTn5-based plasmidSequencing platform using a compact benchtop sequencer (AistSeq).Graphical abstract
Effect of heme oxygenase-1 on the expression of interferon-stimulated genes
Authors: Chudy Patryk , Bednarczyk Katarzyna , Chatian Eryk , Krzeptowski Wojciech , Szade Agata , Szade Krzysztof , Żukowska Monika , Wolnik Jan , Sokołowski Grzegorz , Józkowicz Alicja , Nowak Witold N. 
Published: November 2024

AbstractHeme oxygenase-1 (HO1,Hmox1) degrades excess heme and is considered an anti-oxidative and anti-inflammatory enzyme. Our previous studies inHmox1knockout mice revealed induction of interferon-stimulated genes (ISGs) in all cell types analyzed, despite unchanged interferon production. Here, we sought to identify the pathway underlying HO1-dependent ISG regulation and determine how ISG expression changes in cultured cells in response to stressors typical ofHmox1-deficient mice.Using murine wild-type andHmox1-deficient (KO-Hmox1) fibroblasts, we showed that in cells cultured under control conditions, the expression of most of the tested ISGs was independent of cellular HO1 status. We then analyzed the effect of extrinsic stressors: hemolytic, oxidative, genotoxic, and replication stress, proinflammatory TNFα, and endogenous heme overload. TNFα (upregulated inHmox1knockout mice) was the sole and universal ISG inducer in both wild-type and KO-Hmox1 fibroblasts. Unexpectedly, the response of KO-Hmox1 cells to exogenous TNFα was weakened, probably due to impaired NF-κB activity and reduced p65 nuclear retention. A similar decrease we observed for STAT1. Additionally, the presence of TREX1 exonuclease in the nucleus indicated impaired nuclear envelope integrity. Noteworthy, HO1 colocalizes with PARP1, a protein regulating cytoplasmic-nuclear transport. Olaparib-mediated PARP1 inhibition abolished TNAα-induced nuclear accumulation of p65 and STAT1 in wild-type cells, but not in KO-Hmox1 counterparts.In summary, the inflammation typical ofHmox1-deficient mice appears to be a major inducer of ISGsin vivo. Despite this, the inflammatory response to exogenous TNFα is attenuated in KO-Hmox1 cells, likely due to decreased nuclear retention of NF-κB and STAT1.
Biosynth Pipeline: An integrated platform for merging the computational design of chimeric type I polyketide synthases with enzymatic pathways for chemical biosynthesis
Authors: Chainani Yash , Diaz Jacob , Guilarte-Silva Margaret , Blay Vincent , Tyo Keith E. J. , Broadbelt Linda J. , Mukhopadhyay Aindrila , Keasling Jay D. , Martin Hector Garcia , Backman Tyler W. H. 
Published: November 2024

AbstractSynthetic biology offers the promise of manufacturing chemicals sustainably than petrochemistry. Yet, both the rate at which biomanufacturing synthesize these molecules and the net chemical accessible space limited by existing pathway discovery methods which rely arduous literature searches. Here, present automated retrobiosynthesis tool, Biosynth Pipeline, that simultaneously tackles both problems by integrating multifunctional type I polyketide synthases (PKSs) with monofunctional enzymes to propose the synthesis of desired target chemicals via two tools: DORAnet and RetroTide. While monofunctional enzymes valuable for carefully decorating substrate’s carbon backbone, they typically cannot expand the backbone itself. PKSs can, instead, predictably do this through their unique ability to catalyze carbon-carbon bond formation reactions iteratively. We evaluated the performance of Biosynth Pipeline against previously published set of 155 molecules of interest for biomanufacturing, and report that Biosynth Pipeline could produce exact designs for 93 of them, well pipelines to chemically similar product for most of the remaining molecules. Furthermore, Biosynth Pipeline successfully proposes biosynthetic routes for complex therapeutic natural products (cryptofolione and basidalin) for which no known biosynthetic pathway currently exists.
A cross-study transcriptional patient map of heart failure defines conserved multicellular coordination in cardiac remodeling
Authors: Lanzer Jan D. , Ramirez Flores Ricardo O. , Liñares Blanco José , Saez-Rodriguez Julio 
Published: November 2024

AbstractHeart failure (HF) is characterized by severely reduced cardiac function and tissue remodeling, driven by complex multicellular regulatory processes. Extensive studies have generated molecular profiles at both bulk and single-cell levels; however, systematic integration that describes tissue-wide changes as a function of cell type coordination remains challenging. This disconnect hampers our understanding of the complex multicellular interactions driving heart failure, limiting our ability to translate molecular insights into actionable therapeutic strategies. Here, we integrated bulk and single-cell transcriptional profiles from cardiac tissues of HF and control patients across 25 studies, covering 1,524 individuals and seven cell-types, to delineate consensus multicellular transcriptional changes associated with cardiac remodeling. Our analyses revealed conserved cellular coordination events involving fibrotic, metabolic, inflammatory, and hypertrophic mechanisms, with fibroblasts playing a central role in predicting cardiomyocyte stress. Further analysis of fibroblast populations suggested that their activation in HF represents a broad phenotypic shift rather than solely accumulating distinct cell states. The integration of bulk and single-cell data within our data collection indicated that transcriptional responses to HF across cell types occur independently of tissue composition. Mapping independent data into our consensus programs demonstrated that recovery after left ventricular assist device implantation aligns with molecular recovery, highlighting the clinical relevance of the multicellular molecular state. Overall, our work synthesizes independent cardiac transcriptomics studies and makes the conserved HF associated insights available, establishing a reference for detailed exploration of HF-related multicellular molecular events.Graphical Abstract
mcBERT: Patient-Level Single-cell Transcriptomics Data Representation
Authors: Querfurth Benedikt von , Lohmöller Johannes , Pennekamp Jan , Bleckwehl Tore , Kramann Rafael , Wehrle Klaus , Hayat Sikander 
Published: November 2024

AbstractSingle-cell RNA sequencing (scRNA-seq) transcriptomics improves our understanding of cellular heterogeneity in healthy and pathological states. However, most scRNA-seq analyses remain confined to single cells or distinct cell populations, limiting their clinical applicability. Addressing the need to translate single-cell insights into a patient-level disease understanding, we introduce mcBERT, a new method that leverages scRNA-seq data and a transformer-based model to generate integrative patient representations using a self-supervised learning phase followed by contrastive learning to refine these representations. Our evaluations of mcBERT across 7 million cells from 1223 individuals encompassing diverse disease states in heart, kidney, blood cell, and lung tissues show that learned representations facilitate a robust identification of disease cohorts and enable comparisons of patient similarity. Moreover, our findings indicate that mcBERT can accurately classify disease phenotypes, also in previously unseen biospecimens and patients. Independent of the specific tissue, mcBERT extends the utility of scRNA-seq data from cellular analysis to potentially actionable patient-centric applications.
Towards a standardised method for the characterisation and isolation of colorectal cancer stem cells by SdFFF and UHF-DEP: highlighted by transcriptomic analysis
Authors: Jemfer Charlotte , Blasco Nina , Durand Stéphanie , Blin Elisa , Mas Robin , Basly Isabelle , Boutaud Marie , Daverat Héloïse , Pothier Arnaud , Dalmay Claire , Mathonnet Muriel , Begaud Gaelle , Battu Serge 
Published: November 2024

AbstractCancer stem cells (CSCs) play a crucial role in tumor heterogeneity and the progression of colorectal cancer (CRC). However, identifying and isolating CSCs remains challenging, as conventional methods, such as fluorescent or magnetic labeling, are time-consuming and require substantial technical and biological resources, limiting their clinical applicability. In this study, we evaluated the potential application of a previously established approach with glioma cells, combining sedimentation field-flow fractionation (SdFFF) with a label-free Ultra-High Frequency dielectrophoresis (UHF-DEP) biosensor, for isolating and identifying CRC CSC. The integration of the UHF-DEP biosensor with SdFFF enables the identification of CSCs without specific labeling, simplifying their analysis. To optimize this coupling, we standardized the mobile phase between the two technologies. Producing two CSC sub-populations eluted in Fraction 1 and Fraction 3. For the first time, transcriptomic analysis was employed to deepen our understanding of the genetic composition of the cells, complementing functional and phenotypic characterizations. From these characteristics, it emerged that F1 cells corresponded to precursors, while F3 cells could be considered CSC. The UHF-DEP biosensor demonstrated its ability to detect these differences, linking F3 to cells cultivated in defined medium (DM), used as a reference standard. Finally, transcriptomic analysis (RNA-seq) has deepened our understanding of the genetic profiles of these subpopulations, enriching the interpretation of their characteristics as CSCs. This in-depth approach will also contribute to a better understanding of the results obtained by the UHF-DEP biosensor.
Holotomographic microscopy reveals label-free quantitative dynamics of endothelial cells during endothelialization
Authors: Leineweber William D. , Munares Gabriela Acevedo , Leycam Christian , Noyer Juliette , Jurney Patrick 
Published: November 2024

AbstractHolotomograhic microscopy (HTM) has emerged as a non-invasive imaging technique that offers high-resolution, quantitative 3D imaging of biological samples. This study explores the application of HTM in examining endothelial cells (ECs). HTM overcomes the limitations of traditional microscopy methods in capturing the real-time dynamics of ECs by leveraging the refractive index (RI) to map 3D distributions label-free. This work demonstrates the utility of HTM in visualizing key cellular processes during endothelialization, wherein ECs anchor, adhere, migrate, and proliferate. Leveraging the high resolution and quantitative power of HTM, we show that lipid droplets and mitochondria are readily visualized, enabling more comprehensive studies on their respective roles during endothelialization. The study highlights how HTM can uncover novel insights into EC behavior, offering potential applications in medical diagnostics and research, particularly in developing treatments for cardiovascular diseases. This advanced imaging technique not only enhances our understanding of EC biology but also presents a significant step forward in the study of cardiovascular diseases, providing a robust platform for future research and therapeutic development.
Hallmarks of uterine receptivity predate placental mammals
Authors: Basanta Silvia , Stadtmauer Daniel J. , Maziarz Jamie D. , McDonough-Goldstein Caitlin E. , Cole Alison G. , Dagdas Gülay , Wagner° Günter P. , Pavličev Mihaela 
Published: November 2024

AbstractEmbryo implantation requires tightly coordinated signaling between the blastocyst and the endometrium, and is crucial for the establishment of a uteroplacental unit that persists until term in eutherian mammals. In contrast, marsupials, with a unique life cycle and short gestation, make only brief fetal-maternal contact and lack implantation. To better understand the evolutionary link between eutherian implantation and its ancestral equivalent in marsupials, we compare single-cell transcriptomes from the receptive and non-receptive endometrium of the mouse and guinea pig with that of the opossum, a marsupial. We identify substantial differences between rodent peri-implantation endometrium and opossum placental attachment, including differences in the diversity and abundance of stromal and epithelial cells which parallel the difference between histotrophic and hemotrophic provisioning strategies. We also identify a window of conserved epithelial gene expression between the opossum shelled blastocyst stage and rodent peri-implantation, includingIHHandLIF. We find strong conservation of blastocyst proteases, steroid synthetases, Wnt and BMP signals between eutherians and the opossum despite its lack of implantation. Finally, we show that the signaling repertoire of the maternal uterine epithelium during implantation displays substantial overlap with that of the post-implantation placental trophoblast, suggesting that the fetal trophoblast can compensate for the loss of endometrial epithelium in eutherian invasive placentation. Together, our results suggest that eutherian implantation primarily involved the re-wiring of maternal signaling networks, some of which were already present in the therian ancestor, and points towards an essential role of maternal innovations in the evolution of invasive placentation.
Tenascin-C potentiates Wnt signaling in thyroid cancer
Authors: Hartmann Heather A. , Loberg Matthew A. , Xu George J. , Schwarzkopf Anna C. , Chen Sheau-Chiann , Phifer Courtney J. , Caroland Kailey , Chen Hua-Chang , Diaz Diana , Tigue Megan L. , Hesterberg Amanda B. , Gallant Jean-Nicolas , Shaddy Sophia M. , Sheng Quanhu , Netterville James L. , Rohde Sarah L. , Solórzano Carmen C. , Bischoff Lindsay A. , Baregamian Naira , Hurley Paula J. , Murphy Barbara A. , Choe Jennifer H. , Huang Eric C. , Ye Fei , Lee Ethan , Weiss Vivian L. 
Published: November 2024

AbstractTenascin-C (TNC) is a secreted extracellular matrix protein that is highly expressed during embryonic development and re-expressed during wound healing, inflammation, and neoplasia. Studies in developmental models suggest that TNC may regulate the Wnt signaling pathway. Our lab has shown high levels of Wnt signaling and TNC expression in anaplastic thyroid cancer (ATC), a highly lethal cancer with an abysmal ∼3-5 month median survival. Here, we investigated the role of TNC in facilitating ligand-dependent Wnt signaling in thyroid cancer. We utilized bulk RNA-sequencing from three independent multi-institutional thyroid cancer patient cohorts. TNC expression was spatially localized in patient tumors with RNA in situ hybridization. The role of TNC was investigated in vitro using Wnt reporter assays and in vivo with a NOD.PrkdcscidIl2rg-/- mouse ATC xenograft tumor model. TNC expression was associated with aggressive thyroid cancer behavior, including anaplastic histology, extrathyroidal extension, and metastasis. Spatial localization of TNC in patient tissue demonstrated a dramatic increase in expression within cancer cells along the invasive edge, adjacent to Wnt ligand-producing fibroblasts. TNC expression was also increased in areas of intravascular invasion. In vitro, TNC bound Wnt ligands and potentiated Wnt signaling. Finally, in an ATC mouse model, TNC increased Wnt signaling, tumor burden, invasion, and metastasis. Altogether, TNC potentiated ligand driven Wnt signaling and promotes cancer cell invasion and metastasis in a mouse model of thyroid cancer. Understanding the role of TNC and its interaction with Wnt ligands could lead to the development of novel biomarkers and targeted therapeutics for thyroid cancer.
Discovering and exploiting active sensing motifs for estimation with empirical observability
Authors: Cellini Benjamin , Boyacıoğlu Burak , Stupski Stanley David , van Breugel Floris 
Published: November 2024

ABSTRACTOrganisms and machines must use measured sensory cues to estimate unknown information about themselves or their environment. Cleverly applied sensor motion can be exploited to enrich the quality of sensory data and improve estimation. However, a major barrier to modeling such active sensing problems is the lack of empirical, yet rigorous, tools for quantifying the relationship between movement and estimation performance. Here, we introduce “BOUNDS: Bounding Observability for Uncertain Nonlinear Dynamic Systems”. BOUNDS can discover patterns of sensor motion that increase information and reduce uncertainty in either real or simulated data. Crucially, it is suitable for high dimensional and partially observable nonlinear systems with sensor noise. We demonstrate BOUNDS through a case study on how flying insects estimate wind properties, showing that specific active sensing motifs improve estimation. Additionally, we present a framework to refine sporadic estimates from active sensing. When combined with an artificial neural network, we show that the information gained via active sensing in realDrosophilaflight trajectories is suitable for precise wind direction estimation. Collectively, our work will help decode active sensing in organisms and inform the design of estimation algorithms for machines.
Protein sequencing with single amino acid resolution discerns peptides that discriminate tropomyosin proteoforms
Authors: Sittipongpittaya Natchanon , Skinner Kenneth A. , Jeffery Erin D. , Watts Emily F. , Sheynkman Gloria M. 
Published: November 2024

AbstractProtein variants of the same gene—proteoforms—can have high molecular similarity yet exhibit different biological functions. Thus, identifying unique peptides that unambiguously map to proteoforms can provide crucial biological insights. In humans, four human tropomyosin (TPM) genes produce similar proteoforms that can be challenging to distinguish with standard proteomics tools. For example, TPM1 and TPM2 share 85% sequence identity, with amino acid substitutions that play unique roles in muscle contraction and myopathies. In this study, we evaluated the ability of the recently released Platinum single-molecule protein sequencer to detect proteoform-informative peptides. Platinum employs fluorophore-labeled recognizers that reversibly bind to cognate N-terminal amino acids (NAAs), enabling polypeptide sequencing within nanoscale apertures of a semiconductor chip that can accommodate single peptide molecules. As a proof of concept, we evaluated the ability of Platinum to distinguish three main types of proteoform variation: paralog-level, transcript-level, and post-translational modification (PTM). We distinguished paralogous TPM1 and TPM2 peptides differing by a single isobaric residue (leucine/isoleucine). We also distinguished tissue-specific TPM2 spliceforms. Notably, we found that a phosphotyrosine-modified peptide displayed reduced recognizer affinity for tyrosine, showing sensitivity to PTMs. This study paves the way for the targeted detection of proteoform biomarkers at the single molecule level.Abstract Figure