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Loading Density Influences the Tumor Cell Targeting and Signaling Inhibition Capabilities of Antibody Nanoconjugates
No full textThis publication is licensed under CC-BY 4.0 https://creativecommons.org/licenses/by/4.0/
© 2026 The Authors. Published by American Chemical Society
This article was originally published in ACS Omega. The version of record is available at:https://doi.org/10.1021/acsomega.5c13065Triple-negative breast cancer (TNBC) is the most aggressive breast cancer subtype and accounts for up to 20% of all breast cancers. Since conventional chemotherapy and radiotherapy are ineffective against TNBC, nanoparticle-based medicines are being investigated as a potentially superior treatment option. Of such platforms, antibody–nanoparticle conjugates have been shown to precisely target diseased cells through selective antigen binding and to regulate oncogenic cellular signaling by blocking ligand activation of the targeted receptor. For example, silica core-gold shell “nanoshells” (NS) conjugated to Frizzled7 (FZD7) antibodies can preferentially bind TNBC cells to suppress Wnt signaling and inhibit disease progression. To improve understanding of antibody nanoconjugate structure/function relationships, in this study, we evaluated the influence of antibody loading density on the ability of FZD7-NS conjugates to bind TNBC cells, suppress Wnt signaling, and inhibit oncogenic cell behavior. We found that a lower antibody loading density of ∼60 antibodies per NS provided increased TNBC cellular binding and enhanced therapeutic efficacy compared to a higher antibody loading of ∼170 antibodies per NS. Specifically, the low-density FZD7-NS exhibited ∼2× greater binding avidity to MDA-MB-231 human TNBC cells than high-density FZD7-NS, yielding more robust inhibition of several Wnt target genes, as measured by RT-qPCR. Congruently, tumor spheroids formed from MDA-MB-231 cells that were pretreated with low-density FZD7-NS had significantly reduced area, metabolic activity, and cell number compared to those treated with high-density FZD7-NS. These results emphasize the importance of determining the appropriate surface ligand density when designing antibody–nanoparticle conjugates for therapeutic utility.This project was supported by the National Institutes of Health under award numbers R01CA211925 and R35GM149292 and training grant T32GM133395. G.C.K acknowledges support from the graduate traineeship program NRT-HDR: Computing and Data Science Training for Materials Innovation, Discovery, and AnalyticS (MIDAS) funded by the National Science Foundation grant 2125703. C.G.-C. and N.D.D. received support from the University of Delaware Summer Scholars Program. Microscopy equipment used at the Delaware Biotechnology Institute Core Facility was acquired with support from NIH-NIGMS (S10 OD016361, P20GM103446, and P30GM113125) and the Unidel Foundation, and access was supported by NIH-NIGMS (P20 GM103446 and P20 GM139760) and the State of Delaware
Identification and regulation of heritable biomarkers for manufacturing stress tolerance in CHO to improve monoclonal antibody production performance
No full textBlenner, MarkBiologics, a class of therapeutics derived from living systems, have revolutionized modern medicine and unlocked treatment options for a wide class of diseases. For its production, Chinese hamster ovary (CHO) cells have gradually become the preferred host organism due to its compatibility with large reactor systems, high production, and patterns of human-like post-translational modifications. Any efforts to increase productivity translates to lower operating costs and increases the affordability and accessibility to therapeutics. However, large-scale bioreactors and CHO cell’s inefficient overflow metabolism contribute to the accumulation of inhibitory environmental perturbations that invariably reduce cell growth and volumetric productivity. These include elevated osmolality, oxidative stress, ammonia, and lactate levels that disrupt cellular structure, cause cell-cycle dysregulation, and may induce apoptosis. Traditional cell line development (CLD) workflows often do not screen stress tolerance during clonal evaluation and therefore represents a vulnerability in isolating cell lines suited for scale-up and stress resiliency. Approaches to improve stress tolerance have largely been centered around bioreactor control strategies and knockout of metabolic or apoptotic regulating genes. These have relied on conventional heuristics for cell health, but do not consider or characterize the adaptative regulatory networks that form robust resistance. In this study, a novel approach utilizing population-based transcriptomics for the identification of unique biomarkers for bet-hedging and stress tolerance is demonstrated. Downstream genetic engineering was used to generate biomanufacturing stress-tolerant cell lines with improved growth characteristics across two different biomanufacturing-relevant environmental perturbations. ☐ Initially, three of the most commonly explored stress agents (ammonia, lactate, and osmolality) were used to stress shock monoclonal antibody (mAb) producing CHO cells in fed-batch to determine the phenotypic, morphological, and transcriptomic effects of perturbation. At supplemented concentrations of 10 mM ammonia and 100 mOsm/kg, cell specific growth rates, peak viable cell densities, and the integral of viable cell density (IVCD) were significantly reduced. This translated to a reduction in volumetric productivity or loss of titer. At lactate concentrations of 15 mM, inhibitory effects were not observed, possibly due to a higher baseline tolerance in the cell line or a context dependency in well-controlled environments. Disruption of lysosomal structure, hydrolase activity, and amino acid metabolism were observed in ammonia stress and an increase in surface bound transporters and translational activity were observed in osmotic stress. While this information provided insight regarding the phenotypic effects of stress, broad differential gene expression analysis highlighted confounding and ambiguous patterns of expression that convolutes the search for rational engineering targets. ☐ While traditional transcriptomics are useful, they are often insufficient in elucidating clear targets for genetic engineering. An alternative method for identifying stress-associated biomarkers was explored using a population-based transcriptomic tool known as MemorySeq. This method utilizes RNASeq fluctuation analysis of roughly 40 single-cell derived populations after 17 generations of growth to identify highly variable genes that correlate to intermediate, transient, and heritable memory states. These unique transgenerational properties have been linked to bet-hedging and broad stress resistance mechanisms in cancer, plant, and microbial cells. Using this tool, 199 unique genes with heritable properties were identified and found to be enriched in signaling/communication, regulation of cell proliferation, and apoptosis regulation functionalities. They also significantly overlapped with the differentially expressed genes in stress shocked populations, highlighting their role in early pre-stress resistance states. ☐ With genetic targets identified, stable and homogenous genetic engineering tools would permit replicable characterization of their effect on cell health. To streamline CHO cell line engineering efforts and regulation of native genes, a flexible and modular targeted integration toolkit was developed to accelerate vector construction and stable integration. This toolkit featured a 16 component one-pot Golden Gate (GG) reaction for plug-and-play assembly of complex mammalian expression cassettes. With efficiencies ranging from 100% in 7 element reactions to 35% in 16 element reactions, multifaceted vectors could be generated to optimize cis-acting regulatory elements. The toolkit also outlined a site-specific integration (SSI) workflow displaying 90-100% efficiency of complex payloads utilizing the Cre/lox recombinase system. SSI significantly reduces the transcriptional and transgene stability heterogeneity associated with random integration, therefore isolating intentional changes in vector design to phenotypic deviations. ☐ Finally, with the MemorySeq genetic targets and the SSI toolkit, regulating native gene expression allowed for the induction of stress-tolerant phenotypes. Development and optimization of CRISPR activation/interference (CRISPRa/i) systems allowed for activation and repression of three genes with heritable properties. These included activating transcription factor 3 (Atf3), immediate early response 3 (Ier3), and heme oxygenase-1 (Hmox1). These three genes have been indicated in other cell lines as playing a role in stress detection and response, but never in CHO. CRISPR facilitated activation of Atf3 and Hmox1 and repression of Ier3 resulted in a 30-40% increase in integral viable cell density and peak viable cell density in both ammonia and osmotic stress fed-batch conditions. This translated to measurable improvements in volumetric productivity that may be further compounded in an appropriately controlled bioreactor. Concomitant with improved growth was also a reduction in broad rates of apoptosis, indicating a cytoprotective feature of some of these genes or regulatory pathways. Overall, this thesis reflects a novel approach for identifying, characterizing, and engineering stress tolerant phenotypes in CHO using heritable properties as an early-stress resistance biomarker. Continued exploration of genes displaying these properties may highlight robust rational engineering targets for the development of novel CHO host strains with improved performance in manufacturing scale-bioreactors.University of Delaware, Department of Chemical and Biomolecular EngineeringPh.D
Implementation and analysis of FMCW radar for target detection and SAR imaging
No full textPrather, Dennis W.Frequency Modulated Continuous Wave (FMCW) radar systems are compact, energy efficient, and cost-effective, making them highly suitable for both commercial and defense applications. Operating with continuous low-power transmission, these systems enable accurate detection of target range by measuring the time delay between transmitted and reflected signals and target velocity from the Doppler frequency or position change over time. ☐ To increase the spatial resolution of a radar system, which depends on the antenna aperture and signal bandwidth, without adding hardware complexity, Synthetic Aperture Radar (SAR) techniques are integrated into the FMCW framework. This combination enables the development of a compact and lightweight imaging radar capable of achieving high-resolution imagery through motion. In this approach, measurements are collected at multiple spatial positions under the stop-and-go assumption, and image reconstruction is performed using the Range-Doppler and Backprojection algorithms. ☐ This thesis presents both theoretical and experimental investigations into FMCW radar signal generation, range–velocity measurement, and SAR-based imaging. The results demonstrate the effectiveness of FMCW-based SAR for multi-target localization and high-resolution imaging while maintaining a low-cost and power-efficient hardware design.University of Delaware, Department of Electrical and Computer EngineeringM.S
Dissociable impacts of perceived race and ascribed status in event-related brain potentials and multivariate network activity
No full textThis article was originally published in Cognitive, Affective, & Behavioral Neuroscience. The version of record is available at: https://doi.org/10.3758/s13415-026-01401-9
This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.Humans rapidly and efficiently categorize others with limited information, forming split-second impressions. Prior EEG person perception research has often focused on social categories derived from perceptual cues. However, impressions are frequently based on knowledge of someone. Little research has examined how person knowledge (or the interaction between perceptual category cues and person knowledge) influences the temporal unfolding of person perception, thereby missing a common experience of everyday encounters in which individuals have access to both. Using EEG, this study (n = 29) examined evoked event-related brain potentials (ERPs) and functional neural network responses previously associated with changes in attention and evaluation when perceivers categorized faces based on perceived race (i.e., Black or White) or ascribed socioeconomic status (i.e., high or low). Our findings indicate dissociations between ERPs and functional network dynamics during impression formation. Specifically, in immediate response to a face, perceived race shaped ERPs often associated with attention (P200) and motivation/evaluation (P300). However, ascribed status influenced coordination of the neural networks underlying attention/executive functions and social cognition/evaluation throughout the categorization task, suggesting that participants attended to and evaluated status in a sustained manner. Therefore, while race perception influenced ERPs, status did not. This was the opposite for the network analyses. These findings indicate that perceptual information (perceived race) and person knowledge (ascribed status) can influence impression formation in distinct ways: one in an immediate, evoked manner, and the other through the sustained coordination of functional networks.This work was supported by the Army Research Office as part of the Army Research Laboratory Strengthening Teamwork for Robust Operations in Novel Groups (STRONG) [W911NF2020080]
Connecting phage genotypes to ecological function : ǂb replication protein modules reveal phage dynamics across diel and tidal cycles in Narragansett Bay
No full textPolson, Shawn W.Viruses are the most abundant biological entities on Earth and play critical roles in shaping microbial communities, influencing host metabolism, population dynamics, and nutrient cycling. Despite their ecological importance, the majority of viral diversity remains uncharacterized, and the connections between viral genomic features and infection phenotypes are poorly understood. Replication proteins, including Family A and B DNA polymerases (PolA, PolB), ribonucleotide reductases (RNR), and helicases, are central to viral genome replication and serve as informative markers for predicting viral infection strategies and ecological behavior. ☐ This dissertation establishes a framework for investigating the ecology of unknown viral populations across environmental gradients through replication module analysis. Aim 1 developed a reproducible workflow for identifying and quantifying viral populations in metagenomes based on co-occurring replication proteins, integrating contig assembly, functional annotation, abundance estimation, and phylogenetic placement. Aim 2 expanded detection to PolB–carrying populations, including cyanophage, by constructing a reference database and validating functional PolB proteins through active site and domain analyses. Aim 3 applied these methods to a 48-hour diel and tidal series in Narragansett Bay, Rhode Island, revealing distinct ecological patterns: temperate-associated populations (L762 PolA variants, E. coli numbering) remained stable across diel and tidal gradients, while populations encoding virulent-associated replication modules (F762/Y762 PolA, RNRs, superfamily 4 (SF4) helicases) exhibited condition-specific fluctuations linked to diel host metabolism and tidal transitions. ☐ This work demonstrates that replication module composition provides a robust approach for predicting viral infection strategy and ecological behavior, extending beyond single-protein analyses. The pipelines and PolB-focused developments enable systematic characterization of previously overlooked viral populations, linking genome content to ecological dynamics. By connecting replication machinery to viral population behavior, this research provides a scalable framework for exploring viral ecology across spatial and temporal gradients and lays the foundation for predictive bioinformatic approaches to infer infection strategies in uncultivated viral communities.University of Delaware, Center for Bioinformatics and Computational BiologyPh.D
Vibrational signatures of hydrogen defects in delafossite CuMO2 (M = Al, Ga, In): Hybrid density-functional calculations
No full textThis article was originally published in Journal of Applied Physics. The version of record is available at: https://doi.org/10.1063/5.0309836
© 2026 Author(s). All article content, except where otherwise noted, is licensed under a Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).Hydrogen impurities are known to significantly influence the electronic properties of delafossite oxides CuMO2 (M= Al, Ga, In) by passivating acceptor defects, thereby impacting the p-type conductivity of these materials. Identifying H and its configurations is, therefore, important to understand the properties of these materials. In this study, we employ hybrid density-functional theory calculations to investigate the vibrational properties of various hydrogen-related defects, including interstitial hydrogen (Hi), the hydrogen-copper antisite complex (Hi–CuM), and hydrogen-copper vacancy complexes (Hi–VCu, 2Hi–VCu). Our calculations provide the first theoretical predictions of local vibrational modes associated with these defects, revealing frequencies ranging from approximately 2800 to 3800 cm−1. These results offer valuable insights into the behavior of hydrogen in CuMO2 and serve as a reference for future experimental investigations using techniques such as infrared spectroscopy. By identifying distinct vibrational signatures for different hydrogen configurations, this study lays the groundwork for defect characterization and passivation mechanisms in delafossite oxides, which are critical for optimizing their electronic and optical properties.This work was supported by the Kasetsart Research and Development Institute (KURDI) through Fundamental Funds (FF(KU)55.69). P.R. acknowledges the NSRF via the Program Management Unit for Human Resources & Institutional Development, Research, and Innovation (Grant No. B39G670019). We thank the NSTDA Supercomputer Center (ThaiSC) for providing computing resources for this work. A.J. acknowledges support from NSF through the UD-CHARM University of Delaware Materials Research Science and Engineering Center (MRSEC) (Grant No. DMR-2011824)
Decentralized agents learning with generative communication models
No full textDecker, Keith S.Reinforcement learning (RL) in multi-agent systems is an important and quickly growing domain with diverse applications. Single agent RL methods have been shown effective in low- and high-dimensional state spaces, such as game playing, robotics, and complex optimization problems requiring exploration. Multi-agent RL (MARL) has several additional challenges, including multi-agent credit assignment, the curse of dimensionality, non-stationary learning dynamics, and partial observability when each agent receives private observations. Despite these difficulties, many applications inherently benefit from multiple coordinated agents. ☐ Decentralized MARL offers a scalable and practical approach to coordination, where each agent executes its own policy conditioned solely on local observations and received communication from other agents. Effective decentralized learning typically depends on consistent and reliable communication. However, in real-world scenarios such as robotic teams operating in remote environments, communication channels are often sparse, unreliable, or bandwidth-constrained. ☐ This thesis explores methods that enable decentralized agents to learn effectively under limited communication conditions. Specifically, I extend a class of decentralized MARL algorithms that utilize centralized training with decentralized execution to impute missing communication, which enables continued learning in the decentralized phase. This is accomplished by equipping agents with generative models of joint observations or learned message encoders from teammates. A novel selective sampling approach is introduced that explicitly balances message transmission against model-based inference via a new counterfactual metric called the communication advantage. This value is proven to linearly approximate the associated global advantage, with experimental results demonstrating its efficacy in reducing communication overhead without sacrificing task performance compared to centralized baselines. Additionally, a comprehensive study and empirical analysis of centralization techniques is conducted, clarifying their effects across popular off-policy MARL algorithms and environments. Ultimately, this research provides practical methods and insights to improve MARL scalability and applicability in resource-constrained environments.University of Delaware, Department of Computer and Information SciencesPh.D
Impact of COVID-19 on patellar tendon properties over the first year after infection
No full textOpen Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.
This article was originally published in Scientific Reports. The version of record is available at: https://doi.org/10.1038/s41598-025-06879-wThis study aimed to examine the impact of infection severity and associated inactivity on patellar tendon health following COVID-19. Seventy participants were divided into three groups: moderate COVID-19 (n = 22), severe COVID-19 (n = 18), and control (n = 30). Four assessments were conducted over one-year for the COVID groups - between the 21st and 30th days (A21−30), 31 and 90 days (A31−90), 91 and 180 days (A91−180), and 181 and 360 days (A181−360) after the onset of symptoms for moderate or hospital discharge for severe. Maximal voluntary isometric knee extension contractions were performed, with simultaneous ultrasound imaging of patellar tendon length to calculate material and mechanical properties. Morphological properties (length and cross-sectional area) were obtained at rest. During one year, the severe group consistently had lower state of load on tendon (p 0.256). A reduction in stiffness (p < 0.009) and Young’s modulus (p < 0.015) was observed during the same assessment period. Severe infection cases were associated with prolonged reductions in tendon load and stress. These findings suggest that systemic effects of infection and reduced activity levels may contribute to tendon adaptations.We are grateful for financial support from Coordenação de Aperfeiçoamento de Pessoal de Nível Superior—Brasil (CAPES) (Finance Code 001), Fundação de Apoio a Pesquisa do Distrito Federal (FAPDF) (grant number 00193.00000773/2021-72, 00193–00001261/2021-23; 00193.00000859/2021-3; 00193–00002357/2022-90; 00193.00001222/2021-26), the National Council for Scientific and Technological Development (CNPq; process numbers 309435/2020-0 and 310269/2021), and the Decanato de Pós-Graduação (grant DPG No. 0007/2022, 0010/2023 and 005/2024)
Anoikis resistance and metastasis of ovarian cancer can be overcome by CDK8/19 Mediator kinase inhibition.
No full textThis article was originally published in JCI Insight. The version of record is available at: https://doi.org/10.1172/jci.insight.192113
Copyright © 2026, Monavarian et al. This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.Anoikis resistance or evasion of cell death triggered by matrix detachment is a hallmark of cancer cell survival and metastasis. We show that repeated exposure to suspension stress followed by recovery under attached conditions leads to development of anoikis resistance. The acquisition of anoikis resistance is associated with enhanced invasion, chemoresistance, and immune evasion in vitro and distant metastasis in vivo. This acquired anoikis resistance is not genetic, persisting for a finite duration without detachment stress, but is sensitive to CDK8/19 Mediator kinase inhibition that can also reverse anoikis resistance. Transcriptomic analysis reveals that CDK8/19 kinase inhibition induces bidirectional transcriptional changes in both sensitive and resistant cells, disrupting the balanced reprogramming required for anoikis adaptation and resistance by reversing some resistance associated pathways and enhancing others. Both anoikis resistance and in vivo metastatic growth of ovarian cancers are sensitive to CDK8/19 inhibition, thereby providing a therapeutic opportunity to both prevent and suppress ovarian cancer metastasis.This work was supported in part, by NIH funding and is subject to the NIH Public Access Policy, which permits public availability in PubMed Central. NIH grants R01CA230628 (KM, NH), R35GM148351 (AS), R43CA271996 and R01CA266027 (EVB), and the Norma Livingston Ovarian Cancer Foundation (KM). We acknowledge the University of South Carolina COBRE Center for Targeted Therapeutics Functional Genomics, Microscopy and Flow Cytometry, and Drug Design and Synthesis Cores (P20GM109091). We thank Drs. Amir Jazaeri (MD Anderson Cancer Center, Houston, TX) and Susan Murphy (Duke University) for cell lines. We acknowledge UAB shared resources: Biological Data Science Core (RRID:SCR_021766), Flow Cytometry Core (AI027767), O'Neal Comprehensive Cancer Center (P30CA013148), Preclinical Imaging Shared Facility (P30CA013148, 1S10OD021697), High Resolution Imaging Facility, and Bio-Analytical Redox Biology Core including Melissa J. Sammy, PhD (P30DK079626, P30DK056336, UL1TR003096) and Pathology Core Research lab. Schematics created with BioRender
Integrase anchors viral RNA to the HIV-1 capsid interior
No full textThis article was originally published in Nature. The version of record is available at: https://doi.org/10.1038/s41586-026-10154-x
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.HIV-1 integrase (IN) promotes encapsulation of viral genomic RNA into mature viral cores, and this function is a target for ongoing antiretroviral drug development efforts1,2,3. Here we determined the cryogenic electron microscopy (cryo-EM) structure of a primate lentiviral IN in a complex with RNA, revealing a linear filament made of IN octamer repeat units, each comprising a pair of asymmetric homotetramers. The assembly is stabilized through IN–RNA interactions involving mainly the IN C-terminal domains and RNA backbone. The spacing and orientation of the IN filament repeat units closely matched those of consecutive capsid (CA) hexamers within the mature CA lattice. Using cryo-EM images of native purified HIV-1 cores, we refined the structure of the IN filament as it propagates along the luminal side of the CA lattice. Each IN tetramer within the filament nestled in a CA hexamer, engaging closely with the major homology regions. Substitutions of residues involved in IN–CA contacts yielded eccentric virions with RNA nucleoids located outside of the cores. Collectively, our results establish the structural basis for the HIV-1 IN–RNA interaction and reveal that IN forms an RNA-binding module on the luminal side of the mature CA lattice