Browsing by Author "Biomedical Engineering and Informatics, Luddy School of Informatics, Computing, and Engineering"

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    Altered Caveolin-1 Dynamics Result in Divergent Mineralization Responses in Bone and Vascular Calcification
    (Springer, 2023-08-19) Bakhshian Nik, Amirala; Kaiser, Katherine; Sun, Patrick; Khomtchouk, Bohdan B.; Hutcheson, Joshua D.; Biomedical Engineering and Informatics, Luddy School of Informatics, Computing, and Engineering
    Introduction: Though vascular smooth muscle cells adopt an osteogenic phenotype during pathological vascular calcification, clinical studies note an inverse correlation between bone mineral density and arterial mineral-also known as the calcification paradox. Both processes are mediated by extracellular vesicles (EVs) that sequester calcium and phosphate. Calcifying EV formation in the vasculature requires caveolin-1 (CAV1), a membrane scaffolding protein that resides in membrane invaginations (caveolae). Of note, caveolin-1-deficient mice, however, have increased bone mineral density. We hypothesized that caveolin-1 may play divergent roles in calcifying EV formation from vascular smooth muscle cells (VSMCs) and osteoblasts (HOBs). Methods: Primary human coronary artery VSMCs and osteoblasts were cultured for up to 28 days in an osteogenic media. CAV1 expression was knocked down using siRNA. Methyl β-cyclodextrin (MβCD) and a calpain inhibitor were used, respectively, to disrupt and stabilize the caveolar domains in VSMCs and HOBs. Results: CAV1 genetic variation demonstrates significant inverse relationships between bone-mineral density (BMD) and coronary artery calcification (CAC) across two independent epidemiological cohorts. Culture in osteogenic (OS) media increased calcification in HOBs and VSMCs. siRNA knockdown of CAV1 abrogated VSMC calcification with no effect on osteoblast mineralization. MβCD-mediated caveolae disruption led to a 3-fold increase of calcification in VSMCs treated with osteogenic media (p < 0.05) but hindered osteoblast mineralization (p < 0.01). Conversely, stabilizing caveolae by calpain inhibition prevented VSMC calcification (p < 0.05) without affecting osteoblast mineralization. There was no significant difference in CAV1 content between lipid domains from HOBs cultured in OS and control media. Conclusion: Our data indicate fundamental cellular-level differences in physiological and pathophysiological mineralization mediated by CAV1 dynamics. This is the first study to suggest that divergent mechanisms in calcifying EV formation may play a role in the calcification paradox. Supplementary information: The online version contains supplementary material available at 10.1007/s12195-023-00779-7.
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    Astrocytic GABA transporter 1 deficit in novel SLC6A1 variants mediated epilepsy: Connected from protein destabilization to seizures in mice and humans
    (Elsevier, 2022) Mermer, Felicia; Poliquin, Sarah; Zhou, Shuizhen; Wang, Xiaodong; Ding, Yifeng; Yin, Fei; Shen, Wangzhen; Wang, Juexin; Rigsby, Kathryn; Xu, Dong; Mack, Taralynn; Nwosu, Gerald; Flamm, Carson; Stein, Matthew; Kang, Jing-Qiong; Biomedical Engineering and Informatics, Luddy School of Informatics, Computing, and Engineering
    Objective: Mutations in γ-aminobutyric acid (GABA) transporter 1 (GAT-1)-encoding SLC6A1 have been associated with myoclonic atonic epilepsy and other phenotypes. We determined the patho-mechanisms of the mutant GAT-1, in order to identify treatment targets. Methods: We conducted whole-exome sequencing of patients with myoclonic atonic epilepsy (MAE) and characterized the seizure phenotypes and EEG patterns. We studied the protein stability and structural changes with homology modeling and machine learning tools. We characterized the function and trafficking of the mutant GAT-1 with 3H radioactive GABA uptake assay and confocal microscopy. We utilized different models including a knockin mouse and human astrocytes derived from induced pluripotent stem cells (iPSCs). We focused on astrocytes because of their direct impact of astrocytic GAT-1 in seizures. Results: We identified four novel SLC6A1 variants associated with MAE and 2 to 4 Hz spike-wave discharges as a common EEG feature. Machine learning tools predicted that the variant proteins are destabilized. The variant protein had reduced expression and reduced GABA uptake due to endoplasmic reticular retention. The consistent observation was made in cortical and thalamic astrocytes from variant-knockin mice and human iPSC-derived astrocytes. The Slc6a+/A288V mouse, representative of MAE, had increased 5-7 Hz spike-wave discharges and absence seizures. Interpretation: SLC6A1 variants in various locations of the protein peptides can cause MAE with similar seizure phenotypes and EEG features. Reduced GABA uptake is due to decreased functional GAT-1, which, in thalamic astrocytes, could result in increased extracellular GABA accumulation and enhanced tonic inhibition, leading to seizures and abnormal EEGs.
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    Author Correction: scGNN is a novel graph neural network framework for single-cell RNA-Seq analyses
    (Springer Nature, 2022-05-04) Wang, Juexin; Ma, Anjun; Chang, Yuzhou; Gong, Jianting; Jiang, Yuexu; Qi, Ren; Wang, Cankun; Fu, Hongjun; Ma, Qin; Xu, Dong; Biomedical Engineering and Informatics, Luddy School of Informatics, Computing, and Engineering
    Correction to: Nature Communications 10.1038/s41467-021-22197-x, published online 25 March 2021. In Figure 2, panels (a) and (b) were inadvertently swapped. The correct version of this figure appears below. This has been corrected in the HTML and PDF version of this article.
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    Big Data Edge on Consumer Devices for Precision Medicine
    (IEEE, 2022) Stauffer, Jake; Zhang, Qingxue; Biomedical Engineering and Informatics, Luddy School of Informatics, Computing, and Engineering
    Consumer electronics like smartphones and wearable computers are furthering precision medicine significantly, through capturing/leveraging big data on the edge towards real-time, interactive healthcare applications. Here we propose a big data edge platform that can, not only capture/manage different biomedical dynamics, but also enable real-time visualization of big data. The big data can also be uploaded to cloud for long-term management. The system has been evaluated on the real-world biomechanical data-based application, and demonstrated its effectiveness on big data management and interactive visualization. This study is expected to greatly advance big data-driven precision medicine applications.
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    Cardioinformatics Advancements in Healthcare and Biotechnology
    (American Heart Association, 2023) Khomtchouk, Bohdan B.; Biomedical Engineering and Informatics, Luddy School of Informatics, Computing, and Engineering
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    CETP and SGLT2 inhibitor combination therapy increases glycemic control: a 2x2 factorial Mendelian randomization analysis
    (Frontiers Media, 2024-06-19) Khomtchouk, Bohdan B.; Sun, Patrick; Maggio, Zane A.; Ditmarsch, Marc; Kastelein, John J. P.; Davidson, Michael H.; Biomedical Engineering and Informatics, Luddy School of Informatics, Computing, and Engineering
    Introduction: Cholesteryl ester transfer protein (CETP) inhibitors, initially developed for treating hyperlipidemia, have shown promise in reducing the risk of new-onset diabetes during clinical trials. This positions CETP inhibitors as potential candidates for repurposing in metabolic disease treatment. Given their oral administration, they could complement existing oral medications like sodium-glucose cotransporter 2 (SGLT2) inhibitors, potentially delaying the need for injectable therapies such as insulin. Methods: We conducted a 2x2 factorial Mendelian Randomization analysis involving 233,765 participants from the UK Biobank. This study aimed to evaluate whether simultaneous genetic inhibition of CETP and SGLT2 enhances glycemic control compared to inhibiting each separately. Results: Our findings indicate that dual genetic inhibition of CETP and SGLT2 significantly reduces glycated hemoglobin levels compared to controls and single-agent inhibition. Additionally, the combined inhibition is linked to a lower incidence of diabetes compared to both the control group and SGLT2 inhibition alone. Discussion: These results suggest that combining CETP and SGLT2 inhibitor therapies may offer superior glycemic control over SGLT2 inhibitors alone. Future clinical trials should investigate the potential of repurposing CETP inhibitors for metabolic disease treatment, providing an oral therapeutic option that could benefit high-risk patients before they require injectable therapies like insulin or glucagon-like peptide-1 (GLP-1) receptor agonists.
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    Chikamatsu, Mori, and the uncanny valley
    (Sage, 2025-02-06) MacDorman, Karl F.; Biomedical Engineering and Informatics, Luddy School of Informatics, Computing, and Engineering
    In Japan, robotics projects like Geminoid, modeled after Hiroshi Ishiguro, exhibit a fascination with creating human doubles. Yet, warnings against this also thread through Japanese thought, from the Edo-period playwright Chikamatsu Monzaemon (1653-1724) to the robotics professor Mori Masahiro (1927-2025). Though centuries apart, they describe the same uncanny valley phenomenon-eerie, cold, repellent feelings that arise when confronting the imperfectly human. In an interview with Hozumi Ikan, translated here, Chikamatsu presents a theory of realism exemplified through puppet theater and kabuki. He divides realism into four zones: the unreal, conceptual realism, surface realism, and the real. The unreal lacks authenticity, surface realism lacks soul, and the real lacks expressiveness. For Chikamatsu, it is conceptual realism that captivates an audience. A play's unfolding events evoke empathy and emotion through their meaning for the characters. Similarly, Mori divides realism into four zones: industrial, humanoid, and android robots, and real people. Industrial robots evoke little affinity, and androids risk appearing eerie. Though real people evoke the most affinity, androids cannot become indistinguishable from them. For Mori, only humanoid robots evoke affinity without risking uncanniness. By exploring anthropomorphism, both Chikamatsu and Mori illuminate principles for designing robots that do not unsettle but delight.
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    Clear aligners, the aesthetic solution: a review
    (Scilit, 2021) Ganta, Gopala Krishna; Cheruvu, Kamala; Ravi, Rama Krishna; Reddy, Raghavendra Prasad; Biomedical Engineering and Informatics, Luddy School of Informatics, Computing, and Engineering
    In the recent past, the demand for adult orthodontic treatment has increased multiple folds. As a repercussion of this stipulation, invisible orthodontic treatment has expanded its horizon. Efforts of using aesthetic brackets, wires, and lingual techniques to meet the expectations of adult patients have been practised. Though these techniques seemed to be promising in the initial days, soon decreased in popularity due to drawbacks associated with them. Clear aligners were offered as a newer and superior aesthetic alternative to overcome the difficulties associated with prior aesthetic approaches. These aligners are made up of different thermoplastic materials intended to move the malpositioned teeth in the desired corrected position following push mechanics. This article deals with new generation orthodontic treatment using aligners. It deals with history, generations, different materials used, and the distances yet to be travelled to become the benchmark and replace the existing conventional braces. This paper also gives a bird’s eye view of the method of aligner fabrication and the significant differences between the regular braces and aligners used in orthodontics.
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    Comparative Analysis of Alternative Splicing Profiles in Th Cell Subsets Reveals Extensive Cell Type–Specific Effects Modulated by a Network of Transcription Factors and RNA-Binding Proteins
    (American Association of Immunologists, 2021-09-28) Mir, Quoseena; Lakshmipati, Deepak K.; Ulrich, Benjamin J.; Kaplan, Mark H.; Janga, Sarath Chandra; Biomedical Engineering and Informatics, Luddy School of Informatics, Computing, and Engineering
    Alternative splicing (AS) plays an important role in the development of many cell types; however, its contribution to Th subsets has been clearly defined. In this study, we compare mice naive CD4+ Th cells with Th1, Th2, Th17, and T regulatory cells and observed that the majority of AS events were retained intron, followed by skipped-exon events, with at least 1200 genes across cell types affected by AS events. A significant fraction of the AS events, especially retained intron events from the 72-h time point, were no longer observed 2 wk postdifferentiation, suggesting a role for AS in early activation and differentiation via preferential expression of specific isoforms required during T cell activation, but not for differentiation or effector function. Examining the protein consequence of the exon-skipping events revealed an abundance of structural proteins encoding for intrinsically unstructured peptide regions, followed by transmembrane helices, β strands, and polypeptide turn motifs. Analyses of expression profiles of RNA-binding proteins (RBPs) and their cognate binding sites flanking the discovered AS events revealed an enrichment for specific RBP recognition sites in each of the Th subsets. Integration with publicly available chromatin immunoprecipitation sequencing datasets for transcription factors support a model wherein lineage-determining transcription factors impact the RBP profile within the differentiating cells, and this differential expression contributes to AS of the transcriptome via a cascade of cell type-specific posttranscriptional rewiring events.
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    CrossMP: Enabling Cross-Modality Translation between Single-Cell RNA-Seq and Single-Cell ATAC-Seq through Web-Based Portal
    (MDPI, 2024-07-05) Lyu, Zhen; Dahal, Sabin; Zeng, Shuai; Wang, Juexin; Xu, Dong; Joshi, Trupti; Biomedical Engineering and Informatics, Luddy School of Informatics, Computing, and Engineering
    In recent years, there has been a growing interest in profiling multiomic modalities within individual cells simultaneously. One such example is integrating combined single-cell RNA sequencing (scRNA-seq) data and single-cell transposase-accessible chromatin sequencing (scATAC-seq) data. Integrated analysis of diverse modalities has helped researchers make more accurate predictions and gain a more comprehensive understanding than with single-modality analysis. However, generating such multimodal data is technically challenging and expensive, leading to limited availability of single-cell co-assay data. Here, we propose a model for cross-modal prediction between the transcriptome and chromatin profiles in single cells. Our model is based on a deep neural network architecture that learns the latent representations from the source modality and then predicts the target modality. It demonstrates reliable performance in accurately translating between these modalities across multiple paired human scATAC-seq and scRNA-seq datasets. Additionally, we developed CrossMP, a web-based portal allowing researchers to upload their single-cell modality data through an interactive web interface and predict the other type of modality data, using high-performance computing resources plugged at the backend.