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At least 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Long noncoding RNA AK023096 interacts with hnRNP-K and contributes to the maintenance of self-renewal in bladder cancer stem-like cells

Highlights: • BCSLCs play a critical role for the high risk of recurrence and we identified that lncRNA-AK023096 was required for controls stemness of BCSLCs. • LncRNA-AK023096 recruits hnRNP-K and epigenetically upregulated SOX2 expression by modulating H3K4 trimethylation of SOX2 promoter. • Overexpression of lncRNA-AK023096 expression in the tumor tissue was significantly associated with high risk of recurrence following TUR-Bt. LncRNA contribution to self-renewal of bladder cancer stem-like cells (CSLCs) remains largely unknown. We investigated the expression profile and biological function of lncRNAs in urothelial CSLCs by microarray analysis. Among these, lncRNA-AK023096 was identified as potentially playing a role in maintaining self-renewal of CSLCs. Knockdown of this transcript inhibited spheroid formation and tumor formation. We found that AK023096 mediates recruitment of hnRNP-K to SOX2 promoter and increases H3K4 trimethylation status on SOX2 promoter, leading to a robust change in SOX2 mRNA and protein levels. Moreover, AK023096 expression in primary tumors was found to be a powerful predictor of recurrence following transurethral resection in patients with nonmuscle-invasive bladder cancer, highlighting the critical role of lncRNA in the bladder cancer regulatory network.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Targeting ROR1 in combination with osimertinib in EGFR mutant lung cancer cells

Highlights: • The role of ROR1 was investigated in EGFR mutant lung cancer cells in vitro. • Cell growth and colony formation were suppressed and apoptosis was increased in cell lines treated with siROR1. • A combination of osimertinib with siROR1 was effective for EGFR mutant cell lines. Lung cancer that exhibits epidermal growth factor receptor (EGFR) gene mutation is sensitive to EGFR-tyrosine kinase inhibitors (TKIs), such as osimertinib. Receptor tyrosine kinase-like orphan receptor 1 (ROR1) may be involved in overcoming EGFR-TKI resistance. Growth inhibition, colony formation, apoptosis, and mRNA/protein levels in four osimertinib-sensitive and resistant cell lines transfected with small interfering RNA (siRNA) targeting ROR1 (siROR1) were evaluated. Cell growth and colony formation were suppressed and apoptosis was increased in all cell lines treated with siROR1. Although EGFR, AKT, and ERK phosphorylation were not suppressed in all cell lines, TGF-β2, AXL, CDH2, PARP1, PEG10, and TYMS mRNA expression levels were reduced. The combination of osimertinib with siROR1 was effective for the four cell lines, particularly in the two osimertinib-sensitive lines. In conclusion, targeting ROR1 in combination with osimertinib in EGFR mutant lung cancer may be a novel therapeutic option.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

RCSB Protein Data Bank tools for 3D structure-guided cancer research: human papillomavirus (HPV) case study

Abstract Atomic-level three-dimensional (3D) structure data for biological macromolecules often prove critical to dissecting and understanding the precise mechanisms of action of cancer-related proteins and their diverse roles in oncogenic transformation, proliferation, and metastasis. They are also used extensively to identify potentially druggable targets and facilitate discovery and development of both small-molecule and biologic drugs that are today benefiting individuals diagnosed with cancer around the world. 3D structures of biomolecules (including proteins, DNA, RNA, and their complexes with one another, drugs, and other small molecules) are freely distributed by the open-access Protein Data Bank (PDB). This global data repository is used by millions of scientists and educators working in the areas of drug discovery, vaccine design, and biomedical and biotechnology research. The US Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB) provides an integrated portal to the PDB archive that streamlines access for millions of worldwide PDB data consumers worldwide. Herein, we review online resources made available free of charge by the RCSB PDB to basic and applied researchers, healthcare providers, educators and their students, patients and their families, and the curious public. We exemplify the value of understanding cancer-related proteins in 3D with a case study focused on human papillomavirus.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Selective CK1α degraders exert antiproliferative activity against a broad range of human cancer cell lines

Molecular-glue degraders are small molecules that induce a specific interaction between an E3 ligase and a target protein, resulting in the target proteolysis. The discovery of molecular glue degraders currently relies mostly on screening approaches. Here, we describe screening of a library of cereblon (CRBN) ligands against a panel of patient-derived cancer cell lines, leading to the discovery of SJ7095, a potent degrader of CK1α, IKZF1 and IKZF3 proteins. Through a structure-informed exploration of structure activity relationship (SAR) around this small molecule we develop SJ3149, a selective and potent degrader of CK1α protein in vitro and in vivo. The structure of SJ3149 co-crystalized in complex with CK1α + CRBN + DDB1 provides a rationale for the improved degradation properties of this compound. In a panel of 115 cancer cell lines SJ3149 displays a broad antiproliferative activity profile, which shows statistically significant correlation with MDM2 inhibitor Nutlin-3a. These findings suggest potential utility of selective CK1α degraders for treatment of hematological cancers and solid tumors.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Computational ranking identifies Plexin-B2 in circulating tumor cell clustering with monocytes in breast cancer metastasis

Abstract Multicellular circulating tumor cell (CTC) clusters can be up to 50 times more efficient than single CTCs in mediating viable metastasis. Here, combining computational ranking and functional determination, we identify the transmembrane protein Plexin-B2 (PLXNB2) as one of the top molecular targets associated with unfavorable distant metastasis-free survival, showing enriched expression in CTC clusters versus single CTCs from patients with advanced breast cancer (mostly female). Loss of PLXNB2 (Plxnb2) reduces the formation of homotypic tumor cell clusters and heterotypic tumor-myeloid cell clusters, reducing spontaneous metastases in female mice bearing human (mouse) breast cancer. Interactions of PLXNB2 with its ligands SEMA4C on tumor cells and SEMA4A on myeloid cells (monocytes) promote homotypic and heterotypic CTC cluster formation, respectively, thereby driving lung metastasis. Global proteomic analysis reveals downstream effectors of the PLXNB2 pathway associated with tumor cell clustering. Thus, PLXNB2 is a therapeutic target for preventing new metastasis in breast cancer.

Science & Technology - Other Topics↗
DOE OSTI2024

A multiscale model of immune surveillance in micrometastases gives insights on cancer patient digital twins

Abstract Metastasis is the leading cause of death in patients with cancer, driving considerable scientific and clinical interest in immunosurveillance of micrometastases. We investigated this process by creating a multiscale mathematical model to study the interactions between the immune system and the progression of micrometastases in general epithelial tissue. We analyzed the parameter space of the model using high-throughput computing resources to generate over 100,000 virtual patient trajectories. We demonstrated that the model could recapitulate a wide variety of virtual patient trajectories, including uncontrolled growth, partial response, and complete immune response to tumor growth. We classified the virtual patients and identified key patient parameters with the greatest effect on the simulated immunosurveillance. We highlight the lessons derived from this analysis and their impact on the nascent field of cancer patient digital twins (CPDTs). While CPDTs could enable clinicians to systematically dissect the complexity of cancer in each individual patient and inform treatment choices, our work shows that key challenges remain before we can reach this vision. In particular, we show that there remain considerable uncertainties in immune responses, unreliable patient stratification, and unpredictable personalized treatment. Nonetheless, we also show that in spite of these challenges, patient-specific models suggest strategies to increase control of clinically undetectable micrometastases even without complete parameter certainty.

Mathematical & Computational Biology↗
DOE OSTI2022

Redox signaling by glutathione peroxidase 2 links vascular modulation to metabolic plasticity of breast cancer

Redox regulation of breast cancer underlies malignant progression. Loss of the antioxidant glutathione peroxidase 2 in breast cancer cells increases reactive oxygen species, thereby activating hypoxia inducible factor-α (HIF1α) signaling. This in turn causes vascular malfunction, resulting in hypoxia and metabolic heterogeneity. HIF1α suppresses oxidative phosphorylation and stimulates glycolysis (the Warburg effect) in most of the tumor, except for one cancer subpopulation, which was capable of using both metabolic modalities. Hence, adopting a hybrid metabolic state may allow tumor cells to survive under aerobic or hypoxic conditions, a vulnerability that may be exploited for therapeutic targeting by either metabolic or redox-based strategies.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Chromosome compartmentalization alterations in prostate cancer cell lines model disease progression

Prostate cancer aggressiveness and metastatic potential are influenced by gene expression and genomic aberrations, features that can be influenced by the 3D structure of chromosomes inside the nucleus. Using chromosome conformation capture (Hi-C), we conducted a systematic genome architecture comparison on a cohort of cell lines that model prostate cancer progression, from normal epithelium to bone metastasis. We describe spatial compartment identity (A-open versus B-closed) changes with progression in these cell lines and their relation to gene expression changes in both cell lines and patient samples. In particular, 48 gene clusters switch from the B to the A compartment, including androgen receptor, WNT5A, and CDK14. These switches are accompanied by changes in the structure, size, and boundaries of topologically associating domains (TADs). Further, compartment changes in chromosome 21 are exacerbated with progression and may explain, in part, the genesis of the TMPRSS2-ERG translocation. These results suggest that discrete 3D genome structure changes play a deleterious role in prostate cancer progression.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

HEXIM1 controls P-TEFb processing and regulates drug sensitivity in triple-negative breast cancer

The positive transcription elongation factor b (P-TEFb), composed of CDK9 and cyclin T, stimulates transcriptional elongation by RNA polymerase (Pol) II and regulates cell growth and differentiation. Recently, we demonstrated that P-TEFb also controls the expression of EMT regulators to promote breast cancer progression. In the nucleus, more than half of P-TEFb are sequestered in the inactive-state 7SK snRNP complex. Here, we show that the assembly of the 7SK snRNP is preceded by an intermediate complex between HEXIM1 and P-TEFb that allows transfer of the kinase active P-TEFb from Hsp90 to 7SK snRNP for its suppression. Down-regulation of HEXIM1 locks P-TEFb in the Hsp90 complex, keeping it in the active state to enhance breast cancer progression, but also rendering the cells highly sensitive to Hsp90 inhibition. Because HEXIM1 is often down-regulated in human triple-negative breast cancer (TNBC), these cells are particularly sensitive to Hsp90 inhibition. Our study provides a mechanistic explanation for the increased sensitivity of TNBC to Hsp90 inhibition.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Cervical Precancers and Cancers Attributed to HPV Types by Race and Ethnicity: Implications for Vaccination, Screening, and Management

Abstract Background Racial and ethnic variations in attribution of cervical precancer and cancer to human papillomavirus (HPV) types may result in different HPV vaccine protection, screening test coverage, and clinical management. Methods Pooling data from 7 US studies, we calculated the proportional attribution of precancers and cancers to HPV types using HPV DNA typing from diagnosis. All statistical tests were 2-sided. Results For all racial and ethnic groups, most cases of cervical intraepithelial neoplasia grade 3 (CIN3) (84.2%-90.8% of 5526) and squamous cell carcinoma (SCC) (90.4%-93.8% of 1138) were attributed to types targeted by the 9-valent vaccine. A higher proportion of CIN3s were attributed to nonvaccine HPV types among non-Hispanic Black women (15.8%) compared with non-Hispanic Asian or Pacific Islander (9.7%; P = .002), non-Hispanic White (9.2%; P < .001), and Hispanic (11.3%; P = .004) women. The proportion of SCCs attributed to 9-valent types was similar by race and ethnicity (P = .80). A higher proportion of CIN3s were attributed to nonvaccine HPV35 among non-Hispanic Black (9.0%) compared with non-Hispanic Asian or Pacific Islander (2.2%), non-Hispanic White (2.5%), and Hispanic (3.0%; all P < .001) women. Compared with CIN3, the proportion of SCCs attributed to HPV35 among non-Hispanic Black women (3.2%) was lower and closer to other groups (0.3%-2.1%; P = .70). Conclusion The 9-valent HPV vaccine will prevent nearly all cervical precancers and invasive cancers among major racial and ethnic groups in the United States. Adding HPV35 to vaccines could prevent a small percentage of CIN3s and SCCs, with greater potential impact for CIN3s among Black women. HPV screening tests target high-risk HPV types, including HPV35. Future genotyping triage strategies could consider the importance of HPV35- and other HPV16-related types.

Mix, Jacqueline (ORCID:0000000164187706)↗
DOE OSTI2021

CarcSeq Measurement of Rat Mammary Cancer Driver Mutations and Relation to Spontaneous Mammary Neoplasia

Abstract The ability to deduce carcinogenic potential from subchronic, repeat dose rodent studies would constitute a major advance in chemical safety assessment and drug development. This study investigated an error-corrected NGS method (CarcSeq) for quantifying cancer driver mutations (CDMs) and deriving a metric of clonal expansion predictive of future neoplastic potential. CarcSeq was designed to interrogate subsets of amplicons encompassing hotspot CDMs applicable to a variety of cancers. Previously, normal human breast DNA was analyzed by CarcSeq and metrics based on mammary-specific CDMs were correlated with tissue donor age, a surrogate of breast cancer risk. Here we report development of parallel methodologies for rat. The utility of the rat CarcSeq method for predicting neoplastic potential was investigated by analyzing mammary tissue of 16-week-old untreated rats with known differences in spontaneous mammary neoplasia (Fischer 344, Wistar Han, and Sprague Dawley). Hundreds of mutants with mutant fractions ≥ 10−4 were quantified in each strain, most were recurrent mutations, and 42.5% of the nonsynonymous mutations have human homologs. Mutants in the mammary-specific target of the most tumor-sensitive strain (Sprague Dawley) showed the greatest nonsynonymous/synonymous mutation ratio, indicative of positive selection consistent with clonal expansion. For the mammary-specific target (Hras, Pik3ca, and Tp53 amplicons), median absolute deviation correlated with percentages of rats that develop spontaneous mammary neoplasia at 104 weeks (Pearson r = 1.0000, 1-tailed p = .0010). Therefore, this study produced evidence CarcSeq analysis of spontaneously occurring CDMs can be used to derive an early metric of clonal expansion relatable to long-term neoplastic outcome.

McKim, Karen L.↗
DOE OSTI2025

Psychosomatic Bias in Low-dose Radiation Epidemiology: Assessing the Role of Radiophobia and Stress in Cancer Incidence

Abstract Historical assessment of radiation effects at low doses (below 0.2 Sv) are generally the result of back extrapolation from higher doses, which are known to have a linear relation between risk and dose. There are multiple counter-examples, and some literature argues that a threshold, nonlinear, or even a beneficial effect (hormeisis) can occur from radiation below these doses. The common theme found in all of these studies stems from the traditional approach of correlating disease rates to stimulus and then effectively curve-fitting the result toward zero dose. What has not been considered in general are the personal stress levels of the exposed individuals due to fear of cancer from low doses. The increased levels of cortisol due to the psychological stress from fear or depression has been shown in the literature to increase cancer probability. The extent to which low-dose exposed individuals were highly fearful or stressed from the radiation exposure would then give rise to elevated cancer based on stress rather than a fundamental radiogenic mechanism. If the population under epidemiological study is aware of a potential historical exposure (no matter how small) and has then lived under stress from fear or depression due to that exposure, the psychosomatic effects will bias the epidemiology accordingly and so should be quantified and accounted for as done with the effects of smoking. Health Phys. 129(0):000-000; 2025

Environmental Sciences & Ecology↗
DOE OSTI2020

Hsa_circ_0000515 is a novel circular RNA implicated in the development of breast cancer through its regulation of the microRNA‐296‐5p/CXCL10 axis

Cancer metastasis is a major cause of death among women afflicted with breast cancer (BC) and understanding the molecular processes involved is a major focus in BC research. Circular RNAs (circRNAs) have emerged as genomic regulatory molecules in carcinogenesis and metastasis; however, their role in BC is unclear. We characterized a novel circRNA, hsa_circ_0000515, in context of BC. We collected 340 cancerous tissues surgically resected from BC patients and found hsa_circ_0000515 was upregulated in BC tissues and associated with poor prognosis of BC. Silencing of hsa_circ_0000515 impaired cell cycle progression, cell proliferation, and invasion, attenuated inflammatory response, and reduced the proangiogenetic potential of BC cells. RNA pull‐down and dual‐luciferase reporter gene assays showed that hsa_circ_0000515 binds miR‐296‐5p, preventing it from repressing CXCL10 expression. We also observed that miR‐296‐5p inhibition or CXCL10 overexpression promoted cell cycle progression, restored proliferative, invasive and proangiogenetic abilities, and increased inflammatory response in MCF‐7 cells in the absence of hsa_circ_0000515. In vivo analyses showed that partial loss of hsa_circ_0000515 reduced the tumor growth of MCF‐7 cells in nude mice. The key findings from this study revealed that targeting hsa_circ_0000515 might be an effective strategy to combat BC.

Cai, Fenglin↗
DOE OSTI2024

PpIX‐enabled fluorescence‐based detection and photodynamic priming of platinum‐resistant ovarian cancer cells under fluid shear stress

Over 75% percent of ovarian cancer patients are diagnosed with advanced-stage disease characterized by unresectable intraperitoneal dissemination and the presence of ascites, or excessive fluid build-up within the abdomen. Conventional treatments include cytoreductive surgery followed by multi-line platinum and taxane chemotherapy regimens. Despite an initial response to treatment, over 75% of patients with advanced-stage ovarian cancer will relapse and succumb to platinum-resistant disease. Recent evidence suggests that fluid shear stress (FSS), which results from the movement of fluid such as ascites, induces epithelial-to-mesenchymal transition and confers resistance to carboplatin in ovarian cancer cells. This study demonstrates, for the first time, that FSS-induced platinum resistance correlates with increased cellular protoporphyrin IX (PpIX), the penultimate downstream product of heme biosynthesis, the production of which can be enhanced using the clinically approved pro-drug aminolevulinic acid (ALA). These data suggest that, with further investigation, PpIX could serve as a fluorescence-based biomarker of FSS-induced platinum resistance. Additionally, this study investigates the efficacy of PpIX-enabled photodynamic therapy (PDT) and the secretion of extracellular vesicles under static and FSS conditions in Caov-3 and NIH:OVCAR-3 cells, two representative cell lines for high-grade serous ovarian carcinoma (HGSOC), the most lethal form of the disease. FSS induces resistance to ALA-PpIX-mediated PDT, along with a significant increase in the number of EVs. Finally, the ability of PpIX-mediated photodynamic priming (PDP) to enhance carboplatin efficacy under FSS conditions is quantified. These preliminary findings in monolayer cultures necessitate additional studies to determine the feasibility of PpIX as a fluorescence-based indicator, and mediator of PDP, to target chemoresistance in the context of FSS.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

A Functional Survey of the Regulatory Landscape of Estrogen Receptor–Positive Breast Cancer Evolution

Abstract Only a handful of somatic alterations have been linked to endocrine therapy resistance in hormone-dependent breast cancer, potentially explaining ∼40% of relapses. If other mechanisms underlie the evolution of hormone-dependent breast cancer under adjuvant therapy is currently unknown. In this work, we employ functional genomics to dissect the contribution of cis-regulatory elements (CRE) to cancer evolution by focusing on 12 megabases of noncoding DNA, including clonal enhancers, gene promoters, and boundaries of topologically associating domains. Parallel epigenetic perturbation (CRISPRi) in vitro reveals context-dependent roles for many of these CREs, with a specific impact on dormancy entrance and endocrine therapy resistance. Profiling of CRE somatic alterations in a unique, longitudinal cohort of patients treated with endocrine therapies identifies a limited set of noncoding changes potentially involved in therapy resistance. Overall, our data uncover how endocrine therapies trigger the emergence of transient features which could ultimately be exploited to hinder the adaptive process. Significance: This study shows that cells adapting to endocrine therapies undergo changes in the usage or regulatory regions. Dormant cells are less vulnerable to regulatory perturbation but gain transient dependencies which can be exploited to decrease the formation of dormant persisters.

Oncology↗
DOE OSTI2022

Achieving robust somatic mutation detection with deep learning models derived from reference data sets of a cancer sample

Accurate detection of somatic mutations is challenging but critical in understanding cancer formation, progression, and treatment. We recently proposed NeuSomatic, the first deep convolutional neural network-based somatic mutation detection approach, and demonstrated performance advantages on in silico data. In this study, we use the first comprehensive and well-characterized somatic reference data sets from the SEQC2 consortium to investigate best practices for using a deep learning framework in cancer mutation detection. Using the high-confidence somatic mutations established for a cancer cell line by the consortium, we identify the best strategy for building robust models on multiple data sets derived from samples representing real scenarios, for example, a model trained on a combination of real and spike-in mutations had the highest average performance. The strategy identified in our study achieved high robustness across multiple sequencing technologies for fresh and FFPE DNA input, varying tumor/normal purities, and different coverages, with significant superiority over conventional detection approaches in general, as well as in challenging situations such as low coverage, low variant allele frequency, DNA damage, and difficult genomic regions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Path-BigBird: An AI-Driven Transformer Approach to Classification of Cancer Pathology Reports

PURPOSE Surgical pathology reports are critical for cancer diagnosis and management. To accurately extract information about tumor characteristics from pathology reports in near real time, we explore the impact of using domain-specific transformer models that understand cancer pathology reports. METHODS We built a pathology transformer model, Path-BigBird, by using 2.7 million pathology reports from six SEER cancer registries. We then compare different variations of Path-BigBird with two less computationally intensive methods: Hierarchical Self-Attention Network (HiSAN) classification model and an offthe-shelf clinical transformer model (Clinical BigBird). We use five pathology information extraction tasks for evaluation: site, subsite, laterality, histology, and behavior. Model performance is evaluated by using macro and micro F 1 scores. RESULTS We found that Path-BigBird and Clinical BigBird outperformed the HiSAN in all tasks. Clinical BigBird performed better on the site and laterality tasks. Versions of the Path-BigBird model performed best on the two most difficult tasks: subsite (micro F 1 score of 72.53, macro F 1 score of 35.76) and histology (micro F 1 score of 80.96, macro F 1 score of 37.94). The largest performance gains over the HiSAN model were for histology, for which a Path-BigBird model increased the micro F 1 score by 1.44 points and the macro F 1 score by 3.55 points. Overall, the results suggest that a Path-BigBird model with a vocabulary derived from wellcurated and deidentified data is the best-performing model. CONCLUSION The Path-BigBird pathology transformer model improves automated information extraction from pathology reports. Although Path-BigBird outperforms Clinical BigBird and HiSAN, these less computationally expensive models still have utility when resources are constrained.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Super-resolution and segmentation deep learning for breast cancer histopathology image analysis

Traditionally, a high-performance microscope with a large numerical aperture is required to acquire high-resolution images. However, the images’ size is typically tremendous. Therefore, they are not conveniently managed and transferred across a computer network or stored in a limited computer storage system. As a result, image compression is commonly used to reduce image size resulting in poor image resolution. Here, we demonstrate custom convolution neural networks (CNNs) for both super-resolution image enhancement from low-resolution images and characterization of both cells and nuclei from hematoxylin and eosin (H&E) stained breast cancer histopathological images by using a combination of generator and discriminator networks so-called super-resolution generative adversarial network-based on aggregated residual transformation (SRGAN-ResNeXt) to facilitate cancer diagnosis in low resource settings. The results provide high enhancement in image quality where the peak signal-to-noise ratio and structural similarity of our network results are over 30 dB and 0.93, respectively. The derived performance is superior to the results obtained from both the bicubic interpolation and the well-known SRGAN deep-learning methods. In addition, another custom CNN is used to perform image segmentation from the generated high-resolution breast cancer images derived with our model with an average Intersection over Union of 0.869 and an average dice similarity coefficient of 0.893 for the H&E image segmentation results. Finally, we propose the jointly trained SRGAN-ResNeXt and Inception U-net Models, which applied the weights from the individually trained SRGAN-ResNeXt and inception U-net models as the pre-trained weights for transfer learning. The jointly trained model’s results are progressively improved and promising. We anticipate these custom CNNs can help resolve the inaccessibility of advanced microscopes or whole slide imaging (WSI) systems to acquire high-resolution images from low-performance microscopes located in remote-constraint settings.

60 APPLIED LIFE SCIENCES↗