Publications by authors named "Jeffrey Harrison"

The immune checkpoint inhibitor anti-PD-1, commonly used in cancer immunotherapy, has not been successful as a monotherapy for the highly aggressive brain cancer glioblastoma. However, when used in conjunction with a CC-chemokine receptor-2 (CCR2) antagonist, anti-PD-1 has shown efficacy in preclinical studies. In this paper, we aim to optimize treatment regimens for this combination immunotherapy using optimal control theory.

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Glioblastoma (GBM) is the most common malignant primary brain tumor, resulting in poor survival despite aggressive therapies. GBM is characterized by a highly heterogeneous and immunosuppressive tumor microenvironment (TME) made up predominantly of infiltrating peripheral immune cells. One significant immune cell type that contributes to glioma immune evasion is a population of immunosuppressive cells, termed myeloid-derived suppressor cells (MDSCs).

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The immune checkpoint inhibitor anti-PD-1, commonly used in cancer immunotherapy, has not been successful as a monotherapy for the highly aggressive brain cancer glioblastoma. However, when used in conjunction with a CC-chemokine receptor-2 (CCR2) antagonist, anti-PD-1 has shown efficacy in preclinical studies. In this paper, we aim to optimize treatment regimens for this combination immunotherapy using optimal control theory.

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The focus of nanoparticles in vivo trafficking has been mostly on their tissue-level biodistribution and clearance. Recent progress in the nanomedicine field suggests that the targeting of nanoparticles to immune cells can be used to modulate the immune response and enhance therapeutic delivery to the diseased tissue. In the presence of tumor lesions, monocytic-myeloid-derived suppressor cells (M-MDSCs) expand significantly in the bone marrow, egress into peripheral blood, and traffic to the solid tumor, where they help maintain an immuno-suppressive tumor microenvironment.

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Glioblastoma (GBM) is the most common malignant primary brain tumor, resulting in poor survival despite aggressive therapies. GBM is characterized by a highly heterogeneous and immunosuppressive tumor microenvironment (TME) made up predominantly of infiltrating peripheral immune cells. One significant immune cell type that contributes to glioma immune evasion is a population of immunosuppressive cells, termed myeloid-derived suppressor cells (MDSCs).

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Glioblastoma (GBM) poses a significant challenge in clinical oncology due to its aggressive nature, heterogeneity, and resistance to therapies. Cancer stem cells (CSCs) play a critical role in GBM, particularly in treatment resistance and tumor relapse, emphasizing the need to comprehend the mechanisms regulating these cells. Also, their multifaceted contributions to the tumor microenvironment (TME) underline their significance, driven by their unique properties.

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Article Synopsis
  • Glioblastoma (GBM) is a tough cancer to treat due to its aggressive nature and resistance to therapies, making understanding cancer stem cells (CSCs) crucial for combating it.
  • This study focused on characterizing slow-cycling glioblastoma stem cells (SCCs) in a mouse model (KR158) to see how similar they are to human SCCs.
  • Findings revealed that KR158 mouse SCCs have key characteristics, including the ability to self-renew and resist chemotherapy, validating this model for further research into GSCs and their role in GBM progression and treatment strategies.
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New agents are needed that selectively kill cancer cells without harming normal tissues. The TRAIL ligand and its receptors, DR5 and DR4, exhibit cancer-selective toxicity, but TRAIL analogs or agonistic antibodies targeting these receptors have not received FDA approval for cancer therapy. Small molecules for activating DR5 or DR4 independently of protein ligands may bypass some of the pharmacological limitations of these protein drugs.

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Glioblastoma (GBM) is an aggressive primary brain cancer that currently has minimally effective treatments. Like other cancers, immunosuppression by the PD-L1-PD-1 immune checkpoint complex is a prominent axis by which glioma cells evade the immune system. Myeloid-derived suppressor cells (MDSCs), which are recruited to the glioma microenviroment, also contribute to the immunosuppressed GBM microenvironment by suppressing T cell functions.

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Glioblastoma (GBM) is an aggressive primary brain cancer that currently has minimally effective treatments. Like other cancers, immunosuppression by the PD-L1-PD-1 immune checkpoint complex is a prominent axis by which glioma cells evade the immune system. Myeloid-derived suppressor cells (MDSCs), which are recruited to the glioma microenviroment, also contribute to the immunosuppressed GBM microenvironment by suppressing T cell functions.

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Glioblastoma (GBM) is the most common and malignant primary brain tumor, resulting in poor survival despite aggressive therapies. GBM is characterized in part by a highly heterogeneous and immunosuppressive tumor microenvironment (TME) made up predominantly of infiltrating peripheral immune cells. One significant immune cell type that contributes to glioma immune evasion is a population of immunosuppressive, hematopoietic cells, termed myeloid-derived suppressor cells (MDSCs).

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To commemorate 40 years since the founding of the Journal of Business Ethics, the editors in chief of the journal have invited the editors to provide commentaries on the future of business ethics. This essay comprises a selection of commentaries aimed at creating dialogue around the theme (inspired by the title of the commentary by Jeffrey Harrison). The authors of these commentaries seek to transcend the age-old separation fallacy (Freeman in Bus Ethics Q 4(4):409-421, 1994) that juxtaposes business and ethics/society, posing a forced choice or trade off.

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Glioblastoma is the most aggressive brain cancer and is highly infiltrated with cells of myeloid lineage (TIM) that support tumor growth and invasion. Tumor resection is the primary treatment for glioblastoma; however, the activation state of TIM at the site of tumor resection and its impact on glioma regrowth are poorly understood. Using the C57BL/6/GL261 mouse glioma implantation model, we investigated the state of TIM in the tumor resection area during the post-surgical period.

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Chemokines are a large subfamily of cytokines known for their ability to facilitate cell migration, most notably leukocytes, throughout the body. Chemokines are necessary for a functioning immune system in both health and disease and have received considerable attention for their roles in orchestrating temporal-spatial regulation of immune cell populations in cancer. Gliomas comprise a group of common central nervous system (CNS) primary tumors that are extremely challenging to treat.

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In oncology, "immunotherapy" is a broad term encompassing multiple means of utilizing the patient's immune system to combat malignancy. Prominent among these are immune checkpoint inhibitors, cellular therapies including chimeric antigen receptor T-cell therapy, vaccines, and oncolytic viruses. Immunotherapy for glioblastoma (GBM) has had mixed results in early trials.

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Immunotherapy directed at the PD-L1/PD-1 axis has produced treatment advances in various human cancers. Unfortunately, progress has not extended to glioblastoma (GBM), with phase III clinical trials assessing anti-PD-1 monotherapy failing to show efficacy in newly diagnosed and recurrent tumors. Myeloid-derived suppressor cells (MDSCs), a subset of immunosuppressive myeloid derived cells, are known to infiltrate the tumor microenvironment of GBM.

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Ionic-transport processes govern performance in many classic and emerging devices, ranging from battery storage to modern mixed-conduction organic electrochemical transistors (OECT). Here, we study local ion-transport dynamics in polymer films using time-resolved electrostatic force microscopy (trEFM). We establish a correspondence between local and macroscopic measurements using local trEFM and macroscopic electrical impedance spectroscopy (EIS).

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Correlating nanoscale chemical specificity with operational physics is a long-standing goal of functional scanning probe microscopy (SPM). We employ a data analytic approach combining multiple microscopy modes using compositional information in infrared vibrational excitation maps acquired via photoinduced force microscopy (PiFM) with electrical information from conductive atomic force microscopy. We study a model polymer blend comprising insulating poly(methyl methacrylate) (PMMA) and semiconducting poly(3-hexylthiophene) (P3HT).

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Unlabelled: In this study, the role of CX3CR1 in the progression of diabetic retinopathy (DR) was investigated. The retinas of wild-type (WT), CX3CR1 null (CX3CR1, KO), and heterozygous (CX3CR1, Het) mice were compared in the presence and absence of streptozotocin (STZ)-induced diabetes. CX3CR1 deficiency in STZ-KO increased vascular pathology at 4 months of diabetes, as a significant increase in acellular capillaries was observed only in the STZ-KO group.

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Palliative care services are becoming more prevalent in the United States as greater portions of the population are requiring end-of-life services. Furthermore, recent policy changes and service foci have promoted more continuity and encompassing care. This study evaluates characteristics that distinguish hospitals with a palliative care program from hospitals without such a program in order to better define the markets and environments that promote the creation and usage of these programs.

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The ability to measure microsecond- and nanosecond-scale local dynamics below the diffraction limit with widely available atomic force microscopy hardware would enable new scientific studies in fields ranging from biology to semiconductor physics. However, commercially available scanning-probe instruments typically offer the ability to measure dynamics only on time scales of milliseconds to seconds. Here, we describe in detail the implementation of fast time-resolved electrostatic force microscopy using an oscillating cantilever as a means to measure fast local dynamics following a perturbation to a sample.

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Dynamic force spectroscopy (DFS) measurements on biomolecules typically require classifying thousands of repeated force spectra prior to data analysis. Here, we study classification of atomic force microscope-based DFS measurements using machine-learning algorithms in order to automate selection of successful force curves. Notably, we collect a data set that has a testable positive signal using photoswitch-modified DNA before and after illumination with UV (365 nm) light.

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