Neuroinflammation is associated with the pathophysiologies of neurodegenerative and psychiatric disorders. Evaluating neuroinflammation using positron emission tomography (PET) plays an important role in the early diagnosis and determination of proper treatment of brain diseases. To quantify neuroinflammatory responses in vivo, many PET tracers have been developed using translocator proteins, imidazole-2 binding site, cyclooxygenase, monoamine oxidase-B, adenosine, cannabinoid, purinergic P2X7, and CSF-1 receptors as biomarkers. In this review, we introduce the latest developments in PET tracers that can image neuroinflammation, focusing on clinical trials, and further consider their current implications.
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http://dx.doi.org/10.1007/s13139-023-00831-4 | DOI Listing |
J Nanobiotechnology
December 2024
Key Laboratory of Special Environmental Medicine of Xinjiang, General Hospital of Xinjiang Military Command, No. 359, Youhao North Road, Urumqi, Xinjiang, China.
Objective: This study aims to elucidate the mechanisms by which nanovesicles (NVs) transport curcumin(CUR) across the blood-brain barrier to treat hypothalamic neural damage induced by heat stroke by regulating the expression of poly(c)-binding protein 2 (PCBP2).
Methods: Initially, NVs were prepared from macrophages using a continuous extrusion method. Subsequently, CUR was loaded into NVs using sonication, yielding engineered cell membrane Nanovesicles loaded with curcumin (NVs-CUR), which were characterized and subjected to in vitro and in vivo tracking analysis.
Tomography
December 2024
Department of Radiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH 45229, USA.
Using a pediatric-focused lens, this review article briefly summarizes the presentation of several demyelinating and neuroinflammatory diseases using conventional magnetic resonance imaging (MRI) sequences, such as T1-weighted with and without an exogenous gadolinium-based contrast agent, T2-weighted, and fluid-attenuated inversion recovery (FLAIR). These conventional sequences exploit the intrinsic properties of tissue to provide a distinct signal contrast that is useful for evaluating disease features and monitoring treatment responses in patients by characterizing lesion involvement in the central nervous system and tracking temporal features with blood-brain barrier disruption. Illustrative examples are presented for pediatric-onset multiple sclerosis and neuroinflammatory diseases.
View Article and Find Full Text PDFTomography
December 2024
Department of Radiology, Nemours Children's Health, 1600 Rockland Rd., Wilmington, DE 19803, USA.
Evaluating altered mental status and suspected meningeal disorders in children often begins with imaging, typically before a lumbar puncture. The challenge is that meningeal enhancement is a common finding across a range of pathologies, making diagnosis complex. This review proposes a categorization of meningeal diseases based on their predominant imaging characteristics.
View Article and Find Full Text PDFCurr Issues Mol Biol
December 2024
Department of Histology and Embryology, Faculty of Medicine, Afyonkarahisar Health Sciences University, 03030 Afyonkarahisar, Turkey.
Modified citrus pectin (MCP) modulates galectin-3, a key player in neuroinflammation linked to Alzheimer's disease. By inhibiting galectin-3, MCP reduces the brain's inflammatory response and may alleviate cognitive decline. This study examines MCP's impact on neuroinflammation, cognitive function, and its role in galectin-3 inhibition in a dementia model.
View Article and Find Full Text PDFFront Immunol
December 2024
Emergency Department, Affiliated Yantai Yuhuangding Hospital of Qingdao University, Yantai, Shandong, China.
Objective: Subarachnoid hemorrhage (SAH) and tumorigenesis share numerous biological complexities; nevertheless, the specific gene expression profiles and underlying mechanisms remain poorly understood. This study aims to identify differentially expressed genes (DEGs) that could serve as biomarkers for diagnosis and prognosis.
Methods: Gene expression datasets (GSE122063, GSE13353, GSE161870) were analyzed using machine learning algorithms and logistic regression to identify DEGs associated with both SAH and tumorigenesis.
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