Brown Adipose Tissue as a Unique Niche for Islet Organoid Transplantation: Insights From In Vivo Imaging.

Background: Transplantation of human-induced pluripotent stem cell (hiPSC)-derived islet organoids is a promising cell replacement therapy for type 1 diabetes (T1D). It is important to improve the efficacy of islet organoids transplantation by identifying new transplantation sites with high vascularization and sufficient accommodation to support graft survival with a high capacity for oxygen delivery. Methods: A human-induced pluripotent stem cell line (hiPSCs-L1) was generated constitutively expressing luciferase. Luciferase-expressing hiPSCs were differentiated into islet organoids. The islet organoids were transplanted into the scapular brown adipose tissue (BAT) of nonobese diabetic/severe combined immunodeficiency disease (NOD/SCID) mice as the BAT group and under the left kidney capsule (KC) of NOD/SCID mice as a control group, respectively. Bioluminescence imaging (BLI) of the organoid grafts was performed on days 1, 7, 14, 28, 35, 42, 49, 56, and 63 posttransplantation. Results: BLI signals were detected in all recipients, including both the BAT and control groups. The BLI signal gradually decreased in both BAT and KC groups. However, the graft BLI signal intensity under the left KC decreased substantially faster than that of the BAT. Furthermore, our data show that islet organoids transplanted into streptozotocin-induced diabetic mice restored normoglycemia. Positron emission tomography/MRI verified that the islet organoids were transplanted at the intended location in these diabetic mice. Immunofluorescence staining revealed the presence of functional organoid grafts, as confirmed by insulin and glucagon staining. Conclusions: Our results demonstrate that BAT is a potentially desirable site for islet organoid transplantation for T1D therapy.

Machine Learning and Deep Learning Applications in Magnetic Particle Imaging.

In recent years, magnetic particle imaging (MPI) has emerged as a promising imaging technique depicting high sensitivity and spatial resolution. It originated in the early 2000s where it proposed a new approach to challenge the low spatial resolution achieved by using relaxometry in order to measure the magnetic fields. MPI presents 2D and 3D images with high temporal resolution, non-ionizing radiation, and optimal visual contrast due to its lack of background tissue signal. Traditionally, the images were reconstructed by the conversion of signal from the induced voltage by generating system matrix and X-space based methods. Because image reconstruction and analyses play an integral role in obtaining precise information from MPI signals, newer artificial intelligence-based methods are continuously being researched and developed upon. In this work, we summarize and review the significance and employment of machine learning and deep learning models for applications with MPI and the potential they hold for the future. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY: Stage 1.

Shape Anisotropy-Governed High-Performance Nanomagnetosol for In Vivo Magnetic Particle Imaging of Lungs.

Caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), coronavirus disease 2019 (COVID-19) has shown extensive lung manifestations in vulnerable individuals, putting lung imaging and monitoring at the forefront of early detection and treatment. Magnetic particle imaging (MPI) is an imaging modality, which can bring excellent contrast, sensitivity, and signal-to-noise ratios to lung imaging for the development of new theranostic approaches for respiratory diseases. Advances in MPI tracers would offer additional improvements and increase the potential for clinical translation of MPI. Here, a high-performance nanotracer based on shape anisotropy of magnetic nanoparticles is developed and its use in MPI imaging of the lung is demonstrated. Shape anisotropy proves to be a critical parameter for increasing signal intensity and resolution and exceeding those properties of conventional spherical nanoparticles. The 0D nanoparticles exhibit a 2-fold increase, while the 1D nanorods have a > 5-fold increase in signal intensity when compared to VivoTrax. Newly designed 1D nanorods displayed high signal intensities and excellent resolution in lung images. A spatiotemporal lung imaging study in mice revealed that this tracer offers new opportunities for monitoring disease and guiding intervention.

Three-dimensional imaging and quantification of mouse ovarian follicles via optical coherence tomography.

Ovarian tissue cryopreservation has been successfully applied worldwide for fertility preservation. Correctly selecting the ovarian tissue with high follicle loading for freezing and reimplantation increases the likelihood of restoring ovarian function, but it is a challenging process. In this work, we explore the use of three-dimensional spectral-domain optical coherence tomography (SD-OCT) to identify different follicular stages, compare the identifications with H&E images, and measure the size and age-related follicular density distribution differences in mice ovaries. We use the thickness of the layers of granulosa cells to differentiate primordial and primary follicles from secondary follicles. The measured dimensions and age-related follicular distribution agree well with histological images and physiological aging. Finally, we apply attenuation coefficient map analyses to significantly improve the image contrast and the contrast-to-noise ratio (p < 0.001), facilitating follicle identification and quantification. We conclude that SD-OCT is a promising method to noninvasively evaluate ovarian follicles for ovarian tissue cryopreservation.

Deep learning-enabled quantification of simultaneous PET/MRI for cell transplantation monitoring.

Current methods of in vivo imaging islet cell transplants for diabetes using magnetic resonance imaging (MRI) are limited by their low sensitivity. Simultaneous positron emission tomography (PET)/MRI has greater sensitivity and ability to visualize cell metabolism. However, this dual-modality tool currently faces two major challenges for monitoring cells. Primarily, the dynamic conditions of PET such as signal decay and spatiotemporal change in radioactivity prevent accurate quantification of the transplanted cell number. In addition, selection bias from different radiologists renders human error in segmentation. This calls for the development of artificial intelligence algorithms for the automated analysis of PET/MRI of cell transplantations. Here, we combined K-means++ for segmentation with a convolutional neural network to predict radioactivity in cell-transplanted mouse models. This study provides a tool combining machine learning with a deep learning algorithm for monitoring islet cell transplantation through PET/MRI. It also unlocks a dynamic approach to automated segmentation and quantification of radioactivity in PET/MRI.

Three-dimensional imaging and quantification of mouse ovarian follicles via optical coherence tomography.

Ovarian tissue cryopreservation has been successfully applied worldwide for fertility preservation. Correctly selecting the ovarian tissue with high follicle loading for freezing and reimplantation increases the likelihood of restoring ovarian function, but it is a challenging process. In this work, we explore the use of three-dimensional spectral-domain optical coherence tomography (SD-OCT) to identify different follicular stages, especially primary follicles, compare the identifications with H&E images, and measure the size and age-related follicular density distribution differences in mice ovaries. We use the thickness of the layers of granulosa cells to differentiate primordial and primary follicles from secondary follicles. The measured dimensions and age-related follicular distribution agree well with histological images and physiological aging. Finally, we apply attenuation coefficient map analyses to significantly improve the image contrast and the contrast-to-noise ratio (p < 0.001), facilitating follicle identification and quantification. We conclude that SD-OCT is a promising method to noninvasively evaluate ovarian follicles.

miRNA Theranostic Nanoparticles Promote Pancreatic Beta Cell Proliferation in Type 1 Diabetes Model.

Type 1 diabetes (T1D) is a chronic autoimmune disorder which affects the insulin-producing beta cells in the pancreas. A variety of strategies, namely, insulin replacement therapy, engineered vaccines, immunomodulators, etc., have been explored to correct this condition. Recent studies have attributed the development of T1D to the anomalous expression of microRNAs in the pancreatic islets. Here, we describe the protocol for the development of a theranostic approach to modify the expression of aberrant miRNAs. The MRI-based nanodrug consists of superparamagnetic iron oxide nanoparticles conjugated to microRNA-targeting oligonucleotides that can promote proliferation of pancreatic beta cells in a mouse model of T1D. This theranostic approach can successfully serve as a potential therapeutic approach for the targeted treatment of T1D with minimal side effects.

Nanotechnology in Immunotherapy for Type 1 Diabetes: Promising Innovations and Future Advances.

Diabetes is a chronic condition which affects the glucose metabolism in the body. In lieu of any clinical "cure," the condition is managed through the administration of pharmacological aids, insulin supplements, diet restrictions, exercise, and the like. The conventional clinical prescriptions are limited by their life-long dependency and diminished potency, which in turn hinder the patient's recovery. This necessitated an alteration in approach and has instigated several investigations into other strategies. As Type 1 diabetes (T1D) is known to be an autoimmune disorder, targeting the immune system in activation and/or suppression has shown promise in reducing beta cell loss and improving insulin levels in response to hyperglycemia. Another strategy currently being explored is the use of nanoparticles in the delivery of immunomodulators, insulin, or engineered vaccines to endogenous immune cells. Nanoparticle-assisted targeting of immune cells holds substantial potential for enhanced patient care within T1D clinical settings. Herein, we summarize the knowledge of etiology, clinical scenarios, and the current state of nanoparticle-based immunotherapeutic approaches for Type 1 diabetes. We also discuss the feasibility of translating this approach to clinical practice.

Neurotheranostics as personalized medicines.

The discipline of neurotheranostics was forged to improve diagnostic and therapeutic clinical outcomes for neurological disorders. Research was facilitated, in largest measure, by the creation of pharmacologically effective multimodal pharmaceutical formulations. Deployment of neurotheranostic agents could revolutionize staging and improve nervous system disease therapeutic outcomes. However, obstacles in formulation design, drug loading and payload delivery still remain. These will certainly be aided by multidisciplinary basic research and clinical teams with pharmacology, nanotechnology, neuroscience and pharmaceutic expertise. When successful the end results will provide "optimal" therapeutic delivery platforms. The current report reviews an extensive body of knowledge of the natural history, epidemiology, pathogenesis and therapeutics of neurologic disease with an eye on how, when and under what circumstances neurotheranostics will soon be used as personalized medicines for a broad range of neurodegenerative, neuroinflammatory and neuroinfectious diseases.

Doxorubicin-loaded dendritic-Fe3O4 supramolecular nanoparticles for magnetic drug targeting and tumor regression in spheroid murine melanoma model.

This work evaluates the magnetically-guided delivery of DOX-loaded dendritic-Fe3O4 nanoparticles and their tumor regression efficacy in subcutaneous melanoma in C57BL/6 mice. The hematological, biochemical and histopathological parameters were minimally affected. The nanoparticles localized in lungs, liver and spleen suggesting non-specific uptake. However, in tumor-bearing mice, substantially higher localization in magnetically-targeted tumor was observed when compared to passive localization in non-targeted tumor. The animals of treated group showed significantly high iron levels (161 µg of Fe/mg dry organ weight) in the tumor against the control (<25 µg of Fe/mg dry organ weight). This high localization led to high concentrations of DOX in the tumor which not only induced significant tumor regression but also arrested further growth. Within 14 days, the average tumor volume was reduced to 55±8.3 mm3 (treated) as compared to 4794±844 mm3 (control), i.e. ~88-fold decrease. The tumor disappeared by the end of 20th day post-treatment and ~100% survival rate was observed.

Dendrimer-conjugated iron oxide nanoparticles as stimuli-responsive drug carriers for thermally-activated chemotherapy of cancer.

In recent years, functional nanomaterials have found an appreciable place in the understanding and treatment of cancer. This work demonstrates the fabrication and characterization of a new class of cationic, biocompatible, peptide dendrimers, which were then used for stabilizing and functionalizing magnetite nanoparticles for combinatorial therapy of cancer. The synthesized peptide dendrimers have an edge over the widely used PAMAM dendrimers due to better biocompatibility and negligible cytotoxicity of their degradation products. The surface engineering efficacy of the peptide dendrimers and their potential use as drug carriers were compared with their PAMAM counterparts. The peptide dendrimer was found to be as efficient as PAMAM dendrimers in its drug-carrying capacity, while its drug release profiles substantially exceeded those of PAMAM's. A dose-dependent study was carried out to assess their half maximal inhibitory concentration (IC50) in vitro with various cancer cell lines. A cervical cancer cell line that was incubated with these dendritic nanoparticles was exposed to alternating current magnetic field (ACMF) to investigate the effect of elevated temperatures on the live cell population. The DOX-loaded formulations, in combination with the ACMF, were also assessed for their synergistic effects on the cancer cells for combinatorial therapy. The results established the peptide dendrimer as an efficient alternative to PAMAM, which can be used successfully in biomedical applications.

Combining unique properties of dendrimers and magnetic nanoparticles towards cancer theranostics.

Magnetic nanoparticles (MNPs) are a well explored class of nanomaterials, known for their high magnetization and biocompatibility thus finding their way in several biomedical applications viz., drug delivery, magnetic resonance imaging contrast agent, immunoassay, detoxification of biological fluids and cell separation, biosensing and hyperthermia. On other hand, dendrimers are a class of hyperbranched, mostly symmetrical polymers that originate from a central core with repetitive branching units, called monomers, thus forming a globular structure. Due to their structural properties and controlled size, dendrimers have emerged as an attractive material for biomedical applications particularly as carriers for therapeutic cargo. Of late, researchers have started attempting to combine the unique features of dendrimer chemistry with the versatile magnetic nanoparticles to provide a facile platform for enhanced therapeutics and biomedical applications. This review intends to present the advances made towards fabrication of dendrimer based magnetic nanoparticles with varied surface architecture and their contribution towards theranostics, particularly for cancer.

Poly(ethylene glycol)-modified PAMAM-Fe3O4-doxorubicin triads with the potential for improved therapeutic efficacy: generation-dependent increased drug loading and retention at neutral pH and increased release at acidic pH.

Polyamidoamine (PAMAM) dendrimer-coated magnetic nanoparticles are a promising drug-delivery system that can enhance the therapeutic effects of chemotherapy drugs, such as doxorubicin (DOX), with minimized side effects. This work explores the optimization of the potential therapeutic efficiency of PAMAM-Fe3O4-DOX triads. Different generations (G3, G5, and G6) of PAMAMs were synthesized and modified with poly(ethylene glycol) (PEG) and then used to encapsulate glutamic acid-modified Fe3O4 nanoparticles. The Fe3O4-dendrimer carriers (Fe3O4-DGx where x = the generation 3, 5, or 6 of dendrimers) were electrostatically conjugated with drug DOX. The loading and releasing efficiencies of DOX increased with the PAMAM generation from 3 to 6. The loading efficiencies of DOX molecules were 87, 93, and 96% for generations 3, 5, and 6, respectively. At pH 5, the DOX release efficiencies within 24 h were approximately 60, 68, and 80% for generations 3, 5, and 6, respectively. At pH 7.4, the DOX releasing efficiency was as low as ∼ 15%. Compared to the negative control, the PAMAM-Fe3O4-DOX triads showed only mild toxicity against human cervical adenocarcinoma cell line HeLa at pH 7.4, which indicated that DOX can be fairly benignly carried and sparingly released until PAMAM-Fe3O4-DOX is taken up into the cell.