Accomplishments and challenges in stem cell imaging in vivo.

Stem cell therapies have demonstrated promising preclinical results, but very few applications have reached the clinic owing to safety and efficacy concerns. Translation would benefit greatly if stem cell survival, distribution and function could be assessed in vivo post-transplantation, particularly in patients. Advances in molecular imaging have led to extraordinary progress, with several strategies being deployed to understand the fate of stem cells in vivo using magnetic resonance, scintigraphy, PET, ultrasound and optical imaging. Here, we review the recent advances, challenges and future perspectives and opportunities in stem cell tracking and functional assessment, as well as the advantages and challenges of each imaging approach

Leveraging FAERS and Big Data Analytics with Machine Learning for Advanced Healthcare Solutions

This research study explores the potential of leveraging the FDA Adverse Event Reporting System (FAERS), combined with big data analytics and machine learning techniques, to enhance healthcare solutions. FAERS serves as a comprehensive database maintained by the U.S. Food and Drug Administration (FDA), encompassing reports of adverse events, medication errors, and product quality issues associated with diverse drugs and therapeutic interventions.By harnessing the power of big data analytics applied to the vast information within FAERS, healthcare professionals and researchers gain valuable insights into drug safety, discover potential adverse reactions, and uncover patterns that may not have been discernible through traditional methods. Particularly, machine learning plays a pivotal role in processing and analyzing this extensive dataset, enabling the extraction of meaningful patterns and prediction of adverse events.The findings of this study demonstrate various ways in which FAERS, big data analytics, and machine learning can be leveraged to provide advanced healthcare solutions. Machine learning algorithms trained on FAERS data can effectively identify early signals of adverse events associated with specific drugs or treatments, allowing for prompt detection and appropriate actions.Big data analytics applied to FAERS data facilitate pharmacovigilance and drug safety monitoring. Machine learning models automatically classify and analyze adverse event reports, efficiently flagging potential safety concerns and identifying emerging trends.The integration of FAERS data with big data analytics and machine learning enables signal detection and causality assessment. This approach aids in the identification of signals that suggest a causal relationship between drugs and adverse events, thereby enhancing the assessment of drug safety.By analyzing FAERS data in conjunction with patient-specific information, machine learning models can assist in identifying patient subgroups that are more susceptible to adverse events. This information is instrumental in personalizing treatment plans and optimizing medication choices, ultimately leading to improved patient outcomes.The combination of FAERS data with other biomedical information offers insights into potential new uses or indications for existing drugs. Machine learning algorithms analyze the integrated data, identifying patterns and making predictions about the efficacy and safety of repurposing existing drugs for new applications.The implementation of FAERS, big data analytics, and machine learning in advanced healthcare solutions necessitates meticulous consideration of data privacy, security, and ethical implications. Safeguarding patient privacy and ensuring responsible data use through anonymization techniques and appropriate data governance are paramount.The integration of FAERS, big data analytics, and machine learning holds immense potential in advancing healthcare solutions, enhancing patient safety, and optimizing medical interventions. The findings of this study demonstrate the multifaceted benefits that can be derived from leveraging these technologies, paving the way for a more efficient and effective healthcare ecosystem

Functionalized multiwalled carbon nanotubes as ultrasound contrast agents

Ultrasonography is a fundamental diagnostic imaging tool in everyday clinical practice. Here, we are unique in describing the use of functionalized multiwalled carbon nanotubes (MWCNTs) as hyperechogenic material, suggesting their potential application as ultrasound contrast agents. Initially, we carried out a thorough investigation to assess the echogenic property of the nanotubes in vitro. We demonstrated their long-lasting ultrasound contrast properties. We also showed that ultrasound signal of functionalized MWCNTs is higher than graphene oxide, pristine MWCNTs, and functionalized single-walled CNTs. Qualitatively, the ultrasound signal of CNTs was equal to that of sulfur hexafluoride (SonoVue), a commercially available contrast agent. Then, we found that MWCNTs were highly echogenic in liver and heart through ex vivo experiments using pig as an animal model. In contrast to the majority of ultrasound contrast agents, we observed in a phantom bladder that the tubes can be visualized within a wide variety of frequencies (i.e., 5.5–10 MHz) and 12.5 MHz using tissue harmonic imaging modality. Finally, we demonstrated in vivo in the pig bladder that MWCNTs can be observed at low frequencies, which are appropriate for abdominal organs. Importantly, we did not report any toxicity of CNTs after 7 d from the injection by animal autopsy, organ histology and immunostaining, blood count, and chemical profile. Our results reveal the enormous potential of CNTs as ultrasound contrast agents, giving support for their future applications as theranostic nanoparticles, combining diagnostic and therapeutic modalities

Nanodiagnosis and Nanotreatment of Cardiovascular Diseases: An Overview

Cardiovascular diseases (CVDs) are the world’s leading cause of mortality and represent a large contributor to the costs of medical care. Although tremendous progress has been made for the diagnosis of CVDs, there is an important need for more effective early diagnosis and the design of novel diagnostic methods. The diagnosis of CVDs generally relies on signs and symptoms depending on molecular imaging (MI) or on CVD-associated biomarkers. For early-stage CVDs, however, the reliability, specificity, and accuracy of the analysis is still problematic. Because of their unique chemical and physical properties, nanomaterial systems have been recognized as potential candidates to enhance the functional use of diagnostic instruments. Nanomaterials such as gold nanoparticles, carbon nanotubes, quantum dots, lipids, and polymeric nanoparticles represent novel sources to target CVDs. The special properties of nanomaterials including surface energy and topographies actively enhance the cellular response within CVDs. The availability of newly advanced techniques in nanomaterial science opens new avenues for the targeting of CVDs. The successful application of nanomaterials for CVDs needs a detailed understanding of both the disease and targeting moieties

Recent Advances in Bioimaging for Cancer Research

Molecular imaging techniques as well as nanoparticle applicable to molecular imaging are being explored to improve the cancer detection accuracy, which help to manage efficiently at the early stage. Among the various imaging technologies, optical imaging is a highly sensitive detection technique that allows direct observation of specific molecular events, biological pathways, and disease processes in real time through imaging probes that emit light in a range of wavelengths. Recently, nanoparticles have provided significant progresses that can be simultaneously used for cancer diagnosis and therapy (cancer theranostics). Theranostics aims to provide “image-guided cancer therapy,” by integrating therapeutic and imaging agents in a single platform. In addition, molecular imaging techniques facilitate “image-guided surgery” enabling maximization of tumor excision and minimization of side effects. The optical signals generated by fluorescence nanoparticles offer the possibility to distinguish tumor sites and normal tissues during surgery by real-time guidance, thereby increasing the long-term patient survival. These techniques will considerably contribute to reducing cancer recurrence and developing more effective cures. In this chapter, we will introduce diverse research on nanomaterials-based optical imaging for effective cancer therapy

Rod-shape theranostic nanoparticles facilitate antiretroviral drug biodistribution and activity in human immunodeficiency virus susceptible cells and tissues

Human immunodeficiency virus theranostics facilitates the development of long acting (LA) antiretroviral drugs (ARVs) by defining drug-particle cell depots. Optimal drug formulations are made possible based on precise particle composition, structure, shape and size. Through the creation of rod-shaped particles of defined sizes reflective of native LA drugs, theranostic probes can be deployed to measure particle-cell and tissue biodistribution, antiretroviral activities and drug retention. Methods: Herein, we created multimodal rilpivirine (RPV) 177lutetium labeled bismuth sulfide nanorods (177LuBSNRs) then evaluated their structure, morphology, configuration, chemical composition, biological responses and adverse reactions. Particle biodistribution was analyzed by single photon emission computed tomography (SPECT/CT) and laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) imaging. Results: Nanoformulated RPV and BSNRs-RPV particles showed comparable physicochemical and cell biological properties. Drug-particle pharmacokinetics (PK) and biodistribution in lymphoid tissue macrophages proved equivalent, one with the other. Rapid particle uptake and tissue distribution were observed, without adverse reactions, in primary blood-derived and tissue macrophages. The latter was seen within the marginal zones of spleen. Conclusions: These data, taken together, support the use of 177LuBSNRs as theranostic probes as a rapid assessment tool for PK LA ARV measurements

Eicosapentaenoic acid and oxypurinol in the treatment of muscle wasting in a mouse model of cancer cachexia

Cancer cachexia is a wasting condition, driven by systemic inflammation and oxidative stress. This study investigated eicosapentaenoic acid (EPA) in combination with oxypurinol as a treatment in a mouse model of cancer cachexia. Mice with cancer cachexia were randomized into 4 treatment groups (EPA (0.4 g/kg/day), oxypurinol (1 mmol/L ad-lib), combination, or control), and euthanized after 29 days. Analysis of oxidative damage to DNA, mRNA analysis of pro-oxidant, antioxidant and proteolytic pathway components, along with enzyme activity of pro- and antioxidants were completed on gastrocnemius muscle. The control group displayed earlier onset of tumor compared to EPA and oxypurinol groups (P&lt;0.001). The EPA group maintained body weight for an extended duration (20 days) compared to the oxypurinol (5 days) and combination (8 days) groups (P&lt;0.05). EPA (18.2&plusmn;3.2 pg/ml) and combination (18.4&plusmn;3.7 pg/ml) groups had significantly higher 8-OH-dG levels than the control group (12.9&plusmn;1.4 pg/ml, P&le;0.05) indicating increased oxidative damage to DNA. mRNA levels of GPx1, MURF1 and MAFbx were higher following EPA treatment compared to control (P&le;0.05). Whereas oxypurinol was associated with higher GPx1, MnSOD, CAT, XDH, MURF1, MAFbx and UbB mRNA compared to control (P&le;0.05). Activity of total SOD was higher in the oxypurinol group (32.2&plusmn;1.5 U/ml) compared to control (27.0&plusmn;1.3 U/ml, P&lt;0.01), GPx activity was lower in the EPA group (8.76&plusmn;2.0 U/ml) compared to control (14.0&plusmn;1.9 U/ml, P&lt;0.05), and catalase activity was lower in the combination group (14.4&plusmn;2.8 U/ml) compared to control (20.9&plusmn;2.0 U/ml, P&lt;0.01). There was no change in XO activity. The increased rate of weight decline in mice treated with oxypurinol indicates that XO may play a protective role during the progression of cancer cachexia, and its inhibition is detrimental to outcomes. In combination with EPA, there was little significant improvement from control, indicating oxypurinol is unlikely to be a viable treatment compound in cancer cachexia.<br /

Functional Nanomaterials in Biomedicine

The great success of nanotechnology promotes a tremendous revolution in the biomedical field. Functional nanomaterials have been widely applied for the treatment of various diseases, such as cancer, bacterial infection, diabetes, inflammation, and neurodegenerative disorders. Various therapeutic nanoplatforms have been developed with therapeutic functions and intelligent properties. However, the development of nanomedicine suffers from several challenges prior to their clinical applications. For instance, disease detection in an early stage is a critical challenge for nanomedicine. It is difficult to detect disease markers (e.g., proteins, genes, or cancer circulating cells), so nanoprobes with high sensitivity and selectivity are required. Moreover, to overcome drug resistance, it is highly desirable to develop functional nanomedicines with the combination of multiple therapeutic modalities, such as chemotherapy, photothermal therapy, photodynamic therapy, chemodynamic therapy, radiotherapy, starving therapy, and immunotherapy. Additionally, the stability and degradability of most nanomedicines in biofluids should be carefully evaluated before their administration to humans. This book provides researchers with the latest investigations and findings in this field