MRI Study of the Influence of Surface Coating Aging on the In Vivo Biodistribution of Iron Oxide Nanoparticles

Emerging theranostics to combat cancer: a perspective on metal-based nanomaterials

OBJECTIVE

Theranostics, encompassing diagnostics and therapeutics, has emerged as a critical component of cancer treatment. Metal-based theranostics is one such next-generation nanotechnology-based drug delivery system with a myriad of benefits in pre-clinical and clinical medication for the deadly diseases like cancer, where early detection can actually be life-saving.

SIGNIFICANCE

Metal theranostics have shown promising outcomes in terms of anticancer medication monitoring, targeted drug delivery, and simultaneous detection and treatment of early-stage cancer.

METHODS

For collection of literature data, different search engines including Google scholar, SciFinder, PubMed, ScienceDirect have been employed. With key words like, cancer, theranostics, metal nanoparticles relevant and appropriate data have been generated.

RESULTS

Noninvasive administration of the active drug is made possible by theranostics nanoparticulate systems' ability to aggregate at the tumor site and offer morphological and biochemical characteristics of the tumor site. The recent advancement of metal-based theranostics including metallic nanoparticles, metal oxides, metal sulfides, nanocomposites, etc. has been explored at length in this article.

CONCLUSION

The review highlights emerging applications in terms of molecular imaging, targeted therapy and different diagnostic approaches of metal theranostics. Possible challenges faced by nanotheranostics in terms of clinical immersion and toxicological aspects which need to be addressed at depth are also discussed at the end.

Brain-computer interface to predict impulse buying behavior using functional near-infrared spectroscopy

As the rate of vaccination against COVID-19 is increasing, demand for overseas travel is also increasing. Despite people's preference for duty-free shopping, previous studies reported that duty-free shopping increases impulse buying behavior. There are also self-reported tools to measure their impulse buying behavior, but it has the disadvantage of relying on the human memory and perception. Therefore, we propose a Brain-Computer Interface (BCI)-based brain signal processing methodology to supplement these limitations and to reduce ambiguity and conjecture of data. To achieve this goal, we focused on the brain's prefrontal cortex (PFC) activity, which supervises human decision-making and is closely related to impulse buying behavior. The PFC activation is observed by recording signals using a functional near-infrared spectroscopy (fNIRS) while inducing impulse buying behavior in virtual computing environments. We found that impulse buying behaviors were not only higher in online duty-free shops than in online regular stores, but the fNIRS signals were also different on the two sites. We also achieved an average accuracy of 93.78% in detecting impulse buying patterns using a support vector machine. These results were identical to the people's self-reported responses. This study provides evidence as a potential biomarker for detecting impulse buying behavior with fNIRS.

Recent Progress in Lipid Nanoparticles for Cancer Theranostics: Opportunity and Challenges

Cancer is one of the major leading causes of mortality in the world. The implication of nanotherapeutics in cancer has garnered splendid attention owing to their capability to efficiently address various difficulties associated with conventional drug delivery systems such as non-specific biodistribution, poor efficacy, and the possibility of occurrence of multi-drug resistance. Amongst a plethora of nanocarriers for drugs, this review emphasized lipidic nanocarrier systems for delivering anticancer therapeutics because of their biocompatibility, safety, high drug loading and capability to simultaneously carrying imaging agent and ligands as well. Furthermore, to date, the lack of interaction between diagnosis and treatment has hampered the efforts of the nanotherapeutic approach alone to deal with cancer effectively. Therefore, a novel paradigm with concomitant imaging (with contrasting agents), targeting (with biomarkers), and anticancer agent being delivered in one lipidic nanocarrier system (as cancer theranostics) seems to be very promising in overcoming various hurdles in effective cancer treatment. The major obstacles that are supposed to be addressed by employing lipidic theranostic nanomedicine include nanomedicine reach to tumor cells, drug internalization in cancer cells for therapeutic intervention, off-site drug distribution, and uptake via the host immune system. A comprehensive account of recent research updates in the field of lipidic nanocarrier loaded with therapeutic and diagnostic agents is covered in the present article. Nevertheless, there are notable hurdles in the clinical translation of the lipidic theranostic nanomedicines, which are also highlighted in the present review along with plausible countermeasures.

Deep learning-enabled multi-organ segmentation in whole-body mouse scans

Whole-body imaging of mice is a key source of information for research. Organ segmentation is a prerequisite for quantitative analysis but is a tedious and error-prone task if done manually. Here, we present a deep learning solution called AIMOS that automatically segments major organs (brain, lungs, heart, liver, kidneys, spleen, bladder, stomach, intestine) and the skeleton in less than a second, orders of magnitude faster than prior algorithms. AIMOS matches or exceeds the segmentation quality of state-of-the-art approaches and of human experts. We exemplify direct applicability for biomedical research for localizing cancer metastases. Furthermore, we show that expert annotations are subject to human error and bias. As a consequence, we show that at least two independently created annotations are needed to assess model performance. Importantly, AIMOS addresses the issue of human bias by identifying the regions where humans are most likely to disagree, and thereby localizes and quantifies this uncertainty for improved downstream analysis. In summary, AIMOS is a powerful open-source tool to increase scalability, reduce bias, and foster reproducibility in many areas of biomedical research.

Direct Observation of Nanoparticles within Cells at Subcellular Levels by Super-Resolution Fluorescence Imaging

Direct observation of nanoparticles with high spatial resolution at subcellular levels is of great importance to understand the nanotoxicology and promote the biomedical applications of nanoparticles. Super-resolution fluorescence microscopy can break the diffraction resolution limit to achieve spatial resolution of tens of nanometers, making it ideal for highly accurate observation of nanoparticles in the cellular world. In this study, we introduced the employment of super-resolution fluorescence imaging for monitoring nanoparticles within cells. Carbocyanine dyes Alexa Flour 647 labeled mesoporous silica nanoparticles (designated as MSNs-AF647) were constructed as the super-resolution imaging nanoplatform in this work as proof of concept. The MSNs-AF647 were incubated with Hela cells, and the nanoparticles within cells were further monitored by super-resolution fluorescence microscopy. The fluorescence images of MSNs-AF647 within cells captured with the super-resolution fluorescence microscopy showed a much higher spatial resolution than that obtained using conventional fluorescence microscopy, showing that super-resolution fluorescence images can provide more accurate information to locate the nanoparticles at the subcellular levels. Moreover, other functional molecules can be easily loaded into the MSNs-AF647 super-resolution imaging nanoplatform, which suggested that super-resolution fluorescence imaging can further be applied to various bioimaging-related areas, such as imaging-guided therapy, with the aid of the MSNs-AF647 nanoplatform. This study demonstrates that super-resolution fluorescence microscopy offers a highly accurate method to study nanoparticles in the cellular world. We anticipate this strategy may further be applied to research areas such as studying the nanotoxicology and optimization of nanoparticle-based bioprobes or drugs by designing new nanostructured materials with multifunctional properties based on MSNs-AF647.