Meningioma grading via diagnostic imaging: A systematic review and meta-analysis.

PURPOSE: Meningioma is the most common intracranial tumor, graded on pathology using WHO criteria to predict tumor course and treatment. However, pathological grading via biopsy may not be possible in cases with poor surgical access due to tumor location. Therefore, our systematic review aims to evaluate whether diagnostic imaging features can differentiate high grade (HG) from low grade (LG) meningiomas as an alternative to pathological grading. METHODS: Three databases were searched for primary studies that either use routine magnetic resonance imaging (MRI) or computed tomography (CT) to assess pathologically WHO-graded meningiomas. Two investigators independently screened and extracted data from included studies. RESULTS: 24 studies met our inclusion criteria with 12 significant (p < 0.05) CT and MRI features identified for differentiating HG from LG meningiomas. Cystic changes in the tumor had the highest specificity (93.4%) and irregular tumor-brain interface had the highest positive predictive value (65.0%). Mass effect had the highest sensitivity (81.0%) and negative predictive value (90.7%) of all imaging features. Imaging feature with the highest accuracy for identifying HG disease was irregular tumor-brain interface (79.7%). Irregular tumor-brain interface and heterogenous tumor enhancement had the highest AUC values of 0.788 and 0.703, respectively. CONCLUSION: Our systematic review highlight imaging features that can help differentiate HG from LG meningiomas.

Measuring wellbeing: A scoping review of metrics and studies measuring medical student wellbeing across multiple timepoints.

PURPOSE: Studies have demonstrated poor mental health in medical students. However, there is wide variation in study design and metric use, impairing comparability. The authors aimed to examine the metrics and methods used to measure medical student wellbeing across multiple timepoints and identify where guidance is necessary. METHODS: Five databases were searched between May and June 2021 for studies using survey-based metrics among medical students at multiple timepoints. Screening and data extraction were done independently by two reviewers. Data regarding the manuscript, methodology, and metrics were analyzed. RESULTS: 221 studies were included, with 109 observational and 112 interventional studies. There were limited studies (15.4%) focused on clinical students. Stress management interventions were the most common (40.2%). Few (3.57%) interventional studies followed participants longer than 12 months, and 38.4% had no control group. There were 140 unique metrics measuring 13 constructs. 52.1% of metrics were used only once. CONCLUSIONS: Unique guidance is needed to address gaps in study design as well as unique challenges surrounding medical student wellbeing surveys. Metric use is highly variable and future research is necessary to identify metrics specifically validated in medical student samples that reflect the diversity of today's students.

Collagen - a newly discovered major player in protein corona formation on nanoparticles.

Tracking protein corona (PC) formation on the surface of nanoparticles (NPs) is a prerequisite for successful design of next generation nanocarriers with predictable fate and behavior. However, PC formation has mostly been investigated for plasma proteins without considering potential competition with the extravascular proteins either when the NPs exit the blood circulation or when they are injected extravascularly. This study investigates the deposition of collagen, an extravascular protein that is the most abundant in the body, and albumin, the most abundant vascular protein, on the surface of gold (Au) NPs using UV-Vis and fluorescence spectroscopy with the support of mathematical modeling. Moreover, a novel spectroscopic approach to determining the protein-NP binding constants and surface occupancy is presented. We show that albumin and collagen have drastically different affinities for Au NPs. Our data demonstrates that the surface bound albumin can be exchanged with collagen confirming the dynamic nature of PC in the extravascular milieu. We propose that future PC investigations in the framework of drug delivery should rely on understanding of the NP transit in the body, and include competition experiments with relevant vascular and extravascular proteins. Furthermore, our results that reveal very strong binding of collagen to AuNPs may lay the foundation for designing long circulating collagen-coated NPs with minimal surface adsorption of plasma proteins and, thus, reduced immune recognition.

Localized Plasmonic Photothermal Therapy as a Life-saving Treatment Paradigm for Hospitalized COVID-19 Patients.

Lung failure is the main reason for mortality in COVID-19 patients, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). To date, no drug has been clinically approved for treatment of COVID-19. Nanotechnology has a great potential in contributing significantly to the fight against COVID-19 by developing effective therapies that can selectively eradicate the respiratory virus load. We propose a novel COVID-19 management approach that is efficient in eliminating the virus load from the airways and protecting the lungs from the fatal effects of the virus. This approach relies on targeting the virus using ACE-2-functionalized gold nanorods (AuNRs) followed by irradiation with near-infrared (NIR) light for the selective eradication of SARS-CoV-2 without off-target effects, i.e., targeted plasmonic photothermal therapy. Using discrete dipole approximation (DDA), we quantitatively determined the efficiency of AuNRs (31 nm × 8 nm) in absorbing NIR when present at different orientations relative to one another on the surface of the virus. The safety and the local administration of AuNRs using a well-tolerated flexible bronchoscopy technique, commonly used for hospitalized COVID-19 patients, ensure feasibility and clinical translation. While requiring further research, we anticipate this approach to result in a first-line treatment for hospitalized COVID-19 patients that are experiencing severe respiratory conditions or belong to a high-risk population, e.g., seniors and diabetic patients.

Dynamic placenta-on-a-chip model for fetal risk assessment of nanoparticles intended to treat pregnancy-associated diseases.

Pregnant women often have to take medication either for pregnancy-related diseases or for previously existing medical conditions. Current maternal medications pose fetal risks due to off target accumulation in the fetus. Nanoparticles, engineered particles in the nanometer scale, have been used for targeted drug delivery to the site of action without off-target effects. This has opened new avenues for treatment of pregnancy-associated diseases while minimizing risks on the fetus. It is therefore instrumental to study the potential transfer of nanoparticles from the mother to the fetus. Due to limitations of in vivo and ex vivo models, an in vitro model mimicking the in vivo situation is essential. Placenta-on-a-chip provides a microphysiological recapitulation of the human placenta. Here, we reviewed the fetal risks associated with current therapeutic approaches during pregnancy, analyzed the advantages and limitations of current models used for nanoparticle assessment, and highlighted the current need for using dynamic placenta-on-a-chip models for assessing the safety of novel nanoparticle-based therapies during pregnancy.