Preclinical Characterization of ARX517, a Site-specific Stable PSMA-Targeted Antibody Drug Conjugate for Treatment of Metastatic Castration-Resistant Prostate Cancer.

Metastatic castration-resistant prostate cancer (mCRPC) is an advanced disease in which patients ultimately fail standard of care androgen-deprivation therapies and exhibit poor survival rates. The prostate-specific membrane antigen (PSMA) has been validated as a mCRPC tumor antigen with over-expression in tumors and low expression in healthy tissues. Using our proprietary technology for incorporating synthetic amino acids (SAAs) into proteins at selected sites, we have developed ARX517, an antibody drug conjugate (ADC) which is composed of a humanized anti-PSMA antibody site-specifically conjugated to a tubulin inhibitor at a drug-to-antibody ratio of 2. After binding PSMA, ARX517 is internalized and catabolized, leading to cytotoxic payload delivery and apoptosis. To minimize premature payload release and maximize delivery to tumor cells, ARX517 employs a non-cleavable PEG linker and stable oxime conjugation enabled via SAA protein incorporation to ensure its overall stability. In vitro studies demonstrate that ARX517 selectively induces cytotoxicity of PSMA-expressing tumor cell lines. ARX517 exhibited a long terminal half-life and high serum exposure in mice, and dose-dependent anti-tumor activity in both enzalutamide-sensitive and -resistant CDX and PDX prostate cancer models. Repeat dose toxicokinetic studies in non-human primates demonstrated ARX517 was tolerated at exposures well above therapeutic exposures in mouse pharmacology studies, indicating a wide therapeutic index. In summary, ARX517 inhibited tumor growth in diverse mCRPC models, demonstrated a tolerable safety profile in monkeys, and had a wide therapeutic index based on preclinical exposure data. Based on the encouraging preclinical data, ARX517 is currently being evaluated in a Phase 1 clinical trial ([NCT04662580]).

Targeted opening of the blood-brain barrier using VCAM-1 functionalised microbubbles and "whole brain" ultrasound.

Metastatic tumours in the brain now represent one of the leading causes of death from cancer. Current treatments are largely ineffective owing to the combination of late diagnosis and poor delivery of therapies across the blood-brain barrier (BBB). Conjugating magnetic resonance imaging (MRI) contrast agents with a monoclonal antibody for VCAM-1 (anti-VCAM1) has been shown to enable detection of micrometastases, two to three orders of magnitude smaller in volume than those currently detectable clinically. The aim of this study was to exploit this targeting approach to enable localised and temporary BBB opening at the site of early-stage metastases using functionalised microbubbles and ultrasound. Methods: Microbubbles functionalised with anti-VCAM1 were synthesised and shown to bind to VCAM-1-expressing cells in vitro. Experiments were then conducted in vivo in a unilateral breast cancer brain metastasis mouse model using Gadolinium-DTPA (Gd-DTPA) enhanced MRI to detect BBB opening. Following injection of Gd-DTPA and targeted microbubbles, the whole brain volume was simultaneously exposed to ultrasound (0.5 MHz, 10% duty cycle, 0.7 MPa peak negative pressure, 2 min treatment time). T1-weighted MRI was then performed to identify BBB opening, followed by histological confirmation via immunoglobulin G (IgG) immunohistochemistry. Results: In mice treated with targeted microbubbles and ultrasound, statistically significantly greater extravasation of Gd-DTPA and IgG was observed in the left tumour-bearing hemisphere compared to the right hemisphere 5 min after treatment. No acute adverse effects were observed. There was no investigation of longer term bioeffects owing to the nature of the study. Conclusion: The results demonstrate the feasibility of using targeted microbubbles in combination with low intensity ultrasound to localise opening of the BBB to metastatic sites in the brain. This approach has potential application in the treatment of metastatic tumours whose location cannot be established a priori with conventional imaging methods.

Lipidomic Risk Score to Enhance Cardiovascular Risk Stratification for Primary Prevention.

BACKGROUND: Accurate risk stratification is vital for primary prevention of cardiovascular disease (CVD). However, traditional tools such as the Framingham Risk Score (FRS) may underperform within the diverse intermediate-risk group, which includes individuals requiring distinct management strategies. OBJECTIVES: This study aimed to develop a lipidomic-enhanced risk score (LRS), specifically targeting risk prediction and reclassification within the intermediate group, benchmarked against the FRS. METHODS: The LRS was developed via a machine learning workflow using ridge regression on the Australian Diabetes, Obesity, and Lifestyle Study (AusDiab; n = 10,339). It was externally validated with the Busselton Health Study (n = 4,492), and its predictive utility for coronary artery calcium scoring (CACS)-based outcomes was independently validated in the BioHEART cohort (n = 994). RESULTS: LRS significantly improved discrimination metrics for the intermediate-risk group in both AusDiab and Busselton Health Study cohorts (all P < 0.001), increasing the area under the curve for CVD events by 0.114 (95% CI: 0.1123-0.1157) and 0.077 (95% CI: 0.0755-0.0785), with a net reclassification improvement of 0.36 (95% CI: 0.21-0.51) and 0.33 (95% CI: 0.15-0.49), respectively. For CACS-based outcomes in BioHEART, LRS achieved a significant area under the curve improvement of 0.02 over the FRS (0.76 vs 0.74; P < 1.0 × 10-5). A simplified, clinically applicable version of LRS was also created that had comparable performance to the original LRS. CONCLUSIONS: LRS, augmenting the FRS, presents potential to improve intermediate-risk stratification and to predict atherosclerotic markers using a simple blood test, suitable for clinical application. This could facilitate the triage of individuals for noninvasive imaging such as CACS, fostering precision medicine in CVD prevention and management.

The role of metals in hypothiocyanite resistance in Escherichia coli.

The innate immune system employs a variety of antimicrobial oxidants to control and kill host-associated bacteria. Hypothiocyanite/hypothiocyanous acid (-OSCN/HOSCN) is one such antimicrobial oxidant that is synthesized by lactoperoxidase, myeloperoxidase, and eosinophil peroxidase at sites throughout the human body. HOSCN has potent antibacterial activity while being largely non-toxic toward human cells. The molecular mechanisms by which bacteria sense and defend themselves against HOSCN have only recently begun to be elaborated, notably by the discovery of bacterial HOSCN reductase (RclA), an HOSCN-degrading enzyme widely conserved among bacteria that live on epithelial surfaces. In this paper, I show that Ni2+ sensitizes Escherichia coli to HOSCN by inhibiting glutathione reductase and that inorganic polyphosphate protects E. coli against this effect, probably by chelating Ni2+ ions. I also found that RclA is very sensitive to inhibition by Cu2+ and Zn2+, metals that are accumulated to high levels by innate immune cells, and that, surprisingly, thioredoxin and thioredoxin reductase are not involved in HOSCN stress resistance in E. coli. These results advance our understanding of the contribution of different oxidative stress responses and redox buffering pathways to HOSCN resistance in E. coli and illustrate important interactions between metal ions and the enzymes bacteria use to defend themselves against oxidative stress. IMPORTANCE: Hypothiocyanite (HOSCN) is an antimicrobial oxidant produced by the innate immune system. The molecular mechanisms by which host-associated bacteria defend themselves against HOSCN have only recently begun to be understood. The results in this paper are significant because they show that the low molecular weight thiol glutathione and enzyme glutathione reductase are critical components of the Escherichia coli HOSCN response, working by a mechanism distinct from that of the HOSCN-specific defenses provided by the RclA, RclB, and RclC proteins and that metal ions (including nickel, copper, and zinc) may impact the ability of bacteria to resist HOSCN by inhibiting specific defensive enzymes (e.g., glutathione reductase or RclA).

Health economic analysis of polygenic risk score use in primary prevention of coronary artery disease - A system dynamics model.

Background: Primary prevention programs utilising traditional risk scores fail to identify all individuals who suffer acute cardiovascular events. We aimed to model the impact and cost effectiveness of incorporating a Polygenic risk scores (PRS) into the cardiovascular disease CVD primary prevention program in Australia, using a whole-of-system model. Methods: System dynamics models, encompassing acute and chronic CVD care in the Australian healthcare setting, assessing the cost-effectiveness of incorporating a CAD-PRS in the primary prevention setting. The time horizon was 10-years. Results: Pragmatically incorporating a CAD-PRS in the Australian primary prevention setting in middle-aged individuals already attending a Heart Health Check (HHC) who are determined to be at low or moderate risk based on the 5-year Framingham risk score (FRS), with conservative assumptions regarding uptake of PRS, could have prevented 2, 052 deaths over 10-years, and resulted in 24, 085 QALYs gained at a cost of $19, 945 per QALY with a net benefit of $724 million. If all Australians overs the age of 35 years old had their FRS and PRS performed, and acted upon, 12, 374 deaths and 60, 284 acute coronary events would be prevented, with 183, 682 QALYs gained at a cost of $18, 531 per QALY, with a net benefit of $5, 780 million. Conclusions: Incorporating a CAD-PRS in a contemporary primary prevention setting in Australia would result in substantial health and societal benefits and is cost-effective. The broader the uptake of CAD-PRS in the primary prevention setting in middle-aged Australians, the greater the impact and the more cost-effective the strategy.

C-terminal Poly-histidine Tags Alter Escherichia coli Polyphosphate Kinase Activity and Susceptibility to Inhibition.

In Escherichia coli, many environmental stressors trigger polyphosphate (polyP) synthesis by polyphosphate kinase (PPK1), including heat, nutrient restriction, toxic compounds, and osmotic imbalances. PPK1 is essential for virulence in many pathogens and has been the target of multiple screens for small molecule inhibitors that might serve as new anti-virulence drugs. However, the mechanisms by which PPK1 activity and polyP synthesis are regulated are poorly understood. Our previous attempts to uncover PPK1 regulatory elements resulted in the discovery of PPK1* mutants, which accumulate more polyP in vivo, but do not produce more in vitro. In attempting to further characterize these mutant enzymes, we discovered that the most commonly-used PPK1 purification method - Ni-affinity chromatography using a C-terminal poly-histidine tag - altered intrinsic aspects of the PPK1 enzyme, including specific activity, oligomeric state, and kinetic values. We developed an alternative purification strategy using a C-terminal C-tag which did not have these effects. Using this strategy, we were able to demonstrate major differences in the in vitro response of PPK1 to 5-aminosalicylic acid, a known PPK1 inhibitor, and observed several key differences between the wild-type and PPK1* enzymes, including changes in oligomeric distribution, increased enzymatic activity, and increased resistance to both product (ADP) and substrate (ATP) inhibition, that help to explain their in vivo effects. Importantly, our results indicate that the C-terminal poly-histidine tag is inappropriate for purification of PPK1, and that any in vitro studies or inhibitor screens performed with such tags need to be reconsidered in that light.

Proteobacteria impair anti-tumor immunity in the omentum by consuming arginine.

Gut microbiota influence anti-tumor immunity, often by producing immune-modulating metabolites. However, microbes consume a variety of metabolites that may also impact host immune responses. We show that tumors grow unchecked in the omenta of microbe-replete mice due to immunosuppressive Tregs. By contrast, omental tumors in germ-free, neomycin-treated mice or mice colonized with altered Schaedler's flora (ASF) are spontaneously eliminated by CD8+ T cells. These mice lack Proteobacteria capable of arginine catabolism, causing increases in serum arginine that activate the mammalian target of the rapamycin (mTOR) pathway in Tregs to reduce their suppressive capacity. Transfer of the Proteobacteria, Escherichia coli (E. coli), but not a mutant unable to catabolize arginine, to ASF mice reduces arginine levels, restores Treg suppression, and prevents tumor clearance. Supplementary arginine similarly decreases Treg suppressive capacity, increases CD8+ T cell effectiveness, and reduces tumor burden. Thus, microbial consumption of arginine alters anti-tumor immunity, offering potential therapeutic strategies for tumors in visceral adipose tissue.

Determination of Bovine Lactoferrin in Powdered Infant Formula and Adult Nutritionals by Heparin Affinity Extraction and Reverse-Phase High-Performance Liquid Chromatography/Ultraviolet Detection (HPLC/UV): Single-Laboratory Validation, First Action 2021.10.

BACKGROUND: Infant formulas, and pediatric and adult nutritional products, are being fortified with bovine lactoferrin (bLF) due to its beneficial impacts on immune development and gut health. Lactoferrin supplementation into these products requires an analytical method to accurately quantify the concentrations of bLF to meet global regulatory and quality standards. OBJECTIVE: To develop and validate a lactoferrin method capable of meeting the AOAC INTERNATIONAL Standard Method Performance Requirements (SMPR®) 2020.005. METHODS: Powder formula samples are extracted using warm dibasic phosphate buffer, pH 8, then centrifuged at 4°C to remove insoluble proteins, fat, and other solids. The soluble fraction is further purified on a HiTrap heparin solid-phase extraction (SPE) column to isolate bLF from interferences. Samples are filtered, then analyzed by LC-UV using a protein BEH C4 analytical column and quantitated using an external calibrant. RESULTS: The LOQ (2 mg/100 g), repeatability (RSD: 2.0-4.8%), recovery (92.1-97.7%), and analytical range (4-193 mg/100 g) all meet the method requirements as stated in SMPR 2020.005 for lactoferrin. CONCLUSION: The reported single-laboratory validation (SLV) results demonstrate the ability of this lactoferrin method to meet or exceed the method performance requirements to measure soluble, intact, non-denatured bLF in infant and adult nutritional powder formulas. HIGHLIGHTS: The use of a heparin affinity column to isolate lactoferrin from bovine milk products combined with a selective analytical chromatographic column provides suitable analyte specificity without requiring proprietary equipment or reagents.

Quantifying lung fissure integrity using a three-dimensional patch-based convolutional neural network on CT images for emphysema treatment planning.

Purpose: Evaluation of lung fissure integrity is required to determine whether emphysema patients have complete fissures and are candidates for endobronchial valve (EBV) therapy. We propose a deep learning (DL) approach to segment fissures using a three-dimensional patch-based convolutional neural network (CNN) and quantitatively assess fissure integrity on CT to evaluate it in subjects with severe emphysema. Approach: From an anonymized image database of patients with severe emphysema, 129 CT scans were used. Lung lobe segmentations were performed to identify lobar regions, and the boundaries among these regions were used to construct approximate interlobar regions of interest (ROIs). The interlobar ROIs were annotated by expert image analysts to identify voxels where the fissure was present and create a reference ROI that excluded non-fissure voxels (where the fissure is incomplete). A CNN configured by nnU-Net was trained using 86 CT scans and their corresponding reference ROIs to segment the ROIs of left oblique fissure (LOF), right oblique fissure (ROF), and right horizontal fissure (RHF). For an independent test set of 43 cases, fissure integrity was quantified by mapping the segmented fissure ROI along the interlobar ROI. A fissure integrity score (FIS) was then calculated as the percentage of labeled fissure voxels divided by total voxels in the interlobar ROI. Predicted FIS (p-FIS) was quantified from the CNN output, and statistical analyses were performed comparing p-FIS and reference FIS (r-FIS). Results: The absolute percent error mean (±SD) between r-FIS and p-FIS for the test set was 4.0% (±4.1%), 6.0% (±9.3%), and 12.2% (±12.5%) for the LOF, ROF, and RHF, respectively. Conclusions: A DL approach was developed to segment lung fissures on CT images and accurately quantify FIS. It has potential to assist in the identification of emphysema patients who would benefit from EBV treatment.

MIDRC-MetricTree: a decision tree-based tool for recommending performance metrics in artificial intelligence-assisted medical image analysis.

Purpose: The Medical Imaging and Data Resource Center (MIDRC) was created to facilitate medical imaging machine learning (ML) research for tasks including early detection, diagnosis, prognosis, and assessment of treatment response related to the coronavirus disease 2019 pandemic and beyond. The purpose of this work was to create a publicly available metrology resource to assist researchers in evaluating the performance of their medical image analysis ML algorithms. Approach: An interactive decision tree, called MIDRC-MetricTree, has been developed, organized by the type of task that the ML algorithm was trained to perform. The criteria for this decision tree were that (1) users can select information such as the type of task, the nature of the reference standard, and the type of the algorithm output and (2) based on the user input, recommendations are provided regarding appropriate performance evaluation approaches and metrics, including literature references and, when possible, links to publicly available software/code as well as short tutorial videos. Results: Five types of tasks were identified for the decision tree: (a) classification, (b) detection/localization, (c) segmentation, (d) time-to-event (TTE) analysis, and (e) estimation. As an example, the classification branch of the decision tree includes two-class (binary) and multiclass classification tasks and provides suggestions for methods, metrics, software/code recommendations, and literature references for situations where the algorithm produces either binary or non-binary (e.g., continuous) output and for reference standards with negligible or non-negligible variability and unreliability. Conclusions: The publicly available decision tree is a resource to assist researchers in conducting task-specific performance evaluations, including classification, detection/localization, segmentation, TTE, and estimation tasks.

Assessing variability in non-contrast CT for the evaluation of stroke: The effect of CT image reconstruction conditions on AI-based CAD measurements of ASPECTS value and hypodense volume.

Purpose: To rule out hemorrhage, non-contrast CT (NCCT) scans are used for early evaluation of patients with suspected stroke. Recently, artificial intelligence tools have been developed to assist with determining eligibility for reperfusion therapies by automating measurement of the Alberta Stroke Program Early CT Score (ASPECTS), a 10-point scale with > 7 or ≤ 7 being a threshold for change in functional outcome prediction and higher chance of symptomatic hemorrhage, and hypodense volume. The purpose of this work was to investigate the effects of CT reconstruction kernel and slice thickness on ASPECTS and hypodense volume. Methods: The NCCT series image data of 87 patients imaged with a CT stroke protocol at our institution were reconstructed with 3 kernels (H10s-smooth, H40s-medium, H70h-sharp) and 2 slice thicknesses (1.5mm and 5mm) to create a reference condition (H40s/5mm) and 5 non-reference conditions. Each reconstruction for each patient was analyzed with the Brainomix e-Stroke software (Brainomix, Oxford, England) which yields an ASPECTS value and measure of total hypodense volume (mL). Results: An ASPECTS value was returned for 74 of 87 cases in the reference condition (13 failures). ASPECTS in non-reference conditions changed from that measured in the reference condition for 59 cases, 7 of which changed above or below the clinical threshold of 7 for 3 non-reference conditions. ANOVA tests were performed to compare the differences in protocols, Dunnett's post-hoc tests were performed after ANOVA, and a significance level of p < 0.05 was defined. There was no significant effect of kernel (p = 0.91), a significant effect of slice thickness (p < 0.01) and no significant interaction between these factors (p = 0.91). Post-hoc tests indicated no significant difference between ASPECTS estimated in the reference and any non-reference conditions. There was a significant effect of kernel (p < 0.01) and slice thickness (p < 0.01) on hypodense volume, however there was no significant interaction between these factors (p = 0.79). Post-hoc tests indicated significantly different hypodense volume measurements for H10s/1.5mm (p = 0.03), H40s/1.5mm (p < 0.01), H70h/5mm (p < 0.01). No significant difference was found in hypodense volume measured in the H10s/5mm condition (p = 0.96). Conclusion: Automated ASPECTS and hypodense volume measurements can be significantly impacted by reconstruction kernel and slice thickness.

Genetic testing in cardiovascular disease.

Cardiovascular disease (CVD) is the leading cause of morbidity and mortality globally and is responsible for an estimated one-third of deaths as well as significant morbidity and health care utilisation. Technological and bioinformatic advances have facilitated the discovery of pathogenic germline variants for some specific CVDs, including familial hypercholesterolaemia, cardiomyopathies and arrhythmic syndromes. Use of these genetic tests for earlier disease identification is increasing due, in part, to decreasing costs, Medicare rebates, and consumer comfort with genetic testing. However, CVDs that occur more commonly, including coronary artery disease and atrial fibrillation, do not display monogenic inheritance patterns. Genetically, these diseases have generally been associated with many genetic variants each with a small effect size. This complexity can be expressed mathematically as a polygenic risk score. Genetic testing kits that provide polygenic risk scoring are becoming increasingly available directly to private-paying consumers outside the traditional clinical setting. An improved understanding of the evidence of genetics in CVD will offer clinicians new opportunities for individualised risk prediction and preventive therapy.

The role of metals in hypothiocyanite resistance in Escherichia coli.

The innate immune system employs a variety of antimicrobial oxidants to control and kill host-associated bacteria. Hypothiocyanite/hypothiocyanous acid (-OSCN/HOSCN) is one such antimicrobial oxidant that is synthesized by lactoperoxidase, myeloperoxidase, and eosinophil peroxidase at sites throughout the human body. HOSCN has potent antibacterial activity while being largely non-toxic towards human cells. The molecular mechanisms by which bacteria sense and defend themselves against HOSCN have only recently begun to be elaborated, notably by the discovery of bacterial HOSCN reductase (RclA), an HOSCN-degrading enzyme widely conserved among bacteria that live on epithelial surfaces. In this paper, I show that Ni2+ sensitizes Escherichia coli to HOSCN by inhibiting glutathione reductase, and that inorganic polyphosphate protects E. coli against this effect, probably by chelating Ni2+ ions. I also found that RclA is very sensitive to inhibition by Cu2+ and Zn2+, metals that are accumulated to high levels by innate immune cells, and that, surprisingly, thioredoxin and thioredoxin reductase are not involved in HOSCN stress resistance in E. coli. These results advance our understanding of the contribution of different oxidative stress response and redox buffering pathways to HOSCN resistance in E. coli and illustrate important interactions between metal ions and the enzymes bacteria use to defend themselves against oxidative stress.

Quantitative Computed Tomography Lung COVID Scores with Laboratory Markers: Utilization to Predict Rapid Progression and Monitor Longitudinal Changes in Patients with Coronavirus 2019 (COVID-19) Pneumonia.

Coronavirus disease 2019 (COVID-19), is an ongoing issue in certain populations, presenting rapidly worsening pneumonia and persistent symptoms. This study aimed to test the predictability of rapid progression using radiographic scores and laboratory markers and present longitudinal changes. This retrospective study included 218 COVID-19 pneumonia patients admitted at the Chungnam National University Hospital. Rapid progression was defined as respiratory failure requiring mechanical ventilation within one week of hospitalization. Quantitative COVID (QCOVID) scores were derived from high-resolution computed tomography (CT) analyses: (1) ground glass opacity (QGGO), (2) mixed diseases (QMD), and (3) consolidation (QCON), and the sum, quantitative total lung diseases (QTLD). Laboratory data, including inflammatory markers, were obtained from electronic medical records. Rapid progression was observed in 9.6% of patients. All QCOVID scores predicted rapid progression, with QMD showing the best predictability (AUC = 0.813). In multivariate analyses, the QMD score and interleukin(IL)-6 level were important predictors for rapid progression (AUC = 0.864). With >2 months follow-up CT, remained lung lesions were observed in 21 subjects, even after several weeks of negative reverse transcription polymerase chain reaction test. AI-driven quantitative CT scores in conjugation with laboratory markers can be useful in predicting the rapid progression and monitoring of COVID-19.

Sound speed and attenuation of human pancreas and pancreatic tumors and their influence on focused ultrasound thermal and mechanical therapies.

BACKGROUND: There is increasing interest in using ultrasound for thermal ablation, histotripsy, and thermal or cavitational enhancement of drug delivery for the treatment of pancreatic cancer. Ultrasonic and thermal modelling conducted as part of the treatment planning process requires acoustic property values for all constituent tissues, but the literature contains no data for the human pancreas. PURPOSE: This study presents the first acoustic property measurements of human pancreatic samples and provides examples of how these properties impact a broad range of ultrasound therapies. METHODS: Data were collected on human pancreatic tissue samples at physiological temperature from 23 consented patients in cooperation with a hospital pathology laboratory. Propagation of ultrasound over the 2.1-4.5 MHz frequency range through samples of various thicknesses and pathologies was measured using a set of custom-built ultrasonic calipers, with the data processed to estimate sound speed and attenuation. The results were used in acoustic and thermal simulations to illustrate the impacts on extracorporeal ultrasound therapies for mild hyperthermia, thermal ablation, and histotripsy implemented with a CE-marked clinical system operating at 0.96 MHz. RESULTS: The mean sound speed and attenuation coefficient values for human samples were well below the range of values in the literature for non-human pancreata, while the human attenuation power law exponents were substantially higher. The simulated impacts on ultrasound mediated therapies for the pancreas indicated that when using the human data instead of the literature average, there was a 30% reduction in median temperature elevation in the treatment volume for mild hyperthermia and 43% smaller volume within a 60°C contour for thermal ablation, all driven by attenuation. By comparison, impacts on boiling and intrinsic threshold histotripsy were minor, with peak pressures changing by less than 15% (positive) and 1% (negative) as a consequence of the counteracting effects of attenuation and sound speed. CONCLUSION: This study provides the most complete set of speed of sound and attenuation data available for the human pancreas, and it reiterates the importance of acoustic material properties in the planning and conduct of ultrasound-mediated procedures, particularly thermal therapies.

Protein-Decorated Microbubbles for Ultrasound-Mediated Cell Surface Manipulation.

Delivering cargo to the cell membranes of specific cell types in the body is a major challenge for a range of treatments, including immunotherapy. This study investigates employing protein-decorated microbubbles (MBs) and ultrasound (US) to "tag" cellular membranes of interest with a specific protein. Phospholipid-coated MBs were produced and functionalized with a model protein using a metallochelating complex through an NTA(Ni) and histidine residue interaction. Successful "tagging" of the cellular membrane was observed using microscopy in adherent cells and was promoted by US exposure. Further modification of the MB surface to enable selective binding to target cells was then achieved by functionalizing the MBs with a targeting protein (transferrin) that specifically binds to a receptor on the target cell membrane. Attachment and subsequent transfer of material from MBs functionalized with transferrin to the target cells significantly increased, even in the absence of US. This work demonstrates the potential of these MBs as a platform for the noninvasive delivery of proteins to the surface of specific cell types.

Sonosensitive Cavitation Nuclei-A Customisable Platform Technology for Enhanced Therapeutic Delivery.

Ultrasound-mediated cavitation shows great promise for improving targeted drug delivery across a range of clinical applications. Cavitation nuclei-sound-sensitive constructs that enhance cavitation activity at lower pressures-have become a powerful adjuvant to ultrasound-based treatments, and more recently emerged as a drug delivery vehicle in their own right. The unique combination of physical, biological, and chemical effects that occur around these structures, as well as their varied compositions and morphologies, make cavitation nuclei an attractive platform for creating delivery systems tuned to particular therapeutics. In this review, we describe the structure and function of cavitation nuclei, approaches to their functionalization and customization, various clinical applications, progress toward real-world translation, and future directions for the field.

Sequestration of imaging studies in MIDRC: stratified sampling to balance demographic characteristics of patients in a multi-institutional data commons.

Purpose: The Medical Imaging and Data Resource Center (MIDRC) is a multi-institutional effort to accelerate medical imaging machine intelligence research and create a publicly available image repository/commons as well as a sequestered commons for performance evaluation and benchmarking of algorithms. After de-identification, approximately 80% of the medical images and associated metadata become part of the open commons and 20% are sequestered from the open commons. To ensure that both commons are representative of the population available, we introduced a stratified sampling method to balance the demographic characteristics across the two datasets. Approach: Our method uses multi-dimensional stratified sampling where several demographic variables of interest are sequentially used to separate the data into individual strata, each representing a unique combination of variables. Within each resulting stratum, patients are assigned to the open or sequestered commons. This algorithm was used on an example dataset containing 5000 patients using the variables of race, age, sex at birth, ethnicity, COVID-19 status, and image modality and compared resulting demographic distributions to naïve random sampling of the dataset over 2000 independent trials. Results: Resulting prevalence of each demographic variable matched the prevalence from the input dataset within one standard deviation. Mann-Whitney U test results supported the hypothesis that sequestration by stratified sampling provided more balanced subsets than naïve randomization, except for demographic subcategories with very low prevalence. Conclusions: The developed multi-dimensional stratified sampling algorithm can partition a large dataset while maintaining balance across several variables, superior to the balance achieved from naïve randomization.