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Non-targeted analysis (NTA) using high-resolution mass spectrometry has enabled the detection and identification of unknown and unexpected compounds of interest in a wide range of sample matrices. Despite these benefits of NTA methods, standardized procedures do not yet exist for assessing performance, limiting stakeholders’ abilities to suitably interpret and utilize NTA results. Herein, we first summarize existing performance assessment metrics for targeted analyses to provide context and clarify terminology that may be shared between targeted and NTA methods (e.g., terms such as accuracy, precision, sensitivity, and selectivity). We then discuss promising approaches for assessing NTA method performance, listing strengths and key caveats for each approach, and highlighting areas in need of further development. To structure the discussion, we define three types of NTA study objectives: sample classification, chemical identification, and chemical quantitation. Qualitative study performance (i.e., focusing on sample classification and/or chemical identification) can be assessed using the traditional confusion matrix, with some challenges and limitations. Quantitative study performance can be assessed using estimation procedures developed for targeted methods with consideration for additional sources of uncontrolled experimental error. This article is intended to stimulate discussion and further efforts to develop and improve procedures for assessing NTA method performance. Ultimately, improved performance assessments will enable accurate communication and effective utilization of NTA results by stakeholders.

Background Imaging data contains a substantial amount of information which can be difficult to evaluate by eye. With the expansion of high throughput microscopy methodologies producing increasingly large datasets, automated and objective analysis of the resulting images is essential to effectively extract biological information from this data. CellProfiler is a free, open source image analysis program which enables researchers to generate modular pipelines with which to process microscopy images into interpretable measurements. Results Herein we describe CellProfiler 4, a new version of this software with expanded functionality. Based on user feedback, we have made several user interface refinements to improve the usability of the software. We introduced new modules to expand the capabilities of the software. We also evaluated performance and made targeted optimizations to reduce the time and cost associated with running common large-scale analysis pipelines. Conclusions CellProfiler 4 provides significantly improved performance in complex workflows compared to previous versions. This release will ensure that researchers will have continued access to CellProfiler’s powerful computational tools in the coming years.

Coronavirus disease 2019 (COVID-19) is a highly contagious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Diagnosis of COVID-19 depends on quantitative reverse transcription PCR (qRT-PCR), which is time-consuming and requires expensive instrumentation. Here, we report an ultrasensitive electrochemical biosensor based on isothermal rolling circle amplification (RCA) for rapid detection of SARS-CoV-2. The assay involves the hybridization of the RCA amplicons with probes that were functionalized with redox active labels that are detectable by an electrochemical biosensor. The one-step sandwich hybridization assay could detect as low as 1 copy/μL of N and S genes, in less than 2 h. Sensor evaluation with 106 clinical samples, including 41 SARS-CoV-2 positive and 9 samples positive for other respiratory viruses, gave a 100% concordance result with qRT-PCR, with complete correlation between the biosensor current signals and quantitation cycle (Cq) values. In summary, this biosensor could be used as an on-site, real-time diagnostic test for COVID-19. Currently the most common method of COVID-19 diagnosis is by qRT-PCR which is slow and requires expensive instrumentation. Here the authors report an electrochemical biosensor based on isothermal rolling circle amplification for rapid detection of SARS-CoV-2 in clinical samples.

Oxygen-derived free radicals and related oxidants are ubiquitous and short-lived intermediates formed in aerobic organisms throughout life. These reactive species participate in redox reactions leading to oxidative modifications in biomolecules, among which proteins and lipids are preferential targets. Despite a broad array of enzymatic and nonenzymatic antioxidant systems in mammalian cells and microbes, excess oxidant formation causes accumulation of new products that may compromise cell function and structure leading to cell degeneration and death. Oxidative events are associated with pathological conditions and the process of normal aging. Notably, physiological levels of oxidants also modulate cellular functions via homeostatic redox-sensitive cell signaling cascades. On the other hand, nitric oxide (•NO), a free radical and weak oxidant, represents a master physiological regulator via reversible interactions with heme proteins. The bioavailability and actions of •NO are modulated by its fast reaction with superoxide radical ( O 2 • − ), which yields an unusual and reactive peroxide, peroxynitrite, representing the merging of the oxygen radicals and •NO pathways. In this Inaugural Article, I summarize early and remarkable developments in free radical biochemistry and the later evolution of the field toward molecular medicine; this transition includes our contributions disclosing the relationship of •NO with redox intermediates and metabolism. The biochemical characterization, identification, and quantitation of peroxynitrite and its role in disease processes have concentrated much of our attention. Being a mediator of protein oxidation and nitration, lipid peroxidation, mitochondrial dysfunction, and cell death, peroxynitrite represents both a pathophysiologically relevant endogenous cytotoxin and a cytotoxic effector against invading pathogens.

HIV prevention and treatment with injectable cabotegravir and/or rilpivirine administered once every 4 to 8 weeks is an attractive alternative to daily therapy. Prescribed dosage and drug concentrations in plasma are based on patient data collected in clinical trials, but actual patients are expected to exhibit more variability in drug concentrations, which is important to quantify. Here, we demonstrate the first quantitative point-of-care assay with a miniature mass spectrometer to assess these drug concentrations in whole blood. Quantitative performance is obtained using paper spray ionization in combination with tandem mass spectrometry (MS/MS) in the clinically relevant concentration range of both drugs. Limits of quantitation (LoQs) of cabotegravir and rilpivirine are measured to be 750 ng/mL and 20 ng/mL, respectively. The assay turnaround time is < 4 min, and strong linear relationships are established between MS/MS responses and concentration, with percentage of relative standard deviations (RSDs) that are <15% at concentrations above the LoQs. The speed, portability, low power consumption, and specificity offered by the miniature instrument should make it an appropriate platform for measuring drug concentrations in a walk-in clinic using small volumes of patient blood.

High throughput drug screening is an established approach to investigate tumor biology and identify therapeutic leads. Traditional platforms use two-dimensional cultures which do not accurately reflect the biology of human tumors. More clinically relevant model systems such as three-dimensional tumor organoids can be difficult to scale and screen. Manually seeded organoids coupled to destructive endpoint assays allow for the characterization of treatment response, but do not capture transitory changes and intra-sample heterogeneity underlying clinically observed resistance to therapy. We present a pipeline to generate bioprinted tumor organoids linked to label-free, time-resolved imaging via high-speed live cell interferometry (HSLCI) and machine learning-based quantitation of individual organoids. Bioprinting cells gives rise to 3D structures with unaltered tumor histology and gene expression profiles. HSLCI imaging in tandem with machine learning-based segmentation and classification tools enables accurate, label-free parallel mass measurements for thousands of organoids. We demonstrate that this strategy identifies organoids transiently or persistently sensitive or resistant to specific therapies, information that could be used to guide rapid therapy selection. Traditional 2D cell culture platforms do not accurately reflect the physiology of human tumors. Here, authors combine bioprinting and high-speed live cell interferometry with machine learning to measure drug sensitivity at single-organoid resolution in a label-free manner.

We have developed a method for in vivo quantitation of lung delivery of inhaled nebulized drugs by measuring a fluorescent-labeled analog in bronchioalveolar lavage fluid (BALF) collected immediately after inhalation dosing. The effectiveness of delivery of an aerosolized formulation of our proprietary water-miscible vitamin A product to the deep lung (target organ) was studied; the product is being developed for prevention of bronchopulmonary dysplasia (BPD) in preterm infants. The fluorescent retinol analog was incorporated by spiking into a standard formulation, remaining fully compatible with existing nebulizer administration procedures for animal exposure. The method provides quantitation of the delivered dose (DD) to the lung within a few minutes after dosing; fluorescence in BAL in a plate reader allows for simple rapid quantitation of the delivered drug, while avoiding the complexities of other labeling methods (e.g., heavy labels or radioactivity). Data from newborn rat and lamb models showed linear dose responses, validating the method. Approximately 5–10% of the inhaled drug was recovered in BALF in both models, consistent with reports in the literature. The ease of use of the method facilitated various aspects of our project, including the transition to more clinically relevant animal models and aerosol exposure systems. The formulation of this approach could be spiked into other formulations, allowing application of the method to other aerosol drug development programs.

ObjectiveThere is a need for an improved biomarker for colorectal cancer (CRC) and advanced adenoma. We evaluated faecal microbial markers for clinical use in detecting CRC and advanced adenoma.DesignWe measured relative abundance of Fusobacterium nucleatum (Fn), Peptostreptococcus anaerobius (Pa) and Parvimonas micra (Pm) by quantitative PCR in 309 subjects, including 104 patients with CRC, 103 patients with advanced adenoma and 102 controls. We evaluated the diagnostic performance of these biomarkers with respect to faecal immunochemical test (FIT), and validated the results in an independent cohort of 181 subjects.ResultsThe abundance was higher for all three individual markers in patients with CRC than controls (p<0.001), and for marker Fn in patients with advanced adenoma than controls (p=0.022). The marker Fn, when combined with FIT, showed superior sensitivity (92.3% vs 73.1%, p<0.001) and area under the receiver-operating characteristic curve (AUC) (0.95 vs 0.86, p<0.001) than stand-alone FIT in detecting CRC in the same patient cohort. This combined test also increased the sensitivity (38.6% vs 15.5%, p<0.001) and AUC (0.65 vs 0.57, p=0.007) for detecting advanced adenoma. The performance gain for both CRC and advanced adenoma was confirmed in the validation cohort (p=0.0014 and p=0.031, respectively).ConclusionsThis study identified marker Fn as a valuable marker to improve diagnostic performance of FIT, providing a complementary role to detect lesions missed by FIT alone. This simple approach may improve the clinical utility of the current FIT, and takes one step further towards a non-invasive, potentially more accurate and affordable diagnosis of advanced colorectal neoplasia.

This exploratory study compared doses of ferucarbotran, a superparamagnetic iron oxide nanoparticle, in sentinel lymph nodes (SLNs) and quantified the SLN iron load by dose and localization. Eighteen females aged ≥20 years scheduled for an SLN biopsy with node-negative breast cancer were divided into two equal groups and administered either 1 mL or 0.5 mL ferucarbotran. Iron content was evaluated with a handheld magnetometer and quantification device. The average iron content was 42.8 µg (range, 1.3–95.0; 0.15% of the injected dose) and 21.9 µg (1.1–71.0; 0.16%) in the 1-mL and 0.5-mL groups, respectively (p = 0.131). The iron content of the closest SLN compared to the second SLN was 53.0 vs. 10.0 µg (19% of the injected dose) and 34.8 vs. 4.1 µg (11.1%) for the 1-mL and 0.5-mL groups, respectively (p = 0.001 for both). The magnetic field was high in both groups (average 7.30 µT and 6.00 µT in the 1-mL and 0.5-mL groups, respectively) but was not statistically significant (p = 0.918). The magnetic field and iron content were correlated (overall SLNs, p = 0.02; 1-mL, p = 0.014; 0.5-mL, p = 0.010). A 0.5-mL dose was sufficient for SLN identification. Primary and secondary SLNs could be differentiated based on iron content. Handheld magnetometers could be used to assess the SLN iron content.