An official website of the United States government
Abstract Immunotherapies have shown promising results in treating patients with hematological malignancies like multiple myeloma, which is an incurable but treatable bone marrow-resident plasma cell cancer. Choosing the most efficacious treatment for a patient remains a challenge in such cancers. However, pre-clinical assays involving patient-derived tumor cells co-cultured in anex vivoreconstruction of immune-tumor micro-environment have gained considerable notoriety over the past decade. Such assays can characterize a patient’s response to several therapeutic agents including immunotherapies in a high-throughput manner, where bright-field images of tumor (target) cells interacting with effector cells (T cells, Natural Killer (NK) cells, and macrophages) are captured once every 30 minutes for upto six days. Cell detection, tracking, and classification of thousands of cells of two or more types in each frame is bound to test the limits of some of the most advanced computer vision tools developed to date and requires a specialized approach. We propose TLCellClassifier (time-lapse cell classifier) for live cell detection, cell tracking, and cell type classification, with enhanced accuracy and efficiency obtained by integrating convolutional neural networks (CNN), metric learning, and long short-term memory (LSTM) networks, respectively. State-of-the-art computer vision software like KTH-SE and YOLOv8 are compared with TLCellClassifier, which shows improved accuracy in detection (CNN) and tracking (metric learning). A two-stage LSTM-based cell type classification method is implemented to distinguish between multiple myeloma (tumor/target) cells and macrophages/monocytes (immune/effector cells). Validation of cell type classification was done both using synthetic datasets andex vivoexperiments involving patient-derived tumor/immune cells. Availability and implementationhttps://github.com/QibingJiang/cell classification ml
more »
« less
Facile and Sensitive Detection of Nitrogen-Containing Organic Bases with Near Infrared C-Dots Derived Assays
In this article, we have designed both colorimetric (including solution and test paper type) and spectral sensors (including UV-vis and PL type) for the quick and sensitive detection of general nitrogen-containing organic bases (NCOBs); the limit of detection could reach as low as 0.50 nM. NCOBs included 11 examples, covering aliphatic and aromatic amines, five- and six-membered heterocyclics, fused-ring heterocyclics, amino acids, and antibiotics. Furthermore, the assays demonstrated high reliability in sensing NCOBs and excellent ability to distinguish NCOBs from oxygen and sulfur containing organics. The assays developed could find important applications for the detection of NCOBs in the fields of biomedicine, chemistry, and agriculture.
more »
« less
- Award ID(s):
- 2041413
- PAR ID:
- 10350450
- Date Published:
- Journal Name:
- Nanomaterials
- Volume:
- 11
- Issue:
- 10
- ISSN:
- 2079-4991
- Page Range / eLocation ID:
- 2607
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
null (Ed.)Quantification of cell-secreted molecules, e.g. , cytokines, is fundamental to the characterization of immune responses. Cytokine capture assays that use engineered antibodies to anchor the secreted molecules to the secreting cells are widely used to characterize immune responses because they allow both sensitive identification and recovery of viable responding cells. However, if the cytokines diffuse away from the secreting cells, non-secreting cells will also be identified as responding cells. Here we encapsulate immune cells in microfluidic droplets and perform in-droplet cytokine capture assays to limit the diffusion of the secreted cytokines. We use microfluidic devices to rapidly encapsulate single natural killer NK-92 MI cells and their target K562 cells into microfluidic droplets. We perform in-droplet IFN-γ capture assays and demonstrate that NK-92 MI cells recognize target cells within droplets and become activated to secrete IFN-γ. Droplet encapsulation prevents diffusion of secreted products to neighboring cells and dramatically reduces both false positives and false negatives, relative to assays performed without droplets. In a sample containing 1% true positives, encapsulation reduces, from 94% to 2%, the number of true-positive cells appearing as negatives; in a sample containing 50% true positives, the number of non-stimulated cells appearing as positives is reduced from 98% to 1%. After cells are released from the droplets, secreted cytokine remains captured onto secreting immune cells, enabling FACS-isolation of populations highly enriched for activated effector immune cells. Droplet encapsulation can be used to reduce background and improve detection of any single-cell secretion assay.more » « less
-
The plant endophyte Chalara sp. is able to biotransform the epigenetic modifier vorinostat to form unique, aniline-containing polyketides named chalanilines. Here, we sought to expand the chemical diversity of chalaniline A-type molecules by changing the aniline moiety in the precursor vorinostat. In total, twenty-three different vorinostat analogs were prepared via two-step synthesis, and nineteen were incorporated by the fungus into polyketides. The highest yielding substrates were selected for large-scale precursor-directed biosynthesis and five novel compounds, including two fluorinated chalanilines, were isolated, purified, and structurally characterized. Structure elucidation relied on 1D and 2D NMR techniques and was supported by low- and high-resolution mass spectrometry. All compounds were tested for their bioactivity but were not active in antimicrobial or cell viability assays. Aminofulvene-containing natural products are rare, and this high-yielding, precursor-directed process allows for the diversification of this class of compounds.more » « less
-
Elkins, Christopher A. (Ed.)ABSTRACT Monitoring the prevalence of SARS-CoV-2 variants is necessary to make informed public health decisions during the COVID-19 pandemic. PCR assays have received global attention, facilitating a rapid understanding of variant dynamics because they are more accessible and scalable than genome sequencing. However, as PCR assays target only a few mutations, their accuracy could be reduced when these mutations are not exclusive to the target variants. Here we introduce PRIMES, an algorithm that evaluates the sensitivity and specificity of SARS-CoV-2 variant-specific PCR assays across different geographical regions by incorporating sequences deposited in the GISAID database. Using PRIMES, we determined that the accuracy of several PCR assays decreased when applied beyond the geographic scope of the study in which the assays were developed. Subsequently, we used this tool to design Alpha and Delta variant-specific PCR assays for samples from Illinois, USA. In silico analysis using PRIMES determined the sensitivity/specificity to be 0.99/0.99 for the Alpha variant-specific PCR assay and 0.98/1.00 for the Delta variant-specific PCR assay in Illinois, respectively. We applied these two variant-specific PCR assays to six local sewage samples and determined the dominant SARS-CoV-2 variant of either the wild type, the Alpha variant, or the Delta variant. Using next-generation sequencing (NGS) of the spike (S) gene amplicons of the Delta variant-dominant samples, we found six mutations exclusive to the Delta variant (S:T19R, S:Δ156/157, S:L452R, S:T478K, S:P681R, and S:D950N). The consistency between the variant-specific PCR assays and the NGS results supports the applicability of PRIMES. IMPORTANCE Monitoring the introduction and prevalence of variants of concern (VOCs) and variants of interest (VOIs) in a community can help the local authorities make informed public health decisions. PCR assays can be designed to keep track of SARS-CoV-2 variants by measuring unique mutation markers that are exclusive to the target variants. However, the mutation markers may not be exclusive to the target variants because of regional and temporal differences in variant dynamics. We introduce PRIMES, an algorithm that enables the design of reliable PCR assays for variant detection. Because PCR is more accessible, scalable, and robust for sewage samples than sequencing technology, our findings will contribute to improving global SARS-CoV-2 variant surveillance.more » « less
-
Multi-modal single cell RNA assays capture RNA content as well as other data modalities, such as spatial cell position or the electrophysiological properties of cells. Compared to dedicated scRNA-seq assays however, they may unintentionally capture RNA from multiple adjacent cells, exhibit lower RNA sequencing depth compared to scRNA-seq, or lack genome-wide RNA measurements. We present scProjection, a method for mapping individual multi-modal RNA measurements to deeply sequenced scRNA-seq atlases to extract cell type-specific, single cell gene expression profiles. We demonstrate several use cases of scProjection, including the identification of spatial motifs from spatial transcriptome assays, distinguishing RNA contributions from neighboring cells in both spatial and multi-modal single cell assays, and imputing expression measurements of un-measured genes from gene markers. scProjection therefore combines the advantages of both multi-modal and scRNA-seq assays to yield precise multi-modal measurements of single cells.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.3390/nano11102607
