Replacement of specific markers for apoptosis and necrosis by nuclear morphology for affordable cytometry

A Rare-Earth Near-Infrared Nanoprobe for the Identification of Small Cell Lung Cancer

Background

Small cell lung cancer (SCLC) is a common subtype of lung cancer, and there is currently no established method for the early identification of SCLC. We prepared a novel rare-earth near-infrared (NIR) downconversion nanoprobe to identify SCLC cells.

Methods

The shell precursors Gd-OA and Na-TFA-OA were prepared, and the NaYF4:Nd@NaGdF4-ProGRP antibody probe was obtained after synthesizing downconversion fluorescent nanocrystals. The probe was used for NIR identification of cancer cells and subcutaneous tumors in nude mice. The biotoxicity of the probe to SCLC cells and nude mice was studied.

Results

The NaYF4:Nd@NaGdF4-ProGRP antibody probe was successfully prepared, with a size of 44 nm, an NIR emission peak at approximately 1060 nm, and a concentration of 40 μmol/mL. The probe could achieve accurate NIR identification of SCLC cells and subcutaneous tumors in nude mice. Optimal images of the subcutaneous tumor model were obtained approximately 10 minutes after probe injection. There was no significant change in the hematology indices, respiratory rate, or heart rate of nude mice after the probe was injected (all P > 0.05).

Conclusion

We have successfully prepared a low-toxicity probe that can identify SCLC cells, which may be useful for the early detection of SCLC. And conduct theoretical exploration for non-invasive identification and identification of some early metastatic lesions without pathological sampling in the future.

In vitro immune function in laboratory-reared age-0 smallmouth bass (Micropterus dolomieu) relative to diet

Smallmouth bass (Micropterus dolomieu) are used as an indicator species in environmental monitoring and assessment studies. However, laboratory-based studies for methods development and effector assessment are limited for this species. Nutrition, a known modulator of teleost physiological responses including immune function, is a critical knowledge-gap sometimes overlooked in the design of laboratory studies. We report the results from a study evaluating a commercially available artificial pelleted diet for bass and live feed (fathead minnows). Following a six-month diet-acclimation period, age-0 smallmouth bass were assessed using morphometric measures, histologic and immune-function end points using conventional methods, miniaturized cell isolation and assay methods as well as imaging flow cytometry. Fish on the two diets did not significantly differ in length, weight, or condition factor, indicating that growth was similar in the two groups. Histologic examination revealed relatively higher levels of macrophage aggregates and accumulation of ceroid/lipofuscin in the spleen as well as hepatocyte changes in the pellet-fed group. Leukocytes from the pellet-fed group exhibited significantly elevated bactericidal activity and significantly depressed mitogen response compared to fish fed live feed. Following exposure to a known inducer of inflammatory responses, bacterial lipopolysaccharide, responses including the transition of leukocytes to an apoptotic/necrotic condition differed significantly based on diet. Histologic findings were consistent with the occurrence of diet-related oxidative stress in the pellet-fed fish. Oxidative stress can be induced by multiple factors including environmental pollutants. For a diet to be useful in laboratory-based studies, it cannot elicit response that could also be induced by experimental treatments. To do so greatly complicates the detection of experimental effects. Until an artificial diet is developed for smallmouth bass that does not produce potentially confounding conditions for laboratory-based studies, use of a live feed appears to be the best option.

Automated and Reproducible Detection of Vascular Endothelial Growth Factor (VEGF) in Renal Tissue Sections

Background

Manual analysis of tissue sections, such as for pathological diagnosis, requires an analyst with substantial knowledge and experience. Reproducible image analysis of biological samples is steadily gaining scientific importance. The aim of the present study was to employ image analysis followed by machine learning to identify vascular endothelial growth factor (VEGF) in kidney tissue that had been subjected to hypoxia.

Methods

Light microscopy images of renal tissue sections stained for VEGF were analyzed. Subsequently, machine learning classified the cells as VEGF⁺ and VEGF⁻ cells.

Results

VEGF was detected and cells were counted with high sensitivity and specificity.

Conclusion

With great clinical, diagnostic, and research potential, automatic image analysis offers a new quantitative capability, thereby adding numerical information to a mostly qualitative diagnostic approach.

Comparison between two programs for image analysis, machine learning and subsequent classification

In the early 1950s, flow cytometry was developed as the first method for automated quantitative cellular analysis. In the early 1990s, the first equipment for image cytometry (laser scanning cytometry, LSC) became commercially available. As flow cytometry was considered the gold standard, various studies found that the results of flow cytometry and LSC generated comparable results. One of the first programs for image analysis that included morphological parameters was ImageJ, published in 1997. One of the newer programs for image analysis that is not limited to fluorescence images is the free software CellProfiler. In 2008, the same group published a new software, CellProfiler Analyst. One part of CellProfiler Analyst is a supervised machine-learning-based classifier that allows users to conduct imaging-based diagnoses, e.g., cellular diagnosis based on morphology. Another relatively new, free software for image analysis is QuPath. The aim of the present study was to compare two free programs for conducting image analysis, CellProfiler and QuPath, and the subsequent classification based on machine learning. For this study, images of renal tissue were analyzed, and the identified objects were classified. The same images were loaded in both software programs. Advanced statistical analysis was used to compare the two methods. The Bland-Altman assay showed that all of the differences were within the mean ± 1.96 * standard deviation, i.e., the differences are normally distributed, and the software programs are comparable. For the analyzed samples (renal tissue stained with HIF and TUNEL), the use of QuPath was easier because it offers image analysis without a previous processing of the images (e.g., conversion to grayscale, inverted intensities) and an unsupervised machine learning process.

In vitro Cell Viability by CellProfiler® Software as Equivalent to MTT Assay

Objective:

This study evaluated in vitro cell viability by the colorimetric MTT stands for 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (3-(4, 5-dimethylthiazolyl-2)-2, 5-diphenyltetrazolium bromide) (3-(4, 5-dimethylthiazolyl-2)-2, 5-diphenyltetrazolium bromide) assay compared to image analysis by CellProfiler^® software.

Materials and Methods:

Hepatoma (Hepa-1c1c7) and fibroblast (L929) cells were exposed to isolated substances, camptothecin, lycorine, tazettine, albomaculine, 3-epimacronine, trispheridine, galanthine and Padina gymnospora, Sargassum sp. methanolic extract, and Habranthus itaobinus Ravenna ethyl acetate in different concentrations. After MTT assay, cells were stained with Panotic dye kit. Cell images were obtained with an inverted microscope equipped with a digital camera. The images were analyzed by CellProfiler^®.

Results:

No cytotoxicity at the highest concentration analyzed for 3-epimacronine, albomaculine, galanthine, trispheridine, P. gymnospora extract and Sargassum sp. extract where detected. Tazettine offered cytotoxicity only against the Hepa1c1c7 cell line. Lycorine, camptothecin, and H. itaobinus extract exhibited cytotoxic effects in both cell lines. The viability methods tested were correlated demonstrated by Bland–Atman test with normal distribution with mean difference between the two methods close to zero, bias value 3.0263. The error was within the limits of the confidence intervals and these values had a narrow difference. The correlation between the two methods was demonstrated by the linear regression plotted as R².

Conclusion:

CellProfiler^® image analysis presented similar results to the MTT assay in the identification of viable cells, and image analysis may assist part of biological analysis procedures. The presented methodology is inexpensive and reproducible.

SUMMARY

In vitro cell viability assessment with MTT (3-(4, 5-dimethylthiazolyl-2)-2, 5-diphenyltetrazolium bromide) assay may be replaced by image analysis by CellProfiler^®.

The viability methods tested were correlated demonstrated by Bland-Atman test with normal distribution with mean difference between the two methods close to zero, bias value 3.0263. The correlation between the two methods was demonstrated by the linear regression plotted as R2.

Abbreviations: HPLC: High pressure liquid chromatography MTT: (3-(4, 5-dimethylthiazolyl-2)-2, 5-diphenyltetrazolium bromide) (3-(4, 5-dimethylthiazolyl-2)-2, 5-diphenyltetrazolium bromide)

Automatic detection of hypoxia in renal tissue stained with HIF-1alpha

OBJECTIVE

The objective of this study was the identification of the stain HIF-alpha using the Image Cytometry, and to help to count the positive cells (with HIF-alpha) and the negative cells (without HIF-alpha) from the same sample.

METHOD

17 images of renal tissues from male rats of Winstar lineage; overall, there were 12.587 objects (cells) in the images for analysis. The acquired images were then analyzed through the free softwares CellProfiler (version 2.1.1) and CellProfiler Analyst (version 2.0). In the software CellProfiler Anlyst, there was a separation with the classes of the object, using a classifier, and the classes were: 1) class with HIF-alpha and 2) class without HIF-alpha.

RESULTS

With the data obtained through Score All, it was possible to calculate the percentage of cells that had HIF-alpha; out of 12.587 objects of the sample, 6.773 (54%) had HIF-alpha and 5.814 (46%) did not have HIF-alpha. Data of sensibility 0.90, specificity 0.84 and standard deviation 0.10 and 0.12.

CONCLUSION

The research shows that the free software CellProfiler, through the light microscope, was able to identify the stains, perform the machine's learning, and subsequently count and separate cells from distinct classes (with and without the stain of HIF-alpha).

Objective detection of apoptosis in rat renal tissue sections using light microscopy and free image analysis software with subsequent machine learning: Detection of apoptosis in renal tissue

OBJECTIVE

The current study proposes an automated machine learning approach for the quantification of cells in cell death pathways according to DNA fragmentation.

METHODS

A total of 17 images of kidney histological slide samples from male Wistar rats were used. The slides were photographed using an Axio Zeiss Vert.A1 microscope with a 40x objective lens coupled with an Axio Cam MRC Zeiss camera and Zen 2012 software. The images were analyzed using CellProfiler (version 2.1.1) and CellProfiler Analyst open-source software.

RESULTS

Out of the 10,378 objects, 4970 (47,9%) were identified as TUNEL positive, and 5408 (52,1%) were identified as TUNEL negative. On average, the sensitivity and specificity values of the machine learning approach were 0.80 and 0.77, respectively.

CONCLUSION

Image cytometry provides a quantitative analytical alternative to the more traditional qualitative methods more commonly used in studies.

Trypan blue as an affordable marker for automated live-dead cell analysis in image cytometry

The aim of the present study was to combine image cytometry and trypan blue (TB) exclusion staining for a reproducible high-throughput detection of dead cells, enabling TB as an inexpensive marker, to be affordable for many studies and creating the possibility to combine fluorochromes without or with less spectral overlap. Capillary blood was drawn from a healthy volunteer, red blood cells were lysed and leukocyte cell death was induced. Samples were stained with CD45-FITC, CD14-PE, TB and DAPI, and then analyzed using image cytometry (iCys). TB quenching control tests were performed using DAPI and CD45-FITC. Images were generated in .TIF and .JPEG format using iCys image cytometer. The images were analyzed using CellProfiler (CP) modules to optimize the analysis based on the aims of each phase of this study. CellProfiler Analyst (CPA) was used to classify cells throughout machine learning and to calculate sensibility of the classification. A sensitivity of 0.94 for dead cells and 0.99 for live cells was calculated using CPA. We did not see any quenching effects of the FITC staining. DAPI signal was reduced in the presence of TB. The results of the present study revealed that TB serves as a dead cell marker in an image cytometric analysis, being able to be combined with other fluorescence markers without loss of fluorescence intensity signal or overlapping emission spectrum. SCANNING 38:857-863, 2016. © 2016 Wiley Periodicals, Inc.