Hyperspectral microscopy combined with DAPI staining for the identification of hepatic carcinoma cells

A Novel Laboratory-Based Strategy for Single Adipocyte and Adipose-Derived Stem Cells Extraction for Transplantation: An Experimental Research

BACKGROUND

Autologous fat grafting is widely used in plastic surgery. However, its main limitation is the low survival rate of fat grafts after transplantation. Transplantation of single adipocytes in combination with adipose-derived stem cells (ADSCs) could largely preserve the activity of the fat and improve graft survival.

OBJECTIVE

To verify the long-term survival rate of single adipocyte graft in vivo and its viable fat morphology for future fat grafting.

METHODS

Healthy adipose tissue was harvested and disassociated using fat dissociation solution, the Single-cell Suspension Preparation System (SSPS) was used to obtain a mixture of single adipocytes, ADSCs and stromal vascular fraction (SVF), and the structure of single adipocytes was verified by cell mask red and DAPI double staining. Nine male Balb/c nude mice were used, and three different graft volumes were established (0.05, 0.1 and 0.2 ml). For each mouse, four sites were selected for transplantation, one for macrofat and the other three for single adipocytes, and different transplant volumes 30, 60 and 90 days after transplantation. In each period, 3 mice were selected to measure the volume of fat graft.

RESULTS

Double staining with cell mask red and DAPI confirmed that the nucleus was identified intracellularly, which also indicated that the adipocytes in the single-cell suspension were structurally complete. When evaluating the transplantation, the groups with a volume of 0.05 ml and 0.2 ml performed better in the single-cell fat group in all transplantation periods, the group with a volume of 0.1 ml performed better in the single-cell group in the 30- and 60-day transplantation, and the differences were significant (P<0.05).

CONCLUSION

In this study, the SSPS was used to obtain a new transplant material containing single adipocytes and ADSCs by enzymatic hydrolysis of adipose tissue and converted into single cells. It effectively improved the survival rate of fat grafting and the long-term effect of transplantation.

NO LEVEL ASSIGNED

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Effect of collagen-based scaffolds with hydroxyapatite on the repair of cartilage defects in the rabbit knee joint

BACKGROUND

The repair of articular cartilage defects is always a significant clinical challenge in joint treatment. Therefore, the aim of this study was to investigate that the ColII-HA-CS-HAP scaffolds with BMSCs could repair cartilage defects of knee.

METHODS

Bone marrow mesenchymal stem cells (BMSCs) were extracted from rabbits, identified using immunofluorescence staining, and successfully induced into chondrocytes. Type II collagen (ColII) was isolated from bovine cartilage and constructed into scaffolds with hyaluronic acid, chondroitin sulfate, and hydroxyapatite. Then BMSCs were seeded on the ColII-HA-CS-HAP scaffold to detect biocompatibility.

RESULTS

The results of DAPI fluorescence staining showed that the number of BMSCs on the ColII-HA-CS-HAP scaffolds increased rapidly after culturing for 12 d. The rabbit knee cartilage defect model with a diameter of approximately 3 mm and a thickness of approximately 4 mm was selected to evaluate the regenerative potential of the scaffolds using histological and immunohistochemical analyses. At 6 months, the regenerated cartilage in the ColII-HA-CS-HAP scaffolds with BMSCs was more similar to that of native cartilage than the ColII-HA-CS-HAP scaffold group.

CONCLUSIONS

Our study proved that the ColII-HA-CS-HAP scaffolds with differentiated BMSCs can produce an excellent healing response and repair cartilage defects successfully in a rabbit model.

Developing targeted drug delivery carriers for breast cancer using glutathione-sensitive doxorubicin-coupled glycated bovine serum albumin nanoparticles

Incorporation of the nano-based carriers into drug delivery provides a promising alternative to overcome the limitations of the conventional chemotherapy. Doxorubicin (DOXO) is an effective chemotherapeutic drug widely used in chemotherapy for breast cancer treatment. A globular protein bovine serum albumin (BSA) holds great potential as carriers in pharmaceutical applications. This work is aimed at developing the DOXO-coupled glycated BSA nanoparticles via desolvation method for improving the capability of targeting the GLUT5 transporters over-expressed on breast cancer cells. Fructosamine assay and Fourier transform infrared spectroscopy were employed to determine the content of fructosamine structure and structural changes on the surfaces of nanoparticles, respectively. Additionally, the synthesized BSA nanoparticles were further characterized by electron microscopy and dynamic light scattering. Results revealed that the DOXO-coupled glycated BSA nanoparticles were spherically shaped with a hydrodynamic diameter of ~60.74 nm and a ζ-potential of ~ - 42.20 mV. Moreover, the DOXO release behavior of as-synthesized DOXO-coupled glycated BSA nanoparticles was examined under different conditions. Finally, the DOXO-coupled glycated BSA nanoparticles were found to exhibit cytotoxicity toward both MCF-7 and MDA-MB-231 cells. Our findings evidently suggested that the drug-coupled glycated BSA nanoparticles serve as the potential candidates for targeted drug delivery platform used in breast cancer therapy.

Compressive hyperspectral microscopy for cancer detection

Significance

Hyperspectral microscopy grants the ability to characterize unique properties of tissues based on their spectral fingerprint. The ability to label and measure multiple molecular probes simultaneously provides pathologists and oncologists with a powerful tool to enhance accurate diagnostic and prognostic decisions. As the pathological workload grows, having an objective tool that provides companion diagnostics is of immense importance. Therefore, fast whole-slide spectral imaging systems are of immense importance for automated cancer prognostics that meet current and future needs.

Aim

We aim to develop a fast and accurate hyperspectral microscopy system that can be easily integrated with existing microscopes and provide flexibility for optimizing measurement time versus spectral resolution.

Approach

The method employs compressive sensing (CS) and a spectrally encoded illumination device integrated into the illumination path of a standard microscope. The spectral encoding is obtained using a compact liquid crystal cell that is operated in a fast mode. It provides time-efficient measurements of the spectral information, is modular and versatile, and can also be used for other applications that require rapid acquisition of hyperspectral images.

Results

We demonstrated the acquisition of breast cancer biopsies hyperspectral data of the whole camera area within ∼ 1    s . This means that a typical 1 × 1    cm 2 biopsy can be measured in ∼ 10    min . The hyperspectral images with 250 spectral bands are reconstructed from 47 spectrally encoded images in the spectral range of 450 to 700 nm.

Conclusions

CS hyperspectral microscopy was successfully demonstrated on a common lab microscope for measuring biopsies stained with the most common stains, such as hematoxylin and eosin. The high spectral resolution demonstrated here in a rather short time indicates the ability to use it further for coping with the highly demanding needs of pathological diagnostics, both for cancer diagnostics and prognostics.

SpeCamX: mobile app that turns unmodified smartphones into multispectral imagers

We present the development of SpeCamX, a mobile application that enables an unmodified smartphone into a multispectral imager. Multispectral imaging provides detailed spectral information about objects or scenes, but its accessibility has been limited due to its specialized requirements for the device. SpeCamX overcomes this limitation by utilizing the RGB photographs captured by smartphones and converting them into multispectral images spanning a range of 420 to 680 nm without a need for internal modifications or external attachments. The app also includes plugin functions for extracting medical information from the resulting multispectral data cube. In a clinical study, SpeCamX was used to implement an augmented smartphone bilirubinometer, predicting blood bilirubin levels (BBL) with superior performance in accuracy, efficiency and stability compared to default smartphone cameras. This innovative technology democratizes multispectral imaging, making it accessible to a wider audience and opening new possibilities for both medical and non-medical applications.

A Deep-Learning-Computed Cancer Score for the Identification of Human Hepatocellular Carcinoma Area Based on a Six-Colour Multiplex Immunofluorescence Panel

Liver cancer is one of the most frequently diagnosed and fatal cancers worldwide, with hepatocellular carcinoma (HCC) being the most common primary liver cancer. Hundreds of studies involving thousands of patients have now been analysed across different cancer types, including HCC, regarding the effects of immune infiltrates on the prognosis of cancer patients. However, for these analyses, an unambiguous delineation of the cancer area is paramount, which is difficult due to the strong heterogeneity and considerable inter-operator variability induced by qualitative visual assessment and manual assignment. Nowadays, however, multiplex analyses allow the simultaneous evaluation of multiple protein markers, which, in conjunction with recent machine learning approaches, may offer great potential for the objective, enhanced identification of cancer areas with further in situ analysis of prognostic immune parameters. In this study, we, therefore, used an exemplary five-marker multiplex immunofluorescence panel of commonly studied markers for prognosis (CD3 T, CD4 T helper, CD8 cytotoxic T, FoxP3 regulatory T, and PD-L1) and DAPI to assess which analytical approach is best suited to combine morphological and immunohistochemical data into a cancer score to identify the cancer area that best matches an independent pathologist’s assignment. For each cell, a total of 68 individual cell features were determined, which were used as input for 4 different approaches for computing a cancer score: a correlation-based selection of individual cell features, a MANOVA-based selection of features, a multilayer perceptron, and a convolutional neural network (a U-net). Accuracy was used to evaluate performance. With a mean accuracy of 75%, the U-net was best capable of identifying the cancer area. Although individual cell features showed a strong heterogeneity between patients, the spatial representations obtained with the computed cancer scores delineate HCC well from non-cancer liver tissues. Future analyses with larger sample sizes will help to improve the model and enable direct, in-depth investigations of prognostic parameters, ultimately enabling precision medicine.

A new theranostic pH-responsive niosome formulation for Doxorubicin delivery and bio-imaging against breast cancer

As one of the newest generations of nanoplatforms, smart nanotheranostics have attracted signifivant attentions for medical applications, especially in oncology and cancer treatment. Indeed, their capability to provide treatment and diagnosis simultaneously leads to reduce time and side effects along with improving the performance. This study aims to introduce a novel smart nano-platform composed of doxorubicin-loaded pH-responsive stealth niosomes containing CdSe/ZnS Quantum dots as an imaging agent. Drug loaded nano-platform was fabricated via thin-film hydration method and then evaluated using different physicochemical tests. The entrapment efficiency and release profile of doxorubicin were assessed at three different pH (4, 6.5, and 7.4). Biological features and imaging ability of the nanoparticles were also evaluated by MTT assay, apoptosis assay, and fluorescence microscopy. Results showed that the fabricated nanoparticles were round-shaped, with a mean size of about 100±10 nm, -2 mV surface charge, and about 87% entrapment efficiency. The drug release profile presented a pH-responsive behavior (80, 60, and 40% drug release in pH 4, 6.5, and 7.4, respectively). The bio-activity assessments showed nearly 55% cytotoxicity effects via inducing cell apoptosis. Besides, the uptake of samples by the cells was confirmed through fluorescence imaging. Based on the results, this new nanoformulation could be considered as a candidate for future cancer theranostic applications.

Staging of Skin Cancer Based on Hyperspectral Microscopic Imaging and Machine Learning

Skin cancer, a common type of cancer, is generally divided into basal cell carcinoma (BCC), squamous cell carcinoma (SCC) and malignant melanoma (MM). The incidence of skin cancer has continued to increase worldwide in recent years. Early detection can greatly reduce its morbidity and mortality. Hyperspectral microscopic imaging (HMI) technology can be used as a powerful tool for skin cancer diagnosis by reflecting the changes in the physical structure and microenvironment of the sample through the differences in the HMI data cube. Based on spectral data, this work studied the staging identification of SCC and the influence of the selected region of interest (ROI) on the staging results. In the SCC staging identification process, the optimal result corresponded to the standard normal variate transformation (SNV) for spectra preprocessing, the partial least squares (PLS) for dimensionality reduction, the hold-out method for dataset partition and the random forest (RF) model for staging identification, with the highest staging accuracy of 0.952 ± 0.014, and a kappa value of 0.928 ± 0.022. By comparing the staging results based on spectral characteristics from the nuclear compartments and peripheral regions, the spectral data of the nuclear compartments were found to contribute more to the accurate staging of SCC.

Cancer detection from stained biopsies using high-speed spectral imaging

The escalating demand for diagnosing pathological biopsies requires the procedures to be expedited and automated. The existing imaging systems for measuring biopsies only measure color, and even though a lot of effort is invested in deep learning analysis, there are still serious challenges regarding the performance and validity of the data for the intended medical setting. We developed a system that rapidly acquires spectral images from biopsies, followed by spectral classification algorithms. The spectral information is remarkably more informative than the color information, and leads to very high accuracy in identifying cancer cells, as tested on tens of cancer cases. This was improved even more by using artificial intelligence algorithms that required a rather small training set, indicating the high level of information that exists in the spectral images. The most important spectral differences are observed in the nucleus and they are related to aneuploidy in tumor cells. Rapid spectral imaging measurement therefore can bridge the gap in the machine-aided diagnostics of whole biopsies, thus improving patient care, and expediting the treatment procedure.

Identification of DAPI-stained normal, inflammatory, and carcinoma hepatic cells based on hyperspectral microscopy

Gross chromatin imbalance and high DNA content are distinct features of various types of cancer cells. However, severe inflammation can also produce similar symptoms in cells. In this study, normal, inflammatory, and carcinoma hepatic cells were stained with 4',6-diamidino-2-phenylindole (DAPI) and investigated by hyperspectral microscopy. DAPI is a DNA-sensitive fluorochrome. Therefore, the differences in the cellular DNA of the samples can be revealed by the corresponding fluorescence. Our experimental results demonstrate that although chromosomal disorder and high DNA content both occur in severely inflammatory and carcinoma hepatic cells, there is still a slight difference in their DNA, making their fluorescent intensity and even their spectral shapes distinguishable. Based on these spectral features, we developed a method for the precise identification of normal, inflammatory, and carcinoma hepatic cells in the field of view. The identification accuracy for these three types of cells was 99.8%. We believe that examination that combines DAPI staining with hyperspectral microscopy is a potential method for the identification and investigation of various types of cancer tissues.

A real-time and in-situ monitoring of the molecular interactions between drug carrier polymers and a phospholipid membrane

The dynamic interactions between drug carrier molecules and a cell membrane can not be ignored in their clinical use. Here a simple, label-free and non-invasive approach, photo-voltage transient method, combined with the atomic force microscopy, dynamic giant unilamellar vesicle leakage assay and cytotoxicity method, was employed for a real-time monitoring of the interaction process. Two representative polymer molecules, polyoxyethylene (35) lauryl ether (Brij35) and polyvinylpyrrolidone (PVPk30), were taken as examples to interact with a phospholipid bilayer membrane in a low ionic strength and neutral pH condition. Brij35 demonstrated an adsorption-accumulation-permeabilization dominated process under the modulation of polymer concentration in the solution. In contrast, PVPk30 performed a dynamic balance between adsorption-desorption of the molecules and/or permeabilization-resealing of the membrane. Such difference explains the high and low cytotoxicity of them, respectively, in the living cell tests. Briefly, through combining the photo-voltage approach with conventional fluorescent microscopy method, this work demonstrates new ideas on the time and membrane actions of polymer surfactants which should be taken into account for their biomedical applications.

Lockdown of mitochondrial Ca2+ extrusion and subsequent resveratrol treatment kill HeLa cells by Ca2+ overload

Anticancer effect of resveratrol and the role of sodium/lithium/calcium exchanger in context with calcium ions are studied in human cervical cancer cell line. This therapeutic approach using siNCLX mediated gene silencing and drug therapy with resveratrol indicates the disruption of calcium homeostasis, increase in caspase (-3, 8, 9) mRNA expressions and DNA damage leading to apoptotic cell death. Monitoring the intracellular Ca2+ changes using fluo-4AM indicates highest rise in [Ca2+] level in sodium/lithium/calcium exchanger silenced group with five different stages, that is distinguishable based on the fluorescence intensity. In resveratrol treated and siNCLX + resveratrol treated groups no such cell staging differences were observed, despite uniform Ca2+ rise followed by decrease in the intensity. Integrating RNAi gene silencing of sodium/lithium/calcium exchanger with resveratrol can form the most interesting, efficient and promising therapeutic strategy in the treatment of cancer.