Conventional histological and cytological staining with simultaneous immunohistochemistry enabled by invisible chromogens

Morrison, Larry E.; Lefever, Mark; Lewis, Heather N.; Kapadia, Monesh; Bauer, Daniel R.

doi:10.1038/s41374-021-00714-2

Cited by 20 publications

(8 citation statements)

References 18 publications

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“…No significant loss of body weight was observed in the mice group receiving any of the IFN variants, suggesting that the drugs were all well tolerated at the designated dose in the experiment (Figure c). Hematoxylin and eosin (H&E) staining is widely used in histology and cytology applications . The hematoxylin produces an intense blue-purple stain on nuclei with optimal contrast to the eosin-stained cytoplasm.…”

Section: Resultsmentioning

confidence: 99%

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Mechano-bioconjugation Strategy Empowering Fusion Protein Therapeutics with Aggregation Resistance, Prolonged Circulation, and Enhanced Antitumor Efficacy

et al. 2022

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Bioconjugation is a powerful protein modification strategy to improve protein properties. Herein, we report mechano-bioconjugation as a novel approach to empower fusion protein therapeutics and demonstrate its utility by a protein heterocatenane (cat-IFN-ABD) containing interferon-α2b (IFN) mechanically interlocked with a consensus albumin-binding domain (ABD). The conjugate was selectively synthesized in cellulo following a cascade of post-translational events using a pair of heterodimerizing p53dim variants and two orthogonal split-intein reactions. The catenane topology was proven by combined techniques of LC−MS, SDS-PAGE, SEC, and controlled proteolytic digestion. Not only did cat-IFN-ABD retain activities comparable to those of the wild-type IFN and ABD, the conjugate also exhibited enhanced aggregation resistance and prolonged circulation time over the simple linear and cyclic fusions. Consequently, cat-IFN-ABD potently inhibited tumor growth in the mouse xenograft model. Therefore, mechano-bioconjugation by catenation accomplishes function integration with additional benefits, providing an alternative pathway for developing advanced protein therapeutics.

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Section: Resultsmentioning

confidence: 99%

“…Hematoxylin and eosin (H&E) staining is widely used in histology and cytology applications. 74 The hematoxylin produces an intense blue-purple stain on nuclei with optimal contrast to the eosin-stained cytoplasm. Ki-67 staining using immunohistochemistry is reflective of cancer cell proliferation.…”

Section: ■ Introductionmentioning

confidence: 98%

Mechano-bioconjugation Strategy Empowering Fusion Protein Therapeutics with Aggregation Resistance, Prolonged Circulation, and Enhanced Antitumor Efficacy

et al. 2022

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“…Because of the ubiquitous target Raman-active mode, CH 2 symmetric stretching, which reflects lipid distribution instead of cell-specific labels, our method holds great potential for extension to other cytological scenarios and stain types. [42][43][44]…”

Section: Discussionmentioning

confidence: 99%

Label‐Free Virtual Peritoneal Lavage Cytology via Deep‐Learning‐Assisted Single‐Color Stimulated Raman Scattering Microscopy

Fang,

Wu,

Chen

et al. 2024

Advanced Intelligent Systems

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Clinical guidelines for gastric cancer treatment recommend intraoperative peritoneal lavage cytology to detect free cancer cells. Patients with positive cytology require neoadjuvant chemotherapy instead of instant resection, and conversion to negative cytology results in improved survival. However, pathologists’ or artificial intelligence's accuracy of cytological diagnosis is disturbed by manually produced, unstandardized slides. In addition, the elaborate infrastructure makes cytology accessible to a limited number of medical institutes. This work develops CellGAN, a deep learning method that enables label‐free virtual peritoneal lavage cytology by producing virtual hematoxylin–eosin‐stained images with single‐color stimulated Raman scattering microscopy. A structural similarity loss is introduced to overcome the challenge of unsupervised virtual pathology techniques that cannot accurately present cellular structures. This method achieves a structural similarity of 0.820 ± 0.041 and a nucleus area consistency of 0.698 ± 0.102, indicating the staining fidelity outperforms the state‐of‐the‐art method. Diagnosis using virtually stained cells reaches 93.8% accuracy and substantial consistency with conventional staining. Single‐cell detection and classification on virtual slides achieve a mean average precision of 0.924 and an area under the receiver operating characteristic curve of 0.906, respectively. Collectively, this method achieves standardized and accurate virtual peritoneal lavage cytology and holds great potential for clinical translation.

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“…This is because Papanicolaou stain is the most universal cytology staining owing to its remarkable diagnostic properties [40]. Hematoxylin and eosin stain, on the other hand, is not ideal for cytopathology practice because it contains Mayer's hematoxylin that is not feasible for cytology staining [41,42]. Another notable finding in the current datasets is that they were prepared from old archived Papanicolaou stained slides.…”

Section: Discussionmentioning

confidence: 99%

A Novel Validated Real-World Dataset for the Diagnosis of Multiclass Serous Effusion Cytology according to the International System and Ground-Truth Validation Data

Abd-Almoniem,

Abd-Alsabour,

Elsheikh

et al. 2024

Acta Cytologica

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Introduction: The application of artificial intelligence (AI) algorithms in serous fluid cytology is lacking due to the deficiency in standardized publicly available datasets. Here, we develop a novel public serous effusion cytology dataset. Furthermore, we apply AI algorithms on it to test its diagnostic utility and safety in clinical practice. Methods: The work is divided into three phases. Phase 1 entails building the dataset based on the multitiered evidence-based classification system proposed by the International System (TIS) of serous fluid cytology along with ground-truth tissue diagnosis for malignancy. To ensure reliable results of future AI research on this dataset, we carefully consider all the steps of the preparation and staining from a real-world cytopathology perspective. In phase 2, we pay special consideration to the image acquisition pipeline to ensure image integrity. Then we utilize the power of transfer learning using the convolutional layers of the VGG16 deep learning model for feature extraction. Finally, in phase 3, we apply the random forest classifier on the constructed dataset. Results: The dataset comprises 3,731 images distributed among the four TIS diagnostic categories. The model achieves 74% accuracy in this multiclass classification problem. Using a one-versus-all classifier, the fallout rate for images that are misclassified as negative for malignancy despite being a higher risk diagnosis is 0.13. Most of these misclassified images (77%) belong to the atypia of undetermined significance category in concordance with real-life statistics. Conclusion: This is the first and largest publicly available serous fluid cytology dataset based on a standardized diagnostic system. It is also the first dataset to include various types of effusions and pericardial fluid specimens. In addition, it is the first dataset to include the diagnostically challenging atypical categories. AI algorithms applied on this novel dataset show reliable results that can be incorporated into actual clinical practice with minimal risk of missing a diagnosis of malignancy. This work provides a foundation for researchers to develop and test further AI algorithms for the diagnosis of serous effusions.

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Conventional histological and cytological staining with simultaneous immunohistochemistry enabled by invisible chromogens

Cited by 20 publications

References 18 publications

Mechano-bioconjugation Strategy Empowering Fusion Protein Therapeutics with Aggregation Resistance, Prolonged Circulation, and Enhanced Antitumor Efficacy

Mechano-bioconjugation Strategy Empowering Fusion Protein Therapeutics with Aggregation Resistance, Prolonged Circulation, and Enhanced Antitumor Efficacy

Label‐Free Virtual Peritoneal Lavage Cytology via Deep‐Learning‐Assisted Single‐Color Stimulated Raman Scattering Microscopy

A Novel Validated Real-World Dataset for the Diagnosis of Multiclass Serous Effusion Cytology according to the International System and Ground-Truth Validation Data

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