Histochemistry for Molecular Imaging in Nanomedicine.

All the nanotechnological devices designed for medical purposes have to deal with the common requirement of facing the complexity of a living organism. Therefore, the development of these nanoconstructs must involve the study of their structural and functional interactions and the effects on cells, tissues, and organs, to ensure both effectiveness and safety. To this aim, imaging techniques proved to be extremely valuable not only to visualize the nanoparticles in the biological environment but also to detect the morphological and molecular modifications they have induced. In particular, histochemistry is a long-established science able to provide molecular information on cell and tissue components in situ, bringing together the potential of biomolecular analysis and imaging. The present review article aims at offering an overview of the various histochemical techniques used to explore the impact of novel nanoproducts as therapeutic, reconstructive and diagnostic tools on biological systems. It is evident that histochemistry has been playing a leading role in nanomedical research, being largely applied to single cells, tissue slices and even living animals.

Sliding Window Optimal Transport for Open World Artifact Detection in Histopathology.

Histological images are frequently impaired by local artifacts from scanner malfunctions or iatrogenic processes - caused by preparation - impacting the performance of Deep Learning models. Models often struggle with the slightest out-of-distribution shifts, resulting in compromised performance. Detecting artifacts and failure modes of the models is crucial to ensure open-world applicability to whole slide images for tasks like segmentation or diagnosis. We introduce a novel technique for out-of-distribution detection within whole slide images, compatible with any segmentation or classification model. Our approach tiles multi-layer features into sliding window patches and leverages optimal transport to align them with recognized in-distribution samples. We average the optimal transport costs over tiles and layers to detect out-of-distribution samples. Notably, our method excels in identifying failure modes that would harm downstream performance, surpassing contemporary out-of-distribution detection techniques. We evaluate our method for both natural and synthetic artifacts, considering distribution shifts of various sizes and types. The results confirm that our technique outperforms alternative methods for artifact detection. We assess our method components and the ability to negate the impact of artifacts on the downstream tasks. Finally, we demonstrate that our method can mitigate the risk of performance drops in downstream tasks, enhancing reliability by up to 77%. In testing 7 annotated whole slide images with natural artifacts, our method boosted the Dice score by 68%, highlighting its real open-world utility.

A Comprehensive Study of Meningioma Biomineralization: Morphological, Crystallographic, and Immunohistochemical Aspects.

Biomineralization of brain tissues occurs both in normal and pathological conditions. Dura mater biomineralization is widespread and occurs in 1-72% of cases, depending on the patient's age and research method. The amount of biomineral deposits under the conditions of tumor growth in the meninges only increases, reaching 100% in the case of psammomatous meningiomas. Since calcifications are often found in the meninges, the problem of differential diagnosis with calcified meningiomas arises. A total of 30 samples of meningiomas with signs of biomineralization-dense structure, characteristic crunch, psammoma bodies (group I) and 30 samples of meningiomas without any signs of biomineralization were examined as controls (group II). To detect pathological biomineralization, the meningioma tissue was studied using the methods of macroscopic description, histology, histochemistry, and immunohistochemistry, scanning electron microscopy with microanalysis, and transmission electron microscopy. A significantly higher level of caspase3 and features of the expression of osteoblastic markers (a lower level of OPG expression and a higher level of the presence of RANKL in group I, the absence of fluctuations in the expression of SPARC) may indicate a dystrophic type of development of biomineral deposits in meningiomas.

Histopathology Image Classification With Noisy Labels via The Ranking Margins.

Clinically, histopathology images always offer a golden standard for disease diagnosis. With the development of artificial intelligence, digital histopathology significantly improves the efficiency of diagnosis. Nevertheless, noisy labels are inevitable in histopathology images, which lead to poor algorithm efficiency. Curriculum learning is one of the typical methods to solve such problems. However, existing curriculum learning methods either fail to measure the training priority between difficult samples and noisy ones or need an extra clean dataset to establish a valid curriculum scheme. Therefore, a new curriculum learning paradigm is designed based on a proposed ranking function, which is named The Ranking Margins (TRM). The ranking function measures the 'distances' between samples and decision boundaries, which helps distinguish difficult samples and noisy ones. The proposed method includes three stages: the warm-up stage, the main training stage and the fine-tuning stage. In the warm-up stage, the margin of each sample is obtained through the ranking function. In the main training stage, samples are progressively fed into the networks for training, starting from those with larger margins to those with smaller ones. Label correction is also performed in this stage. In the fine-tuning stage, the networks are retrained on the samples with corrected labels. In addition, we provide theoretical analysis to guarantee the feasibility of TRM. The experiments on two representative histopathologies image datasets show that the proposed method achieves substantial improvements over the latest Label Noise Learning (LNL) methods.

The Evolving Role of Artificial Intelligence in Gastrointestinal Histopathology: An Update.

Significant advances in artificial intelligence (AI) over the past decade potentially may lead to dramatic effects on clinical practice. Digitized histology represents an area ripe for AI implementation. We describe several current needs within the world of gastrointestinal histopathology, and outline, using currently studied models, how AI potentially can address them. We also highlight pitfalls as AI makes inroads into clinical practice.

Lectin histochemistry of posterior lingual glands of developing rats.

The posterior lingual glands are classified as Weber and von Ebner glands. Glycans play an important role in salivary glands. Although the distribution of glycans can explain functional diversity and variation, there are many unknowns in the developing rat posterior lingual glands. The purpose of this study was to elucidate the relationship between the development and function of the posterior lingual gland in rats by histochemical analysis using lectins that bind to sugar residues. In adult rats, Arachis hypogaea (PNA), Glycine maximus (SBA), and Triticum vulgaris (WGA) were associated with serous cells and Dolichos biflorus (DBA) with mucous cells. In both Weber's and von Ebner's glands, all 4 lectins were bound to serous cells in early development, but as development progressed, DBA disappeared in serous cells and only the DBA remained in mucous cells. These results suggest that Galß (1,3) > Galß(1,4) > Gal, αGalNAc > αGal > ßGalNAc, NeuAc > (GalNAc)2-3>>>GlcNAc, and GalNAcα(1,3) are present in the early stage of development, but that GalNAcα(1,3) disappear in serous cells and only GalNAcα(1,3) are localized in mucous cells after maturation. These results indicate that Weber glands function as serous glands in the early postnatal stage when von Ebner glands have not matured.

Combined Lectin- and Immuno-histochemistry (CLIH) for Fluorescence Microscopy.

The function of glycoproteins depends both on their polypeptide chain and sugar residues. For detection and localization of glycoproteins in tissue sections, methods of immunohistochemistry (IHC) and lectin histochemistry (LHC) are usually used separately. For a better understanding of the expression and distribution of variants of glycoproteins, tissue sections can be analyzed by combined lectin- and immuno-histochemistry (CLIH). CLIH exploits the advantages of both IHC and LHC and can therefore contribute to research in glycobiology and other fields of cell biology. Since cancer transformation is accompanied by alterations in the glycosylation of some glycoproteins, CLIH could also be exploited for improved classification of cancers. The chapter considers how CLIH could be employed on paraffin sections and semithin cryosections for fluorescence microscopy. Five different protocols of CLIH are described in detail as well as appropriate negative controls.

The Graham and Karnovsky Horseradish Peroxidase Ultrastructural Method: A Premier JHC Citation Classic.

This commentary briefly reviews the background for the development of the horseradish peroxidase-diaminobenzidine tetrahydrochloride histochemical method originally described by Graham and Karnovsky in their citation classic, reprinted in full in this issue of Journal of Histochemistry & Cytochemistry. Some of the method's subsequent applications, including its use as a macromolecular tracer for kidney glomerular permeability and use in immunoelectron microscopy and other immunoassays, are also discussed.

A Rapid Cytological Screening as pre-Endoscopy Screening for Early Esophageal Squamous Cell Lesions: A Prospective Pilot Study from a Chinese Academic Center.

Background: Cytological detection of early esophageal squamous cell carcinoma (ESCC) remains challenging. Therefore, we introduced a rapid cytological screening method and evaluated its efficacy as a pre-endoscopy screening for early ESCC and precursor lesions. Methods: This method consisted of a sponge sample retrieval, automatic liquid-based cytological treatment and slides preparation, computer-assisted screening and manual diagnosis. Efficacy for detection of early ESCC and precursor lesions was evaluated. Also, diagnostic efficiency was compared with manual diagnosis. Results: Eighty-three patients with early ESCC and precursor lesions and 2,090 asymptomatic participants with high risks of ESCC were enrolled. Whole procedure was accomplished within two working days. Abnormal cells were detected in all 83 patients, and in 272 (13.01%) subjects among 2,090 asymptomatic participants. Early ESCC, high-grade intraepithelial neoplasia, low-grade intraepithelial neoplasia and reflux esophagitis and normal endoscopic findings were detected in 8, 13, 11, 187 and 53 participants with abnormal cells, respectively. The calculated sensitivity, specificity, positive predictive value and negative predictive value for detection of early ESCC and precursor lesions were 100%, 88.34%, 11.76%, and 100%, respectively. Compared with manual diagnosis, this method was accomplished in a shorter time duration (5.4 ± 0.45 min vs 320.2 ± 132.4 min, p < 0.001), a higher diagnostic accuracy (96.7% vs74.4%, p = 0.015) and a better inter-observer agreement (93.3% vs66.7%, K = 0.286, p < 0.001). Conclusions: Our study provides a promising methodology as pre-endoscopy screening for early ESCC and precursor lesions.

Gene Expression Studies in Formalin-Fixed Paraffin-Embedded Samples of Cutaneous Cancer: The Need for Reference Genes.

Formalin-fixed paraffin-embedded (FFPE) tumour samples may provide crucial data regarding biomarkers for neoplasm progression. Analysis of gene expression is frequently used for this purpose. Therefore, mRNA expression needs to be normalized through comparison to reference genes. In this study, we establish which of the usually reported reference genes is the most reliable one in cutaneous malignant melanoma (MM) and cutaneous squamous cell carcinoma (CSCC). ACTB, TFRC, HPRT1 and TBP expression was quantified in 123 FFPE samples (74 MM and 49 CSCC biopsies) using qPCR. Expression stability was analysed by NormFinder and Bestkeeper softwares, and the direct comparison method between means and SD. The in-silico analysis with BestKeeper indicated that HPRT1 was more stable than ACTB and TFRC in MM (1.85 vs. 2.15) and CSCC tissues (2.09 vs. 2.33). The best option to NormFinder was ACTB gene (0.56) in MM and TFRC (0.26) in CSCC. The direct comparison method showed lower SD means of ACTB expression in MM (1.17) and TFRC expression in CSCC samples (1.00). When analysing the combination of two reference genes for improving stability, NormFinder indicated HPRT1 and ACTB to be the best for MM samples, and HPRT1 and TFRC genes for CSCC. In conclusion, HPRT1 and ACTB genes in combination are the most appropriate choice for normalization in gene expression studies in MM FFPE tissue, while the combination of HPRT1 and TFRC genes are the best option in analysing CSCC FFPE samples. These may be used consistently in forthcoming studies on gene expression in both tumours.

Histochemistry for nanomedicine: Novelty in tradition.

During the last two centuries, histochemistry has provided significant advancements in many fields of life sciences. After a period of neglect due to the great development of biomolecular techniques, the histochemical approach has been reappraised and is now widely applied in the field of nanomedicine. In fact, the novel nanoconstructs intended for biomedical purposes must be visualized to test their interaction with tissue and cell components. To this aim, several long-established staining methods have been re-discovered and re-interpreted in an unconventional way for unequivocal identification of nanoparticulates at both light and transmission electron microscopy.

Spatial analysis of organ-wide RNA, protein expression, and lineage tracing in the female mouse reproductive tract.

Visualizing precise spatial patterns of an organ-wide gene and protein expression among diverse cell types can provide critical insights into the fundamental processes underlying normal tissue homeostasis and disease development. Here, we describe an optimized protocol for single-molecule RNA in situ hybridization (smRNA-ISH), immunohistochemistry, and cell lineage analysis of the female reproductive tract organs using commercially available smRNA-ISH probes, antibodies, and inducible Cre-mice. The high-resolution multispectral fluorescence imaging is performed using wide-field epifluorescence or confocal microscopy combined with a slide scanner. For complete details on the use and execution of this protocol, please refer to Chumduri et al. (2021).

Assessment of neurodegeneration and neuronal loss in aged 5XFAD mice.

Neuronal loss resulting from progressive neurodegeneration is a major pathological feature of Alzheimer's disease (AD). Here, we present a protocol to detect neurodegeneration, neuronal apoptosis, and neuronal loss in 5XFAD mouse strain, which is a well-established model for interrogating the molecular mechanism of neuronal death in AD. This protocol describes the use of the neurodegenerative marker Fluro-Jade C, cleaved caspase-3 immunofluorescent staining and Nissl staining for the analysis of neurodegeneration and neuronal loss in 5XFAD mice. For complete details on the use and execution of this protocol, please refer to Zhang et al. (2021).

Protocol for labeling and fixation of intact lysosomes with esterified amino acid analogs to assess lysosomal expansion in living eukaryotic cells.

The lysosomal compartment is a key hub for cell metabolism, and morphological alterations have been described in several pathological conditions. Here, we describe the use of amino acid analogs modified by the presence of a methyl ester group that accumulates within lysosomes. This generates an intraluminal osmotic effect able to trigger a rapid and selective expansion of the lysosomal compartment within 2 h of treatment. We also present protocols to preserve lysosomal morphology, which yields a more accurate size measurement. For complete details on the use and execution of this protocol, please refer to Scerra et al. (2021).

Tracking of the biochemical changes upon pleomorphic adenoma progression using vibrational microspectroscopy.

Head and neck tumors can be very challenging to treat because of the risk of problems or complications after surgery. Therefore, prompt and accurate diagnosis is extremely important to drive appropriate treatment decisions, which may reduce the chance of recurrence. This paper presents the original research exploring the feasibility of Fourier transform infrared (FT-IR) and Raman spectroscopy (RS) methods to investigate biochemical alterations upon the development of the pleomorphic adenoma. Principal component analysis (PCA) was used for a detailed assessment of the observed changes and to determine the spectroscopic basis for salivary gland neoplastic pathogenesis. It is implied that within the healthy margin, as opposed to the tumoral tissue, there are parts that differ significantly in lipid content. This observation shed new light on the crucial role of lipids in tissue physiology and tumorigenesis. Thus, a novel approach that eliminates the influence of lipids on the elucidation of biochemical changes is proposed. The performed analysis suggests that the highly heterogeneous healthy margin contains more unsaturated triacylglycerols, while the tumoral section is rich in proteins. The difference in protein content was also observed for these two tissue types, i.e. the healthy tissue possesses more proteins in the anti-parallel ß-sheet conformation, whereas the tumoral tissue is dominated by proteins rich in unordered random coils. Furthermore, the pathogenic tissue shows a higher content of carbohydrates and reveals noticeable differences in nucleic acid content. Finally, FT-IR and Raman spectroscopy methods were proposed as very promising methods in the discrimination of tumoral and healthy tissues of the salivary gland.

Clinical application of whole transcriptome sequencing for the classification of patients with acute lymphoblastic leukemia.

BACKGROUND: Considering the clinical and genetic characteristics, acute lymphoblastic leukemia (ALL) is a rather heterogeneous hematological neoplasm for which current standard diagnostics require various analyses encompassing morphology, immunophenotyping, cytogenetics, and molecular analysis of gene fusions and mutations. Hence, it would be desirable to rely on a technique and an analytical workflow that allows the simultaneous analysis and identification of all the genetic alterations in a single approach. Moreover, based on the results with standard methods, a significant amount of patients have no established abnormalities and hence, cannot further be stratified. METHODS: We performed WTS and WGS in 279 acute lymphoblastic leukemia (ALL) patients (B-cell: n = 211; T-cell: n = 68) to assess the accuracy of WTS, to detect relevant genetic markers, and to classify ALL patients. RESULTS: DNA and RNA-based genotyping was used to ensure correct WTS-WGS pairing. Gene expression analysis reliably assigned samples to the B Cell Precursor (BCP)-ALL or the T-ALL group. Subclassification of BCP-ALL samples was done progressively, assessing first the presence of chromosomal rearrangements by the means of fusion detection. Compared to the standard methods, 97% of the recurrent risk-stratifying fusions could be identified by WTS, assigning 76 samples to their respective entities. Additionally, read-through fusions (indicative of CDKN2A and RB1 gene deletions) were recurrently detected in the cohort along with 57 putative novel fusions, with yet untouched diagnostic potentials. Next, copy number variations were inferred from WTS data to identify relevant ploidy groups, classifying an additional of 31 samples. Lastly, gene expression profiling detected a BCR-ABL1-like signature in 27% of the remaining samples. CONCLUSION: As a single assay, WTS allowed a precise genetic classification for the majority of BCP-ALL patients, and is superior to conventional methods in the cases which lack entity defining genetic abnormalities.

Predicting Molecular Phenotypes from Histopathology Images: A Transcriptome-Wide Expression-Morphology Analysis in Breast Cancer.

Molecular profiling is central in cancer precision medicine but remains costly and is based on tumor average profiles. Morphologic patterns observable in histopathology sections from tumors are determined by the underlying molecular phenotype and therefore have the potential to be exploited for prediction of molecular phenotypes. We report here the first transcriptome-wide expression-morphology (EMO) analysis in breast cancer, where individual deep convolutional neural networks were optimized and validated for prediction of mRNA expression in 17,695 genes from hematoxylin and eosin-stained whole slide images. Predicted expressions in 9,334 (52.75%) genes were significantly associated with RNA sequencing estimates. We also demonstrated successful prediction of an mRNA-based proliferation score with established clinical value. The results were validated in independent internal and external test datasets. Predicted spatial intratumor variabilities in expression were validated through spatial transcriptomics profiling. These results suggest that EMO provides a cost-efficient and scalable approach to predict both tumor average and intratumor spatial expression from histopathology images. SIGNIFICANCE: Transcriptome-wide expression morphology deep learning analysis enables prediction of mRNA expression and proliferation markers from routine histopathology whole slide images in breast cancer.

Cytomorphology of normal, reactive, dysmorphic, and dysplastic megakaryocytes in bone marrow aspirates.

This paper aims to emphasize the importance of applying international consensus guidelines to detect qualitative and quantitative abnormalities of megakaryocytes on smears of bone marrow aspirates (BMA) for a shared and harmonized diagnostic path between different laboratories. Careful evaluation of megakaryocytes on BMA smears represents a cornerstone in the diagnosis of most clonal and nonclonal hematological diseases. Images associated with the detailed morphologic description of normal, reactive, abnormal, and dysplastic megakaryocytes are also reported together with examples of similar cells that, if not promptly identified, can lead to a morphological misdiagnosis.

Full-field hemocytometry. Forty years of progress seen through Clinical and Laboratory Hematology and the International Journal of Laboratory Hematology.

The extraordinary advances in clinical hematology, biology, and oncology in the last decades would not have been possible without discovering how to identify and count the cells circulating in the blood. For centuries, scientists have used slides, counting chambers (hemocytometers), and diluting and staining solutions for this task. Then, automated hemocytometry began. This science, now linked to the daily routine of laboratory hematology, has completed an overwhelming path over a few decades. Our laboratories today operate with versatile multiparameter systems, ranging from complex single-channel instruments to bulky continuous flow machines. In terms of clinical information obtained from a simple routine blood test, the full exploitation of their potential depends on the operators' imagination and courage. A comprehensive review of the scientific publications that have accompanied the development of hemocytometry from the 1950s to today would require entire volumes. More than seven hundred contributions that authors worldwide have published in Clinical and Laboratory Haematology until 2007 and then the International Journal of Laboratory Hematology are summarized. Such journals have represented and hopefully will continue to represent the privileged place of welcome for future scientific research in hemocytometry. Improved technologies, attention to quality, new reagents and electronics, information technology, and scientist talent ensure a more profound and deeper knowledge of cell properties: current laboratory devices measure and count even minor immature or pathological cell subpopulations. Full-field hemocytometry includes the analysis of nonhematic fluids, digital adds to the microscope, and the development of effective point-of-care devices.

Multiplexed Tissue Tomography.

Multiplexed tissue tomography enables comprehensive spatial analysis of markers within a whole tissue or thick tissue section. Clearing agents are often used to make tissue transparent and facilitate deep tissue imaging. Many methods of clearing and tissue tomography are currently used in a variety of tissue types. Here we detail a workflow known as transparent tissue tomography (T3), which builds upon previous methods and can be applied to difficult to clear tissues such as tumors.