目的： 探讨茜素红S（alizarin red S）染色在血管钙化疾病中的应用价值。 方法： 选择钙盐含量高、中、低的组织共31例分别进行茜素红S染色和von Kossa硝酸银染色，对比2种不同染色法的一致性。对58例慢性肾病，17例动脉粥样硬化以及13例主动脉夹层血管组织进行茜素红S染色观察钙化情况。 结果： 茜素红S染色和硝酸银染色对高、中、低钙含量组织31例均能明确着色，结果差异无统计学意义（P>0.05），但在钙盐颗粒信号显示方面，茜素红S染色明显强于硝酸银染色，且前者比后者更易识别杂质。在染色时间方面，茜素红S染色明显短于硝酸银染色法（40 s比30 min）。使用茜素红S法染色：53%（31/58）慢性肾病、13例（13/17）动脉粥样硬化和13例（13/13）主动脉夹层组织可见钙盐沉积，获得双盲一致的结果。 结论： 茜素红S染色和硝酸银染色的检测结果一致，但前者相比后者具有操作快捷简便的特点，且阳性信号更容易识别，可作为血管钙化疾病中显示钙盐沉积的首选方法推荐。.

OBJECTIVE: to investigate whether baseline mineral distribution modulates the ability of silver diammine fluoride (SDF) to remineralize and stain enamel caries lesions.
METHODS: This laboratory study followed a 3 [treatment: SDF/fluoride varnish (FV)/deionized water (DIW)] ×3 [lesion protocol: methylcellulose (MeC)/hydroxyethylcellulose (HEC)/Carbopol 907 (C907)] factorial design. Lesions were created in bovine enamel specimens (n = 20). Treatments were applied and lesions remineralized in artificial saliva. Digital transverse microradiography (TMR-D) was used to analyze lesions. Lesion color was monitored spectrophotometrically. The effects of lesion protocol and treatment on changes in lesion depth (ΔLD), mineral loss (ΔΔZ), maximum mineral density at the surface zone (ΔSZmax), and color changes related to remineralization (ΔL*remin) were analyzed using two-way ANOVA.
RESULTS: The treatment×lesion protocol interaction was significant for ΔΔZ (p < 0.01) and ΔL*remin (p < 0.01), however not for ΔLD (p = 0.23) or ΔSZmax (p = 0.91). There were no differences in ΔΔZ between treatments in HEC and C907 lesions. However, DIW resulted in more remineralization than both SDF (p < 0.01) and FV (p = 0.01) in MeC lesions. Considering changes from lesion baseline after remineralization in MeC lesions, SDF treatment resulted in the highest mineral gain in the surface zone. However, DIW revealed the highest mineral gain after remineralization in the lesion body. SDF stained lesions with the intensity increasing after remineralization in C907 lesions, whereas staining decreased in MeC and HEC lesions.
CONCLUSIONS: High fluoride treatments can interfere with continuous remineralization of caries lesions due to partial arrest. Baseline lesion mineral distribution affects SDF\'s ability to enhance remineralization and the staining caused by SDF.
CONCLUSIONS: SDF is being used to arrest active caries lesions extending into dentin and to treat dentin hypersensitivity. This study shed light on SDF\'s effect on an isolated process in dental caries only, remineralization. It achieved this by examining enamel caries lesions with differing mineral distributions and assessing their staining properties.

BACKGROUND: The brain is built of neurons supported by myelin, a fatty substance that improves cellular communication. Noninvasive magnetic resonance imaging (MRI) is now able to measure brain structure like myelin and requires histological validation.
METHODS: Here we present work in small and large biomedical model mammals to standardize a silver impregnation method as a high-throughput histological myelin visualization procedure. Specifically, we built a new staining well plate to increase batch size, and then systematically varied the staining and clearing cycles to describe the staining response curve across taxa and conditions. We compared tissues fixed by immersion or perfusion, mounted versus free-floating, and cut as thicker or thinner slices, with two-weeks of post-fixation.
RESULTS: The staining response curves show optimal staining with a single exposure across taxa when incubation and clearing epochs are held to within 3-9 min. We show that clearing was slower in mounted vs free-floating tissue, and that staining was faster and caused fracturing earlier in thinner sliced and smaller volumes of tissue.
METHODS: We developed a batch processing approach to increase throughput while ensuring reproducibility and demonstrate the optimal conditions for fine myelinated fiber morphology visualization with short cycles (<9 minutes).
CONCLUSIONS: We present our optimized protocol to reveal mesoscale neuroanatomical myelin content in histology across mammals. This standard staining procedure will facilitate multiscale analyses of myelin content across development as well as in the presence of injury or disease.

Golgi methods were used to study human neuropathology in the 1970s, 1980s, and 1990s of the last century. Although a relatively small number of laboratories applied these methods, their impact was crucial by increasing knowledge about: (1) the morphology, orientation, and localization of neurons in human cerebral and cerebellar malformations and ganglionic tumors, and (2) the presence of abnormal structures including large and thin spines (spine dysgenesis) in several disorders linked to mental retardation, focal enlargements of the axon hillock and dendrites (meganeurites) in neuronal storage diseases, growth cone-like appendages in Alzheimer disease, as well as abnormal structures in other dementias. Although there were initial concerns about their reliability, reduced dendritic branches and dendritic spines were identified as common alterations in mental retardation, dementia, and other pathological conditions. Similar observations in appropriate experimental models have supported many abnormalities that were first identified using Golgi methods in human material. Moreover, electron microscopy, immunohistochemistry, fluorescent tracers, and combined methods have proven the accuracy of pioneering observations uniquely visualized as 3D images of fully stained individual neurons. Although Golgi methods had their golden age many years ago, these methods may still be useful complementary tools in human neuropathology.

The objective of this chapter is to provide an overview of the methods used to investigate the connectivity and structure of the nervous system. These methods allow neuronal cells to be categorized according to their location, shape, and connections to other cells. The Golgi-Cox staining gives a thorough picture of all significant neuronal structures found in the brain that may be distinguished from one another. The most significant characteristic is its three-dimensional integrity since all neuronal structures may be followed continuously from one part to the next. Successions of sections of the brain\'s neurons are seen with the Golgi stain. The Golgi method is used to serially segment chosen brain parts, and the resulting neurons are produced from those sections.

Traumatic brain injury (TBI) is a leading cause of morbidity and mortality, especially in teenagers to young adults. In recent decades, different biomarkers and/or staining protocols have been employed to evaluate the post-injury development of pathological structures, but they have produced many contradictory findings. Since correctly identifying the underlying neuroanatomical changes is critical to advancing TBI research, we compared three commonly used markers for their ability to detect TBI pathological structures: Fluoro-Jade C, the rabbit monoclonal antibody Y188 against amyloid precursor protein and the NeuroSilver kit were used to stain adjacent slices from naïve or injured mouse brains harvested at different time points from 30 min to 3 months after lateral fluid percussion injury. Although not all pathological structures were stained by all markers at all time points, we found damaged neurons and deformed dendrites in gray matter, punctate and perivascular structures in white matter, and axonal blebs and Wallerian degeneration in both gray and white matter. The present study demonstrates the temporal and structural sensitivities of the three biomarkers: each marker is highly effective for a set of pathological structures, each of which in turn emerges at a particular time point. Furthermore, the different biomarkers showed different abilities at detecting identical types of pathological structures. In contrast to previous studies that have used a single biomarker at a single time range, the present report strongly recommends that a combination of different biomarkers should be adopted and different time points need to be checked when assessing neuropathology after TBI.

Quantification of the histological staining images gives important insights in biomedical research. In wet lab, it is common to have some stains off the target to become unwanted noisy stains during the generation of histological staining images. The current tools designed for quantification of histological staining images do not consider such situations; instead, the stained region is identified based on assumptions that the background is pure and clean. The goal of this study is to develop a light software named Staining Quantification (SQ) tool which could handle the image quantification job with features for removing a large amount of unwanted stains blended or overlaid with Region of Interest (ROI) in complex scenarios. The core algorithm was based on the method of higher order statistics transformation, and local density filtering. Compared with two state-of-art thresholding methods (i.e. Otsu\'s method and Triclass thresholding method), the SQ tool outperformed in situations such as (1) images with weak positive signals and experimental caused dirty stains; (2) images with experimental counterstaining by multiple colors; (3) complicated histological structure of target tissues. The algorithm was developed in R4.0.2 with over a thousand in-house histological images containing Alizarin Red (AR) and Von Kossa (VK) staining, and was validated using external images. For the measurements of area and intensity in total and stained region, the average mean of difference in percentage between SQ and ImageJ were all less than 0.05. Using this as a criterion of successful image recognition, the success rate for all measurements in AR, VK and external validation batch were above 0.8. The test of Pearson\'s coefficient, difference between SQ and ImageJ, and difference of proportions between SQ and ImageJ were all significant at level of 0.05. Our results indicated that the SQ tool is well established for automatic histological staining image quantification.

OBJECTIVE: Oral cancer is the sixth most common kind of human cancer. Brush cytology for counting Argyrophilic Nucleolar Organizer Regions (AgNORs) can help early mouth cancer detection, lowering patient mortality. However, the manual counting of AgNORs still in use today is time-consuming, labor-intensive, and error-prone. The goal of our work is to address these shortcomings by proposing a convolutional neural network (CNN) based method to automatically segment individual nuclei and AgNORs in microscope slide images and count the number of AgNORs within each nucleus.
METHODS: We systematically defined, trained and tested 102 CNNs in the search for a high-performing solution. This included the evaluation of 51 network architectures combining 17 encoders with 3 decoders and 2 loss functions. These CNNs were trained and evaluated on a new AgNOR-stained image dataset of epithelial cells from oral mucosa containing 1,171 images from 48 patients, with ground truth annotated by specialists. The annotations were greatly facilitated by a semi-automatic procedure developed in our project. Overlapping nuclei, which tend to hide AgNORs, thus affecting their true count, were discarded using an automatic solution also developed in our project. Besides the evaluation on the test dataset, the robustness of the best performing model was evaluated against the results produced by a group of human experts on a second dataset.
RESULTS: The best performing CNN model on the test dataset consisted of a DenseNet-169 + LinkNet with Focal Loss (DenseNet-169 as encoder and LinkNet as decoder). It obtained a Dice score of 0.90 and intersection over union (IoU) of 0.84. The counting of nuclei and AgNORs achieved precision and recall of 0.94 and 0.90 for nuclei, and 0.82 and 0.74 for AgNORs, respectively. Our solution achieved a performance similar to human experts on a set of 291 images from 6 new patients, obtaining Intraclass Correlation Coefficient (ICC) of 0.91 for nuclei and 0.81 for AgNORs with 95% confidence intervals of [0.89, 0.93] and [0.77, 0.84], respectively, and p-values < 0.001, confirming its statistical significance. Our AgNOR-stained image dataset is the most diverse publicly available AgNOR-stained image dataset in terms of number of patients and the first for oral cells.
CONCLUSIONS: CNN-based joint segmentation and quantification of nuclei and NORs in AgNOR-stained images achieves expert-like performance levels, while being orders of magnitude faster than the later. Our solution demonstrated this by showing strong agreement with the results produced by a group of specialists, highlighting its potential to accelerate diagnostic workflows. Our trained model, code, and dataset are available and can stimulate new research in early oral cancer detection.

Antibodies are essential components of the immune system with a wide range of molecular targets. They have been recognized as modalities for treating several diseases and more than 130 approved antibody-based therapeutics are available for clinical use. However, limitations remain associated with its efficacy, tissue permeability, and safety, especially in cancer treatment. Nanoparticles, particularly those responsive to external stimuli, have shown promise in improving the efficacy of antibody-based therapeutics and tissue-selective delivery. In this study, we developed a reliable and accurate method for quantifying the amount of antibody loaded onto lipid nanoparticles modified with Herceptin® (Trastuzumab), an antibody-based therapeutic used to treat HER2-positive cancers, using sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) followed by silver staining. This method proved to be a suitable alternative to commonly used protein quantification techniques, which are limited by lipid interference present in the samples. Furthermore, the amount of Herceptin modified on the liposomes, measured by this method, was confirmed by Herceptin\'s antibody-dependent cell-mediated cytotoxicity activity. Our results demonstrate the potential of this method as a critical tool for developing tissue-selective antibody delivery systems, leading to improved efficacy and reduced side effects of antibody-based therapeutics.

Two siblings with deletion mutation ∆K281 in MAPT developed frontotemporal dementia. At autopsy, numerous inclusions of hyperphosphorylated 3R Tau were present in neurons and glial cells of neocortex and some subcortical regions, including hippocampus, caudate/putamen and globus pallidus. The inclusions were argyrophilic with Bodian silver, but not with Gallyas-Braak silver. They were not labelled by an antibody specific for tau phosphorylated at S262 and/or S356. The inclusions were stained by luminescent conjugated oligothiophene HS-84, but not by bTVBT4. Electron cryo-microscopy revealed that the core of tau filaments was made of residues K254-F378 of 3R Tau and was indistinguishable from that of Pick\'s disease. We conclude that MAPT mutation ∆K281 causes Pick\'s disease.