Quantifies pulmonary fibrosis by measuring the collagen-to-tissue ratio in rat lung sections stained with Masson’s trichrome. Collagen is stained blue, making it easily distinguishable from other tissue types. Using 5X magnification and a random 50% sampling, this method provides an accurate and robust estimation of fibrosis in the lung parenchyma.

Detects and quantifies cells and probe signals in dual probe RNAscope images for hepatocellular carcinoma (HCC) diagnosis. Automatically identifies cells and classifies them based on the number of associated probe signals, enhancing sensitivity and specificity for early detection of HCC markers.

Automatically detects and quantifies probes for genes including ANGPT2, EGLN3, GLP1R, HIF1A, PECAM1, SLC2A1, and dapB using RNAscope. Each cell is classified as 0, 1+, 2+, 3+, or 4+ based on the number of probes it contains, as recommended by ACD, ensuring high sensitivity and specificity in gene expression analysis.

Automatically detects and quantifies RNAscope probes associated with cell nuclei in the dermis and epidermis, leveraging a probe design strategy for increased sensitivity and specificity. The protocol does not require manual outlining, as dermis and epidermis regions are identified automatically.

Quantifies nasal mucous cell metaplasia (MCM) in the respiratory epithelium by measuring the volume of mucosubstances per length of basal lamina using Alcian Blue (pH 2.5)/Periodic Acid-Schiff (AB/PAS or AB-PAS) staining. This helps assess the degree of MCM, often seen in allergic airways diseases after allergen exposure.

Quantifies pulmonary mucous cell metaplasia (MCM) in bronchioles by measuring the volume of mucosubstances per length of basal lamina using Alcian Blue (pH 2.5)/Periodic Acid-Schiff (AB/PAS or AB-PAS) staining. This assessment aids in evaluating the degree of MCM, often observed in allergic airways diseases such as asthma after allergen exposure.

Provides consistent positive and negative reference materials for accurate and reproducible IHC assay development and quality control. The ROS1 analysis algorithms for ONCOtopix® quantify ROS1 protein expression, offering positive ratio or H-Score outputs to identify negative, intermediate, and positive cores. Combining IHC HDx™ Cell lines with ONCOtopix and the ROS1 APP ensures a high-quality reagent QC system.

Quantifies nuclear expression of Survivin, a protein that inhibits apoptosis, regulates cell division, and enhances angiogenesis. This tool has shown a statistically significant correlation to manual scoring in a study involving 300 patients, aiding in the assessment of Survivin’s role in cancer progression, particularly in non-muscle invasive bladder cancer.

This Quickstart APP detects and outlines tissue in a brightfield (RGB) image without any manual annotation. Trained on IHC and H&E slides, it’s designed to get you started on tissue analysis without building from scratch. After tissue detection, you may segment specific regions of tissue you want to analyze further

Evaluates nervous tissue by quantifying axon cross-sectional area, myelin thickness, and the G-ratio (axon major axis length / myelin major axis length). Automatically detects nerve cross sections, assessing large, small, and degenerated nerve fibers. Partitions small and large fibers into axon and myelin, exporting key parameters such as major axis length per axon. This protocol is useful for studying neurodegenerative diseases and various neuropathies.

Quantifies cytoplasmic expression of TRIM29, a protein involved in cell proliferation through p53 inhibition and implicated in tumor growth and DNA damage response. High correlation to manual scoring (R² = 0.78) has been demonstrated in a study involving 300 patients. This tool aids in assessing TRIM29 expression, which is linked to poor prognosis in several cancers and functions variably as an oncogene or tumor suppressor depending on the cancer type.

Quantifies cytoplasmic expression of UBE2C, a marker with high expression in various cancers and low expression in normal tissues. High UBE2C levels correlate with poor survival in several cancers and may indicate tumor response to therapy when down-regulated. This tool shows a statistically significant correlation to manual scoring in a study involving 300 patients.