Quantifies NBCN1 membrane immunoreactivity in tissue sections, measuring the expression of sodium/proton exchangers at the plasma membrane. This tool allows for comparison of matched samples (e.g., tumors versus normal) to correlate localized expression with function and disease status.

Quantifies NHE1 membrane immunoreactivity, measuring the expression of sodium/proton exchangers at the plasma membrane in tissue sections. This tool aids in correlating localized expression with function, allowing comparison of matched samples (e.g., tumors versus normal) to assess expression as a function of disease status.

Measures epidermal thickness and collagen/elastin content in the dermal layer, assessing their relationship to factors like age, gender, skin type, pigmentation, blood content, smoking habits, and body site. Relevant in dermatologic research, particularly for skin diseases such as psoriasis, where epidermal thickness can indicate disease progression and treatment effect. The arithmetic mean thickness is estimated by dividing the epidermis area by its length.

Automates the detection and quantification of p16/Ki-67 dual stained cells in cervical cytology specimens, enhancing the specificity and sensitivity of HPV testing for high-grade lesions. This method reduces the subjectivity and labor intensity of manual evaluation by providing a final review of suspicious cells selected by the computer, outputting a score for each p16/Ki-67 nucleus based on the degree of positively stained cytoplasm.

Uses PAS staining to identify mucosubstances in salivary gland tissue sections. Automatically detects glandular regions of interest and differentiates between mucus and serous glands, aiding in the correlation of mucin expression with tumor grade and type in salivary gland neoplasms.

Quantifies tumor budding in PCK stained colorectal sections by detecting tumor buds in a manually marked invasive front. The protocol assigns hot spots to the ten most affected areas, providing a strong and reproducible prognostic factor for colorectal carcinoma.

Automatically identify invasive cancer areas, count tumor cells based on PD-L1 expression, and calculate the Tumor Proportion Score for NSCLC cases.

Ensures quality control of PD-L1 expression in strong positive, intermediate positive, weak positive, and negative cell line materials by quantifying PD-L1 expression and comparing it to known reference values. This process improves the accuracy and reproducibility of IHC assays, eliminating variability associated with patient-derived reference standards.

Automatically outlines germinal centers in tonsils stained for PD-L1, aiding in the differentiation of tissue regions before evaluating PD-L1 expression. Intended as an accessory APP to isolate regions for further analysis.

Determines the proportion of PD-L1 positive cells by quantifying all cells and classifying PD-L1 positive cells based on brown/DAB positive membrane staining. This helps assess the potential for immune system intervention in tumor cells.

Automatically detects cells and probe signals on RNAscope images to assess PD-L1 expression at the transcriptomic level. Cells are classified based on the number of associated probes, and a composite score is calculated and reported, providing insights into the activity of the PD-L1/PD-1 axis.

Determines the number of tumor and non-tumor cells expressing PD-L1 without needing to outline tumor regions. By combining SOX10, a marker for malignant melanoma, with PD-L1, this method assesses whether PD-L1 expression originates from tumor cells or adjacent non-tumor cells, aiding in the evaluation of immune response modulation in cancer treatment.