Automatically quantifies CD3 positive T-cells and CD20 positive B-cells within CK positive ducts in salivary gland tissue, aiding in the evaluation of lymphocytic infiltration relevant to Sjögren’s syndrome. This facilitates the study of the pathogenesis and outcomes of the disease, addressing the challenge of manual evaluation.

Automates and accelerates the quantification of CD3 positive T cells in lung biopsies to study acute rejection and its link to chronic rejection in lung transplantation. By identifying CD3 positive areas and calculating the CD3 positive ratio, this method provides insights into the immunological mechanisms and the role of regulatory T lymphocytes (Tregs) in graft tolerance and patient outcomes.

Addresses lymphocytic colitis by quantifying T-lymphocytes targeted by the CD3 marker in different tissue compartments. This method helps in diagnosing microscopic colitis, characterized by increased lymphocytes, specifically distinguishing lymphocytic colitis from collagenous colitis.

Measures the ratio of uNK cells among stromal cells near the epithelial edge in approximately 3 µm sections of endometrial tissue immunostained with anti-CD56 monoclonal antibody and counterstained with Mayer’s haematoxylin. This tool excludes cells in the glands and the epithelial edge from the calculations, aiding in the study of recurrent miscarriage and implantation failure.

Evaluates the number or density of CD57 positive nuclei, aiding in the investigation of tumor infiltrating NK cells in ovarian cancer. This assessment supports research on the prognostic and therapeutic potential of NK cells in cancer treatment.

Quantifies the number of positive cells in serial section TMAs stained with CD68 and CD163, enabling the calculation of the M2/M1 ratio as #CD163/(#CD68 – #CD163). This analysis helps assess the balance between M1-like and M2-like macrophages, which can influence breast cancer development and progression.

Detects and classifies nuclei based on CD74 staining expression in the tumor microenvironment (TME) of melanoma. The “10130 – CD74, Melanoma, TME” APP categorizes nuclei as negative, 1+, 2+, or 3+ according to the level of CD74 expression around each nucleus, aiding in prognostic evaluation and immune response analysis.

Assesses tumors by determining CD8 positivity, automatically identifying and outlining tissue and tumor regions. Provides the number of positive and negative nuclei and the positive percentage, with adjustable sensitivity and threshold settings for different staining intensities.

This Quickstart APP segments cells in images captured by imaging mass cytometry (IMC), such as those acquired by the Hyperion XTi imaging system by Standard Biotools. Despite the high background noise in IMC images, this APP segments cells based on DNA channels, ensuring high accuracy and precision

Quantifies epidermal expression of CK16, a marker for epidermal hyperplasia associated with inflammatory skin diseases like atopic dermatitis and psoriasis. The protocol categorizes CK16 staining intensity into four levels: no staining (negative), low (1+), medium (2+), and high (3+), and calculates an intensity score based on these categories.​

Detects and classifies nuclei based on COX2 staining expression in the tumor microenvironment (TME) of melanoma. The “10133 – COX2, Melanoma, TME” protocol categorizes nuclei as negative, 1+, 2+, or 3+ according to the level of COX2 expression around each nucleus, aiding in the assessment of inflammation and cancer progression.

Detects and classifies nuclei based on COX2 staining expression in the tumor microenvironment (TME) of melanoma. The “10133 – COX2, Melanoma, TME” protocol categorizes nuclei as negative, 1+, 2+, or 3+ according to the level of COX2 expression around each nucleus, aiding in the assessment of inflammation and cancer progression.