Adherent stromal cells cultured under three dimensional conditions are provided, characterized, and distinguished from adherent stromal cells cultured under two dimensional conditions.

This invention is directed to compositions and methods for detecting proteinopathies.

The present invention relates to the biomarkers for predicting the clinical response to anti-LPS immunoglobulin treatments in patients in need thereof. In particular, the invention provides methods for predicting the clinical response to an anti-LPS immunoglobulin treatment in a patient in need thereof, said method comprising the steps of evaluating the expression of a predictive biomarker selected from the group consisting of CD14, CD68, TLR4, TLR7, IL6, IL8, IL10, IFN-alpha, IGF1, CXCL1, CXCL9, CXCL10, RAGE, GDNF, BCHE, and combination thereof, in said patient.

Provided are novel IFB-a binding molecules of human origin, particularly human-derived anti-IFN-? antibodies as well as IFN-? binding fragments, derivatives and variants thereof. In addition, pharmaceutical compositions, kits, and methods for use in diagnosis and therapy are described.

The disclosure relates to methods and assay that assists in the diagnosis of autoimmune and chronic inflammatory disorders such as systemic lupus erythematosus and rheumatoid arthritis by analyzing drug-responsiveness of an interferon signal in a hematological sample (e.g., blood) obtained from a human subject. The assay involves comparing the interferon signal in a control aliquot of the sample with the same interferon sample in an aliquot that has been exposed to a therapeutic modality (e.g., combined with a drug) that is known to be efficacious to treat the disorder. A significant difference between the interferon signals of the control and treated aliquots that corresponds to a characteristic interferon signature for the disorder indicates that the subject is afflicted with, or is likely to develop, the disorder.

This document provides methods and materials involved in treating autoimmune conditions. For example, methods and materials for using either (a) one or more tumor necrosis factor alpha (TNF-) inhibitors or (b) one or more Janus kinase (JAK) inhibitors to treat autoimmune conditions such as rheumatoid arthritis are provided.

This invention is directed to compositions and methods for detecting proteinopathies.

Provided are methods for treating cancer by converting tumor-resident macrophages into a hybrid M1/M2 macrophage phenotype; this phenotype has attributes that are advantageous for cancer therapy. Hybrid markers include (lower than M2, higher than M1): SPP1, CD209, and CD206, and induced markers include MERTK, C1QC, IFNa, IFNb, CXCL10, 4-1BBL, and MYC. The methods include administering a therapeutic that effects the phenotypic conversion. Therapeutics, such as delivery vehicles, including immunostimulatory bacteria with genome modifications, are designed so that they do not induce or result in a sufficient TLR2, TLR4, TLR5 response to inhibit type I IFN. The therapeutics also encode a payload that encodes immunostimulatory proteins, such as a cytokine and a modified cytosolic DNA/RNA sensor that constitutively induces type I IFN, such as a modified STING protein. The combination of payload immunostimulatory proteins and properties of the therapeutic delivery vehicle, upon administration, results in macrophage with the hybrid phenotype. The therapeutics are administered to subjects identified as having tumors that comprise proliferating M2 macrophages.

This invention is directed to compositions and methods for detecting proteinopathies.

The present invention relates to the biomarkers for predicting the clinical response to anti-LPS immunoglobulin treatments in patients in need thereof. In particular, the invention provides methods for predicting the clinical response to an anti-LPS immunoglobulin treatment in a patient in need thereof, said method comprising the steps of evaluating the expression of a predictive biomarker selected from the group consisting of CD14, CD68, TLR4, TLR7, IL6, IL8, IL10, IFN-alpha, IGF1, CXCL1, CXCL9, CXCL10, RAGE, GDNF, BCHE, and combination thereof, in said patient.