Pathological lesions in and around a joint can arise from underlying dermis, subcutis, deep muscle, bone or synovium. Clinical presentation can include joint pain, joint swelling, palpable masses and mechanical restriction. Whilst giant cell tumour of tendon sheath, pigmented villonodular synovitis, synovial chondromatosis, lipoma arborescens, juxta articular myxomas and inflammatory arthritis are the better-known conditions of the joint. Intra-articular nodular fasciitis, on the other hand, is less well recognized both clinically and radiologically. It is rarely seen in routine practice and is only described in case reports in the literature. Due to the non-specific clinical and radiological findings as well as the unfamiliarity with the entity, the diagnosis of intra-articular nodular fasciitis is usually clinched only after histological examination. We present a case of intra-articular nodular fasciitis arising in the knee joint which was not suspected clinically or radiologically
Knee Joint

To address the increasing need for detecting and validating protein biomarkers in clinical specimens, mass spectrometry (MS)-based targeted proteomic techniques, including the selected reaction monitoring (SRM), parallel reaction monitoring (PRM), and massively parallel data-independent acquisition (DIA), have been developed. For optimal performance, they require the fragment ion spectra of targeted peptides as prior knowledge. In this report, we describe a MS pipe-line and spectral resource to support targeted proteomics studies for human tissue samples. To build the spectral resource, we integrated common open-source MS computational tools to assemble a freely accessible computational workflow based on Docker. We then applied the workflow to gen-erate DPHL, a comprehensive DIA pan-human library, from 1096 data-dependent acquisition (DDA) MS raw files for 16 types of cancer samples. This extensive spectral resource was then applied to a proteomic study of 17 prostate cancer (PCa) patients. Thereafter, PRM validation was applied to a larger study of 57 PCa patients and the differential expression of three proteins in prostate tumor was validated. As a second application, the DPHL spectral resource was applied to a study consisting of plasma samples from 19 diffuse large B cell lymphoma (DLBCL) patients and 18 healthy control subjects. Differentially expressed proteins between DLBCL patients and healthy control subjects were detected by DIA-MS and confirmed by PRM. These data demonstrate that the DPHL supports DIA and PRM MS pipelines for robust protein biomarker discovery. DPHL is freely accessible at https://www.iprox.org/page/project.html?id=IPX0001400000.