Beyond the marrow:insights from comprehensive next-generation sequencing of extramedullary multiple myeloma tumors

Extramedullary multiple myeloma (EMM) is an aggressive form of multiple myeloma (MM). This study represents the most comprehensive next-generation sequencing analysis of EMM tumors (N = 14) to date, uncovering key molecular features and describing the tumor microenvironment. We observed the co-occurrence of 1q21 gain/amplification and MAPK pathway mutations in 79% of EMM samples, suggesting that these are crucial mutational events in EMM development. We also demonstrated that patients with mutated KRAS and 1q21 gain/amplification at the time of diagnosis have a significantly higher risk of EMM development (HR = 2.4, p = 0.011) using data from a large CoMMpass dataset. We identified downregulation of CXCR4 and enhanced cell proliferation, along with reduced expression of therapeutic targets (CD38, SLAMF7, GPRC5D, FCRH5), potentially explaining diminished efficacy of immunotherapy. Conversely, we identified significantly upregulated EZH2 and CD70 as potential future therapeutic options. For the first time, we report on the tumor microenvironment of EMM, revealing CD8+ T cells and NK cells as predominant immune effector cells using single-cell sequencing. Finally, this is the first longitudinal study in EMM revealing the molecular changes from the time of diagnosis to EMM relapse.</p

Structural integrity assessment of railway bridges during the passage of trains

Traditional algorithms for the identification of dynamic parameters based on vibrational structural response generally involve strict assumptions about stationarity and may not be suitable for time-varying systems. Therefore, there is a tendency to discard the measurements of the structural response collected during short-time events, such as train passages on bridges. The response to a strong event may however include valuable information about structural features that cannot be observed in low-excitation scenarios. Moreover, a strong excitation typically generates a higher-amplitude structural response, which is particularly convenient when using low-cost instrumentation for data collection that is usually characterized by low sensitivity. In this paper, dynamic parameters of bridges during the passage of trains are identified by fitting the structural response to a simplified analytical model specialized for railway applications. The efficacy of a damage index based on the fitting residuals is investigated using a numerical study, simulating the use of an event-triggered smart sensing system. Applying the proposed method, damage detection can be achieved using a single low-cost sensing node