Low Cell Bioenergetic Metabolism Characterizes Chronic Lymphocytic Leukemia Patients with Unfavorable Genetic Factors and with a Better Response to BTK Inhibition.

Chronic Lymphocytic Leukemia (CLL) is an indolent malignancy characterized by the accumulation of quiescent mature B cells. However, these cells are transcriptionally and translationally active, implicating an active metabolism. The recent literature suggests that CLL cells have an oxidative-type phenotype. Given the role of cell metabolism, which is able to influence the outcome of treatments, in other neoplasms, we aimed to assess its prognostic role in CLL patients by determining the ex vivo bioenergetic metabolic profile of CLL cells, evaluating the correlation with the patient clinical/biological characteristics and the in vivo response to BTK inhibitor treatment. Clustering analysis of primary samples identified two groups, characterized by low (CLL low) or high (CLL high) bioenergetic metabolic rates. Compared to the CLL high, CLL with lower bioenergetic metabolic rates belonged to patients characterized by a statistically significant higher white blood cell count and by unfavorable molecular genetics. More importantly, patients in the CLL low cluster displayed a better and more durable response to the BTK inhibitor ibrutinib, thus defining a bioenergetic metabolic subgroup that can benefit the most from this therapy.

Wind speed and direction estimation based on the spatial coherence of closely spaced microphones.

Wind-induced noise recorded with a compact microphone array can be exploited to infer the mean velocity of the free-field airflow. In this work, a model-based method to estimate the wind flow speed and direction is proposed that uses spectro-spatial correlations of closely spaced microphone signals. As shown in a recent work by the present authors, the normalized cross-power spectral density of flow-induced noise measured with closely spaced microphones, also referred to as the spatial coherence, can be approximated by a semi-empirical model, named the Corcos model. Due to the dependency of the Corcos model on the airflow velocity, the measured spatial coherence provides information on the sought quantity. Speed and direction can be resolved by fitting the measured spatial coherence to the analytical Corcos model in the least squares sense. The accuracy of the proposed method is investigated across a range of wind speed between 0.5 and 12 ms-1 and all directions, using observation lengths from 5 s to 1 h. The audio samples under test were recorded indoors and outdoors and labeled by an ultrasonic anemometer. The evaluation results show that the accuracy can be increased by reducing the time resolution.

Generating coherence-constrained multisensor signals using balanced mixing and spectrally smooth filters.

The spatial properties of a noise field can be described by a spatial coherence function. Synthetic multichannel noise signals exhibiting a specific spatial coherence can be generated by properly mixing a set of uncorrelated, possibly non-stationary, signals. The mixing matrix can be obtained by decomposing the spatial coherence matrix. As proposed in a widely used method, the factorization can be performed by means of a Choleski or eigenvalue decomposition. In this work, the limitations of these two methods are discussed and addressed. In particular, specific properties of the mixing matrix are analyzed, namely, the spectral smoothness and the mix balance. The first quantifies the mixing matrix-filters variation across frequency and the second quantifies the number of input signals that contribute to each output signal. Three methods based on the unitary Procrustes solution are proposed to enhance the spectral smoothness, the mix balance, and both properties jointly. A performance evaluation confirms the improvements of the mixing matrix in terms of objective measures. Furthermore, the evaluation results show that the error between the target and the generated coherence is lowered by increasing the spectral smoothness of the mixing matrix.