A Computer Vision-Based System to Help Health Professionals to Apply Tests for Fall Risk Assessment.

The increase in life expectancy, and the consequent growth of the elderly population, represents a major challenge to guarantee adequate health and social care. The proposed system aims to provide a tool that automates the evaluation of gait and balance, essential to prevent falls in older people. Through an RGB-D camera, it is possible to capture and digitally represent certain parameters that describe how users carry out certain human motions and poses. Such individual motions and poses are actually related to items included in many well-known gait and balance evaluation tests. According to that information, therapists, who would not need to be present during the execution of the exercises, evaluate the results of such tests and could issue a diagnosis by storing and analyzing the sequences provided by the developed system. The system was validated in a laboratory scenario, and subsequently a trial was carried out in a nursing home with six residents. Results demonstrate the usefulness of the proposed system and the ease of objectively evaluating the main items of clinical tests by using the parameters calculated from information acquired with the RGB-D sensor. In addition, it lays the future foundations for creating a Cloud-based platform for remote fall risk assessment and its integration with a mobile assistant robot, and for designing Artificial Intelligence models that can detect patterns and identify pathologies for enabling therapists to prevent falls in users under risk.

Activation of the PP2A-B56α heterocomplex synergizes with venetoclax therapies in AML through BCL2 and MCL1 modulation.

Venetoclax combination therapies are becoming the standard of care in acute myeloid leukemia (AML). However, the therapeutic benefit of these drugs in older/unfit patients is limited to only a few months, highlighting the need for more effective therapies. Protein phosphatase 2A (PP2A) is a tumor suppressor phosphatase with pleiotropic functions that becomes inactivated in ∼70% of AML cases. PP2A promotes cancer cell death by modulating the phosphorylation state in a variety of proteins along the mitochondrial apoptotic pathway. We therefore hypothesized that pharmacological PP2A reactivation could increase BCL2 dependency in AML cells and, thus, potentiate venetoclax-induced cell death. Here, by using 3 structurally distinct PP2A-activating drugs, we show that PP2A reactivation synergistically enhances venetoclax activity in AML cell lines, primary cells, and xenograft models. Through the use of gene editing tools and pharmacological approaches, we demonstrate that the observed therapeutic synergy relies on PP2A complexes containing the B56α regulatory subunit, of which expression dictates response to the combination therapy. Mechanistically, PP2A reactivation enhances venetoclax-driven apoptosis through simultaneous inhibition of antiapoptotic BCL2 and extracellular signal-regulated kinase signaling, with the latter decreasing MCL1 protein stability. Finally, PP2A targeting increases the efficacy of the clinically approved venetoclax and azacitidine combination in vitro, in primary cells, and in an AML patient-derived xenograft model. These preclinical results provide a scientific rationale for testing PP2A-activating drugs with venetoclax combinations in AML.