COMBINING MASS SPECTROMETRY-BASED PHOSPHOPROTEOMICS WITH A NETWORK-BASED APPROACH TO REVEAL FLT3-DEPENDENT MECHANISMS OF CHEMORESISTANCE

Combining Mass Spectrometry-Based Phosphoproteomics with a Network-Based Approach to Reveal FLT3-Dependent Mechanisms of Chemoresistance

FLT3 mutations are the most frequently identified genetic alterations in acute myeloid leukemia (AML) and are associated with poor clinical outcome, relapse and chemotherapeutic resistance.Elucidating the molecular mechanisms Dong Quai underlying FLT3-dependent pathogenesis and drug resistance is a crucial goal of biomedical research.Given the comp

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Assessing the Impact of Prolonged Sitting and Poor Posture on Lower Back Pain: A Photogrammetric and Machine Learning Approach

Prolonged static sitting at the workplace is considered one of the main risks for the development of musculoskeletal disorders (MSDs) and adverse health effects.Factors such as poor posture and extended sitting are perceived to be a reason for conditions such as lumbar discomfort and lower back pain (LBP), even though the scientific explanation of

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Systematic Mapping of Global Research on Disaster Damage Estimation for Buildings: A Machine Learning-Aided Study

Research on disaster damage estimation for buildings has gained extensive attention due to the increased number of disastrous events, facilitating risk assessment, the effective integration of disaster resilience measures, and policy development.A systematic mapping study has been conducted, focusing on disaster damage estimation studies to identif

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