Cost-effectiveness of a machine learning risk prediction model (LungFlag) in the selection of high-risk individuals for non-small cell lung cancer screening in Spain.

Objective: The LungFlag risk prediction model uses individualized clinical variables to identify individuals at high-risk of non-small cell lung cancer (NSCLC) for screening with low-dose computed tomography (LDCT). This study evaluates the cost-effectiveness of LungFlag implementation in the Spanish setting for the identification of individuals at high-risk of NSCLC.

Methods: A model combining a decision-tree with a Markov model was adapted to the Spanish setting to calculate health outcomes and costs over a lifetime horizon, comparing two hypothetical scenarios: screening with LungFlag versus non-screening, and screening with LungFlag versus screening the entire population meeting 2013 US Preventive Services Task Force (USPSTF) criteria.

Integration of spectroscopic techniques and machine learning for optimizing Phaeodactylum tricornutum cell and fucoxanthin productivity.

The development of sustainable and controlled microalgae bioprocesses relies on robust and rapid monitoring tools that facilitate continuous process optimization, ensuring high productivity and minimizing response times. In this work, we analyse the influence of medium formulation on the growth and productivity of axenic Phaeodactylum tricornutumcultures and use the resulting data to develop machine learning (ML) models based on spectroscopy. Our culture assays produced a comprehensive dataset of 255 observations, enabling us to train 55 (24+31) robust models that predict cells or fucoxanthin directly from either absorbance or 2D-fluorescence spectroscopy.

Unbiased discovery of antibody therapies that stimulate macrophage-mediated destruction of B-cell lymphoma.

Macrophages are critical effectors of antibody therapies for lymphoma, but the best targets for this purpose remain unknown. Here, we sought to define a comprehensive repertoire of cell surface antigens that can be targeted to stimulate macrophage-mediated destruction of B-cell lymphoma. We developed a high-throughput assay to screen hundreds of antibodies for their ability to provoke macrophages to attack B-cell lymphoma cells.

Evocation of positive memories as complement to trauma-focused cognitive-behavioural therapy for intimate partner violence against women.

Focusing on positive memories as a complement to trauma-focused interventions for intimate partner violence against women (IPVAW) could contribute to enhancing the recovery from trauma with the development of a more integrated and emotionally modulated autobiographical narrative. To test the effectiveness of a trauma-focused cognitive behavioural therapy (CBT) tailored for IPVAW that incorporates the evocation of positive memories. Female survivors of IPVAW entered a randomized controlled trial comparing trauma-focused CBT for IPVAW (CBT;  = 35) to a version that incorporates the evocation of positive memories (CBT-M+;  = 44) and to a waitlist (WL;  = 12) control group.