Multi-dimensional Dataset of Stress Measurements based on Performance, Behavioural, and Perceptual Indicators.

The role of humans in industry is changing due to the technological transformation of production processes, which represents a potential source of stress for workers. In this context, the NO-STRESS project aims to combine objective and subjective data collected during task execution to explore causes of work-related stress and propose solutions to mitigate them. This paper describes the within-subjects study design used in the project, where each participant was exposed to all experimental conditions, and outlines the workflow developed during the study.

Small extracellular vesicle-based human melanocyte and melanoma signature.

Intercellular communication is a cell-type and stimulus-dependent event driven not only by soluble factors but also by extracellular vesicles (EVs). EVs include vesicles of different size and origin that contain a myriad of molecules. Among them, small EVs (sEV; <200 nm) have been shown to modulate not just regional cell responses but also distant organ behavior.

Development of a new set of Heuristics for the evaluation of Human-Robot Interaction in industrial settings: Heuristics Robots Experience (HEUROBOX).

Humans and robots will increasingly have to work together in the new industrial context. Therefore, it is necessary to improve the User Experience, Technology Acceptance, and overall wellbeing to achieve a smoother and more satisfying interaction while obtaining the maximum performance possible out of it. For this reason, it is essential to analyze these interactions to enhance User Experience.

Pirin is a prognostic marker of human melanoma that dampens the proliferation of malignant cells by downregulating JARID1B/KDM5B expression.

Originally considered to act as a transcriptional co-factor, Pirin has recently been reported to play a role in tumorigenesis and the malignant progression of many tumors. Here, we have analyzed the diagnostic and prognostic value of Pirin expression in the early stages of melanoma, and its role in the biology of melanocytic cells. Pirin expression was analyzed in a total of 314 melanoma biopsies, correlating this feature with the patient's clinical course.

Melanoma Clinical Decision Support System: An Artificial Intelligence-Based Tool to Diagnose and Predict Disease Outcome in Early-Stage Melanoma Patients.

This study set out to assess the performance of an artificial intelligence (AI) algorithm based on clinical data and dermatoscopic imaging for the early diagnosis of melanoma, and its capacity to define the metastatic progression of melanoma through serological and histopathological biomarkers, enabling dermatologists to make more informed decisions about patient management. Integrated analysis of demographic data, images of the skin lesions, and serum and histopathological markers were analyzed in a group of 196 patients with melanoma. The interleukins (ILs) IL-4, IL-6, IL-10, and IL-17A as well as IFNγ (interferon), GM-CSF (granulocyte and macrophage colony-stimulating factor), TGFβ (transforming growth factor), and the protein DCD (dermcidin) were quantified in the serum of melanoma patients at the time of diagnosis, and the expression of the RKIP, PIRIN, BCL2, BCL3, MITF, and ANXA5 proteins was detected by immunohistochemistry (IHC) in melanoma biopsies.