Metabolic Adaptations in Cancer and the Host Using Models and Advanced Tools.

Cancer is a multifactorial process involving genetic, epigenetic, physiological, and metabolic changes. The ability of tumours to regulate new reactive pathways is essential for their survival. A key aspect of this involves the decision-making process of cancer cells as they balance the exploitation of surrounding and distant tissues for their own benefit while avoiding the rapid destruction of the host.

Factors associated with obtaining lower IQR-CAP values in the detection of hepatic steatosis by transient elastography.

Introduction And Objectives: Controlled attenuation parameter (CAP) has been developed as a non-invasive method for detecting liver steatosis. The aim of the study was to determine factors associated with non-obtaining lower IQR-CAP values.

Materials And Methods: Retrospective revision of medical records of CAP studies for steatosis screening.

Evidence gaps in orthognathic surgery: an international Delphi study.

The aim of this study was to assess the evidence gaps identified in a recent mapping review of orthognathic surgery by evaluating them through consultation with maxillofacial surgeons. Using the Delphi technique, a panel of surgeons who regularly perform orthognathic surgery was engaged. Potential participants were identified through articles included in the mapping review, peer nominations, and social media platforms .

Body composition differences in patients with Metabolic Dysfunction-Associated Steatotic Liver Disease.

Background: Although body composition (BC) has been associated with Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD), there is little evidence of differences in BC in patients with MASLD regarding body mass index (BMI). The aim of this study was to determine differences in BC in terms of BMI and metabolic comorbidities in patients with MASLD.

Materials And Methods: It is a cross-sectional study with patients who attended the check-up unit.

Assessing the effectiveness of vegetation indices in detecting forest disturbances in the southeast Amazon.

Amazon forests are becoming increasingly vulnerable to disturbances such as droughts, fires, windstorms, logging, and forest fragmentation, all of which lead to forest degradation. Nevertheless, quantifying the extent and severity of disturbances and their cumulative impact on forest degradation remains a significant challenge. In this study, we combined multispectral data from Landsat sensors with hyperspectral data from the Earth Observing-One (Hyperion/EO-1) sensor to evaluate the efficacy of multiple vegetation indices in detecting forest responses to disturbances in an experimentally burned forest in southeastern Amazonia.