Colorectal cancer (CRC) burden across the world is expected to increase by ~2.2 million new cases and ~1.1 million deaths by 2030. Regular physical exercise is recommended to prevent CRC, but the myriad of protocols preclude further discussion on how to manage its variables for this population. Home-based exercise guided by remote monitoring provides an alternative to surpass the barriers of supervised exercise. However, no meta-analysis was conducted to verify the effectiveness of this intervention for improving physical activity (PA). We performed a systematic review of remote and unsupervised strategies imposed on CRC patients for improving PA and compared, via a meta-analysis, their effectiveness against CRC patients submitted to usual care or no intervention. The databases PubMed, Scopus, and Web of Science were searched on 20 September 2022. Eleven studies attained the criteria for eligibility in the qualitative approach, and seven were included in the meta-analysis. No significant effect (p = 0.06) of remote and unsupervised exercise intervention was observed. However, a sensitivity analysis including three studies that only considered CRC patients was performed, demonstrating a significant effect in favor of exercise (p = 0.008). Based on our sensitivity analysis, remote and unsupervised exercise strategies were effective to improve the PA of CRC patients.

Background/Objectives: Major depressive disorder is a significant public health concern linked to factors such as a low-quality diet, a sedentary lifestyle, and poor sleep quality, all of which contribute to its development; nevertheless, the existing literature lacks a comprehensive framework to effectively integrate these interrelated influences. Methods: To address this gap, we conducted a questionnaire-based study involving 411 individuals aged 18 to 74 and employed a weighted complex network model to clarify the associations among nutritional factors, physical activity levels, psychological parameters, and sleep profiles and depression. In addition to constructing networks that encompass distinct subgroups based on general context, sex differences (female vs. male), and four age categories, our network was designed with a clearly defined target: the score from the Beck Depression Inventory. Results: In all networks studied, psychological parameters (e.g., tension, depression, hostility, fatigue, confusion, and total mood disturbance) emerged as the most influential nodes in relation to the targeted node (Eigenvector centrality of approximately 0.30). Additionally, sleep quality was identified as the next most relevant parameter for the general network (Eigenvector = 0.25), while nutritional factors—particularly carbohydrates—demonstrated greater prestige within the male network (Eigenvector = 0.06). Nutritional parameters had a stronger influence on depressive symptoms among individuals aged 29–39 years (Eigenvectors = 0.09, 0.09, and 0.14 for energy, carbohydrates, and fat, respectively). Conclusions: This novel approach allowed for a clearer visualization of how the studied parameters impact depressive symptoms, revealing significant differences when certain aspects are examined independently across distinct groups.

Three-dimensional (3D) cell culture technologies, which more closely mimic the complex microenvironment of tissue, are being increasingly evaluated as a tool for the preclinical screening of clinically promising new molecules, and studying of tissue metabolism. Studies of metabolites released into the extracellular space (secretome) allow understanding the metabolic dynamics of tissues and changes caused by therapeutic interventions. Although quite advanced in the field of proteomics, studies on the secretome of low molecular weight metabolites (< 1500 Da) are still very scarce. We present an untargeted metabolomic protocol based on the hybrid technique of liquid chromatography coupled with high-resolution mass spectrometry for the analysis of low-molecular-weight metabolites released into the culture medium by 3D cultures and co-culture (secretome model). For that we analyzed HT-29 human colon carcinoma cells and 3T3-L1 preadipocytes in 3D-monoculture and 3D-co-culture. The putative identification of the metabolites indicated a sort of metabolites, among them arachidonic acid, glyceric acid, docosapentaenoic acid and beta-Alanine which are related to cancer and obesity. This protocol represents a possibility to list metabolites released in the extracellular environment in a comprehensive and untargeted manner, opening the way for the generation of metabolic hypotheses that will certainly contribute to the understanding of tissue metabolism, tissue-tissue interactions, and metabolic responses to the most varied interventions. Moreover, it brings the potential to determine novel pathways and accurately identify biomarkers in cancer and other diseases. The metabolites indicated in our study have a close relationship with the tumor microenvironment in accordance with the literature review.

Athymic mice are unable to produce T-cells and are then characterized as immunodeficient. This characteristic makes these animals ideal for tumor biology and xenograft research. New non-pharmacological therapeutics are required owing to the exponential increase in global oncology costs over the last 10 years and the high cancer mortality rate. In this sense, physical exercise is regarded as a relevant component of cancer treatment. However, the scientific community lacks information regarding the effect of manipulating training variables on cancer in humans, and experiments with athymic mice. Therefore, this systematic review aimed to address the exercise protocols used in tumor-related experiments using athymic mice. The PubMed, Web of Science, and Scopus databases were searched without restrictions on published data. A combination of key terms such as athymic mice, nude mice, physical activity, physical exercise, and training was used. The database search retrieved 852 studies (PubMed, 245; Web of Science, 390; and Scopus, 217). After title, abstract, and full-text screening, 10 articles were eligible. Based on the included studies, this report highlights the considerable divergences in the training variables adopted for this animal model. No studies have reported the determination of a physiological marker for intensity individualization. Future studies are recommended to explore whether invasive procedures can result in pathogenic infections in athymic mice. Moreover, time-consuming tests cannot be applied to experiments with specific characteristics such as tumor implantation. In summary, non-invasive, low-cost, and time-saving approaches can suppress these limitations and improve the welfare of these animals during experiments.

Three-dimensional (3D) cell culture technologies, which more closely mimic the complex microenvironment of tissue, are being increasingly evaluated as a tool for the preclinical screening of clinically promising new molecules, and for the study of tissue metabolism. Studies of metabolites released into the extracellular space (secretome) allow understanding the metabolic dynamics of tissues and changes caused by therapeutic interventions. Although quite advanced in the field of proteomics, studies on the secretome of low molecular weight metabolites (< 1500 Da) are still very scarce. We present an untargeted metabolomic protocol based on the hybrid technique of high-performance liquid- chromatography coupled with high-resolution mass spectrometry for the analysis of low-molecular-weight metabolites released into the culture medium by 3D cultures and coculture (secretoma model). For that, we analayzed HT-29 human colon carcinoma cells and 3T3-L1 preadipocytes in 3D-monoculture and 3D-coculture. This protocol represents a possibility to list metabolites released in the extracellular environment in a comprehensive and untargeted manner, opening the way for the generation of metabolic hypotheses that will certainly contribute to the understanding of tissue metabolism, tissue-tissue interactions, and metabolic responses to the most varied interventions. Moreover, it brings potential to determine novel pathways and identify accurate biomarkers in cancer and other diseases. The metabolites indicated in our study have a close relationship with the tumor microenvironment in accordance with the literature review. For the 3D cell culture by levitation we used Bio-Assembler™ system (Bio Science 662840, Greiner One Bio, Americana, Brazil) in the n3D Biosciences and adapted protocol published by: HAISLER, W. L. et al. Three-dimensional cell culturing by magnetic levitation. Nature protocols, v. 8, n. 10, p. 1940-1949, 2013. https://doi.org/10.1038/nprot.2013.125

Three-dimensional (3D) cell culture technologies, which more closely mimic the complex microenvironment of tissue, are being increasingly evaluated as a tool for the preclinical screening of clinically promising new molecules, and for the study of tissue metabolism. Studies of metabolites released into the extracellular space (secretome) allow understanding the metabolic dynamics of tissues and changes caused by therapeutic interventions. Although quite advanced in the field of proteomics, studies on the secretome of low molecular weight metabolites (< 1500 Da) are still very scarce. We present an untargeted metabolomic protocol based on the hybrid technique of high-performance liquid- chromatography coupled with high-resolution mass spectrometry for the analysis of low-molecular-weight metabolites released into the culture medium by 3D cultures and coculture (secretoma model). For that, we analayzed HT-29 human colon carcinoma cells and 3T3-L1 preadipocytes in 3D-monoculture and 3D-coculture. This protocol represents a possibility to list metabolites released in the extracellular environment in a comprehensive and untargeted manner, opening the way for the generation of metabolic hypotheses that will certainly contribute to the understanding of tissue metabolism, tissue-tissue interactions, and metabolic responses to the most varied interventions. Moreover, it brings potential to determine novel pathways and identify accurate biomarkers in cancer and other diseases. The metabolites indicated in our study have a close relationship with the tumor microenvironment in accordance with the literature review. For the 3D cell culture by levitation we used Bio-Assembler™ system (Bio Science 662840, Greiner One Bio, Americana, Brazil) in the n3D Biosciences and adapted protocol published by: HAISLER, W. L. et al. Three-dimensional cell culturing by magnetic levitation. Nature protocols, v. 8, n. 10, p. 1940-1949, 2013. https://doi.org/10.1038/nprot.2013.125