Journal of Exercise & Organ Cross Talk

Abstract Obesity is a major risk factor for metabolic diseases. Subfatin, an adipokine with potential metabolic benefits, is of increasing interest. This study investigated the effects of eight weeks of Moderate-Intensity Interval Training (MIIT) on plasma subfatin levels and body composition in sedentary, obese, middle-aged women. Thirty sedentary women (aged 50-60 years; BMI >30 kg/m²) were purposively selected and randomly assigned to an experimental (n=15) or a control (n=15) group. The experimental group performed an eight-week MIIT program (three sessions/week) at an intensity of 50-75% of heart rate reserve, following the principle of progressive overload. The control group maintained their usual sedentary routine. Fasting plasma subfatin levels were measured via enzyme-linked immunosorbent assay (ELISA), and body composition indices (BMI, body fat percentage [BFP], waist-to-hip ratio [WHR]) were assessed pre- and post-intervention. The MIIT group exhibited a significant increase in plasma subfatin levels (p=0.016) and a significant decrease in BFP (p=0.01) compared to the control group. While positive trends were observed, no significant inter-group differences were found for BMI (p>0.05) or WHR (p=0.095). An eight-week MIIT program effectively elevated plasma subfatin concentration and reduced body fat percentage in sedentary, obese, middle-aged women. These results suggest that MIIT may be a valuable exercise strategy for improving adipokine profile and body composition in this population.

 
 


 

Abstract The purpose of this research is to investigate the effect of High-intensity interval training and spirulina supplementation on the levels of Pannexin-1 and NLRP-1 proteins in hippocampal tissue in male rats with type 1 diabetes. In this experimental study, 30 Wistar rats, aged 10 weeks and weighing 180-260 grams, were randomly divided into 5 groups of 6 each: exercise group, supplement group, exercise + supplement group, control group, 5 healthy group. After inducing diabetes and implementing the protocol, hippocampal tissue from the rats was extracted, and the levels of PANNXIN-1 and NLRP-1 proteins were measured using the western blot method. Statistical analyses and data processing were conducted using SPSS version 26 software, with significance set at P≤0.05. The results showed a significant increase in Pannexin-1 and NLRP-1 proteins in diabetic rats (P<0.05). There was a noticeable decrease in protein expression after 6 weeks of rigorous intermittent exercise and spirulina supplements in the exercise, supplement, and exercise + supplement groups compared to the diabetic group. This reduction was mostly due to the combined effects of exercise and supplementation rather than either alone. Our research has verified the hypoglycemic effects of intense interval training and spirulina supplementation, along with their impact on reducing PANX-1 and NLRP-1 protein expression. Consequently, it appears that this form of physical activity and herbal supplement could significantly enhance the management of neurodegenerative disorders in individuals with type 1 diabetes.

Abstract This study investigated the effects of resistance training and pineapple extract consumption on intratumoral NF-κB and LIN28B gene expression and serum TNF-α levels in a murine C57 melanoma model. Twenty C57BL/6 mice were allocated into four groups (n=5/group): melanoma tumor control (MT), MT with resistance training (MT+RT), MT with pineapple extract (MT+PJ), and MT with combined intervention (MT+RT+PJ). The RT protocol and PJ administration (300 mg/kg/day via gavage) were conducted for six weeks’ post-tumor induction. Serum TNF-α was quantified by ELISA, and tumor gene expression of NF-κB and LIN28B was analyzed via RT-PCR. Data were analyzed using one-way ANOVA followed by Tukey's post hoc test. All three intervention groups exhibited a significant downregulation of NF-κB and LIN28B gene expression in tumor tissue compared to the MT control group (p<0.05). Conversely, serum TNF-α levels were significantly elevated in the intervention groups relative to the control (p<0.05). Resistance training and pineapple extract consumption, both individually and in combination, significantly modulated pro-tumorigenic pathways by suppressing intratumoral NF-κB and LIN28B expression, despite an observed increase in systemic TNF-α.

Abstract This study aimed to evaluate the individual and combined effects of aerobic training (AT) and pineapple supplementation (extract) on programmed cell death protein 1 (PD-1) gene expression within the tumor microenvironment and on systemic interleukin-10 (IL-10) levels in a murine melanoma model. Twenty C57BL/6 mice were randomly assigned into four groups (n=5 per group) following melanoma tumor induction: Tumor control, AT, Pineapple Supplement (PS), and AT+PS. The AT group underwent a structured aerobic training program, while the PS group received pineapple extract (300 mg/kg/day) via oral gavage for six weeks. Serum IL-10 concentrations were quantified by ELISA, and PD-1 mRNA expression in tumor tissue was analyzed using quantitative RT-PCR. All intervention groups—AT, PS, and their combination—resulted in a significant downregulation of PD-1 gene expression within the tumor compared to the control group (p < 0.05). In contrast, neither AT nor PS alone significantly altered systemic IL-10 levels. The combination therapy (AT+PS) produced the most pronounced suppression of PD-1 and was the only intervention to elicit a significant, though modest, reduction in serum IL-10. These findings indicate that the primary immunomodulatory effect of these interventions is localized to the tumor microenvironment and is largely independent of systemic IL-10 signaling. The synergistic combination of aerobic training and pineapple supplementation potently suppresses PD-1 gene expression, suggesting a promising, non-pharmacological strategy for enhancing anti-tumor immunity. Further investigation is required to confirm these effects at the protein level and to elucidate the underlying mechanisms.

Abstract High blood pressure or hypertension has become the most common cardiovascular and renal risk factor among people around the world and is mainly associated with an inactive lifestyle and unhealthy diet. The aim of the present study was to investigate the effect of eight weeks of moderate-intensity interval training on plasma levels of FoxN1 and blood pressure indices in middle-aged men with hypertension. In the present quasi-experimental study, 32 middle-aged men with an age range of 50-60 years and with high blood pressure were purposefully selected and then randomly assigned to two control (n = 15) and experimental (n = 17) groups. The experimental group performed interval training for eight weeks with a frequency of three sessions per week and an intensity of 50-75% of heart rate reserve based on the principle of gradual overload, while the control group did not participate in any training program. Plasma levels of FoxN1 were measured by the ELISA protein assay. Systolic, diastolic and mean arterial blood pressure were also measured in the subjects of the two groups before and after the training period. to evaluation the normality of the data, the Shapiro-Wilk test was used, and the homogeneity of variances was assessed with the Levene test. The analysis of covariance (ANCOVA) test was also used to compare the variables in the two groups. The data were analyzed at a significance level of 0.05 and using SPSS-23 software. The results showed that eight weeks of moderate-intensity interval training led to a significant increase in FoxN1 (P < 0.05). Also, a significant decrease was observed in systolic blood pressure, diastolic blood pressure, and mean arterial blood pressure after eight weeks of interval training (P < 0.05). According to the results of the present study, it is recommended that people with high blood pressure perform moderate-intensity interval training to control blood pressure, reduce inflammation, and improve immune function.

Abstract Movement disorders such as Parkinson’s disease frequently present with comorbid sleep disturbances, which exacerbate motor symptoms and reduce patients’ quality of life. The striatum, a critical basal ganglia structure, is implicated in both motor control and sleep regulation and represents the key anatomical locus affected in these disorders. While nutritional and exercise interventions have shown promise independently, a significant gap remains in understanding the synergistic molecular crosstalk between these lifestyle modifications and how they collectively target the striatal mechanisms disrupted by sleep deprivation. This review synthesizes evidence to elucidate the integrated, neurobiological effects of combined nutritional and exercise interventions on sleep deprivation-associated movement disorders, emphasizing the striatum’s pivotal role. We establish that exercise, through the induction of neurotrophic factors (like BDNF/GDNF) and enhanced dopaminergic signaling (DAT), provides a critical foundation for synaptic repair. This foundation is synergistically amplified by targeted nutritional strategies, such as polyphenols and omega-3s, which augment antioxidant capacity, dampen neuroinflammation (NRF2/NFκB axis), and modulate key receptors (like A2AR) within the striatum. These combined, non-pharmacological approaches more effectively restore striatal homeostasis and redox balance than either intervention alone, resulting in superior improvement in both motor function and sleep quality. Further longitudinal and mechanistic studies (e.g., RCTs with multimodal endpoints) are warranted to refine optimal intervention protocols and personalize therapeutic strategies. Incorporating these findings into clinical guidelines could promote holistic, synergistic management strategies that improve patient outcomes and reduce healthcare costs.

Abstract The pursuit of peak athletic performance is increasingly driven by technological innovation. This narrative review explores the role of emerging technologies in monitoring, analyzing, and enhancing the capabilities of athletes. We focus on the crosstalk between specific organ systems-the brain, the musculoskeletal system, and the cardiovascular system-and the technologies designed to interface with them. Key areas discussed include neurotechnology for cognitive training and recovery, wearable sensors and imaging for musculoskeletal assessment, and advanced biomonitoring for cardiovascular and metabolic optimization. A summary table synthesizes the technologies, their target organs, and primary applications. While these tools offer unprecedented insights, we also discuss challenges related to data interpretation, integration, and accessibility. The future of athletic performance lies in a holistic, technology-enabled understanding of the athlete as a complete, interconnected system.

Abstract Dear Editor-in-Chief
We are pleased to submit our manuscript, "Unveiling Systemic Complexity: The Role of Artificial Intelligence in Integrative Athlete Monitoring," for peer review and potential publication as a Letter in Exercise & Organ Crosstalk. 
The current paradigm in athlete monitoring, while rich in data from wearables and physiological assays, often struggles with a fundamental challenge: synthesizing disparate data streams into a coherent, holistic model of the athlete's state. While systematic reviews highlight the potential of AI for multivariate injury risk assessment (Claudino et al., 2019), and recent studies demonstrate success in forecasting complex, temporal phenomena like sleep and performance (Mateus et al., 2024), a generalized AI framework for modeling the underlying cross-talk between physiological systems is still lacking. Traditional statistical methods, and even many current AI applications, remain inadequate for fully capturing the non-linear, dynamic, and highly individualized nature of inter-organ communication and systemic response to exercise stress.
Our manuscript directly addresses this challenge by proposing a novel framework that leverages the power of artificial intelligence (AI) and machine learning (ML). We argue that techniques such as recurrent neural networks (RNNs) and graph neural networks (GNNs) are uniquely suited to model the very "cross-talk" that is the focus of your journal. These models can integrate data from the cardiovascular, musculoskeletal, endocrine, and nervous systems to identify complex, latent patterns that predict performance outcomes, fatigue, and injury risk far more accurately than univariate or linear multivariate models.
This work aligns perfectly with the scope of Exercise & Organ Cross Talk, as it moves beyond viewing physiological systems in isolation.We provide a perspective on how AI can act as the essential computational tool to finally quantify and model the deep, systemic interactions that define an athlete's adaptation to training. We believe this perspective will be of significant interest to your readership, stimulating new research at the intersection of computational biology, exercise physiology, and sports medicine.