Bioengineering of exercise: biomechanical and metabolic aspects

The field of research of this dissertation concerns the bioengineering of exercise, in particular the relationship between biomechanical and metabolic knowledge. This relationship can allow to evaluate exercise in many different circumstances: optimizing athlete performance, understanding and helping compensation in prosthetic patients and prescribing exercise with high caloric consumption and minimal joint loading to obese subjects. Furthermore, it can have technical application in fitness and rehabilitation machine design, predicting energy consumption and joint loads for the subjects who will use the machine. The aim of this dissertation was to further understand how mechanical work and metabolic energy cost are related during movement using interpretative models. Musculoskeletal models, when including muscle energy expenditure description, can be useful to address this issue, allowing to evaluate human movement in terms of both mechanical and metabolic energy expenditure. A whole body muscle-skeletal model that could describe both biomechanical and metabolic aspects during movement was identified in literature and then was applied and validated using an EMG-driven approach. The advantage of using EMG driven approach was to avoid the use of arbitrary defined optimization functions to solve the indeterminate problem of muscle activations. A sensitivity analysis was conducted in order to know how much changes in model parameters could affect model outputs: the results showed that changing parameters in between physiological ranges did not influence model outputs largely. In order to evaluate its predicting capacity, the musculoskeletal model was applied to experimental data: first the model was applied in a simple exercise (unilateral leg press exercise) and then in a more complete exercise (elliptical exercise). In these studies, energy consumption predicted by the model resulted to be close to energy consumption estimated by indirect calorimetry for different intensity levels at low frequencies of movement. The use of muscle skeletal models for predicting energy consumption resulted to be promising and the use of EMG driven approach permitted to avoid the introduction of optimization functions. Even though many aspects of this approach have still to be investigated and these results are preliminary, the conclusions of this dissertation suggest that musculoskeletal modelling can be a useful tool for addressing issues about efficiency of movement in healthy and pathologic subjects.

Ottimizzazione del consumo dei grassi durante esercizio fisico: studio di un test per il target mirato di allenamento individuale

Il primo studio ha verificato l'affidabilità del software Polimedicus e gli effetti indotti d'allenamento arobico all’intensità del FatMax. 16 soggetti sovrappeso, di circa 40-55anni, sono stati arruolati e sottoposti a un test incrementale fino a raggiungere un RER di 0,95, e da quel momento il carico è stato aumentato di 1 km/ h ogni minuto fino a esaurimento. Successivamente, è stato verificato se i valori estrapolati dal programma erano quelli che si possono verificare durante a un test a carico costante di 1ora. I soggetti dopo 8 settimane di allenamento hanno fatto un altro test incrementale. Il dati hanno mostrato che Polimedicus non è molto affidabile, soprattutto l'HR. Nel secondo studio è stato sviluppato un nuovo programma, Inca, ed i risultati sono stati confrontati con i dati ottenuti dal primo studio con Polimedicus. I risultati finali hanno mostrato che Inca è più affidabile. Nel terzo studio, abbiamo voluto verificare l'esattezza del calcolo del FatMax con Inca e il test FATmaxwork. 25 soggetti in sovrappeso, tra 40-55 anni, sono stati arruolati e sottoposti al FATmaxwork test. Successivamente, è stato verificato se i valori estrapolati da INCA erano quelli che possono verificarsi durante un carico di prova costante di un'ora. L'analisi ha mostrato una precisione del calcolo della FatMax durante il carico di lavoro. Conclusione: E’ emersa una certa difficoltà nel determinare questo parametro, sia per la variabilità inter-individuale che intra-individuale. In futuro bisognerà migliorare INCA per ottenere protocolli di allenamento ancora più validi.

Autoantibodies in patients with psoriasis on anti-TNFalpha therapy

Introduction: Anti-TNF-alfa therapy has been effective in the treatment of patients with refractory psoriasis and psoriasic arthritis. However, the risk of developing autoantibodies in these patients undergoing this therapy is not clear. Objective: To evaluate the induction of specific autoantibodies after anti-TNFα therapy in patients with psoriasis and psoriasic arthritis and, to evaluate the influence of the use of methotrexate on the values of autoantibodies developed during this therapy. Patients and methods: Serum samples from 120 patients, obtained before(baseline) the introduction of anti-TNF-alpha therapy and approximately each 3-6 months during the therapy.O f these 120 patients, 113 were found negative for autoantibodies before starting anti -TNFalpha therapy, 7 were found positive for ANA. The analysis included detection of antinuclear antibodies (ANA) and anti-dsDNA antibodies (indirect immunofluorescence on Hep-2 cells and Crithidia luciliae, respectively); anti extractable nuclear antigens antibodies( ENA)(ELISA). RESULTS: Infliximab is associated with the highest occurrence rate of ANA, anti-dsDNA, ENA with approximately 69,2%, 11,5%, 7,6% of patients treated testing positive. In comparison, only 20%, 6,6%, 2,2% of patients treated with Adalimumab, and 19%, 2,3%, 2,3% of patients treated with Etanercept were positive for ANA, Anti-dsDNA, ENA respectively. As regard the seven patients who were positive at baseline, six of them (85.7%) in addition to being remained positive during the therapy they have also increased the autoantibodies ’s titers. Conclusion: our study have shown that Infliximab is associated with the highest rate of autoantibodies. The concomitant treatment with methotrexate did not modify the titers of autoantibodies developed during the therapy anti-TNFalph. The incidence of ANA, anti-dsDNA antibodies did not correlate with development of Lupus-like syndromes. The difference in the frequency of autoantibodies between psoriasis and psoriatic arthritis was not statistically significant (p = 0.867).

Evaluation of Antitumoral activity of bone targeted drugs/conventional chemotherapies and identification of biomarkers for the selection of patients with breast cancer for the bone targeted therapy in adjuvant setting

Bone metastases are responsible for different clinical complications defined as skeletal-related events (SREs) such as pathologic fractures, spinal cord compression, hypercalcaemia, bone marrow infiltration and severe bone pain requiring palliative radiotherapy. The general aim of these three years research period was to improve the management of patients with bone metastases through two different approaches of translational research. Firstly in vitro preclinical tests were conducted on breast cancer cells and on indirect co-colture of cancer cells and osteoclasts to evaluate bone targeted therapy singly and in combination with conventional chemotherapy. The study suggests that zoledronic acid has an antitumor activity in breast cancer cell lines. Its mechanism of action involves the decrease of RAS and RHO, as in osteoclasts. Repeated treatment enhances antitumor activity compared to non-repeated treatment. Furthermore the combination Zoledronic Acid + Cisplatin induced a high antitumoral activity in the two triple-negative lines MDA-MB-231 and BRC-230. The p21, pMAPK and m-TOR pathways were regulated by this combined treatment, particularly at lower Cisplatin doses. A co-colture system to test the activity of bone-targeted molecules on monocytes-breast conditioned by breast cancer cells was also developed. Another important criticism of the treatment of breast cancer patients, is the selection of patients who will benefit of bone targeted therapy in the adjuvant setting. A retrospective case-control study on breast cancer patients to find new predictive markers of bone metastases in the primary tumors was performed. Eight markers were evaluated and TFF1 and CXCR4 were found to discriminate between patients with relapse to bone respect to patients with no evidence of disease. In particular TFF1 was the most accurate marker reaching a sensitivity of 63% and a specificity of 79%. This marker could be a useful tool for clinicians to select patients who could benefit for bone targeted therapy in adjuvant setting.