The effects of fatigue on the relationship between ankle angle at initial contact and the knee and hip joints in landing: Assessing the risk of ACL injury.

BACKGROUND: Anterior cruciate ligament (ACL) injuries may correlate with lower limb angles and biomechanical factors in both dominant and non-dominant legs at initial contact (IC) post-landing. This study aims to investigate the correlation between ankle angles in three axes at IC and knee and hip joint angles during post-spike landings in professional volleyball players, both pre- and post-fatigue induction. RESEARCH QUESTION: To what extent does fatigue influence lower limb joint angles, and what is the relationship between ankle joint angles and hip and knee angles at IC during the landing phase following a volleyball spike? METHODS: Under conditions involving the peripheral fatiguing protocol, the lower limb joint angles at IC following post-spike landings were measured in 28 professional male volleyball players aged between 19 and 28 years, who executed the Bosco fatigue protocol both before and after inducing fatigue. A paired t-test was utilized to compare the joint angles pre- and post-fatigue in both dominant and non-dominant legs. Furthermore, Pearson's correlation test was conducted to explore the relationship between ankle angles at IC and the corresponding knee and hip joint angles. RESULTS: The findings of the study revealed that fatigue significantly increased hip external rotation and decreased knee joint flexion and external rotation in both the dominant and non-dominant legs (p < 0.05). Additionally, correlation analysis demonstrated that the ankle joint's positioning in the frontal and horizontal planes was significantly associated with hip flexion and external rotation at the IC, as well as with knee flexion and rotation (0.40 < r < 0.80). CONCLUSION: Fatigue increased hip external rotation and ankle internal rotation, weakening the correlation between these joints while strengthening the ankle-knee relationship, indicating a reduced hip control in jumps. This suggests a heightened ACL injury risk in the dominant leg due to the weakened ankle-hip connection, contrasting with the non-dominant leg.

Flatfoot Deformity; Exercise to Therapeutic Interventions: A Systematic Review.

Background: Deviation of the foot from the normal posture affects the function of the foot and lower limb and causes lower limb injuries in normal people and athletes. Flat feet or flatfoot deformity are usually associated with pain in the foot area and a decrease in the normal function of the foot, which can negatively affect the sports ability of athletes. Therefore, we aimed to investigate the abnormality of flat feet from training, exercise to therapeutic interventions. Methods: Articles were identified by searching five databases: PubMed, Scopus, Google Scholar, Science Direct, and Gate & Pasteur from 2000 to 2022. The keywords were selected specifically and correctly and all the researches and articles related to the title of the article were searched and found. This research was also searched in Persian databases that this database, included: Irandoc, Mag Iran and Noormagz. Results: Finally, 30 studies met the criteria for entering this study, selected and used to conduct this study. Conclusion: By using the results obtained in the research, which include corrective exercises and therapeutic interventions, especially the use of orthoses and various medical insoles, it is possible to help in the treatment and improvement of this anomaly.

Artificial Intelligence Approach in Biomechanics of Gait and Sport: A Systematic Literature Review.

Background: Artificial neural network helps humans in a wide range of activities, such as sports. Objective: This paper aims to investigate the effect of artificial intelligence on decision-making related to human gait and sports biomechanics, using computer-based software, and to investigate the impact of artificial intelligence on individuals' biomechanics during gait and sports performance. Material and Methods: This review was conducted in compliance with the PRISMA guidelines. Abstracts and citations were identified through a search based on Science Direct, Google Scholar, PubMed, Elsevier, Springer Link, Web of Science, and Scopus search engines from 1995 up to 2023 to obtain relevant literature about the impact of artificial intelligence on biomechanics. A total of 1000 articles were found related to biomechanical characteristics of gait and sport and 26 articles were directly pertinent to the subject. Results: The extent of the application of artificial intelligence in sports biomechanics in various fields. In addition, various variables in the fields of kinematics, kinetics, and the field of time can be investigated based on artificial intelligence. Conventional computational techniques are limited by the inability to process data in its raw form. Artificial Intelligence (AI) and Machine Learning (ML) techniques can handle complex and high-dimensional data. Conclusion: The utilization of specialized systems and neural networks in gait analysis has shown great potential in sports performance analysis. Integrating AI into this field would be a significant advancement in sport biomechanics. Coaches and athletes can develop more precise training regimens with specialized performance prediction models.

Relationship between impulse and kinetic variables during jumping and landing in volleyball players.

BACKGROUND: This study examined the relationships between impulse and kinetic variables during jumping and landing in elite young male volleyball players. METHODOLOGY: Eighteen players were recruited and asked to jump on a force plate, which allowed for the direct extraction of jump and landing kinetic data. The data was then analysed using stepwise regression to explore the relationship between landing impulse and various kinetic variables. RESULTS: Our findings revealed a significant positive relationship between the peak rate of force development concentric (PRFD CON) and impulse at landing (ß = 0.537, p = 0.02). In a secondary analysis, we found that PRFD CON (ß = 0.497, p = 0.01) and time to peak power concentric (TPPC) (ß = 0.424, p = 0.04) were also positively correlated with landing impulse. Importantly, PRFD CON and TPPC were the variables that had the most muscular predictive power for impulse at landing. CONCLUSION: These findings offer crucial insights into the biomechanics of jumping and landing in elite young male volleyball players, informing the development of more effective training programs. Our study identifies PRFD CON and TPPC as critical factors for improving landing impulse, emphasizing the need to consider multiple kinetic variables when designing training programs for explosive skills. These insights can help optimize performance and reduce the risk of injury in elite young male volleyball players.

An Improved Moth-Flame Optimization Algorithm with Adaptation Mechanism to Solve Numerical and Mechanical Engineering Problems.

Moth-flame optimization (MFO) algorithm inspired by the transverse orientation of moths toward the light source is an effective approach to solve global optimization problems. However, the MFO algorithm suffers from issues such as premature convergence, low population diversity, local optima entrapment, and imbalance between exploration and exploitation. In this study, therefore, an improved moth-flame optimization (I-MFO) algorithm is proposed to cope with canonical MFO's issues by locating trapped moths in local optimum via defining memory for each moth. The trapped moths tend to escape from the local optima by taking advantage of the adapted wandering around search (AWAS) strategy. The efficiency of the proposed I-MFO is evaluated by CEC 2018 benchmark functions and compared against other well-known metaheuristic algorithms. Moreover, the obtained results are statistically analyzed by the Friedman test on 30, 50, and 100 dimensions. Finally, the ability of the I-MFO algorithm to find the best optimal solutions for mechanical engineering problems is evaluated with three problems from the latest test-suite CEC 2020. The experimental and statistical results demonstrate that the proposed I-MFO is significantly superior to the contender algorithms and it successfully upgrades the shortcomings of the canonical MFO.

J-binding protein 1 and J-binding protein 2 expression in clinical Leishmania major no response-antimonial isolates.

Cutaneous leishmaniasis (CL) is a major disease in many parts of the world. Since no vaccine has been developed, treatment is the best way to control it. In most areas, antimonial resistance whose mechanisms have not been completely understood has been reported. The main aim of this study is gene expression assessing of J-binging protein 1 and J-binding protein 2 in clinical Leishmania major isolates. The patients with CL from central and north Iran were considered for this study. The samples were transferred in RNAlater solution and stored in - 20 °C. RNA extraction and cDNA synthesis were performed. The gene expression analysis was done with SYBR Green real-time PCR using ∆∆CT. Written informed consent forms were filled out by patients, and then, information forms were filled out based on the Helsinki Declaration. Statistical analysis was done with SPSS (16.0; SPSS Inc, Chicago) using independent t test, Shapiro-Wilk, and Pearson's and Spearman's rank correlation coefficients. P ≤ 0.05 was considered significant. The gene expression of JBP1 and JBP2 had no relation with sex and age. The JBP1 gene expression was high in sensitive isolates obtained from north of the country. The JBP2 gene expression was significant in sensitive and no response-antimonial isolates from the north, but no significant differences were detected in sensitive and resistant isolates from central Iran. Differential gene expression of JBP1 and JBP2 in various clinical resistances isolates in different geographical areas shows multifactorial ways of developing resistance in different isolates.