Neuropathic pain is a type of chronic pain that arises due to damage or dysfunction in the nervous system. Unlike pain caused by tissue damage, neuropathic pain results from nerve issues, which can stem from injuries to the spinal cord, brain, or peripheral nerves [1]. In athletic activities, athletes may encounter various types of injuries that can lead to neuropathic pain. Sports involving intense physical contact or rapid movements pose the highest risk of causing this type of pain. For instance, spinal cord injuries, which can occur in sports like football or gymnastics, can directly affect spinal nerves and lead to neuropathic pain [2]. On the other hand, sports such as tennis or basketball, which require repetitive movements and continuous pressure on muscles and joints, can damage peripheral nerves and result in neuropathic pain [3]. Additionally, concussions, commonly seen in sports like boxing or football, are another frequent cause of this type of pain [4]. Direct blows to the head can disrupt the functioning of the brain and nerves, leading to symptoms of neuropathic pain. . . . .

Introduction: Since school sports are the main cause of students’ injuries, awareness of the causes and factors underlying these injuries can pave the way for the development and planning of injury prevention strategies. The present study was conducted in two quantitative and qualitative phases using the data in the sports injury surveillance system and the interviews designed by the researchers to analyze the epidemiological indicators and causes of students’ injuries. Methods: This mixed-method study was conducted using qualitative and quantitative descriptive techniques. The injuries made to male students of physical education high schools in Kerman were recorded for 6 months in a sports injury surveillance system developed by the researchers. Then, the qualitative data were collected using in-depth and semi-structured interviews to explore the possible causes of sports injuries. The collected data were analyzed using a content analysis method via descriptive statistics and the chi-square test with SPSS software (version 21) at a significance level of P=0. 05. Besides, the qualitative data were analyzed using a conventional content analysis technique. Results: The results of data analysis indicated that most of the injuries occurring in sports movements to the student-athletes were caused by collision. Moreover, muscle strain injuries were the most frequently found sports injuries. Improper techniques were also reported as the most important cause of sports injuries. Pain was found as the most significant indicator of the early post-injury symptoms. An analysis of the quantitative-descriptive data recorded in the sports injury surveillance system showed the injury incidence rate of 33. 3 injuries per 100 student-athletes and 63. 3 injuries per 100 hours of training and competition. Furthermore, the lower extremity with 51. 6% and minor injuries with 45. 3% showed the highest rate and improper techniques accounting for 25% of the injuries were the most important risk factor for injury. Conclusion: Given the high prevalence of muscle strains and the highest percentage of lower extremity injuries in students caused by using improper techniques, addressing sports injury indicators, as well as explaining their causes and underlying factors can significantly contribute to reducing students’ injuries. Moreover, regular systematic reviews of epidemiological studies can be effective in developing practical programs for injury prevention in students.

Bioinformatics, a combination of biology, data science, and computer science, has emerged as a key tool in various biological sciences and medicine fields in recent decades. One of this science's novel and intriguing applications is managing sports injuries [1]. Professional and even amateur athletes are exposed to various injuries during training and competitions. These injuries include muscle strains, tendon tears, joint injuries, and bone fractures. Proper and accurate management of these injuries, both in the prevention and treatment stages, is essential to maintaining athletes' health and optimal performance [2]. In this context, bioinformatics plays a crucial role. Bioinformatics is particularly valuable in sports injury management when analyzing biological data from athletes and offering data-driven solutions for preventing, diagnosing, and treating injuries [3]. For instance, genetic data can predict an athlete's predisposition to certain injuries. Due to their specific genetics, some athletes are at higher risk for muscle or joint injuries. These risks can be identified by analyzing athletes’ genetic data through bioinformatics techniques, and appropriate training and preventive programs can be developed [4]. . . . . . . .