The existing literature on balance in young children is mixed: while some studies report that girls sway less than boys up to the age of 10, others report no gender differences. Thus, this paper aims to investigate the effect of sport on postural control abilities and gender differences in a critical period of growth, namely children under twelve years of age. The sample consisted of 50 athletes, aged 11– 12, from three different groups (gymnasts, handball players, and non-athletes). The participants were instructed to maintain an upright and quiet stance, as well as a static and/or dynamic balance, on a stabilometric platform with their eyes open. The center of pressure sway (COP) left/right and forward/backward sway displacements, velocity, and acceleration were measured in the frontal and sagittal planes. The results presented greater postural control in the athlete groups compared to the non-athletes. An expertise in gymnastics seemed to improve the postural performance compared to handball players and the sedentary groups. Gymnastics girls revealed better COP left/right sway displacements in static and dynamic balance than gymnastics, handball players, and non-athletes’ boys, thus highlighting that gymnastics training promotes improvements in postural control of children under twelve. In conclusion, the main results revealed the importance of engaging in sports during childhood. Regular sport activities are crucial during this period to promote significant enhancements of neuromuscular control and balance, which are critical to maintain stability. Based on the results of the study, engaging in gymnastics is recommended to improve balance training, especially at a rich high- performance level in specific sports.

Understanding neural excitability and action potential generation is a cornerstone of neuroscience, relying on the complex interplay of biophysical mechanisms governed by ion channels in neuronal membranes. Traditional approaches, such as the Hodgkin-Huxley model, have provided a robust framework for simulating these processes using classical computational techniques. However, the advent of quantum computing opens new avenues for exploring neuronal dynamics, particularly due to ion movement’s inherently quantum mechanical properties at atomic scales. In this study, I investigated the intersection of quantum computing and membrane biophysics, evaluating how quantum algorithms could revolutionize simulations of ion channel behavior and neuronal signaling. I began by analyzing the limitations of classical methods in handling high-dimensional, nonlinear systems. Next, I introduced key quantum computing principles, including qubits, superposition, and entanglement, and their potential applications in solving molecular dynamics and differential equations relevant to neuronal activity. Despite promising theoretical advantages, practical challenges such as qubit coherence, error rates, and hardware scalability must be addressed before quantum models can outperform classical simulations. I also discussed hybrid classical-quantum approaches as a transitional strategy, leveraging the strengths of both paradigms. By bridging neuroscience, biophysics, and quantum information science, I aimed to stimulate interdisciplinary research toward more efficient and accurate models of neural excitability.

Sanda, a dynamic combat sport rooted in Wushu, relies on diverse striking techniques for competitive success. This study aimed to compare two fundamental Sanda punches (i.e., the straight punch and the hook punch) through kinetic and kinematic analysis to evaluate their effectiveness in terms of force, speed, and execution dynamics. Nineteen elite Sanda athletes (i.e., 14 males and 5 females) from Tunisia’s national team participated in the study. Kinematic data were captured using SkillSpector motion analysis software, while kinetic parameters were calculated through inverse dynamics. Linear and angular kinematics (i.e., displacement, velocity, acceleration, segment angles, and angular velocity) and kinetics (i.e., force, power, linear momentum, and inertia) were assessed. The results revealed significant differences between the punches. The straight punch demonstrated superior execution speed, while the hook punch generated greater force. Kinematically, the straight punch emphasized linear dynamics, whereas the hook punch utilized enhanced angular coordination. These findings highlight distinct biomechanical characteristics; the straight punch excels in rapid linear force transmission, while the hook punch maximizes rotational power. This provides valuable insights for optimizing Sanda training and performance.

Systemic lupus erythematosus (SLE) is a prototypical autoimmune disease characterized by immune dysregulation and multi-organ damage. Recent advances have underscored the critical involvement of extracellular matrix (ECM) biophysical properties in shaping immune cell behavior and metabolic states that contribute to disease progression. This review systematically delineates the pathological remodeling of ECM biophysics in SLE, with a focus on their roles in mechanotransduction, immune-metabolic interplay, and organ-specific tissue injury. By integrating current evidence, we highlight how ECM-derived mechanical cues orchestrate aberrant immune responses and propose new perspectives for targeting ECM-immune crosstalk in the development of organ-specific, mechanism-based therapies for SLE.

Triathlon is an endurance sport growing in popularity. There are various triathlon race formats that require different types of effort. However, there is a lack of information regarding the integrated physiological and biomechanical characteristics of the different race formats. Thus, our aim of this systematic review was to synthesize the biophysical characteristics of different triathlon race formats. The methodology was conducted following PRISMA 2020 guidelines searching Web of Science, PubMed, and Scopus databases. Eligibility criteria were defined for the PICOS strategy (healthy mature triathletes, biomechanical and/or physiological assessment, continuous efforts simulating either segments of races or full races, cardiovascular demand, aero/hydrodynamic, and a technical profile). The quality index was assessed with the Downs and Black Assessment Checklist. A total of 8560 articles were screened, of which 30 satisfied the inclusion criteria, and these were grouped in short-distance race formats (n = 18) and middle-distance race formats (n = 12). Overall, studies showed a quality score of 11.86 ± 1.05 points. The biophysical profile of triathlon is influenced by multiple factors, including race distance, competitive level, segment-specific demands, and sex. Within the literature, there is a lack of analysis concerning other race formats, such as long-distance events (e.g., Ironman and Deca-Ironman), as well as new emerging race formats (e.g., Supertri, Arena Supertri E World Triathlon Championship, or T100).

This review critically examines the current landscape of protein biophysics, highlighting a significant epistemological divide emerging from the rapid advancement of predictive algorithms compared to the slower pace of experimental validation. While artificial intelligence models and inferential statistical methods can generate millions of in silico protein interactions, experimental biophysics remains limited by physiological and technical challenges, leading to a scarcity of confirmed, functional data. This imbalance creates an environment where hypotheses and large-scale interactome networks proliferate based on unverified interactions. This fosters a false sense of causal understanding, potential misdirection in therapeutic development, and overinterpreting omics datasets. The challenge becomes even more urgent with complex, multifactorial diseases such as cancer and viral infections. Recognizing this subtle but crucial disparity is essential for researchers in protein biophysics to navigate the evolving landscape effectively and to focus validation efforts that support meaningful scientific and clinical progress. The review emphasizes the critical need for rigorous experimental validation alongside rapid computational advances. It highlights key challenges, including complexities in protein folding, dynamics, membrane interactions, and quantum effects. It discusses emerging technologies such as AI-based structure prediction (e.g., AlphaFold), cryo-electron microscopy, and integrated biophysical approaches. The importance of multidisciplinary collaboration and orthogonal validation methods is underscored to enhance the reliability of protein interaction data. While technological advances promise to deepen our understanding of protein functions and their roles in health and disease, the review advocates for cautious integration of predictive models with meticulous experimental verification, ensuring the development of accurate, biologically meaningful insights poised to advance medicine and biotechnology.

Nucleic acid testing (NAT) is widely used in disease screening and diagnosis due to its high sensitivity and strong specificity. In addition, whole blood circulation analysis has become a promising non-invasive strategy for cancer diagnosis and surveillance. With the growing testing demand and the advancement of new amplification technologies, nucleic acid detection methods are evolving toward simplicity, speed, and cost-effectiveness. As the gold standard in nucleic acid detection, real-time fluorescence quantitative PCR (qPCR) relies on expensive fluorescence reading equipment and professional operators and is not suitable for the rapid diagnosis of infectious diseases and other diseases. Biosensors have attracted the attention of scientists due to their advantages of rapidity, reliability, and cost-effectiveness. They have been widely applied in medical diagnosis, including point-of-care testing, forensic science, and biomedical research. This paper reviews the recent research progress of NAT methods for pathogenic microorganisms and disease markers and points out future prospects of point-of-care testing, with great significance in improving health care and disease surveillance in resource-constrained areas.