Synthetic surfactants are often non-biodegradable and derived from petrochemical sources, which can harm the environment. In contrast, natural surfactants, also known as biosurfactants (BSs), are typically sourced from microorganisms, plants, or animals and are generally nontoxic and biodegradable, which minimizes their ecological impact and enhances their environmental biocompatibility. Among these biomolecules, plant-derived BSs (PdBSs), particularly saponins, are the best-known members that are abundantly found in nature and traditionally have been used as emulsifiers and detergents. Their favorable physicochemical and biological properties suggest significant potential for biomedical applications. Optimizing plant resource utilization and developing commercial formulations of PdBSs could support global sustainability efforts. Furthermore, PdBSs hold great promise for scientific and commercial applications in skincare and other cosmeceutical products. In this review, we examined the potential bioactivities of PdBSs, particularly saponins, as valuable ingredients for the cosmetic industry and skincare products to promote eco-friendly practices in the cosmeceutical sector.

Wearable devices are widely utilized in the field of health monitoring. Given the real-time requirements of wearable devices for dynamic tracking of muscle fatigue, and addressing the issues of prolonged computation time and failure to extract fatigue-related modal information when applying the variational mode decomposition (VMD) algorithm to surface electromyography (sEMG) signals, this paper proposes the fast VMD (FVMD) algorithm. The objective was to rapidly decompose fatigue-related modal information and extract a complete fatigue curve to alert users. The proposed algorithm is an engineering acceleration of the VMD algorithm. FVMD extends the original signal and applies the Fourier transform to convert the time-domain variational problem into the frequency domain. The optimization problem was constrained to the positive frequency range to simplify calculations while leveraging the unilateral spectrum characteristics to streamline optimization and focus on narrowband modes. The alternating direction method of multipliers framework was employed to decompose the problem into subproblems solvable in closed form, with modal updates inspired by Wiener filtering. The Lagrange multipliers were iteratively updated, and convergence criteria were established to ensure stability. The time-domain signal was reconstructed via the inverse Fourier transform. According to the experimental results, the proposed algorithm exhibits a substantial improvement in processing time compared to the original algorithm and other enhanced algorithms. Compared with other VMD variant algorithms using the same experimental data, the fast recursive VMD (FRVMD) algorithm takes 9.93 s. In contrast, the FVMD method can complete the same task in a shorter time. An evaluation metric was used to select the muscle fatigue modal component most correlated with the original signal and extract the muscle fatigue curve. The FVMD algorithm enhances computational efficiency, overcoming the computational limitations of wearable devices, and provides reliable technical support for real-time muscle fatigue quantification and early warning in scenarios such as sports rehabilitation and occupational health.

The escalating waste generated from agriculture, forestry, aquatic, and industrial sectors poses significant challenges, including environmental pollution, increased greenhouse gas emissions, and depletion of valuable resources. In response to these pressing issues, biochar has emerged as a renewable and sustainable biotechnological approach. Biochar, known as the Black Gold, is derived from the pyrolysis of various organic waste materials, reducing waste and creating a useful product for protecting the environment. Agriculture, forestry waste, food and fiber processing residues, and grassland biomass are the main sources for biochar production. Lignocellulosic materials with low moisture content are the preferred feedstock for biochar production. Biochar has diverse applications in carbon sequestration, soil remediation, and water and air purification, including toxic heavy metals (HMs) removal (e.g., chromium, arsenic, and lead). Biochar applications vary depending on the composition of the feedstocks used in the pyrolysis process. Chemically modified pristine biochar exhibits enhanced adsorption capacities for HMs, making it particularly effective for soil and water decontamination applications. This review highlights the important roles of biochar material for sustainable environmental applications, particularly in HMs removal from contaminated water systems. Innovations in biochar technologies are beneficial bioengineering activities to address the intertwined challenges of waste management toward environmental sustainability.

Comprehensive biochemical analysis is an essential part of clinical diagnostics, pharmaceutical development, and biomedical research. The gold-standard technique for such analysis is spectrophotometry, which has demonstrated excellent reliability, quantitative accuracy, and broad biomolecular sensitivity. Commercial micro-volume spectrophotometers, which are instrumental to applications with limited sample volumes, are often restricted to well-equipped laboratories due to the high cost and portability limitations especially in resource-limited settings. To address this gap, we propose a proof-of-concept, 3D-printed micro-volume spectrophotometer that integrates precision optics, microfluidic sample handling (8–15 µL), combined with spectral reconstruction and machine learning-based concentration estimation algorithm in a compact and affordable format. Preliminary validation of the proposed system based on bovine serum albumin (BSA) protein quantification via Biuret assay demonstrates strong agreement with commercial spectrophotometers (R² > 0.91). With a production cost of approximately $36 and rapid measurement, the architecture provides a framework that can be extended to other absorbance-based biochemical assays ensuring accessible spectrophotometric systems for point-of-care and resource-limited applications, overcoming traditional limits of cost, sample volume, and portability.

To clarify the specific effects of sports biomechanical regulation on improving technical performance and preventing sports injuries in rugby and soccer players, this study employed a randomized controlled trial design. A total of 48 rugby players (24 males and 24 females) and 40 soccer players (20 males and 20 females) were enrolled and randomly assigned to an experimental group (receiving an 8-week personalized biomechanical intervention) and a control group (undergoing conventional training) by gender stratification. The intervention protocol was developed and dynamically optimized based on high-precision kinematic and kinetic data collected by a multi-channel synchronous sensor system: 8 infrared high-speed motion capture cameras (sampling frequency: 200 Hz) were used to obtain the 3D motion trajectories of the athletes’ lower limb joints; 16-channel wireless surface electromyography (sEMG) sensors (sampling frequency: 1500 Hz) were applied to monitor the activation timing and amplitude of the quadriceps femoris, hamstrings, and lateral ankle muscle groups; and a 3D force platform (1000 Hz) was utilized to synchronously record ground reaction forces and lower limb joint torque data. The core of the intervention focused on optimizing the angular and torque parameters of the hip, knee, and ankle joints. Statistical analyses were performed using repeated-measures analysis of variance (ANOVA) and independent samples t-tests. The intraclass correlation coefficient (ICC) was used to assess the reliability of coaches’ scores, with ICC values ranging from 0.89 to 0.93. For technical improvement, the average skill scores of male/female rugby players in the experimental group increased from 57.83 ± 5.31 / 55.33 ± 2.87 to 68.42 ± 5.35 / 65.33 ± 3.67 (all P < 0.001); those of male/female soccer players rose from 41.85 ± 5.72 / 49.70 ± 5.13 to 58.75 ± 5.28 / 74.35 ± 6.89 (all P < 0.001). Time-frequency analysis based on sEMG sensors revealed that the percentage of myoelectric activity in key muscle groups was significantly higher in the experimental group than in the control group (e.g., a 7% increase in males and 3% in females for the lateral ankle muscle group of rugby players, P < 0.05), indicating optimized muscle activation efficiency. Regarding injury prevention, after the intervention, the hip frontal torque of female rugby players in the experimental group decreased to 8.73 ± 0.32 N·m (control group: 9.14 ± 0.41 N·m, P = 0.03), and the ankle coronal torque of male soccer players decreased by 8.6% (P = 0.02). The injury incidence during the intervention period was significantly lower in the experimental group (3.1%) than in the control group (15.6%, P = 0.01). This study confirms that multi-sensor fusion-based sports biomechanical intervention can simultaneously improve technical performance and reduce injury risk in rugby and soccer players by optimizing lower limb joint mechanical parameters and muscle activation patterns. It provides quantitative sensor data support and a precision intervention basis from an engineering perspective for the formulation of gender-specific specialized training programs.

Load-bearing biomedical implants in severe physiological environments must compromise mechanical compatibility, corrosion resistance, and long-term biocompatibility. The fear of the long-term liberation of vanadium and aluminum has provoked the creation of vanadium-free options, despite Ti-6Al-4V remaining clinically viable. This has proved promising, with high- and medium-entropy alloys (HEAs/MEAs) of titanium containing non-toxic two stabilizing elements such as Nb, Ta, Mo, and Zr. Concentrating on the interdependent nature of alloy composition, microstructural development, phase stability, corrosion characteristics, ion release, and biological response, the present critical review article discusses vanadium-free Ti-based HEAs/MEAs and their potential use in biomedical implants. Ti-based HEAs/MEAs have been found to possess low elastic modulus values, corrosion resistance (owing to the presence of multicomponent passive oxide films), and good in vitro cytocompatibility compared to conventional Ti-6Al-4V alloys. This review highlights that microstructural heterogeneity, particularly in additively produced alloys, may have a significant influence on corrosion and biological performance, and that high configurational entropy is not sufficient to ensure improved performance. The challenges that are left to overcome include the lack of standardized testing procedures and long-term in vivo validation. This review presents research priorities so that the clinical translation of vanadium-free Ti-based HEAs/MEAs to be used in load-bearing applications is carried out safely.