Frontiers in Bioengineering and Biotechnology最新文献

Nonalcoholic steatohepatitis (NASH) or metabolic dysfunction-associated steatohepatitis (MASH) is a long-term chronic liver disease condition that stems from nonalcoholic fatty liver disease (NAFLD) and results from multiple factors, including lifestyle, metabolic dysfunction, and genetic predisposition. The increasing prevalence of NAFLD in the global population is expected to reach over 35% by 2030. It thus has become a significant public health concern because of its association with metabolic syndrome, cardiovascular diseases, diabetes mellitus, and hepatocellular carcinoma. Therefore, early diagnosis is crucial to avoid further liver disease complications and to provide early and effective patient care. Though there are diagnostic measures available for NASH/MASH detection, like biopsy and serological assays, these are mostly invasive and do not provide the complete picture of the liver condition. Point-of-care diagnostics like biosensors can help overcome these limitations by allowing for a rapid, inexpensive, and more straightforward diagnostic method that also aligns with the present global health needs. Moreover, integrating artificial intelligence and machine learning approaches for automated analysis alongside real-time cloud-based reporting and telehealth interfaces can potentially aid in expanding the utility of these systems into integrated diagnostic systems. Through this review, we aim to address the interplay of technological innovation, public health significance, and implementation barriers in advancing biosensor diagnostics for effective and reliable detection of NASH/MASH for better liver health.

Background: Rotator cuff tears represent a prevalent musculoskeletal challenge with high postoperative retear rates despite surgical advances. Platelet-rich plasma (PRP) has emerged as a promising biological adjunct in arthroscopic repair, though clinical evidence remains inconsistent regarding its efficacy in improving structural and functional outcomes.

Methods: This PRISMA-guided meta-analysis evaluated 13 randomized controlled trials (n = 880 patients) comparing PRP-augmented versus conventional arthroscopic rotator cuff repair. Primary outcomes included retear rates and functional scores (UCLA, Constant, SST, ASES, VAS). Statistical analysis employed fixed/random-effects models with subgroup analyses of PRP formulations and tear characteristics.

Results: PRP augmentation significantly improved functional outcomes, with mean differences of 1.82 points (95% CI: 1.13-2.51) for UCLA scores, 2.31 points (95% CI: 1.02-3.61) for Constant scores, and 0.43 points (95% CI: 0.11-0.75) for SST scores (all p < 0.01). VAS pain scores decreased by 0.23 points (95% CI: -0.41 to -0.05, p = 0.01). However, retear rates showed no significant reduction (RR = 0.71, 95% CI: 0.48-1.05, p = 0.09). Benefits were most pronounced in medium/large tears treated with leukocyte-poor PRP and double-row repairs (I² = 0-40% for functional outcomes). Conclusion: While PRP enhances early functional recovery and pain control after rotator cuff repair, its capacity to improve structural integrity remains unproven. Clinical implementation requires standardization of PRP protocols and targeted application in patients with larger tears. Future research should investigate optimized biomaterial formulations and personalized treatment strategies.

Lung cancer is a major cause of cancer related mortality due to delayed diagnosis and limited therapeutic efficiency. Early detection and effective immune modulation are important to control lung cancer. Advancements in nanotechnology have improved oncology due to sensitive, specific, and minimally invasive detection platforms along with immune regulatory therapeutic approaches. Smart nanoplatforms fabricated with high precision and responsiveness have the ability to treat diseases as well as the immune system. These systems combine functional nanomaterials with biomolecular recognition elements to detect biomarkers such as exosomes, DNA, RNA, and proteins. They also facilitate targeted immune activation through checkpoint inhibition, nanovaccines, and tumor microenvironment reprogramming. Moreover, artificial intelligence and machine learning are enhancing the interpretation of complex data, which increases the diagnostic accuracy and predictive power. Despite advances in diagnostic and immune modulation, there are also several challenges related to biological barriers and biocompatibility. This review comprehensively explains the molecular basis of lung cancer, recent progress in nanotechnology based diagnostics and immunotherapy, and the design of multifunctional smart nanoplatforms. Future studies emphasize integrating personalized medicine, digital modeling, and bioinspired nanosystems for clinically translatable solutions in early lung cancer management.

Objective: This study aims to compare different intraocular pressure (IOP) correction formulas in post-refractive surgery patients who underwent Femtosecond Laser-Assisted In Situ Keratomileusis (FS-LASIK), Small Incision Lenticule Extraction (SMILE), and Trans-epithelial Photorefractive Keratectomy (tPRK), and to identify the most accurate formula for correcting IOP values measured by Goldmann applanation tonometer (GAT).

Methods: This prospective study included 160 patients (160 eyes) who underwent FS-LASIK (58 eyes), SMILE (52 eyes), or tPRK (50 eyes) at the Eye Hospital, Wenzhou Medical University. IOP was measured using GAT and Dynamic Contour Tonometry (DCT) preoperatively and 3 months postoperatively. Optical zone diameter, ablation depth (AD), residual stromal thickness, refractive error correction, central corneal thickness (CCT), and mean corneal curvature (Km) were collected. Fourteen published GAT correction formulas (F1-F14) were applied to postoperative GAT values and compared with preoperative measurements. Differences between pre- and postoperative DCT readings served as a reference.

Results: In FS-LASIK and SMILE, formulas F3, F4, and F11 showed superior correction performance. In FS-LASIK, the mean differences, concordance correlation coefficients (CCC), and proportions of differences within ±2 mmHg were closer to or better than the DCT reference (0.58, 0.572, 55.17%), with F3 (0.25, 0.372, 72.41%), F4 (0.20, 0.373, 63.79%), and F11 (0.04, 0.324, 67.24%) showing high agreement. Similarly, in SMILE, F3 (0.25, 0.379, 57.69%), F4 (0.22, 0.375, 61.54%), and F11 (0.01, 0.399, 63.46%) outperformed or approximated DCT (0.86, 0.447, 44.23%). In tPRK, F1 (0.18, 0.653, 64.00%) and F2 (0.25, 0.316, 62.00%) provided better correction than DCT (0.19, 0.493, 56.00%).

Conclusion: Formulas F3, F4, and F11 are applicable for GAT IOP correction in both FS-LASIK and SMILE eyes. F1 and F2 are more suitable for tPRK; the preoperative IOP parameters included in F1 may lead to assessment bias, making F2 the recommended choice when preoperative IOP is unavailable.

Objective: Accurate, non-invasive assessment of muscle strength remains a key challenge for functional health monitoring and wearable systems. This study investigates whether segmental bioimpedance (BioZ) and anthropometry measurements from the wrist and forearm can predict hand grip strength (HGS) in healthy young adults, and characterizes how measurement site, frequency, and applied pressure influence BioZ signal behavior, which are critical factors for translating BioZ into wearable applications.

Methods: We recruited twenty healthy young adults who underwent standardized HGS testing alongside segmental BioZ measurements at the wrist and forearm using a bipolar electrode configuration. Anthropometric variables including age, height, body mass, and limb circumference were recorded. Nonparametric statistical analyses were used to examine anatomical site-specific differences and associations among BioZ, circumference, and HGS. Multiple linear regression (MLR) and random forest (RF) regression models were developed to estimate HGS from anthropometric and localized BioZ features and evaluated using leave-one-out cross validation. In addition, exploratory single-subject experiments were conducted to assess BioZ responses to varying frequency, applied pressure, and electrode configuration at both anatomical sites.

Results: At the cohort level, forearm BioZ values were higher than wrist BioZ (p = 0.0001) and inversely correlated with forearm circumference (ρ = -0.54, p = 0.014). Forearm circumference showed the strongest positive association with HGS, while forearm BioZ exhibited a moderate inverse association. Incorporating localized forearm BioZ into baseline improved predictive performance (RF regression: R² _cv = 0.44). A size-normalized BioZ index further enhanced prediction accuracy, achieving the highest in RF regression models (R² _cv = 0.56). Frequency- and pressure-dependent analyses revealed that high-frequency BioZ increased linearly with applied pressure, whereas low-frequency BioZ exhibited non-linear and less stable behavior, suggesting sensitivity to tissue compression and local fluid redistribution.

Conclusion: This pilot study demonstrates that localized, size-normalized forearm BioZ provides physiologically complementary information to basic anthropometry for estimating HGS in healthy young adults. By integrating cohort-level modeling with exploratory mechanistic experiments, the findings provide insight into the anatomical and mechanical determinants of localized BioZ behavior. This supports the potential utility of combining experimental and computational approaches to inform the future development of next-generation BioZ-based wearable systems for non-invasive assessment of muscle strength, rehabilitation progress, and early signs of muscular decline.

Introduction: Prolonged air leaks (PAL) are considered to be one of the leading causes of postoperative complications following lung surgery. There are currently no clinically relevant methods for efficiently and systematically evaluating the underlying causes of PAL. Here, we introduce a new intuitive, physiologically-representative system for ex vivo negative pressure ventilation of lungs, equipped with PAL-oriented features.

Methods: Reproducibility and system capabilities were assessed using a lung simulation model capable of controlling the effective area of the defect, then validated with ex vivo specimens.

Results: Our system enables dynamic control of ventilation using either pressure (PCV) or volume (VCV) targets, with respective standard deviations of ±0.08 cm H2O and ±2.1 mL with moderate air leaks (<1,000 mL/min) and respective standard deviations of ±0.18 cm H2O and ±11 mL with severe air leaks (>1,000 mL/min). Additionally, leak quantification features proved comparable to that of the Thopaz+ (Medela Healthcare, Baar, Switzerland), a standard commercial digital thoracic drainage system, offering sufficient resolution to differentiate among clinically relevant air leaks. In the lower leak ranges (<400 mL/min) across all methods of evaluations, there were no significant differences between measured leak rates. For higher leak ranges, although there remained no significant differences between the Ex-PALM methods evaluated, the Thopaz + proved to systematically report lower leak rates values (Thopaz+ 420.0 ± 10.0 mL/min vs. PCV-derived 449.0 ± 19.9 mL/min, p < 0.05) and (Thopaz+ 1,200.0 + 0.0 mL/min vs. PCV-derived 1,239.7 ± 21.1 mL/min, p < 0.001). Unlike current systems, coughing was predictably replicated using peak pressure targets ranging from 100 to 300 cm H2O with a standard deviation of ±1.30 cm H2O from target. Our system allows extraction of biomechanical parameters at every breath, with theoretically expected pressures matching experimental measurements with a goodness fit value (R2) above 0.95 for the vast majority of breaths.

Discussion: The Ex vivo Pulmonary Air Leak Model (Ex-PALM) provides a preclinical PAL testing platform with high translational potential and applications in studying biomechanical mechanisms of PAL and developing intraoperative mitigation strategies.

With the synergistic advancement of micro/nanotechnology and intelligent control systems, medical micromachines are emerging as promising alternatives to conventional diagnostic and therapeutic methods, offering enhanced operational precision and minimal invasiveness for precision medicine applications. However, most existing micromachines rely on artificial synthetic materials, which involve complex micro-nano fabrication and raise biosafety concerns regarding immunogenicity and limited long-term therapeutic efficacy in deep tissues. The integration of natural biological cells with programmable optical tweezer has opened new avenues to overcome these limitations, enabling precise behavioral regulation and in situ assembly of cell-based micromachines. This review systematically outlines the design strategies underlying five categories of light force-powered cellular micromachines, including chemotactic bacteria, photosynthetic microalgae, red blood cells (RBCs), immune cells and subcellular structures, and highlights their pioneering applications in targeted drug delivery, minimally invasive surgery and desired immunotherapy. Meanwhile, it also addresses key challenges such as limited tissue penetration depth, phototoxicity management and operation intelligence, while suggesting future directions like adaptive optics-driven swarm control, optomechanobiological coupling and bioprinting-integrated systems. Additionally, the convergence of photonic technology, synthetic biology and artificial intelligence is expected to advance these micromachines into next-generation biomedical platforms for health supervision and disease therapy in vivo.

[This corrects the article DOI: 10.3389/fbioe.2022.945149.].

Gene and genome editing therapies are increasingly connected with nanomaterials, which protect and transport fragile nucleic acids and CRISPR/Cas systems through biological barriers safely and accurately. This review discusses how different nanocarriers, including lipid-based, polymeric, inorganic, and vesicle-derived systems, can improve delivery efficiency, cell targeting, endosomal escape, and intracellular movement for gene and genome editing. It summarizes findings from early clinical and preclinical studies, comparing several carrier types such as ionizable lipid nanoparticles, polymeric nanoparticles, micelles, gold and silica nanostructures, and engineered extracellular vesicles. The review also explains how specific design factors, such as surface ligands, charge modification, PEGylation, and stimulus-responsive behaviors, influence biodistribution, and improve on-target efficiency while lowering immune responses and off-target effects. Ethical and regulatory concerns for in vivo editing are highlighted, along with current methods used to study nano-bio interactions. Among these carriers, ionizable lipid nanoparticles show the most advanced performance for delivering nucleic acids and CRISPR systems. However, new polymer-based and exosome-inspired carriers are progressing rapidly for repeated and targeted applications. Hybrid and responsive systems may also enable better spatial and temporal control of editing. Future research should focus on stronger in vivo potency testing, improved biocompatibility evaluation, and standardized manufacturing to ensure clinical safety and reliability.

Glioblastoma GBM: Glioblastoma multiforme (GBM) remains one of the most lethal and treatment-resistant brain cancers, driven in part by the complexity of its tumour microenvironment (TME). While organ-on-chip (OoC) platforms offer more physiologically relevant models than traditional 2D or static 3D systems, their design remains largely empirical, lacking predictive control over flow conditions, biochemical gradients, and mechanical cues. Computational Fluid Dynamics (CFD) has emerged as a powerful tool to enhance the design, precision, and biological fidelity of OoC platforms. This comprehensive review highlights current limitations in replicating GBM's biological complexity and technical constraints in device fabrication and maintenance, mapping them to specific CFD strategies. It synthesises current strategies into a structured workflow for integrating CFD into the design, optimisation, and validation of microfluidic tumour models-bridging engineering precision with biological complexity. In addition, validation frameworks reported in the literature are highlighted and mapped onto GBM-on-chip applications have been recommended, drawing on widely recognised international standards for engineering validation and regulatory modelling practices. Finally, this review positions CFD as a core component of GBM-on-chip development and explores how its integration with AI-based optimisation can advance the creation of more predictive, scalable, and biologically relevant in vitro tumour models.