Annals of Biomedical Engineering最新文献

Purpose: Astrocytes regulate the activity of nearby neurons so disruption of astrocyte calcium dynamics by traumatic brain injury (TBI) could have profound consequences for neural network activity in the brain. This study aimed to define how mechanical stretch injury alters calcium signaling, mitochondrial membrane potential, and mechanosensitive ion channel organization in human induced pluripotent stem cell (hiPSC)-derived astrocytes.

Methods: Human iPSC-derived astrocytes were subjected to controlled two-dimensional stretch injury across multiple severities. Live-cell calcium and mitochondrial membrane potential imaging, Piezo1 immunostaining, and RNA sequencing were used to assess functional and transcriptional responses.

Results: Cell viability, mitochondrial membrane potential, and spontaneous calcium transients declined in a severity-dependent manner. At moderate injury levels, reductions in mitochondrial function, calcium dynamics, and Piezo1 spatial distribution were transient. RNA sequencing identified 196 differentially expressed genes, including downregulation of mitochondrial and oxidative metabolic pathways and upregulation of cortical thinning-associated pathways.

Conclusion: This platform captures functional and molecular hallmarks of astrocyte injury and provides a human in vitro model for studying mechanobiological pathways linking TBI to neurodegenerative processes.

Purpose: Fetal magnetoencephalography (fMEG) enables non-invasive monitoring of fetal brain function with high temporal resolution. However, how can we isolate low signal-to-noise ratio signals of the developing brain when disruptive artifacts arise from maternal and fetal movements? Addressing this challenge is critical for understanding brain development. We present Advanced Localization and Processing of fMEG Signals based on Maternal and Gross fetal body Movement Exclusion (ALPS-FMEG), a MATLAB-based framework that improves fetal brain signals by removing fetal and maternal movement artifacts.

Methods: ALPS-FMEG integrates Independent Component Analysis for separation and reconstruction of fetal brain, fetal and maternal cardiac signal components in sensor space, Empirical Mode Decomposition for noise reduction, and a movement artifact detection-and-exclusion technique based on actogramCOG associated with heart rate patterns. This novel integration modifies the actogramCOG approach by pre-interpolating R waves for enhanced robustness and combines it with HRV-based logic gates, representing a first in fMEG processing to achieve artifact-free signals while preserving physiological latencies.

Results: ALPS-FMEG was applied to 50 fMEG datasets from 28 to 39 weeks of gestation, enhancing signal quality. For group analysis, 45 datasets were retained after excluding recordings with auditory event-related field (fAEF) latencies < 70 ms. In these, it significantly improved signal-to-noise ratio and fAEF amplitudes (p < 0.0001), with preserved latencies. fAEF latency showed a significant negative correlation with gestational age (p < 0.001).

Conclusion: ALPS-FMEG improves fetal brain signal extraction by addressing movement artifacts. This method supports robust fetal brain analysis and may be adaptable to future fMEG systems, including optically pumped magnetometers, enhancing prenatal neurophysiology and clinical research, though manual steps currently limit scalability and could be addressed via automation for broader practical use.

Purpose: This study presents a novel algorithm for the automatic detection of motor unit (MU) fractions within the motor unit potential (MUP) scans derived from multiscanning EMG recordings. MU fractions are spatially distinct regions identified in the MUP scans that reflect the distribution of muscle fibres within each MU. Multiscanning EMG allows recording multiple MUPs simultaneously in a single recording, improving efficiency and reducing patient discomfort.

Methods: The algorithm combines amplitude thresholding, morphological operations, and connected component analysis to identify MU fractions. Algorithm performance was evaluated using MUP scans from tibialis anterior muscles of five healthy individuals. The analysis was performed in two ways: the first included all the fractions detected automatically, and the second included only those fractions detected in both the automatic and the ground truth. Additionally, the association between muscle depth, number of MU fractions, and signal-to-noise ratio (SNR) of the recorded signals was analysed.

Results: T-tests showed no statistically significant difference between the algorithm and ground truth for both start and end markers. ANOVA indicated that muscle depth did not affect the signal-to-noise ratio (f = 1.06, p = 0.35). Overall, the algorithm reliably identified MU fractions.

Conclusion: The proposed automatic method accurately detects MU fractions, providing a valuable tool for analysing motor unit activity in clinical and research settings.

Purpose: The effects of different posterosuperior rotator cuff tear patterns, ranging from isolated supraspinatus tears to partial or complete infraspinatus involvement, on glenohumeral joint contact mechanics in reverse total shoulder arthroplasty (RTSA) remain unclear. This study aimed to investigate how varying levels of posterosuperior cuff tear (PCT) severity affect three-dimensional center-of-pressure (COP) trajectories, joint contact forces (JCFs), and muscle-tendon forces using a musculoskeletal shoulder model of RTSA.

Methods: Three-dimensional marker trajectory data from eleven male participants were collected during 120° of shoulder abduction in the coronal plane and used as consistent inputs for the RTSA model. Model simulations were performed for various stages of PCT severity. For comparison with each stage of the model, an intact cuff model of RTSA was also simulated.

Results: As PCTs progressed, the COP trajectories increasingly shifted in the superior (P < 0.001), anterior (P < 0.001), and medial (P < 0.001) directions. Additionally, the peak inferior and posterior JCFs decreased by 5.6% (P = 0.02) and 20.0% (P = 0.002), respectively (i.e., the contact area moved in a more anterosuperior direction). Conversely, preserving more posterosuperior cuffs increased muscle-tendon forces in the subscapularis and pectoralis major.

Conclusion: Preserving the middle-inferior infraspinatus can restore joint contact mechanics and mitigate increased muscle-tendon forces in RTSA. These findings can help orthopedic surgeons in deciding whether to repair the rotator cuff during RTSA to mitigate increased muscle-tendon forces and restore the transverse force couple between the anterior and posterior cuffs, thereby improving glenohumeral joint stability.

Purpose: Autologous fat grafting is widely used for soft tissue augmentation but hindered by unpredictable volume retention and donor site morbidity. Decellularized adipose extracellular matrix (DAM) represents a promising alternative. Herein we evaluate an injectable, human-derived DAM decellularized via supercritical carbon dioxide (scCO₂, sDAM), promising a gentler, more eco-friendly isolation of matrix components than conventional chemical decellularization.

Methods: Human adipose tissue was homogenized, delipidated, then underwent scCO₂ cleansing, two cycles of scCO₂ decellularization, cryomilling, and scCO₂ terminal sterilization. The sDAM was injected into dorsal flank and cranial subcutaneous pockets of immunocompetent C57BL/6 mice (400 mm³ of 0.5 g sample/mL PBS). Commercially available hyaluronic acid (HA) was injected (400 mm³) for comparison. Samples were explanted after 1, 3 and 6 months.

Results: sDAM demonstrated a mean of 47 ng DNA/mg of dry weight, below the 50 ng/mg "complete" decellularization threshold. After 6 months, adipose flank volume was 307 mm³ (77% of initial volume), adipose cranial was 273 mm³ (68%), and HA flank was 1393 mm³ (348%), due to its hydrophilic nature. sDAM explants demonstrated significantly higher cellular density over HA explants (p < 0.0001). Perilipin expression revealed adipocytes developing within sDAM after 3 months, increasing in density and size by 6 months; few cells were noted in HA explants. Similarly, CD31 expression demonstrated neo-vascularization in sDAM only. Picrosirius red staining of sDAM demonstrated deposition of new fibrillar collagen after 1 month, which became more aligned over time.

Conclusion: We present the first description of scCO₂ DAM preparation foregoing the use of detergents and enzymatic chemicals with successful volume preservation and adipose tissue regeneration in vivo.

Purpose: To establish an automated, landmark-based patellar coordinate system for standardized alignment, develop a patellar statistical shape model (SSM), and quantify 3D morphological variations associated with patellar dislocation (PD).

Methods: Patellar surface models were reconstructed from CT/MRI scans of 54 participants (33 PD, 21 controls). An automated coordinate system was established and quantitatively validated. Demographic/morphometric risk factors were assessed using logistic regression. An SSM was built for the entire cohort, and principal component analysis (PCA) was used to extract major 3D shape modes. Between-group differences in PC scores were evaluated with multiple-testing control and covariate adjustment. A logistic regression classifier based on shape modes and demographics was evaluated using stratified 10-fold cross-validation.

Results: The automated coordinate system showed high repeatability. Patellar linear dimensions and centroid size did not differ between groups and were not independent predictors. Two robust shape modes differentiated PD from controls: PC4 (thickness/facet morphology) and PC7 (facet-edge morphology). A cross-validated classifier showed good in-cohort discrimination (mean AUC ≈ 0.91).

Conclusion: In this cohort, PD was associated with localized 3D articular-surface shape patterns, characterized by a prominent medial facet, a flattened posterolateral facet, and accentuated facet margins, without corresponding differences in linear dimensions. The automated coordinate system and SSM provide a reproducible approach for quantitative patellar phenotyping. These shape modes may deepen understanding of PD pathomechanics and provide a quantitative basis for future, externally validated risk modeling in diverse populations.

Purpose: Head and neck injuries remain a critical area of concern in automotive safety. To inform injury prediction tools, like crash test dummies, neck validation data are needed. While neck response information for midsize males is available, anthropometry-specific data are needed for other body shapes, including small females. The objective of this study is to characterize the neck response (head and neck kinematics and neck injuries) for small females and compare it to the response of midsize males in the same testing conditions.

Methods: Six small adult female post-mortem human subjects (PMHS) and three midsize adult male PMHS were each tested twice, once at 3-g (20 km/h) and again at 8-g (43 km/h) in frontal impacts. Motion-capture measurements of the skull and first thoracic vertebrae (T1) were analyzed to calculate head and neck motion.

Results: Females had less downward and less forward head excursion than males for both 3-g and 8-g impact tests. The decreases in peak head responses between the 8-g and 3-g tests were larger for small females than for males, with the largest decrease of 30% for small female downward excursion. Rotation responses were similar for females and males at 3-g. At 8-g; the overall range of T1 pitch was similar for both sexes, although males exhibited an initial rearward T1 pitch. No injuries were found for the male PMHS, while two of the female PMHS had cervical spine injuries.

Conclusion: These kinematic and injury data can be used for injury prediction tool neck validation.

Purpose: Hemolysis remains a concern in mechanical circulatory support devices (MCSDs). Capturing flow-induced red blood cell (RBC) deformation is important to improve these technologies. Deformation models that are feasible for macroscale MCSD flows have not been calibrated with human RBC deformation data across multiple conditions. The purpose of this study is to modify and test a droplet deformation model that is applicable for MCSD flows for predicting human RBC deformation in silico.

Methods: In vitro human RBC deformation is studied in microfluidic flows in two suspension viscosities (2.05 and 4.17 cP) at MCSD relevant strain rates (5,000 - 200,000 s^-1 in shear flow; 330 - 13,160 s^-1 in extensional flow). Modifications are made to the deformation model's constitutive parameters to represent the observed RBC deformation in silico.

Results: The calibrated model reproduces the unique RBC deformation behaviors observed in shear and extensional flows across a range of conditions. In silico shear deformation index data have mean absolute error (MAE) ≤ 0.15 compared to in vitro results for both viscosity conditions from 5,000 to 200,000 s^-1. Peak in silico extensional deformation data demonstrate MAE ≤ 0.11 compared to our in vitro results for both viscosity conditions from 670 to 1,300 s^-1, while MAE is higher (up to 0.17) for conditions at 330 s^-1.

Conclusion: The model adaptations successfully produce accurate RBC deformation results at MCSD relevant strain rates for two flow types and two suspension viscosities. The strengths of the model are in relatively high velocity gradient magnitudes and/or suspension viscosities where RBCs emulate liquid droplets.

Purpose: A diagnostic challenge in the management of chronic kidney disease (CKD) is distinguishing diabetic kidney disease (DKD) from hypertensive kidney disease (HKD) in patients with coexisting diabetes mellitus (DM) and hypertension (HTN), because accurate diagnosis often depends on renal biopsy as a reference standard. This study proposes a modeling approach to identify cardiovascular biomarkers for differentiating DKD from HKD.

Methods: An existing whole-body circulation model of the vascular tree was extended with a detailed renal circulation network to predict biomarkers measured at different locations. The model parameterized sex, age, and disease factors and was used to conduct virtual clinical trials that identified individual and combined biomarkers for DKD-HKD differentiation. Biomarkers were identified with univariate and multivariate analysis and characterized with the area under the receiver operating characteristic curve (AUC).

Results: Results show that the strongest individual biomarker that is commonly used in clinical practice is pulsatility index (PI) measured in the main renal artery, with an AUC of 0.87. Among all evaluated two-biomarker combinations, PI and resistive index (RI) measured in the same artery achieved the highest classification performance (AUC 0.94). In comparison, the highest performance among three-biomarker combinations (AUC 0.96) is achieved by mean blood flow rate, systolic blood flow rate, and diastolic flow rate.

Conclusion: This modeling work suggests that cardiovascular biomarkers can assist in differentiating DKD and HKD, and proposes specific hypotheses that form a strong rationale for targeted clinical trials. If confirmed, these methods could enable non-invasive assessment of renal vascular alterations associated with DKD and HKD, reducing reliance on kidney biopsies for diagnostic evaluation.