Conductive/Insulating Bioinks with Multitechnology Compatibility and Adjustable Performance.

Conducting/insulating inks have received significant attention for the fabrication of a wide range of additive manufacturing technology. However, current inks often demonstrate poor biocompatibility and face trade-offs between conductivity and mechanical stiffness under physiological conditions. Here, conductive/insulating bioinks based on two-dimensional materials are proposed. The conductive bioink, graphene (GR)-poly(lactic-co-glycolic acid) (PLGA), is prepared by introducing conductive GR into a degradable polymer matrix, PLGA, while the insulating bioink, boron nitride (BN)-PLGA, is synthesized by adding insulating BN. By optimizing the material ratios, this work achieves precise control of the electromechanical properties of the bioinks, thereby enabling the flexible construction of conductive networks according to specific requirements. Furthermore, these bioinks are compatible with a variety of manufacturing technologies such as 3D printing, electrospinning, spin coating, and injection molding, expanding their application range in the biomedical field. Overall, the results suggest that these conducting/insulating bioinks offer improved mechanical, electronic, and biological properties for various emerging biomedical applications.

The coexistence of myosteatosis and the creatinine/cystatin C ratio are determinants of outcomes in cholangiocarcinoma patients undergoing curative surgery.

Background: Myosteatosis is a well-established predictor of poor prognosis in many types of cancer, and a decreased Creatinine/Cystatin C ratio (CCR) is a known indicator of unfavorable outcomes in patients with metabolic disorders and cancer. Despite this knowledge, the significance of concurrent CCR and myosteatosis in predicting the prognosis of patients with cholangiocarcinoma (CCA) who undergo radical surgery remains uncertain. Method: Data from 757 patients with cholangiocarcinoma who underwent the first radical resection in the Affiliated Hospital of Qingdao University from January 2017 to March 2022 were collected. According to the inclusion and exclusion criteria, 149 patients were finally included in the retrospective study cohort. Various clinicopathological, serological, and radiological data were collected at admission. Myosteatosis was evaluated using sliceOmatic software on computed tomography (CT) images. The study used receiver operating characteristic (ROC) curve analysis to determine the critical value of CCR, which predicts overall survival (OS) based on the Kaplan-Meier method. Univariate and multivariate Cox regression analyses were employed to identify the risk factors associated with OS and RFS confidently. Results: The group identified as the myosteatosis cohort consisted of 79 patients with an average age of 64.3 ± 7.8 years. The ROC curve analysis revealed an optimal critical CCR value of 10.834. A low CCR ≤ 10.834 and myosteatosis were found to be associated with poor OS and RFS outcomes (P = 0.022; P = 0.017; P = 0.038; P = 0.030 respectively). Moreover, patients with myosteatosis and a CCR ≤ 10.834 had the worst OS and RFS outcomes (P = 0.035; P = 0.027). Conclusion: After radical excision in CCA patients, the presence of myosteatosis and CCR had a negative correlation with prognosis. A more accurate prediction of OS and RFS was possible by combining CCR and myosteatosis, compared to CCR alone.

Application of Hashin-Shtrikman bounds homogenization model for frequency analysis of imperfect FG bio-composite plates.

Despite abundant theoretical investigations on the dynamic behavior of functionally graded (FG) structures, the study on frequency analysis of FG bio-composite structures is limited. FG bio-composite materials due to their biocompatibility potentials and good material properties can be applied in biomedical applications, especially dental implants. In this investigation, a natural frequency response of the FG bio-composite plate is analyzed within the framework of the newly developed refined higher-order shear deformation plate theory. Additionally, the imperfection impact on frequency behavior is evaluated while three imperfection distribution patterns are taken into account. The constitutive materials of FG bio-composite plate are Hydroxyapatite and Titanium. The effective material properties of the structure are determined with the help of the upper Hashin-Shtrikman bounds homogenization model. In continuation, to solve the derived governing equations of imperfect FG bio-composite plate, Galerkin's analytical method is employed. Also, the precision of the used theory is validated, the obtained outcomes are compared and an acceptable matching is found. Later, the sensitivity of different considerable variables is comprehensively assessed and discussed.

ADSC-derived exosomes-coupled decellularized matrix for endometrial regeneration and fertility restoration.

Endometrium is suspectable to severe injury due to recurrent abortion, curettage or intrauterine infection which could lead to pathological conditions and sabotage women's fertility. Promoting endometrium regeneration is the core of the treatments to uterine related infertility. Patients who received traditional treatments can only expect limited effects, thereby novel therapies are badly in need to promote endometrium regeneration. Here we generated a decellularized extracellular matrix (ECM) from porcine dermis, and composited adipose stem cell derived exosomes (ADSC-exos) on it (ECM@ADSC-exos). In vitro experiments proved that ECM@ADSC-exos exhibited good cytocompatibility and could improve cell proliferation, migration and angiogenesis. We also observed that, when implanted in the uterine cavity of a rat model of endometrium injury, ECM@ADSC-exos improved endometrium regeneration, enhanced local angiogenesis, promoted myometrium repair and finally preserved fertility. Our results proved that ECM@ADSC-exos could be a novel option for endometrium regeneration.

Reduced CPU Workload for Human Pose Detection with the Aid of a Low-Resolution Infrared Array Sensor on Embedded Systems.

Modern embedded systems have achieved relatively high processing power. They can be used for edge computing and computer vision, where data are collected and processed locally, without the need for network communication for decision-making and data analysis purposes. Face detection, face recognition, and pose detection algorithms can be executed with acceptable performance on embedded systems and are used for home security and monitoring. However, popular machine learning frameworks, such as MediaPipe, require relatively high usage of CPU while running, even when idle with no subject in the scene. Combined with the still present false detections, this wastes CPU time, elevates the power consumption and overall system temperature, and generates unnecessary data. In this study, a low-cost low-resolution infrared thermal sensor array was used to control the execution of MediaPipe's pose detection algorithm using single-board computers, which only runs when the thermal camera detects a possible subject in its field of view. A lightweight algorithm with several filtering layers was developed, which allowed the effective detection and isolation of a person in the thermal image. The resulting hybrid computer vision proved effective in reducing the average CPU workload, especially in environments with low activity, almost eliminating MediaPipe's false detections, and reaching up to 30% power saving in the best-case scenario.

Differential Diagnosis of Benign and Malignant Pulmonary Nodules in CT Images Based on Multitask Learning.

BACKGROUND: Artificial intelligence-based aided diagnostic systems for pulmonary nodules can be divided into subtasks such as nodule detection, segmentation, and benign and malignant differentiation. Most current studies are limited to single-target tasks. However, aided diagnosis aims to distinguish benign from malignant pulmonary nodules, which requires the fusion of multiple-scale features and comprehensive discrimination based on the results of multiple learning tasks. OBJECTIVE: This study focuses on the aspects of model design, network structure, and constraints and proposes a novel model that integrates the learning tasks of pulmonary nodule detection, segmentation, and classification under weakly supervised conditions. METHODS: The main innovations include the following three aspects: (1) a two-dimensional sequence detection model based on a ConvLSTM (Convolutional Long Short-Term Memory) network and U-shaped structure network is proposed to obtain the context space features of image slices fully; (2) a differential diagnosis of benign and malignant pulmonary nodules based on multitask learning is proposed, which uses the annotated data of different types of tasks to mine the potential common features among tasks; and (3) an optimization strategy incorporating prior knowledge of computed tomography images and dynamic weight adjustment of multiple tasks is proposed to ensure that each task can efficiently complete training and learning. RESULTS: Experiments on the LIDC-IDRI and LUNA16 datasets showed that our proposed method achieved a final competition performance metric score of 87.80% for nodule detection and a Dice similarity coefficient score of 83.95% for pulmonary nodule segmentation. CONCLUSION: The cross-validation results of the LIDC-IDRI and LUNA16 datasets show that our model achieved 87.80% of the final competition performance metric score for nodule detection and 83.95% of the DSC score for pulmonary nodule segmentation, representing the optimal result for that dataset.

Noninvasive grading of glioma brain tumors using magnetic resonance imaging and deep learning methods.

PURPOSE: Convolutional Neural Networks (ConvNets) have quickly become popular machine learning techniques in recent years, particularly in the classification and segmentation of medical images. One of the most prevalent types of brain cancers is glioma, and early, accurate diagnosis is essential for both treatment and survival. In this study, MRI scans were examined utilizing deep learning techniques to examine glioma diagnosis studies. METHODS: In this systematic review, keywords were used to obtain English-language studies from the Arxiv, IEEE, Springer, ScienceDirect, and PubMed databases for the years 2010-2022. The material needed for review was then collected from the articles once they had been chosen based on the entry and exit criteria and in accordance with the research's goal. RESULTS: Finally, 77 different academic articles were chosen. According to a study of published articles, glioma brain tumors were discovered, categorized, and segmented utilizing a coordinated approach that included image collecting, pre-processing, model design and execution, and model output evaluation. The majority of investigations have used publicly accessible photo databases and already-trained algorithms. The bulk of studies have employed Dice's classification accuracy and similarity coefficient metrics to assess model performance. CONCLUSION: The results of this study indicate that glioma segmentation has received more attention from researchers than glioma detection and classification. It is advised that more research be done in the areas of glioma detection and, particularly, grading in order to be included in systems that support medical diagnosis.

Evaluating the characteristics of myocardial work by two-dimensional echocardiography during pre-eclampsia pregnancy.

This study aimed to analyze the changes in myocardial work (MyW) properties and the correlation of MyW with cardiovascular and clinical indices during the pre-eclampsia (PE) pregnancy. Standard two-dimensional and speckle-tracking echocardiography were sequentially performed on 77 women with PE and 89 with normal pregnancy. Four components of MyW: global myocardial work index (GWI), constructive work (GCW), wasted work (GWW), and work efficiency (GWE) were measured. The significant increased GWI, GCW and GWW were observed, while GWW elevated more than GCW with consequently resulting the decline in GWE among PE cases. Although there was a diverse relationship between MyW components and LV morphological as well as functional indices, MyW parameters were significantly correlated with the grades of arterial hypertension and the incidence of adverse outcome of PE. With the hypertension stages, GWI, GCW and GWW gradually increased but GWE decreased. Meanwhile, the higher GWI and GCW and the lower GWE, the more adverse events occurred in PE group. In conclusion, during the PE pregnancy, GWI, GCW and GWW increase, while GWW elevates more than GCW, which leads to the decrease in GWE. Moreover, the changes in MyW are associated with the hypertension grades and the poor prognosis in PE. The non-invasive manner for MyW assessment provides a new perspective on the myocardial biomechanics, cardio-metabolic conditions and pathophysiological changes in the condition of PE.

Quantification of Myocardial Work by 2-D Echocardiography during a Normal Pregnancy: A Preliminary Study.

This study was aimed at investigating the adaptive changes in myocardial work (MyW) during normal pregnancy. Sequential 2D standard and speckle-tracking echocardiography was performed on 41 pregnant women in each gestational trimester and 4 to 11 mo after delivery. Thirty-eight age-matched, healthy, non-pregnant women served as controls. Four components of MyW-global myocardial work index (GWI), constructive work (GCW), wasted work (GWW) and work efficiency (GWE)-were calculated. GWI began to decline early in the first trimester and remained at a low level until delivery; GCW gradually decreased with gestational progression and reached its lowest level in the third trimester. When compared with the values for non-pregnant women and those postpartum, GWE and GWW remained unchanged in gestation. This study provides normal ranges of MyW during pregnancy. Despite the adapted decrease in GWI and GCW, the myocardium manages to work efficiently in the healthy pregnancy with drastic hemodynamic alternations.

Molecular classification of human papillomavirus-positive cervical cancers based on immune signature enrichment.

Background: Human papillomavirus-positive (HPV+) cervical cancers are highly heterogeneous in clinical and molecular characteristics. Thus, an investigation into their heterogeneous immunological profiles is meaningful in providing both biological and clinical insights into this disease. Methods: Based on the enrichment of 29 immune signatures, we discovered immune subtypes of HPV+ cervical cancers by hierarchical clustering. To explore whether this subtyping method is reproducible, we analyzed three bulk and one single cell transcriptomic datasets. We also compared clinical and molecular characteristics between the immune subtypes. Results: Clustering analysis identified two immune subtypes of HPV+ cervical cancers: Immunity-H and Immunity-L, consistent in the four datasets. In comparisons with Immunity-L, Immunity-H displayed stronger immunity, more stromal contents, lower tumor purity, proliferation potential, intratumor heterogeneity and stemness, higher tumor mutation burden, more neoantigens, lower levels of copy number alterations, lower DNA repair activity, as well as better overall survival prognosis. Certain genes, such as MUC17, PCLO, and GOLGB1, showed significantly higher mutation rates in Immunity-L than in Immunity-H. 16 proteins were significantly upregulated in Immunity-H vs. Immunity-L, including Caspase-7, PREX1, Lck, C-Raf, PI3K-p85, Syk, 14-3-3_epsilon, STAT5-α, GATA3, Src_pY416, NDRG1_pT346, Notch1, PDK1_pS241, Bim, NF-kB-p65_pS536, and p53. Pathway analysis identified numerous immune-related pathways more highly enriched in Immunity-H vs. Immunity-L, including cytokine-cytokine receptor interaction, natural killer cell-mediated cytotoxicity, antigen processing and presentation, T/B cell receptor signaling, chemokine signaling, supporting the stronger antitumor immunity in Immunity-H vs. Immunity-L. Conclusion: HPV+ cervical cancers are divided into two subgroups based on their immune signatures' enrichment. Both subgroups have markedly different tumor immunity, progression phenotypes, genomic features, and clinical outcomes. Our data offer novel perception in the tumor biology as well as clinical implications for HPV+ cervical cancer.

A Multimodel Fusion Method for Cardiovascular Disease Detection Using ECG.

Objective. Electrocardiogram (ECG) is an important diagnostic tool that has been the subject of much research in recent years. Owing to a lack of well-labeled ECG record databases, most of this work has focused on heartbeat arrhythmia detection based on ECG signal quality. Approach. A record quality filter was designed to judge ECG signal quality, and a random forest method, a multilayer perceptron, and a residual neural network (RESNET)-based convolutional neural network were implemented to provide baselines for ECG record classification according to three different principles. A new multimodel method was constructed by fusing the random forest and RESNET approaches. Main Results. Owing to its ability to combine discriminative human-crafted features with RESNET deep features, the proposed new method showed over 88% classification accuracy and yielded the best results in comparison with alternative methods. Significance. A new multimodel fusion method was presented for abnormal cardiovascular detection based on ECG data. The experimental results show that separable convolution and multiscale convolution are vital for ECG record classification and are effective for use with one-dimensional ECG sequences.

Human cytomegalovirus infection and its association with gestational diabetes mellitus during pregnancy.

BACKGROUND: Infection is an important risk factor for gestational diabetes mellitus (GDM), while infection of human cytomegalovirus (HCMV) with GDM remains unclear and rarely reported. This study aimed to investigate the association of HCMV infection and serum inflammatory factor levels in pregnancy with GDM. METHODS: This prospective study included pregnant women who attended at Affiliated Hospital of Qingdao Hospital and Zibo Maternal and Child Health Hospital between December 2018 and August 2020. HCMV specific IgM and serum levels of inflammatory factors, including TNF-α, IL-6, and IL-1ß, were analyzed. RESULTS: A total of 5,316 pregnant women were included (415 with GDM (107 with HCMV+GDM+ and 308 with HCMV-GDM+) and 4901 GDM-free (759 with HCMV+GDM- and 4142 with HCMV-GDM-)). The prevalence of GDM was 7.81%. The rate of activation of HCMV was 16.29%. Specifically, 107 and 759 women in the GDM and control group exhibited HCMV infection, with positive rates of25.78% and 15.48%, respectively (P < 0.01). TNF-α, IL-6, and IL-1ß at 24-28 weeks of gestation were significantly higher in women with GDM and HCMV infection than inthe other groups (all P < 0.01). Multivariable analysis showed that HCMV positive (OR = 1.851; 95% CI [1.425-2.403]; P < 0.001), IL-6 (OR = 1.010; 95% CI [1.002-1.018]; P = 0.013), and IL-1ß (OR = 1.410; 95% CI [1.348-1.474]; P < 0.001) were all significantly correlated with GDM. CONCLUSION: This study suggests HCMV infection during pregnancy is an independent risk factor of GDM and could significantly increase its incidence. Further studies are needed to elucidate possible mechanisms underlying associations between HCMV infection and GDM.

Identification of Differentially Expressed Plasma lncRNAs As Potential Biomarkers for Breast Cancer.

BACKGROUND: Breast cancer is the most common malignant tumor in women and is not easy to diagnose. Increasing evidence has underscored that long non-coding RNAs (lncRNAs) play important regulatory roles in the occurrence and progression of many cancers, including breast cancer. We aimed to identify lncRNAs in plasma as potential biomarkers for breast cancer. PATIENTS AND METHODS: We analyzed the Gene Expression Omnibus (GEO) datasets GSE22820, GSE42568, and GSE65194 to identify the common differential genes between cancer tissues and adjacent tissues. Then 14 lncRNAs were identified among the common differential genes and validated by using real-time quantitative polymerase chain reaction in 92 patients with breast cancer and 100 healthy controls. Receiver operating characteristic (ROC) curves were constructed to evaluate their diagnostic value for breast cancer. RESULTS: Integrated analysis of the GEO datasets identified three significantly upregulated and 11 downregulated lncRNAs in breast cancer tissues. Compared with healthy controls, MIAT was significantly upregulated in breast cancer patient plasma, and LINC00968 and LINC01140 were significantly downregulated. ROC curve analysis suggested that these three lncRNAs can discriminate breast cancer from healthy individual with high specificity and sensitivity. CONCLUSION: This research identified three differentially expressed lncRNAs in breast cancer patient plasma. Our data suggest that these three lncRNAs can be used as potential diagnostic biomarkers of breast cancer.

Left Atrial Strain and Compliance Correlate with Diastolic Dysfunction Grades and Complications during Pre-eclampsia: A Speckle-Tracking Echocardiography Study.

This study aimed to investigate left atrium (LA) strain components in the assessment of cardiac function and its clinical correlates in pre-eclampsia (PE). With the use of speckle tracking echocardiography, phasic LA strain and (LASr)/(E/e'), the surrogate of LA compliance, were compared between healthy pregnant women (n = 70) and those with PE (n = 146) and among different diastolic dysfunction (DD) grades in PE. Receiver operating characteristic curves and logistic regression analysis were used to identify the role of strain components in distinguishing DD grades and predicting cardiac complications. LA reservoir strain, conduit strain and LA compliance reduced significantly in PE (p < 0.01). LASr/(E/e') gradually decreased with worsening DD and LASr/(E/e') <3.40 was the independent risk factor for cardiac events in PE (p < 0.01). This study observed significantly decreased LA strain and compliance in PE. Notably, LA compliance decreased progressively with the severity of DD, and LASr/(E/e') <3.40 is the independent risk factor for cardiac complications during PE pregnancy.

Atomic Layer Deposition (ALD) of Alumina over Activated Carbon Electrodes Enabling a Stable 4†V Supercapacitor Operation.

Designing high voltage (>3 V) and stable electrochemical supercapacitors with low self-discharge is desirable for the applications in modern electronic devices. This work demonstrates a 4 V symmetric supercapacitor with stabilized cycling performance through atomic layer deposition (ALD) of alumina (Al2 O3 ) on the surface of activated carbon (AC). The 20-cycle ALD Al2 O3 coated AC delivers 84 % capacitance retention after 1000 charge/discharge cycles under 4 V, contrary to the bare AC cells having only 48 % retention. The extended cycling life is associated with the thickened Stern layer and suppressed oxygen functional group. The self-discharge data also show that the Al2 O3 coating enables AC cells to maintain 53 % of charge retention after 12 h, which is more than twice higher than that of bare AC cells under the same test protocol of 4 V charging. The curve fitting analysis reveals that ALD coating induced slow self-discharge dominated by ion diffusion mechanism, thus enhancing the AC surface energy.

Elevated RUNX1 is a prognostic biomarker for human head and neck squamous cell carcinoma.

Runt-related transcription factors regulate many developmental processes such as proliferation and differentiation. In this study, the function of the runt-related transcription factor 1 (RUNX1) was investigated in head and neck squamous cell carcinoma (HNSCC). Our results show that RUNX1 expression was elevated in HNSCC patients, which was greatly correlated with the N stage, tumor size, and American Joint Committee on Cancer stage. Cox proportional hazard models showed that RUNX1 could be used as a prognostic indicator for the overall survival of HNSCC patients (hazard ratio, 5.572; 95% confidence interval, 1.860-9.963; P < 0.001). Moreover, suppression of RUNX1 inhibited HNSCC cell proliferation, migration, and invasion. Using the HNSCC xenograft nude mouse model, we found that the shRUNX1-transfected tumor (sh-RUNX1) was significantly smaller both in size and weight than the control vector-transfected tumor (sh-Control). In conclusion, our results show that the elevated RUNX1 expression was correlated with tumor growth and metastasis in HNSCC, indicating that RUNX1 could be used as a biomarker for tumor recurrence and prognosis.

Interleukin-18 Is a Prognostic Marker and Plays a Tumor Suppressive Role in Colon Cancer.

Interleukin-18 (IL-18) belongs to the IL-1 family and is an essential proinflammatory and immune regulatory cytokine. The present study was designed to investigate the expression and function of IL-18 in colon cancer. In clinical analyses, mRNA and protein expressions of IL-18 were decreased in tissues of colon cancer patients. This decreased expression of IL-18 was significantly correlated with the tumor size (P = 0.001) and American Joint Committee on Cancer (AJCC) stage (P = 0.013). Patients with IL-18-positive tumors had a better survival rate than patients with IL-18-negative tumors. Moreover, upregulation of IL-18 inhibited colon cancer cell proliferation. Our data suggest that the decreased expression of IL-18 in colon cancer was associated with prognosis and tumor proliferation. IL-18 may be considered a novel tumor suppressor and a potential therapeutic target for colon cancer patients.

Prevalence and Therapies of Antibiotic-Resistance in Staphylococcus aureus.

Infectious diseases are the second most important cause of human death worldwide; Staphylococcus aureus (S. aureus) is a very common human pathogenic microorganism that can trigger a variety of infectious diseases, such as skin and soft tissue infections, endocarditis, osteomyelitis, bacteremia, and lethal pneumonia. Moreover, according to the sensitivity to antibiotic drugs, S. aureus can be divided into methicillin-sensitive Staphylococcus aureus (MSSA) and methicillin-resistant Staphylococcus aureus (MRSA). In recent decades, due to the evolution of bacteria and the abuse of antibiotics, the drug resistance of S. aureus has gradually increased, the infection rate of MRSA has increased worldwide, and the clinical anti-infective treatment for MRSA has become more difficult. Accumulating evidence has demonstrated that the resistance mechanisms of S. aureus are very complex, especially for MRSA, which is resistant to many kinds of antibiotics. Therefore, understanding the drug resistance of MRSA in a timely manner and elucidating its drug resistance mechanism at the molecular level are of great significance for the treatment of S. aureus infection. A large number of researchers believe that analyzing the molecular characteristics of S. aureus can help provide a basis for designing effective prevention and treatment measures against hospital infections caused by S. aureus and further monitor the evolution of S. aureus. This paper reviews the research status of MSSA and MRSA, the detailed mechanisms of the intrinsic antibiotic resistance and the acquired antibiotic resistance, the advanced research on anti-MRSA antibiotics and novel therapeutic strategies for MRSA treatment.

Development, validation, and application of ligamentous cervical spinal segment C6-C7 of a six-year-old child and an adult.

BACKGROUND AND OBJECTIVE: The cervical spine is one of the primary regions that is easily injured in traffic accidents. Although adult cervical spine finite element models have been widely adopted to investigate the cervical injury, few efforts have been made with respect to the development and application of FE models of the pediatric cervical spine, especially that of a six-year-old child. The objective of this study is to develop and validate high quality cervical spinal segment C6-C7 FE models of a six-year-old child and an adult, and to further investigate the differences of C6-C7 between the child and adult under different loading conditions. METHODS: The cervical spinal segment C6-C7 FE models were developed by a structured multiblock method, and were verified under flexion, extension, axial rotation, and lateral bending conditions. The validated models were used to investigate the differences of C6-C7 between the child and adult under different loading conditions. RESULTS: The global angular displacement of C6-C7, the ligament elongation ratio, and the maximum effective strain of annulus fibrosus of the child were obviously larger than those of the adult under the same loading conditions. Regarding the loading forms, the flexion angular displacement of C6-C7 of the child was obviously larger than those of the extension and lateral bending, while for the adult cervical segment C6-C7, no obvious differences existed. The elongation ratio of different ligaments was highly dependent on the types of loadings. The maximum effective strain of annulus fibrosus under flexion, extension and lateral bending loads occurred at the compressive region of the front, rear, and one compressive lateral side, in which the annulus fibrosus was more susceptible to injury under the lateral bending condition, compared with those of the flexion and extension conditions. CONCLUSIONS: Both the developed child and adult cervical spinal segment C6-C7 FE models exhibited high biofidelity. The responses (angular displacement, the ligament elongation ratio, and the maximum effective strain of annulus fibrosus) of the child and adult are dependent on the loading types, and the responses of the child were obviously larger than those of the adult under the same loading conditions.

Anisotropic and strain rate-dependent mechanical properties and constitutive modeling of the cancellous bone from piglet cervical vertebrae.

BACKGROUND AND OBJECTIVE: Characterizing the mechanical properties of the cancellous bone from the cervical vertebrae of child or child surrogate is important for the development of spine finite element models and the investigation of injury mechanism, however, there is currently no public data available as far as we know. METHODS: Compression tests were conducted on the specimens from the cervical vertebrae of 8-week-old piglets (child surrogates) in axial and radial directions at the strain rates of 0.01, 0.1, 1 and 10/s. The influences of directionality and strain rate on the mechanical properties of the vertebral cancellous bone were statistically investigated. The typical transversely isotropic model, which was added a strain rate item and a plasticity item, was implemented into LS-DYNA finite element code. Based on the material subroutine code, simulation was conducted on the vertebral tissue under compression in axial and radial directions at different strain rates. RESULTS: The mechanical properties of the cancellous bone of cervical vertebrae were obtained and most of the stress-strain curves showed major linear elastic stage and short plastic stage before fracture. Significant anisotropic behavior was observed for the vertebral tissue in axial and radial directions. The elastic modulus, ultimate stress,yield stress, and ultimate strain of the speimens in axial direction was obtained, with on average, 2.5 ±â€¯0.6 times, 2.1 ±â€¯0.15 times, and 2.1 ±â€¯0.1 times higher and 0.86 ± 0.076 times lower respecitvely, than those in radial direction. In addition, with the strain rate varying from 0.01/s to 10/s, the mechanical parameters, like elastic modulus, yield and ultimte stresses exhibited significant strain rate effect, however, no significant difference was found for the ultimate strain. CONCLUSIONS: The cervical vertebrae showed significant anisotropic and strain rate-dependent behaviors. The self-developed subroutine codes based on the strain rate-dependent transversely isotropic elastic and plastic constitutive model can simulate the behaviors well.