Quantitative morphological analysis framework of infant cranial sutures and fontanelles based on CT images.

Characterizing the suture morphological variation is a crucial step to investigate the influence of sutures on infant head biomechanics. This study aimed to establish a comprehensive quantitative framework for accurately capturing the cranial suture and fontanelle morphologies in infants. A total of 69 CT scans of 2-4 month-old infant heads were segmented to identify semilandmarks at the borders of cranial sutures and fontanelles. Morphological characteristics, including length, width, sinuosity index (SI), and surface area, were measured. For this, an automatic method was developed to determine the junction points between sutures and fontanelles, and thin-plate-spline (TPS) was utilized for area calculation. Different dimensionality reduction methods were compared, including nonlinear and linear principal component analysis (PCA), as well as deep-learning-based variational autoencoder (VAE). Finally, the significance of various covariates was analyzed, and regression analysis was performed to establish a statistical model relating morphological parameters with global parameters. This study successfully developed a quantitative morphological framework and demonstrate its application in quantifying morphologies of infant sutures and fontanelles, which were shown to significantly relate to global parameters of cranial size, suture SI, and surface area for infants aged 2-4 months. The developed framework proved to be reliable and applicable in extracting infant suture morphology features from CT scans. The demonstrated application highlighted its potential to provide valuable insights into the morphologies of infant cranial sutures and fontanelles, aiding in the diagnosis of suture-related skull fractures. Infant suture, Infant fontanelle, Morphological variation, Morphology analysis framework, Statistical model.

Characterization of linezolid- and methicillin-resistant coagulase-negative staphylococci in a tertiary hospital in China.

BACKGROUND: Recently, linezolid-resistant staphylococci have become an emerging problem worldwide. Understanding the mechanisms of resistance, molecular epidemiology and transmission of linezolid-resistant CoNS in hospitals is very important. METHODS: The antimicrobial susceptibilities of all isolates were determined by the microdilution method. The resistance mechanisms and molecular characteristics of the strains were determined using whole-genome sequencing and PCR. RESULTS: All the strains were resistant to oxacillin and carried the mecA gene; 13 patients (36.1%) had prior linezolid exposure. Most S. epidermidis and S. hominis isolates were ST22 and ST1, respectively. MLST typing and evolutionary analysis indicated most linezolid-resistant CoNS strains were genetically related. In this study, we revealed that distinct CoNS strains have different mechanisms of linezolid resistance. Among ST22-type S. epidermidis, acquisition of the T2504A and C2534T mutations in the V domain of the 23 S rRNA gene, as well as mutations in the ribosomal proteins L3 (L101V, G152D, and D159Y) and L4 (N158S), were linked to the development of linezolid resistance. In S. cohnii isolates, cfr, S158Y and D159Y mutations in the ribosomal protein L3 were detected. Additionally, emergence of the G2576T mutation and the cfr gene were major causes of linezolid resistance in S. hominis isolates. The cfr gene, G2576T and C2104T mutations, M156T change in L3 protein, and I188S change in L4 protein were found in S. capitis isolates. CONCLUSION: The emergence of linezolid-resistant CoNS in the environment is concerning because it involves clonal dissemination and frequently coexists with various drug resistance mechanisms.

A method for generating case-specific vehicle models from a single-view vehicle image for accurate pedestrian injury reconstructions.

Developing vehicle finite element (FE) models that match real accident-involved vehicles is challenging. This is related to the intricate variety of geometric features and components. The current study proposes a novel method to efficiently and accurately generate case-specific buck models for car-to-pedestrian simulations. To achieve this, we implemented the vehicle side-view images to detect the horizontal position and roundness of two wheels to rectify distortions and deviations and then extracted the mid-section profiles for comparative calculations against baseline vehicle models to obtain the transformation matrices. Based on the generic buck model which consists of six key components and corresponding matrices, the case-specific buck model was generated semi-automatically based on the transformation metrics. Utilizing this image-based method, a total of 12 vehicle models representing four vehicle categories including family car (FCR), Roadster (RDS), small Sport Utility Vehicle (SUV), and large SUV were generated for car-to-pedestrian collision FE simulations in this study. The pedestrian head trajectories, total contact forces, head injury criterion (HIC), and brain injury criterion (BrIC) were analyzed comparatively. We found that, even within the same vehicle category and initial conditions, the variation in wrap around distance (WAD) spans 84-165 mm, in HIC ranges from 98 to 336, and in BrIC fluctuates between 1.25 and 1.46. These findings highlight the significant influence of vehicle frontal shape and underscore the necessity of using case-specific vehicle models in crash simulations. The proposed method provides a new approach for further vehicle structure optimization aiming at reducing pedestrian head injury and increasing traffic safety.

Subject-specific finite element head models for skull fracture evaluation-a new tool in forensic pathology.

Post-mortem computed tomography (PMCT) enables the creation of subject-specific 3D head models suitable for quantitative analysis such as finite element analysis (FEA). FEA of proposed traumatic events is an objective and repeatable numerical method for assessing whether an event could cause a skull fracture such as seen at autopsy. FEA of blunt force skull fracture in adults with subject-specific 3D models in forensic pathology remains uninvestigated. This study aimed to assess the feasibility of FEA for skull fracture analysis in routine forensic pathology. Five cases with blunt force skull fracture and sufficient information on the kinematics of the traumatic event to enable numerical reconstruction were chosen. Subject-specific finite element (FE) head models were constructed by mesh morphing based on PMCT 3D models and A Detailed and Personalizable Head Model with Axons for Injury Prediction (ADAPT) FE model. Morphing was successful in maintaining subject-specific 3D geometry and quality of the FE mesh in all cases. In three cases, the simulated fracture patterns were comparable in location and pattern to the fractures seen at autopsy/PMCT. In one case, the simulated fracture was in the parietal bone whereas the fracture seen at autopsy/PMCT was in the occipital bone. In another case, the simulated fracture was a spider-web fracture in the frontal bone, whereas a much smaller fracture was seen at autopsy/PMCT; however, the fracture in the early time steps of the simulation was comparable to autopsy/PMCT. FEA might be feasible in forensic pathology in cases with a single blunt force impact and well-described event circumstances.

Evaluating child helmet protection and testing standards: A study using PIPER child head models aged 1.5, 3, 6, and 18 years.

The anatomy of children's heads is unique and distinct from adults, with smaller and softer skulls and unfused fontanels and sutures. Despite this, most current helmet testing standards for children use the same peak linear acceleration threshold as for adults. It is unclear whether this is reasonable and otherwise what thresholds should be. To answer these questions, helmet-protected head responses for different ages are needed which is however lacking today. In this study, we apply continuously scalable PIPER child head models of 1.5, 3, and 6 years old (YO), and an upgraded 18YO to study child helmet protection under extensive linear and oblique impacts. The results of this study reveal an age-dependence trend in both global kinematics and tissue response, with younger children experiencing higher levels of acceleration and velocity, as well as increased skull stress and brain strain. These findings indicate the need for better protection for younger children, suggesting that youth helmets should have a lower linear kinematic threshold, with a preliminary value of 150g for 1.5-year-old helmets. However, the results also show a different trend in rotational kinematics, indicating that the threshold of rotational velocity for a 1.5YO is similar to that for adults. The results also support the current use of small-sized adult headforms for testing child helmets before new child headforms are available.

Development of personalizable female and male pedestrian SAFER human body models.

OBJECTIVES: Vulnerable road users are globally overrepresented as victims of road traffic injuries. Developing biofidelic male and female pedestrian human body models (HBMs) that represent diverse anthropometries is essential to enhance road safety and propose intervention strategies. METHODS: In this study, 50th percentile male and female pedestrians of the SAFER HBM were developed via a newly developed image registration-based mesh morphing framework. The performance of the HBMs was evaluated by means of a set of cadaver experiments, involving subjects struck laterally by a generic sedan buck. RESULTS: In simulated whole-body pedestrian collisions, the personalized HBMs effectively replicate trajectories of the head and lower body regions, as well as head kinematics, in lateral impacts. The results also demonstrate the personalization framework's capacity to generate personalized HBMs with reliable mesh quality, ensuring robust simulations. CONCLUSIONS: The presented pedestrian HBMs and personalization framework provide robust means to reconstruct and evaluate head impacts in pedestrian-to-vehicle collisions thoroughly and accurately.

Prediction of skull fractures in blunt force head traumas using finite element head models.

Traumatic head injuries remain a leading cause of death and disability worldwide. Although skull fractures are one of the most common head injuries, the fundamental mechanics of cranial bone and its impact tolerance are still uncertain. In the present study, a strain-rate-dependent material model for cranial bone has been proposed and implemented in subject-specific Finite Element (FE) head models in order to predict skull fractures in five real-world fall accidents. The subject-specific head models were developed following an established image-registration-based personalization pipeline. Head impact boundary conditions were derived from accident reconstructions using personalized human body models. The simulated fracture lines were compared to those visible in post-mortem CT scans of each subject. In result, the FE models did predict the actual occurrence and extent of skull fractures in all cases. In at least four out of five cases, predicted fracture patterns were comparable to ones from CT scans and autopsy reports. The tensile material model, which was tuned to represent rate-dependent tensile data of cortical skull bone from literature, was able to capture observed linear fractures in blunt indentation loading of a skullcap specimen. The FE model showed to be sensitive to modeling parameters, in particular to the constitutive parameters of the cortical tables. Nevertheless, this study provides a currently lacking strain-rate dependent material model of cranial bone that has the capacity to accurately predict linear fracture patterns. For the first time, a procedure to reconstruct occurrences of skull fractures using computational engineering techniques, capturing the all-in-all fracture initiation, propagation and final pattern, is presented.

Personalization of human body models and beyond via image registration.

Finite element human body models (HBMs) are becoming increasingly important numerical tools for traffic safety. Developing a validated and reliable HBM from the start requires integrated efforts and continues to be a challenging task. Mesh morphing is an efficient technique to generate personalized HBMs accounting for individual anatomy once a baseline model has been developed. This study presents a new image registration-based mesh morphing method to generate personalized HBMs. The method is demonstrated by morphing four baseline HBMs (SAFER, THUMS, and VIVA+ in both seated and standing postures) into ten subjects with varying heights, body mass indices (BMIs), and sex. The resulting personalized HBMs show comparable element quality to the baseline models. This method enables the comparison of HBMs by morphing them into the same subject, eliminating geometric differences. The method also shows superior geometry correction capabilities, which facilitates converting a seated HBM to a standing one, combined with additional positioning tools. Furthermore, this method can be extended to personalize other models, and the feasibility of morphing vehicle models has been illustrated. In conclusion, this new image registration-based mesh morphing method allows rapid and robust personalization of HBMs, facilitating personalized simulations.

Study on the Prognostic Values of TTC36 Correlated with Immune Infiltrates and Its Methylation in Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) remains an incurable disease with a very poor clinical outcome. The purpose of this article was to investigate whether the expression or methylation of tetrapeptide repeat domain 36 (TTC36) could be used as a prognostic marker in hepatocellular carcinoma. TCGA database was used to obtain information on HCC gene expression and the associated clinical features of HCC patients. Differentially expressed genes (DEGs) were screened between 374 HCC specimens and 50 nontumor specimens. The expression and prognostic value of TTC36 were analyzed. The correlations between TTC36 and cancer immune infiltrates were investigated via TIMER. In this study, HCC specimens and nontumor specimens were compared and 35 DEGs were found between them. Among the 35 DEGs, the expression of TTC36 was significantly reduced in HCC samples compared with nontumor samples. Survival tests revealed that patients with low TTC36 expression had a shorter overall survival than patients with high TTC36 expression. TTC36 was found to be an independent predictive factor for HCC in both univariate and multivariate regression analyses. TTC36 was negatively regulated by TTC36 methylation, leading to its low expression in HCC tissues. Immune analysis revealed that TTC36 expression has significant correlations with B cell, T cell CD4+, neutrophil, macrophage, and myeloid dendritic cell. Finally, TTC36 expression was dramatically reduced in HCC cells, and overexpression greatly suppressed HCC cell proliferation and invasion, according to our experimental results. Overall, our data suggested that TTC36 could be applied as a prognostic marker for predicting outcome and immune infiltration in HCC.

Fiber orientation downsampling compromises the computation of white matter tract-related deformation.

Incorporating neuroimaging-revealed structural details into finite element (FE) head models opens vast new opportunities to better understand brain injury mechanisms. Recently, growing efforts have been made to integrate fiber orientation from diffusion tensor imaging (DTI) into FE models to predict white matter (WM) tract-related deformation that is biomechanically characterized by tract-related strains. Commonly used approaches often downsample the spatially enriched fiber orientation to match the FE resolution with one orientation per element (i.e., element-wise orientation implementation). However, the validity of such downsampling operation and corresponding influences on the computed tract-related strains remain elusive. To address this, the current study proposed a new approach to integrate voxel-wise fiber orientation from one DTI atlas (isotropic resolution of 1 mm3) into FE models by embedding orientations from multiple voxels within one element (i.e., voxel-wise orientation implementation). By setting the responses revealed by the newly proposed voxel-wise orientation implementation as the reference, we evaluated the reliability of two previous downsampling approaches by examining the downsampled fiber orientation and the computationally predicted tract-related strains secondary to one concussive impact. Two FE models with varying element sizes (i.e., 6.4 ± 1.6 mm and 1.3 ± 0.6 mm, respectively) were incorporated. The results showed that, for the model with a large voxel-mesh resolution mismatch, the downsampled element-wise fiber orientation, with respect to its voxel-wise counterpart, exhibited an absolute deviation over 30° across the WM/gray matter interface and the pons regions. Accordingly, this orientation deviation compromised the computation of tract-related strains with normalized root-mean-square errors up to 30% and underestimated the peak tract-related strains up to 10%. For the other FE model with finer meshes, the downsampling-induced effects were lower, both on the fiber orientation and tract-related strains. Taken together, the voxel-wise orientation implementation is recommended in future studies as it leverages the DTI-delineated fiber orientation to a larger extent than the element-wise orientation implementation. Thus, this study yields novel insights on integrating neuroimaging-revealed fiber orientation into FE models and may better inform the computation of WM tract-related deformation.

The Presence of the Temporal Horn Exacerbates the Vulnerability of Hippocampus During Head Impacts.

Hippocampal injury is common in traumatic brain injury (TBI) patients, but the underlying pathogenesis remains elusive. In this study, we hypothesize that the presence of the adjacent fluid-containing temporal horn exacerbates the biomechanical vulnerability of the hippocampus. Two finite element models of the human head were used to investigate this hypothesis, one with and one without the temporal horn, and both including a detailed hippocampal subfield delineation. A fluid-structure interaction coupling approach was used to simulate the brain-ventricle interface, in which the intraventricular cerebrospinal fluid was represented by an arbitrary Lagrangian-Eulerian multi-material formation to account for its fluid behavior. By comparing the response of these two models under identical loadings, the model that included the temporal horn predicted increased magnitudes of strain and strain rate in the hippocampus with respect to its counterpart without the temporal horn. This specifically affected cornu ammonis (CA) 1 (CA1), CA2/3, hippocampal tail, subiculum, and the adjacent amygdala and ventral diencephalon. These computational results suggest that the presence of the temporal horn exacerbate the vulnerability of the hippocampus, highlighting the mechanobiological dependency of the hippocampus on the temporal horn.

Evaluation of parental education using biomechanical visualization to increase child restraint use in China.

INTRODUCTION: Despite demonstrated effectiveness of child restraint system (CRS), its use in China is extremely low due to the lack of national legislation requiring the use of CRS, as well as lack of child passenger safety knowledge among caregivers. Implementing an effective intervention is urgently needed to promote the use of CRS. In this study, we primarily evaluated the effectiveness of biomechanical visualization delivered in the context of CRS education to promote CRS use. METHODS: We conducted a cluster randomised controlled trial to test the effects of educational intervention programs on increased use of CRS. Participants included caregivers from 8 pre-schools located in two cities (i.e., Chaozhou and Shantou) in China. Following a baseline survey, 8 pre-schools were randomly assigned into 1 of 4 groups with 2 schools in each group: 1) CRS education-only, 2) CRS education with behavioral skill training, 3) CRS education with biomechanical visualization, and 4) control. The primary outcome was CRS use, and the secondary outcomes included scores of child passenger safety-related knowledge and CRS use-related attitudes. The effect of the intervention was assessed among caregivers at two time points: baseline preintervention and 6 months postintervention. RESULTS: More than 70% caregivers had never used CRS at baseline. No statistically significant between-group differences CRS use were observed at baseline preintervention (34.2%, 25.4%, 29.6% and 21.9%, respectively, P = 0.18). However, compared to the control group, odds of CRS non-use was significantly lower in caregivers assigned to the CRS education with biomechanical visualization (adjusted odd ratio (AOR) = 0.11, 95% confidence interval (CI) = 0.07-0.17), CRS education with behavioral skill training (AOR = 0.15, 95%CI = 0.10-0.24) and CRS education-only (AOR = 0.26, 95%CI = 0.17-0.41) groups, respectively. Statistically significant differences were also observed in the secondary outcomes postintervention across groups. Specifically, the CRS education with biomechanical visualization and CRS education with behavioral skill training groups had higher mean knowledge change scores than the CRS education-only group (3.3 ± 1.5 vs. 2.9 ± 2.2, p = 0.035 and 3.2 ± 1.9 vs. 2.9 ± 2.2, p = 0.039, respectively). We also observed a significantly higher increase in the attitudes scores in the CRS education with biomechanical visualization group compared with the CRS education-only group (4.7 ± 2.1 vs. 3.5 ± 2.8,p = 0.026). CONCLUSIONS: This study shows that both biomechanical visualization and behavioral skill training supplements to education improved understanding of CRS knowledge compared to education only, and all three strategies led to increased CRS use. Importantly, CRS education with biomechanical visualization was shown to be more effective than CRS education alone in improving caregiver's knowledge and attitudes. The use of biomechanical visualization may be an effective supplement to traditional education programs.

Trends in antimicrobial resistance in bloodstream infections at a large tertiary-care hospital in China: a 10-year retrospective study (2010-2019).

OBJECTIVES: Bloodstream infections (BSIs) are a major cause of morbidity and mortality worldwide. This study aimed to explore the distribution and antimicrobial resistance of BSI pathogens at a tertiary-care hospital in China. METHODS: Surveillance blood cultures were routinely taken from patients with fever or suspected sepsis from 2010-2019 at the First Affiliated Hospital of Zhengzhou University. Isolate identification was performed by VITEK®2 Compact and/or VITEK® MS. Antimicrobial susceptibility testing was carried out by MIC determination and/or disk diffusion. RESULTS: Totally, 18 180 strains were isolated from blood cultures, the most common being Escherichia coli (21.7%), followed by coagulase-negative staphylococci (CoNS) (18.8%), Klebsiella pneumoniae (13.0%) and Staphylococcus aureus (6.6%). Escherichia coli resistance rates to ceftazidime, ceftriaxone, cefepime and aztreonam showed a significant declining trend, and the frequency of carbapenem-resistant E. coli was <6.0% over time. Noteworthy, the proportion of carbapenem-resistant K. pneumoniae exhibited a sharp upward trend (from 6.7% to 56.7%). The prevalence of carbapenem-resistant A. baumannii remained at a high level (>75%). Pseudomonas aeruginosa resistance rates against all tested agents were <25%, and resistance rates to aminoglycosides and fluoroquinolones showed a significant downward trend. The frequency of methicillin-resistant CoNS maintained a high level (>70%), however the isolation rate of MRSA ranged from 58.0% to 34.7%, showing a significant decline. CONCLUSION: The dramatic increase in carbapenem-resistant K. pneumoniae during 10 years was noteworthy. Effective infection control measures and stewardship efforts should be taken to prevent their spread. Our results indicate the importance of active surveillance for aetiology and resistance of BSI isolates.

Subject-Specific Head Model Generation by Mesh Morphing: A Personalization Framework and Its Applications.

Finite element (FE) head models have become powerful tools in many fields within neuroscience, especially for studying the biomechanics of traumatic brain injury (TBI). Subject-specific head models accounting for geometric variations among subjects are needed for more reliable predictions. However, the generation of such models suitable for studying TBIs remains a significant challenge and has been a bottleneck hindering personalized simulations. This study presents a personalization framework for generating subject-specific models across the lifespan and for pathological brains with significant anatomical changes by morphing a baseline model. The framework consists of hierarchical multiple feature and multimodality imaging registrations, mesh morphing, and mesh grouping, which is shown to be efficient with a heterogeneous dataset including a newborn, 1-year-old (1Y), 2Y, adult, 92Y, and a hydrocephalus brain. The generated models of the six subjects show competitive personalization accuracy, demonstrating the capacity of the framework for generating subject-specific models with significant anatomical differences. The family of the generated head models allows studying age-dependent and groupwise brain injury mechanisms. The framework for efficient generation of subject-specific FE head models helps to facilitate personalized simulations in many fields of neuroscience.

Toward a Comprehensive Delineation of White Matter Tract-Related Deformation.

Finite element (FE) models of the human head are valuable instruments to explore the mechanobiological pathway from external loading, localized brain response, and resultant injury risks. The injury predictability of these models depends on the use of effective criteria as injury predictors. The FE-derived normal deformation along white matter (WM) fiber tracts (i.e., tract-oriented strain) recently has been suggested as an appropriate predictor for axonal injury. However, the tract-oriented strain only represents a partial depiction of the WM fiber tract deformation. A comprehensive delineation of tract-related deformation may improve the injury predictability of the FE head model by delivering new tract-related criteria as injury predictors. Thus, the present study performed a theoretical strain analysis to comprehensively characterize the WM fiber tract deformation by relating the strain tensor of the WM element to its embedded fiber tract. Three new tract-related strains with exact analytical solutions were proposed, measuring the normal deformation perpendicular to the fiber tracts (i.e., tract-perpendicular strain), and shear deformation along and perpendicular to the fiber tracts (i.e., axial-shear strain and lateral-shear strain, respectively). The injury predictability of these three newly proposed strain peaks along with the previously used tract-oriented strain peak and maximum principal strain (MPS) were evaluated by simulating 151 impacts with known outcome (concussion or non-concussion). The results preliminarily showed that four tract-related strain peaks exhibited superior performance than MPS in discriminating concussion and non-concussion cases. This study presents a comprehensive quantification of WM tract-related deformation and advocates the use of orientation-dependent strains as criteria for injury prediction, which may ultimately contribute to an advanced mechanobiological understanding and enhanced computational predictability of brain injury.

Influence of Anisotropic White Matter on Electroosmotic Flow Induced by Direct Current.

Treatment of cerebral edema remains a major challenge in clinical practice and new innovative therapies are needed. This study presents a novel approach for mitigating cerebral edema by inducing bulk fluid transport utilizing the brain's electroosmotic property using an anatomically detailed finite element head model incorporating anisotropy in the white matter (WM). Three representative anisotropic conductivity algorithms are employed for the WM and compared with isotropic WM. The key results are (1) the electroosmotic flow (EOF) is driven from the edema region to the subarachnoid space under an applied electric field with its magnitude linearly correlated to the electric field and direction following current flow pathways; (2) the extent of EOF distribution variation correlates highly with the degree of the anisotropic ratio of the WM regions; (3) the directions of the induced EOF in the anisotropic models deviate from its isotropically defined pathways and tend to move along the principal fiber direction. The results suggest WM anisotropy should be incorporated in head models for more reliable EOF evaluations for cerebral edema mitigation and demonstrate the promise of the electroosmosis based approach to be developed as a new therapy for edema treatment as evaluated with enhanced head models incorporating WM anisotropy.

Nanosilver-Decorated Biodegradable Mesoporous Organosilica Nanoparticles for GSH-Responsive Gentamicin Release and Synergistic Treatment of Antibiotic-Resistant Bacteria.

PURPOSE: Antibiotic-resistant bacteria are pathogens that have emerged as a serious public health risk. Thus, there is an urgent need to develop a new generation of anti-bacterial materials to kill antibiotic-resistant bacteria. METHODS: Nanosilver-decorated mesoporous organosilica nanoparticles (Ag-MONs) were fabricated for co-delivery of gentamicin (GEN) and nanosilver. After investigating the glutathione (GSH)-responsive matrix degradation and controlled release of both GEN and silver ions, the anti-bacterial activities of Ag-MONs@GEN were systematically determined against several antibiotic-susceptible and antibiotic-resistant bacteria including Escherichia coli, Pseudomonas aeruginosa, Staphylococcus aureus, and Enterococcus faecalis. Furthermore, the cytotoxic profiles of Ag-MONs@GEN were evaluated. RESULTS: The GEN-loaded nanoplatform (Ag-MONs@GEN) showed glutathione-responsive matrix degradation, resulting in the simultaneous controlled release of GEN and silver ions. Ag-MONs@GEN exhibited excellent anti-bacterial activities than Ag-MONs and GEN alone via inducing ROS generation, especially enhancing synergetic effects against four antibiotic-resistant bacteria including Escherichia coli, Pseudomonas aeruginosa, Staphylococcus aureus, and Enterococcus faecalis. Moreover, the IC50 values of Ag-MONs@GEN in L929 and HUVECs cells were 313.6 ± 15.9 and 295.7 ± 12.3 µg/mL, respectively, which were much higher than their corresponding minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) values. CONCLUSION: Our study advanced the development of Ag-MONs@GEN for the synergistic and safe treatment of antibiotic-resistant bacteria.

Designing electrode configuration of electroosmosis based edema treatment as a complement to hyperosmotic therapy.

BACKGROUND: Hyperosmotic therapy is a mainstay treatment for cerebral edema. Although often effective, its disadvantages include mainly acting on the normal brain region with limited effectiveness in eliminating excess fluid in the edema region. This study investigates how to configure our previously proposed novel electroosmosis based edema treatment as a complement to hyperosmotic therapy. METHODS: Three electrode configurations are designed to drive the excess fluid out of the edema region, including 2-electrode, 3-electrode, and 5-electrode designs. The focality and directionality of the induced electroosmotic flow (EOF) are then investigated using the same patient-specific head model with localized edema. RESULTS: The 5-electrode design shows improved EOF focality with reduced effect on the normal brain region than the other two designs. Importantly, this design also achieves better directionality driving excess edema tissue fluid to a larger region of surrounding normal brain where hyperosmotic therapy functions better. Thus, the 5-electrode design is suggested to treat edema more efficiently via a synergic effect: the excess fluid is first driven out from the edema to surrounding normal brain via EOF, where it can then be treated with hyperosmotic therapy. Meanwhile, the 5-electrode design drives 2.22 mL excess fluid from the edema region in an hour comparable to the other designs, indicating a similar efficiency of EOF. CONCLUSIONS: The results show that the promise of our previously proposed novel electroosmosis based edema treatment can be designed to achieve better focality and directionality towards a complement to hyperosmotic therapy.

A Novel Neuromuscular Head-Neck Model and Its Application on Impact Analysis.

OBJECTIVE: Neck muscle activation plays an important role in maintaining posture and preventing trauma injuries of the head-neck system, levels of which are primarily controlled by the neural system. Thus, the present study aims to establish and validate a neuromuscular head-neck model as well as to investigate the effects of realistic neural reflex control on head-neck behaviors during impact loading. METHODS: The neuromuscular head-neck model was first established based on a musculoskeletal model by including neural reflex control of the vestibular system and proprioceptors. Then, a series of human posture control experiments was implemented and used to validate the model concerning both joint kinematics of the cervical spine and neck muscle activations. Finally, frontal impact experiments of varying loading severities were simulated with the newly established model and compared with an original model to investigate the influences of the implanted neural reflex controllers on head-neck kinematic responses. RESULTS: The simulation results using the present neuromuscular model showed good correlations with in-vivo experimental data while the original model even cannot reach a correct balance status. Furthermore, the vestibular reflex is noted to dominate the muscle activation in less severe impact loadings while both vestibular and proprioceptive controllers have a lot of effect in higher impact loading severity cases. CONCLUSIONS: In summary, a novel neuromuscular head-model was established and its application demonstrated the significance of the neural reflex control in predicting in vivo head-neck responses and preventing related injury risk due to impact loading.