Parametric Design of Femoral Implant with Gradient Porous Structure

Patients who has been implanted with hip implant usually undergo revision surgery. The reason is that high stiff implants would cause non-physiological distribution loadings, which is also known as stress shielding, and finally lead to bone loss and aseptic loosening. Titanium implants are widely used in human bone tissues; however, the subsequent elastic modulus mismatch problem has become increasingly serious, and can lead to stress-shielding effects. This study aimed to develop a parametric design methodology of porous titanium alloy hip implant with gradient elastic modulus, and mitigate the stress-shielding effect. Four independent adjustable dimensions of the porous structure were parametrically designed, and the Kriging algorithm was used to establish the mapping relationship between the four adjustable dimensions and the porosity, surface-to-volume ratio, and elastic modulus. Moreover, the equivalent stress on the surface of the femur was optimized by response surface methodology, and the optimal gradient elastic modulus of the implant was obtained. Finally, through the Kriging approximation model and optimization results of the finite element method, the dimensions of each segment of the porous structure that could effectively mitigate the stress-shielding effect were determined. Experimental results demonstrated that the parameterized design method of the porous implant with gradient elastic modulus proposed in this study increased the strain value on the femoral surface by 17.1% on average. Consequently, the stress-shielding effect of the femoral tissue induced by the titanium alloy implant was effectively mitigated

A review on the shear performance of reinforced concrete (RC) beams strengthened with externally bonded mortar-based composites

This paper reviews the performance of shear strengthened reinforced concrete (RC) beams with the use of externally bonded mortar-based composite jackets (e.g. FRCM, ECC, UHPFRC). An experimental database was compiled gathering all the known studies in strengthening shear deficient RC beams using innovative mortar-based systems. The role of the RC beams’ inherent deficiencies as well as the impact of the design parameters of the alternative jacketing configurations were identified. Existing design models proposed to predict the contribution of the mortar-based composites to the shear strength of RC beams were assessed using the database and conclusions were drawn regarding their accuracy

Human posture recognition based on multiple features and rule learning

The use of skeleton data for human posture recognition is a key research topic in the human-computer interaction field. To improve the accuracy of human posture recognition, a new algorithm based on multiple features and rule learning is proposed in this paper. Firstly, a 219-dimensional vector that includes angle features and distance features is defined. Specifically, the angle and distance features are defined in terms of the local relationship between joints and the global spatial location of joints. Then, during human posture classification, the rule learning method is used together with the Bagging and random sub-Weili Ding space methods to create different samples and features for improved classification of sub-classifiers for different samples. Finally, the performance of our proposed algorithm is evaluated on four human posture datasets. The experimental results show that our algorithm can recognize many kinds of human postures effectively, and the results obtained by the rule-based learning method are of higher interpretability than those by traditional machine learning methods and CNNs

Theoretical modeling approach for adsorption of fibronectin on the nanotopographical implants

The success of orthopedic implants depends on the sufficient integration between tissue and implant, which is influenced by the cellular responses to their microenvironment. The conformation of adsorbed extracellular matrix is crucial for cellular behavior instruction via manipulating the physiochemical features of materials. To investigate the electrostatic adsorption mechanism of fibronectin on nanotopographies, a theoretical model was established to determine surface charge density and Coulomb’s force of nanotopography – fibronectin interactions using a Laplace equation satisfying the boundary conditions. Surface charge density distribution of nanotopographies with multiple random fibronectin was simulated based on random number and Monte Carlo hypothesis. The surface charge density on the nanotopographies was compared to the experimental measurements, to verify the effectiveness of the theoretical model. The model was implemented to calculate the Coulomb’s force generated by nanotopographies to compare the fibronectin adsorption. This model has revealed the multiple random quantitative fibronectin electrostatic adsorption to the nanotopographies, which is beneficial for orthopedic implant surface design. Significance: The conformation and distribution of adsorbed extracellular matrix on biomedical implants are crucial for directing cellular behaviors. However, the Ti nanotopography-ECM interaction mechanism remains largely unknown. This is mostly because of the interactions that are driven by electrostatic force, and any experimental probe could interfere with the electric field between the charged protein and Ti surface. A theoretical model is hereby proposed to simulate the adsorption between nanotopographies and fibronectin. Random number and Monte Carlo hypothesis were applied for multiple random fibronectin simulation, and the Coulomb’s force between nanoconvex and nanoconcave structures was comparatively analyzed

Optimization of nano coating to reduce the thermal deformation of ball screws

To reduce the thermal deformation of ball screws, the process of nano coating preparation for coating on ball screws to reduce temperature rise and thereby thermal deformation was discussed in this article. Simultaneously, the cooling mechanism was presented. The thermal channels and the relatively even distribution of graphene in the nano coating were observed in scanning electron microscopic images. In terms of the preparation of nano coating, optimization design was carried out to obtain the optimized material ratio and nozzle flow through orthogonal experiment. The influence of design parameters of nano coating on reducing thermal deformation was also discussed. The experimental results show that the maximum temperature rise, thermal deformation, and time to reach thermal balance decreased by 12.5, 69.1, and 46.3%, respectively. The effectiveness of nano coating in reducing thermal deformation was validated experimentally

Imaging of objects through a thin scattering layer using a spectrally and spatially separated reference

Incoherently illuminated or luminescent objects give rise to a low-contrast speckle-like pattern when observed through a thin diffusive medium, as such a medium effectively convolves their shape with a speckle-like point spread function (PSF). This point spread function can be extracted in the presence of a reference object of known shape. Here it is shown that reference objects that are both spatially and spectrally separated from the object of interest can be used to obtain an approximation of the point spread function. The crucial observation, corroborated by analytical calculations, is that the spectrally shifted point spread function is strongly correlated to a spatially scaled one. With the approximate point spread function thus obtained, the speckle-like pattern is deconvolved to produce a clear and sharp image of the object on a speckle-like background of low intensity

Establishment of a large animal model for research on transbronchial arterial intervention for lung cancer

PURPOSEWe aimed to evaluate whether bronchial artery can supply a percutaneously inoculated canine transmissible venereal tumor (CTVT) in a lung tumor model.METHODSFresh CTVT tissue blocks were percutaneously inoculated into unilateral or bilateral lungs of six immunosuppressed dogs at the mid zone of the middle or lower lobe. Tumor growth was monitored by computed tomography (CT). Ten weeks after inoculation, pulmonary arterial digital subtraction angiography (DSA), bronchial arterial DSA, transpulmonary arterial contrast-enhanced multislice CT, transbronchial arterial contrast-enhanced multislice CT (BA-MSCT), and transpulmonary arterial lipiodol multislice CT were performed.RESULTSTumor growth was seen in all 10 inoculated sites, with a maximum diameter of 2.734±0.138 cm at 10th week. Bronchial arterial blood supply was evident in 9 nodules on DSA, and was equivocal in one which was later demonstrated on BA-MSCT. No obvious pulmonary arterial blood supply was observed in any of the nodules. Lipiodol deposition was displayed in two of the small distant metastases, which indicated that pulmonary artery was involved in the supply of the metastases.CONCLUSIONOur results demonstrated bronchial arterial blood supply in this new lung cancer model. This model may be used in further research on transbronchial arterial intervention for lung cancer

KMT2A promotes melanoma cell growth by targeting hTERT signaling pathway.

Melanoma is an aggressive cutaneous malignancy, illuminating the exact mechanisms and finding novel therapeutic targets are urgently needed. In this study, we identified KMT2A as a potential target, which promoted the growth of human melanoma cells. KMT2A knockdown significantly inhibited cell viability and cell migration and induced apoptosis, whereas KMT2A overexpression effectively promoted cell proliferation in various melanoma cell lines. Further study showed that KMT2A regulated melanoma cell growth by targeting the hTERT-dependent signal pathway. Knockdown of KMT2A markedly inhibited the promoter activity and expression of hTERT, and hTERT overexpression rescued the viability inhibition caused by KMT2A knockdown. Moreover, KMT2A knockdown suppressed tumorsphere formation and the expression of cancer stem cell markers, which was also reversed by hTERT overexpression. In addition, the results from a xenograft mouse model confirmed that KMT2A promoted melanoma growth via hTERT signaling. Finally, analyses of clinical samples demonstrated that the expression of KMT2A and hTERT were positively correlated in melanoma tumor tissues, and KMT2A high expression predicted poor prognosis in melanoma patients. Collectively, our results indicate that KMT2A promotes melanoma growth by activating the hTERT signaling, suggesting that the KMT2A/hTERT signaling pathway may be a potential therapeutic target for melanoma