Modeling the biomechanics of swine mastication – An inverse dynamics approach

A novel reconstructive alternative for patients with severe facial structural deformity is Le Fort-based, face-jaw-teeth transplantation (FJTT). To date, however, only ten surgeries have included underlying skeletal and jaw-teeth components, all yielding sub-optimal results and a need for a subsequent revision surgery, due to size mismatch and lack of precise planning. Numerous studies have proven swine to be appropriate candidates for translational studies including pre-operative planning of transplantation. An important aspect of planning FJTT is determining the optimal muscle attachment sites on the recipient?s jaw, which requires a clear understanding of mastication and bite mechanics in relation to the new donated upper and/or lower jaw. A segmented CT scan coupled with data taken from literature defined a biomechanical model of mandible and jaw muscles of a swine. The model was driven using tracked motion and external force data of one cycle of chewing published earlier, and predicted the muscle activation patterns as well as temporomandibular joint (TMJ) reaction forces and condylar motions. Two methods, polynomial and min/max optimization, were used for solving the muscle recruitment problem. Similar performances were observed between the two methods. On average, there was a mean absolute error (MAE) of <0.08 between the predicted and measured activation levels of all muscles, and an MAE of <7 N for TMJ reaction forces. Simulated activations qualitatively followed the same patterns as the reference data and there was very good agreement for simulated TMJ forces. The polynomial optimization produced a smoother output, suggesting that it is more suitable for studying such motions. Average MAE for condylar motion was 1.2 mm, which reduced to 0.37 mm when the input incisor motion was scaled to reflect the possible size mismatch between the current and original swine models. Results support the hypothesis that the model can be used for planning of facial transplantation.     

MicroRNA-4731-5p delivered by AD-mesenchymal stem cells induces cell cycle arrest and apoptosis in glioblastoma

Glioblastoma multiforme (GBM) exhibits the most malignant brain tumor with very poor prognosis. MicroRNAs (miRNAs) are regulatory factors that can downregulate the expression of multiple genes. Several miRNAs acting as tumor-suppressor genes have been identified so far. The delivery of miRNA by mesenchymal stem cell (MSC) due to their ability to specifically target tumors is a new, hopeful therapeutic approach for glioblastoma. The objective of our study is the investigation of the effect of lentivirus-mediated microRNA-4731 (miR-4731) genetic manipulated adipose-derived (AD)-MSC on GBM. The downregulation of miR-4731 in human GBM tumor was detected using the GEO dataset. To evaluate the function of miR-4731, we overexpressed miR-4731 using lentiviral vectors in U-87 and U-251 GBM cell lines. The effects of miR-4731 on cell proliferation and cell cycle of glioma cells were analyzed by wound test and flow-cytometry assay. miR-4731 inhibited the proliferation of GBM cancer cells. Coculturing was used to study the antiproliferative effect of miR-4731-AD-MSCs on GBM cell lines. Direct and indirect coculture of GBM cell lines with miR-4731-AD-MSCs induced cell cycle arrest and apoptosis. Our findings suggest that AD-MSCs expressing miR-4731 have favorable antitumor characteristics and should be further explored in future glioma therapy.     

Population Decoding in Rat Barrel Cortex: Optimizing the Linear Readout of Correlated Population Responses

Sensory information is encoded in the response of neuronal populations. How might this information be decoded by downstream neurons? Here we analyzed the responses of simultaneously recorded barrel cortex neurons to sinusoidal vibrations of varying amplitudes preceded by three adapting stimuli of 0, 6 and 12 µm in amplitude. Using the framework of signal detection theory, we quantified the performance of a linear decoder which sums the responses of neurons after applying an optimum set of weights. Optimum weights were found by the analytical solution that maximized the average signal-to-noise ratio based on Fisher linear discriminant analysis. This provided a biologically plausible decoder that took into account the neuronal variability, covariability, and signal correlations. The optimal decoder achieved consistent improvement in discrimination performance over simple pooling. Decorrelating neuronal responses by trial shuffling revealed that, unlike pooling, the performance of the optimal decoder was minimally affected by noise correlation. In the non-adapted state, noise correlation enhanced the performance of the optimal decoder for some populations. Under adaptation, however, noise correlation always degraded the performance of the optimal decoder. Nonetheless, sensory adaptation improved the performance of the optimal decoder mainly by increasing signal correlation more than noise correlation. Adaptation induced little systematic change in the relative direction of signal and noise. Thus, a decoder which was optimized under the non-adapted state generalized well across states of adaptation.     

OptCAM: An ultra‐fast all‐optical architecture for DNA variant discovery

Nowadays, the accelerated expansion of genetic data challenges speed of current DNA sequence alignment algorithms due to their electrical implementations. Essential needs of an efficient and accurate method for DNA variant discovery demand new approaches for parallel processing in real time. Fortunately, photonics, as an emerging technology in data computing, proposes optical correlation as a fast similarity measurement algorithm; while complexity of existing local alignment algorithms severely limits their applicability. Hence, in this paper, employing optical correlation for global alignment, we present an optical processing approach for local DNA sequence alignment to benefit both high‐speed processing and operational parallelism, inherently exist in optics. The proposed method, named as OptCAM, utilizes amplitude and wavelength of the optical signals, to accurately locate mutations through three main procedures. Furthermore, an all‐optical implementation of the OptCAM method is proposed consisting of three units, corresponding to the three OptCAM procedures. Performing considerably fast processes by passing optical signals through high‐throughput photonic devices, OptCAM avoids various limitations of electrical implementations. Accuracy and efficiency of the OptCAM method and its optical implementation are validated through numerical simulation by a gold standard simulation benchmark. The results indicate the proposed method is significantly faster than its electrical counterparts, in both single node and grid computation.      

Improved osteogenic differentiation of human induced pluripotent stem cells cultured on polyvinylidene fluoride/collagen/platelet-rich plasma composite nanofibers

Blood transfusion or blood products, such as plasma, have a long history in improving health, but today, platelet-rich plasma (PRP) is used in various medical areas such as surgery, orthopedics, and rheumatology in many ways. Considering the high efficiency of tissue engineering in repairing bone defects, in this study, we investigated the combined effect of nanofibrous scaffolds in combination with PRP on the osteogenic differentiation potential of human induced pluripotent stem cells (iPSCs). Electrospinning was used for fabricating nanofibrous scaffolds by polyvinylidene fluoride/collagen (PVDF/col) with and without PRP. After scaffold characterization, the osteoinductivity of the fabricated scaffolds was studied by culturing human iPSCs under osteogenic medium. The results showed that PRP has a considerable positive effect on the biocompatibility of the PVDF/col nanofibrous scaffold when examined by protein adsorption, cell attachment, and 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide assays. In addition, the results obtained from alkaline phosphatase activity and calcium content assays demonstrated that nanofibers have higher osteoinductivity while grown on PRP-incorporated PVDF/col nanofibers. These results were also confirmed while the osteogenic differentiation of the iPSCs was more investigated by evaluating the most important bone-related genes expression level. According to the results, it can be concluded that PVDF/col/PRP has much more osteoinductivity while compared with the PVDF/col, and it can be introduced as a promising bone bio-implant for use in bone tissue engineering applications.