Lessons learned in delayed identification of a misplaced electrode array in the vestibule

To report a case of cochlear implantation with a misplaced electrode array in the vestibule and the causes for the delay in identification.A 23-year-old male with left single-sided deafness underwent cochlear implantation.The intraoperative assessment did not reveal any major red flags of electrode array misplacement.He did not display any vestibular symptoms postoperatively but showed poor speech performance,even though the aided tone audiometry revealed good sound detection thresholds.High-resolution computed tomography(HRCT)showed that the entire perimodiolar electrode array was situated within the vestibule,and a revision surgery was conducted.Retrospective analysis of the neural response telemetry(NRT)revealed subtle differences in responses between the misplaced and correctly placed electrode arrays.Unlike previously reported cases,the patient did not display vestibular symptoms despite the misplacement of the electrode in the vestibule due to existing weakness in otolithic function.Further investigation is warranted when a motivated patient with normal inner ear anatomy does not show benefit with the cochlear implant post-operatively.

AB001.How to optimize the visual contrast response of cortical neurons

Background:In the visual system,one of the most explored neural behaviors is the response of cells to changes in visual contrast.This neural response to visual contrast,also known as the contrast response function(CRF),can be fitted with the Naka-Rushton equation(NRE).Assessing the CRF of many neurons at the same time is critical to establishing functional visual properties.However,maximizing the performance of neurons to fit the NRE,while minimizing their time acquisitions is a challenge.We present a method to accurately obtain reliable NRE fits from experimental data,that ensure a reasonable time of record acquisition.Methods:We simulated CRF of cortical neurons with a toy model based on the response of Poisson spike trains to varied levels of contrasts.We first tested whether mean values or the whole set of contrast responses fit better the NRE.Then,we analyzed what were the boundaries to optimize the fit of the NRE,and after we explore the consequences of fitting the NRE with single-or multi-units.With these outcomes,we varied experimental parameters such as the number of trials,number of input contrasts and length of time acquisition to calculate the errors of fitting CRFs.Those data sets that maximize the CRF fit but minimize the time of recording were selected.The selected data set was then evaluated in visual cortical neurons of anesthetized cats from areas 17,18 and 21a.Results:First,we found that is always better to fit the NRE with mean values rather than the whole set of points.Then,we noticed that either removing or imposing loose boundaries to the CRF parameters lead to an increase in the performance of the NRE fit.Afterward,we found that single units(SU)or assume multi-unit formed of several SUs(>30)adjusted considerably better the NRE fit.Finally,the experiments showed that specific sets of patterns(number of trials,number of input contrasts and length of time acquisition)satisfied our two constraints:minimize the error of the NRE fit while maximizing the acquisition time of recording.The most characteristic pattern was the one with 6 points,15 repetitions and 1 second of duration.However,cortical areas varied in the representation of the patterns.Conclusions:Theoretical simulations of many different sets of patterns and their following experimental validation suggest strongly that a particular set of patterns can satisfy the imposed constraints.With this approach,we provided a tool that allows an optimal design of stimuli to assess the CRF of large neuronal populations and guarantees the finest fit for each unit analyzed.

Optimization of press bend forming path of aircraft integral panel

In order to design the press bend forming path of aircraft integral panels,a novel optimization method was proposed, which integrates FEM equivalent model based on previous study,the artificial neural network response surface,and the genetic algorithm.First,a multi-step press bend forming FEM equivalent model was established,with which the FEM experiments designed with Taguchi method were performed.Then,the BP neural network response surface was developed with the sample data from the FEM experiments.Furthermore,genetic algorithm was applied with the neural network response surface as the objective function. Finally,verification was carried out on a simple curvature grid-type stiffened panel.The forming error of the panel formed with the optimal path is only 0.098 39 and the calculating efficiency has been improved by 77%.Therefore,this novel optimization method is quite efficient and indispensable for the press bend forming path designing.

Neuroprotective effect of Cerebralcare Granule after cerebral ischemia/reperfusion injury

Cerebralcare Granule（CG） improves cerebral microcirculation and relieves vasospasm,but studies investigating its therapeutic effect on cerebral ischemia/reperfusion injury are lacking.In the present study,we administered CG（0.3,0.1 and 0.03 g/m L intragastrically） to rats for 7 consecutive days.We then performed transient occlusion of the middle cerebral artery,followed by reperfusion,and administered CG daily for a further 3 or 7 days.Compared with no treatment,high-dose CG markedly improved neurological function assessed using the Bederson and Garcia scales.At 3 days,animals in the high-dose CG group had smaller infarct volumes,greater interleukin-10 expression,and fewer interleukin-1β-immunoreactive cells than those in the untreated model group.Furthermore,at 7 days,high-dose CG-treated rats had more vascular endothelial growth factor-immunoreactive cells,elevated angiopoietin-1 and vascular endothelial growth factor expression,and improved blood coagulation and flow indices compared with untreated model animals.These results suggest that CG exerts specific neuroprotective effects against cerebral ischemia/reperfusion injury.

Anti-inflammatory properties of lipoxin A4 protect against diabetes mellitus complicated by focal cerebral ischemia/reperfusion injury

Lipoxin A4 can alleviate cerebral ischemia/reperfusion injury by reducing the inflammatory reaction,but it is currently unclear whether it has a protective effect on diabetes mellitus complicated by focal cerebral ischemia/reperfusion injury.In this study,we established rat models of diabetes mellitus using an intraperitoneal injection of streptozotocin.We then induced focal cerebral ischemia/reperfusion injury by occlusion of the middle cerebral artery for 2 hours and reperfusion for 24 hours.After administration of lipoxin A4 via the lateral ventricle,infarction volume was reduced,the expression levels of pro-inflammatory factors tumor necrosis factor alpha and nuclear factor-kappa B in the cerebral cortex were decreased,and neurological functioning was improved.These findings suggest that lipoxin A4 has strong neuroprotective effects in diabetes mellitus complicated by focal cerebral ischemia/reperfusion injury and that the underlying mechanism is related to the anti-inflammatory action of lipoxin A4.

The HMGB1 signaling pathway activates the inflammatory response in Schwann cells

Schwann cells are not only myelinating cells, but also function as immune cells and express numerous innate pattern recognition receptors, including the Toll-like receptors. Injury to peripheral nerves activates an inflammatory response in Schwann cells. However, it is unclear whether specific endogenous damage-associated molecular pattern molecules are involved in the inflammatory response following nerve injury. In the present study, we demonstrate that a key damage-associated molecular pattern molecule, high mobility group box 1（HMGB1）, is upregulated following rat sciatic nerve axotomy, and we show colocalization of the protein with Schwann cells. HMGB1 alone could not enhance expression of Toll-like receptors or the receptor for advanced glycation end products（RAGE）, but was able to facilitate migration of Schwann cells. When Schwann cells were treated with HMGB1 together with lipopolysaccharide, the expression levels of Toll-like receptors and RAGE, as well as inflammatory cytokines were upregulated. Our novel findings demonstrate that the HMGB1 pathway activates the inflammatory response in Schwann cells following peripheral nerve injury.

Design and Optimization of Press Bend Forming Path for Producing Aircraft Integral Panels with Compound Curvatures

In order to find out the optimal press bend forming path in fabricating aircraft integral panels, this article proposes a new method on the basis of the authors＇ previous work. It is composed of the finite element method （FEM） equivalent model, the surface curvature analysis, the artificial neural network response surface and the genetic algorithm. The method begins with analyzing the objective＇s shape curvature to determine the bending position. Then it optimizes the punch travel at each bending position by the following steps： （1） Establish a multi-step press bend forming FEM equivalent model, with which the FEM ex- periments designed with the Taguchi method are performed. （2） Construct a back-propagation （BP） neural network response surface with the data from the FEM experiments. （3） Use the genetic algorithm to optimize the neural network response surface as the objective function. Finally, this method is verified by press bending a complicated double-curvature grid-type stiffened panel and bears out its effectiveness and intrinsic worth in designing the press bend forming path.

Forming Path Optimization for Press Bending of Aluminum Alloy Aircraft Integral Panel

Because of the light weight,high stiffness and high structural efficiency,aluminium alloy integral panels are widely used on modern aircrafts.Press bend forming has many advantages,and it becomes a significant technique in aircraft manufacturing field.In order to design the press bend forming path for aircraft integral panels,we propose a novel optimization method which integrates the finite element method(FEM) equivalent model based on our previous study,the artificial neural network response surface,and the genetic algorithm. First,a multi-step press bend forming FEM equivalent model is established,with which the FEM experiments designed with Taguchi method are performed.Then,the backpropagation(BP) neural network response surface is developed with the sample data from the FEM experiments.Further more,genetic algorithm(GA) is applied with the neural network response surface as the objective function.Finally,experimental and simulation verifications are carried out on a single stiffener specimen.The forming error of the panel formed with the optimal path is only 5.37%and the calculating efficiency has been improved by 90.64%.Therefore,this novel optimization method is quite efficient and indispensable for the press bend forming path designing.

Strength Prediction of Aluminum–Stainless Steel-Pulsed TIG Welding–Brazing Joints with RSM and ANN

Pulsed TIG welding–brazing process was applied to join aluminum with stainless steel dissimilar metals. Major parameters that affect the joint property significantly were identified as pulsed peak current, base current, pulse on time,and frequency by pre-experiments. A sample was established according to central composite design. Based on the sample,response surface methodology（RSM） and artificial neural networks（ANN） were employed to predict the tensile strength of the joints separately. With RSM, a significant and rational mathematical model was established to predict the joint strength.With ANN, a modified back-propagation algorithm consisting of one input layer with four neurons, one hidden layer with eight neurons, and one output layer with one neuron was trained for predicting the strength. Compared with RSM, average relative prediction error of ANN was ／10% and it obtained more stable and precise results.