Transplantation of NEP1-40 and NT-3 Gene-Co-Transduced Neural Stem Cells Improves Function and Neurogenesis after Spinal Cord Injury in a Rat Model.

Background: Spinal cord injury (SCI) generally results in necrosis, scarring, cavitation, and a release of inhibitory molecules of the nervous system, which lead to disruption of neurotransmission and impede nerve fiber regeneration. This study was intended to evaluate the therapeutic efficacy rates of the transplantation of NEP1-40- and NT-3 gene-co-transduced neural stem cells (NSCs) in a rat model of SCI. Methods: Ninety Sprague-Dawley rats were subdivided randomly into six groups: sham-operated, SCI model, SCI + NSCs-NC, SCI + NEP1-40-NSCs, SCI + NT-3-NSCs, and SCI + NEP1-40/NT-3-NSCs. Motor function at different time points was evaluated using the Basso, Beattie, and Bresnahan locomotor activity scoring system (BBB). At 8 weeks post-transplantation, histological analysis, a terminal deoxynucleotidyl transferase-mediated dUTP nick-end labeling (TUNEL) assay, immunofluorescent assay, immunocytochemical staining, and cholera toxin subunit B (CTB) retrograde tracing were performed. Results: BBB scores of the co-transduction group significantly surpassed those of other transplantation groups and of the SCI-model group after 2 weeks post-transplantation. The apoptotic rate of neurocytes was significantly lower in the co-transduction group than in other experimental groups. Expression of NF-200, MBP, and ChAT was significantly higher in the SCI + NEP1-40/NT-3-NSCs group than in other transplantation groups, whereas the expression of GFAP and GAD67 was the second lowest after the sham-operated group. CTB retrograde tracing showed that CTB-positive neural fibers on the caudal side of the hemisected site were more numerous in the SCI + NEP1-40/NT-3-NSCs group than in other experimental groups. Conclusion: Transplantation of NEP1-40- and NT-3-gene-co-transduced NSCs can modify the protein expression following acute SCI and promote neuron formation and axonal regeneration, thus having a neuroprotective effect. Furthermore, this effect surpasses that of transplantation of single-gene-transduced NSCs. Transplantation of NEP1-40- and NT-3-gene-co-transduced NSCs is effective at the neural recovery of the rat model of SCI and may be a novel strategy for clinical treatment of SCI.

Clinical algorithm for preventing missed diagnoses of occult cervical spine instability after acute trauma: A case report.

BACKGROUND: Missed or delayed diagnosis of cervical spine instability after acute trauma can have catastrophic consequences for the patient, resulting in severe neurological impairment. Currently, however, there is no consensus on the optimal strategy for diagnosing occult cervical spine instability. Thus, we present a case of occult cervical spine instability and provide a clinical algorithm to aid physicians in diagnosing occult instability of the cervical spine. CASE SUMMARY: A 57-year-old man presented with cervical spine pain and inability to stand following a serious fall from a height of 2 m. No obvious vertebral fracture or dislocation was found at the time on standard lateral X-ray, computed tomography, and magnetic resonance imaging (MRI). Subsequently, the initial surgical plan was unilateral open-door laminoplasty (C3-7) with alternative levels of centerpiece mini-plate fixation (C3, 5, and 7). However, the intraoperative C-arm fluoroscopic X-rays revealed significantly increased intervertebral space at C5-6, indicating instability at this level that was previously unrecognized on preoperative imaging. We finally performed lateral mass fixation and fusion at the C5-6 level. Looking back at the preoperative images, we found that the preoperative T2 MRI showed non-obvious high signal intensity at the C5-6 intervertebral disc and posterior interspinous ligament. CONCLUSION: MRI of cervical spine trauma patients should be carefully reviewed to detect disco-ligamentous injury, which will lead to further cervical spine instability. In patients with highly suspected cervical spine instability indicated on MRI, lateral X-ray under traction or after anesthesia and muscle relaxation needs to be performed to avoid missed diagnoses of occult cervical instability.

Predictive ability of pharyngeal inlet angle for the occurrence of postoperative dysphagia after occipitocervical fusion.

BACKGROUND: PIA has been proven to be a predictor for postoperative dysphagia in patients who undergo occipitospinal fusion. However, its predictive effect for postoperative dysphagia in patients who undergo OCF is unknown. The aim of this study was to evaluate the predictive ability of the pharyngeal inlet angle (PIA) for the occurrence of postoperative dysphagia in patients who undergo occipitocervical fusion (OCF). METHODS: Between 2010 and 2018, 98 patients who had undergone OCF were enrolled and reviewed. Patients were divided into two groups according to the presence of postoperative dysphagia. Radiographic parameters, including the atlas-dens interval (ADI), O-C2 angle (O-C2a), occipital and external acoustic meatus to axis angle (O-EAa), C2 tilting angle (C2Ta), C2-7 angle (C2-7a), PIA and narrowest oropharyngeal airway space (nPAS), were measured and compared. Simple linear regression and multiple regression analysis were used to evaluate the radiographic predictors for dysphagia. In addition, we used PIA = 90° as a threshold to analyze its effect on predicting dysphagia. RESULTS: Of the 98 patients, 26 exhibited postoperative dysphagia. Preoperatively, PIA in the dysphagia group was significantly higher than that in the nondysphagia group. We detected that O-C2a, O-EAa, PIA and nPAS all decreased sharply in the dysphagia group but increased slightly in the nondysphagia group. The changes were all significant. Through regression analyses, we found that PIA had a similar predictive effect as O-EAa for postoperative dysphagia and changes in nPAS. Additionally, patients with an increasing PIA exhibited no dysphagia, and the sensitivity of PIA <90° in predicting dysphagia reached 88.5%. CONCLUSIONS: PIA could be used as a predictor for postoperative dysphagia in patients undergoing OCF. Adjusting a PIA level higher than the preoperative PIA level could avoid dysphagia. For those who inevitably had decreasing PIA, preserving intraoperative PIA over 90° would help avert postoperative dysphagia. TRIAL REGISTRATION: This trial has been registered in the Medical Ethics Committee of West China Hospital, Sichuan University. The registration number is 762 and the date of registration is Sep. 9 th, 2019.

Loss of Correction After Removal of Spinal Implants in Congenital Scoliosis.

BACKGROUND: Previous studies have reported the progression of deformity in patients with adolescent idiopathic scoliosis after implant removal. However, for patients with congenital scoliosis, few studies have investigated the prognosis after implant removal. METHODS: We observed 24 patients with congenital scoliosis, who underwent implant removal, for at least 3 years. Radiographic parameters and demographic data were compared to evaluate whether implant removal would lead to deformity progression. RESULTS: Four of the 24 patients (16.7%) suffered correction loss and underwent revision surgery (RS). All correction losses occurred within 12 months of implant removal. The average curve of fixed segments (9.84° ± 7.22° to 16.42° ± 16.79°; P = 0.017) and kyphosis of fixed segments (10.46° ± 13.42° to 18.98° ± 25.99°; P = 0.03) increased significantly throughout the follow-up. After excluding patients who underwent RS, the changes in curve of fixed segments (9.10°-11.58°) and kyphosis of fixed segments (8.50°-9.24°) were all within the measurement error. The coronal and sagittal balance maintained during the follow-up. Through comparison, we thought that the younger age and lower Risser's grade with larger scoliosis might be risk factors for correction loss. CONCLUSIONS: Implant removal after fusion surgery for congenital scoliosis may present loss of correction and require RS, thus preserving implants is recommended. When removal of instrumentation is inevitable, parents and patients should be counseled for potential loss of correction and RS, and patients should be monitored for the progression of deformity.

Predictive abilities of O-C2a and O-EAa for the development of postoperative dysphagia in patients undergoing occipitocervical fusion.

BACKGROUND CONTEXT: Dysphagia is a common postoperative complication in patients undergoing occipitocervical fusion (OCF). Previous studies had proposed the use of two measures-the occipital to C2 angle (O-C2a) and the occipital and external acoustic meatus to axis angle (O-EAa)-to predict postoperative dysphagia after OCF. However, these studies had small sample sizes and the predictive abilities of both measures are still not clear. PURPOSE: To evaluate the predictive ability of O-EAa and O-C2a for dysphagia after OCF. STUDY DESIGN: A retrospective clinical study. PATIENT SAMPLE: A total of 109 consecutive patients who had undergone OCF. OUTCOME MEASURES: Presence of postoperative dysphagia, O-C2a, C2 tilting angle (C2Ta), O-EAa, and the narrowest oropharyngeal airway space (nPAS). METHODS: Between April 2010 and June 2018, 109 consecutive patients who had undergone OCF were reviewed. Patients were divided into two groups according to the presence of postoperative dysphagia. Radiographic measurements, including O-C2a, C2Ta, O-EAa, and nPAS, were evaluated at preoperative and 1 month postoperative and the findings were compared. Simple linear regression was used to measure the correlations between the parameters and the presence of dysphagia, and the correlations within the parameters. Multiple regression analysis was used to examine the variables that affected the change of nPAS (dnPAS%). Sensitivity and specificity analyses were used to evaluate the effectiveness of the previously proposed measures ("O-C2a change≤-5°" and "postoperative O-EAa<100°") for prediction of post-OCF dysphagia. RESULTS: The incidence of dysphagia after OCF was 26.6% (29/109). Preoperative values for the radiographic parameters were similar between patients with and without dysphagia. In the dysphagia group, both O-C2a and O-EAa values showed a dramatic decrease after surgery, which was accompanied by a decrease in nPAS. Postoperative O-C2a, O-EAa, and nPAS in the dysphagia group were significantly smaller than those in the nondysphagia group (p<.05). The changes in O-EAa, O-C2a, and nPAS showed a linear correlation with the presence of dysphagia (p<.05). In addition, linear correlations were found between two of the three parameters. Multiple regression showed the change of O-C2a and O-EAa were significant predictors for dnPAS% (ß=0.200, p=.022 and ß=0.549, p=.000). The sensitivity and specificity of "O-C2a change≤-5°" in predicting dysphagia were 75.9% and 80.0% respectively, and those of "postoperative O-EAa<100°" were 75.9% and 62.5%, respectively. However, the sensitivity of the combination of these two values in predicting postoperative dysphagia was as high as 96.6%. CONCLUSION: Both O-EAa and O-C2a could be critical predictors for postoperative dysphagia. During surgery, ensuring that the O-EAa exceeds 100° and simultaneously avoiding an O-C2a reduction greater than 5° could effectively avert postoperative dysphagia.

[Biomechanical study of the stability of subaxial cervical anterior transpedicular screw fixation for three-column injury].

OBJECTIVE: To compare the stability of subaxial cervical anterior transpedicular screw(ATPS) fixation and three traditional fixations for three-column injury. METHODS: Six specimens of cervical spine were prepared. After measurememt of the range of motion(ROM) in intact state, the specimens were made into three-column injury models. The models were reconstructed with an anterior cervical cage, and stabilized by ATPS, anterior plate(AP), anterior plate + lateral mass screw(AP+LMS) and posterior transpedicular screw(PTPS). The ROM of the models in the four states were measured, and the results of data were compared after standardization. RESULTS: The normalized ROM of ATPS state in flexion-extension, lateral bending, axial rotation were(77.17±4.75)%, (82.00±2.61)%, (83.17±2.23)%, which were significant small than those in intact state(P<0.05). The normalized ROM of AP state in flexion-extension, lateral bending, axial rotation were(119.67±7.42)%, (116.33±7.53)%, (112.67±5.99)% , which were significant larger than those in intact state(P<0.05). The normalized ROM of AP in all directions were significant larger than those of ATPS(P<0.05). There was no significant difference between normalized ROM of PTPS state and those of ATPS state in flexion-extension and lateral bending(P>0.05). The normalized ROM of PTPS state in axial rotation was(6.83±2.48)% and was significant larger than that of ATPS state(P=0.009). The normalized ROM of AP+LMS state in flexion-extension was(68.50±2.43)%, which was significant smaller than that of ATPS state(P=0.003). There was no significant difference between the normalized ROM of AP+LMS state and those of ATPS state in lateral bending and axial rotation(P>0.05). CONCLUSIONS: Subaxial cervical three-column injury model reconstruction by ATPS can provide the adequate primary stability, of which biomechanics property is superior compared to AP and PTPS, and is similar to that of AP+LMS. It can be applied to the patients with no need to decompression and reduction through posterior approach.

Micro-Expression Recognition Using Color Spaces.

Micro-expressions are brief involuntary facial expressions that reveal genuine emotions and, thus, help detect lies. Because of their many promising applications, they have attracted the attention of researchers from various fields. Recent research reveals that two perceptual color spaces (CIELab and CIELuv) provide useful information for expression recognition. This paper is an extended version of our International Conference on Pattern Recognition paper, in which we propose a novel color space model, tensor independent color space (TICS), to help recognize micro-expressions. In this paper, we further show that CIELab and CIELuv are also helpful in recognizing micro-expressions, and we indicate why these three color spaces achieve better performance. A micro-expression color video clip is treated as a fourth-order tensor, i.e., a four-dimension array. The first two dimensions are the spatial information, the third is the temporal information, and the fourth is the color information. We transform the fourth dimension from RGB into TICS, in which the color components are as independent as possible. The combination of dynamic texture and independent color components achieves a higher accuracy than does that of RGB. In addition, we define a set of regions of interests (ROIs) based on the facial action coding system and calculated the dynamic texture histograms for each ROI. Experiments are conducted on two micro-expression databases, CASME and CASME 2, and the results show that the performances for TICS, CIELab, and CIELuv are better than those for RGB or gray.

A General Exponential Framework for Dimensionality Reduction.

As a general framework, Laplacian embedding, based on a pairwise similarity matrix, infers low dimensional representations from high dimensional data. However, it generally suffers from three issues: 1) algorithmic performance is sensitive to the size of neighbors; 2) the algorithm encounters the well known small sample size (SSS) problem; and 3) the algorithm de-emphasizes small distance pairs. To address these issues, here we propose exponential embedding using matrix exponential and provide a general framework for dimensionality reduction. In the framework, the matrix exponential can be roughly interpreted by the random walk over the feature similarity matrix, and thus is more robust. The positive definite property of matrix exponential deals with the SSS problem. The behavior of the decay function of exponential embedding is more significant in emphasizing small distance pairs. Under this framework, we apply matrix exponential to extend many popular Laplacian embedding algorithms, e.g., locality preserving projections, unsupervised discriminant projections, and marginal fisher analysis. Experiments conducted on the synthesized data, UCI, and the Georgia Tech face database show that the proposed new framework can well address the issues mentioned above.

Fusion tensor subspace transformation framework.

Tensor subspace transformation, a commonly used subspace transformation technique, has gained more and more popularity over the past few years because many objects in the real world can be naturally represented as multidimensional arrays, i.e. tensors. For example, a RGB facial image can be represented as a three-dimensional array (or 3rd-order tensor). The first two dimensionalities (or modes) represent the facial spatial information and the third dimensionality (or mode) represents the color space information. Each mode of the tensor may express a different semantic meaning. Thus different transformation strategies should be applied to different modes of the tensor according to their semantic meanings to obtain the best performance. To the best of our knowledge, there are no existing tensor subspace transformation algorithm which implements different transformation strategies on different modes of a tensor accordingly. In this paper, we propose a fusion tensor subspace transformation framework, a novel idea where different transformation strategies are implemented on separate modes of a tensor. Under the framework, we propose the Fusion Tensor Color Space (FTCS) model for face recognition.

Inferring gene regulatory networks by singular value decomposition and gravitation field algorithm.

Reconstruction of gene regulatory networks (GRNs) is of utmost interest and has become a challenge computational problem in system biology. However, every existing inference algorithm from gene expression profiles has its own advantages and disadvantages. In particular, the effectiveness and efficiency of every previous algorithm is not high enough. In this work, we proposed a novel inference algorithm from gene expression data based on differential equation model. In this algorithm, two methods were included for inferring GRNs. Before reconstructing GRNs, singular value decomposition method was used to decompose gene expression data, determine the algorithm solution space, and get all candidate solutions of GRNs. In these generated family of candidate solutions, gravitation field algorithm was modified to infer GRNs, used to optimize the criteria of differential equation model, and search the best network structure result. The proposed algorithm is validated on both the simulated scale-free network and real benchmark gene regulatory network in networks database. Both the Bayesian method and the traditional differential equation model were also used to infer GRNs, and the results were used to compare with the proposed algorithm in our work. And genetic algorithm and simulated annealing were also used to evaluate gravitation field algorithm. The cross-validation results confirmed the effectiveness of our algorithm, which outperforms significantly other previous algorithms.

Improved gravitation field algorithm and its application in hierarchical clustering.

BACKGROUND: Gravitation field algorithm (GFA) is a new optimization algorithm which is based on an imitation of natural phenomena. GFA can do well both for searching global minimum and multi-minima in computational biology. But GFA needs to be improved for increasing efficiency, and modified for applying to some discrete data problems in system biology. METHOD: An improved GFA called IGFA was proposed in this paper. Two parts were improved in IGFA. The first one is the rule of random division, which is a reasonable strategy and makes running time shorter. The other one is rotation factor, which can improve the accuracy of IGFA. And to apply IGFA to the hierarchical clustering, the initial part and the movement operator were modified. RESULTS: Two kinds of experiments were used to test IGFA. And IGFA was applied to hierarchical clustering. The global minimum experiment was used with IGFA, GFA, GA (genetic algorithm) and SA (simulated annealing). Multi-minima experiment was used with IGFA and GFA. The two experiments results were compared with each other and proved the efficiency of IGFA. IGFA is better than GFA both in accuracy and running time. For the hierarchical clustering, IGFA is used to optimize the smallest distance of genes pairs, and the results were compared with GA and SA, singular-linkage clustering, UPGMA. The efficiency of IGFA is proved.

Sparse tensor discriminant color space for face verification.

As one of the fundamental features, color provides useful information and plays an important role for face recognition. Generally, the choice of a color space is different for different visual tasks. How can a color space be sought for the specific face recognition problem? To address this problem, we propose a sparse tensor discriminant color space (STDCS) model that represents a color image as a third-order tensor in this paper. The model cannot only keep the underlying spatial structure of color images but also enhance robustness and give intuitionistic or semantic interpretation. STDCS transforms the eigenvalue problem to a series of regression problems. Then one spare color space transformation matrix and two sparse discriminant projection matrices are obtained by applying lasso or elastic net on the regression problems. The experiments on three color face databases, AR, Georgia Tech, and Labeled Faces in the Wild face databases, show that both the performance and the robustness of the proposed method outperform those of the state-of-the-art TDCS model.

Tensor discriminant color space for face recognition.

Recent research efforts reveal that color may provide useful information for face recognition. For different visual tasks, the choice of a color space is generally different. How can a color space be sought for the specific face recognition problem? To address this problem, this paper represents a color image as a third-order tensor and presents the tensor discriminant color space (TDCS) model. The model can keep the underlying spatial structure of color images. With the definition of n-mode between-class scatter matrices and within-class scatter matrices, TDCS constructs an iterative procedure to obtain one color space transformation matrix and two discriminant projection matrices by maximizing the ratio of these two scatter matrices. The experiments are conducted on two color face databases, AR and Georgia Tech face databases, and the results show that both the performance and the efficiency of the proposed method are better than those of the state-of-the-art color image discriminant model, which involve one color space transformation matrix and one discriminant projection matrix, specifically in a complicated face database with various pose variations.

Gravitation field algorithm and its application in gene cluster.

BACKGROUND: Searching optima is one of the most challenging tasks in clustering genes from available experimental data or given functions. SA, GA, PSO and other similar efficient global optimization methods are used by biotechnologists. All these algorithms are based on the imitation of natural phenomena. RESULTS: This paper proposes a novel searching optimization algorithm called Gravitation Field Algorithm (GFA) which is derived from the famous astronomy theory Solar Nebular Disk Model (SNDM) of planetary formation. GFA simulates the Gravitation field and outperforms GA and SA in some multimodal functions optimization problem. And GFA also can be used in the forms of unimodal functions. GFA clusters the dataset well from the Gene Expression Omnibus. CONCLUSIONS: The mathematical proof demonstrates that GFA could be convergent in the global optimum by probability 1 in three conditions for one independent variable mass functions. In addition to these results, the fundamental optimization concept in this paper is used to analyze how SA and GA affect the global search and the inherent defects in SA and GA. Some results and source code (in Matlab) are publicly available at http://ccst.jlu.edu.cn/CSBG/GFA.

Pep-3D-Search: a method for B-cell epitope prediction based on mimotope analysis.

BACKGROUND: The prediction of conformational B-cell epitopes is one of the most important goals in immunoinformatics. The solution to this problem, even if approximate, would help in designing experiments to precisely map the residues of interaction between an antigen and an antibody. Consequently, this area of research has received considerable attention from immunologists, structural biologists and computational biologists. Phage-displayed random peptide libraries are powerful tools used to obtain mimotopes that are selected by binding to a given monoclonal antibody (mAb) in a similar way to the native epitope. These mimotopes can be considered as functional epitope mimics. Mimotope analysis based methods can predict not only linear but also conformational epitopes and this has been the focus of much research in recent years. Though some algorithms based on mimotope analysis have been proposed, the precise localization of the interaction site mimicked by the mimotopes is still a challenging task. RESULTS: In this study, we propose a method for B-cell epitope prediction based on mimotope analysis called Pep-3D-Search. Given the 3D structure of an antigen and a set of mimotopes (or a motif sequence derived from the set of mimotopes), Pep-3D-Search can be used in two modes: mimotope or motif. To evaluate the performance of Pep-3D-Search to predict epitopes from a set of mimotopes, 10 epitopes defined by crystallography were compared with the predicted results from a Pep-3D-Search: the average Matthews correlation coefficient (MCC), sensitivity and precision were 0.1758, 0.3642 and 0.6948. Compared with other available prediction algorithms, Pep-3D-Search showed comparable MCC, specificity and precision, and could provide novel, rational results. To verify the capability of Pep-3D-Search to align a motif sequence to a 3D structure for predicting epitopes, 6 test cases were used. The predictive performance of Pep-3D-Search was demonstrated to be superior to that of other similar programs. Furthermore, a set of test cases with different lengths of sequences was constructed to examine Pep-3D-Search's capability in searching sequences on a 3D structure. The experimental results demonstrated the excellent search capability of Pep-3D-Search, especially when the length of the query sequence becomes longer; the iteration numbers of Pep-3D-Search to precisely localize the target paths did not obviously increase. This means that Pep-3D-Search has the potential to quickly localize the epitope regions mimicked by longer mimotopes. CONCLUSION: Our Pep-3D-Search provides a powerful approach for localizing the surface region mimicked by the mimotopes. As a publicly available tool, Pep-3D-Search can be utilized and conveniently evaluated, and it can also be used to complement other existing tools. The data sets and open source code used to obtain the results in this paper are available on-line and as supplementary material. More detailed materials may be accessed at (http://kyc.nenu.edu.cn/Pep3DSearch/).