Orthopedic screw parameters in the orthogonal test: Biocompatibility evaluation / 中国组织工程研究

BACKGROUND: Most current studies of orthopedic screw parameters focus on mechanical properties but lack biocompatiblllty assessment. OBJECTIVE: To Investigate the Influence of geometric parameters and material properties of orthopedic screws on blomechanical compatibility, explore the optimal combination of various factors and parameterization levels, providing a theoretical reference for the design of orthopedic screws. METHODS: An orthogonal experiment protocol was designed according to the five factors and three parameterization levels of orthopedic screws. Factor A was the screw diameter (4.5, 5.5, 6.5 mm), factor В was thread profile (rectangular, trapezoidal, triangular), factor С was screw pitch (1.75, 2.25, 2.75 mm), factor D was the thread depth (0.5,1.0,1.5 mm), and factor E was elastic modulus (45,110, 200 GPa). The blomechanical finite element analysis of the three-dimensional bone-nail model under different sets of screw parameters was carried out. Stress distribution and two experimental indicators (the stress transfer parameter STPa between the cortical bone and the screw, and the stress transfer parameter STPß between the cancellous bone and the screw) under different experimental schemes were obtained. The weighted matrix analysis method was used to analyze the orthogonal experimental data to obtain the influence law and the optimal combination. RESULTS AND CONCLUSION: Different levels of different factors have different degrees of influence on biocompatiblllty. Among them, the screw material properties are the most Important factors, followed by the thread profile, pitch and thread diameter, and the last was the thread depth. The thread profile, pitch, and thread diameter had similar influence on biocompatiblllty. The optimal combination of the orthogonal experiment was an orthopedic screw with a large diameter of 6.5 mm, a trapezoidal thread, a pitch of 2.75 mm, a thread depth of 0.5 mm, and an elastic modulus of 45 GPa.

Identification of nucleosome positioning using support vector machine method based on comprehensive DNA sequence feature / 生物医学工程学杂志

In this article, based on z-curve theory and position weight matrix (PWM), a model for nucleosome sequences was constructed. Nucleosome sequence dataset was transformed into three-dimensional coordinates, PWM of the nucleosome sequences was calculated and the similarity score was obtained. After integrating them, a nucleosome feature model based on the comprehensive DNA sequences was obtained and named CSeqFM. We calculated the Euclidean distance between nucleosome sequence candidates or linker sequences and CSeqFM model as the feature dataset, and put the feature datasets into the support vector machine (SVM) for training and testing by ten-fold cross-validation. The results showed that the sensitivity, specificity, accuracy and Matthews correlation coefficient (MCC) of identifying nucleosome positioning for were 97.1%, 96.9%, 94.2% and 0.89, respectively, and the area under the receiver operating characteristic curve (AUC) was 0.980 1. Compared with another z-curve method, it was found that our method had better identifying effect and each evaluation performance showed better superiority. CSeqFM method was applied to identify nucleosome positioning for other three species, including , and . The results showed that AUCs of the three species were all higher than 0.90, and CSeqFM method also showed better stability and effectiveness compared with iNuc-STNC and iNuc-PseKNC methods, which is further demonstrated that CSeqFM method has strong reliability and good identification performance.

Application of fuzzy comprehensive evaluation model in configuration management of medical equipment / 中国医学装备

Objective: To explore the optimal configuration methods of medical equipment of hospital so as to increase the scientific, rationality, fairness and effectiveness of decisions for equipment configuration of hospital. Methods:The applications of ultrasound imaging equipment configuration of two departments were used as example. Through a series of steps, included establishing the hierarchical structure of model, constructing the judgment matrix, consistency check, determining the weight matrix, determining the evaluation set and fuzzy evaluation matrix, and calculating the evaluation vector quantity and so on, the fuzzy comprehensive evaluation model was performed and applied in the evaluation of equipment configuration. Results: After evaluation, for the ultrasound imaging equipment configuration of department 1, the ratio of experts who thought the introduction of this equipment was very good was 82.92%, and the ratio of experts who thought it was better was 12.36%, and the ratio of experts who though it was normal was 4.72%. While for department 2, the ration of experts who though it was normal or worst was more than 50%. Conclusion:The fuzzy comprehensive evaluation model is an effective method for verifying equipment configuration. It can provide effective and quantitative assessment results for decision makers of hospital and provide reference for optimal configuration of medical equipment of hospital.

Parametric Study on Screw Layout of Internal Fixation System of Femoral Shaft Fracture Based on Orthogonal Experiment / 医用生物力学

Objective To evaluate the effects of locked plates with different screw layouts on stability of the internal fixation system for femoral shaft fracture, so as to provide guidance for clinical study on screw layout of the internal fixation system for femoral shaft fracture. Methods Orthogonal test design method was used with 4 groups of screws at 3 parametric levels. Biomechanical properties of the internal fixation system for femoral shaft fracture under 9 screw layouts were analyzed respectively by the finite element method, and 4 inspection indices, namely, the maximum equivalent stress of the plate, the screw and the femur, and the maximum axial displacement of the internal fixation system were obtained from each group of the experiment, and the orthogonal test weight matrix analysis method was conducted for data analysis. Results The influences of different screw parameters on stability of the internal fixation system varied, and the maximum weights of the 4 sets of screw parameters in stability of the internal fixation system were 13.86%, 7.57%, 7.53% and 5.91%, respectively. Conclusions The best scheme for screw layout in orthogonal test is the screw with none-fixed threaded holes in the first group, the single cortical screws with fixed threaded holes in the second group and the double cortical screws with fixed threaded holes in the third and fourth group.

Analysis of Plant TATA and TATA-less Promoters by Using Sequence and Structure Features / 生物化学与生物物理进展

Analysis of regular elements in promoter region is the base for elucidating the mechanism of gene transcription initiation.The TATA and the TATA-less promoters of plant RNA polymerase Ⅱ gene are chosen from the PlanPromDB.The GC bias,position structure conservation,nucleotide content and conservative motifs of sequences,position distribution of TATA box and conservation of correlation position are analyzed.Many specific regulars for the two types of promoters are found.These features can offer some help for revealing the transcription regulation of plant gene.A new prediction algorithm based on position-correlation weight matrix(PCWM) is proposed.The better discrimination results for two sort plant promoters are obtained by using score function.It is confirmed that the performance of position-correlation weight matrix(PCWM) is superior to single-base position weight matrix(PWM).

A genomic-scale search for regulatory binding sites in the integration host factor regulon of Escherichia coli K12

We examined general aspects of the DNA-protein interaction between the integration host factor (IHF) global regulator and its regulatory binding sites in the Escherichia coli K12 genome. Two models were developed with distinct weight matrices for the regulatory binding sites recognized by IHF. Using these matrices we performed a genome scale scan and built a set of computationally predicted binding sites for each of the models. The sites found by the model associated with repetitive sequences had a higher score in the sequence to matrix alignment. They were also more rare than the other sites. The sites not associated with repeats rapidly tended to become undistinguishable from the background as statistical stringency was relaxed. We compared our results to the known sites documented in RegulonDB and found new members of the IHF Regulon. The two models exhibit clearly distinct affinity patterns (scores in the sequence to matrix alignments and in the number of regulatory sites), as we vary the stringency of the statistical confidence parameters. We suggest that these differences may play an important role in the dynamics of the network. We concluded that IHF may regulate two genes encoding ATP-dependent RNA helicases. This interaction is not described in RegulonDB, even as a computational prediction. IHF may also regulate RNA modification processes.

A Hybrid Machine Learning Approach To the Promoter Prediction Problem / 대한의료정보학회지

With recent explosive growth of bulky biological data available, there are great needs of developing rapid autonomous algorithms in bioinformatics. In result, there has be en a great deal of attempts to apply various data mining techniques and learning algorithms to various fields of bioinformatics and a good example of this trend is the promoter and motif search area to which NN (Neural Network), HMM (Hidden Markov Model), and clustering algorithms have been applied and several good public software programs are available. Learning algorithms explore a part of big learning space effectively by their own biases. Thus, in many occasions, different learning algorithms have radically different results especially when the target concept is uncertain or stochastically defined and/or the background knowledge of the problem is limited. In this case, it is useful to apply a hybrid learning approach which two or more mutually compensative algorithms (e.g. a low false positive algorithm and a low false negative algorithm) are effectively combined. In this paper, we report a series of experiments with a hybrid learning approach in promoter prediction problem. Three available public software systems are tested and two of them (McPromoter and PROMOTER SCAN) are hierarchically combined and tested. The result shows that the hybrid learning model in this problem is quite plausible (better than any of the two base systems in accuracy and low false alarms) and many other learning algorithms could be more useful in this approach than being applied independently.