BACKGROUND:Silk fibroin has excel ent biocompatibility, biodegradability and unique mechanical properties. Its composite, silk fibroin/nano-hydroxyapatite, can simulate the composition and structure of nature bone tissue, contributing to remedying the insufficient mechanical properties of nano-hydroxyapatites. OBJECTIVE:To observe the biological safety of silk fibroin/nano-hydroxyapatite composites. METHODS:Silk fibroin/nano-hydroxyapetite composite biomaterial was synthesized by the coprecipitation method using silk fibroin, calcium chloride and diammonium phosphate as raw materials. According to the demands of International Standard Organization (ISO10993) and Technical Evaluation Standards of Biomedical Materials and Medical Instruments promulgated by Chinese Board of Health (GB/T 16886), experiments of cel toxicity in vitro, acute toxicity and hemolysis were investigated to evaluate the biocompatibility of silk fibroin/nano-hydroxyapetite composite. RESULTS AND CONCLUSION:L929 cel s co-cultured with silk fibroin/nano-hydroxyapatite composite leaching liquor had good cel morphology, metabolism and proliferation. The leaching extract of silk fibroin/nano-hydroxyapatite composite injected into mice intraperitoneal y had no significant adverse reactions. And silk fibroin/nano-hydroxyapatite composite extracts caused 2.39%blood hemolysis, less than the international standards 5%. These experimental results on cel toxicity test in vitro, acute toxicity and hemolysis met the demands of ISO10993 and GB/T, which show the biological safety of the silk fibroin/nano-hydroxyapatite composite for clinical application.

Objective To discuss indications,operation method and clinical outcome of posterior short-segment pedicle fixation at the injured level for treatment of thoracolumbar spine fractures.Methods A total of 38 patients with thoracolumbar spine fractures were equally randomized to Group A(treated with classic short-segment pedicle screw fixation)and Group B(treated with short-segment pedicle screw fixation at the injured level)based on fixation methods(19 patients per group).Preoperative and postoperative JOA score,segmental lordosis(Cobb' s angle),R value(anterior fractured vertebral body height/mean normal vertebral body height×100%),VSA score and internal fixation condition were assessed and compared clinically.Results All patients were followed up for 6-37 months(mean 20.5 months),which showed no statistical difference upon Frankel scores of two operation modes,while the segmental lordosis,VAS score and R value in Group B were than those in Group A.There occurred nuts loosening in one patient and screw bending in one in Group A.There was no implant breakage,loosening or emersion in Group B.Conclusion Posterior short-segmental fixation at the injured level is an adequate and effective procedure for compression fractures and mild to moderate burst fractures of the thoracolumbar spine.

OBJECTIVETo detect potential mutation in a Chinese family affected with succinic semialdehyde dehydrogenase deficiency.

METHODSGenomic DNA was extracted from the peripheral blood samples of the proband, her family members and 100 healthy controls. All exons and flanking intronic regions of the ALDH5A1 gene were amplified by PCR and subjected to direct sequencing.

RESULTSThe proband was found to have compound heterozygous mutations of the ALDH5A1 gene, namely c.398_399delAA (p.N134X) and c.638G>T (p.R213L), for which her parents were both heterozygous carriers. The same mutations were not found among the 100 healthy controls.

CONCLUSIONThe novel mutations of the ALDH5A1 gene probably underlie the pathogenesis of the disease in the infant, which also enriched the mutation spectrum of the ALDH5A1 gene.

Amino Acid Metabolism, Inborn Errors ; ethnology ; genetics ; Amino Acid Sequence ; Asian Continental Ancestry Group ; genetics ; Base Sequence ; China ; DNA Mutational Analysis ; methods ; Developmental Disabilities ; ethnology ; genetics ; Exons ; genetics ; Family Health ; Female ; Heterozygote ; Humans ; Infant ; Introns ; genetics ; Male ; Mutation ; Sequence Homology, Amino Acid ; Succinate-Semialdehyde Dehydrogenase ; deficiency ; genetics

Objective:Glioblastoma(GBM)and brain metastases(BMs)are the two most common malignant brain tumors in adults.Magnetic resonance imaging(MRI)is a commonly used method for screening and evaluating the prognosis of brain tumors,but the specificity and sensitivity of conventional MRI sequences in differential diagnosis of GBM and BMs are limited.In recent years,deep neural network has shown great potential in the realization of diagnostic classification and the establishment of clinical decision support system.This study aims to apply the radiomics features extracted by deep learning techniques to explore the feasibility of accurate preoperative classification for newly diagnosed GBM and solitary brain metastases(SBMs),and to further explore the impact of multimodality data fusion on classification tasks. Methods:Standard protocol cranial MRI sequence data from 135 newly diagnosed GBM patients and 73 patients with SBMs confirmed by histopathologic or clinical diagnosis were retrospectively analyzed.First,structural T1-weight,T1C-weight,and T2-weight were selected as 3 inputs to the entire model,regions of interest(ROIs)were manually delineated on the registered three modal MR images,and multimodality radiomics features were obtained,dimensions were reduced using a random forest(RF)-based feature selection method,and the importance of each feature was further analyzed.Secondly,we used the method of contrast disentangled to find the shared features and complementary features between different modal features.Finally,the response of each sample to GBM and SBMs was predicted by fusing 2 features from different modalities. Results:The radiomics features using machine learning and the multi-modal fusion method had a good discriminatory ability for GBM and SBMs.Furthermore,compared with single-modal data,the multimodal fusion models using machine learning algorithms such as support vector machine(SVM),Logistic regression,RF,adaptive boosting(AdaBoost),and gradient boosting decision tree(GBDT)achieved significant improvements,with area under the curve(AUC)values of 0.974,0.978,0.943,0.938,and 0.947,respectively;our comparative disentangled multi-modal MR fusion method performs well,and the results of AUC,accuracy(ACC),sensitivity(SEN)and specificity(SPE)in the test set were 0.985,0.984,0.900,and 0.990,respectively.Compared with other multi-modal fusion methods,AUC,ACC,and SEN in this study all achieved the best performance.In the ablation experiment to verify the effects of each module component in this study,AUC,ACC,and SEN increased by 1.6%,10.9%and 15.0%,respectively after 3 loss functions were used simultaneously. Conclusion:A deep learning-based contrast disentangled multi-modal MR radiomics feature fusion technique helps to improve GBM and SBMs classification accuracy.