Evaluation of BMP-2 Minicircle DNA for Enhanced Bone Engineering and Regeneration

Application of BMP-2 and its gene delivery vehicles in dentistry

The restoration of bone defects resulting from tooth loss, periodontal disease, severe trauma, tumour resection and congenital malformations is a crucial task in dentistry and maxillofacial surgery. Growth factor- and gene-activated bone graft substitutes can be used instead of traditional materials to solve these problems. New materials will overcome the low efficacy and difficulties associated with the use of traditional bone substitutes in complex situations. One of the most well-studied active components for bone graft substitutes is bone morphogenetic protein-2 (BMP-2), which has strong osteoinductive properties. The aim of this review was to examine the use of BMP-2 protein and gene therapy for bone regeneration in the oral and maxillofacial region and to discuss its future use.

Bioinformatics analysis methods for cell-free DNA

As a kind of novel non-invasive marker for molecular detection, cell-free DNA (cfDNA) has potential value for the early diagnosis of diseases, prognosis assessment, and efficacy monitoring. The constant developments in molecular biology detection technologies have led to an increase in clinical studies on the use of cfDNA detection methods for patients, and many gratifying outcomes have been achieved. In this review, the contributions of bioinformatics tools to the study of cfDNA are well discussed. The focus of the review is on cfDNA identification signals, cfDNA identification methods, and the relationship of cfDNA with human diseases such as hepatic cancer, lung cancer, end-stage kidney disease, and ischemic stroke. The research significance and existing problems of using cfDNA as a biomarker for diseases are also discussed.

HKAM-MKM: A hybrid kernel alignment maximization-based multiple kernel model for identifying DNA-binding proteins

The identification of DNA-binding proteins (DBPs) has always been a hot issue in the field of sequence classification. However, considering that the experimental identification method is very resource-intensive, the construction of a computational prediction model is worthwhile. This study developed and evaluated a hybrid kernel alignment maximization-based multiple kernel model (HKAM-MKM) for predicting DBPs. First, we collected two datasets and performed feature extraction on the sequences to obtain six feature groups, and then constructed the corresponding kernels. To ensure the effective utilisation of the base kernel and avoid ignoring the difference between the sample and its neighbours, we proposed local kernel alignment to calculate the kernel between the sample and its neighbours, with each sample as the centre. We combined the global and local kernel alignments to develop a hybrid kernel alignment model, and balance the relationship between the two through parameters. By maximising the hybrid kernel alignment value, we obtained the weight of each kernel and then linearly combined the kernels in the form of weights. Finally, the fused kernel was input into a support vector machine for training and prediction. Finally, in the independent test sets PDB186 and PDB2272, we obtained the highest Matthew's correlation coefficient (MCC) (0.768 and 0.5962, respectively) and the highest accuracy (87.1% and 78.43%, respectively), which were superior to the other predictors. Therefore, HKAM-MKM is an efficient prediction tool for DBPs.

Comparison of promoter, DNA vector, and cationic carrier for efficient transfection of hMSCs from multiple donors and tissue sources

Human mesenchymal stem cells (hMSCs) are primary cells with high clinical relevance that could be enhanced through genetic modification. However, gene delivery, particularly through nonviral routes, is inefficient. To address the shortcomings of nonviral gene delivery to hMSCs, our lab has previously demonstrated that pharmacological "priming" of hMSCs with clinically approved drugs can increase transfection in hMSCs by modulating transfection-induced cytotoxicity. However, even with priming, hMSC transfection remains inefficient for clinical applications. This work takes a complementary approach to addressing the challenges of transfecting hMSCs by systematically investigating key transfection parameters for their effect on transgene expression. Specifically, we investigated two promoters (cytomegalovirus [CMV] and elongation factor 1 alpha), four DNA vectors (plasmid, plasmid with no F1 origin, minicircle, and mini-intronic plasmid), two cationic carriers (Lipofectamine 3000 and Turbofect), and four donors of hMSCs from two tissues (adipose and bone marrow) for efficient hMSC transfection. Following systematic comparison of each variable, we identified adipose-derived hMSCs transfected with mini-intronic plasmids containing the CMV promoter delivered using Lipofectamine 3000 as the parameters that produced the highest transfection levels. The data presented in this work can guide the development of other hMSC transfection systems with the goal of producing clinically relevant, genetically modified hMSCs.