Reconstruction of bone defects and compensation of deficient repair mechanisms represent important goals within the field of regenerative medicine and require novel safe strategies for translation into the clinic. A non-viral osteogenic gene therapeutic vector system ('hybrid vectors') was generated, combining an improved bone morphogenetic protein 2 (BMP2) gene cassette and single pro-osteogenic microRNAs (miR-148b-3p, miR-20-5p, miR-590b-5p), driven by the U6 promoter. The vectors were tested in vitro for their osteogenic differentiation potential in C2C12 and C3H/10T1/2 cell lines, using BMP2 alone as control. After confirming BMP2 expression and miRNA transcription, increased osteogenic differentiation was observed by all hybrid vectors, but most consistently by BMP2/miR-590-5p, using alkaline phosphatase enzyme activity assays and osteogenic marker mRNA quantitation, including runt-related transcription factor 2 (Runx2), collagen type 1 (Col1a1) and osteocalcin. To visualise target mRNAs of the respective miRNAs, next generation sequencing was performed, confirming down-regulation of mRNA targets of the hybrid vectors. Since the hybrid vector consisting of BMP2 and miR-590-5p showed the largest increase in osteogenic differentiation in vitro, this was tested in a mouse ectopic-bone model. Mineralisation was more than with BMP2 alone. The present study showed hybrid vectors as a novel non-viral gene therapeutic plasmid system for combining therapeutic effects of recombinant protein expression and miRNA transcription that did not add to the burden of the translation machinery, while improving the therapeutic efficacies. In vivo proof-of-principle in the context of bone regeneration suggested that such hybrid vectors will be applicable in a wide array of gene therapeutic strategies.
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http://dx.doi.org/10.22203/eCM.v041a18 | DOI Listing |
Food Res Int
February 2025
State Key Laboratory of Food Science and Resources, Jiangnan University, Wuxi, Jiangsu Province, China; School of Food Science and Technology, Jiangnan University University, Wuxi, Jiangsu Province, China; Collaborative Innovation Center of Food Safety and Quality Control in Jiangsu Province, Jiangnan University, China. Electronic address:
The aim of this study was to explore application of visible and near-infrared (Vis/NIR) spectroscopy combined with machine learning models for SSC and TA prediction of hybrid citrus. The Vis/NIR spectra of samples including navel-region, equator-region and multi-region combination spectra in navel-region and equator-region were collected using a benchtop equipment. The performance of SSC and TA prediction models with different region spectra, including partial least squares (PLS), random forest (RF), k-nearest neighbors (KNN), support vector machine (SVM) and multilayer feedforward neural network (MFNN), was assessed.
View Article and Find Full Text PDFJ Phys Chem A
January 2025
Department of Physics, Chemistry and Pharmacy, University of Southern Denmark, Campusvej 55, Odense M DK-5230, Denmark.
Quantum computing presents a promising avenue for solving complex problems, particularly in quantum chemistry, where it could accelerate the computation of molecular properties and excited states. This work focuses on computing excitation energies with hybrid quantum-classical algorithms for near-term quantum devices, combining the quantum linear response (qLR) method with a polarizable embedding (PE) environment. We employ the self-consistent operator manifold of quantum linear response (q-sc-LR) on top of a unitary coupled cluster (UCC) wave function in combination with a Davidson solver.
View Article and Find Full Text PDFThe coastline reflects coastal environmental processes and dynamic changes, serving as a fundamental parameter for coast. Although several global coastline datasets have been developed, they mainly focus on coastal morphology, the typology of coastlines are still lacking. We produced a Global CoastLine Dataset (GCL_FCS30) with a detailed classification system.
View Article and Find Full Text PDFAnalyst
January 2025
Department of Chemistry, University of Victoria, Victoria, British Columbia, V8W 3V6, Canada.
Infrared absorption spectroscopy and surface-enhanced Raman spectroscopy were integrated into three data fusion strategies-hybrid (concatenated spectra), mid-level (extracted features from both datasets) and high-level (fusion of predictions from both models)-to enhance the predictive accuracy for xylazine detection in illicit opioid samples. Three chemometric approaches-random forest, support vector machine, and -nearest neighbor algorithms-were employed and optimized using a 5-fold cross-validation grid search for all fusion strategies. Validation results identified the random forest classifier as the optimal model for all fusion strategies, achieving high sensitivity (88% for hybrid, 92% for mid-level, and 96% for high-level) and specificity (88% for hybrid, mid-level, and high-level).
View Article and Find Full Text PDFEur Heart J
January 2025
School of Chemical Biology and Biotechnology, Peking University Shenzhen Graduate School, Shenzhen, 2199 Lishui Rd, Nanshan, Shenzhen, Guangdong Province 518055, China.
Background And Aims: Lackluster results from recently completed gene therapy clinical trials of VEGF-A delivered by viral vectors have heightened the need to develop alternative delivery strategies. This study aims to demonstrate the pre-clinical efficacy and safety of extracellular vesicles (EVs) loaded with VEGF-A mRNA for the treatment of ischaemic vascular disease.
Methods: After encapsulation of full-length VEGF-A mRNA into fibroblast-derived EVs via cellular nanoporation (CNP), collected VEGF-A EVs were delivered into mouse models of ischaemic injury.
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