Dahlgaardbering5417

The last chapter summarizes the results found regarding the advantages of using such substrates as component parts in biosensing devices, with foreseen applicability in medical diagnosis and the clinical healthcare domain.Self-assembling prodrug nanotherapeutics have emerged as a promising nanoplatform for anticancer drug delivery. The specific and efficient activation of prodrug nanotherapeutics inside tumor cells is vital for the antitumor efficacy and security. Herein, a triple-activable prodrug polymer (TAP) is synthesized by conjugating polyethylene glycol-poly-(caprolactone)-paclitaxel (PTX) polymer with two tumor-responsive bonds, disulfide and acetal. TAP could self-assemble into nanotherapeutics (TAP NTs) free of surfactant with a high drug loading (32.6%). In blood circulation, TAP NTs could remain intact to efficiently accumulate in tumor sites. Thereafter, tumor cells would internalize TAP NTs through multiple endocytosis pathways. Inside tumor cells, TAP NTs could be activated to release PTX and induce tumor cell apoptosis in triple pathways (i) lysosomal acidity rapid activation; (ii) ROS-acidity tandem activation and (iii) GSH-acidity tandem activation. Compared with Taxol and non-activable control, TAP NTs significantly potentiate the antitumor efficacy and security of PTX against solid tumors including breast cancer and colon cancer.Photodynamic therapy (PDT) is a promising therapeutic strategy for tumor ablation by generating highly toxic reactive oxygen species (ROS) to damage DNA and other biomacromolecules. However, the local hypoxic microenvironment of the tumor and the presence of ROS-defensing system, such as the mobilization of mutt homolog 1 (MTH1) to sanitize ROS-oxidized nucleotide pool, severely limit the efficiency of PDT. Therefore, a novel tumor ablation strategy was developed that not only focused on the enhancement of ROS generation but also weakened the ROS-defensing system by inhibiting MTH1 enzyme activity. In our work, a simple one-step reduction approach was applied to enable platinum nanoparticles (Pt NPs) with catalase activity to grow in situ in the nanochannels of mesoporous silica nanoparticles (MSNs). After physical encapsulation of photosensitizer chlorin e6 (Ce6) and MTH1 inhibitor TH588, the drug loading nanoplatform was modified with an arginine-glycine-aspartic acid (RGD) functionalized liposome shell, resulting in the fabrication of amplified oxidative damage nanoplatform MSN-Pt@Ce6/TH588 @Liposome-RGD (MPCT@Li-R). The prepared MPCT@Li-R NPs could continuously catalyze the decomposition of hydrogen peroxide (H2O2) into oxygen (O2) in tumor, thus promoting the generation of singlet oxygen during PDT process for improved oxidative damage of bases. Simultaneously, acid responsive released TH588 hindered MTH1-mediated scavenging of oxidative bases, further aggravating DNA oxidative damage. Consequently, this cascade therapy strategy exhibited excellent tumor suppression efficiency both in vitro and in vivo.This paper reports the effects of rhamnolipids presence in the alginate hydrogel and CO32- solution, on the precipitation of CaCO3 in the Ca2+ loaded alginate hydrogel. Characteristics of the formed particles are discussed. Model conditions containing alginate hydrogel and rhamnolipids were used in order to mimic the natural environment of biomineralization in biofilms. It has been shown that rhamnolipids affect the characteristics of precipitated calcium carbonate effect of using these biosurfactants depends on their concentration as well as whether they are directly present in the hydrogel matrix or the carbonate solution surrounding the hydrogel. The greatest effect compared to the control samples was found for the rhamnolipids in the form of micelles directly present in the hydrogel with the CaCl2 cross-linked solution at concentration of 0.05 M. These conditions result in the highest increase in vaterite content, specific surface area, and pore volume. The mechanism of CaCO3 precipitation in alginate hydrogel containing rhamnolipids has been proposed.Monitoring of pesticide residues in food and environmental matrices is undoubtedly crucial to guarantee food safety and ecological health, yet how to realize their sensitive and convenient detection is still challenging. Herein, we propose an all-in-one test strip that elaborately integrates bioenzyme, nanozyme and chromogen together, and achieve the highly sensitive and convenient sensing of pesticide residues assisted by a smartphone. A sequential self-assembly strategy was first explored to acquire an integrative bioenzyme-nanozyme-chromogen assembly, and then the assembly was confined in a biocompatible hydrogel to construct the test strip. Thanks to both the proximity and confinement effects, a ∼1.2-fold improvement of the cascade catalytic efficiency was gained to benefit high-sensitivity detection. More importantly, since all the sensing elements, including target recognition units and signal amplification modules, were rationally integrated in the test strip, detection operation was significantly simplified, making it possible for in-field rapid analysis. Besides, the microenvironment provided by the alginate hydrogel carrier endowed the test strip with an excellent sensing stability. By taking paraoxon as a typical pesticide, high-performance detection of the target was accomplished via the smartphone-assisted all-in-one test strip. Moreover, the test strip was successfully applied for paraoxon detection in various real samples and exhibited good correlations with commercial kits, demonstrating its great prospect for practical applications. Our work not only offers a new tool for the high-sensitivity and convenient monitoring of pesticide residues, but will also inspire the development of efficient multi-enzyme sensing platforms.Organ-on-chip and tumor-on-chip microfluidic cell cultures represent a fast-growing research field for modelling organ functions and diseases, for drug development, and for promising applications in personalized medicine. Still, one of the bottlenecks of this technology is the analysis of the huge amount of bio-images acquired in these dynamic 3D microenvironments, a task that we propose to achieve by exploiting the interdisciplinary contributions of computer science and electronic engineering. In this work, we apply this strategy to the study of oncolytic vaccinia virus (OVV), an emerging agent in cancer immunotherapy. Infection and killing of cancer cells by OVV were recapitulated and directly imaged in tumor-on-chip. By developing and applying appropriate image analysis strategies and advanced automatic algorithms, we uncovered synergistic cooperation of OVV and immune cells to kill cancer cells. Moreover, we observed that the kinetics of immune cells were modified in presence of OVV and that these immune modulations varied during the course of infection. A correlation between cancer cell infection and cancer-immune interaction time was pointed out, strongly supporting a cause-effect relationship between infection of cancer cells and their recognition by the immune cells. These results shed new light on the mode of action of OVV, and suggest new clinical avenues for immunotherapy developments.Rapid and sensitive Escherichia coli (E. coli) detection is important in determining environmental contamination, food contamination, as well as bacterial infection. Conventional methods based on bacterial culture suffer from long testing time (24 h), whereas novel nucleic acid-based and immunolabelling approaches are hindered by complicated operation, the need of complex and costly equipment, and the lack of differentiation of live and dead bacteria. Herein, we propose a chemiluminescence digital microwell array chip based on the hydrolysis of 6-Chloro-4-methylumbelliferyl-β-D-glucuronide by the β-D-glucuronidase in E. coli to achieve fast single bacterial fluorescence detection. Taking the advantage of the picoliter microwells, single bacteria are digitally encapsulated in these microwells, thus the accurate quantification of E. coli can be realized by counting the number of positive microwells. We also show that the chemiluminescence digital microwell array chip is not affected by the turbidity of the test samples as well as the temperature. Most importantly, our method can differentiate live and dead bacteria through bacterial proliferation and enzyme expression, which is confirmed by detecting E. coli after pH and chlorination treatment. By comparing with the standard method of plate counting, our method has comparable performance but significantly reduces the testing time from over 24 h-2 h and 4 h for qualitative and quantitative analysis, respectively. In addition, the microfluidic chip is portable and easy to operate without external pump, which is promising as a rapid and on-site platform for single E. coli analysis in water and food monitoring, as well as infection diagnosis.Impaired peroxisome assembly caused by mutations in PEX genes results in a human congenital metabolic disease called Zellweger spectrum disorder (ZSD), which impacts the development and physiological function of multiple organs. In this study, we revealed a long-standing problem of heterogeneous peroxisome distribution among cell population, so called "peroxisomal mosaicism", which appears in patients with mild form of ZSD. We mutated PEX3 gene in HEK293 cells and obtained a mutant clone with peroxisomal mosaicism. We found that peroxisomal mosaicism can be reproducibly arise from a single cell, even if the cell has many or no peroxisomes. Using time-lapse imaging and a long-term culture experiment, we revealed that peroxisome biogenesis oscillates over a span of days; this was also confirmed in the patient's fibroblasts. During the oscillation, the metabolic activity of peroxisomes was maintained in the cells with many peroxisomes while depleted in the cells without peroxisomes. Our results indicate that ZSD patients with peroxisomal mosaicism have a cell population whose number and metabolic activities of peroxisomes can be recovered. This finding opens the way to develop novel treatment strategy for ZSD patients with peroxisomal mosaicism, who currently have very limited treatment options.Recently, identifying robust biomarkers or signatures from gene expression profiling data has attracted much attention in computational biomedicine. The successful discovery of biomarkers for complex diseases such as spontaneous preterm birth (SPTB) and high-grade serous ovarian cancer (HGSOC) will be beneficial to reduce the risk of preterm birth and ovarian cancer among women for early detection and intervention. Imlunestrant manufacturer In this paper, we propose a stable machine learning-recursive feature elimination (StabML-RFE for short) strategy for screening robust biomarkers from high-throughput gene expression data. We employ eight popular machine learning methods, namely AdaBoost (AB), Decision Tree (DT), Gradient Boosted Decision Trees (GBDT), Naive Bayes (NB), Neural Network (NNET), Random Forest (RF), Support Vector Machine (SVM) and XGBoost (XGB), to train on all feature genes of training data, apply recursive feature elimination (RFE) to remove the least important features sequentially, and obtain eight gene subsets with feature importance ranking.