nanomaterials and their application in the biomedicine. [7] Indeed, over the past decades, formation of protein corona onto surfaces of NPs has attracted great attentions in the nanotechnology and biology community, and impressive progress has been achieved. [8,9] Nevertheless, a quantitative analysis on the formation process of the protein corona is very difficult and complicated, owing to the highly dynamic NP-protein interaction process and too many influencing factors.Among various types of nanomaterials, ultrasmall NPs with sizes smaller than 10 nm (i.e., quantum dots, [10] metal nanoclusters, [11] and carbon dots) [12] show unique properties and great potential in molecular imaging for disease diagnosis and cancer treatment. Particularly, compared with large NPs, these ultrasmall NPs can more readily escape from macrophages, pass biological barriers, show longer blood circulation times, and be easily degraded or excreted in the living systems. [13,14] Thus, these ultrasmall NPs have been widely employed in various biomedical applications. However, a deep and comprehensive understanding of their biological behavior, i.e., NP-protein interactions, remains largely unclear yet mainly due to the lack of appropriate in situ characterization tools for these ultrasmall NPs. While researchers have developed several techniques such as fluorescence correlation spectroscopy, [15] dynamic light scattering, [16] synchrotron radiation-based techniques, [17] and nuclear magnetic resonance spectroscopy [18] enabling quantitative analysis of protein corona, it still requires the development of new approaches to monitor the protein-NP interactions in a highly sensitive and quantitative manner owing to the diversity of nanomaterials and complexity of biological systems. [19] Fluorescence resonance energy transfer (FRET) is the process of nonradiative transmission of excitation energy from an excited state donor to a ground state acceptor, resulting from the dipole-dipole interactions. [20] The efficiency of this energy transfer process is inversely proportional to the sixth power of the distance between donor and acceptor, making FRET extremely sensitive to small changes in distance. Therefore, FRET has been widely exploited as a "spectroscopic ruler" in many biological and biophysical researches. For example, FRET can be employed for monitoring conformational changes of biomolecules, [21] developing highly sensitive fluorescence A fundamental understanding of nanoparticle-protein corona and its interactions with biological systems is essential for future application of engineered nanomaterials. In this work, fluorescence resonance energy transfer (FRET) is employed for studying the protein adsorption behavior of nanoparticles. The adsorption of human serum albumin (HSA) onto the surface of InP@ZnS quantum dots (QDs) with different chirality (dand l-penicillamine) shows strong discernible differences in the binding behaviors including affinity and adsorption orientation that are obtained upon quantitative analysis of FRET data...

Reactive oxygen species-mediated tumor chemodynamic therapy and photodynamic therapy have captured extensive attention in practical cancer combination therapies. However, the severe treatment conditions and the hypoxic microenvironment of solid tumors significantly limit the efficacy of these therapies. This work demonstrates the design and fabrication of a multifunctional persistent luminescence nanoplatform (PHFI, refers to PLNP-HSA-Fe3+-IR780) for cancer multimodal imaging and effective photoenhanced combination therapy. The near-infrared-emitted persistent luminescence nanoparticles (PLNP) was modified with human serum albumin (HSA) combined with an IR780 probe and Fe3+. The synthesized PHFI possesses high longitudinal relaxivity, obvious photoacoustic contrast signals, and long-lasting persistent luminescence, indicating that PHFI can be used for cancer magnetic resonance imaging, photoacoustic imaging, and persistent luminescence multimodal imaging. PHFI shows intrinsic photoenhanced Fenton-like catalytic activities as well as photodynamic and photothermal effects and thereby can effectively overcome severe treatment conditions for killing tumor cells. It is worth noting that PHFI serving as a rechargeable internal light source for photoenhanced combination therapy was first disclosed. We believe that our work shows the great potential of PHFI for cancer theranostics and will advance the development of PLNP-based nanoplatforms in tumor catalytic therapy.

Elucidating the biological behavior of engineered nanoparticles, for example, the protein corona, is important for the development of safe and efficient nanomedicine, but our current understanding is still limited due to its highly dynamic nature and lack of adequate analytical tools. In the present work, we demonstrate the establishment of a fluorescence resonance energy transfer (FRET)-based platform for monitoring the dynamic evolution behavior of the protein corona in complex biological media. With human serum albumin and lysozyme as the model serum proteins, the protein exchange process of the preformed corona on the surface of chiral quantum dots (QDs) upon feeding either individual protein or human serum was monitored in situ by FRET. Important parameters characterizing the evolution process of protein corona could be obtained upon quantitative analysis of FRET data. Further combining real-time FRET monitoring with gel electrophoresis experiments revealed that the nature of the protein initially adsorbed on the surface of QDs significantly affects the subsequent dynamic exchange behavior of the protein corona. Furthermore, our results also revealed that only a limited proportion of proteins are involved in the protein exchange, and the exchange process exhibits a significant dependence on the surface chirality of QDs. This work demonstrates the feasibility of FRET as a powerful tool to exploit the dynamic evolution process of the protein corona, which can provide theoretical guidance for further design of advanced nanomaterials for biomedical applications.

Ultrasensitive molecular detection and quantization are crucial for many applications including clinical diagnostics, functional proteomics, and drug discovery; however, conventional biochemical sensors cannot satisfy the stringent requirements, and this has resulted in a long-standing dilemma regarding sensitivity improvement. To this end, we have developed an ultrasensitive relay-type nanomechanical sensor based on a magneto lever. By establishing the link between very weak molecular interaction and five orders of magnitude larger magnetic force, analytes at ultratrace level can produce a clearly observable mechanical response. Initially, proof-of-concept studies showed an improved detection limit up to five orders of magnitude when employing the magneto lever, as compared with direct detection using probe alone. In this study, we subsequently demonstrated that the relay-type sensing mode was universal in application ranging from micromolecule to macromolecule detection, which can be easily extended to detect enzymes, DNA, proteins, cells, viruses, bacteria, chemicals, etc. Importantly, we found that, sensitivity was no longer subject to probe affinity when the magneto lever was sufficiently high, theoretically, even reaching single-molecule resolution.

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Under the rapid development of the economy and society, the development process of the financial sector is also accelerating now. Nowadays, a variety of financial data information is emerging, how to fully combine these big data with the financial field is the key topic of general concern in the financial field, the combination of the two can make effective use of various financial data, so as to promote the healthy and sustainable development of the entire financial field. Therefore, this paper focuses on the specific application of computer big data in the field of finance, which has practical significance.

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This paper presents the system architecture of a driverless robot car, designed to participate in the Carolo-Cup, a competition regarding automated model vehicles. We describe an implementation that completed the different tasks in this competition on our EyeBot platform in detail. EyeBot has one RGB camera as well as three infrared distance sensors, and it’s powered by Raspberry Pi 3B. We developed the lane detection algorithm using the OpenCV library and completed the traffic sign recognition task based on SVM which can be used offline. Experimental and simulation results recorded in real-time are also reported. The test result showed that our programs can run at high speed to achieve stable motion control in real time and complete all the tasks in the competition. The highlight of our work is that the whole system can run on a platform with limited computing resources.