Enhancement of the SNR (signal to noise ratio) in single-molecule imaging is significantly important for improving image resolu-tion and distinguishing the fine structures of single molecules at a higher precision level.Image processing techniques have dem-onstrated the remarkable capability to improve the SNR and the resolution level by breaking through some inherent limitations unresolved by instrument hardware optimization.In this paper, we focus on single-biomolecule imaging using atomic force mi-croscopy (AFM), a unique method in separated single-biomolecule imaging, and there was few suitable image processing tech-niques reported to increase the SNR of a single molecule’s AFM image.With the typical samples of separately dispersed DNA molecules, we replaced the classified averaging method, which is usually used when the molecules’ structure can be easily and repeatedly prepared, with the time averaging method to improve the SNR in a single molecule’s AFM imaging.Combining the time averaging technique with the image alignment method for the series of time-lapse AFM images of a single DNA molecule, we were able to improve the image’s SNR and recover some buried signals from the background noises.Furthermore, the fine structures of single molecules can potentially be further resolved if other image processing techniques are applied collaboratively with some newly developed imaging methods like Vibrating Mode Scanning Polarization Force Microscopy (VSPFM), and such combination will also be advantageous for the manipulation of single-biomolecules by AFM.In addition, the proposed algorithms for the estimations of drift, distortion and SNR are applicable for quantitative status characterization of AFM imaging.
Reversible assembly and disassembly of rodlike large complex micelles have been achieved by applying photoswitching of supramolecular inclusion and exclusion of azobenzene-functionalized hyperbranched polyglycerol and acyclodextrin as driv ing force, promising a versatile system for selfassembly switched by light. Hydrogennuclear magnetic resonance （H NMR） and Fourier transform infrared （FTIR） spectroscopy were applied to characterize the azobenzenefunctionalized hyperbranched polyglycerol. Atomic force microscopy （AFM）, transmission electron microscopy （TEM） and dynamic laser light scattering （DLS） were employed to investigate and track the morphology of the rodlike large complex micelles before and after irradiation of UV light.
Among the proposed techniques for delivering drugs to specific sites within the human body, magnetic targeting drug delivery surpasses due to its non-invasive character and its high targeting efficiency. Although there have been some analyses theoretically for magnetic drug targeting, very few researchers have addressed the hydrodynamic models of magnetic fluids in the blood vessel of human body. This paper presents a mathematical model to describe the hydrodynamics of ferrofluids as drug carriers flowing in a blood vessel under the applied magnetic field. A 3D flow field of magnetic particles in a blood vessel model is numerically simulated in order to further understand clinical application of magnetic targeting drug delivery. Simulation results show that magnetic nanoparticles can be enriched in a target region depending on the applied magnetic field intensity. Magnetic resonance imaging confirms the enrichment of ferrofluids in a desired body tissue of Sprague-Dawley rats. The simulation results coincide with those animal experiments. Results of the analysis provide the important information and can suggest strategies for improving delivery in favor of the clinical application.
Biologically important proteins related to membrane receptors,signal transduction,regulation,transcription,and translation are usually low in abundance and identified with low probability in mass spectroscopy(MS)-based analyses.Most valuable proteomics information on them were hitherto discarded due to the application of excessively strict data filtering for accurate identification.In this study,we present a stagedprobability strategy for assessing proteomic data for potential functionally important protein clues.MS-based protein identifications from the second(L2)and third(L3)layers of the cascade affinity fractionation using the Trans-Proteomic Pipeline software were classified into three probability stages as 1.00–0.95,0.95–0.50,and 0.50–0.20 according to their distinctive identification correctness rates(i.e.100%–95%,95%–50%,and 50%–20%,respectively).We found large data volumes and more functionally important proteins located at the previously unacceptable lower probability stages of 0.95–0.50 and 0.50–0.20 with acceptable correctness rate.More importantly,low probability proteins in L2 were verified to exist in L3.Together with some MS spectrogram examples,comparisons of protein identifications of L2 and L3 demonstrated that the stagedprobability strategy could more adequately present both quantity and quality of proteomic information,especially for researches involving biomarker discovery and novel therapeutic target screening.
Hong XuGuijun MaQingqiao TanQiang ZhouWen SuRongxiu Li
