Luminescent Quantum dots for Cellular Analysis

Luminescent quantum dots have attracted great interest in recent years among biological researchers since they provide solutions to problems associated with use of organic fluorophores in cellular studies. Quantum dots show high photostability, high emission quantum yield, narrow and symmetric emission peaks and size-dependent wavelength tunability. The objective of my PhD studies was to develop CdSe/ZnS quantum dot-based probes and utilize them in cellular assays. The first phase of the work was to develop luminescent quantum dot fluorescence resonance energy transfer (FRET) based probes for protease activity. The probes were based on FRET interactions between quantum dots that serve as donors and rhodamine molecular acceptors that were immobilized to the surface of the quantum dots through peptide linkers, which contained selective enzymatic cleavage sites. Upon enzymatic cleavage of the peptide linkers, the rhodamine molecules no longer provided an efficient energy transfer channel to the quantum dots, which brightened the previously quenched quantum dots. The probes were applied to detect enzyme activity, screen enzyme inhibitors, and discriminate between normal and cancerous cells primarily because of the difference in the proteolytic activity in extracellular matrices. The second phase of my work was to take advantage of FRET and quantum dots to develop pH sensor. First quantum dots were modified with metallothionein (MT) to be water-soluble and biocompatible. The MT-coated quantum dots were labeled with Rhodamine through the formation of amide bonds with å-amine group of lysine in MT peptide to form the probes. FRET efficiency between quantum dots (donor) and rhodamine (acceptor) was pH dependent. The final phase of my studies focused on the first preparation of reversible quantum dot-based cellular probes for labile iron. The MT coated quantum dots was modified with EDTA to form probes. When captured by the EDTA molecules, iron ions quenched the emission of quantum dots. Removal of iron from the quantum dot surface by free EDTA or other iron chelators with higher binding affinity resulted in a rise in the luminescence of quantum dots. The analytical properties of the probes including sensitivity, selectivity, and reversibility were characterized. Intracellular assays in iron-enriched astrocytes will be carried out

Transglutaminase 2 regulates terminal erythroid differentiation via cross-linking activity

Transglutaminase 2 (TGM2) is a versatile enzyme that modulates cell survival and differentiation. However, its role in terminal erythroid differentiation is poorly understood. In this study, we investigated the function of TGM2 in primary fetal liver erythroid differentiation. We predicted TGM2 as an upstream regulator via ingenuity pathway analysis (IPA), and found that its expression was increased at both RNA and protein level during terminal erythroid differentiation. TGM2 cross-linking activity inhibitors GK921 and Z-DON suppressed erythroid maturation and enucleation, while its GTPase inhibitor LDN27219 had no such effect. Z-DON treatment arrested differentiation at basophilic erythroblast stage, and interfered with cell cycle progression. RT-PCR demonstrated decreased GATA-1 and KLF1, and disarranged cyclin, CDKI and E2F family genes expression after Z-DON treatment. In conclusion, TGM2 regulates terminal erythroid differentiation through its cross-linking enzyme activity

Influence of Cr adhesion layer on detection of amyloid-derived diffusible ligands based on localized surface plasmon resonance

A Cr adhesion layer inserted between Ag nanoparticles and a glass substrate, for the purpose of improving the adhesion of Ag nanoparticles to glass, was observed to cause an abnormal peak shift of extinction spectra in non-specific reactions. The undesired peak shift misleads molecule detection in non-specific reactions. To solve this issue, a practical technique using n-propyl-trimethoxysilane-based passivation for the detection of amyloid-derived diffusible ligands was investigated as a route to eliminate the abnormal peak shifting observed in the non-specific reactions. To evaluate this passivation technique, localized surface plasmon resonance immunoassay experiments were conducted. Experimental results derived with and without the passivation process were investigated as a basis for comparative analysis. Our experimental results demonstrate that this passivation technique effectively eliminates the observed peak shift originating from the Cr adhesion layer. © 2009 Springer Science+Business Media, LLC

A Novel Approach for Effective Multi-View Clustering with Information-Theoretic Perspective

Multi-view clustering (MVC) is a popular technique for improving clustering performance using various data sources. However, existing methods primarily focus on acquiring consistent information while often neglecting the issue of redundancy across multiple views. This study presents a new approach called Sufficient Multi-View Clustering (SUMVC) that examines the multi-view clustering framework from an information-theoretic standpoint. Our proposed method consists of two parts. Firstly, we develop a simple and reliable multi-view clustering method SCMVC (simple consistent multi-view clustering) that employs variational analysis to generate consistent information. Secondly, we propose a sufficient representation lower bound to enhance consistent information and minimise unnecessary information among views. The proposed SUMVC method offers a promising solution to the problem of multi-view clustering and provides a new perspective for analyzing multi-view data. To verify the effectiveness of our model, we conducted a theoretical analysis based on the Bayes Error Rate, and experiments on multiple multi-view datasets demonstrate the superior performance of SUMVC

OpenNDD: Open Set Recognition for Neurodevelopmental Disorders Detection

Neurodevelopmental disorders (NDDs) are a highly prevalent group of disorders and represent strong clinical behavioral similarities, and that make it very challenging for accurate identification of different NDDs such as autism spectrum disorder (ASD) and attention-deficit hyperactivity disorder (ADHD). Moreover, there is no reliable physiological markers for NDDs diagnosis and it solely relies on psychological evaluation criteria. However, it is crucial to prevent misdiagnosis and underdiagnosis by intelligent assisted diagnosis, which is closely related to the follow-up corresponding treatment. In order to relieve these issues, we propose a novel open set recognition framework for NDDs screening and detection, which is the first application of open set recognition in this field. It combines auto encoder and adversarial reciprocal points open set recognition to accurately identify known classes as well as recognize classes never encountered. And considering the strong similarities between different subjects, we present a joint scaling method called MMS to distinguish unknown disorders. To validate the feasibility of our presented method, we design a reciprocal opposition experiment protocol on the hybrid datasets from Autism Brain Imaging Data Exchange I (ABIDE I) and THE ADHD-200 SAMPLE (ADHD-200) with 791 samples from four sites and the results demonstrate the superiority on various metrics. Our OpenNDD has achieved promising performance, where the accuracy is 77.38%, AUROC is 75.53% and the open set classification rate is as high as 59.43%.Comment: 10 pages, 2 figure

High-Resolution Imaging of Dendrimers Used in Drug Delivery via Scanning Probe Microscopy

Dendrimers and telodendrimer micelles represent two new classes of vehicles for drug delivery that have attracted much attention recently. Their structural characterization at the molecular and submolecular level remains a challenge due to the difficulties in reaching high resolution when imaging small particles in their native media. This investigation offers a new approach towards this challenge, using scanning tunneling microscopy (STM) and atomic force microscopy (AFM). By using new sample preparation protocols, this work demonstrates that (a) intramolecular features such as drug molecules and dendrimer termini can be resolved; and (b) telodendrimer micelles can be immobilized on the surface without compromising structural integrity, and as such, high resolution AFM imaging may be performed to attain 3D information. This high-resolution structural information should enhance our knowledge of the nanocarrier structure and nanocarrier-drug interaction and, therefore, facilitate design and optimization of the efficiency in drug delivery

Epidemiological characteristics of noise-induced hearing loss among workers in five automobile manufacturing enterprises in Zhejiang Province

BackgroundNoise is the most common occupational hazard in the automobile manufacturing industry with the most workers exposed. Automobile manufacturing industry is a high-risk industry for noise-induced hearing loss. ObjectiveTo understand the epidemiological characteristics of noise-induced hearing loss among workers in automobile manufacturing industry and explore related influencing factors. MethodsA questionnaire survey, individual noise recording, and pure tone audiometry were conducted among workers (n=656) exposed to noise from five automobile manufacturing enterprises. The data on age, sex, exposure duration, noise intensity, kurtosis, and hearing loss were obtained. The positive rates of high-frequency noise-induced hearing loss (HFNIHL) and speech-frequency noise-induced hearing loss (SFNIHL) were calculated, and each factor was compared between workers with and without HFNIHL. Chi-square test and analysis of trend were conducted among different groups of age, sex, exposure duration, A-weighted equivalent continuous sound pressure level normalized to a nominal 8-hour working day (LAeq,8h), and kurtosis. Logistic regression analysis was conducted to analyze the factors influencing the positive rates of HFNIHL and SFNIHL. ResultsThe exposure rates of non-Gaussian noise was 73.6%. The positive rates of HFNIHL and SFNIHL were 32.6% (214 workers) and 6.7% (44 workers), respectively. The HFNIHL workers showed older age, higher proportion of male, longer exposure duration, higher noise intensity (LAeq,8 h), and increased kurtosis than those without HFNIHL (P<0.05). The positive rates of HFNIHL increased with the increase of age, exposure duration, LAeq,8 h, and kurtosis (\begin{document}${\chi ^2}$\end{document}trend-age=49.25, P<0.001; \begin{document}${\chi ^2}$\end{document}trend-duration=22.19, P<0.001; \begin{document}${\chi ^2}$\end{document}trend-LAeq=6.91, P=0.009; \begin{document}${\chi ^2}$\end{document}trend-kurtosis=8.56, P=0.003). The results of logistic regression showed that age (OR=2.13, 95%CI: 1.67-2.71, P<0.001), sex (OR=2.29, 95%CI: 1.44-3.62, P<0.001), exposure duration (OR=1.43, 95%CI: 1.11-1.85, P=0.006), LAeq,8h (OR=1.37, 95%CI: 1.08~1.76, P=0.011), and kurtosis (OR=1.37, 95%CI: 1.14-1.63, P=0.001) were factors associated with the risk of HFNIHL, while only age was associated with the risk of SFNIHL (OR=2.15, 95%CI: 1.33-3.33, P=0.001). ConclusionWorkers exposed to noise in automobile manufacturing industry are at a high risk of hearing loss. Age, sex, exposure duration, LAeq,8 h, and kurtosis are key influencing factors of hearing loss

Binary interactions on the calibrations of star formation rate

Using the evolutionary population synthesis (EPS) models with and without binary interactions (BIs), we present L_Ha, L_[OII], L_{i,UV} and L_FIR for Burst, S0, Sa-Sd and Irr galaxies, and present the calibrations of star formation rate (SFR) in terms of these diagnostics. By comparison, we find that BIs lower the SFR.vs.L_Ha and SFR.vs.L_[OII] conversion factors by ~0.2 dex. Moreover, BIs do not significantly vary the calibrations of SFR in terms of L_{i,UV}. In addition, BIs have little effect on the flux at 2800A. At last, the calibration of SFR from L_FIR is almost unaffected by BIs. This is caused by the fact that BIs almost do not affect the bolometric magnitudes of SPs. We also discuss the effects of initial mass function (IMF), gas-recycle assumption (GRA) and EPS models on these SFR calibrations. Comparing the results by using Salpeter (S55) IMF with those by using Miller & Scalo (MS79) IMF, we find that the SFR.vs.L_Ha and SFR.vs.L_[OII] conversion factors by using S55 IMF are greater by 0.4 and 0.2 dex than those by using MS79 IMF for the models with and without BIs, respectively. The SFR.vs.L_{i,UV} and SFR.vs.L_FIR conversion factors by using S55 IMF are larger by an amount of 0.2 dex than the corresponding ones by using MS79 IMF. The inclusion of GRA only lowers these SFR calibrations at faint SFR. Moreover, comparing the results when using different EPS models, we find that the differences in the SFR.vs.L_Ha and SFR.vs.L_[OII] conversion factors reach ~ 0.7 and 0.9 dex, the difference in the SFR.vs.L_FIR conversion factor reaches 0.4 and 0.8 dex, and the differences in the SFR.vs.L_{i,UV} conversion factors reach 0.3 and 0.2 dex when using S55 and NON-S55 IMF (including Cha03, K01, K93' and MS79 IMFs, partly caused by the difference in the IMF), respectively. At last, we give the conversion coefficients between SFR and these diagnostics for all models.Comment: 17 pages, 21 figures, 5 tables, accepted by MNRAS; 201