RAPID CONSTRUCTION OF PET PROBES VIA TETRAZINE LIGATION

Positron emission tomography (PET) is a non-invasive imaging modality that is widely used to observe metabolic process in vivo by tracking the interactions between PET probes and biomarkers. Facilitated by the recent development in the instrumentation and synthetic chemistry, clinical application of PET has been proven to be vital in theranostic uses. It possesses the advantages of high sensitivity, quantitative images, and great tissue penetration capability, all of which make it one of the most powerful molecular imaging techniques currently available in clinical use. In order to visualize biochemical processes in vivo, corresponding PET probes are needed which could be synthesized based on PET radionuclides and biomolecules such as antibodies, proteins and peptides. 18F is the most broadly used radionuclides in PET due to the high positron enrichment, high specific activity and clinically attractive half-life (~110min). However, the low concentration of 18F and low reactivity make it challenging to be incorporated into biomolecules. This becomes more problematic when biomolecules become larger. It is also difficult to separate labeled large biomolecules (such as proteins) from unlabeled ones. As a result, the presence of unlabeled compound could saturate targeted receptors causing blocking effect in PET imaging. Therefore, the goal of this dissertation is to develop a highly efficient method for rapid construction of PET probes, especially large biomolecule based PET probes. To achieve this goal, we hypothesize that a radiolabeling method based on the biorthogonal tetrazine-trans-cyclooctene (TTCO) ligation can enable fast reaction at submicromolar concentration, which will allow efficient construction of PET agents in high specific activity. In brief, biomolecules were modified with different tetrazine derivatives while the trans-cyclooctene (TCO) derivatives were radiolabeled with PET imaging radioisotopes such as 18F or 64Cu. The fast reaction rate between tetrazines and TCOs allowed us to form radio labeled biomolecules in seconds at low concentrations. The labeling strategy was applied to peptides and proteins to construct novel PET probes. The prepared PET probes showed uncompromised binding affinity and good targeting property and pharmacokinetics in PET imaging studies. We also explored the pre-targeting concept and showed the potential of using radiolabeled TTCO ligation for in vivo reaction.Doctor of Philosoph

Neural labeling and manipulation by neonatal intraventricular viral injection in mice

This step-by-step protocol provides a fast and easy technique to label and/or genetically manipulate neural cells, achieved by intraventricular injection of viral vectors into neonatal mice under ultrasound guidance. Successful injection of ad-eno-associated viral vectors (AAV) induces neural transduction as fast as 3 days post injection (dpi) in both the central and peripheral nervous systems. Virally driven expression persists until early adulthood. The same setup enables injec-tion of other viral vectors as well as intramuscular injection. For complete details on the use and execution of this protocol, please refer to Wang et al. (2021) and Brill et al. (2016)

Research on VIKOR group decision making using WOWA operator based on interval Pythagorean triangular fuzzy numbers

A new decision-making method based on interval Pythagorean triangular fuzzy numbers is proposed for fuzzy information decision-making problems, taking the advantages of interval Pythagorean fuzzy numbers and triangular fuzzy numbers into account. The VIse Kriterijumski Optimizacioni Racun (VIKOR) group decision-making method is based on the Weighted Ordered Weighted Average (WOWA) operator of interval Pythagorean triangular fuzzy numbers (IVPTFWOWA). First, this article provides the definition of the IVPTFWOWA operator and proves its degeneracy, idempotence, monotonicity, and boundedness. Second, the decision steps of the VIKOR decision method using the IVPTFWOWA operator are presented. Finally, the scientificity and effectiveness of the proposed method were verified through case studies and comparative discussions. The research results indicate that the following: (1) the IVPTFWOWA operator combines interval Pythagorean fuzzy numbers and triangular fuzzy numbers, complementing the shortcomings of the two fuzzy numbers, and can characterize fuzzy information on continuous geometry, thereby reducing decision errors caused by inaccurate and fuzzy information; (2) the VIKOR decision-making method based on the IVPTFWOWA operator applies comprehensive weights, fully considering the positional weights of the scheme attributes and the weights of raters, and fully utilizing the attribute features of decision-makers and cases; and (3) compared to other methods, there is a significant gap between the decision results obtained using this method, making it easier to identify the optimal solution

Hyper-parameter Adaptation of Conformer ASR Systems for Elderly and Dysarthric Speech Recognition

Automatic recognition of disordered and elderly speech remains highly challenging tasks to date due to data scarcity. Parameter fine-tuning is often used to exploit the large quantities of non-aged and healthy speech pre-trained models, while neural architecture hyper-parameters are set using expert knowledge and remain unchanged. This paper investigates hyper-parameter adaptation for Conformer ASR systems that are pre-trained on the Librispeech corpus before being domain adapted to the DementiaBank elderly and UASpeech dysarthric speech datasets. Experimental results suggest that hyper-parameter adaptation produced word error rate (WER) reductions of 0.45% and 0.67% over parameter-only fine-tuning on DBank and UASpeech tasks respectively. An intuitive correlation is found between the performance improvements by hyper-parameter domain adaptation and the relative utterance length ratio between the source and target domain data.Comment: 5 pages, 3 figures, 3 tables, accepted by Interspeech202

Synthesis and Evaluation of 64 Cu-DOTA-NT-Cy5.5 as a Dual-Modality PET/Fluorescence Probe to Image Neurotensin Receptor-Positive Tumor

Overexpression of neurotensin receptors (NTRs) has been suggested to play important roles in the growth and survival of a variety of tumor types. The aim of this study is to develop a dual-modality probe (64Cu -DOTA-NT-Cy5.5) for imaging NTR1 expression in vivo with both positron emission tomography (PET) and fluorescence. In this approach, the thiol group and N terminal amino group of neurotensin analogue (Cys-NT) were chemically modified with Cy5.5 dye and DOTA chelator, respectively. After radiolabeling with 64Cu, the resulting probe (64Cu-DOTA-NT-Cy5.5) was evaluated in NTR1 positive HT-29 tumor model. Small animal PET quantification analysis demonstrated that the tumor uptake was 1.91 ± 0.22 and 1.79 ± 0.16%ID/g at 1 and 4 h postinjection (p.i.), respectively. The tumor-to-muscle ratio was 17.44 ± 3.25 at 4 h p.i. based on biodistribution. Receptor specificity was confirmed by the successful blocking experiment at 4 h p.i. (0.42 ± 0.05%ID/g). In parallel with PET experiment, fluorescence imaging was also performed, which demonstrated prominent tumor uptake in HT-29 model. As a proof of concept, an imaging guided surgery was performed to the fluorescent moiety of this probe and could provide potential surgery guidance for NTR positive patients. In summary, our results clearly indicated that the dual-modality probe, 64Cu-DOTA-NT-Cy5.5, could serve as a promising agent to image NTR positive tumors in vivo

Adversarial Data Augmentation Using VAE-GAN for Disordered Speech Recognition

Automatic recognition of disordered speech remains a highly challenging task to date. The underlying neuro-motor conditions, often compounded with co-occurring physical disabilities, lead to the difficulty in collecting large quantities of impaired speech required for ASR system development. This paper presents novel variational auto-encoder generative adversarial network (VAE-GAN) based personalized disordered speech augmentation approaches that simultaneously learn to encode, generate and discriminate synthesized impaired speech. Separate latent features are derived to learn dysarthric speech characteristics and phoneme context representations. Self-supervised pre-trained Wav2vec 2.0 embedding features are also incorporated. Experiments conducted on the UASpeech corpus suggest the proposed adversarial data augmentation approach consistently outperformed the baseline speed perturbation and non-VAE GAN augmentation methods with trained hybrid TDNN and End-to-end Conformer systems. After LHUC speaker adaptation, the best system using VAE-GAN based augmentation produced an overall WER of 27.78% on the UASpeech test set of 16 dysarthric speakers, and the lowest published WER of 57.31% on the subset of speakers with "Very Low" intelligibility.Comment: Submitted to ICASSP 202

Rapid and Simple Detection of Viable Foodborne Pathogen Staphylococcus aureus

Staphylococcus aureus (S. aureus) contamination in food safety has become a worldwide health problem. In this work, we utilized RNA one-step detection of denaturation bubble-mediated Strand Exchange Amplification (SEA) method to realize the detection of viable foodborne pathogen S. aureus. A pair of S. aureus specific primers were designed for the SEA reaction by targeting hypervariable V2 region of 16S rDNA and the amplification reaction was finished about 1 h. The results of amplification reaction could be observed by the naked eyes with a significant color change from light yellow to red to realize the colorimetric detection of S. aureus. Therefore, there only required an isothermal water bath, which was very popular for areas with limited resources. In real sample testing, although the SEA detection was so time-saving compared with the traditional plating method, the SEA method showed great consistency with the traditional plating method. In view of the above-described advantages, we provided a simple, rapid and equipment-free detection method, which had a great potential on ponit-of-care testing (POCT) application. Our method reported here will also provide a POCT detection platform for other food-borne pathogens in food, even pathogenic bacteria from other fields