Self-assembly of perfunctionalized Beta-cyclodextrins and chiral discrimination by quartz crystal microbalance

Ph.DDOCTOR OF PHILOSOPH

DiffusionInst: Diffusion Model for Instance Segmentation

Diffusion frameworks have achieved comparable performance with previous state-of-the-art image generation models. Researchers are curious about its variants in discriminative tasks because of its powerful noise-to-image denoising pipeline. This paper proposes DiffusionInst, a novel framework that represents instances as instance-aware filters and formulates instance segmentation as a noise-to-filter denoising process. The model is trained to reverse the noisy groundtruth without any inductive bias from RPN. During inference, it takes a randomly generated filter as input and outputs mask in one-step or multi-step denoising. Extensive experimental results on COCO and LVIS show that DiffusionInst achieves competitive performance compared to existing instance segmentation models with various backbones, such as ResNet and Swin Transformers. We hope our work could serve as a strong baseline, which could inspire designing more efficient diffusion frameworks for challenging discriminative tasks. Our code is available in https://github.com/chenhaoxing/DiffusionInst

Backpropagation Path Search On Adversarial Transferability

Deep neural networks are vulnerable to adversarial examples, dictating the imperativeness to test the model's robustness before deployment. Transfer-based attackers craft adversarial examples against surrogate models and transfer them to victim models deployed in the black-box situation. To enhance the adversarial transferability, structure-based attackers adjust the backpropagation path to avoid the attack from overfitting the surrogate model. However, existing structure-based attackers fail to explore the convolution module in CNNs and modify the backpropagation graph heuristically, leading to limited effectiveness. In this paper, we propose backPropagation pAth Search (PAS), solving the aforementioned two problems. We first propose SkipConv to adjust the backpropagation path of convolution by structural reparameterization. To overcome the drawback of heuristically designed backpropagation paths, we further construct a DAG-based search space, utilize one-step approximation for path evaluation and employ Bayesian Optimization to search for the optimal path. We conduct comprehensive experiments in a wide range of transfer settings, showing that PAS improves the attack success rate by a huge margin for both normally trained and defense models.Comment: Accepted by ICCV202

DiffUTE: Universal Text Editing Diffusion Model

Diffusion model based language-guided image editing has achieved great success recently. However, existing state-of-the-art diffusion models struggle with rendering correct text and text style during generation. To tackle this problem, we propose a universal self-supervised text editing diffusion model (DiffUTE), which aims to replace or modify words in the source image with another one while maintaining its realistic appearance. Specifically, we build our model on a diffusion model and carefully modify the network structure to enable the model for drawing multilingual characters with the help of glyph and position information. Moreover, we design a self-supervised learning framework to leverage large amounts of web data to improve the representation ability of the model. Experimental results show that our method achieves an impressive performance and enables controllable editing on in-the-wild images with high fidelity. Our code will be avaliable in \url{https://github.com/chenhaoxing/DiffUTE}

Whole exome sequencing of well-differentiated liposarcoma and dedifferentiated liposarcoma in older woman: a case report

BackgroundCommon kinds of soft tissue sarcomas (STS) include well-differentiated liposarcoma (WDLPS) and dedifferentiated liposarcoma (DDLPS). In this case, we present a comprehensive clinical profile of a patient who underwent multiple recurrences during the progression from WDLPS to DDLPS.Case presentationA 62-year-old Asian female underwent retroperitoneal resection of a large tumor 11 years ago, the initial pathology revealed a fibrolipoma-like lesion. Over the next six years, the patient underwent three resections for recurrence of abdominal tumors. Postoperative histology shows mature adipose tissue with scattered “adipoblast”-like cells with moderate-to-severe heterogeneous spindle cells, pleomorphic cells, or tumor giant cells. Immunohistochemistry (IHC) demonstrated positive staining for MDM2 and CDK4, confirming that the abdominal tumor was WDLPS and gradually progressing to DDLPS. Post-operative targeted sequencing and IHC confirmed the POC1B::ROS1 fusion gene in DDLPS. Whole-exome sequencing (WES) revealed that WDLPS and DDLPS shared similar somatic mutations and copy number variations (CNVs), whereas DDLPS had more mutated genes and a higher and more concentrated amplification of the chromosome 12q region. Furthermore, somatic mutations in DDLPS were significantly reduced after treatment with CDK4 inhibitors, while CNVs remained elevated.ConclusionDue to the high likelihood of recurrence of liposarcoma, various effective treatments should be taken into consideration even if surgery is the primary treatment for recurrent liposarcoma. To effectively control the course of the disease following surgery, combination targeted therapy may be a viable alternative to chemotherapy and radiotherapy in the treatment of liposarcoma

Targeting of Embryonic Stem Cells by Peptide-Conjugated Quantum Dots

Targeting stem cells holds great potential for studying the embryonic stem cell and development of stem cell-based regenerative medicine. Previous studies demonstrated that nanoparticles can serve as a robust platform for gene delivery, non-invasive cell imaging, and manipulation of stem cell differentiation. However specific targeting of embryonic stem cells by peptide-linked nanoparticles has not been reported.Here, we developed a method for screening peptides that specifically recognize rhesus macaque embryonic stem cells by phage display and used the peptides to facilitate quantum dot targeting of embryonic stem cells. Through a phage display screen, we found phages that displayed an APWHLSSQYSRT peptide showed high affinity and specificity to undifferentiated primate embryonic stem cells in an enzyme-linked immunoabsorbent assay. These results were subsequently confirmed by immunofluorescence microscopy. Additionally, this binding could be completed by the chemically synthesized APWHLSSQYSRT peptide, indicating that the binding capability was specific and conferred by the peptide sequence. Through the ligation of the peptide to CdSe-ZnS core-shell nanocrystals, we were able to, for the first time, target embryonic stem cells through peptide-conjugated quantum dots.These data demonstrate that our established method of screening for embryonic stem cell specific binding peptides by phage display is feasible. Moreover, the peptide-conjugated quantum dots may be applicable for embryonic stem cell study and utilization

Higher FOXP3-TSDR demethylation rates in adjacent normal tissues in patients with colon cancer were associated with worse survival

BACKGROUND: The influence of natural regulatory T cells (nTregs) on the patients with colon cancer is unclear. Demethylated status of the Treg-specific demethylated region (TSDR) of the FOXP3 gene was reported to be a potential biomarker for the identification of nTregs. METHODS: The demethylation rate of the TSDR (TSDR-DMR) was calculated by using methylation-specific quantitative polymerase chain reaction (MS-qPCR) assay. The expression of TSDR-DMR and FOXP3 mRNA was investigated in various colorectal cancer cell lines. A total of 130 colon carcinoma samples were utilized to study the DMR at tumor sites (DMR(T)) and adjacent normal tissue (DMR(N)). The correlations between DMRs and clinicopathological variables of patients with colon cancer were studied. RESULTS: The TSDR-DMRs varied dramatically among nTregs (97.920 ± 0.466%) and iTregs (3.917 ± 0.750%). Significantly, DMR(T) (3.296 ± 0.213%) was higher than DMR(N) (1.605 ± 0.146%) (n = 130, p = 0.000). Higher DMR(N) levels were found in female patients (p = 0.001) and those with distant metastases (p = 0.017), and were also associated with worse recurrence-free survival in non-stage IV patients (low vs. high, p = 0.022). However, further Cox multivariate analysis revealed that the FOXP3-TSDR status does not have prognostic value. CONCLUSION: MS-qPCR assays of FOXP3-TSDR can efficiently distinguish nTregs from non-nTregs. Abnormal recruitment of nTregs occurs in the local tumor microenvironment. Infiltration of tissue-resident nTregs may have a negative role in anti-tumor effects in patients with colon cancer; however, this role is limited and complicated