Grow and Merge: A Unified Framework for Continuous Categories Discovery

Although a number of studies are devoted to novel category discovery, most of them assume a static setting where both labeled and unlabeled data are given at once for finding new categories. In this work, we focus on the application scenarios where unlabeled data are continuously fed into the category discovery system. We refer to it as the {\bf Continuous Category Discovery} ({\bf CCD}) problem, which is significantly more challenging than the static setting. A common challenge faced by novel category discovery is that different sets of features are needed for classification and category discovery: class discriminative features are preferred for classification, while rich and diverse features are more suitable for new category mining. This challenge becomes more severe for dynamic setting as the system is asked to deliver good performance for known classes over time, and at the same time continuously discover new classes from unlabeled data. To address this challenge, we develop a framework of {\bf Grow and Merge} ({\bf GM}) that works by alternating between a growing phase and a merging phase: in the growing phase, it increases the diversity of features through a continuous self-supervised learning for effective category mining, and in the merging phase, it merges the grown model with a static one to ensure satisfying performance for known classes. Our extensive studies verify that the proposed GM framework is significantly more effective than the state-of-the-art approaches for continuous category discovery.Comment: This paper has already been accepted by 36th Conference on Neural Information Processing Systems (NeurIPS 2022

Genome-wide CRISPR/Cas9 screening for drug resistance in tumors

Genome-wide clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR associated nuclease 9 (Cas9) screening is a simple screening method for locating loci under specific conditions, and it has been utilized in tumor drug resistance research for finding potential drug resistance-associated genes. This screening strategy has significant implications for further treatment of malignancies with acquired drug resistance. In recent years, studies involving genome-wide CRISPR/Cas9 screening have gradually increased. Here we review the recent application of genome-wide CRISPR/Cas9 screening for drug resistance, involving mitogen-activated protein kinase (MAPK) pathway inhibitors, poly (ADP-ribose) polymerase inhibitors (PARPi), alkylating agents, mitotic inhibitors, antimetabolites, immune checkpoint inhibitors (ICIs), and cyclin-dependent kinase inhibitors (CDKI). We summarize drug resistance pathways such as the KEAP1/Nrf2 pathway MAPK pathway, and NF-κB pathway. Also, we analyze the limitations and conditions for the application of genome-wide CRISPR/Cas9 screening techniques

An enhanced tilted-angle acoustic tweezer for mechanical phenotyping of cancer cells

Acoustofluidic devices becomes one of the emerging and versatile tools for many biomedical applications. Most of the previous acoustofluidic devices are used for cells manipulation, and the few devices for cell phenotyping with a limitation in throughput. In this study, an enhanced tilted-angle (ETA) acoustofluidic device is developed and applied for mechanophenotyping of live cells. The ETA Device consists of an interdigital transducer which is positioned along a microfluidic channel. An inclination angle of 5° is introduced between the interdigital transducer and the liquid flow direction. The pressure nodes formed inside the acoustofluidic field in the channel deflect the biological cells from their original course in accordance with their mechanical properties, including volume, compressibility, and density. The threshold power for fully converging the cells to the pressure node is used to calculate the acoustic contrast factor. To demonstrate the ETA device in cell mechanophenotyping, and distinguishing between different cell types, further experimentation is carried out by using A549 (lung cancer cells), MDB-MA-231 (breast cancer cells), and leukocytes. The resulting acoustic contrast factors for the lung and breast cancer cells are different from that of the leukocytes by 27.9% and 21.5%, respectively. These results suggest this methodology can successfully distinguish and phenotype different cell types based on the acoustic contrast factor

Comparison of immature and mature bone marrow-derived dendritic cells by atomic force microscopy

A comparative study of immature and mature bone marrow-derived dendritic cells (BMDCs) was first performed through an atomic force microscope (AFM) to clarify differences of their nanostructure and adhesion force. AFM images revealed that the immature BMDCs treated by granulocyte macrophage-colony stimulating factor plus IL-4 mainly appeared round with smooth surface, whereas the mature BMDCs induced by lipopolysaccharide displayed an irregular shape with numerous pseudopodia or lamellapodia and ruffles on the cell membrane besides becoming larger, flatter, and longer. AFM quantitative analysis further showed that the surface roughness of the mature BMDCs greatly increased and that the adhesion force of them was fourfold more than that of the immature BMDCs. The nano-features of the mature BMDCs were supported by a high level of IL-12 produced from the mature BMDCs and high expression of MHC-II on the surface of them. These findings provide a new insight into the nanostructure of the immature and mature BMDCs

Efficient Parameter Estimation for Sparse SAR Imaging Based on Complex Image and Azimuth-Range Decouple

Sparse signal processing theory has been applied to synthetic aperture radar (SAR) imaging. In compressive sensing (CS), the sparsity is usually considered as a known parameter. However, it is unknown practically. For many functions of CS, we need to know this parameter. Therefore, the estimation of sparsity is crucial for sparse SAR imaging. The sparsity is determined by the size of regularization parameter. Several methods have been presented for automatically estimating the regularization parameter, and have been applied to sparse SAR imaging. However, these methods are deduced based on an observation matrix, which will entail huge computational and memory costs. In this paper, to enhance the computational efficiency, an efficient adaptive parameter estimation method for sparse SAR imaging is proposed. The complex image-based sparse SAR imaging method only considers the threshold operation of the complex image, which can reduce the computational costs significantly. By utilizing this feature, the parameter is pre-estimated based on a complex image. In order to estimate the sparsity accurately, adaptive parameter estimation is then processed in the raw data domain, combining with the pre-estimated parameter and azimuth-range decouple operators. The proposed method can reduce the computational complexity from a quadratic square order to a linear logarithm order, which can be used in the large-scale scene. Simulated and Gaofen-3 SAR data processing results demonstrate the validity of the proposed method

N-doped carbon dots derived from bovine serum albumin and formic acid with one- and two-photon fluorescence for live cell nuclear imaging

Carbon dots with both one- and two-photon fluorescence have drawn great attention for biomedical imaging. Herein, nitrogen-doped carbon dots were facilely developed by one-pot hydrothermal method using bovine serum albumin and formic acid as carbon sources. They are highly water-soluble with strong fluorescence when excited with ultraviolet or near infrared light. The carbon dots have a diameter of similar to 8.32 nm and can emit strong two-photon induced fluorescence upon excitation at 750 nm with a femtosecond laser. X-ray photoelectron spectrometer analysis revealed that the carbon dots contained three components, C, N and 0, corresponding to the peak at 285, 398 and 532 eV, respectively. The Fourier-transform infrared spectroscopy analysis revealed that there are carboxyl and carboxylic groups on the surface, which allowed further linking of functional molecules. pH stability study demonstrated that the carbon dots are able to be used in a wide range of pH values. The fluorescence mechanism is also discussed in this study. Importantly, these carbon dots are biocompatible and highly photostable, which can be directly applied for both one- and two-photon living cell imaging. After proper surface functionalization with TAT peptide, they can be used as fluorescent probes for live cell nuclear-targeted imaging. (C) 2015 Elsevier B.V. All rights reserved