NOC: High-Quality Neural Object Cloning with 3D Lifting of Segment Anything

With the development of the neural field, reconstructing the 3D model of a target object from multi-view inputs has recently attracted increasing attention from the community. Existing methods normally learn a neural field for the whole scene, while it is still under-explored how to reconstruct a certain object indicated by users on-the-fly. Considering the Segment Anything Model (SAM) has shown effectiveness in segmenting any 2D images, in this paper, we propose Neural Object Cloning (NOC), a novel high-quality 3D object reconstruction method, which leverages the benefits of both neural field and SAM from two aspects. Firstly, to separate the target object from the scene, we propose a novel strategy to lift the multi-view 2D segmentation masks of SAM into a unified 3D variation field. The 3D variation field is then projected into 2D space and generates the new prompts for SAM. This process is iterative until convergence to separate the target object from the scene. Then, apart from 2D masks, we further lift the 2D features of the SAM encoder into a 3D SAM field in order to improve the reconstruction quality of the target object. NOC lifts the 2D masks and features of SAM into the 3D neural field for high-quality target object reconstruction. We conduct detailed experiments on several benchmark datasets to demonstrate the advantages of our method. The code will be released

speech and noise dual-stream spectrogram refine network with speech distortion loss for robust speech recognition

In recent years, the joint training of speech enhancement front-end and automatic speech recognition (ASR) back-end has been widely used to improve the robustness of ASR systems. Traditional joint training methods only use enhanced speech as input for the backend. However, it is difficult for speech enhancement systems to directly separate speech from input due to the diverse types of noise with different intensities. Furthermore, speech distortion and residual noise are often observed in enhanced speech, and the distortion of speech and noise is different. Most existing methods focus on fusing enhanced and noisy features to address this issue. In this paper, we propose a dual-stream spectrogram refine network to simultaneously refine the speech and noise and decouple the noise from the noisy input. Our proposed method can achieve better performance with a relative 8.6% CER reduction

MoWE: Mixture of Weather Experts for Multiple Adverse Weather Removal

Currently, most adverse weather removal tasks are handled independently, such as deraining, desnowing, and dehazing. However, in autonomous driving scenarios, the type, intensity, and mixing degree of the weather are unknown, so the separated task setting cannot deal with these complex conditions well. Besides, the vision applications in autonomous driving often aim at high-level tasks, but existing weather removal methods neglect the connection between performance on perceptual tasks and signal fidelity. To this end, in upstream task, we propose a novel \textbf{Mixture of Weather Experts(MoWE)} Transformer framework to handle complex weather removal in a perception-aware fashion. We design a \textbf{Weather-aware Router} to make the experts targeted more relevant to weather types while without the need for weather type labels during inference. To handle diverse weather conditions, we propose \textbf{Multi-scale Experts} to fuse information among neighbor tokens. In downstream task, we propose a \textbf{Label-free Perception-aware Metric} to measure whether the outputs of image processing models are suitable for high level perception tasks without the demand for semantic labels. We collect a syntactic dataset \textbf{MAW-Sim} towards autonomous driving scenarios to benchmark the multiple weather removal performance of existing methods. Our MoWE achieves SOTA performance in upstream task on the proposed dataset and two public datasets, i.e. All-Weather and Rain/Fog-Cityscapes, and also have better perceptual results in downstream segmentation task compared to other methods. Our codes and datasets will be released after acceptance

THE ANTI-TUMOR EFFECT AND BIOLOGICAL ACTIVITIES OF THE EXTRACT JMM6 FROM THE STEM-BARKS OF THE CHINESE JUGLANS MANDSHURICA MAXIM ON HUMAN HEPATOMA CELL LINE BEL-7402

Juglans mandshurica Maxim is a traditional herbal medicines in China, and its anti-tumor bioactivities are of research interest. Bioassay-guided fractionation method was employed to isolate anti-tumor compounds from the stem barks of the Juglans mandshurica Maxim. The anti-tumor effect and biological activities of the extracted compound JMM6 were studied in BEL-7402 cells by MTT, Cell cycle analysis, Hoechst 33342 staining, Annexin V-FITC/PI assay and Detection of mitochondrial membrane potential (△Ψm). After treatment with the JMM6, the growth of BEL-7402 cells was inhibited and cells displayed typical morphological apoptotic characteristics. Further investigations revealed that treatment with JMM6 mainly caused G2/M cell cycle arrest and induced apoptosis in BEL-7402 cells. To evaluate the alteration of mitochondria in JMM6 induced apoptosis. The data showed that JMM6 decreased significantly the △Ψm, causing the depolarization of the mitochondrial membrane. Our results show that the JMM6 will have a potential advantage of anti-tumor, less harmful to normal cells. This paper not only summarized the JMM6 pick-up technology from Juglans mandshurica Maxim and biological characteristic, but also may provide further evidence to exploit the potential medicine compounds from the stem-barks of the Chinese Juglans mandshurica Maxim

Musca domestica Cecropin (Mdc) Alleviates Salmonella typhimurium-Induced Colonic Mucosal Barrier Impairment: Associating With Inflammatory and Oxidative Stress Response, Tight Junction as Well as Intestinal Flora

Salmonella typhimurium, a Gram-negative food-borne pathogen, induces impairment in intestinal mucosal barrier function frequently. The injury is related to many factors such as inflammation, oxidative stress, tight junctions and flora changes in the host intestine. Musca domestica cecropin (Mdc), a novel antimicrobial peptide containing 40 amino acids, has potential antibacterial, anti-inflammatory, and immunological functions. It remains unclear exactly whether and how Mdc reduces colonic mucosal barrier damage caused by S. typhimurium. Twenty four 6-week-old male mice were divided into four groups: normal group, control group (S. typhimurium-challenged), Mdc group, and ceftriaxone sodium group (Cs group). HE staining and transmission electron microscopy (TEM) were performed to observe the morphology of the colon tissues. Bacterial load of S. typhimurium in colon, liver and spleen were determined by bacterial plate counting. Inflammatory factors were detected by enzyme linked immunosorbent assay (ELISA). Oxidative stress levels in the colon tissues were also analyzed. Immunofluorescence analysis, RT-PCR, and Western blot were carried out to examine the levels of tight junction and inflammatory proteins. The intestinal microbiota composition was assessed via 16s rDNA sequencing. We successfully built and evaluated an S. typhimurium-infection model in mice. Morphology and microcosmic change of the colon tissues confirmed the protective qualities of Mdc. Mdc could inhibit colonic inflammation and oxidative stress. Tight junctions were improved significantly after Mdc administration. Interestingly, Mdc ameliorated intestinal flora imbalance, which may be related to the improvement of tight junction. Our results shed a new light on protective effects and mechanism of the antimicrobial peptide Mdc on colonic mucosal barrier damage caused by S. typhimurium infection. Mdc is expected to be an important candidate for S. typhimurium infection treatment

Epigenetic control of translation checkpoint and tumor progression via RUVBL1-EEF1A1 axis

Epigenetic dysregulation is reported in multiple cancers including Ewing sarcoma (EwS). However, the epigenetic networks underlying the maintenance of oncogenic signaling and therapeutic response remain unclear. Using a series of epigenetics- and complex-focused CRISPR screens, RUVBL1, the ATPase component of NuA4 histone acetyltransferase complex, is identified to be essential for EwS tumor progression. Suppression of RUVBL1 leads to attenuated tumor growth, loss of histone H4 acetylation, and ablated MYC signaling. Mechanistically, RUVBL1 controls MYC chromatin binding and modulates the MYC-driven EEF1A1 expression and thus protein synthesis. High-density CRISPR gene body scan pinpoints the critical MYC interacting residue in RUVBL1. Finally, this study reveals the synergism between RUVBL1 suppression and pharmacological inhibition of MYC in EwS xenografts and patient-derived samples. These results indicate that the dynamic interplay between chromatin remodelers, oncogenic transcription factors, and protein translation machinery can provide novel opportunities for combination cancer therapy.</p