NeuDA: Neural Deformable Anchor for High-Fidelity Implicit Surface Reconstruction

This paper studies implicit surface reconstruction leveraging differentiable ray casting. Previous works such as IDR and NeuS overlook the spatial context in 3D space when predicting and rendering the surface, thereby may fail to capture sharp local topologies such as small holes and structures. To mitigate the limitation, we propose a flexible neural implicit representation leveraging hierarchical voxel grids, namely Neural Deformable Anchor (NeuDA), for high-fidelity surface reconstruction. NeuDA maintains the hierarchical anchor grids where each vertex stores a 3D position (or anchor) instead of the direct embedding (or feature). We optimize the anchor grids such that different local geometry structures can be adaptively encoded. Besides, we dig into the frequency encoding strategies and introduce a simple hierarchical positional encoding method for the hierarchical anchor structure to flexibly exploit the properties of high-frequency and low-frequency geometry and appearance. Experiments on both the DTU and BlendedMVS datasets demonstrate that NeuDA can produce promising mesh surfaces.Comment: Accepted to CVPR 2023, project page: https://3d-front-future.github.io/neud

Seeing What You Miss: Vision-Language Pre-training with Semantic Completion Learning

Cross-modal alignment is essential for vision-language pre-training (VLP) models to learn the correct corresponding information across different modalities. For this purpose, inspired by the success of masked language modeling (MLM) tasks in the NLP pre-training area, numerous masked modeling tasks have been proposed for VLP to further promote cross-modal interactions. The core idea of previous masked modeling tasks is to focus on reconstructing the masked tokens based on visible context for learning local-to-local alignment. However, most of them pay little attention to the global semantic features generated for the masked data, resulting in the limited cross-modal alignment ability of global representations. Therefore, in this paper, we propose a novel Semantic Completion Learning (SCL) task, complementary to existing masked modeling tasks, to facilitate global-to-local alignment. Specifically, the SCL task complements the missing semantics of masked data by capturing the corresponding information from the other modality, promoting learning more representative global features which have a great impact on the performance of downstream tasks. Moreover, we present a flexible vision encoder, which enables our model to perform image-text and video-text multimodal tasks simultaneously. Experimental results show that our proposed method obtains state-of-the-art performance on various vision-language benchmarks, such as visual question answering, image-text retrieval, and video-text retrieval

Effect of Biodentine on Odonto/Osteogenic Differentiation of Human Dental Pulp Stem Cells

This study aims to compare the biological characteristics of human dental pulp stem cells (hDPSCs) isolated from different-aged populations and examine the effects of Biodentine on proliferation and odonto/osteogenic differentiation of hDPSCs isolated from the elderly in vitro. hDPSCs were isolated from three different-aged populations: group A (≤18 years old), group B (19–59 years old), and group C (≥60 years old). The adhesion, proliferation, odonto/osteogenesis, and senescence were compared. The optimal concentration of aqueous Biodentine extract was determined by CCK-8 assay, alkaline phosphatase (ALP), and alizarin red staining (ARS). The effect of Biodentine on odonto/osteogenic gene and protein expression of hDPSCs in each group was evaluated by quantitative real-time PCR (QRT-PCR) and Western blot. hDPSCs were successfully isolated from three different-aged populations. Flow cytometry revealed that all isolated hDPSCs were positive for CD73 (>90%), CD90 (>90%), CD146 (p p < 0.05). hDPSCs can be obtained from populations of all ages. Though there is an age-related decline in their biological properties, hDPSCs from the elderly still maintain certain proliferation and multidirectional differentiation abilities. Biodentine can significantly promote the proliferation and odonto/osteogenic differentiation of hDPSCs isolated from the elderly over 60 years old, which could be considered a pulp capping material for vital pulp therapy in the elderly. Nevertheless, the efficacy of Biodentine in clinical application has to be further studied

Effect of the Biofilm Age and Starvation on Acid Tolerance of Biofilm Formed by Streptococcus mutans Isolated from Caries-Active and Caries-Free Adults

Streptococcus mutans (S. mutans) is considered a leading cause of dental caries. The capability of S. mutans to tolerate low pH is essential for its cariogenicity. Aciduricity of S. mutans is linked to its adaptation to environmental stress in oral cavity. This study aimed to investigate the effect of biofilm age and starvation condition on acid tolerance of biofilm formed by S. mutans clinical isolates. S. mutans clinical strains isolated from caries-active (SM593) and caries-free (SM18) adults and a reference strain (ATCC25175) were used for biofilm formation. (1) Both young and mature biofilms were formed and then exposed to pH 3.0 for 30 min with (acid-adapted group) or without (non-adapted group) pre-exposure to pH 5.5 for three hours. (2) The mature biofilms were cultured with phosphate-buffered saline (PBS) (starved group) or TPY (polypeptone-yeast extract) medium (non-starved group) at pH 7.0 for 24 h and then immersed in medium of pH 3.0 for 30 min. Biofilms were analyzed through viability staining and confocal laser scanning microscopy. In all three strains, mature, acid-adapted and starved biofilms showed significantly less destructive structure and more viable bacteria after acid shock than young, non-adapted and non-starved biofilms, respectively (all p &lt; 0.05). Furthermore, in each condition, SM593 biofilm was denser, with a significantly larger number of viable bacteria than that of SM18 and ATCC25175 (all p &lt; 0.05). Findings demonstrated that mature, acid-adapted and starvation might protect biofilms of all three S. mutans strains against acid shock. Additionally, SM593 exhibited greater aciduricity compared to SM18 and ATCC25175, which indicated that the colonization of high cariogenicity of clinical strains may lead to high caries risk in individuals

The Immunotherapy and Immunosuppressive Signaling in Therapy-Resistant Prostate Cancer.

Prostate cancer is one of the most common malignant tumors in men. Initially, it is androgen-dependent, but it eventually develops into castration-resistant prostate cancer (CRPC), which is incurable with current androgen receptor signaling target therapy and chemotherapy. Immunotherapy, specifically with immune checkpoint inhibitors, has brought hope for the treatment of this type of prostate cancer. Approaches such as vaccines, adoptive chimeric antigen receptor-T (CAR-T) cells, and immune checkpoint inhibitors have been employed to activate innate and adaptive immune responses to treat prostate cancer, but with limited success. Only Sipuleucel-T and the immune checkpoint inhibitor pembrolizumab are approved by the US FDA for the treatment of limited prostate cancer patients. Prostate cancer has a complex tumor microenvironment (TME) in which various immunosuppressive molecules and mechanisms coexist and interact. Additionally, prostate cancer is considered a "cold" tumor with low levels of tumor mutational burden, low amounts of antigen-presenting and cytotoxic T-cell activation, and high levels of immunosuppressive molecules including cytokines/chemokines. Thus, understanding the mechanisms of immunosuppressive signaling activation and immune evasion will help develop more effective treatments for prostate cancer. The purpose of this review is to summarize emerging advances in prostate cancer immunotherapy, with a particular focus on the molecular mechanisms that lead to immune evasion in prostate cancer. At the same time, we also highlight some potential therapeutic targets to provide a theoretical basis for the treatment of prostate cancer

HunYuan_tvr for Text-Video Retrieval

Text-Video Retrieval plays an important role in multi-modal understanding and has attracted increasing attention in recent years. Most existing methods focus on constructing contrastive pairs between whole videos and complete caption sentences, while ignoring fine-grained cross-modal relationships, e.g., short clips and phrases or single frame and word. In this paper, we propose a novel method, named HunYuan\_tvr, to explore hierarchical cross-modal interactions by simultaneously exploring video-sentence, clip-phrase, and frame-word relationships. Considering intrinsic semantic relations between frames, HunYuan\_tvr first performs self-attention to explore frame-wise correlations and adaptively clusters correlated frames into clip-level representations. Then, the clip-wise correlation is explored to aggregate clip representations into a compact one to describe the video globally. In this way, we can construct hierarchical video representations for frame-clip-video granularities, and also explore word-wise correlations to form word-phrase-sentence embeddings for the text modality. Finally, hierarchical contrastive learning is designed to explore cross-modal relationships,~\emph{i.e.,} frame-word, clip-phrase, and video-sentence, which enables HunYuan\_tvr to achieve a comprehensive multi-modal understanding. Further boosted by adaptive label denoising and marginal sample enhancement, HunYuan\_tvr obtains new state-of-the-art results on various benchmarks, e.g., Rank@1 of 55.0%, 57.8%, 29.7%, 52.1%, and 57.3% on MSR-VTT, MSVD, LSMDC, DiDemo, and ActivityNet respectively

Prognostic Value of Cancer Stem Cell Marker Aldehyde Dehydrogenase in Ovarian Cancer: A Meta-Analysis

<div><p>Objective</p><p>Aldehyde dehydrogenase (ALDH) has recently been reported as a marker of cancer stem-like cells in ovarian cancer. However, the prognostic role of ALDH in ovarian cancer still remains controversial. In this study, we aimed to evaluate the association between the expression of ALDH and the outcome of ovarian cancer patients by performing a meta-analysis.</p> <p>Methods</p><p>We systematically searched for studies investigating the relationships between ALDH expression and outcome of ovarian cancer patients. Only articles in which ALDH expression was detected by immunohistochemical staining were included. A meta-analysis was performed to generate combined hazard ratios (HRs) with 95% confidence intervals (CIs) for overall survival (OS) and disease-free survival (DFS).</p> <p>Results</p><p>A total of 1,258 patients from 7 studies (6 articles) were included in the analysis. Our results showed that high ALDH expression in patients with ovarian cancer was associated with poor prognosis in terms of Os (HR, 1.25; 95% CI, 1.07-1.47; P = 0.005) and DFS (HR, 1.58; 95% CI, 1.00-2.49; P = 0.052), though the difference for DFS was not statistically significant. In addition, there was no evidence of publication bias as suggested by Begg’s and Egger’s tests (Begg’s test, P = 0.707; Egger’s test, P = 0.355).</p> <p>Conclusion</p><p>The present meta-analysis indicated that elevated ALDH expression was associated with poor prognosis in patients with ovarian cancer.</p> </div