Facile Preparation of Oxygen-Vacancy-Engineered MoOx Nanostructures for Photoreversible Switching Systems

Photochromic materials have attracted increasing attention. Here, we report a novel photo-reversible color switching system based on oxygen-vacancy-engineered MoOx nanostructures with water/N-methyl-2-pyrrolidone (NMP) as solvents. In this work, the system rapidly changed from colorless to blue under UV irradiation (360–400 nm) and slowly recovered its colorless state under visible light irradiation. The obtained oxygen vacancy-engineered MoOx nanostructures exhibited good repeatability, chemical stability, and cycling stability. Upon UV light irradiation, H+ was intercalated into layered MoOx nanostructures and the Mo6+ concentration in the HxMoOx decreased, while the Mo5+ concentration increased and increased oxygen vacancies changed the color to blue. Then, it recovered its original color slowly without UV light irradiation. What is more, the system was highly sensitive to UV light even on cloudy days. Compared with other reported photochromic materials, the system in this study has the advantage of facile preparation and provides new insights for the development of photochromic materials without dyes

Measurements of the branching fractions for D + → K S 0 K S 0 K + , K S 0 K S 0 π + and D 0 → K S 0 K S 0 , K S 0 K S 0 K S 0

By analyzing $2.93\ \rm fb^{-1}$ of data taken at the $\psi(3770)$ resonance peak with the BESIII detector, we measure the branching fractions for the hadronic decays $D^+\to K^0_SK^0_S K^+$, $D^+\to K^0_SK^0_S \pi^+$, $D^0\to K^0_S K^0_S$ and $D^0\to K^0_SK^0_SK^0_S$. They are determined to be ${\mathcal B}(D^+\to K^0_SK^0_SK^+)=(2.54 \pm 0.05_{\rm stat.} \pm 0.12_{\rm sys.})\times 10^{-3}$, ${\mathcal B}(D^+\to K^0_SK^0_S\pi^+)=(2.70 \pm 0.05_{\rm stat.} \pm 0.12_{\rm sys.})\times 10^{-3}$, ${\mathcal B}(D^0\to K^0_SK^0_S)=(1.67 \pm 0.11_{\rm stat.} \pm 0.11_{\rm sys.})\times 10^{-4}$ and ${\mathcal B}(D^0\to K^0_SK^0_SK^0_S)=(7.21 \pm 0.33_{\rm stat.} \pm 0.44_{\rm sys.})\times 10^{-4}$, where the second one is measured for the first time and the others are measured with significantly improved precision over the previous measurements

Characterizing the Tumor Suppressor Role of CEACAM1 in Multiple Myeloma

Background/Aims: Carcinoembryonic antigen-related cell adhesion molecule 1 (CEACAM1), also known as CD66a, is a member of the immunoglobulin (Ig) superfamily that belongs to the carcinoembryonic antigen (CEA) family which plays a dual role in cancer. Previous studies showed high expression of CEACAM1 in multiple myeloma (MM). The aim of this study was to investigate the biological consequences of CEACAM1 overexpression in MM. Methods: pEGFP-N1-CEACAM1 and pcDNA3.1-CEACAM1 expression plasmids were transfected into U-266 and RPMI8266 cell lines . Effect of CEACAM1 overexpression on the proliferation of two cell lines were tested by the CCK8 assay. Cell cycle and Apoptotic changes after CEACAM1 transfection were examined with AnnexinV–FITC/PI by flow cytometry. Hochest staining assay was used to confirm the apoptotic changes. Caspase-3 activity was examined by Western blotting. The cell invasion and migration activity change after CEACAM1 transfection were performed by well chamber assays and a wound healing, respectively. MMP-2 and MMP-9 proteins expression were detected by Western blotting. Flow cytometry immunophenotyping was be evaluated on myeloma cells from bone marrow taken from 50 patients with symptomatic MM newly diagnosed. The correlations between CEACAM1 expression levels and the clinical features across all groups were investigated. Results: CEACAM1 overexpression significantly suppressed MM cell proliferation, induced cell apoptosis, and inhibited cell invasion and migration possibly through activation of caspase-3 and downregulation of MMP-2 and MMP-9. CEACAM1 expression in patients with DS stage I was more frequent (61.5%) than those with DS stage II (21.1%) or III (22.2%). Furthermore, patients with β2-microglobulin levels equal to or less than 3.5 mg/L had higher CEACAM1 expression than those with β2-microglobulin levels greater than 3.5 mg/L. Conclusion: Our findings suggest that CEACAM1 may act as a tumor suppressor in MM

Bifidobacterium adolescentis induces Decorin+ macrophages via TLR2 to suppress colorectal carcinogenesis

Abstract Background The interplay between gut microbiota and tumor microenvironment (TME) in the pathogenesis of colorectal cancer (CRC) is largely unknown. Here, we elucidated the functional role of B. adolescentis and its possible mechanism on the manipulation of Decorin+ macrophages in colorectal cancer. Methods The relative abundance of B. adolescentis in tumor or para-tumor tissue of CRC patients was analyzed. The role of B. adolescentis was explored in the CRC animal models. The single cell-RNA sequencing (scRNA-seq) was used to investigate the myeloid cells subsets in TME. The expression level of TLR2/YAP axis and its downstream Decorin in macrophages were tested by Western blot and qRT-PCR. Knockdown of Decorin in Raw264.7 was performed to investigate the effect of Decorin+ macrophages on subcutaneous tumor formation. Multi-immunofluorescence assay examined the number of Decorin+ macrophages on the CRC tissue. Results We found that the abundance of B. adolescentis was significantly reduced in tumor tissue of CRC patients. Supplementation with B. adolescentis suppressed AOM/DSS-induced tumorigenesis in mice. ScRNA-seq and animal experiment revealed that B. adolescentis increased Decorin+ macrophages. Mechanically, Decorin was activated by TLR2/YAP axis in macrophages. The abundance of B. adolescentis was correlated with the number of Decorin+ macrophages and the expression level of TLR2 in tumor tissue of CRC patients. Conclusions These results highlight that B. adolescentis induced Decorin+ macrophages and provide a novel therapeutic target for probiotic-based modulation of immune microenvironment in CRC

Gastric precancerous diseases classification using CNN with a concise model.

Gastric precancerous diseases (GPD) may deteriorate into early gastric cancer if misdiagnosed, so it is important to help doctors recognize GPD accurately and quickly. In this paper, we realize the classification of 3-class GPD, namely, polyp, erosion, and ulcer using convolutional neural networks (CNN) with a concise model called the Gastric Precancerous Disease Network (GPDNet). GPDNet introduces fire modules from SqueezeNet to reduce the model size and parameters about 10 times while improving speed for quick classification. To maintain classification accuracy with fewer parameters, we propose an innovative method called iterative reinforced learning (IRL). After training GPDNet from scratch, we apply IRL to fine-tune the parameters whose values are close to 0, and then we take the modified model as a pretrained model for the next training. The result shows that IRL can improve the accuracy about 9% after 6 iterations. The final classification accuracy of our GPDNet was 88.90%, which is promising for clinical GPD recognition

Discovery of an 8-oxoguanine regulator PCBP1 inhibitor by virtual screening and its synergistic effects with ROS-modulating agents in pancreatic cancer

Introduction: Drugs that target reactive oxygen species (ROS) metabolism have progressed the treatment of pancreatic cancer treatment, yet their efficacy remains poor because of the adaptation of cancer cells to high concentration of ROS. Cells cope with ROS by recognizing 8-oxoguanine residues and processing severely oxidized RNA, which make it feasible to improve the efficacy of ROS-modulating drugs in pancreatic cancer by targeting 8-oxoguanine regulators.Methods: Poly(rC)-binding protein 1 (PCBP1) was identified as a potential oncogene in pancreatic cancer through datasets of The Cancer Genome Atlas (TCGA) project and Gene Expression Omnibus (GEO). High-throughput virtual screening was used to screen out potential inhibitors for PCBP1. Computational molecular dynamics simulations was used to verify the stable interaction between the two compounds and PCBP1 and their structure–activity relationships. In vitro experiments were performed for functional validation of silychristin.Results: In this study, we identified PCBP1 as a potential oncogene in pancreatic cancer. By applying high-throughput virtual screening, we identified Compound 102 and Compound 934 (silychristin) as potential PCBP1 inhibitors. Computational molecular dynamics simulations and virtual alanine mutagenesis verified the structure–activity correlation between PCBP1 and the two identified compounds. These two compounds interfere with the PCBP1–RNA interaction and impair the ability of PCBP1 to process RNA, leading to intracellular R loop accumulation. Compound 934 synergized with ROS agent hydrogen peroxide to strongly improve induced cell death in pancreatic cancer cells.Discussion: Our results provide valuable insights into the development of drugs that target PCBP1 and identified promising synergistic agents for ROS-modulating drugs in pancreatic cancer

Real-time gastric polyp detection using convolutional neural networks.

Computer-aided polyp detection in gastric gastroscopy has been the subject of research over the past few decades. However, despite significant advances, automatic polyp detection in real time is still an unsolved problem. In this paper, we report on a convolutional neural network (CNN) for polyp detection that is constructed based on Single Shot MultiBox Detector (SSD) architecture and which we call SSD for Gastric Polyps (SSD-GPNet). To take full advantages of feature maps' information from the feature pyramid and to acquire higher accuracy, we re-use information that is abandoned by Max-Pooling layers. In other words, we reuse the lost data from the pooling layers and concatenate that data as extra feature maps to contribute to classification and detection. Meanwhile, in the feature pyramid, we concatenate feature maps of the lower layers and feature maps that are deconvolved from upper layers to make explicit relationships between layers and to effectively increase the number of channels. The results show that our enhanced SSD for gastric polyp detection can realize real-time polyp detection with 50 frames per second (FPS) and can improve the mean average precision (mAP) from 88.5% to 90.4%, with only a little loss in time-performance. And the further experiment shows that SSD-GPNet has excellent performance in improving polyp detection recalls over 10% (p = 0.00053), especially in small polyp detection. This can help endoscopic physicians more easily find missed polyps and decrease the gastric polyp miss rate. It may be applicable in daily clinical practice to reduce the burden on physicians

CD4-Targeted T Cells Rapidly Induce Remissions in Mice with T Cell Lymphoma

Objective. To explore the immune cell therapy for T cell lymphoma, we developed CD4-specific chimeric antigen receptor- (CAR-) engineered T cells (CD4CART), and the cytotoxic effects of CD4CART cells were determined in vitro and in vivo. Methods. CD4CART cells were obtained by transduction of lentiviral vector encoding a single-chain antibody fragment (scFv) specific for CD4 antigen, costimulatory factor CD28 fragment, and intracellular signal transduction domain of CD3 fragments. Control T cells were obtained by transduction of reporter lentiviral vector. The cytotoxicity, tumor growth, and survival rate of mice with T cell lymphoma were analyzed after adoptive T cell transfer in vivo. Results. CD4CART cells had potent cytotoxic activity against CD4+ T1301 tumor T cells in a concentration-dependent manner. In addition, adoptive CD4CART cell transfer significantly suppressed tumor growth and improved animal survival with T cell lymphoma, compared to the mice who received control T cells and PBS. Conclusion. CD4CART cells have potent cytotoxic effects on T cell lymphoma. The study provided an experimental basis for CD4CART-mediated therapy of T cell lymphoma