Automatic detection of steel surface defects is very important for product quality control in the steel industry. However, the traditional method cannot be well applied in the production line, ...because of its low accuracy and slow running speed. The current, popular algorithm (based on deep learning) also has the problem of low accuracy, and there is still a lot of room for improvement. This paper proposes a method combining improved ResNet50 and enhanced faster region convolutional neural networks (faster R-CNN) to reduce the average running time and improve the accuracy. Firstly, the image input into the improved ResNet50 model, which add the deformable revolution network (DCN) and improved cutout to classify the sample with defects and without defects. If the probability of having a defect is less than 0.3, the algorithm directly outputs the sample without defects. Otherwise, the samples are further input into the improved faster R-CNN, which adds spatial pyramid pooling (SPP), enhanced feature pyramid networks (FPN), and matrix NMS. The final output is the location and classification of the defect in the sample or without defect in the sample. By analyzing the data set obtained in the real factory environment, the accuracy of this method can reach 98.2%. At the same time, the average running time is faster than other models.
Understanding the mechanism of radioresistance could help develop strategies to improve therapeutic response of patients with PDAC. The
gene is frequently mutated in pancreatic cancer. In this study, ...we investigated the role of
deficiency in pancreatic cancer cells' response to radiotherapy.
We downregulated SMAD4 expression with
siRNA or
shRNA and overexpressed SMAD4 in
mutant pancreatic cancer cells followed by clonogenic survival assay to evaluate their effects on cell radioresistance. To study the mechanism of radioresistance, the effects of
loss on reactive oxygen species (ROS) and autophagy were determined by flow cytometry and immunoblot analysis, respectively. Furthermore, we measured radioresistance by clonogenic survival assay after treatment with autophagy inhibitor (Chloroquine) and ROS inhibitor (N-acetyl-l-cysteine) in
-depleted pancreatic cancer cells. Finally, the effects of
on radioresistance were also confirmed in an orthotopic tumor model derived from
-depleted Panc-1 cells.
-depleted pancreatic cancer cells were more resistant to radiotherapy based on clonogenic survival assay. Overexpression of wild-type SMAD4 in
-mutant cells rescued their radiosensitivity. Radioresistance mediated by
depletion was associated with persistently higher levels of ROS and radiation-induced autophagy. Finally,
depletion induced
radioresistance in Panc-1-derived orthotopic tumor model (
= 0.038). More interestingly, we observed that the protein level of SMAD4 is inversely correlated with autophagy in orthotopic tumor tissue samples.
Our results demonstrate that defective
is responsible for radioresistance in pancreatic cancer through induction of ROS and increased level of radiation-induced autophagy.
.
Checkpoint blockade antibodies have been approved as immunotherapy for multiple types of cancer, but the response rate and efficacy are still limited. There are few immunogenic cell death ...(ICD)-inducing drugs available that can kill cancer cells, enhance tumor immunogenicity, increase the in vivo immune infiltration, and thereby boosting a tumor response to immunotherapy. So far, the ICD markers have been identified as the few immuno-stimulating characteristics of dead cells, but whether the presence of such ICD markers on tumor cells translates into enhanced antitumor immunity in vivo is still investigational. To identify anticancer drugs that could induce tumor cell death and boost T cell response, we performed drug screenings based on both an ICD reporter assay and T cell activation assay. We identified that teniposide, a DNA topoisomerase II inhibitor, could induce high mobility group box 1 (HMGB1) release and type I interferon signaling in tumor cells, and teniposide-treated tumor cells could activate antitumor T cell response both in vitro and in vivo. Mechanistically, teniposide induced tumor cell DNA damage and innate immune signaling including NF-κB activation and STING-dependent type I interferon signaling, both of which contribute to the activation of dendritic cells and subsequent T cells. Furthermore, teniposide potentiated the antitumor efficacy of anti-PD1 on multiple types of mouse tumor models. Our findings showed that teniposide could trigger tumor immunogenicity, and enabled a potential chemo-immunotherapeutic approach to potentiate the therapeutic efficacy of anti-PD1 immunotherapy.
The heterogeneous nature of tumour microenvironment (TME) underlying diverse treatment responses remains unclear in nasopharyngeal carcinoma (NPC). Here, we profile 176,447 cells from 10 NPC ...tumour-blood pairs, using single-cell transcriptome coupled with T cell receptor sequencing. Our analyses reveal 53 cell subtypes, including tumour-infiltrating CD8
T, regulatory T (Treg), and dendritic cells (DCs), as well as malignant cells with different Epstein-Barr virus infection status. Trajectory analyses reveal exhausted CD8
T and immune-suppressive TNFRSF4
Treg cells in tumours might derive from peripheral CX3CR1
CD8
T and naïve Treg cells, respectively. Moreover, we identify immune-regulatory and tolerogenic LAMP3
DCs. Noteworthily, we observe intensive inter-cell interactions among LAMP3
DCs, Treg, exhausted CD8
T, and malignant cells, suggesting potential cross-talks to foster an immune-suppressive niche for the TME. Collectively, our study uncovers the heterogeneity and interacting molecules of the TME in NPC at single-cell resolution, which provide insights into the mechanisms underlying NPC progression and the development of precise therapies for NPC.
To better solve the problem of thermal error of computerized numerical control machining equipment (CNCME), a thermal error prediction model based on the sparrow search algorithm and long short-term ...memory neural network (SSA-LSTMNN) is proposed. Firstly, the Fuzzy C-means clustering algorithm (FCMCA) is used to screen the key temperature-sensitive points of the CNCME. Secondly, by taking the temperature rise data of key temperature-sensitive points as input and the corresponding time thermal error data as output, we established the SSA-LSTMNN thermal error prediction model. The SSA is used to optimize the parameters of LSTMNN and make its performance play the best. Taking the VMC1060 vertical machining center as the research object, we carried out the experiment. Finally, the prediction effect of the proposed model is compared with the article swarm optimized algorithm and LSTM neural network (PSOA-LSTMNN), the LSTMNN, and the traditional recurrent neural network (TRNN) model. The results show that the average values of the predicted residual fluctuations of the SSA-LSTMNN model are all more than 44% lower than those of the other three models under different operating conditions, which has a strong practicality.
Messenger RNA (mRNA)-based cancer vaccine has become a popular approach for developing personalized and effective antitumor immunotherapy. To achieve robust antitumor efficacy, mRNA-encoding tumor ...antigens needs to be efficiently delivered and translated in dendritic cells for efficient antigen presentation; meanwhile, the vaccine would have adjuvant effect by stimulating innate immune response to boost the full activation of adaptive immunity. Recently, we reported a minimalist nanovaccine by formulating tumor antigen-encoding mRNA with a lipid-like material named C1, which could efficiently deliver mRNA into dendritic cells with simultaneous Toll-like receptor 4 (TLR4) stimulation, together induced T cell activation. Importantly, C1 mRNA nanovaccine exhibited significant antitumor efficacy on several tumor mouse models. Here, we discuss the nanovector-facilitated mRNA delivery and translation in dendritic cells, the self-adjuvant property of nanovectors, the challenges of personalized tumor antigen selection, and the potential strategies for developing efficacious mRNA cancer vaccines targeting the immunosuppressive tumor microenvironment.
As core units of organ tissues, cells of various types play their harmonious rhythms to maintain the homeostasis of the human body. It is essential to identify the characteristics of cells in human ...organs and their regulatory networks for understanding the biological mechanisms related to health and disease. However, a systematic and comprehensive single-cell transcriptional profile across multiple organs of a normal human adult is missing.
We perform single-cell transcriptomes of 84,363 cells derived from 15 tissue organs of one adult donor and generate an adult human cell atlas. The adult human cell atlas depicts 252 subtypes of cells, including major cell types such as T, B, myeloid, epithelial, and stromal cells, as well as novel COCH
fibroblasts and FibSmo cells, each of which is distinguished by multiple marker genes and transcriptional profiles. These collectively contribute to the heterogeneity of major human organs. Moreover, T cell and B cell receptor repertoire comparisons and trajectory analyses reveal direct clonal sharing of T and B cells with various developmental states among different tissues. Furthermore, novel cell markers, transcription factors, and ligand-receptor pairs are identified with potential functional regulations in maintaining the homeostasis of human cells among tissues.
The adult human cell atlas reveals the inter- and intra-organ heterogeneity of cell characteristics and provides a useful resource in uncovering key events during the development of human diseases in the context of the heterogeneity of cells and organs.
Macrophage polarization to proinflammatory M1-like or anti-inflammatory M2-like cells is critical to mount a host defense or repair tissue. The exact molecular mechanisms controlling this process are ...still elusive. Here, we report that ubiquitin-specific protease 19 (USP19) acts as an anti-inflammatory switch that inhibits inflammatory responses and promotes M2-like macrophage polarization. USP19 inhibited NLRP3 inflammasome activation by increasing autophagy flux and decreasing the generation of mitochondrial reactive oxygen species. In addition, USP19 inhibited the proteasomal degradation of inflammasome-independent NLRP3 by cleaving its polyubiquitin chains. USP19-stabilized NLRP3 promoted M2-like macrophage polarization by direct association with interferon regulatory factor 4, thereby preventing its p62-mediated selective autophagic degradation. Consistent with these observations, compared to wild-type mice, Usp19
mice had decreased M2-like macrophage polarization and increased interleukin-1β secretion, in response to alum and chitin injections. Thus, we have uncovered an unexpected mechanism by which USP19 switches the proinflammatory function of NLRP3 into an anti-inflammatory function, and suggest that USP19 is a potential therapeutic target for inflammatory interventions.
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