Single-cell RNA sequencing identifies a novel proliferation cell type affecting clinical outcome of pancreatic ductal adenocarcinoma.

Background: Pancreatic ductal adenocarcinoma (PDAC) is an extremely deadly neoplasm, with only a 5-year survival rate of around 9%. The tumor and its microenvironment are highly heterogeneous, and it is still unknown which cell types influence patient outcomes. Methods: We used single-cell RNA sequencing (scRNA-seq) and spatial transcriptome (ST) to identify differences in cell types. We then applied the scRNA-seq data to decompose the cell types in bulk RNA sequencing (bulk RNA-seq) data from the Cancer Genome Atlas (TCGA) cohort. We employed unbiased machine learning integration algorithms to develop a prognosis signature based on cell type makers. Lastly, we verified the differential expression of the key gene LY6D using immunohistochemistry and qRT-PCR. Results: In this study, we identified a novel cell type with high proliferative capacity, Prol, enriched with cell cycle and mitosis genes. We observed that the proportion of Prol cells was significantly increased in PDAC, and Prol cells were associated with reduced overall survival (OS) and progression-free survival (PFS). Additionally, the marker genes of Prol cell type, identified from scRNA-seq data, were upregulated and associated with poor prognosis in the bulk RNA-seq data. We further confirmed that mutant KRAS and TP53 were associated with an increased abundance of Prol cells and that these cells were associated with an immunosuppressive and cold tumor microenvironment in PDAC. ST determined the spatial location of Prol cells. Additionally, patients with a lower proportion of Prol cells in PDAC may benefit more from immunotherapy and gemcitabine treatment. Furthermore, we employed unbiased machine learning integration algorithms to develop a Prol signature that can precisely quantify the abundance of Prol cells and accurately predict prognosis. Finally, we confirmed that the LY6D protein and mRNA expression were markedly higher in pancreatic cancer than in normal pancreatic tissue. Conclusions: In summary, by integrating bulk RNA-seq and scRNA-seq, we identified a novel proliferative cell type, Prol, which influences the OS and PFS of PDAC patients.

The roles of IDH1 in tumor metabolism and immunity.

IDH1 is a key metabolic enzyme for cellular respiration in the tricarboxylic acid (TCA) cycle that can convert isocitrate into α-ketoglutarate (α-KG) and generate NADPH. The reduction of IDH1 may affect dioxygenase activity and damage the body's detoxification mechanism. Many studies have shown that IDH1 is closely related to the occurrence and development of tumors, and the changes in IDH1 expression levels or gene mutations have appeared in many tumor tissues and produced a series of metabolic and immunity changes at the same time. To better understand the relationship between IDH1 and tumor development, this article reviews the latest advances in IDH1 and tumor metabolism, tumor immunity, IDH1 regulatory mechanisms and IDH1 target inhibitors.

IDH1 is a key metabolic enzyme for cellular respiration. The changes in IDH1 expression or gene mutations may affect enzyme activity and damage the body's detoxification mechanism. Studies have shown that IDH1 is closely related to the occurrence and development of tumors, and the changes in IDH1 also produced a series of metabolic and immunity changes. To better understand the relationship between IDH1 and tumor development, this article reviews the latest advances in IDH1 and tumor metabolism, tumor immunity, IDH1 regulatory mechanisms and IDH1 target inhibitors.

Synergistic Effect of Hydrogen Bonds and Chemical Bonds to Construct a Starch-Based Water-Absorbing/Retaining Hydrogel Composite Reinforced with Cellulose and Poly(ethylene glycol).

The hydrogel prepared by graft copolymerization of starch (ST) and acrylamide (AM) is a commonly used absorbent material; however, due to their irregular network structure and a limited number of hydrophilic groups, starch-based hydrogels have poor water absorption and water retention. To overcome this, here, we provide a new preparation method for starch-based hydrogels. Using cerium ammonium nitrate (CAN) as an initiator, the starch-acrylamide-cellulose (CMC)/poly(ethylene glycol) (S-A-M/PEG) superabsorbent hydrogel was prepared by graft copolymerization. The starch-acrylamide-cellulose/poly(ethylene glycol) hydrogel network is constructed through the synergistic effect of hydrogen bonds and chemical bonds. The experimental results showed that the starch-acrylamide-cellulose/poly(ethylene glycol) superabsorbent hydrogel has a complete network structure that does not easily collapse due to its superior mechanical properties. The water swelling rate reached 80.24 times, and it reached 50.61% water retention after 16 days. This hydrogel has excellent water-absorbing and water-retaining properties, biocompatibility, and degradability, making it useful for further studies in medical, agricultural, and other fields.

Construction of Porous Starch-Based Hydrogel via Regulating the Ratio of Amylopectin/Amylose for Enhanced Water-Retention.

The performance of hydrogels prepared with traditional natural starch as raw materials is considerable; the fixed ratio of amylose/amylopectin significantly limits the improvement of hydrogel structure and performance. In this paper, starch hydrogels were prepared by physical blending and chemical grafting, with the aid of ultrasonic heating. The effects of different amylose/amylopectin ratios on the microstructure and water retention properties of starch hydrogels were studied. The results show that an increase in amylopectin content is beneficial to improve the grafting ratio of acrylamide (AM). The interaction between the AM grafted on amylopectin and amylose molecules through hydrogen bonding increases the pores of the gel network and thins the pore walls. When the amylopectin content was 70%, the water absorption (swelling 45.25 times) and water retention performance (16 days water retention rate 44.17%) were optimal. This study provides new insights into the preparation of starch-based hydrogels with excellent physical and chemical properties.

An Infrared-Visible Image Registration Method Based on the Constrained Point Feature.

It is difficult to find correct correspondences for infrared and visible image registration because of different imaging principles. Traditional registration methods based on the point feature require designing the complicated feature descriptor and eliminate mismatched points, which results in unsatisfactory precision and much calculation time. To tackle these problems, this paper presents an artful method based on constrained point features to align infrared and visible images. The proposed method principally contains three steps. First, constrained point features are extracted by employing an object detection algorithm, which avoids constructing the complex feature descriptor and introduces the senior semantic information to improve the registration accuracy. Then, the left value rule (LV-rule) is designed to match constrained points strictly without the deletion of mismatched and redundant points. Finally, the affine transformation matrix is calculated according to matched point pairs. Moreover, this paper presents an evaluation method to automatically estimate registration accuracy. The proposed method is tested on a public dataset. Among all tested infrared-visible image pairs, registration results demonstrate that the proposed framework outperforms five state-of-the-art registration algorithms in terms of accuracy, speed, and robustness.

Saliency Detection with Bilateral Absorbing Markov Chain Guided by Depth Information.

The effectiveness of depth information in saliency detection has been fully proved. However, it is still worth exploring how to utilize the depth information more efficiently. Erroneous depth information may cause detection failure, while non-salient objects may be closer to the camera which also leads to erroneously emphasis on non-salient regions. Moreover, most of the existing RGB-D saliency detection models have poor robustness when the salient object touches the image boundaries. To mitigate these problems, we propose a multi-stage saliency detection model with the bilateral absorbing Markov chain guided by depth information. The proposed model progressively extracts the saliency cues with three level (low-, mid-, and high-level) stages. First, we generate low-level saliency cues by explicitly combining color and depth information. Then, we design a bilateral absorbing Markov chain to calculate mid-level saliency maps. In mid-level, to suppress boundary touch problem, we present the background seed screening mechanism (BSSM) for improving the construction of the two-layer sparse graph and better selecting background-based absorbing nodes. Furthermore, the cross-modal multi-graph learning model (CMLM) is designed to fully explore the intrinsic complementary relationship between color and depth information. Finally, to obtain a more highlighted and homogeneous saliency map in high-level, we structure a depth-guided optimization module which combines cellular automata and suppression-enhancement function pair. This optimization module refines the saliency map in color space and depth space, respectively. Comprehensive experiments on three challenging benchmark datasets demonstrate the effectiveness of our proposed method both qualitatively and quantitatively.

HMGA2 upregulation mediates Cd-induced migration and invasion in A549 cells and in lung tissues of mice.

Cadmium (Cd) is a toxic metal widely found in a number of environmental matrices, and it induces serious adverse effects in various organs and tissues. In this study, the role of high mobility group A2 (HMGA2) in promoting migration and invasion in Cd-treated A549 cells and lung tissues of mice was investigated. Our findings showed that exposure to Cd (2 µM) for 48 h or subcutaneous injection of Cd daily for 6 weeks significantly enhanced the expression of matrix metalloproteinase-9 (MMP-9), matrix metalloproteinase-2 (MMP-2), phosphorylated focal adhesion kinase (p-FAK), and HMGA2 in A549 cells or lung tissues of mice. In A549 cells, HMGA2 knockdown significantly decreased expression of MMP-9, MMP-2 and p-FAK and inhibited the migration and invasion compared to that of only Cd-treated cultures. Overexpression of HMGA2 in HEK-293T cells increased expression of MMP-9, MMP-2 and p-FAK and enhanced the migration and invasion compared with the empty vector transfection group. In conclusion, upregulation of HMGA2 plays an important role in Cd-enhanced migration and invasion. Suppressing HMGA2 expression might have potential values in prevention of Cd-resulted toxicities.

[Identification of a recurrent mutation in the ROR2 gene in a Chinese family with brachydactyly type B].

OBJECTIVE: To identify the disease-causing mutation in a Chinese family with brachydactyly type B (BDB). METHODS: Genomic DNA was extracted from peripheral blood samples of family members. Exons 8 and 9 of the ROR2 gene were amplified by polymerase chain reaction (PCR) and sequenced directly. Furthermore, the PCR products showing mutation were cloned into pMD18T vector and the insert fragments were sequenced. RESULTS: A 1398-1399 insA heterozygous mutation was detected in the patient. This mutation had been found in German families with BDB. CONCLUSION: To the authors' knowledge, it is the first report on identification of the ROR2 pathogenic mutation in Chinese patients with BDB.

[Functional analysis of the single nucleotide polymorphisms in the PRKCZ gene].

OBJECTIVE: To study the function of 5 single nucleotide polymorphisms (SNPs) of the PRKCZ gene, a susceptibility gene for type 2 diabetes in Han population of North China, in the pathogenesis of the disease. METHODS: Bioinformatic methods and reporter gene activity determination were used to analyze the function of the 5 SNPs. RESULTS: The reporter gene activities of different alleles of 2 SNPs, rs427811 and rs809912, were obviously different, which implies that these 2 SNPs might be susceptibility loci of the disease. CONCLUSION: The PRKCZ gene is further confirmed to be a susceptibility gene for type 2 diabetes in Han population of North China. Two SNPs in the gene play a role in the pathogenesis of the disease by affecting the expression level of PRKCZ gene.

[Linkage disequilibrium analysis of the single nucleotide polymorphisms in the PRKCZ gene].

OBJECTIVE: To search for the disease-associated haplotype in the PRKCZ gene, a susceptibility gene for type 2 diabetes in Han population of North China, by case-control study and linkage disequilibrium (LD) analysis using single nucleotide polymorphisms (SNPs). METHODS: SNPs located in the PRKCZ gene were chosen from public SNP domain by bioinformatic methods and single base extension (SBE) method was used to genotype the loci in 173 sporadic type 2 diabetes patients and 152 normal individuals to perform case-control study and LD analysis. Haplotype block were constructed in these populations. RESULTS: Several SNPs in the PRKCZ gene were found to be associated with the disease. The SNPs formed different haplotype block pattern in case and control groups. The frequencies of the haplotypes formed by 5 SNPs were statistically different between the two groups. CONCLUSION: The haplotype formed by 5 SNPs in the PRKCZ gene may be associated with type 2 diabetes in Han population of China, which is confirmed from statistics to be a susceptibility gene for the disease.