Atomic Magnetic Heating Effect Enhanced Hydrogen Evolution Reaction of Gd@MoS2 Single-Atom Catalysts.

Atomic heating on single atoms (SAs) to maximize the catalytic efficiency of each active site would be a fascinating solution to break the bottleneck for the performance improvement of single-atom catalysts (SACs) but highly challenging task. Here, based on the Gd@MoS2 SACs synthesized by a facile laser molecular beam epitaxy method, high-frequency alternating magnetic field (AMF) technology is employed to induce atomic magnetic heating on Gd SAs that is meanwhile demonstrated to be the catalytic active center. Significant improvement in catalytic kinetics under AMF excitation (3.9 mT) is achieved, yielding a remarkable enhancement of hydrogen evolution reaction magnetothermal-current by ≈924%. Through theoretical calculations and spin-related electrochemical experiments, such promotion in catalyst activity can be attributed to spin flip (or canting) in Gd SAs leading to the atomic magnetic heating effect on catalytic active center. Together with the embodied high stability, the implement of AMF to the SAs field is demonstrated in this work, and the precisely atomic magnetic heating on specific SAs offers unprecedented thinking for further improvement of SACs performance in the future.

Electrochemical Reconstruction of NiFe/NiFeOOH Superparamagnetic Core/Catalytic Shell Heterostructure for Magnetic Heating Enhancement of Oxygen Evolution Reaction.

Although (oxy)hydroxides generated by electrochemical reconstruction (EC-reconstruction) of transition-metal catalysts exhibit highly catalytic activities, the amorphous nature fundamentally impedes the electrochemical kinetics due to its poor electrical conductivity. Here, EC-reconstructed NiFe/NiFeOOH core/shell nanoparticles in highly conductive carbon matrix based on the pulsed laser deposition prepared NiFe nanoparticles is successfully confined. Electrochemical characterizations and first-principles calculations demonstrate that the reconstructed NiFe/NiFeOOH core/shell nanoparticles exhibit high oxygen evolution reaction (OER) electrocatalytic activity (a low overpotential of 342.2 mV for 10 mA cm-2 ) and remarkable durability due to the efficient charge transfer in the highly conductive confined heterostructure. More importantly, benefit from the superparamagnetic nature of the reconstructed NiFe/NiFeOOH core/shell nanoparticles, a large OER improvement is achieved (an ultralow overpotential of 209.2 mV for 10 mA cm-2 ) with an alternating magnetic field stimulation. Such OER improvement can be attributed to the Néel relaxation related magnetic heating effect functionalized superparamagnetic NiFe cores, which are generally underutilized in reconstructed core/shell nanoparticles. This work demonstrates that the designed superparamagnetic core/shell nanoparticles, combined with the large improvement by magnetic heating effect, are expected to be highly efficient OER catalysts along with the confined structure guaranteed high conductivity and catalytic stability.

Investigating the Eley-Rideal recombination of hydrogen atoms on Cu (111) via a high-dimensional neural network potential energy surface.

As a prototypical system for studying the Eley-Rideal (ER) mechanism at the gas-surface interface, the reaction between incident H/D atoms and pre-covered D/H atoms on Cu (111) has attracted much experimental and theoretical interest. Detailed final state-resolved experimental data have been available for about thirty-years, leading to the discovery of many interesting dynamical features. However, previous theoretical models have suffered from reduced-dimensional approximations and/or omitting energy transfer to surface phonons and electrons, or the high cost of on-the-fly ab initio molecular dynamics, preventing quantitative comparisons with experimental data. Herein, we report the first high-dimensional neural network potential (NNP) for this ER reaction based on first-principles calculations including all molecular and surface degrees of freedom. Thanks to the high efficiency of this NNP, we are able to perform extensive quasi-classical molecular dynamics simulations with the inclusion of the excitation of low-lying electron-hole pairs (EHPs), which generally yield good agreement with various experimental results. More importantly, the isotopic and/or EHP effects in total reaction cross-sections and distributions of the product energy, scattering angle, and individual ro-vibrational states have been more clearly shown and discussed. This study sheds valuable light on this important ER prototype and opens a new avenue for further investigations of ER reactions using various initial conditions, surface temperatures, and coverages in the future.

Alternating Magnetic Field Induced Magnetic Heating in Ferromagnetic Cobalt Single-Atom Catalysts for Efficient Oxygen Evolution Reaction.

Alternating magnetic field (AMF) is a promising methodology for further improving magnetic single-atom catalyst (SAC) activity toward oxygen evolution reaction (OER). Herein, the anchoring of Co single atoms on MoS2 support (Co@MoS2), leading to the appearance of in-plane room-temperature ferromagnetic properties, is favorable for the parallel spin arrangement of oxygen atoms when a magnetic field is applied. Moreover, field-assisted electrocatalytic experiments confirmed that the spin direction of Co@MoS2 is changing with the applied magnetic field. On this basis, under AMF, the active sites in ferromagnetic Co@MoS2 were heated by exploiting the magnetic heating generated from spin polarization flip of these SACs to further expedite OER efficiency, with overpotential at 10 mA cm-2 reduced from 317 mV to 250 mV. This work introduces a feasible and efficient approach to enhance the OER performance of Co@MoS2 by AMF, shedding some light on the further development of magnetic SACs for energy conversion.

Efficient Charge Transfers in Highly Conductive Copper Selenide Quantum Dot-Confined Catalysts for Robust Oxygen Evolution Reaction.

Defective quantum dots (QDs) are the emerging materials for catalysis by virtue of their atomic-scale size, high monodispersity, and ultra-high specific surface area. However, the dispersed nature of QDs fundamentally prohibits the efficient charge transfer in various catalytic processes. Here, we report efficient and robust electrocatalytic oxygen evolution based on defective and highly conductive copper selenide (CuSe) QDs confined in an amorphous carbon matrix with good uniformity (average diameter 4.25 nm) and a high areal density (1.8 × 1012 cm-2). The CuSe QD-confined catalysts with abundant selenide vacancies were prepared by using a pulsed laser deposition system benefitted by high substrate temperature and ultrahigh vacuum growth conditions, as evidenced by electron paramagnetic resonance characterizations. An ultra-low charge transfer resistance (about 7 Ω) determined by electrochemical impedance spectroscopy measurement indicates the efficient charge transfer of CuSe quantum-confined catalysts, which is guaranteed by its high conductivity (with a low resistivity of 2.33 µΩ·m), as revealed by electrical transport measurements. Our work provides a universal design scheme of the dispersed QD-based composite catalysts and demonstrates the CuSe QD-confined catalysts as an efficient and robust electrocatalyst for oxygen evolution reaction.

Field-Free Improvement of Oxygen Evolution Reaction in Magnetic Two-Dimensional Heterostructures.

Ferromagnetic (FM) electrocatalysts have been demonstrated to reduce the kinetic barrier of oxygen evolution reaction (OER) by spin-dependent kinetics and thus enhance the efficiency fundamentally. Accordingly, FM two-dimensional (2D) materials with unique physicochemical properties are expected to be promising oxygen-evolution catalysts; however, related research is yet to be reported due to their air-instabilities and low Curie temperatures (TC). Here, based on the synthesis of 2D air-stable FM Cr2Te3 nanosheets with a low TC around 200 K, room-temperature ferromagnetism is achieved in Cr2Te3 by proximity to an antiferromagnetic (AFM) CrOOH, demonstrating the accomplishment of long-ranged FM ordering in Cr2Te3 because the magnetic proximity effect stems from paramagnetic (PM)/AFM heterostructure. Therefore, the OER performance can be permanently promoted (without applied magnetic field due to nonvolatile nature of spin) after magnetization. This work demonstrates that a representative PM/AFM 2D heterostructure, Cr2Te3/CrOOH, is expected to be a high-efficient magnetic heterostructure catalysts for oxygen-evolution.

Accelerating atomistic simulations with piecewise machine-learned ab Initio potentials at a classical force field-like cost.

Recently, machine learning methods have become easy-to-use tools for constructing high-dimensional interatomic potentials with ab initio accuracy. Although machine-learned interatomic potentials are generally orders of magnitude faster than first-principles calculations, they remain much slower than classical force fields, at the price of using more complex structural descriptors. To bridge this efficiency gap, we propose an embedded atom neural network approach with simple piecewise switching function-based descriptors, resulting in a favorable linear scaling with the number of neighbor atoms. Numerical examples validate that this piecewise machine-learning model can be over an order of magnitude faster than various popular machine-learned potentials with comparable accuracy for both metallic and covalent materials, approaching the speed of the fastest embedded atom method (i.e. several µs per atom per CPU core). The extreme efficiency of this approach promises its potential in first-principles atomistic simulations of very large systems and/or in a long timescale.

Analysis and application of RNA binding protein gene pairs to predict the prognosis of gastric cancer.

Background: RNA-binding proteins (RBPs) are closely related to tumors, but little is known about the mechanism of RBPs in tumorigenesis and progression of gastric cancer (GC). As genes do not usually act alone in the pathway deregulation, gene pair combinations are more likely to become stable and accurate biomarkers. The purpose of our research is to establish a novel signature based on RBP gene pairs to predict the prognosis of gastric cancer patients. Methods: We downloaded genetic and clinical information from the TCGA and GEO database. TCGA and GSE13911 were used for screening differentially expressed genes (DEGs). The RBP genes were gathered from previous studies and employed to screen out DE-RBP genes after intersecting with DEGs. Samples were classified according to the relative expression of each pair of DE-RBP genes. The univariate Cox regression analysis and random forest were used to identify hub gene pairs to construct signature for predicting the prognosis of gastric cancer. Time-dependent ROC curves and KM survival curves were performed to evaluate the signature. GSEA was performed in TCGA training cohort and GSE62254 testing cohort to analyze enrichment pathways. Finally, the influence of these gene pairs on the prognosis of GC patients was further elucidated respectively through the combination of high and low expression of the two genes in each hub gene pair. Results: We screened out 6 hub RBP gene pairs (COL5A2/FEN1, POP1/GFRA1, EXO1/PLEKHS1, SLC39A10/CHI3L1, MMP7/PPP1R1 B and SLC5A6/BYSL) to predict the prognosis of patients with gastric cancer. Using the optimal cut-off value to divide patients into high-risk and low-risk groups in the training and testing cohort, we found that the overall survival (OS) of the low-risk group was higher than that of the high-risk group (P < 0.05). The area under the ROC curves for 1, 3, and 5 years were (0.659, 0.744, 0.758) and (0.624, 0.650, 0.653) in two cohorts. Univariate and multivariate Cox regression analysis showed that 6 RBP gene pairs signature were independent prognostic factors for gastric cancer (P < 0.05). In addition, the prognostic survival analysis showed that COL5A2-high/FEN1-low, POP1-low/GFRA1-high, EXO1-low/PLEKHS1-low,SLC39A10-high/CHI3L1-low, MMP7-high/PPP1R1 B-low, SLC5A6-low/BYSL-low had worse OS (P < 0.05). And the gene correlation analysis showed that there was no obvious correlation between the genes in each gene pairs except SLC5A6/BYSL and POP1/GFRA1. Finally, GSEA analysis showed that the high-risk group was enriched in tumor migration, invasion and growth-related pathways. Conclusion: Our study identified a novel 6 RBP gene pairs signature to predict the prognosis of gastric cancer patients and provide potential targets for clinical gene therapy.

Suppressed charge recombination via defect engineering of confined semiconducting quantum dots for photoelectrocatalysis.

Confined semiconducting CuSe quantum dots with abundant Se vacancies are synthesized by pulsed laser deposition with in situ vacuum annealing. With the presence of Se vacancies, the photogenerated charge recombination is suppressed by the self-introduced in-gap trapping states, thus enhancing the photoelectrocatalytic activity under solar illumination.

Interlayer-Confined NiFe Dual Atoms within MoS2 Electrocatalyst for Ultra-Efficient Acidic Overall Water Splitting.

Confining dual atoms (DAs) within the van der Waals gap of 2D layered materials is expected to expedite the kinetic and energetic strength in catalytic process, yet is a huge challenge in atomic-scale precise assembling DAs within two adjacent layers in the 2D limit. Here, an ingenious approach is proposed to assemble DAs of Ni and Fe into the interlayer of MoS2 . While inheriting the exceptional merits of diatomic species, this interlayer-confined structure arms itself with confinement effect, displaying the more favorable adsorption strength on the confined metal active center and higher catalytic activity towards acidic water splitting, as verified by intensive research efforts of theoretical calculations and experimental measurements. Moreover, the interlayer-confined structure also renders metal DAs a protective shelter to survive in harsh acidic environment. The findings embodied the confinement effects at the atom level, and interlayer-confined assembling of multiple species highlights a general pathway to advance interlayer-confined DAs catalysts within various 2D materials.

Prognostic significance of the preoperative hemoglobin to albumin ratio for the short-term survival of gastric cancer patients.

BACKGROUND: Hemoglobin and albumin are associated with the prognosis of gastric cancer (GC) patients. However, the prognostic value of the hemoglobin to albumin ratio (HAR) for the short-term survival of GC patients with D2 radical resection has not been studied. AIM: To investigate the significance of the HAR in evaluating the short-term survival of GC patients after D2 radical resection and to construct a nomogram to predict the prognosis in GC patients after surgery, thus providing a reference for the development of postoperative individualized treatment and follow-up plans. METHODS: Cox regression and Kaplan-Meier analysis was used for prognostic analysis. Logistic regression was used to analyze the relationships between HAR and the clinicopathological characteristics of the GC patients. A prognostic nomogram model for the short-term survival of GC patients was constructed by R software. RESULTS: HAR was an independent risk factor for the short-term survival of GC patients. GC patients with a low HAR had a poor prognosis (P < 0.001). Low HAR was markedly related to high stage [odds ratio (OR) = 0.45 for II vs I; OR = 0.48 for III vs I], T classification (OR = 0.52 for T4 vs T1) and large tumor size (OR = 0.51 for ≥ 4 cm vs < 4 cm) (all P < 0.05). The nomogram model was based on HAR, age, CA19-9, CA125 and stage, and the C-index was 0.820. CONCLUSION: Preoperative low HAR was associated with short-term survival in GC patients. The prognostic nomogram model can accurately predict the short-term survival of GC patients with D2 radical resection.

Current-assisted magnetization reversal in Fe3GeTe2 van der Waals homojunctions.

Among the numerous two-dimensional van der Waals (vdW) magnetic materials, Fe3GeTe2 (FGT), due to its outstanding properties such as metallicity, high Curie temperature and strong perpendicular magnetic anisotropy, has quickly emerged as a candidate with the most potential for the fabrication of all-vdW spintronic devices. Here, we fabricated a simple vertical homojunction based on two few-layer exfoliated FGT flakes. Under a certain range of external magnetic fields, the magnetization reversal can be achieved by applying a negative or positive pulse current, which can reduce the coercivity through the spin orbit torque of FGT itself in addition to the Joule heat. Moreover, the asymmetrical switching current is caused by the spin transfer torque in the homojunction. As the temperature increases, the magnetization reversal can be observed at a smaller external magnetic field. Our demonstrations of the current-assisted magnetization reversal under a magnetic field in all-vdW structures may provide support for the potential application of vdW magnetism.

The Hypoxic Landscape Stratifies Gastric Cancer Into 3 Subtypes With Distinct M6a Methylation and Tumor Microenvironment Infiltration Characteristics.

The interaction between hypoxia and RNA N6-methyladenosine (m6A) is an emerging focus of investigation. However, alterations in m6A modifications at distinct hypoxia levels remain uncharacterized in gastric cancer (GC). Unsupervised hierarchical clustering was performed to stratify samples into different clusters. Differentially expressed gene analysis, univariate Cox proportional hazards regression analysis, and hazard ratio calculations were used to establish an m6A score to quantify m6A regulator modification patterns. After using an algorithm integrating Least absolute shrinkage and selection operator (LASSO) and bootstrapping, we identified the best candidate predictive genes. Thence, we established an m6A-related hypoxia pathway gene prognostic signature and built a nomogram to evaluate its predictive ability. The area under the curve (AUC) value of the nomogram was 0.811, which was higher than that of the risk score (AUC=0.695) and stage (AUC=0.779), suggesting a high credibility of the nomogram. Furthermore, the clinical response of anti-PD-1/CTLA-4 immunotherapy between high- and low-risk patients showed a significant difference. Our study successfully explored a brand-new GC pathological classification based on hypoxia pathway genes and the quantification of m6A modification patterns. Comprehensive immune analysis and validation demonstrated that hypoxia clusters were reliable, and our signature could provide a new approach for clinical decision-making and immunotherapeutic strategies for GC patients.

Nine-long non-coding ribonucleic acid signature can improve the survival prediction of colorectal cancer.

BACKGROUND: Investigating molecular biomarkers that accurately predict prognosis is of considerable clinical significance. Accumulating evidence suggests that long non-coding ribonucleic acids (lncRNAs) are frequently aberrantly expressed in colorectal cancer (CRC). AIM: To elucidate the prognostic function of multiple lncRNAs serving as biomarkers in CRC. METHODS: We performed lncRNA expression profiling using the lncRNA mining approach in large CRC cohorts from The Cancer Genome Atlas (TCGA) database. Receiver operating characteristic analysis was performed to identify the optimal cutoff point at which patients could be classified into the high-risk or low-risk groups. Based on the Cox coefficient of the individual lncRNAs, we identified a nine-lncRNA signature that was associated with the survival of CRC patients in the training set (n = 175). The prognostic value of this nine-lncRNA signature was validated in the testing set (n = 174) and TCGA set (n = 349). The prognostic models, consisting of these nine CRC-specific lncRNAs, performed well for risk stratification in the testing set and TCGA set. Time-dependent receiver operating characteristic analysis indicated that this predictive model had good performance. RESULTS: Multivariate Cox regression and stratification analysis demonstrated that this nine-lncRNA signature was independent of other clinical features in predicting overall survival. Functional enrichment analysis of Kyoto Encyclopedia of Genes and Genomes pathways and Gene Ontology terms further indicated that these nine prognostic lncRNAs were closely associated with carcinogenesis-associated pathways and biological functions in CRC. CONCLUSION: A nine-lncRNA expression signature was identified and validated that could improve the prognosis prediction of CRC, thereby providing potential prognostic biomarkers and efficient therapeutic targets for patients with CRC.

Predictors of lymph-node metastasis in surgically resected T1 colorectal cancer in Western populations.

BACKGROUND: The risk of lymph-node metastasis (LNM) in T1 colorectal cancer (CRC) has not been well documented in heterogeneous Western populations. This study investigated the predictors of LNM and the long-term outcomes of patients by analysing T1 CRC surgical specimens and patients' demographic data. METHODS: Patients with surgically resected T1 CRC between 2004 and 2014 were identified from the Surveillance, Epidemiology, and End Results (SEER) database. Patients with multiple primary cancers, with neoadjuvant therapy, or without a confirmed histopathological diagnosis were excluded. Multivariate logistic-regression analysis was used to identify the predictors of LNM. RESULTS: Of the 22,319 patients, 10.6% had a positive lymph-node status based on the final pathology (nodal category: N1 9.6%, N2 1.0%). Younger age, female sex, Asian or African-American ethnicity, poor differentiation, and tumor site outside the rectum were significantly associated with LNM. Subgroup analyses for patients stratified by tumor site suggested that the rate of positive lymph-node status was the lowest in the rectum (hazard ratio: 0.74; 95% confidence interval: 0.63-0.86). CONCLUSION: The risk of LNM was potentially lower in Caucasian patients than in API or African-American patients with surgically resected T1 CRC. Regarding the T1 CRC site, the rectum was associated with a lower risk of LNM.

Large Tunneling Magnetoresistance in van der Waals Ferromagnet/Semiconductor Heterojunctions.

2D layered chalcogenide semiconductors have been proposed as a promising class of materials for low-dimensional electronic, optoelectronic, and spintronic devices. Here, all-2D van der Waals vertical spin-valve devices, that combine the 2D layered semiconductor InSe as a spacer with the 2D layered ferromagnetic metal Fe3 GeTe2 as spin injection and detection electrodes, are reported. Two distinct transport behaviors are observed: tunneling and metallic, which are assigned to the formation of a pinhole-free tunnel barrier at the Fe3 GeTe2 /InSe interface and pinholes in the InSe spacer layer, respectively. For the tunneling device, a large magnetoresistance (MR) of 41% is obtained under an applied bias current of 0.1 µA at 10 K, which is about three times larger than that of the metallic device. Moreover, the tunneling device exhibits a lower operating bias current but a more sensitive bias current dependence than the metallic device. The MR and spin polarization of both the metallic and tunneling devices decrease with increasing temperature, which can be fitted well by Bloch's law. These findings reveal the critical role of pinholes in the MR of all-2D van der Waals ferromagnet/semiconductor heterojunction devices.

Efficient and Accurate Simulations of Vibrational and Electronic Spectra with Symmetry-Preserving Neural Network Models for Tensorial Properties.

Machine learning has revolutionized the high-dimensional representations for molecular properties such as potential energy. However, there are scarce machine learning models targeting tensorial properties, which are rotationally covariant. Here, we propose tensorial neural network (NN) models to learn both tensorial response and transition properties in which atomic coordinate vectors are multiplied with scalar NN outputs or their derivatives to preserve the rotationally covariant symmetry. This strategy keeps structural descriptors symmetry invariant so that the resulting tensorial NN models are as efficient as their scalar counterparts. We validate the performance and universality of this approach by learning response properties of water oligomers and liquid water and transition dipole moment of a model structural unit of proteins. Machine-learned tensorial models have enabled efficient simulations of vibrational spectra of liquid water and ultraviolet spectra of realistic proteins, promising feasible and accurate spectroscopic simulations for biomolecules and materials.

Activation of P2×7 Receptor Promotes the Invasion and Migration of Colon Cancer Cells via the STAT3 Signaling.

The pathological mechanism of colon cancer is very complicated. Therefore, exploring the molecular basis of the pathogenesis of colon cancer and finding a new therapeutic target has become an urgent problem to be solved in the treatment of colon cancer. ATP plays an important role in regulating the progression of tumor cells. P2 × 7 belongs to ATP ion channel receptor, which is involved in the progression of tumors. In this study, we explored the effect and molecular mechanism of ATP-mediated P2 × 7 receptor on the migration and metastasis of colon cancer cells. The results showed that ATP and BzATP significantly increased the inward current and intracellular calcium concentration of LOVO and SW480 cells, while the use of antagonists (A438079 and AZD9056) could reverse the above phenomenon. We found that ATP promoted the migration and invasion of LOVO and SW480 cells and is dose-dependent on ATP concentration (100-300 µM). Similarly, BzATP (10, 50, and 100 µM) also significantly promoted the migration and invasion of colon cancer cells in a concentration-dependent manner. While P2 × 7 receptor antagonists [A438079 (10 µM), AZD9056 (10 µM)] or P2 × 7 siRNA could significantly inhibit ATP-induced colon cancer cell migration and invasion. Moreover, in vivo experiments showed that ATP-induced activation of P2 × 7 receptor promoted the growth of tumors. Furthermore, P2 × 7 receptor activation down-regulated E-cadherin protein expression and up-regulated MMP-2 mRNA and concentration levels. Knocking down the expression of P2 × 7 receptor could significantly inhibit the increase in the expression of N-cadherin, Vimentin, Zeb1, and Snail induced by ATP. In addition, ATP time-dependently induced the activation of STAT3 via the P2 × 7 receptor, and the STAT3 pathway was required for the ATP-mediated invasion and migration. Our conclusion is that ATP-induced P2 × 7 receptor activation promotes the migration and invasion of colon cancer cells, possibly via the activation of STAT3 pathway. Therefore, the P2 × 7 receptor may be a potential target for the treatment of colon cancer.

Identification of key genes controlling cancer stem cell characteristics in gastric cancer.

BACKGROUND: Self-renewal of gastric cancer stem cells (GCSCs) is considered to be the underlying cause of the metastasis, drug resistance, and recurrence of gastric cancer (GC). AIM: To characterize the expression of stem cell-related genes in GC. METHODS: RNA sequencing results and clinical data for gastric adenoma and adenocarcinoma samples were obtained from The Cancer Genome Atlas database, and the results of the GC mRNA expression-based stemness index (mRNAsi) were analyzed. Weighted gene coexpression network analysis was then used to find modules of interest and their key genes. Survival analysis of key genes was performed using the online tool Kaplan-Meier Plotter, and the online database Oncomine was used to assess the expression of key genes in GC. RESULTS: mRNAsi was significantly upregulated in GC tissues compared to normal gastric tissues (P < 0.0001). A total of 16 modules were obtained from the gene coexpression network; the brown module was most positively correlated with mRNAsi. Sixteen key genes (BUB1, BUB1B, NCAPH, KIF14, RACGAP1, RAD54L, TPX2, KIF15, KIF18B, CENPF, TTK, KIF4A, SGOL2, PLK4, XRCC2, and C1orf112) were identified in the brown module. The functional and pathway enrichment analyses showed that the key genes were significantly enriched in the spindle cellular component, the sister chromatid segregation biological process, the motor activity molecular function, and the cell cycle and homologous recombination pathways. Survival analysis and Oncomine analysis revealed that the prognosis of patients with GC and the expression of three genes (RAD54L, TPX2, and XRCC2) were consistently related. CONCLUSION: Sixteen key genes are primarily associated with stem cell self-renewal and cell proliferation characteristics. RAD54L, TPX2, and XRCC2 are the most likely therapeutic targets for inhibiting the stemness characteristics of GC cells.

Effect of P2X7 receptor on tumorigenesis and its pharmacological properties.

The occurrence and development of tumors is a multi-factor, multi-step, multi-gene pathological process, and its treatment has been the most difficult problem in the field of medicine today. Therefore, exploring the relevant factors involved in the pathogenesis of tumors, improving the diagnostic rate, treatment rate, and prognosis survival rate of tumors have become an urgent problem to be solved. A large number of studies have shown that the P2X7 receptor (P2X7R) and the tumor microenvironment play an important role in regulating the growth, apoptosis, migration and invasion of tumor cells. P2X7R is an ATP ligand-gated cationic channel receptor, which exists in most tissues of the human body. The main function of P2X7R is to regulate the relevant cells (such as macrophages, lymphocytes, and glial cells) to release damaging factors and induce apoptosis and cell death. In recent years, with continuous research and exploration of P2X7R, it has been found that P2X7R exists on the surface of most tumor cells and plays an important role in tumor pathogenesis. The activation of the P2X7R can open the ion channels on the tumor cell membrane (sodium ion, calcium ion influx and potassium ion outflow), trigger rearrangement of the cytoskeleton and changes in membrane fluidity, allow small molecule substances to enter the cell, activate enzymes and kinases in related signaling pathways in cells (such as PKA, PKC, ERK1/2, AKT, and JNK), thereby affecting the development of tumor cells, and can also indirectly affect the growth, apoptosis and migration of tumor cells through tumor microenvironment. At present, P2X7R has been widely recognized for its important role in tumorigenesis and development. In this paper, we give a comprehensive description of the structure and function of the P2X7R gene. We also clarified the concept of tumor microenvironment and its effect on tumors, discussed the relevant pathological mechanisms in the development of tumors, and revealed the intrinsic relationship between P2X7R and tumors. We explored the pharmacological properties of P2X7R antagonists or inhibitors in reducing its expression as targeted therapy for tumors.