Geological suitability of natural sponge body for the construction of sponge city——a case study of Shuanghe Lake district in Zhengzhou airport zone

Natural and geological environmental conditions have an important impact on the planning and construction of sponge cities.This paper analyzes geological factors that influence the usage of natural sponge bodies,taking the Shuanghe lake district of Zhengzhou airport zone as an example.An evaluation system with seven factors has been established and the weights of these factors are determined using the analytic hierarchy process(AHP)method.Overlay analysis is then carried out on all factors using GIS to evaluate the geological suitability of the construction of the sponge city.The results show that geologically suitable area for city construction in Shuanghe lake district accounts for 12.3%,relatively suitable area accounts for 76.1%,and relatively unsuitable area accounts for 11.6%.For suitable and relatively suitable areas,we should make full use of the advantages of surface infiltration,vadose zone transportation and aquifer storage to build a sponge city infrastructure with geological engineering as the main component,supplemented by engineering measures such as surface water storage and drainage,and jointly establish a sustainable urban hydrological cycle.For less suitable areas,artificial rain and flood control works,such as roof garden,should be considered.The findings of this paper can serve as an important reference for sponge city planning and construction not only in the research area but also in other regions with similar geological conditions.

Self‑Assembly of Binderless MXene Aerogel for Multiple‑Scenario and Responsive Phase Change Composites with Ultrahigh Thermal Energy Storage Density and Exceptional Electromagnetic Interference Shielding

The severe dependence of traditional phase change materials(PCMs)on the temperature-response and lattice deficiencies in versatility cannot satisfy demand for using such materials in complex application scenarios.Here,we introduced metal ions to induce the self-assembly of MXene nanosheets and achieve their ordered arrangement by combining suction filtration and rapid freezing.Subsequently,a series of MXene/K^(+)/paraffin wax(PW)phase change composites(PCCs)were obtained via vacuum impregnation in molten PW.The prepared MXene-based PCCs showed versatile applications from macroscale technologies,successfully transforming solar,electric,and magnetic energy into thermal energy stored as latent heat in the PCCs.Moreover,due to the absence of binder in the MXene-based aerogel,MK3@PW exhibits a prime solar-thermal conversion efficiency(98.4%).Notably,MK3@PW can further convert the collected heat energy into electric energy through thermoelectric equipment and realize favorable solar-thermal-electric conversion(producing 206 mV of voltage with light radiation intensity of 200 mw cm^(−2)).An excellent Joule heat performance(reaching 105℃with an input voltage of 2.5 V)and responsive magnetic-thermal conversion behavior(a charging time of 11.8 s can achieve a thermal insulation effect of 285 s)for contactless thermotherapy were also demonstrated by the MK3@PW.Specifically,as a result of the ordered arrangement of MXene nanosheet self-assembly induced by potassium ions,MK3@PW PCC exhibits a higher electromagnetic shielding efficiency value(57.7 dB)than pure MXene aerogel/PW PCC(29.8 dB)with the same MXene mass.This work presents an opportunity for the multi-scene response and practical application of PCMs that satisfy demand of next-generation multifunctional PCCs.

Edaravone-loaded poly(amino acid) nanogel inhibits ferroptosis for neuroprotection in cerebral ischemia injury

Neurological injury caused by ischemic stroke is a major cause of permanent disability and death. The currently available neuroprotective drugs fail to achieve desired therapeutic efficacy mainly due to short circulation half-life and poor blood−brain barrier (BBB) permeability. For that, an edaravone-loaded pH/glutathione (pH/GSH) dual-responsive poly(amino acid) nanogel (NG/EDA) was developed to improve the neuroprotection of EDA. The nanogel was triggered by acidic and EDA-induced high-level GSH microenvironments, which enabled the selective and sustained release of EDA at the site of ischemic injury. NG/EDA exhibited a uniform sub-spherical morphology with a mean hydrodynamic diameter of 112.3 ± 8.2 nm. NG/EDA efficiently accumulated at the cerebral ischemic injury site of permanent middle cerebral artery occlusion (pMCAO) mice, showing an efficient BBB crossing feature. Notably, NG/EDA with 50 µM EDA significantly increased neuron survival (29.3%) following oxygen and glucose deprivation by inhibiting ferroptosis. In addition, administering NG/EDA for 7 d significantly reduced infarct volume to 22.2% ± 7.2% and decreased neurobehavioral scores from 9.0 ± 0.6 to 2.0 ± 0.8. Such a pH/GSH dual-responsive nanoplatform might provide a unique and promising modality for neuroprotection in ischemic stroke and other central nervous system diseases.

Long-term prognosis and its associated predictive factors in patients with eosinophilic gastroenteritis

BACKGROUND Eosinophilic gastroenteritis(EGE)is a chronic recurrent disease with abnormal eosinophilic infiltration in the gastrointestinal tract.Glucocorticoids remain the most common treatment method.However,disease relapse and glucocorticoid dependence remain notable problems.To date,few studies have illuminated the prognosis of EGE and risk factors for disease relapse.AIM To describe the clinical characteristics of EGE and possible predictive factors for disease relapse based on long-term follow-up.METHODS This was a retrospective cohort study of 55 patients diagnosed with EGE admitted to one medical center between 2013 and 2022.Clinical records were collected and analyzed.Kaplan-Meier curves and log-rank tests were conducted to reveal the risk factors for long-term relapse-free survival(RFS).RESULTS EGE showed a median onset age of 38 years and a slight female predominance(56.4%).The main clinical symptoms were abdominal pain(89.1%),diarrhea(61.8%),nausea(52.7%),distension(49.1%)and vomiting(47.3%).Forty-three(78.2%)patients received glucocorticoid treatment,and compared with patients without glucocorticoid treatments,they were more likely to have elevated serum immunoglobin E(IgE)(86.8%vs 50.0%,P=0.022)and descending duodenal involvement(62.8%vs 27.3%,P=0.046)at diagnosis.With a median follow-up of 67 mo,all patients survived,and 56.4%had at least one relapse.Six variables at baseline might have been associated with the overall RFS rate,including age at diagnosis<40 years[hazard ratio(HR)2.0408,95%confidence interval(CI):1.0082–4.1312,P=0.044],body mass index(BMI)>24 kg/m^(2)(HR 0.3922,95%CI:0.1916-0.8027,P=0.014),disease duration from symptom onset to diagnosis>3.5 mo(HR 2.4725,95%CI:1.220-5.0110,P=0.011),vomiting(HR 3.1259,95%CI:1.5246-6.4093,P=0.001),total serum IgE>300 KU/L at diagnosis(HR 0.2773,95%CI:0.1204-0.6384,P=0.022)and glucocorticoid treatment(HR 6.1434,95%CI:2.8446-13.2676,P=0.003).CONCLUSION In patients with EGE,younger onset age,longer disease course,vomiting and glucocorticoid treatment were risk factors for disease relapse,whereas higher BMI and total IgE level at baseline were protective.

Using MsfNet to Predict the ISUP Grade of Renal Clear Cell Carcinoma in Digital Pathology Images

Clear cell renal cell carcinoma(ccRCC)represents the most frequent form of renal cell carcinoma(RCC),and accurate International Society of Urological Pathology(ISUP)grading is crucial for prognosis and treatment selection.This study presents a new deep network called Multi-scale Fusion Network(MsfNet),which aims to enhance the automatic ISUP grade of ccRCC with digital histopathology pathology images.The MsfNet overcomes the limitations of traditional ResNet50 by multi-scale information fusion and dynamic allocation of channel quantity.The model was trained and tested using 90 Hematoxylin and Eosin(H&E)stained whole slide images(WSIs),which were all cropped into 320×320-pixel patches at 40×magnification.MsfNet achieved a micro-averaged area under the curve(AUC)of 0.9807,a macro-averaged AUC of 0.9778 on the test dataset.The Gradient-weighted Class Activation Mapping(Grad-CAM)visually demonstrated MsfNet’s ability to distinguish and highlight abnormal areas more effectively than ResNet50.The t-Distributed Stochastic Neighbor Embedding(t-SNE)plot indicates our model can efficiently extract critical features from images,reducing the impact of noise and redundant information.The results suggest that MsfNet offers an accurate ISUP grade of ccRCC in digital images,emphasizing the potential of AI-assisted histopathological systems in clinical practice.

Identification of different degrees of processed ginger using GC-IMS combined with machine learning

Ginger,the rhizomes of Zingiber officinale Roscoe,was a wellknown edible plant species commonly used in China,which has pungent flavor[1].Ginger has numerous chemical compounds,such as phenolic constituents,volatile compounds(VOCs),and polysaccharides[2].Among them,VOCs are considered one of the effective compounds in ginger due to their functional properties,including anti-inflammatory,antioxidant,and analgesic[3].

Interception of Layered LP-N and HLP-N at Ambient Conditions by Confined Template

We propose a feasible strategy of intercepting the layered polymeric nitrogen(LP-N)and hexagonal layered polymeric nitrogen(HLP-N)at ambient conditions by using the confinement templates.The stable mechanism of confined LP-N and HLP-N at ambient conditions is revealed.

Systematical High-Pressure Study of Praseodymium Nitrides in N-Rich Region

We investigate high-pressure phase diagrams of Pr–N compounds by proposing five stable structures(PnmaPr N,Ⅰ4/mmm-PrN_(2),C2/m-PrN_(3),P■-PrN_(4),and R3-PrN_(8))and two metastable structures(P■-PrN_(6)and P■-PrN_(10)).The P■-PrN_(6)with the N14-ring layer and R3-PrN_(8)with the N18-ring layer can be quenched to ambient conditions.For the P■-PrN_(10),the N_(22)-ring layer structure transfers into infinite chains with the pressure quenched to ambient pressure.Remarkably,a novel polynitrogen h R8-N designed by the excision of Pr atoms from R3-PrN_(8)is obtained and can be quenched to ambient conditions.The N-rich structures of P■-PrN_(6),R3-PrN_(8),c-PrN_(10)and the solid pure nitrogen structure exhibit outstanding properties of energy density and explosive performance.

Finite Element Method Simulation of Wellbore Stability under Different Operating and Geomechanical Conditions

The variation of the principal stress of formations with the working and geo-mechanical conditions can trigger wellbore instabilities and adversely affect the well completion.A finite element model,based on the theory of poro-elasticity and the Mohr-Coulomb rock damage criterion,is used here to analyze such a risk.The changes in wellbore stability before and after reservoir acidification are simulated for different pressure differences.The results indicate that the risk of wellbore instability grows with an increase in the production-pressure difference regardless of whether acidification is completed or not;the same is true for the instability area.After acidizing,the changes in the main geomechanical parameters(i.e.,elastic modulus,Poisson’s ratio,and rock strength)cause the maximum wellbore instability coefficient to increase.

Exponential Time Differencing Method for a Reaction-Diffusion System with Free Boundary

For reaction-diffusion equations in irregular domains with moving boundaries,the numerical stability constraints from the reaction and diffusion terms often require very restricted time step sizes,while complex geometries may lead to difficulties in the accuracy when discretizing the high-order derivatives on grid points near the boundary.It is very challenging to design numerical methods that can efficiently and accurately handle both difficulties.Applying an implicit scheme may be able to remove the stability constraints on the time step,however,it usually requires solving a large global system of nonlinear equations for each time step,and the computational cost could be significant.Integration factor(IF)or exponential time differencing(ETD)methods are one of the popular methods for temporal partial differential equations(PDEs)among many other methods.In our paper,we couple ETD methods with an embedded boundary method to solve a system of reaction-diffusion equations with complex geometries.In particular,we rewrite all ETD schemes into a linear combination of specificФ-functions and apply one state-of-the-art algorithm to compute the matrix-vector multiplications,which offers significant computational advantages with adaptive Krylov subspaces.In addition,we extend this method by incorporating the level set method to solve the free boundary problem.The accuracy,stability,and efficiency of the developed method are demonstrated by numerical examples.

Protein succinylation,hepatic metabolism,and liver diseases

Succinylation is a highly conserved post-translational modication that is processed via enzymatic and non-enzymatic mechanisms.Succinylation exhibits strong effects on protein stability,enzyme activity,and transcriptional regulation.Protein succinylation is extensively present in the liver,and increasing evidence has demonstrated that succinylation is closely related to hepatic metabolism.For instance,histone acetyltransferase 1 promotes liver glycolysis,and the sirtuin 5-induced desuccinylation is involved in the regulation of the hepatic urea cycle and lipid metabolism.Therefore,the effects of succinylation on hepatic glucose,amino acid,and lipid metabolism under the action of various enzymes will be discussed in this work.In addition,how succinylases regulate the progression of different liver diseases will be reviewed,including the desuccinylation activity of sirtuin 7,which is closely associated with fatty liver disease and hepatitis,and the actions of lysine acetyltransferase 2A and histone acetyltransferase 1 that act as succinyltransferases to regulate the succinylation of target genes that influence the development of hepatocellular carcinoma.In view of the diversity and significance of protein succinylation,targeting the succinylation pathway may serve as an attractive direction for the treatment of liver diseases.

Discussion on the Ideological and Political Education for Poor College Students

At present,ideological and political education is significant for poor college students.The focus of funding for poor students has gradually transformed from providing economic support for them to ideological and spiritual help,which puts forward higher requirements on how to carry out ideological and political work.It also requires us to advance the work of ideological and moral education and put it in the most important position in the ideological and educational work for poor college students.Combined with the reality of poor college students,we will adhere to the idea of being student-oriented and endeavor to enhance the effectiveness,pertinence,and relevance of the work of ideological and political education.This paper analyzes the significance and problems of ideological and political education for poor college students and puts forward effective ways to solve the problems from the levels of ideology,cognition,and teaching staff.

BODIPY荧光探针的合成及次氯酸检测的综合实验

有机实验和仪器分析实验是本科生阶段化学教学的重点内容,虽然现有的教学实验内容已十分丰富与完善,但缺少两者之间的融合以及与科研领域的联系。针对上述不足,我们将科学研究前沿和热点的荧光检测技术引入教学实践。实验通过对BODIPY (氟硼二吡咯)荧光染料结构的设计改良,合成一种具有快速响应、选择性高和灵敏度好的新型次氯酸荧光探针,对荧光探针结构进行表征,并测定荧光探针的荧光性质。通过对探针结构与荧光性质之间关系的研究,有助于加深学生荧光发光原理的理解。实验内容涵盖有机合成、产物仪器表征、光谱分析等方面,综合性强且易于学生操作。教学实践过程有助于培养学生的科学思维、理论与实践相结合的能力。

1例碘美普尔肾损伤致依诺肝素严重肝损伤病例的药学实践

1例67岁的男性肺腺癌合并心力衰竭患者在使用碘美普尔后出现急性肾损伤(血清肌酐149μmol·L^(-1),尿素氮13.23 mmol·L^(-1),尿酸439μmol·L^(-1))和严重肝损伤(丙氨酸氨基转移酶592 U·L^(-1),天冬氨酸氨基转移酶782 U·L^(-1),γ-谷氨酰转移酶121 U·L^(-1))。通过用药分析,药师判断该患者使用碘美普尔对比剂后引发急性肾损伤,导致依诺肝素钠在体内蓄积,继发严重肝损伤。药师建议观察肾功能变化并停用依诺肝素钠、暂停甲磺酸阿美替尼,此后患者肝肾功能均恢复正常。该病例提示对于具有对比剂肾病高危因素的患者,使用对比剂后可能出现急性肾损伤,引起药物蓄积性不良反应。对这类患者药师应做好药学监护,发生不良反应后及时进行用药分析和充分的临床评估,协助医生调整治疗方案。

High expression of PD-L1 mainly occurs in non-small cell lung cancer patients with squamous cell carcinoma or poor differentiation

Background:Lung cancer is one of the most lethal cancers worldwide,but studies have shown that the higher the expression of programmed cell death protein 1 ligand 1(PD-L1)in non-small cell lung cancer(NSCLC),the more likely it will benefit from anti-PD-L1 immunotherapy.The purpose of our study was to collect and analyze abundant clinical samples in order to provide evidence for clinicians and patients who might consider anti-PD-L1 immunotherapy while jointly formulating treatment plans.Methods:On the one hand,we obtained cases from The Cancer Genome Atlas(TCGA)database,including 498 lung squamous cell cancer(LUSC)patients and 515 lung adenocarcinoma(LUAD)patients.We studied the lung caner driver gene in LUSC and LUAD.On the other hand,PD-L1 expression was detected in lung cancer tissues of 1,008 NSCLC patients with immunohistochemistry staining(IHC),and we studied the correlation between PD-L1 protein expression and clinicopathological characteristics.Results:PD-L1 expression was higher in LUSC than in LUAD at the mRNA level.In univariate analysis,PD-L1 expression at the protein level was higher in patients who were males,were LUSC,were smokers,had a tumor diameter>3 cm,had poor differentiation,or had stages Ⅲ-Ⅳ disease.In multivariate analysis,PD-L1 expression was higher in patients who were LUSC or in poor differentiation.Conclusion:In term of protein level,PD-L1 expression was higher in NSCLC patients who were LUSC or in poor differentiation.We recommend that PD-L1 IHC detection can be routinely performed in such populations that are likely to benefit most from PD-L1 immunotherapy.

Residual Feature Attentional Fusion Network for Lightweight Chest CT Image Super-Resolution

The diagnosis of COVID-19 requires chest computed tomography(CT).High-resolution CT images can provide more diagnostic information to help doctors better diagnose the disease,so it is of clinical importance to study super-resolution(SR)algorithms applied to CT images to improve the reso-lution of CT images.However,most of the existing SR algorithms are studied based on natural images,which are not suitable for medical images;and most of these algorithms improve the reconstruction quality by increasing the network depth,which is not suitable for machines with limited resources.To alleviate these issues,we propose a residual feature attentional fusion network for lightweight chest CT image super-resolution(RFAFN).Specifically,we design a contextual feature extraction block(CFEB)that can extract CT image features more efficiently and accurately than ordinary residual blocks.In addition,we propose a feature-weighted cascading strategy(FWCS)based on attentional feature fusion blocks(AFFB)to utilize the high-frequency detail information extracted by CFEB as much as possible via selectively fusing adjacent level feature information.Finally,we suggest a global hierarchical feature fusion strategy(GHFFS),which can utilize the hierarchical features more effectively than dense concatenation by progressively aggregating the feature information at various levels.Numerous experiments show that our method performs better than most of the state-of-the-art(SOTA)methods on the COVID-19 chest CT dataset.In detail,the peak signal-to-noise ratio(PSNR)is 0.11 dB and 0.47 dB higher on CTtest1 and CTtest2 at×3 SR compared to the suboptimal method,but the number of parameters and multi-adds are reduced by 22K and 0.43G,respectively.Our method can better recover chest CT image quality with fewer computational resources and effectively assist in COVID-19.

Multi-Classification of Polyps in Colonoscopy Images Based on an Improved Deep Convolutional Neural Network

Achieving accurate classification of colorectal polyps during colonoscopy can avoid unnecessary endoscopic biopsy or resection.This study aimed to develop a deep learning model that can automatically classify colorectal polyps histologically on white-light and narrow-band imaging(NBI)colonoscopy images based on World Health Organization(WHO)and Workgroup serrAted polypS and Polyposis(WASP)classification criteria for colorectal polyps.White-light and NBI colonoscopy images of colorectal polyps exhibiting pathological results were firstly collected and classified into four categories:conventional adenoma,hyperplastic polyp,sessile serrated adenoma/polyp(SSAP)and normal,among which conventional adenoma could be further divided into three sub-categories of tubular adenoma,villous adenoma and villioustublar adenoma,subsequently the images were re-classified into six categories.In this paper,we proposed a novel convolutional neural network termed Polyp-DedNet for the four-and six-category classification tasks of colorectal polyps.Based on the existing classification network ResNet50,Polyp-DedNet adopted dilated convolution to retain more high-dimensional spatial information and an Efficient Channel Attention(ECA)module to improve the classification performance further.To eliminate gridding artifacts caused by dilated convolutions,traditional convolutional layers were used instead of the max pooling layer,and two convolutional layers with progressively decreasing dilation were added at the end of the network.Due to the inevitable imbalance of medical image data,a regularization method DropBlock and a Class-Balanced(CB)Loss were performed to prevent network overfitting.Furthermore,the 5-fold cross-validation was adopted to estimate the performance of Polyp-DedNet for the multi-classification task of colorectal polyps.Mean accuracies of the proposed Polyp-DedNet for the four-and six-category classifications of colorectal polyps were 89.91%±0.92%and 85.13%±1.10%,respectively.The metrics of precision,recall and F1-score were also improved by 1%∼2%compared to the baseline ResNet50.The proposed Polyp-DedNet presented state-of-the-art performance for colorectal polyp classifying on white-light and NBI colonoscopy images,highlighting its considerable potential as an AI-assistant system for accurate colorectal polyp diagnosis in colonoscopy.

Acinous cell AR42J-derived exosome miR125b-5p promotes acute pancreatitis exacerbation by inhibiting M2 macrophage polarization via PI3K/AKT signaling pathway

BACKGROUND The incidence rate of acute pancreatitis(AP), which is a pathophysiological process with complex etiology, is increasing globally. miR-125b-5p, a bidirectional regulatory miRNA, is speculated to exhibit anti-tumor activity. However,exosome-derived miR-125b-5p in AP has not been reported.AIM To elucidate the molecular mechanism of exosome-derived miR-125b-5p promoting AP exacerbation from the perspective of the interaction between immune cells and acinar cells.METHODS Exosomes derived from AR42J cells were isolated and extracted in active and inactive states by an exosome extraction kit, and were verified via transmission electron microscopy, nanoparticle tracking analysis, and western blotting. RNA sequencing assay technology was used to screen differentially expressed miRNAs in active and inactive AR42J cell lines, and bioinformatics analysis was used to predict downstream target genes of miR-125b-5p. The expression level of miR-125b-5p and insulin-like growth factor 2(IGF2) in the activated AR42J cell line and AP pancreatic tissue were detected by quantitative real-time polymerase chain reaction and western blots. The changes in the pancreatic inflammatory response in a rat AP model were detected by histopathological methods. Western Blot was used to detect the expression of IGF2, PI3K/AKT signaling pathway proteins, and apoptosis and necrosis related proteins.RESULTS miR-125b-5p expression was upregulated in the activated AR42J cell line and AP pancreatic tissue,while that of IGF2 was downregulated. In vitro experiments confirmed that miR-125b-5p could promote the death of activated AR42J cells by inducing cell cycle arrest and apoptosis. In addition,miR-125b-5p was found to act on macrophages to promote M1 type polarization and inhibit M2type polarization, resulting in a massive release of inflammatory factors and reactive oxygen species accumulation. Further research found that miR-125b-5p could inhibit the expression of IGF2 in the PI3K/AKT signaling pathway. Additionally, in vivo experiments revealed that miR-125b-5p can promote the progression of AP in a rat model.CONCLUSION miR-125b-5p acts on IGF2 in the PI3K/AKT signaling pathway and promotes M1 type polarization and inhibits M2 type polarization of macrophage by inhibiting IGF2 expression, resulting in a large release of pro-inflammatory factors and an inflammatory cascade amplification effect, thus aggravating AP.

Joint computation offloading and resource allocation in vehicular edge computing networks

Vehicular Edge Computing(VEC)is a promising technique to accommodate the computation-intensive and delaysensitive tasks through offloading the tasks to the RoadSide-Unit(RSU)equipped with edge computing servers or neighboring vehicles.Nevertheless,the limited computation resources of edge computing servers and the mobility of vehicles make the offloading policy design very challenging.In this context,through considering the potential transmission gains brought by the mobility of vehicles,we propose an efficient computation offloading and resource allocation scheme in VEC networks with two kinds of offloading modes,i.e.,Vehicle to Vehicle(V2V)and Vehicle to RSU(V2R).We define a new cost function for vehicular users by incorporating the vehicles’offloading delay,energy consumption,and expenses with a differentiated pricing strategy,as well as the transmission gain.An optimization problem is formulated to minimize the average cost of all the task vehicles under the latency and computation capacity constraints.A distributed iterative algorithm is proposed by decoupling the problem into two subproblems for the offloading mode selection and the resource allocation.Matching theorybased and Lagrangian-based algorithms are proposed to solve the two subproblems,respectively.Simulation results show the proposed algorithm achieves low complexity and significantly improves the system performance compared with three benchmark schemes.

Pressure-induced structural transition and low-temperature recovery of sodium pentazolate

Pentazolate compounds have attracted extensive attention as high energy density materials.The synthesis and recovery of pentazolate compounds is of great importance for their potential applications.Here,we report the synthesis of Pmn2_(1)-NaN_(5)and Pm-Na_(2)N_(5)through compressing and laser heating pure NaN_(3)at~60 GPa.Upon decompression,the pressureinduced structural transition from Pmn2_(1)-NaN_(5)into Cm-NaN_(5)is observed in the pressure range of 14-23 GPa for the first time.The cyclo-N_(5)^(-)can be traced down to 4.7 GPa at room temperature and recovered to ambient pressure under low temperature condition(up to 160 K).The Pm-Na_(2)N_(5)is suggested to decompose into the P4/mmm-NaN_(2)at 23 GPa,and be stable at ambient conditions.This work provides insight into the high-pressure behaviors of pentazolate compounds and an alternative way to stabilize energetic polynitrogen compounds.