A Meta-Analysis of the Prognostic and Clinicopathological Significance of circZFR in Human Gastrointestinal Cancers

Background: Studies of gastrointestinal (GIT) cancers have shown that circZFR could be involved in the development and progression of various GIT cancers. However, small sample sizes limit the clinical significance of these studies. Here, a meta-analysis was conducted to ascertain the actual involvement of circZFR in the development and prognosis of GIT cancers. Methods: PubMed, Embase, Web of Science, and the Cochrane Library were searched up to December 31, 2023. Hazard ratios (HRs) or odds ratios (ORs) with 95% confidence intervals (CIs) were pooled to evaluate the association between circZFR expression and overall survival (OS). Publication bias was measured using the funnel plot and Egger’s test. Results: 10 studies having 659 participants were enrolled for meta-analysis. High circZFR expression was associated with poor OS (HR = 1.4, 95% CI: 1.20, 1.70). High circZFR expression also predicted larger tumor size (OR = 4.38, 95% CI 2.65, 7.25), advanced clinical stage (OR = 5.33, 95% CI 3.10, 9.16), and tendency for distant metastasis (OR = 2.89, 95% CI: 1.62, 5.11), but was not related to age, gender, and histological grade. Conclusions: In summary, high circZFR expression was associated with poor OS, larger tumor size, advanced stage cancer and tendency for distant metastasis. These findings suggested that circZFR could be a prognostic marker for GIT cancers.

Research on Multi-Wave Pore Pressure Prediction Method Based on Three Field Velocity Fusion

The optimization of velocity field is the core issue in reservoir seismic pressure prediction. For a long time, the seismic processing velocity analysis method has been used in the establishment of pressure prediction velocity field, which has a long research period and low resolution and restricts the accuracy of seismic pressure prediction;This paper proposed for the first time the use of machine learning algorithms, based on the feasibility analysis of wellbore logging pressure prediction, to integrate the CVI velocity inversion field, velocity sensitive post stack attribute field, and AVO P-wave and S-wave velocity reflectivity to obtain high-precision seismic P and S wave velocities. On this basis, high-resolution formation pore pressure and other parameters prediction based on multi waves is carried out. The pressure prediction accuracy is improved by more than 50% compared to the P-wave resolution of pore pressure prediction using only root mean square velocity. Practice has proven that the research method has certain reference significance for reservoir pore pressure prediction.

Research on Fracture Prediction Method Based on Multi-Source Information Fusion

Machine learning is a good method for predicting fracture by integrating multi-source information. Post-stack seismic attributes are commonly used to predict medium to large fractures, while pre-stack seismic attributes are proven to be more sensitive to small and micro sized fractures through forward modeling. Using machine learning algorithm to fuse information from different scales to predict fracture can greatly improve the accuracy of fracture prediction. On the basis of In-Situ stress prediction, the paper conducted post-stack seismic attribute analysis and pre-stack seismic attribute analysis, further studied on the sensitivity of seismic attributes to fracture and selected sensitive attributes, used the sensitivity log of well-bore fractures as the target log for learning, ultimately obtained a comprehensive body of fracture. Through blind well verification, the prediction results match well with the we1l data and the prediction results is highly consistent with the production data. The results of fracture prediction are reliable, and the research method has certain reference significance for fracture prediction.

行为公共政策的工具设计、应用策略与政策效应:基于类型学的分析

行为公共政策的兴起使公共政策研究逐渐转向对个体行为决策的微观解释及有效干预,然而当前研究多局限于“助推”,一定程度上忽视了行为公共政策工具丛的拓展及其策略与效应的差异。论文基于政策工具的干预对象与干预核心,创新性地构建了需求行为型、需求能力型和供给行为型的行为公共政策工具类型学分析框架,并从三个主维度和六个子维度分别对四类行为公共政策工具,即助推、强推、助力和督推进行了系统深描与比较分析。研究表明,尽管行为公共政策工具均瞄准传统工具难以应对的“个体失灵”与“行为偏差”问题,但其干预策略不尽相同。政策制定者应在系统分析政策情境与实践场域的前提下,合理选择政策工具及其组合,以提高政策执行成效。

COX-2/PGE2/EP4轴诱导巨噬细胞功能活化在NSCLC发展过程中的作用

背景与目的肿瘤微环境(tumor microenvironment,TME)是肿瘤发生、发展的重要因素之一,其中肿瘤相关巨噬细胞(tumor-associated macrophages,TAMs)在非小细胞肺癌(non-small cell lung cancer,NSCLC)进展中起着重要作用。然而,TAMs在NSCLC发展过程中的作用机制仍不清楚,因此本研究旨在探讨TAMs在NSCLC发展过程中的作用,并寻找潜在的治疗靶点。方法使用GEPIA(Gene Expression Profiling Interactive Analysis)数据库分析前列腺素E2受体4(prostaglandin E2 receptor 4,EP4)mRNA在NSCLC和正常肺组织中的表达情况;利用免疫组化(immunohistochemistry,IHC)方法检测120例NSCLC组织及24例癌旁组织标本中环氧合酶-2(cyclooxygenase-2,COX-2)、EP4、分化簇86(cluster of differentiation 86,CD86)、CD163、CD31的蛋白表达水平;建立裸鼠肺腺癌细胞A549与巨噬细胞RAW264.7共移植瘤模型,使用EP4抑制剂E7046灌胃,收集样本行苏木素-伊红(hematoxylin-eosin,HE)、IHC和免疫荧光(immunofluorescence,IF)染色,免疫印迹(Western blot)检测各组裸鼠肿瘤组织上皮间充质转化(epithelial-mesenchymal transformation,EMT)相关蛋白表达情况;全长转录组测序技术筛选引起肿瘤肝转移的关键基因并进行KEGG(Kyoto Encyclopedia of Genes and Genomes)富集分析。结果EP4 mRNA在NSCLC组织中表达水平普遍低于正常肺组织(P<0.05);COX-2、EP4、CD163、CD31蛋白在NSCLC组织和癌旁组织中差异性表达且在NSCLC患者多项临床病理参数中存在差异;RAW264.7缩短了A549的成瘤潜伏期,促进肿瘤增殖及肿瘤肝转移,E7046可降低裸鼠肿瘤细胞增殖活性、肿瘤组织血管密度及M2型巨噬细胞浸润;IF染色显示巨噬细胞主要分布在肿瘤转移灶周围;Western blot结果显示与A549单独移植组相比,A549与RAW264.7共移植组小鼠肿瘤组织中E-钙黏蛋白(E-cadherin)相对表达量明显降低,差异具有统计学意义(P<0.05),N-钙黏蛋白(N-cadherin)相对表达量上调,但差异无统计学意义(P>0.05);全长转录组差异基因主要富集的通路为PI3K-AKT、MAPK信号通路。结论在NSCLC发生发展过程中,COX-2/PGE2/EP4轴可能通过诱导巨噬细胞功能活化来促进肿瘤的进展,EP4可能是具有潜力的肿瘤免疫治疗新靶点。本研究为深入探讨NSCLC的发生发展机制提供了新的视角和思路,同时为开发新的NSCLC治疗策略提供了理论依据。

管理决策中的分布鲁棒优化

《中华人民共和国国民经济和社会发展第十四个五年规划和2035年远景目标纲要》要求大力发展物流、交通、医疗等行业,其中做好管理决策是关键。作为管理决策的引擎,分布鲁棒优化以其决策稳健性、计算便利性、应用普适性等突出优势,在近20年得到了学界和业界的广泛关注。本文从优化问题环境参数的不确定性建模、分布鲁棒机会约束优化以及分布鲁棒线性优化等方面,梳理了分布鲁棒优化的经典结论与研究现状,并以车辆路径优化、共享出行车辆调配、医疗手术室调度三个典型问题为例,回顾了分布鲁棒优化在管理决策中的应用。立足大数据时代,当前研究趋势包括:特征数据驱动的分布鲁棒优化、结合具体应用场景的数据驱动型分布鲁棒优化以及数据驱动型分布鲁棒离散优化的算法设计等。这些重要问题的解决将推动该领域的数据化发展,并进一步为服务国家战略赋能。

Alterations in the gut microbiome after transjugular intrahepatic portosystemic shunt in patients with hepatitis B virus-related portal hypertension

BACKGROUND Gut microbiota(GM)affects the progression and response to treatment in liver diseases.The GM composition is diverse and associated with different etiologies of liver diseases.Notably,alterations in GM alterations are observed in patients with portal hypertension(PH)secondary to cirrhosis,with hepatitis B virus(HBV)infection being a major cause of cirrhosis in China.Thus,understanding the role of GM alterations in patients with HBV infection-related PH is essential.AIM To evaluate GM alterations in patients with HBV-related PH after transjugular intrahepatic portosystemic shunt(TIPS)placement.METHODS This was a prospective,observational clinical study.There were 30 patients(with a 100%technical success rate)recruited in the present study.Patients with esophagogastric variceal bleeding due to HBV infection-associated PH who underwent TIPS were enrolled.Stool samples were obtained before and one month after TIPS treatment,and GM was analyzed using 16S ribosomal RNA amplicon sequencing.RESULTS One month after TIPS placement,8 patients developed hepatic encephalopathy(HE)and were assigned to the HE group;the other 22 patients were assigned to the non-HE group.There was no substantial disparity in the abundance of GM at the phylum level between the two groups,regardless of TIPS treatment(all,P>0.05).However,following TIPS placement,the following results were observed:(1)The abundance of Haemophilus and Eggerthella increased,whereas that of Anaerostipes,Dialister,Butyricicoccus,and Oscillospira declined in the HE group;(2)The richness of Eggerthella,Streptococcus,and Bilophila increased,whereas that of Roseburia and Ruminococcus decreased in the non-HE group;and(3)Members from the pathogenic genus Morganella appeared in the HE group but not in the non-HE group.CONCLUSION Intestinal microbiota-related synergism may predict the risk of HE following TIPS placement in patients with HBVrelated PH.Prophylactic microbiome therapies may be useful for preventing and treating HE after TIPS placement.

Spatial transcriptomics reveals that metabolic characteristics define the tumor immunosuppression microenvironment via iCAF transformation in oral squamous cell carcinoma

Tumor progression is closely related to tumor tissue metabolism and reshaping of the microenvironment. Oral squamous cell carcinoma (OSCC), a representative hypoxic tumor, has a heterogeneous internal metabolic environment. To clarify the relationship between different metabolic regions and the tumor immune microenvironment (TME) in OSCC, Single cell (SC) and spatial transcriptomics (ST) sequencing of OSCC tissues were performed. The proportion of TME in the ST data was obtained through SPOTlight deconvolution using SC and GSE103322 data. The metabolic activity of each spot was calculated using scMetabolism,and k-means clustering was used to classify all spots into hyper-, normal-, or hypometabolic regions. CD4T cell infiltration and TGF-βexpression is higher in the hypermetabolic regions than in the others. Through CellPhoneDB and NicheNet cell-cell communication analysis, it was found that in the hypermetabolic region, fibroblasts can utilize the lactate produced by glycolysis of epithelial cells to transform into inflammatory cancer-associated fibroblasts (iCAFs), and the increased expression of HIF1A in iCAFs promotes the transcriptional expression of CXCL12. The secretion of CXCL12 recruits regulatory T cells (Tregs), leading to Treg infiltration and increased TGF-β secretion in the microenvironment and promotes the formation of a tumor immunosuppressive microenvironment. This study delineates the coordinate work axis of epithelial cells-iCAFs-Tregs in OSCC using SC, ST and TCGA bulk data, and highlights potential targets for therapy.

Cytokine release syndrome triggered by programmed death 1 blockade(sintilimab)therapy in a psoriasis patient:A case report

BACKGROUND In recent years,immune checkpoint inhibitors(ICIs)have demonstrated remarkable efficacy across diverse malignancies.Notably,in patients with advanced gastric cancer,the use of programmed death 1(PD-1)blockade has significantly prolonged overall survival,marking a pivotal advancement comparable to the impact of Herceptin over the past two decades.While the therapeutic benefits of ICIs are evident,the increasing use of immunotherapy has led to an increase in immune-related adverse events.CASE SUMMARY This article presents the case of a patient with advanced gastric cancer and chronic plaque psoriasis.Following sintilimab therapy,the patient developed severe rashes accompanied by cytokine release syndrome(CRS).Fortunately,effective management was achieved through the administration of glucocorticoid,tocilizumab,and acitretin,which resulted in favorable outcomes.CONCLUSION Glucocorticoid and tocilizumab therapy was effective in managing CRS after PD-1 blockade therapy for gastric cancer in a patient with chronic plaque psoriasis.

Lightweight Dual‑Functional Segregated Nanocomposite Foams for Integrated Infrared Stealth and Absorption‑Dominant Electromagnetic Interference Shielding

Lightweight infrared stealth and absorption-dominant electromagnetic interference(EMI)shielding materials are highly desirable in areas of aerospace,weapons,military and wearable electronics.Herein,lightweight and high-efficiency dual-functional segregated nanocomposite foams with microcellular structures are developed for integrated infrared stealth and absorption-dominant EMI shielding via the efficient and scalable supercritical CO_(2)(SC-CO_(2))foaming combined with hydrogen bonding assembly and compression molding strategy.The obtained lightweight segregated nanocomposite foams exhibit superior infrared stealth performances benefitting from the synergistic effect of highly effective thermal insulation and low infrared emissivity,and outstanding absorption-dominant EMI shielding performances attributed to the synchronous construction of microcellular structures and segregated structures.Particularly,the segregated nanocomposite foams present a large radiation temperature reduction of 70.2℃ at the object temperature of 100℃,and a significantly improved EM wave absorptivity/reflectivity(A/R)ratio of 2.15 at an ultralow Ti_(3)C_(2)T_(x) content of 1.7 vol%.Moreover,the segregated nanocomposite foams exhibit outstanding working reliability and stability upon dynamic compression cycles.The results demonstrate that the lightweight and high-efficiency dual-functional segregated nanocomposite foams have excellent potentials for infrared stealth and absorption-dominant EMI shielding applications in aerospace,weapons,military and wearable electronics.

Influence of Irregular Coastlines on a Tornadic Mesovortex in the Pearl River Delta during the Monsoon Season. Part Ⅰ:Pre-storm Environment and Storm Evolution

The Pearl River Delta(PRD),a tornado hotspot,forms a distinct trumpet-shaped coastline that concaves toward the South China Sea.During the summer monsoon season,low-level southwesterlies over the PRD’s sea surface tend to be turned toward the west coast,constituting a convergent wind field along with the landward-side southwesterlies,which influences regional convective weather.This two-part study explores the roles of this unique land–sea contrast of the trumpet-shaped coastline in the formation of a tornadic mesovortex within monsoonal flows in this region.Part I primarily presents observational analyses of pre-storm environments and storm evolutions.The rotating storm developed in a lowshear environment(not ideal for a supercell)under the interactions of three air masses under the influence of the land–sea contrast,monsoon,and storm cold outflows.This intersection zone(or“triple point”)is typically characterized by local enhancements of ambient vertical vorticity and convergence.Based on a rapid-scan X-band phased-array radar,finger-like echoes were recognized shortly after the gust front intruded on the triple point.Developed over the triple point,they rapidly wrapped up with a well-defined low-level mesovortex.It is thus presumed that the triple point may have played roles in the mesovortex genesis,which will be demonstrated in Part II with multiple sensitivity numerical simulations.The findings also suggest that when storms pass over the boundary intersection zone in the PRD,the expected possibility of a rotating storm occurring is relatively high,even in a low-shear environment.Improved knowledge of such environments provides additional guidance to assess the regional tornado risk.

Designing Symmetric Gradient Honeycomb Structures with Carbon‑Coated Iron‑Based Composites for High‑Efficiency Microwave Absorption

The impedance matching of absorbers is a vital factor affecting their microwave absorption(MA)properties.In this work,we controllably synthesized Material of Institute Lavoisier 88C(MIL-88C)with varying aspect ratios(AR)as a precursor by regulating oil bath conditions,followed by one-step thermal decomposition to obtain carbon-coated iron-based composites.Modifying the precursor MIL-88C(Fe)preparation conditions,such as the molar ratio between metal ions and organic ligands(M/O),oil bath temperature,and oil bath time,influenced the phases,graphitization degree,and AR of the derivatives,enabling low filler loading,achieving well-matched impedance,and ensuring outstanding MA properties.The MOF-derivatives 2(MD_(2))/polyvinylidene Difluoride(PVDF),MD_(3)/PVDF,and MD4/PVDF absorbers all exhibited excellent MA properties with optimal filler loadings below 20 wt%and as low as 5 wt%.The MD_(2)/PVDF(5 wt%)achieved a maximum effective absorption bandwidth(EAB)of 5.52 GHz(1.90 mm).The MD_(3)/PVDF(10 wt%)possessed a minimum reflection loss(RL_(min))value of−67.4 at 12.56 GHz(2.13 mm).A symmetric gradient honeycomb structure(SGHS)was constructed utilizing the high-frequency structure simulator(HFSS)to further extend the EAB,achieving an EAB of 14.6 GHz and a RL_(min) of−59.0 dB.This research offers a viable inspiration to creating structures or materials with high-efficiency MA properties.

Porous metal oxides in the role of electrochemical CO_(2) reduction reaction

The global energy-related CO_(2) emissions have rapidly increased as the world economy heavily relied on fossil fuels.This paper explores the pressing challenge of CO_(2) emissions and highlights the role of porous metal oxide materials in the electrocatalytic reduction of CO_(2)(CO_(2)RR).The focus is on the development of robust and selective catalysts,particularly metal and metal-oxide-based materials.Porous metal oxides offer high surface area,enhancing the accessibility to active sites and improving reaction kinetics.The tunability of these materials allows for tailored catalytic behavior,targeting optimized reaction mechanisms for CO_(2)RR.The work also discusses the various synthesis strategies and identifies key structural and compositional features,addressing challenges like high overpotential,poor selectivity,and low stability.Based on these insights,we suggest avenues for future research on porous metal oxide materials for electrochemical CO_(2) reduction.

Automatic detection of small bowel lesions with different bleeding risks based on deep learning models

BACKGROUND Deep learning provides an efficient automatic image recognition method for small bowel(SB)capsule endoscopy(CE)that can assist physicians in diagnosis.However,the existing deep learning models present some unresolved challenges.AIM To propose a novel and effective classification and detection model to automatically identify various SB lesions and their bleeding risks,and label the lesions accurately so as to enhance the diagnostic efficiency of physicians and the ability to identify high-risk bleeding groups.METHODS The proposed model represents a two-stage method that combined image classification with object detection.First,we utilized the improved ResNet-50 classification model to classify endoscopic images into SB lesion images,normal SB mucosa images,and invalid images.Then,the improved YOLO-V5 detection model was utilized to detect the type of lesion and its risk of bleeding,and the location of the lesion was marked.We constructed training and testing sets and compared model-assisted reading with physician reading.RESULTS The accuracy of the model constructed in this study reached 98.96%,which was higher than the accuracy of other systems using only a single module.The sensitivity,specificity,and accuracy of the model-assisted reading detection of all images were 99.17%,99.92%,and 99.86%,which were significantly higher than those of the endoscopists’diagnoses.The image processing time of the model was 48 ms/image,and the image processing time of the physicians was 0.40±0.24 s/image(P<0.001).CONCLUSION The deep learning model of image classification combined with object detection exhibits a satisfactory diagnostic effect on a variety of SB lesions and their bleeding risks in CE images,which enhances the diagnostic efficiency of physicians and improves the ability of physicians to identify high-risk bleeding groups.

Efficient stochastic parallel gradient descent training for on-chip optical processor

In recent years,space-division multiplexing(SDM)technology,which involves transmitting data information on multiple parallel channels for efficient capacity scaling,has been widely used in fiber and free-space optical communication sys-tems.To enable flexible data management and cope with the mixing between different channels,the integrated reconfig-urable optical processor is used for optical switching and mitigating the channel crosstalk.However,efficient online train-ing becomes intricate and challenging,particularly when dealing with a significant number of channels.Here we use the stochastic parallel gradient descent(SPGD)algorithm to configure the integrated optical processor,which has less com-putation than the traditional gradient descent(GD)algorithm.We design and fabricate a 6×6 on-chip optical processor on silicon platform to implement optical switching and descrambling assisted by the online training with the SPDG algorithm.Moreover,we apply the on-chip processor configured by the SPGD algorithm to optical communications for optical switching and efficiently mitigating the channel crosstalk in SDM systems.In comparison with the traditional GD al-gorithm,it is found that the SPGD algorithm features better performance especially when the scale of matrix is large,which means it has the potential to optimize large-scale optical matrix computation acceleration chips.

Network Intrusion Traffic Detection Based on Feature Extraction

With the increasing dimensionality of network traffic,extracting effective traffic features and improving the identification accuracy of different intrusion traffic have become critical in intrusion detection systems(IDS).However,both unsupervised and semisupervised anomalous traffic detection methods suffer from the drawback of ignoring potential correlations between features,resulting in an analysis that is not an optimal set.Therefore,in order to extract more representative traffic features as well as to improve the accuracy of traffic identification,this paper proposes a feature dimensionality reduction method combining principal component analysis and Hotelling’s T^(2) and a multilayer convolutional bidirectional long short-term memory(MSC_BiLSTM)classifier model for network traffic intrusion detection.This method reduces the parameters and redundancy of the model by feature extraction and extracts the dependent features between the data by a bidirectional long short-term memory(BiLSTM)network,which fully considers the influence between the before and after features.The network traffic is first characteristically downscaled by principal component analysis(PCA),and then the downscaled principal components are used as input to Hotelling’s T^(2) to compare the differences between groups.For datasets with outliers,Hotelling’s T^(2) can help identify the groups where the outliers are located and quantitatively measure the extent of the outliers.Finally,a multilayer convolutional neural network and a BiLSTM network are used to extract the spatial and temporal features of network traffic data.The empirical consequences exhibit that the suggested approach in this manuscript attains superior outcomes in precision,recall and F1-score juxtaposed with the prevailing techniques.The results show that the intrusion detection accuracy,precision,and F1-score of the proposed MSC_BiLSTM model for the CIC-IDS 2017 dataset are 98.71%,95.97%,and 90.22%.

消失的对话性:作为伪命题的AI时评

人工智能对新闻业的影响已从信息类的新闻报道领域渗透至观点性的新闻评论,AI时评给被视为“不可被机器替代的最后领地”的评论写作带来某种挑战。本文认为,AI时评不符合新闻评论的对话性要求,有智能而无智识,有套话而无对话,有答案而无问答。本研究通过分析AI小壹创作的26篇时评文章,从选题、行文和效果三方面探究AI写作如何消灭了新闻评论的对话性。对话性的缺失,让AI时评只能成为一场自言自语的“对空言说”。人化的AI时评目前还无法取代人的写作,但对机器化的“人的写作”形成了一种反向测试。

信息化环境下高校工程管理审计组织模式创新探析——以某高校理工楼项目管理审计工作为例

新时代要求高校审计工作坚持科学的审计理念,积极运用现代信息技术,探索创新审计组织模式和方式方法。本研究在分析信息化环境下工程管理审计的特征和要求的基础上,着力破解传统审计模式下审计时效低、监督滞后的难题,坚持风险和问题导向,采用施工过程结算审计模式,以期通过信息化环境下审计业务组织模式和方式方法创新,提高工程管理审计质量和效果,推动工程管理审计发挥更大作用。

How do lateral septum projections to the ventral CA1 influence sociability?

Social dysfunction is a risk factor for several neuropsychiatric illnesses.Previous studies have shown that the lateral septum(LS)-related pathway plays a critical role in mediating social behaviors.Howeve r,the role of the connections between the LS and its downstream brain regions in social behavio rs remains unclea r.In this study,we conducted a three-chamber test using electrophysiological and chemogenetic approaches in mice to determine how LS projections to ventral CA1(vCA1)influence sociability.Our res ults showed that gamma-aminobutyric acid(GABA)-e rgic neuro ns were activated following social experience,and that social behavio rs were enhanced by chemogenetic modulation of these neurons.Moreover,LS GABAergic neurons extended their functional neural connections via vCA1 glutamatergic pyramidal neurons,and regulating LSGABA→vCA1Gluneural projections affected social behaviors,which were impeded by suppressing LSprojecting vCA1 neuronal activity or inhibiting GABAAreceptors in vCA1.These findings support the hypothesis that LS inputs to the vCA1 can control social prefe rences and social novelty behaviors.These findings provide new insights rega rding the neural circuits that regulate sociability.

Rock physical characteristics of deep dolomite under complex geological conditions:A case study of 4th Member of Sinian Dengying Formation in the Sichuan Basin,China

The deep-ultra deep carbonate reservoir in China,commonly subjected to modification of multi-stage diagenesis,has extremely high heterogeneity.Conventional rock physics analysis cannot accurately identify the elastic responses of reservoir.Here,the rock physics properties of the dolomite from the 4th Member of the Sinian Dengying Formation are experimentally measured,and the change law of rock physics characteristics is investigated within the framework of the diagenetic processes by the analysis of the elastic and petrologic characteristics,pore structure,and sedimentary environments.The results show that the differentiated diagenesis results in different pore structure characteristics and microtexture characteristics of the rock.The microbial dolomite of the algal mound-grain beach facies is subjected to the contemporaneous microbial dolomitization and seepage-reflux dolomitization,penecontemporaneous selective dissolution,burial dolomitization,and hydrothermal dolomitization.The resultant crystalline dolomite is found with one main type of the dolomite crystal contact boundaries,and the dissolution pore is extensive development.The siliceous,muddy,and limy dolomite of the interbeach sea environment mainly experiences the weak capillary concentration dolomitization,intensive mechanical compaction-induced densification,and burial dolomitization.Such crystalline dolomite is observed with four types of contact boundaries,namely the dolomite contact,clay contact,quartz contact,and calcite contact boundaries,and porosity mostly attributed to residual primary inter-granular or crystalline pores.The samples with the same crystal boundary condition have consistent correlations between the compressional-and shear-wave velocities,and between the compressional-wave velocity and the velocity ratio.Additionally,the variation of the acoustic velocity with effective pressure and the intensity of pore-scale fluid-related dispersion are controlled by the differentiation of pore structure types of the samples.The varied effects of soft pores like micro-cracks on the compressional-and shearwave velocity causes considerable changes in the relationships between the compressional-and shearwave velocities,compressional-wave velocity and velocity ratio,and porosity and acoustic velocity.This research is an attempt to demonstrate a novel method for investigating the rock physics variation of rock during the geological process,and the obtained findings can provide the rock physics basis for seismic prediction of the characteristics of deep carbonate reservoirs.