基于Bagging-WOA-SVR的粮堆温度场预测模型

采用阵列式分布的测温电缆检测粮仓温度变化情况,利用机器学习技术来预测粮食温度,用粮仓1年监测数据来预测粮堆未来27 d温度。传统的BP、RBF、RF、SVR单模型对粮堆温度进行预测存在误差大、泛化能力差等缺点,提出一种基于Bagging集成的鲸鱼算法优化支持向量回归模型(Bagging-WOA-SVR),并与灰狼算法优化支持向量回归模型作比较。将影响粮堆温度的多种因素做灰色关联分析,选取粮仓内温度、粮仓内湿度、粮仓外温度、粮仓外湿度、粮仓平均温度、地表温度作为神经网络的输入,粮堆平均温度作为预测输出,选取3个指标为评判标准,对比分析模型预测精度。结果表明:提出的Bagging-WOA-SVR模型相比之下有着较好的稳定性,均方误差为0.24,相关系数为0.9892。

糙皮侧耳BAG家族蛋白鉴定及其基因表达模式分析

在NCBI、JGI数据库检索糙皮侧耳(Pleurotus ostreatus)BAG蛋白(PoBAGs),对其进行生物信息学分析,并测定不同发育(菌丝、原基、子实体)阶段和高温(42℃)、低温(4℃)胁迫时PoBAG基因的表达情况,分析其表达模式。结果表明:共检索到3个(分别命名为PoBAG-1、PoBAG-2、PoBAG-3)具有BAG结构域的蛋白,其中,PoBAG-1、PoBAG-2还分别含有1个IQ基序和类泛素化结构域;PoBAG-1、PoBAG-3为亲水性不稳定蛋白,且亲缘关系较近,可能主要定位于细胞核和细胞质中;PoBAG-2为亲水性稳定蛋白,与其他具有类泛素化结构域的BAG蛋白具有较近的亲缘关系,可能主要定位于线粒体和细胞质中。与菌丝相比,3个PoBAGs在原基和子实体中相对表达量均显著上调;与对照(25℃)相比,42℃高温胁迫时,PoBAG-1、PoBAG-3相对表达量极显著上调,PoBAG-2显著下调;4℃低温胁迫时,PoBAG-1和PoBAG-2相对表达量显著上调,PoBAG-3显著下调。研究结果为进一步解析BAG家族蛋白在糙皮侧耳生长发育以及温度胁迫响应过程中的功能提供参考。

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.

Transplantation of fibrin-thrombin encapsulated human induced neural stem cells promotes functional recovery of spinal cord injury rats through modulation of the microenvironment

Recent studies have mostly focused on engraftment of cells at the lesioned spinal cord,with the expectation that differentiated neurons facilitate recovery.Only a few studies have attempted to use transplanted cells and/or biomaterials as major modulators of the spinal cord injury microenvironment.Here,we aimed to investigate the role of microenvironment modulation by cell graft on functional recovery after spinal cord injury.Induced neural stem cells reprogrammed from human peripheral blood mononuclear cells,and/or thrombin plus fibrinogen,were transplanted into the lesion site of an immunosuppressed rat spinal cord injury model.Basso,Beattie and Bresnahan score,electrophysiological function,and immunofluorescence/histological analyses showed that transplantation facilitates motor and electrophysiological function,reduces lesion volume,and promotes axonal neurofilament expression at the lesion core.Examination of the graft and niche components revealed that although the graft only survived for a relatively short period(up to 15 days),it still had a crucial impact on the microenvironment.Altogether,induced neural stem cells and human fibrin reduced the number of infiltrated immune cells,biased microglia towards a regenerative M2 phenotype,and changed the cytokine expression profile at the lesion site.Graft-induced changes of the microenvironment during the acute and subacute stages might have disrupted the inflammatory cascade chain reactions,which may have exerted a long-term impact on the functional recovery of spinal cord injury rats.

New roles of tumor-derived exosomes in tumor microenvironment

Throughout tumorigenesis, the co-evolution of tumor cells and their surrounding microenvironment leads to the development of malignant phenotypes. Cellular communication within the tumor microenvironment(TME) plays a critical role in influencing various aspects of tumor progression, including invasion and metastasis. The release of exosomes, a type of extracellular vesicle, by most cell types in the body, is an essential mediator of intercellular communication. A growing body of research indicates that tumor-derived exosomes(TDEs) significantly expedite tumor progression through multiple mechanisms, inducing epithelial-mesenchymal transition and macrophage polarization, enhancing angiogenesis, and aiding in the immune evasion of tumor cells. Herein, we describe the formation and characteristics of the TME, and summarize the contents of TDEs and their diverse functions in modulating tumor development. Furthermore, we explore potential applications of TDEs in tumor diagnosis and treatment.

Hepatocellular carcinoma immune microenvironment and check point inhibitors-current status

Hepatocellular carcinoma(HCC)is the most common primary tumor of the liver and has a high mortality rate.The Barcelona Clinic Liver Cancer staging system in addition to tumor staging also links the modality of treatment available to a particular stage.The recent description of the tumor microenvironment(TME)in HCC has provided a new concept of immunogenicity within the HCC.Virusrelated HCC has been shown to be more immunogenic with higher expression of cytotoxic T lymphocytes and decreased elements for immunosuppression such as regulatory T cells.This immunogenic milieu provides a better response to immunotherapy especially immune checkpoint inhibitors(ICIs).In addition,the recent data on combining locoregional therapies and other strategies may convert the less immunogenic state of the TME towards higher immunogenicity.Therefore,data are emerging on the use of combinations of locoregional therapy and ICIs in unresectable or advanced HCC and has shown better survival outcomes in this difficult population.

Mechanisms of tumor immunosuppressive microenvironment formation in esophageal cancer

As a highly invasive malignancy,esophageal cancer(EC)is a global health issue,and was the eighth most prevalent cancer and the sixth leading cause of cancerrelated death worldwide in 2020.Due to its highly immunogenic nature,emerging immunotherapy approaches,such as immune checkpoint blockade,have demonstrated promising efficacy in treating EC;however,certain limitations and challenges still exist.In addition,tumors may exhibit primary or acquired resistance to immunotherapy in the tumor immune microenvironment(TIME);thus,understanding the TIME is urgent and crucial,especially given the importance of an immunosuppressive microenvironment in tumor progression.The aim of this review was to better elucidate the mechanisms of the suppressive TIME,including cell infiltration,immune cell subsets,cytokines and signaling pathways in the tumor microenvironment of EC patients,as well as the downregulated expression of major histocompatibility complex molecules in tumor cells,to obtain a better understanding of the differences in EC patient responses to immunotherapeutic strategies and accurately predict the efficacy of immunotherapies.Therefore,personalized treatments could be developed to maximize the advantages of immunotherapy.

基于MLP-Bagging集成分类模型的在线学习行为分析

针对教育者难以对学习者多样化的在线学习行为进行监测和研判等问题,提出一种带嵌入层的MLP-Bagging集成分类模型对学习者的在线学习行为进行分析与判别.考虑到学习者的在线学习行为以及个体特性,从学习准备行为、知识获取行为、交互学习行为、学习巩固行为和辅助特征5个方面构建在线学习行为模型,并采用MLP-Bagging集成分类模型对学习者进行分类判别.实验结果表明,所构建的学习模型可对在线学习者的学习行为进行符合实际的建模,加入辅助特征有利于对各类学习者的在线学习行为进行深入的分析与指导,并且在分类模型中加入嵌入层可以有效克服标签编码带来的数据冗余和误差缺陷,从而获得更好的分类效果.与其他分类模型相比,融合多个MLP分类器的Bagging集成模型可以减少单个MLP分类器的方差,其分类准确率达到98.72%,具有较好的实际应用价值.

Open AccessComplex role of neutrophils in the tumor microenvironment:an avenue for novel immunotherapies

Neutrophils,which originate from the bone marrow and are characterized by a segmented nucleus and a brief lifespan,have a crucial role in the body’s defense against infections and acute inflammation.Recent research has uncovered the complex roles of neutrophils as regulators in tumorigenesis,during which neutrophils exhibit a dualistic nature that promotes or inhibits tumor progression.This adaptability is pivotal within the tumor microenvironment(TME).In this review,we provide a comprehensive characterization of neutrophil plasticity and heterogeneity,aiming to illuminate current research findings and discuss potential therapeutic avenues.By delineating the intricate interplay of neutrophils in the TME,this review further underscores the urgent need to understand the dual functions of neutrophils with particular emphasis on the anti-tumor effects to facilitate the development of effective therapeutic strategies against cancer.

Estimation of cancer cell migration in biomimetic random/oriented collagen fiber microenvironments

Increasing data indicate that cancer cell migration is regulated by extracellular matrixes and their surrounding biochemical microenvironment,playing a crucial role in pathological processes such as tumor invasion and metastasis.However,conventional two-dimensional cell culture and animal models have limitations in studying the influence of tumor microenvironment on cancer cell migration.Fortunately,the further development of microfluidic technology has provided solutions for the study of such questions.We utilize microfluidic chip to build a random collagen fiber microenvironment(RFM)model and an oriented collagen fiber microenvironment(OFM)model that resemble early stage and late stage breast cancer microenvironments,respectively.By combining cell culture,biochemical concentration gradient construction,and microscopic imaging techniques,we investigate the impact of different collagen fiber biochemical microenvironments on the migration of breast cancer MDA-MB-231-RFP cells.The results show that MDA-MB-231-RFP cells migrate further in the OFM model compared to the RFM model,with significant differences observed.Furthermore,we establish concentration gradients of the anticancer drug paclitaxel in both the RFM and OFM models and find that paclitaxel significantly inhibits the migration of MDA-MB-231-RFP cells in the RFM model,with stronger inhibition on the high concentration side compared to the low concentration side.However,the inhibitory effect of paclitaxel on the migration of MDA-MB-231-RFP cells in the OFM model is weak.These findings suggest that the oriented collagen fiber microenvironment resembling the late-stage tumor microenvironment is more favorable for cancer cell migration and that the effectiveness of anticancer drugs is diminished.The RFM and OFM models constructed in this study not only provide a platform for studying the mechanism of cancer development,but also serve as a tool for the initial measurement of drug screening.

Prognositic value of anoikis and tumor immune microenvironment-related gene in the treatment of osteosarcoma

Objective:Osteosarcoma is a highly aggressive primary malignant bone tumor commonly seen in children and adolescents,with a poor prognosis.Anchorage-dependent cell death(anoikis)has been proven to be indispensable in tumor metastasis,regulating the migration and adhesion of tumor cells at the primary site.However,as a type of programmed cell death,anoikis is rarely studied in osteosarcoma,especially in the tumor immune microenvironment.This study aims to clarify prognostic value of anoikis and tumor immune microenvironment-related gene in the treatment of osteosarcoma.Methods:Anoikis-related genes(ANRGs)were obtained from GeneCards.Clinical information and ANRGs expression profiles of osteosarcoma patients were sourced from the therapeutically applicable research to generate effective therapies and Gene Expression Omnibus(GEO)databases.ANRGs highly associated with tumor immune microenvironment were identified by the estimate package and the weighted gene coexpression network analysis(WGCNA)algorithm.Machine learning algorithms were performed to construct long-term survival predictive strategy,each sample was divided into high-risk and low-risk subgroups,which was further verified in the GEO cohort.Finally,based on single-cell RNA-seq from the GEO database,analysis was done on the function of signature genes in the osteosarcoma tumor microenvironment.Results:A total of 51 hub ANRGs closely associated with the tumor microenvironment were identified,from which 3 genes(MERTK,BNIP3,S100A8)were selected to construct the prognostic model.Significant differences in immune cell activation and immune-related signaling pathways were observed between the high-risk and low-risk groups based on tumor microenvironment analysis(all P<0.05).Additionally,characteristic genes within the osteosarcoma microenvironment were identified in regulation of intercellular crosstalk through the GAS6-MERTK signaling pathway.Conclusion:The prognostic model based on ANRGs and tumor microenvironment demonstrate good predictive power and provide more personalized treatment options for patients with osteosarcoma.

Hypoxic tumor microenvironment:Destroyer of natural killer cell function

In recent years, immunotherapy has made remarkable progress in treating certain tumors and hematological malignancies. However, the efficacy of natural killer(NK) cells, which are an important subset of innate lymphocytes used in anticancer immunotherapy, remains limited. Hypoxia, a critical characteristic of the tumor microenvironment(TME), is involved in tumor development and resistance to radiotherapy, chemotherapy, and immunotherapy. Moreover, hypoxia contributes to the impairment of NK cell function and may be a significant factor that limits their therapeutic effects. Targeted hypoxia therapy has emerged as a promising research area for enhancing the efficacy of NK cell therapy. Therefore, understanding how the hypoxic TME influences NK cell function is crucial for improving antitumor treatment outcomes.

Microenvironment and electronic state modulation of Pd nanoparticles within MOFs for enhancing low-temperature activity towards DCPD hydrogenation

Precise control of the local environment and electronic state of the guest is an important method of controlling catalytic activity and reaction pathways.In this paper,guest Pd NPs were introduced into a series of host UiO-67 MOFs with different functional ligands and metal nodes,the microenvironment and local electronic structure of Pd is modulated by introducing bipyridine groups and changing metal nodes(Ce_(6)O_(6) or Zr_(6)O_(6)).The bipyridine groups not only promoted the dispersion Pd NPs,but also facilitated electron transfer between Pd and UiO-67 MOFs through the formation of Pd-N bridges.Compared with Zr6 clusters,the tunability and orbital hybridisation of the 4f electronic structure in the Ce_(6) clusters modulate the electronic structure of Pd through the construction of the Ce-O-Pd interfaces.The optimal catalyst Pd/UiO-67(Ce)-bpy presented excellent low-temperature activity towards dicyclopentadiene hydrogenation with a conversion of>99% and a selectivity of>99%(50℃,10 bar).The results show that the synergy of Ce-O-Pd and Pd-N promotes the formation of active Pd^(δ+),which not only enhances the adsorption of H_(2) and electron-rich C=C bonds,but also contributes to the reduction of proton migration distance and improves proton utilization efficiency.These results provide valuable insights for investigating the regulatory role of the host MOFs,the nature of host-guest interactions,and their correlation with catalytic performance.

Microenvironmental effects on growth response of Pinus massoniana to climate at its northern boundary in the Tongbai Mountains,Central China

The Tongbai Mountains is an ecologically sensi-tive region and the northern boundary of Pinus massoniana Lamb.To analyze the effect of different microenvironments on tree growth response to climate factors,we developed standard chronologies for earlywood width(EWW),late-wood width(LWW),and total ring width(TRW)of P.massoniana at two sampling sites on slopes with different orientations,then analyzed characteristics of the chronolo-gies and their correlations with climate variables from five stations in the region and with a regional normalized differ-ence vegetation index(NDVI).Statistical results showed that the TRW/EWW/LWW chronology consistency and charac-teristics(mean sensitivity,signal to noise ratio,expressed population signal)for trees growing on the southeastern slope were much higher than for trees on the northeastern slope.Correlations indicated that temperature in current March and August has a significant positive effect on TRW/EWW/LWW formation,and the effect on the northeastern slope was weaker than on the southeastern slope.Compared to temperature,precipitation has more complicated effects on tree growth,but the effect on the northeastern slope was also generally weaker than on the southeastern slope.Step-wise linear regression analyses showed that temperature in August was the main limiting factor at the two sampling sites.Similarly,the response of tree growth on the southeast-ern slope as determined by the NDVI is better than on the northeastern slope,and the TRW/EWW/LWW chronologies for the southeastern slope explained over 50%of the total NDVI variances in June.Overall,the results indicate that the difference in the climate response of P.massoniana at two sampling sites is clearly caused by differences in the microenvironment,and such differences should be properly considered in future studies of forest dynamics and climate reconstructions.

Tailoring the microenvironment of Ti sites in Ti-containing materials for synergizing with Au sites to boost propylene epoxidation

Au sites supported on Ti-containing materials(Au/Ti-containing catalyst)are currently considered as a promising catalyst for the propylene epoxidation owing to the synergistic effect that hydrogen peroxide species formed on Au sites diffuses to the Ti sites to form the Ti-hydroperoxo intermedi-ates and contributes to the formation of propylene oxide(PO).In principle,thermal treatment will significantly affect the chemical and physical structures of Ti-containing materials.Consequently,the synergy between tailored Ti sites with different surface properties and Au sites is highly expected to enhance the catalytic performance for the reaction.Herein,we systematically studied the intrinsic effects of different microenvironments around Ti sites on the PO adsorption/desorption and conversion,and then effectively improved the catalytic performance by tailoring the number of surface hydroxyl groups.The Ti^(Ⅵ) material with fewer hydroxyls stimulates a remarkable enhancement in PO selectivity and H_(2) efficiency compared to the Ti^(Ⅵ) material that possessed more hydroxyls,offering a 7-fold and 4-fold increase,respectively.As expected,the Ti^(Ⅵ+Ⅳ) and Ti^(Ⅳ) materials also exhibit a similar phenomenon to the Ti^(Ⅵ) materials through the same thermal treatment,which strongly supports that the Ti sites microenvironment is an important factor in suppressing PO con-version and enhancing catalytic performance.These insights could provide guidance for the rational preparation and optimization of Ti-containing materials synergizing with Au catalysts for propylene epoxidation.

Hypoxia-related bioinformatic signatures associated with prognosis and tumor microenvironment of pancreatic cancer:Current status,concerns,and future perspectives

Pancreatic cancer(PC),a highly lethal tumor with nearly identical incidence and mortality rates,has become the sixth leading cause of cancer-related deaths.Hypoxia is an important malignant factor in PC,as it regulates angiogenesis,metabolic reprogramming,tumor progression,and metastasis.Disrupting the hypoxic microenvironment can enhance the efficacy of antitumor therapy and improve the prognosis of patients with PC.With the advent of bioinformatics,hypoxia-related PC models have emerged in recent years.They provide a reference for estimating the prognosis and immune microenvironment of patients with PC and identify potential biomarkers for targeting hypoxic microenvironment.However,these findings based on bioinformatic analysis may not be completely reliable without further experimental evidence and clinical cohort validation.The application of these models and biomarkers in clinical practice to predict survival time and develop anti hypoxic therapeutic strategies for patients with PC remains in its infancy.In this editorial,we review the current status of hypoxia-related prognostic models in PC,analyze their similarities and differences,discuss several existing challenges,and provide potential solutions and directions for further studies.This editorial will facilitate the optimization,validation,and determination of the molecular mechanisms of related models.

Construction and validation of a pancreatic cancer prognostic model based on genes related to the hypoxic tumor microenvironment

BACKGROUND Pancreatic cancer is one of the most lethal malignancies,characterized by poor prognosis and low survival rates.Traditional prognostic factors for pancreatic cancer offer inadequate predictive accuracy,often failing to capture the complexity of the disease.The hypoxic tumor microenvironment has been recognized as a significant factor influencing cancer progression and resistance to treatment.This study aims to develop a prognostic model based on key hypoxia-related molecules to enhance prediction accuracy for patient outcomes and to guide more effective treatment strategies in pancreatic cancer.AIM To develop and validate a prognostic model for predicting outcomes in patients with pancreatic cancer using key hypoxia-related molecules.METHODS This pancreatic cancer prognostic model was developed based on the expression levels of the hypoxia-associated genes CAPN2,PLAU,and CCNA2.The results were validated in an independent dataset.This study also examined the correlations between the model risk score and various clinical features,components of the immune microenvironment,chemotherapeutic drug sensitivity,and metabolism-related pathways.Real-time quantitative PCR verification was conducted to confirm the differential expression of the target genes in hypoxic and normal pancreatic cancer cell lines.RESULTS The prognostic model demonstrated significant predictive value,with the risk score showing a strong correlation with clinical features:It was significantly associated with tumor grade(G)(bP<0.01),moderately associated with tumor stage(T)(aP<0.05),and significantly correlated with residual tumor(R)status(bP<0.01).There was also a significant negative correlation between the risk score and the half-maximal inhibitory concentration of some chemotherapeutic drugs.Furthermore,the risk score was linked to the enrichment of metabolism-related pathways in pancreatic cancer.CONCLUSION The prognostic model based on hypoxia-related genes effectively predicts pancreatic cancer outcomes with improved accuracy over traditional factors and can guide treatment selection based on risk assessment.

DNA Damage-driven Inflammatory Cytokines:Reprogramming of Tumor Immune Microenvironment and Application of Oncotherapy

DNA damage occurs across tumorigenesis and tumor development.Tumor intrinsic DNA damage can not only increase the risk of mutations responsible for tumor generation but also initiate a cellular stress response to orchestrate the tumor immune microenvironment(TIME)and dominate tumor progression.Accumulating evidence documents that multiple signaling pathways,including cyclic GMP-AMP synthase-stimulator of interferon genes(cGAS-STING)and ataxia telangiectasia-mutated protein/ataxia telangiectasia and Rad3-related protein(ATM/ATR),are activated downstream of DNA damage and they are associated with the secretion of diverse cytokines.These cytokines possess multifaced functions in the anti-tumor immune response.Thus,it is necessary to deeply interpret the complex TIME reshaped by damaged DNA and tumor-derived cytokines,critical for the development of effective tumor therapies.This manuscript comprehensively reviews the relationship between the DNA damage response and related cytokines in tumors and depicts the dual immunoregulatory roles of these cytokines.We also summarize clinical trials targeting signaling pathways and cytokines associated with DNA damage and provide future perspectives on emerging technologies.

基于小波和Bagging-PNN网络的柴油机轴承故障研究

针对柴油机故障诊断速度慢、诊断模型准确率低等问题。提出一种基于小波和Bagging-PNN网络的柴油机轴承故障诊断法。首先,利用时域、频域对采样后的故障数据进行分析,通过小波分析对数据进行去噪处理;然后,将Bagging算法与概率神经网络(Probabilistic Neural Network, PNN)进行融合,通过多个PNN分类器以相同的方式进行投票建立柴油机轴承故障分类模型,提高诊断准确度;最后,通过对比实验表明基于小波和Bagging-PNN的柴油机轴承故障诊断方法的识别准确性有明显提高。

The lactylation index predicts the immune microenvironment and prognosis of pan-cancer patients

Background:Protein lactylation is a new way for the“metabolic waste”lactic acid to perform novel functions.Nevertheless,our understanding of the contribution of protein lactylation to both tumor progression and therapeutic interventions remains imited.The construction of a scoring system for lactylation to predict the prognosis of pancancer patients and to evaluate the tumor immune microenvironment(TIME)would improve our understanding of the clinical significance of lactylation.Methods:Consensus clustering analysis of lactylation-related genes was used to cluster 177 pancreatic adenocarcinoma(PAAD)patients.Subsequently,a scoring system was developed using the least absolute shrinkage and selection operator(LASSO)regression.Internal validation and external validation were both conducted to assess and confirm the predictive accuracy of the scoring system.Finally,leucine rich repeat containing 1(LRRC1),a newly discovered lactylation-related gene,was analyzed in PAAD in vitro.Results:Utilizing the profiles of 332 lactylation-related genes,a total of 177 patients with PAAD were segregated into two distinct groups.LacCluster^(high) patients had a poorer prognosis than LacCluster^(low) patients.Through the differential analysis between the LacCluster^(high) and LacCluster^(low) groups,we identified additional genes associated with lactylation.These genes were then integrated to construct the LacCluster-enhanced system,which enabled more accurate prognosis prediction for patients with PAAD.Then,a lactylation index containing three genes(LacI-3)was constructed using LASSO regression.This was done to enhance the usability of the LacCluster-enhanced system in the clinic.Compared to those in the LacI-3^(high) subgroup,patients in the LacI-3^(low) subgroup exhibited increased expression of immune checkpoint-related genes,more immune cell infiltration,lower tumor mutation burdens,and better prognoses,indicating a“hot tumor”phenotype.Moreover,knocking down the expression of LRRC1,the hub gene in the LacI-3 scoring system,inhibited PAAD cell invasion,migration,and proliferation in vitro.Ultimately,the significance of LacI-3 across cancers was confirmed.Conclusion:Our findings strongly imply that protein lactylation may represent a new approach to diagnosing and treating malignant tumors.