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This work reports a new Zn-COF with a three-dimension framework, which presents superior ability toward glycolaldehyde conversion to tetroses under mechano-catalysis conditions.

Bio-based degradable supramolecular plastics with a high fracture strength of 265 MPa and excellent water-resistance are fabricated through complexation of regenerated cellulose with tannic acid, and can be fully degraded under soil in ∼35 days.

Trace N facilitates the desorption of intermediates in the HER and accelerates MOOH species formation in the OER, thus promoting the OWS.

FePO4 supported Rh based catalysts exhibited excellent performance in the hydrogenation of substituted quinoline, attributed to the synergy between Rh subnano clusters and FePO4 support.

Background Although deep learning has brought revolutionary changes in health care, reliance on manually selected cross-sectional images and segmentation remain methodological barriers. Purpose To develop and validate an automated preoperative artificial intelligence (AI) algorithm for tumor and lymph node (LN) segmentation with CT imaging for prediction of LN metastasis in patients with pancreatic ductal adenocarcinoma (PDAC). Materials and Methods In this retrospective study, patients with surgically resected, pathologically confirmed PDAC underwent multidetector CT from January 2015 to April 2020. Three models were developed, including an AI model, a clinical model, and a radiomics model. CT-determined LN metastasis was diagnosed by radiologists. Multivariable logistic regression analysis was conducted to develop the clinical and radiomics models. The performance of the models was determined on the basis of their discrimination and clinical utility. Kaplan-Meier curves, the log-rank test, or Cox regression were used for survival analysis. Results Overall, 734 patients (mean age, 62 years ± 9 [SD]; 453 men) were evaluated. All patients were split into training (

The purpose of this study is to assess the effects of early high-carbohydrate stimulus on glucose metabolism in zebrafish (Danio rerio) over two generations and explore the mechanisms that explain those nutritional programming effects via epigenetic modifications. The larvae were delivered a high-carbohydrate diet (53.66%) that was used as an early nutritional stimulus from the first feeding to the end of the yolk sac (FF) and 5 days after yolk-sac exhaustion (YE). The larvae (F0) and their offspring (F1) were then both fed the control diet (22.69%) until adulthood (15 weeks), and they were challenged with a high-carbohydrate diet (35.36%) at the 16th week. The results indicated that early stimulus immediately raised the mRNA levels of genes involved in glycolysis and gluconeogenesis. At the end of F0 challenge, both treatment groups decreased the plasma glucose levels, increased the expression levels of glucokinase (gck), and inhibited the mRNA during gluconeogenesis. When challenged in F1, the glucose levels were lower in FF (F1), and the mRNA levels of phosphoenolpyruvate carboxykinase 1 (pck1) were decreased in FF (F1) and YE (F1). Besides, in both experimental groups (F0 and F1), the CpG island of pck1 maintained lower levels of hypermethylated expression from F0 adult, 24 h post-fertilization embryo, to F1 adult. In conclusion, these results indicated that an early high-carbohydrate stimulus could significantly reprogram glucose metabolism in adult zebrafish, that those modifications could be partially transmitted to the next generation, and that the DNA methylation of pck1 might work as a stable epigenetic marker to contribute to those processes.

Japanese encephalitis virus (JEV), an important neurotropic pathogen, belongs to the genus Flavivirus of the family Flaviviridae and has caused huge threat to public health. It is still obscure regarding the functions of stem-loop (SL) and dumbbell (DB) domains of JEV 3��� UTR in viral replication and virulence. In the current study, using the infectious clone of JEV SA14 strain as a backbone, we constructed a series of deletion mutants of 3��� UTR to investigate their effects on virus replication. The results showed that partial deletions within SL or DB domain had no apparent effects on virus replication in both mammalian (BHK-21) and mosquito (C6/36) cells, suggesting that they were not involved in viral host-specific replication. However, the entire SL domain deletion (��VR) significantly reduced virus replication in both cell lines, indicating the important role of the complete SL domain in virus replication. The revertant of ��VR mutant virus was obtained by serial passage in BHK-21 cells that acquired a duplication of DB domain (DB-dup) in the 3��� UTR, which greatly restored virus replication as well as the capability to produce the subgenomic flavivirus RNAs (sfRNAs). Interestingly, the DB-dup mutant virus was highly attenuated in C57BL/6 mice despite replicating similar to WT JEV. These findings demonstrate the significant roles of the duplicated structures in 3��� UTR in JEV replication and provide a novel strategy for the design of live-attenuated vaccines.

Tumor-associated macrophages (TAM) are the most abundant immune cells in the tumor microenvironment. They consist of various subsets but primarily resemble the M2 macrophage phenotype. TAMs are known to promote tumor progression and are associated with poor clinical outcomes. CD47 on tumor cells and SIRPα on TAMs facilitate a “don't-eat-me” signal which prevents cancer cells from immune clearance. Therefore, blockade of the CD47–SIRPα interaction represents a promising strategy for tumor immunotherapy. Here, we present the results on ZL-1201, a differentiated and potent anti-CD47 antibody with improved hematologic safety profile compared with 5F9 benchmark. ZL-1201 enhanced phagocytosis in combination with standards of care (SoC) therapeutic antibodies in in vitro coculture systems using a panel of tumor models and differentiated macrophages, and these combinational effects are Fc dependent while potently enhancing M2 phagocytosis. In vivo xenograft studies showed that enhanced antitumor activities were seen in a variety of tumor models treated with ZL-1201 in combination with other therapeutic mAbs, and maximal antitumor activities were achieved in the presence of chemotherapy in addition to the combination of ZL-1201 with other mAbs. Moreover, tumor-infiltrating immune cells and cytokine analysis showed that ZL-1201 and chemotherapies remodel the tumor microenvironment, which increases antitumor immunity, leading to augmented antitumor efficacy when combined with mAbs. Significance: ZL-1201 is a novel anti-CD47 antibody that has improved hematologic safety profiles and combines with SoC, including mAbs and chemotherapies, to potently facilitate phagocytosis and antitumor efficacy.

The horizontal strain in the vacuum preloading/dewatering of dredged slurry is significant to the apparent clogging effect and estimation of surface settlement around a drain; however, it has seldom been investigated in previous studies. In this study, a vacuum consolidation model test assisted by particle image velocimetry (PIV) technology was conducted. The displacement vector field was obtained through PIV analysis and image processing; it was used to visually observe the deformation features around a drain. Based on the displacement field, the vertical/horizontal strains at varied radial distances were calculated to explain the ‘soil pile’ and apparent clogging effect. From the strain distribution with radial distances, a significant lateral compression zone near the drain and an extension zone at farther areas were confirmed. Furthermore, a simple explicit model was established to evaluate the horizontal strain within a prefabricated vertical drain unit cell considering a horizontal attenuated vacuum and compression/extension zone. Finally, this method was applied to predict the horizontal displacement in the model test. The results showed that the proposed method can estimate the lateral displacement of soft clay slurry fairly well.

Wan-Yi Rao,1,&ast; Fang Xu,1,&ast; Shao-Bing Dai,1 Zhong Mei,2 Xiao-Ping Chen,1 Chang-Cheng Lv,1 Chun-Lei Liu,1 Warwick Ngan Kee,1 Xin-Zhong Chen1 1Department of Anesthesia, Women’s Hospital, Zhejiang University School of Medicine, Hangzhou, People’s Republic of China; 2Department of Anesthesiology, Affiliated Xiaoshan Hospital, Hangzhou Normal University, Hangzhou, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Xin-Zhong Chen, Department of Anesthesia, Women’s Hospital, Zhejiang University School of Medicine, No. 1 Bachelor’s Road, Hangzhou, 310000, People’s Republic of China, Email chenxinz@zju.edu.cnPurpose: Catheter-based techniques such as combined spinal-epidural (CSE) anesthesia which are sometimes indicated for obstetric anesthesia have a complex mechanism of action. The application of the dural puncture epidural (DPE) anesthesia for cesarean section (CS) has not been well investigated. The present study compared the relatively novel DPE technique with epidural (EA) and CSE anesthesia.Patients and Methods: We randomly assigned 150 parturients who underwent elective CS to receive DPE, EA or CSE anesthesia. The primary outcome was the onset of sensory anesthesia to the T5 dermatome assessed using the Cox proportional hazards model. Secondary outcomes included median time to sensory block, quality of block, patient and surgeon satisfaction, APGAR scores and other side effects.Results: For DPE anesthesia versus EA anesthesia, the onset of anesthesia was faster (hazard ratio 2.47 [95% CI 1.56 to 3.90], adjusted P < 0.001) and the median time to surgical level was shorter (16 [IQR 14– 18] min versus 19 [15.5– 21] min, adjusted P < 0.001); the incidence of intraoperative pain was lower (7/48 versus 17/47, adjusted P = 0.046) and the median patient satisfaction score was higher (9 [IQR 9– 10] versus 8 [8– 9.5], adjusted P = 0.004). In the CSE group, the onset of anesthesia was faster than in the other two but the incidence of hypotension was higher (P < 0.001) and the phenylephrine requirement was greater (P < 0.001).Conclusion: DPE anesthesia had a faster onset and better quality of block than EA anesthesia and provided less influence to maternal hemodynamic parameters than CSE anesthesia for CS. These results suggest that the dural puncture plays a significant role in enhancing the effectiveness of epidural top-ups during CSE anesthesia and indicates enlightenment that contributes to the satisfaction of anesthetic effect in DPE technique labor analgesia transferred to CS.Keywords: anesthesia, dural puncture epidural, anesthesia, epidural, cesarean section

Advancements in sensor technology, artificial intelligence (AI), and augmented reality (AR) have unlocked opportunities across various domains. AR and large language models like GPT have witnessed substantial progress and are increasingly being employed in diverse fields. One such promising application is in operations and maintenance (O&M). O&M tasks often involve complex procedures and sequences that can be challenging to memorize and execute correctly, particularly for novices or under high-stress situations. By marrying the advantages of superimposing virtual objects onto the physical world, and generating human-like text using GPT, we can revolutionize O&M operations. This study introduces a system that combines AR, Optical Character Recognition (OCR), and the GPT language model to optimize user performance while offering trustworthy interactions and alleviating workload in O&M tasks. This system provides an interactive virtual environment controlled by the Unity game engine, facilitating a seamless interaction between virtual and physical realities. A case study (N=15) is conducted to illustrate the findings and answer the research questions. The results indicate that users can complete similarly challenging tasks in less time using our proposed AR and AI system. Moreover, the collected data also suggests a reduction in cognitive load and an increase in trust when executing the same operations using the AR and AI system., 36 pages

During the manufacturing process of three-dimensions integrated circuits (3-D ICs), many defects may occur in through-silicon vias (TSVs). These defects affect integrity of the signal passing through TSVs, therefore detecting these defects in early production stage is crucial. This paper proposed a built-in-self-test (BIST) method with simple test structure and easily-implemented fault detection process. Due to the fact that the defects in TSVs influence the charge/discharge speed of TSVs’ equivalent capacitance, a weak current source is designed as the central part of the proposed test structure, which can measure the TSVs’ charge/discharge speed and quantify it using digital values. The effectiveness and robustness of the proposed method is validated by HSPICE simulation. The minimum measurable fault, test time and test circuit area are also assessed in this paper. The simulation results show that the method this paper proposed can detect weaker faults, compared with the traditional test methods.

In this article, we consider the formation tracking problem of nonholonomic multiagent systems only using relative bearing measurements between the agents. Such a practical and important yet challenging issue has been taken into limited consideration by existing approaches, which usually requires additional measurements such as relative positions. The contributions of this article are two-fold. First, a fully distributed reference velocity estimator is proposed. Under the proposed adaptive estimator, each agent can estimate the time-varying reference velocity asymptotically. Second, an input-to-state stable controller is designed according to the bearing rigid theory. Under the proposed controller, the formation with bearing-only constraints can be achieved. Finally, the proposed scheme is demonstrated and its effectiveness is verified by presenting some simulation and experimental tests.

BACKGROUND: Psoriasis is associated with an increased risk for cardiovascular disease (CVD). Methotrexate (MTX) is often used as a first-line system therapy and there is a need to determine its effect on whole blood viscosity (WBV) and plasma viscosity (PV) in psoriasis. METHODS A prospective, single-center, interventional study with a total of 111 psoriatic patients who received MTX therapy from October 22, 2018, to December 28, 2019, and 111 age- and sex-matched healthy controls. Changes in WBV, PV, blood counts, liver and renal function were evaluated. RESULTS Psoriatic patients had significantly higher levels of WBV and relative viscosity (RV) at low shear rate (LSR), erythrocyte aggregation index (EAI), and PV than sex and age-matched healthy controls. PV was positively correlated with erythrocyte sedimentation rate (ESR), ESR was positively correlated with high sensitive C-reactive protein (hCRP). But only hCRP was positively associated with psoriasis area severity index (PASI) score. MTX significantly decreased the levels of PV, ESR, hCRP, and blood pressure (BP) in male patients, and the level of WBV in female patients. CONCLUSION: Sex-specific downregulation of MTX on WBV, PV, hCRP, and BP, indicating that the effect of MTX on the risk of cardiovascular disease was related with sex.

Vertebral compression fractures are more common in the elderly, particularly in postmenopausal women. Most of these people are accompanied by osteoporosis, which can easily lead to spinal deformities and fractures. Once a fracture occurs, the patient would have severe pain response, limited spinal movement, and need to stay in bed for a long time, resulting in a significant decrease in their quality of life. Percutaneous vertebroplasty (PVP) is a minimally invasive spinal surgery that injects bone cement into the diseased vertebrae for therapeutic purposes. It can quickly relieve pain and stabilize the spine. It is widely used in the treatment of vertebral compression fractures and is currently an ideal treatment method. There are many materials of bone cement used in clinical treatment, and each material has unique characteristics. Many scholars would modify the bone cement according to the advantages and disadvantages to make it more suitable for clinical use. In this review, we discuss the clinical application and modification of bone cement.

The aims of the study were to develop and validate a machine learning classifier for preoperative prediction of tumor-infiltrating lymphocytes (TILs) in patients with pancreatic ductal adenocarcinoma (PDAC).In this retrospective study of 183 PDAC patients who underwent multidetector computed tomography and surgical resection, CD4 + , CD8 + , and CD20 + expression was evaluated using immunohistochemistry, and TIL scores were calculated using the Cox regression model. The patients were divided into TIL-low and TIL-high groups. An extreme gradient boosting (XGBoost) classifier was developed using a training set consisting of 136 consecutive patients, and the model was validated in 47 consecutive patients. The discriminative ability, calibration, and clinical utility of the XGBoost classifier were evaluated.The prediction model showed good discrimination in the training (area under the curve, 0.93; 95% confidence interval, 0.89-0.97) and validation (area under the curve, 0.79; 95% confidence interval, 0.65-0.92) sets with good calibration. The sensitivity, specificity, accuracy, positive predictive value, and negative predictive value for the training set were 0.93, 0.85, 0.90, 0.89, and 0.91, respectively, while those for the validation set were 0.63, 0.91, 0.77, 0.88, and 0.70, respectively.The XGBoost-based model could predict PDAC TILs and may facilitate clinical decision making for immune therapy.

The Qinghai-Tibet Plateau (QTP) is an important cushion plant hotspot. However, the distribution of cushion plants on the QTP is unknown, as are the factors that drive cushion plant distribution, limiting our understanding of the evolution of cushion species in the region. In this study, we assessed spatial patterns of total cushion plant diversity (including taxonomic and phylogenetic) over the entire QTP and compared patterns of diversity of cushion plants with different typologies (i.e., compact vs. loose). We also examined how these patterns were related to climatic features. Our results indicate that the southern QTP hosts the highest total cushion plant richness, especially in the south-central Hengduan Mountains subregion. The total number of cushion species declines from south to north and from southeast to northwest. Compact cushion plants exhibit similar patterns as the total cushion plant richness, whereas loose cushion plants show random distribution. Cushion plant phylogenetic diversity showed a similar pattern as that of the total cushion plant richness. In addition, cushion plant phylogenetic community structure was clustered in the eastern and southwestern QTP, whereas random or overdispersed in other areas. Climatic features represented by annual energy and water trends, seasonality and extreme environmental factors, had significant effects on cushion plant diversity patterns but limited effects on the phylogenetic community structure, suggesting that climatic features indeed promote the formation of cushion plants. Because cushion plants play vital roles in alpine ecosystems, our findings not only promote our understanding of the evolution and formation of alpine cushion plant diversity but also provide an indispensable foundation for future studies on cushion plant functions and thus alpine ecosystem sustainability in the entire QTP region.

To develop and validate a radiomics model to predict fibroblast activation protein (FAP) expression in patients with pancreatic ductal adenocarcinoma (PDAC).This retrospective study included consecutive 152 patients with PDAC who underwent MDCT scan and surgical resection from January 2017 to December 2017 (training set) and from January 2018 to April 2018 (validation set). In the training set, 1409 portal radiomic features were extracted from each patient's preoperative imaging. Optimal features were selected using the least absolute shrinkage and selection operator (LASSO) logistic regression algorithm, whereupon the extreme gradient boosting (XGBoost) was developed using the radiomics features. The performance of the XGBoost classifier performance was assessed by its calibration, discrimination, and clinical usefulness.The patients were divided into FAP-low (n = 91; 59.87%) and FAP-high (n = 61; 40.13%) groups according to the optimal FAP cutoff (45.71%). Patients in the FAP-low group showed longer survival. The XGBoost classifier comprised 13 selected radiomics features and showed good discrimination in the training set [area under the curve (AUC), 0.97] and the validation set (AUC, 0.75). It also performed well in the calibration test and decision-curve analysis, demonstrating its potential clinical value.The XGBoost classifier based on CT radiomics in the portal venous phase can non-invasively predict FAP expression and may help to improve clinical decision-making in patients with PDAC.

Objectives We aimed to develop and validate a multimodality radiomics model for the preoperative prediction of nonfunctional pancreatic neuroendocrine tumor (NF-pNET) grade (G). Methods This retrospective study assessed 123 patients with surgically resected, pathologically confirmed NF-pNETs who underwent multidetector computed tomography and MRI scans between December 2012 and May 2020. Radiomic features were extracted from multidetector computed tomography and MRI. Wilcoxon rank-sum test and Max-Relevance and Min-Redundancy tests were used to select the features. The linear discriminative analysis (LDA) was used to construct the four models including a clinical model, MRI radiomics model, computed tomography radiomics model, and mixed radiomics model. The performance of the models was assessed using a training cohort (82 patients) and a validation cohort (41 patients), and decision curve analysis was applied for clinical use. Results We successfully constructed 4 models to predict the tumor grade of NF- pNETs. Model 4 combined 6 features of T2-weighted imaging radiomics features and 1 arterial-phase computed tomography radiomics feature, and showed better discrimination in the training cohort (AUC = 0.92) and validation cohort (AUC = 0.85) relative to the other models. In the decision curves, if the threshold probability was 0.07–0.87, the use of the radiomics score to distinguish NF-pNET G1 and G2/3 offered more benefit than did the use of a “treat all patients” or a “treat none” scheme in the training cohort of the MRI radiomics model. Conclusion The LDA classifier combining multimodality images may be a valuable noninvasive tool for distinguishing NF-pNET grades and avoid unnecessary surgery.

Objective To develop and validate a magnetic resonance imaging (MRI)-based machine learning classifier for evaluating the tumor-stroma ratio (TSR) in patients with pancreatic ductal adenocarcinoma (PDAC). Materials and Methods In this retrospective study, 148 patients with PDAC underwent an MR scan and surgical resection. We used hematoxylin and eosin to quantify the TSR. For each patient, we extracted 1,409 radiomics features and reduced them using the least absolute shrinkage and selection operator logistic regression algorithm. The extreme gradient boosting (XGBoost) classifier was developed using a training set comprising 110 consecutive patients, admitted between December 2016 and December 2017. The model was validated in 38 consecutive patients, admitted between January 2018 and April 2018. We determined the performance of the XGBoost classifier based on its discriminative ability, calibration, and clinical utility. Results A log-rank test revealed significantly longer survival in the TSR-low group. The prediction model displayed good discrimination in the training (area under the curve [AUC], 0.82) and validation set (AUC, 0.78). While the sensitivity, specificity, accuracy, positive predictive value, and negative predictive value for the training set were 77.14%, 75.00%, 0.76%, 0.84%, and 0.65%, respectively, those for the validation set were 58.33%, 92.86%, 0.71%, 0.93%, and 0.57%, respectively. Conclusion We developed an XGBoost classifier based on MRI radiomics features, a non-invasive prediction tool that can evaluate the TSR of patients with PDAC. Moreover, it will provide a basis for interstitial targeted therapy selection and monitoring.

Heavy metal pollution caused by industrial wastewater such as mining and metallurgical wastewater is a major global concern. Therefore, this study used modified lignite as a low-cost adsorbent for heavy metal ions. Pingzhuang lignite was dissolved and modified using Fusarium lignite B3 to prepare a biotransformed-lignite adsorbent (BLA). The O, H, and N contents of the BLA increased after transformation, and the specific surface area increased from 1.81 to 5.66 m2·g−1. Various adsorption properties were investigated using an aqueous solution of Cu(Ⅱ). The kinetic and isothermal data were well-fitted by pseudo-second-order and Langmuir models, respectively. The Langmuir model showed that the theoretical Cu(II) adsorption capacity was 71.47 mg·g−1. Moreover, large particles and a neutral pH were favorable for the adsorption of heavy metal ions. The adsorption capacities of raw lignite and BLA were compared for various ions. Microbial transformation greatly improved the adsorption capacity, and the BLA had good adsorption and passivation effects with Cu(II), Mn(II), Cd(II), and Hg(II). Investigation of the structural properties showed that the porosity and specific surface area increased after biotransformation, and there were more active groups such as –COOH, Ar–OH, and R–OH, which were involved in the adsorption performance.

The longstanding muon (g−2) anomaly, as well as some hints of lepton flavor universality violation in B-meson decays, could be signaling new physics beyond the Standard Model (SM). A minimal R-parity-violating supersymmetric framework with light third-generation sfermions (dubbed as ‘RPV3’) provides a compelling solution to these flavor anomalies, while simultaneously addressing other pressing issues of the SM. We propose a new RPV3 scenario for the solution of the muon (g−2) anomaly, which leads to an interesting LHC signal of μ+μ−τ+τ− final state. We analyze the Run-2 LHC multilepton data to derive stringent constraints on the sneutrino mass and the relevant RPV coupling in this scenario. We then propose dedicated selection strategies to improve the bound even with the existing dataset. We also show that the high-luminosity LHC will completely cover the remaining muon (g−2)-preferred parameter space, thus providing a robust, independent test of the muon (g−2) anomaly.

The medaka (Oryzias latipes) is an excellent vertebrate model for studying the development of the retina. Its genome database is complete, and the number of opsin genes is relatively small compared to zebrafish. Short wavelength sensitive 2 (sws2), a G-protein-coupled receptor expressed in the retina, has been lost in mammals, but its role in eye development in fish is still poorly understood. In this study, we established a sws2a and sws2b knockout medaka model by CRISPR/Cas9 technology. We discovered that medaka sws2a and sws2b are mainly expressed in the eyes and may be regulated by growth differentiation factor 6a (gdf6a). Compared with the WT, sws2a−/− and sws2b−/− mutant larvae displayed an increase in swimming speed during the changes from light to dark. We also observed that sws2a−/− and sws2b−/− larvae both swam faster than WT in the first 10 s of the 2 min light period. The enhanced vision-guided behavior in sws2a−/− and sws2b−/− medaka larvae may be related to the upregulation of phototransduction-related genes. Additionally, we also found that sws2b affects the expression of eye development genes, while sws2a is unaffected. Together, these findings indicate that sws2a and sws2b knockouts increase vision-guided behavior and phototransduction, but on the other hand, sws2b plays an important role in regulating eye development genes. This study provides data for further understanding of the role of sws2a and sws2b in medaka retina development.

Accurate tool condition monitoring (TCM) is important for the development and upgrading of the manufacturing industry. Recently, machine-learning (ML) models have been widely used in the field of TCM with many favorable results. Nevertheless, in the actual industrial scenario, only a few samples are available for model training due to the cost of experiments, which significantly affects the performance of ML models. A time-series dimension expansion and transfer learning (TL) method is developed to boost the performance of TCM for small samples. First, a time-frequency Markov transition field (TFMTF) is proposed to encode the cutting force signal in the cutting process to two-dimensional images. Then, a modified TL network is established to learn and classify tool conditions under small samples. The performance of the proposed TFMTF-TL method is demonstrated by the benchmark PHM 2010 TCM dataset. The results show the proposed method effectively obtains superior classification accuracies for small samples and outperforms other four benchmark methods.

Background TDP-43 (43-kD transactive response DNA-binding protein) is a DNA-/RNA-binding protein that plays an important role in several nervous system diseases, such as amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). Whether it plays an important role in glioma patients is unknown. Methods Datasets were downloaded from the Chinese Glioma Genome Atlas (CGGA) website (http://www.cgga.org.cn/). Cox survival analysis was performed to determine the relationship between TARDBP gene expression and the overall survival of glioma patients. GO analyses were performed to determine the biological functions of the TARDBP gene. Finally, we used PRS type, age, grade, IDH mutation status, 1p/19q codeletion status, and expression value of the TARDBP gene to construct a prediction model. With this model, we can predict patients’ 1-, 2-, 3-, 5-, and 10-year survival rates. Results The TARDBP gene plays an important role in glioma patients. The expression of the TARDBP gene has a significant correlation with glioma patient survival. We also constructed an ideal prediction model. Conclusion Our findings suggest that the TARDBP gene and the protein it encodes play important roles in glioma patients. The expression of the TARDBP gene has a significant correlation with the overall survival of glioma patients.