Abstract Objective: To explore the relationship between the circular clock gene NPAS2 (neural PAS domain protein 2) and the survival prognosis of gastric cancer (GC) patients and clarify its role in evaluating GC prognosis. Methods: The tumor tissues and clinical data of 101 patients with GC were collected retrospectively. Immunohistochemical staining (IHC) was used to detect the expression of NPAS2 protein in GC and adjacent tissues. Univariate and multivariate Cox regression analysis was used to determine the independent prognostic factors of GC, and a nomogram prediction model was established. The ROC curve, the ROC area under the curve (AUC), the calibration curve, and C-index were used to evaluate the predictive effectiveness of the model. Kaplan Meier analysiswas used to compare the risk stratification of subgroups according to the median score in the nomogram model of each patient. Results: Microarray IHC analysis showed that the positive rate of NPAS2 protein expression in GC tissues was 65.35%, which was significantly higher than 30.69% in adjacent tissues. The high expression of NPAS2 was correlated with TNM stage (P<0.05), pN stage (P<0.05), metastasis (P<0.05), venous invasion (P<0.05), lymphatic invasion (P<0.05), and lymph node positive (P<0.05) of GC. Kaplan Meier survival analysis showed that the 3-year overall survival (OS) of patients with high NPAS2 expression was significantly shortened (P<0.0001). Univariate and multivariate COX regression analysis showed that TNM stage (P=0.009), metastasis (P=0.009), and NPAS2 expression (P=0.020) were independent prognostic factors of OS in GC patients for 3 years. The nomogram prediction model based on independent prognostic factors has a C-Index of 0.740 (95% CI: 0.713-0.767). Furthermore, subgroup analysis showed that the 3-year OS time of the high-risk group was significantly lower than that of the low-risk group (P<0.0001). Conclusion: NPAS2 is highly expressed in GC tissues and is closely related to worse OS in patients. Therefore, the evaluation of NPAS2 expression may be a potential marker for GC prognosis evaluation. Notably, the nomogram model based on NPAS2 can improve the accuracy of GC prognosis prediction and assist clinicians in postoperative patient management and decision-making.
The failure of cutting tools significantly decreases machining productivity and product quality; thus, tool condition monitoring is significant in modern manufacturing processes. A new method that is based on singular spectrum analysis and Mahalanobis distance are combined to extract the crucial characteristics from spindle motor current to monitor the tool's condition. The singular spectrum analysis is a novel nonparametric technique for extracting the properties of nonlinear and nonstationary signals. However, because the components are not completely independent, the original singular spectrum analysis eventually leads to misinterpretation of the final results. The proposed method is used to overcome the weakness of the original singular spectrum analysis. The singular spectrum analysis algorithm is adopted to decompose the original signal and the useful singular values that correspond to the tool condition can be extracted. The Mahalanobis distance of the singular values is proposed as a feature that can effectively express the tool condition. The experiments on a CNC Vertical Machining Center demonstrate that this method is effective and can accurately detect the tool breakage in mill process.
The prognostic assessment of patients after surgical resection of gastric cancer (GC) patients is critical. However, the role of the circadian clock gene NPAS2 expression in GC remains unknown.To explore the relationship between NPAS2 and the survival prognosis of GC patients and clarify its role in evaluating GC prognosis.The tumor tissues and clinical data of 101 patients with GC were collected retrospectively. Immunohistochemical staining (IHC) was used to detect the expression of NPAS2 protein in GC and adjacent tissues. Univariate and multivariate Cox regression analysis was used to determine the independent prognostic factors of GC, and a nomogram prediction model was established. The receiver operating characteristic (ROC) curve, the ROC area under the curve, the calibration curve, and C-index were used to evaluate the predictive effectiveness of the model. Kaplan Meier analysis was used to compare the risk stratification of subgroups according to the median score in the nomogram model of each patient.Microarray IHC analysis showed that the positive rate of NPAS2 protein expression in GC tissues was 65.35%, which was significantly higher than 30.69% in adjacent tissues. The high expression of NPAS2 was correlated with tumor-node-metastasis (TNM) stage (P < 0.05), pN stage (P < 0.05), metastasis (P < 0.05), venous invasion (P < 0.05), lymphatic invasion (P < 0.05), and lymph node positive (P < 0.05) of GC. Kaplan Meier survival analysis showed that the 3-year overall survival (OS) of patients with high NPAS2 expression was significantly shortened (P < 0.0001). Univariate and multivariate COX regression analysis showed that TNM stage (P = 0.009), metastasis (P = 0.009), and NPAS2 expression (P = 0.020) were independent prognostic factors of OS in GC patients for 3 years. The nomogram prediction model based on independent prognostic factors has a C-Index of 0.740 (95%CI: 0.713-0.767). Furthermore, subgroup analysis showed that the 3-year OS time of the high-risk group was significantly lower than that of the low-risk group (P < 0.0001).NPAS2 is highly expressed in GC tissues and is closely related to worse OS in patients. Therefore, the evaluation of NPAS2 expression may be a potential marker for GC prognosis evaluation. Notably, the nomogram model based on NPAS2 can improve the accuracy of GC prognosis prediction and assist clinicians in postoperative patient management and decision-making.
NPM1 plays an important role in the occurrence and development of leukemia and various solid tumors. This study aimed to investigate the expression of NPM1 in gastric cancer (GC) and adjacent normal tissues, study the relationship between NPM1 expression and clinicopathological characteristics in GC patients, and explore the impact of NPM1 expression on the diagnosis and prognosis of GC. We used tissue microarray immunohistochemical analysis to examine the expression level of NPM1 in GC and adjacent tissues and analyzed the relationship between NPM1 expression, clinicopathological factors, and GC prognosis. Prognostic values of NPM1 mRNA were also investigated using an online database. qRT-PCR was used to detect the expression of NPM1 mRNA in cancer and adjacent tissues. According to microarray immunohistochemical analysis and qRT-PCR results, NPM1 had a high expression in all adjacent normal tissues. Microarray immunohistochemical analyses demonstrated that the NPM1 was lowly expressed in 75.5% of GC tissues but highly expressed in 24.5% of GC tissues. qRT-PCR results showed NPM1 mRNA low expression in most GC tissues. NPM1 high expression group was associated with a better overall survival rate and disease-free survival rate than the NPM1 low expression group (p<0.01). This result is consistent with that of the online database. The receiver operating characteristics curve showed that NPM1 was valuable in the diagnosis of GC. The assessment of NPM1 expression in GC samples may represent a useful tool for GC diagnosis and prognosis assessment.
Abstract Background and aims: NPM1 plays an important role in the occurrence and development of leukemia, and its role in some solid tumors has gradually received attention. The purpose of this study is to explore the expression of NPM1 in gastric cancer (GC) tissues, to study the relationship between NPM1 expression and clinicopathological characteristics of GC patients, and to study the influence of NPM1 expression levels on the prognosis of GC patients. Methods: The study was conducted from tissue samples obtained after radical gastrectomy in 106 patients with GC. We used tissue microarray immunohistochemical analysis to examine the expression level of NPM1 in different GC and adjacent tissues, and finally analyzed the relationship between NPM1 expression, clinicopathological factors and survival rate. Results: Compared with the corresponding adjacent tissues, NPM1 is low-expressed in 75.5% of GC tissues. High NPM1 expression group was associated with better overall survival rate and disease free survival rate compared to low NPM1 expression group with GC ( p <0.01). Conclusion： The assessment of NPM1 expression in GC samples may represent a useful tool for GC diagnosis and prognostic prediction. Nonetheless, our study should be regarded as a preliminary study, and its predictive value as a single-center retrospective study is limited.
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