Computational and Mathematical Methods in Medicine
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Acceptance rate32%
Submission to final decision46 days
Acceptance to publication39 days
CiteScore3.500
Journal Citation Indicator0.520
Impact Factor2.238

Analysis of Related Risk Factors of Microvascular Invasion in Hepatocellular Carcinoma

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Computational and Mathematical Methods in Medicine publishes research and review articles focused on the application of mathematics to problems arising from the biomedical sciences.

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Chief Editor, David Winkler's research focuses on dissecting the quantitative structure-activity method and rebuilding it with modern mathematical and AI methods, and adapting evolutionary methods to design of bioactive molecules and materials for diagnostics, therapeutics, and regeneration.

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Research Article

Protective Effect of Sufentanil on Myocardial Ischemia-Reperfusion Injury in Rats by Inhibiting Endoplasmic Reticulum Stress

Objective. Sufentanil is the most common drug in clinical practice for the treatment of ischemic heart disease. This study is to investigate the protective mechanism of sufentanil on rat myocardial ischemia-reperfusion (I/R) injury. Methods. A rat I/R model was established by ligating the left anterior descending coronary artery. A total of 24 SD male rats were enrolled and divided randomly into the control group, I/R group, sufentanil group (SUF; 3 μg/kg), and diltiazem group (DLZ; 20 mg/kg; positive control). The rat hearts were subjected to 30 min of ischemia followed by 120 min of reperfusion. Subsequently, hemodynamics, pathological changes of myocardial tissue, serum biochemical parameters, oxidative stress factors, the level of serum inducible nitric oxide synthases (iNOS), interleukin-6 (IL-6), and other bioactive factors were analyzed in the rats. Result. Compared with the I/R group, sufentanil significantly improved cardiac action, myocardial fiber, and cardiomyocyte morphology and reduced inflammatory cell infiltration in rats in the SUF group. And the level of creatine kinase isoenzyme (CK-MB), troponin (cTn), lactate dehydrogenase (LDH), malondialdehyde (MDA), iNOS, and IL-6 was significantly declined in the serum of SUF group, while the activities of glutathione peroxidase (GSH-Px) and superoxide dismutase (SOD) were significantly activated in the myocardial tissues. In addition, sufentanil also significantly decreased the protein expression of GRP78, CHOP, Caspase 12, and ATF6 in the myocardial tissue of the SUF group. Conclusion. Sufentanil has a significant protective activity on myocardial I/R injury in rats, the mechanism of which may be associated with the inhibition of endoplasmic reticulum stress and oxidative stress.

Research Article

Online Diagnosis and Classification of CT Images Collected by Internet of Things Using Deep Learning

Deep learning technology has recently played an important role in image, language processing, and feature extraction. In the past disease diagnosis, most medical staff fixed the images together for observation and then combined with their own work experience to judge. The diagnosis results are subjective, time-consuming, and inefficient. In order to improve the efficiency of diagnosis, this paper applies the deep learning algorithm to the online diagnosis and classification of CT images. Based on this, in this paper, the deep learning algorithm is applied to CT image online diagnosis and classification. Based on a brief analysis of the current situation of CT image classification, this paper proposes to use the Internet of things technology to collect CT image information and establishes the Internet of things to collect the CT image model. In view of image classification and diagnosis, the convolution neural network algorithm in the deep learning algorithm is proposed to diagnose and classify CT images, and several factors affecting the accuracy of classification are proposed, including the convolution number and network layer number. Using the CT image of the hospital brain for simulation analysis, the simulation results confirm the effectiveness of the deep learning algorithm. With the increase of convolution and network layer and the decrease of compensation, the accuracy of image classification will decline. Using the maximum pool method, reducing the step size can improve the classification effect. Using relu function as the activation function can improve the classification accuracy. In the process of large data set processing, appropriately adding a network layer can improve classification accuracy. In the diagnosis and analysis of brain CT images, the overall classification accuracy is close to 70%, and in the diagnosis of tumor diseases, the accuracy is higher, up to 80%.

Research Article

The Value of DTI Parameters in Predicting Postoperative Spinal Cord Function Fluctuations in Patients with High Cervical Disc Tumors

Objective. To explore the characteristics of magnetic resonance diffusion tensor imaging (DTI) parameters in patients with high cervical spinal myeloma and the evaluation of postoperative spinal cord function. Methods. In recent years, 42 patients with high cervical spine myeloma were selected as the observation group, and 42 healthy volunteers were selected as the control group during the same period. The apparent dispersion coefficient (ADC), the fractional anisotropy (FA), the number of fiber bundles (FT), and the fiber bundle ratio (FTR) were compared between the two groups. The correlation between the ADC, FA, FT, FTR, and the International Standard for Neurological Classification of Spinal Cord Injury (ISNCSCI) score in the observation group were analyzed. Spinal cord function was evaluated using the Japanese Orthopaedic Association Score (JOA). Logistic regression model was used to analyze the factors affecting the recovery of spinal cord function after surgery. The receiver operating characteristic curve (ROC) was used to analyze the value of ADC, FA, FT, FTR1, and FTR2 in predicting the recovery of spinal cord function. Results. The ADCs of the lesion layer and lower layer of the observation group were higher than the middle and lower layers of the control group, the FA and FT were lower than the middle and lower layers of the control group, and FTR1 and FTR2 were lower than those of the control group (). The ADC of the lesion layer in the observation group was negatively correlated with ISNCSCI score, and the FA, FT, FTR1, FTR2, and ISNCSCI scores were positively correlated (). Three months after the operation, JOA was used to evaluate the spinal cord function, which was excellent in 23 cases and poor in 19 cases. Logistic regression model analysis showed that after the ISNCSCI score was controlled, the increase in ADC and the decrease in FA, FT, FTR1, and FTR2 of the lesion layer were independent risk factors for poor postoperative body function recovery (). ROC analysis showed that the combination of ADC, FA, FT, FTR1, and FTR2 of the lesion layer predicted the AUC of spinal cord functional recovery was 0.941, which was better than the single prediction (). Conclusion. The abnormal DTI parameter values of patients with high cervical spinal myeloma can better reflect the lack of spinal cord function, and they can effectively predict the recovery of the patient’s body function after surgery, providing a reference for clinical diagnosis and treatment.

Research Article

Risk Prediction of Coronary Artery Stenosis in Patients with Coronary Heart Disease Based on Logistic Regression and Artificial Neural Network

Objective. Coronary heart disease (CHD) is considered an inflammatory relative disease. This study is aimed at analyzing the health information of serum interferon in CHD based on logistic regression and artificial neural network (ANN) model. Method. A total of 155 CHD patients diagnosed by coronary angiography in our department from January 2017 to March 2020 were included. All patients were randomly divided into a training set () and a test set (). Logistic regression and ANN models were constructed using the training set data. The predictive factors of coronary artery stenosis were screened, and the predictive effect of the model was evaluated by using the test set data. All the health information of participants was collected. Expressions of serum IFN-γ, MIG, and IP-10 were detected by double antibody sandwich ELISA. Spearman linear correlation analysis determined the relationship between the interferon and degree of stenosis. The logistic regression model was used to evaluate independent risk factors of CHD. Result. The Spearman correlation analysis showed that the degree of stenosis was positively correlated with serum IFN-γ, MIG, and IP-10 levels. The logistic regression analysis and ANN model showed that the MIG and IP-10 were independent predictors of Gensini score: MIG (95% CI: 0.876~0.934, ) and IP-10 (95% CI: 1.009~1.039, ). There was no statistically significant difference between the logistic regression and the ANN model (). Conclusion. The logistic regression model and ANN model have similar predictive performance for coronary artery stenosis risk factors in patients with CHD. In patients with CHD, the expression levels of IFN-γ, IP-10, and MIG are positively correlated with the degree of stenosis. The IP-10 and MIG are independent risk factors for coronary artery stenosis.

Research Article

Identification of Nine mRNA Signatures for Sepsis Using Random Forest

Sepsis has high fatality rates. Early diagnosis could increase its curating rates. There were no reliable molecular biomarkers to distinguish between infected and uninfected patients currently, which limit the treatment of sepsis. To this end, we analyzed gene expression datasets from the GEO database to identify its mRNA signature. First, two gene expression datasets (GSE154918 and GSE131761) were downloaded to identify the differentially expressed genes (DEGs) using Limma package. Totally 384 common DEGs were found in three contrast groups. We found that as the condition worsens, more genes were under disorder condition. Then, random forest model was performed with expression matrix of all genes as feature and disease state as label. After which 279 genes were left. We further analyzed the functions of 279 important DEGs, and their potential biological roles mainly focused on neutrophil threshing, neutrophil activation involved in immune response, neutrophil-mediated immunity, RAGE receptor binding, long-chain fatty acid binding, specific granule, tertiary granule, and secretory granule lumen. Finally, the top nine mRNAs (MCEMP1, PSTPIP2, CD177, GCA, NDUFAF1, CLIC1, UFD1, SEPT9, and UBE2A) associated with sepsis were considered as signatures for distinguishing between sepsis and healthy controls. Based on 5-fold cross-validation and leave-one-out cross-validation, the nine mRNA signature showed very high AUC.

Research Article

Comparative Analysis of Efficacy and Prognosis of Hemodialysis and Peritoneal Dialysis for End-Stage Renal Disease: A Meta-analysis

Objective. This meta-analysis is aimed at systematically assessing the efficacy and prognosis of hemodialysis (HD) and peritoneal dialysis (PD) in the treatment of end-stage renal disease (ESRD). Methods. China National Knowledge Infrastructure, VIP, SinoMed, Cochrane Library, PubMed, and Embase databases were searched for relevant studies to evaluate the two different dialysis methods for ESRD. The search time was set from 2010 to 2021. Meta-analysis was performed using Stata16.0. The treatment group received PD, while the control group was given HD. Results. Out of 317 articles initially retrieved, 14 studies were finally included in our meta-analysis. The analysis results showed that there was no marked difference in the 1-year survival rate between the two groups (; 95% CI: 1.00, 1.10; ), but the incidence rate of adverse reactions in the treatment group was significantly lower than that in the control group (; 95% CI: 0.37, 0.70; ). In addition, PD and HD treatments caused significant decreases in serum creatinine levels (PD, ; 95% CI: -3.79, -2.04; ; HD, ; 95% CI: -4.01, -2.16; ) and blood urea nitrogen levels (PD, , 95% CI: -3.37, -1.72, ; HD, , 95% CI: -3.47, -1.77, ); however, there was no significant statistical difference in posttreatment levels of serum creatinine and blood urea nitrogen between the two groups. Compared with the control group, the hemoglobin (, 95% CI: 0.07, 1.06; ) and serum albumin (, 95% CI: 0.46, 1.76, ) levels were significantly increased in the treatment group after treatment. Conclusion. In summary, both PD and HD can improve renal function in uremic patients, but PD is superior to HD in reducing the incidence of adverse reactions, improving the nutritional status, and therefore improving the quality of life of patients.

Computational and Mathematical Methods in Medicine
 Journal metrics
Acceptance rate32%
Submission to final decision46 days
Acceptance to publication39 days
CiteScore3.500
Journal Citation Indicator0.520
Impact Factor2.238
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