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SPIRAL WAVE GENERATION IN A DIFFUSIVE PREDATOR-PREY MODEL WITH TWO TIME DELAYS
Wenzhen Gan,Peng Zhu 대한수학회 2015 대한수학회보 Vol.52 No.4
This paper is concerned with the pattern formation of a diffusive predator-prey model with two time delays. Based upon an analysis of Hopf bifurcation, we demonstrate that time delays can induce spatial patterns under some conditions. Moreover, by use of a series of numerical simulations, we show that the type of spatial patterns is the spiral wave. Finally, we demonstrate that the spiral wave is asymptotically stable.
SPIRAL WAVE GENERATION IN A DIFFUSIVE PREDATOR-PREY MODEL WITH TWO TIME DELAYS
GAN, WENZHEN,ZHU, PENG Korean Mathematical Society 2015 대한수학회보 Vol.52 No.4
This paper is concerned with the pattern formation of a diffusive predator-prey model with two time delays. Based upon an analysis of Hopf bifurcation, we demonstrate that time delays can induce spatial patterns under some conditions. Moreover, by use of a series of numerical simulations, we show that the type of spatial patterns is the spiral wave. Finally, we demonstrate that the spiral wave is asymptotically stable.
Manganese-based hollow nanoplatforms for MR imaging-guided cancer therapies
Shuang Liang,Guangfu Liao,Wenzhen Zhu,Li Zhang 한국생체재료학회 2022 생체재료학회지 Vol.26 No.3
Theranostic nanoplatforms integrating diagnostic and therapeutic functions have received considerable attention in the past decade. Among them, hollow manganese (Mn)-based nanoplatforms are superior since they combine the advantages of hollow structures and the intrinsic theranostic features of Mn2+. Specifically, the hollow cavity can encapsulate a variety of small-molecule drugs, such as chemotherapeutic agents, photosensitizers and photothermal agents, for chemotherapy, photodynamic therapy (PDT) and photothermal therapy (PTT), respectively. After degradation in the tumor microenvironment (TME), the released Mn2+ is able to act simultaneously as a magnetic resonance (MR) imaging contrast agent (CA) and as a Fenton-like agent for chemodynamic therapy (CDT). More importantly, synergistic treatment outcomes can be realized by reasonable and optimized design of the hollow nanosystems. This review summarizes various Mn-based hollow nanoplatforms, including hollow MnxOy, hollow matrix-supported MnxOy, hollow Mn-doped nanoparticles, hollow Mn complex-based nanoparticles, hollow Mn-cobalt (Co)-based nanoparticles, and hollow Mn-iron (Fe)-based nanoparticles, for MR imaging-guided cancer therapies. Finally, we discuss the potential obstacles and perspectives of these hollow Mn-based nanotheranostics for translational applications. Graphical AbstractMn-based hollow nanoplatforms such as hollow MnxOy nanoparticles, hollow matrix-supported MnxOy nanoparticles, Mn-doped hollow nanoparticles, Mn complex-based hollow nanoparticles, hollow Mn-Cobased nanoparticles and hollow Mn-Fe-based nanoparticles show great promise in cancer theranostics.
Simin Liu,Weiwei Chen,Min Wang,Tong Wu,Lingli Dong,Chu Pan,Wenzhen Zhu 대한영상의학회 2019 Korean Journal of Radiology Vol.20 No.3
Objective: To evaluate the secretory function of parotid glands by dynamic magnetic resonance (MR) sialography and determine the clinical performance of this technique in diagnosing and evaluating Sjögren’s syndrome (SS) patients. Materials and Methods: This study enrolled 29 healthy volunteers (25 women and 4 men; mean age, 34.8 ± 6.3 years; age range, 26–47 years) and 25 primary SS (pSS) patients (23 women and 2 men; mean age, 37.7 ± 7.9 years; age range, 25–50 years) with decreased secretory function. The volume of the parotid gland ducts was precisely measured for both groups at single pre- and 6 post-gustatory-stimulated phases. Time-dependent volume change ratio curves were generated, four parameters were derived from the curves: the slope of the increase in the first post-stimulation phase (slope1st), the peak value, the time-to-peak, the total saliva secretion post-stimulation. All values were used to quantitatively evaluate the secretory function of the parotid gland. The repeated measurement analysis, Mann-Whitney U test and receiver operating characteristic curve were applied. Results: Time-dependent volume change ratio curves demonstrated that there is a statistically significant difference between the two groups (F = 8.750; p = 0.005). A quickly increasing curve was shown in the volunteer group, whereas a slowly increasing curve was shown in the pSS patient group. The slope1st, peak value and total saliva secretion post-stimulation of the patient group were significantly lower than those of the volunteer group (p = 0.005, p = 0.003, and p = 0.002, respectively). The timeto-peak between the two groups was not significantly different (p = 0.383). The slope1st can be used as a discriminator to diagnose SS patients (p = 0.015; odds ratio = 4.234; area under the curve = 0.726). Conclusion: Dynamic MR sialography is proven to be an effective method in evaluating salivary gland function and has a great potential in diagnosing and evaluating pSS patients.
Feasibility of a Clinical-Radiomics Model to Predict the Outcomes of Acute Ischemic Stroke
Zhou Yiran,Wu Di,Yan Su,Xie Yan,Zhang Shun,Lv Wenzhi,Qin Yuanyuan,Liu Yufei,Liu Chengxia,Lu Jun,Li Jia,Zhu Hongquan,Liu Weiyin Vivian,Liu Huan,Zhang Guiling,Zhu Wenzhen 대한영상의학회 2022 Korean Journal of Radiology Vol.23 No.8
Objective: To develop a model incorporating radiomic features and clinical factors to accurately predict acute ischemic stroke (AIS) outcomes. Materials and Methods: Data from 522 AIS patients (382 male [73.2%]; mean age ± standard deviation, 58.9 ± 11.5 years) were randomly divided into the training (n = 311) and validation cohorts (n = 211). According to the modified Rankin Scale (mRS) at 6 months after hospital discharge, prognosis was dichotomized into good (mRS ≤ 2) and poor (mRS > 2); 1310 radiomics features were extracted from diffusion-weighted imaging and apparent diffusion coefficient maps. The minimum redundancy maximum relevance algorithm and the least absolute shrinkage and selection operator logistic regression method were implemented to select the features and establish a radiomics model. Univariable and multivariable logistic regression analyses were performed to identify the clinical factors and construct a clinical model. Ultimately, a multivariable logistic regression analysis incorporating independent clinical factors and radiomics score was implemented to establish the final combined prediction model using a backward step-down selection procedure, and a clinical-radiomics nomogram was developed. The models were evaluated using calibration, receiver operating characteristic (ROC), and decision curve analyses. Results: Age, sex, stroke history, diabetes, baseline mRS, baseline National Institutes of Health Stroke Scale score, and radiomics score were independent predictors of AIS outcomes. The area under the ROC curve of the clinical-radiomics model was 0.868 (95% confidence interval, 0.825–0.910) in the training cohort and 0.890 (0.844–0.936) in the validation cohort, which was significantly larger than that of the clinical or radiomics models. The clinical radiomics nomogram was well calibrated (p > 0.05). The decision curve analysis indicated its clinical usefulness. Conclusion: The clinical-radiomics model outperformed individual clinical or radiomics models and achieved satisfactory performance in predicting AIS outcome