[MPV17 inhibits iron overload-induced ferroptosis of splenic CD3+ T cells in mice by blocking ERK pathway].

Objective This work aimed to explore the effect of iron overload on splenic injury and the role of MPV17 in the ferroptosis of splenic CD3+ T cells from mice subjected to iron overload. Methods Mice were randomly divided into normal diet group, high-iron diet group, high-iron diet combined with Fer-1 treatment group, and high-iron diet combined with adenovirus harboring MPV17 injection group, with 5 mice in each group. After treatment for 8 weeks, mice spleens were harvested and fixed; Histological section and HE staining were performed to observe the structures of the spleens; Cell death of CD3+ T cells was detected by propidium iodide (PI) staining; The lipid peroxidation levels were detected by C11 BODIPY581/591 staining; The mRNA levels of Solute carrier family 7 member 11 (SLC7A11) and prostaglandin-endoperoxide synthase 2 (PTGS2) were detected by qPCR assays; The macrophage phenotype-switching (M1/M2) were detected by flow cytometry; The levels of TNF-α, IL-1ß and IL-6 were measured by ELISA assays. Moreover, high-iron diet combined with extracellular signal-regulated kinase (ERK) inhibitor treatment group, ERK agonist treatment group, ß-gal combined with ERK agonist treatment group, and MPV17 overexpression combined with ERK agonist treatment group were added. The protein levels of MPV17, glutathione peroxidase 4 (GPX4) and phosphorylated ERK (p-ERK) were detected by Western blot; The mitochondrial membrane potential was detected by JC-1 staining and flow cytometry. Results Compared with the normal diet group, the red pulps of the mice spleens from the high-iron diet group showed irregular structures and the white pulps were almost missing; Cell death, lipid peroxides, and the expression levels of SLC7A11 and PTGS2 increased; Both the ratio of M1 macrophages to M2 macrophages and the levels of inflammatory factors increased. Fer-1 treatment or overexpression of MPV17 in the high-iron diet mice group partially recovered the irregular structures of the spleens, reduced cell death and lipid peroxides in CD3+ T cells, and decreased the expression levels of SLC7A11 and PTGS2; The ratio of M1/M2 macrophages and the levels of inflammatory factors were decreased. High-iron diet decreased the protein levels of GPX4 while p-ERK were up-regulated. Inhibition of ERK partially recovered the protein levels of GPX4; ERK agonist decreased the protein levels of GPX4; MPV17 inhibited the ERK signaling and partially recovered the protein levels of GPX4 and the decreased mitochondrial membrane potential of CD3+ T induced by ERK activation. Conclusion Iron overload resulted in splenic injury and ferroptosis in the splenic CD3+ T cells; MPV17 prevented splenic injury and ferroptosis of splenic CD3+ T cells of the iron overload mice through blocking ERK signaling pathway.

Development and validation of a clinical prediction model for ischemic stroke recurrence after successful stent implantation in symptomatic intracranial atherosclerotic stenosis.

OBJECTIVE: This study aimed to analyze the risk factors for recurrent ischemic stroke in patients with symptomatic intracranial atherosclerotic stenosis (ICAS) who underwent successful stent placement and to establish a nomogram prediction model. METHODS: We utilized data from a prospective collection of 430 consecutive patients at Jining NO.1 People's Hospital from November 2021 to November 2022, conducting further analysis on the subset of 400 patients who met the inclusion criteria. They were further divided into training (n=321) and validation (n=79) groups. In the training group, we used univariate and multivariate COX regression to find independent risk factors for recurrent stroke and then created a nomogram. The assessment of the nomogram's discrimination and calibration was performed through the examination of various measures including the Consistency index (C-index), the area under the receiver operating characteristic (ROC) curves (AUC), and the calibration plots. Decision curve analysis (DCA) was used to evaluate the clinical utility of the nomogram by quantifying the net benefit to the patient under different threshold probabilities. RESULTS: The nomogram for predicting recurrent ischemic stroke in symptomatic ICAS patients after stent placement utilizes six variables: coronary heart disease (CHD), smoking, multiple ICAS, systolic blood pressure (SBP), in-stent restenosis (ISR), and fasting plasma glucose. The C-index (0.884 for the training cohort and 0.87 for the validation cohort) and the time-dependent AUC (>0.7) indicated satisfactory discriminative ability of the nomogram. Furthermore, DCA indicated a clinical net benefit from the nomogram. CONCLUSIONS: The predictive model constructed includes six predictive factors: CHD, smoking, multiple ICAS, SBP, ISR and fasting blood glucose. The model demonstrates good predictive ability and can be utilized to predict ischemic stroke recurrence in patients with symptomatic ICAS after successful stent placement.

Dynamical modeling the effect of glucagon-like peptide on glucose-insulin regulatory system based on mice experimental observation.

As an emerging global epidemic, type 2 diabetes mellitus (T2DM) represents one of the leading causes of morbidity and mortality worldwide. Existing evidences demonstrated that glucagon-like peptide-1 (GLP-1) modulate the glucose regulatory system by enhancing the ß-cell function. However, the detailed process of GLP-1 in glycaemic regulator for T2DM remains to be clarified. Thus, in this study, we propose an Institute of Cancer Research (ICR) mice high fat and cholesterol dietary experimental data-driven mathematical model to investigate the secretory effect of GLP-1 on the dynamics of glucose-insulin regulatory system. Specifically, we develop a mathematical model of GLP-1 dynamics as part of the interaction model of ß-cell, insulin, and glucose dynamics. The parameter estimation and data fitting are in agreement with the data in mice experiments In addition, uncertainty quantification is performed to explore the possible factors that influence the pathways leading to the pathological state. Model analyses reveal that the high fat or high cholesterol diet stimulated GLP-1 plays an important role in the dynamics of glucose, insulin and ß cells in short-term. These results show that enhanced GLP-1 may mitigate the dysregulation of glucose-insulin regulatory system via promoting the ß cells function and stimulating secretion of insulin, which offers an in-depth insights into the mechanistic of hyperglycemia from dynamical approach and provide the theoretical basis for GLP-1 served as a potential clinical targeted drug for treatment of T2DM.

Spatial Heterogeneity and Its Influencing Factors of Syphilis in Ningxia, Northwest China, from 2004 to 2017: A Spatial Analysis.

Syphilis remains a growing and resurging infectious disease in China. However, exploring the influence of environmental factors on the spatiotemporal distribution of syphilis remains under explore. This study aims to analyze the spatiotemporal distribution characteristics of syphilis in Ningxia, Northwest China, and its potential environmental influencing factors. Based on the standardized incidence ratio of syphilis for 22 administrative areas in Ningxia from 2004 to 2017, spatiotemporal autocorrelation and scan analyses were employed to analyze the spatial and temporal distribution characteristics of syphilis incidence, while a fixed-effect spatial panel regression model identified the potential factors affecting syphilis incidence. Syphilis incidence increased from 3.78/100,000 in 2004 to 54.69/100,000 in 2017 with significant spatial clustering in 2007 and 2009-2013. The "high-high" and "low-low" clusters were mainly distributed in northern and southern Ningxia, respectively. The spatial error panel model demonstrated that the syphilis incidence may be positively correlated with the per capita GDP and tertiary industry GDP and negatively correlated with the number of health facilities and healthcare personnel. Sex ratio and meteorological factors were not significantly associated with syphilis incidence. These results show that the syphilis incidence in Ningxia is still increasing and has significant spatial distribution differences and clustering. Socio-economic and health-resource factors could affect the incidence; therefore, strengthening syphilis surveillance of migrants in the economically developed region and allocating health resources to economically underdeveloped areas may effectively help prevent and control syphilis outbreaks in high-risk cluster areas of Ningxia.

The effect of public health awareness and behaviors on the transmission dynamics of syphilis in Northwest China, 2006-2018, based on a multiple-stages mathematical model.

Syphilis, a sexually transmitted infectious disease caused by the bacterium treponema pallidum, has re-emerged as a global public health issue with an estimated 12 million people infected each year. Understanding the impacts of health awareness and behaviors on transmission dynamics of syphilis can help to establish optimal control strategy in different regions. In this paper, we develop a multiple-stage SIRS epidemic model taking into account the public health awareness and behaviors of syphilis. First, the basic reproduction number R 0 is obtained, which determines the global dynamics behaviors of the model. We derive the necessary conditions for implementing optimal control and the corresponding optimal solution for mitigation syphilis by using Pontryagin's Maximum Principle. Based on the data of syphilis in Ningxia from 2006 to 2018, the parameterizations and model calibration are carried out. The fitting results are in good agreement with the data. Moreover, sensitivity analysis shows that the public awareness induced protective behaviors C e , compliance of condom-induced preventability ε and treatment for the primary syphilis m 1 play an important role in mitigating the risk of syphilis outbreaks. These results can help us gain insights into the epidemiology of syphilis and provide guidance for the public health authorities to implement health education programs.

Incorporating textual network improves Chinese stock market analysis.

This study adopts the textual network to describe the coordination among the interplay of words, where nodes represent words and nodes are connected if the corresponding words have co-occurrence pattern across documents. To study stock movements, we further proposed the sparse laplacian shrinkage logistic model (SLS_L) which can properly take into account the network connectivity structure. By using this approach, we investigated the relationship between Shenwan index and analysts' research reports. The securities analysts' research reports are crawled by a famous financial website in China: EastMoney, and are then parsed into time-series textual data. The empirical results show that the proposed SLS_L model outperforms alternatives including Lasso-Logistics (L_L) and MCP-Logistic (MCP_L) models by having better prediction performance. Besides, we search published literature and find the identified keywords with more lucid interpretations. Our study unveils some interesting findings that the efficient use of textual network is important to improve the predictive power as well as the semantic interpretability in stock market analysis.

Avian Influenza A (H7N9) Model Based on Poultry Transport Network in China.

In order to analyze the spread of avian influenza A (H7N9), we construct an avian influenza transmission model from poultry (including poultry farm, backyard poultry farm, live-poultry wholesale market, and wet market) to human according to poultry transport network. We obtain the threshold value for the prevalence of avian influenza A (H7N9) and also give the existence and number of the boundary equilibria and endemic equilibria in different conditions. We can see that poultry transport network plays an important role in controlling avian influenza A (H7N9). Finally, numerical simulations are presented to illustrate the effects of poultry in different places on avian influenza. In order to reduce human infections in China, our results suggest that closing the retail live-poultry market or preventing the poultry of backyard poultry farm into the live-poultry market is feasible in a suitable condition.

An SIR pairwise epidemic model with infection age and demography.

The demography and infection age play an important role in the spread of slowly progressive diseases. To investigate their effects on the disease spreading, we propose a pairwise epidemic model with infection age and demography on dynamic networks. The basic reproduction number of this model is derived. It is proved that there is a disease-free equilibrium which is globally asymptotically stable if the basic reproduction number is less that unity. Besides, sensitivity analysis is performed and shows that increasing the variance in recovery time and decreasing the variance in infection time can effectively control the diseases. The complex interaction between the death rate and equilibrium prevalence suggests that it is imperative to correctly estimate the parameters of demography in order to assess the disease transmission dynamics accurately. Moreover, numerical simulations show that the endemic equilibrium is globally asymptotically stable.