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"Jin, Zhen"
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Multi-region infectious disease prediction modeling based on spatio-temporal graph neural network and the dynamic model
Human mobility between different regions is a major factor in large-scale outbreaks of infectious diseases. Deep learning models incorporating infectious disease transmission dynamics for predicting the spread of multi-regional outbreaks due to human mobility have become a hot research topic. In this study, we incorporate the Graph Transformer Neural Network and graph learning mechanisms into a metapopulation SIR model to build a hybrid framework, Metapopulation Graph Transformer Neural Network (M-Graphormer), for high-dimensional parameter estimation and multi-regional epidemic prediction. The framework effectively solves the problem that existing models may lose some hidden spatial dependencies in the data when dealing with the dynamic graph structure of the network due to human mobility. We performed multi-wave infectious disease prediction in multiple regions based on real epidemic data. The results show that the framework is capable of performing high-dimensional parameter estimation and accurately predicting epidemic transmission dynamics in multiple regions even with low data quality. In addition, we retrospectively extrapolate the temporal evolution patterns of contact rate under different interventions implemented in different regions, reflecting the dynamics of intervention intensity and the need for flexibility in adjusting interventions in different regions. To provide early warning of infectious disease transmission, we retrospectively predicted the arrival time of infectious diseases using data from the early stages of outbreaks.
Journal Article
Delay-induced patterns in a predator-prey model on complex networks with diffusion
Reaction-diffusion (RD) systems with time delays have been commonly used in modeling biological systems and can significantly change the dynamics of these systems. For predator-prey model with modified Leslie-Gower and Holling-type III schemes governed by RD equations, instability induced by time delay can generate spiral waves. Considering that populations are usually organized as networks instead of being continuously distributed in space, it is essential to study the predator-prey model on complex networks. In this paper, we investigate instability induced by time delay for the corresponding network organized system and explore pattern formations on several different networks including deterministic networks and random networks. We firstly obtain instability condition via linear stability analysis and then the condition is applied to study pattern formations for the model in question. The simulation results show that wave patterns can be generated on different networks. However, wave patterns on random networks differ significantly from patterns on deterministic networks. Finally, we discuss the influences of network topology on wave patterns from the aspects of amplitude and period, and reveal the ecology significance implied by these results.
Journal Article
Current Nanoparticle-Based Technologies for Osteoarthritis Therapy
Osteoarthritis (OA) is a common chronic joint disease that is characterized by joint pain and stiffness, and limitation of motion and the major cause of disability, which reduces life quality of patients and brings a large economic burden to the family and society. Current clinical treatment is mostly limited to symptomatic treatment aimed at pain alleviation and functional improvement, rather than suppressing the progression of OA. Nanotechnology is a promising strategy for the treatment of OA. In this review, we summarize the current experimental progress that focuses on technologies such as liposomes, micelles, dendrimers, polymeric nanoparticles (PNPs), exosomes, and inorganic nanoparticles (NPs) for their potential treatment of OA.
Journal Article
Berberine protects rat heart from ischemia/ reperfusion injury via activating JAK2/STAT3 signaling and attenuating endoplasmic reticulum stress
Aim： Berberine （BBR）, an isoquinoline-derived alkaloid isolated from Rhizoma coptidis, exerts cardioprotective effects. Because endoplasmic reticulum （ER） stress plays a pivotal role in myocardial ischemia/reperfusion （MI/R）-induced apoptosis, it was interesting to examine whether the protective effects of BBR resulted from modulating ER stress levels during MI/R injury, and to define the signaling mechanisms in this process. Methods： Male rats were treated with BBR （200 mg.k-1.d-1, ig） for 2 weeks, and then subjected to MI/R surgery. Cardiac dimensions and function were assessed using echocardiography. Myocardial infarct size and apoptosis was examined. Total serum LDH levels and CK activities, superoxide production, MDA levels and the antioxidant SOD activities in heart tissue were determined. An in vitro study was performed on cultured rat embryonic myocardium-derived cells H9C2 exposed to simulated ischemia/reperfusion （SIR）. The expression of apoptotic, ER stress-related and signaling proteins were assessed using Western blot analyses.Results： Pretreatment with BBR significantly reduced MI/R-induced myocardial infarct size, improved cardiac function, and suppressed myocardial apoptosis and oxidative damage. Furthermore, pretreatment with BBR suppressed MI/R-induced ER stress, evidenced by down-regulating the phosphorylation levels of myocardial PERK and elF2a and the expression of ATF4 and CHOP in heart tissues. Pretreatment with BBR also activated the JAK2/STAT3 signaling pathway in heart tissues, and co-treatment with AG490, a specific JAK2/STAT3 inhibitor, blocked not only the protective effects of BBR, but also the inhibition of BBR on MI/R-induced ER stress. In H9C2 cells, treatment with BBR （50 pmol/L） markedly reduced SIR-induced cell apoptosis, oxidative stress and ER stress, which were abolished by transfection with JAK2 siRNA. Conclusion： BBR ameliorates MI/R injury in rats by activating the AK2/STAT3 signaling pathway and attenuating ER stress-induced apoptosis.
Journal Article
Comparative Performance of Endoscopic Ultrasound-Based Techniques in Patients With Pancreatic Cystic Lesions: A Network Meta-Analysis
Evidence on the comparative diagnostic performance of endoscopic ultrasound (EUS)-based techniques for pancreatic cystic lesions (PCLs) is limited. This network meta-analysis comprehensively compared EUS-based techniques for PCL diagnosis.
A comprehensive literature search was performed for all comparative studies assessing the accuracy of 2 or more modalities for PCL diagnosis. The primary outcome was the diagnostic efficacy for mucinous PCLs. Secondary outcomes were the diagnostic efficacy for malignant PCLs, diagnostic success rate, and adverse event rate. A network meta-analysis was conducted using the ANOVA model to assess the diagnostic accuracy of each index.
Forty studies comprising 3,641 patients were identified. The network ranking of the superiority index for EUS-guided needle-based confocal laser endomicroscopy (EUS-nCLE) and EUS-guided through-the-needle biopsy (EUS-TTNB) were significantly higher than other techniques for differentiating mucinous PCLs; besides, EUS-TTNB was also the optimal technique in identifying malignant PCLs. The evidence was inadequate for EUS-nCLE diagnosing malignant PCLs and contrast-enhanced harmonic EUS diagnosing both mucinous and malignant PCLs. Glucose showed a high sensitivity but low specificity, and molecular analysis (KRAS, GNAS, and KRAS + GNAS mutations) showed a high specificity but low sensitivity for diagnosing mucinous PCLs. Satisfactory results were not obtained during the evaluation of the efficiency of pancreatic cyst fluid (PCF) biomarkers in detecting malignant PCLs.
For centers with relevant expertise and facilities, EUS-TTNB and EUS-nCLE were better choices for the diagnosis of PCLs. Further studies are urgently required for further improving PCF biomarkers and validating the diagnostic performance of the index techniques.
Journal Article
Comparison of Chondrocyte Behaviors Between Silk Microfibers and Polycaprolactone Microfibers in Tissue Engineering and Regenerative Medicine Applications
Silk and polycaprolactone (PCL), derived from natural and synthetic sources, respectively, are suture materials commonly used in surgery. Beyond their application in sutures, they are also compelling subjects in regenerative medicine and tissue engineering. This study evaluated the effects of degummed silk microfibers compared to electrospun PCL microfibers of a similar diameter on chondrocyte behavior. The two types of microfibers were analyzed using scanning electron microscopy (SEM), real-time PCR, Western blotting, and DMMB analysis. The results demonstrated that the silk microfibers exhibited a higher proliferative cell rate over time compared to the PCL microfibers. Additionally, the expression of chondrogenic phenotypes was significantly upregulated, while the marker for hypertrophic chondrocytes—type X collagen—was downregulated in cell-laden silk microfibers compared to cell-laden PCL microfibers. These findings suggest that natural degummed silk microfibers may be a viable option for repairing damaged cartilage in the future of orthopedic surgery and bioengineering.
Journal Article
A stochastic model explains the periodicity phenomenon of influenza on network
Influenza is an infectious disease with obvious periodic changes over time. It is of great practical significance to explore the non-environment-related factors that cause this regularity for influenza control and individual protection. In this paper, based on the randomness of population number and the heterogeneity of population contact, we have established a stochastic infectious disease model about influenza based on the degree of the network, and obtained the power spectral density function by using the van Kampen expansion method of the master equation. The relevant parameters are obtained by fitting the influenza data of sentinel hospitals. The results of the numerical analysis show that: (1) for the infected, the infection period of patients who go to the sentinel hospitals is particularly different from the others who do not; (2) for all the infected, there is an obvious nonlinear relationship between their infection period and the visiting rate of the influenza sentinel hospitals, the infection rate and the degree. Among them, only the infection period of patients who do not go to the sentinel hospitals decreased monotonously with the infection rate (increased monotonously with the visiting rate), while the rest had a non-monotonic relationship.
Journal Article
Transmission dynamics of COVID-19 in Wuhan, China: effects of lockdown and medical resources
Due to the strong infectivity of COVID-19, it spread all over the world in about three months and thus has been studied from different aspects including its source of infection, pathological characteristics, diagnostic technology and treatment. Yet, the influences of control strategies on the transmission dynamics of COVID-19 are far from being well understood. In order to reveal the mechanisms of disease spread, we present dynamical models to show the propagation of COVID-19 in Wuhan. Based on mathematical analysis and data analysis, we systematically explore the effects of lockdown and medical resources on the COVID-19 transmission in Wuhan. It is found that the later lockdown is adopted by Wuhan, the fewer people will be infected in Wuhan, and nevertheless it will have an impact on other cities in China and even the world. Moreover, the richer the medical resources, the higher the peak of new infection, but the smaller the final scale. These findings well indicate that the control measures taken by the Chinese government are correct and timely.
Journal Article
The association between potassium level during the anhepatic stage of orthotopic liver transplantation and postoperative acute kidney injury: an exploratory study
Background
Acute kidney injury (AKI) refers to a clinical syndrome characterized by a sudden decrease in kidney function over a short period, with clinical manifestations ranging from a slight increase in serum creatinine to anuric renal failure.As a common complication following liver transplantation (LT), often accompanying significant electrolyte imbalances. The predictive value of serum potassium imbalances for the development of AKI in LT merits further investigation. Our study focuses on examining the correlation between the two variables then evaluates the efficacy of potassium levels as a predictive biomarker.
Methods
In this single-center, retrospective study, we examined 136 adult patients who underwent orthotopic LT at Qingdao University Affiliated Hospital from October 1, 2022 to July 31, 2023. Patients were stratified by their serum potassium levels during the anhepatic stage (Group A 3.0 ≤ K + ≤ 3.5; Group B 3.6 ≤ K + ≤ 4.0; Group C 4.1 ≤ K + ≤ 4.5). Their intraoperative potassium fluctuations and postoperative AKI were compared. Logistic regression analysis was conducted to determine risk factors for AKI. The receiver operating characteristic curve was utilized to assess the predictive value of intraoperative serum potassium for AKI.
Results
In neo-hepatic phase, potassium levels peaked early and then declined, with Group C showing higher rates of post-reperfusion hyperkalemia and AKI (
p
< 0.05). Regression analysis identified anhepatic potassium (OR:9.597,95%CI:3.169,29.064) as independent predictors of AKI following LT. The receiver operating characteristic curve revealed an optimal potassium cutoff of 4.05 mmol/L.
Conclusion
This study indicates that serum potassium at anhepatic stage is an independent risk factor for AKI following LT, capable of predicting the onset of AKI.
Trial registration
This study is a retrospective study, and it has already been approved by the Ethics Committee.
Journal Article