Spinal cord injury (SCI) is a highly debilitating disease and is increasingly being recognized as an important global health priority. However, the mechanisms underlying SCI have not yet been fully elucidated, and effective therapies for SCI are lacking. Long noncoding RNAs (lncRNAs), which form a major class of noncoding RNAs, have emerged as novel targets for regulating several physiological functions and mediating numerous neurological diseases. Notably, gene expression profile analyses have demonstrated aberrant changes in lncRNA expression in rats or mice after traumatic or nontraumatic SCI. LncRNAs have been shown to be associated with multiple pathophysiological processes following SCI including inflammation, neural apoptosis, and oxidative stress. They also play a crucial role in the complications associated with SCI, such as neuropathic pain. At the same time, some lncRNAs have been found to be therapeutic targets for neural stem cell transplantation and hydrogen sulfide treatment aimed at alleviating SCI. Therefore, lncRNAs could be promising biomarkers for the diagnosis, treatment, and prognosis of SCI. However, further researches are required to clarify the therapeutic effects of lncRNAs on SCI and the mechanisms underlying these effects. In this study, we reviewed the current progress of the studies on the involvement of lncRNAs in SCI, with the aim of drawing attention towards their roles in this debilitating condition.
In this project, we propose a malaria model which takes into account the climate factors, the extrinsic incubation period (EIP) and the vector-bias effect. We first obtain the basic reproduction ratio R0 and then prove that it serves as a threshold parameter in determining the global dynamics of the model, that is, the disease-free periodic solution is globally attractive if R0 is less than one, and the system admits a unique positive periodic solution which is globally attractive if R0 is greater than one. Numerically, we study the malaria transmission case in Maputo Province, Mozambique. Our numerical simulations are consistent with the obtained analytic results. In addition, we observe that the ignorance of vector-bias effect may overestimate the number of the infectious humans and prolonging the length of the EIP is helpful for the control of the disease.
Malaria is an infectious disease caused by Plasmodium parasites and is transmitted among humans by female Anopheles mosquitoes. Climate factors have significant impact on both mosquito life cycle and parasite development. To consider the temperature sensitivity of the extrinsic incubation period (EIP) of malaria parasites, we formulate a delay differential equations model with a periodic time delay. We derive the basic reproduction ratio [Formula: see text] and establish a threshold type result on the global dynamics in terms of [Formula: see text], that is, the unique disease-free periodic solution is globally asymptotically stable if [Formula: see text]; and the model system admits a unique positive periodic solution which is globally asymptotically stable if [Formula: see text]. Numerically, we parameterize the model with data from Maputo Province, Mozambique, and simulate the long-term behavior of solutions. The simulation result is consistent with the obtained analytic result. In addition, we find that using the time-averaged EIP may underestimate the basic reproduction ratio.
Mosquito-borne diseases remain a significant threat to public health and economics. Since mosquitoes are quite sensitive to temperature, global warming may not only worsen the disease transmission case in current endemic areas but also facilitate mosquito population together with pathogens to establish in new regions. Therefore, understanding mosquito population dynamics under the impact of temperature is considerably important for making disease control policies. In this paper, we develop a stage-structured mosquito population model in the environment of a temperature-controlled experiment. The model turns out to be a system of periodic delay differential equations with periodic delays. We show that the basic reproduction number is a threshold parameter which determines whether the mosquito population goes to extinction or remains persistent. We then estimate the parameter values for Aedes aegypti, the mosquito that transmits dengue virus. We verify the analytic result by numerical simulations with the temperature data of Colombo, Sri Lanka where a dengue outbreak occurred in 2017.
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