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In this task, you're given a paragraph from the research paper and your task is to generate a suitable title for the research paper based on the given paper. Under 100 words is a good title length.
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Toxoplasma gondii is a worldwide spread protozoan and is able to infect almost all warm-blood animals. No effective drugs are available clinically on toxoplasmosis. Chinese traditional herbal medicines have provided remedies for many health problems. There exists a possibility that Chinese herbs may provide protection against T. gondii. This work aims to assess the protective efficacy of combined Chinese herbs against T. gondii. We screened five herbal medicines that have different pharmacological effects and combined them into a prescription according to the traditional Chinese medicine compatibility principle. The drug potential and protective efficacy were evaluated through a mouse model by determining the survival time, the parasite load in blood and tissues, the change of cell proportions in blood and histological detection. The results showed that the survival time of mice in the 500 mg Chinese herbs group and sulfadiazine group was significantly longer than that of the PBS control group. Also the parasite load in blood and tissues of 500 mg Chinese herbs and sulfadiazine groups was significantly lower than that of PBS group at 7 days post infection (dpi), which was in accordance with the result of histological detection. Monocyte and neutrophil of infected mice were remarkably increased while lymphocyte was dramatically decreased compared to that of blank group at 7 dpi. The results demonstrated that the 500 mg dosage of our Chinese herbs could slow down the replication of T. gondii and prolong the survival time of mice and could be considered as possible candidate drug against toxoplasmosis.
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Evaluation of potential anti-toxoplasmosis efficiency of combined traditional herbs in a mouse model *


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The global spread of SARS-CoV-2 requires an urgent need to find effective therapeutics for the treatment of COVID-19. We developed a data-driven drug repositioning framework, which applies both machine learning and statistical analysis approaches to systematically integrate and mine large-scale knowledge graph, literature and transcriptome data to discover the potential drug candidates against SARS-CoV-2. The retrospective study using the past SARS-CoV and MERS-CoV data demonstrated that our machine learning based method can successfully predict effective drug candidates : bioRxiv preprint against a specific coronavirus. Our in silico screening followed by wet-lab validation indicated that a poly-ADP-ribose polymerase 1 (PARP1) inhibitor, CVL218, currently in Phase I clinical trial, may be repurposed to treat COVID-19. Our in vitro assays revealed that CVL218 can exhibit effective inhibitory activity against SARS-CoV-2 replication without obvious cytopathic effect. In addition, we showed that CVL218 is able to suppress the CpG-induced IL-6 production in peripheral blood mononuclear cells, suggesting that it may also have anti-inflammatory effect that is highly relevant to the prevention immunopathology induced by SARS-CoV-2 infection. Further pharmacokinetic and toxicokinetic evaluation in rats and monkeys showed a high concentration of CVL218 in lung and observed no apparent signs of toxicity, indicating the appealing potential of this drug for the treatment of the pneumonia caused by SARS-CoV-2 infection. Moreover, molecular docking simulation suggested that CVL218 may bind to the N-terminal domain of nucleocapsid (N) protein of SARS-CoV-2, providing a possible model to explain its antiviral action. We also proposed several possible mechanisms to explain the antiviral activities of PARP1 inhibitors against SARS-CoV-2, based on the data present in this study and previous evidences reported in the literature. In summary, the PARP1 inhibitor CVL218 discovered by our data-driven drug repositioning framework can serve as a potential therapeutic agent for the treatment of COVID-19. author/funder. All rights reserved. No reuse allowed without permission. : bioRxiv preprint known evidences reported in the literature, we also discussed several putative mechanisms of the anti-SARS-CoV-2 effects for CVL218 or other PARP1 inhibitors to be involved in the treatment of COVID-19. Overall, our results indicated that the PARP1 inhibitor CVL218 identified by our drug repositioning pipeline may serve as an effective therapeutic agent against COVID-19. Results The overview of our data-driven drug repositioning framework is shown in Figure 1A . We first constructed a virus related knowledge graph consisting of drug-target interactions, protein-protein interactions and similarity networks from publically available databases (Methods). Three different types of nodes (i.e., drugs, human targets and virus targets) within the knowledge graph were connected through edges describing their interactions, associations or similarities to establish bridges of information aggregation and knowledge mining. We then applied a network-based knowledge mining algorithm to predict an initial list of drug candidates that can be potentially used to treat SARS-CoV-2 infection ( Figure 1B and Methods). Next, we further narrowed down the list of drug candidates with the previously reported evidences of antiviral activities based on the text mining results from the large-scale literature texts, which were derived through a deep learning based relation extraction method named BERE [4] ( Figure 1C and Methods), followed by a minimum of manual checking. After that, we used the connectivity map analysis approach [5] with the gene expression profiles of ten SARS-CoV-infected patients [6] to further refine the list of drug candidates against SARS-CoV-2 ( Figure 1D , Table 1, Table S1 and Methods). The above screening process revealed that a poly-ADP-ribose polymerase 1 (PARP1) inhibitor PJ-34 could potentially have the antiviral activities against SARS-CoV-2. 4 author/funder. All rights reserved. No reuse allowed without permission.
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A data-driven drug repositioning framework discovered a potential therapeutic agent targeting COVID-19


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Drugs that inhibit the production of angiotensin II (AngII) or its access to the type 1 angiotensin receptor (AT 1 R) are prescribed to alleviate high blood pressure and its cardiovascular complications. Accordingly, much research has focused on the molecular pharmacology of AT 1 R activation and signaling. An emerging theme is that the AT 1 R generates G protein dependent as well as independent signals and that these transduction systems separately contribute to AT 1 R biology in health and disease. Regulatory molecules termed arrestins are central to this process as is the capacity of AT 1 R to crosstalk with other receptor systems, such as the widely studied transactivation of growth factor receptors. AT 1 R function can also be modulated by polymorphisms in the AGTR gene, which may significantly alter receptor expression and function; a capacity of the receptor to dimerize/oligomerize with altered pharmacology; and by the cellular environment in which the receptor resides. Together, these aspects of the AT 1 R "flavour" the response to angiotensin; they may also contribute to disease, determine the efficacy of current drugs and offer a unique opportunity to develop new therapeutics that antagonize only selective facets of AT 1 R function.
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Type 1 angiotensin receptor pharmacology: Signaling beyond G proteins