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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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The renin-angiotensin system plays an important role in the maintenance of blood pressure homeostasis. The angiotensin-converting enzyme (ACE) converts angiotensin I into angiotensin II. Angiotensin II, which binds the angiotensin II type-1 receptor (AT1R), is a potent vasoconstrictor. On a pathophysiological basis, both ACE I/D and AT1R A1166C polymorphism lead to an enhanced activity of the angiotensin II-AT1R axis, thereby possibly contributing to circulatory disturbances. A mutually facilitatory effect may be presumed between the two polymorphisms. We examined whether this synergistic effect is involved in the evolution of different types of ischemic stroke. Genetic and clinical data on 308 consecutive patients with acutely developing ischemic stroke were analyzed. A total of 272 stroke and neuroimaging alteration-free subjects served as a control group. Univariate and logistic regression statistical approaches were used. The ACE D allele combined with the AT1R 1166C allele did not yield a risk of ischemic stroke. However, the co-occurrence of the homozygous ACE D/D and at least one AT1R 1166C allele was more frequent in the ischemic stroke group than in the control group (22.4 vs 11%, p < 0.005, OR, 2.33; 95% CI, 1.46-3.7). After specific subgroup analysis, this synergistic association was even stronger for small-vessel ischemic stroke (OR, 3.44; 95% CI, 1.9-6.24; p < 0.0005). Multivariate logistic regression analysis of the data confirmed this association (adjusted OR, 3.54, 95% CI, 1.88-7.16; p < 0.0005). Our results demonstrate that ACE D/D and AT1R 1166C NeuroMolecular Medicine
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Coexistence of Angiotensin II Type-1 Receptor A1166C and Angiotensin-Converting Enzyme D/D Polymorphism Suggests Susceptibility for Small-Vessel-Associated Ischemic Stroke


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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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publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. v a c u n a s . 2 0 1 9;2 0(2):53-59 a b s t r a c t Introduction: Influenza is a common respiratory infectious disease affecting population worldwide yearly. The aim of this work is to describe the 2017-2018 influenza season and how it affected elderly population in Catalonia despite moderate vaccine coverage among this age group. Methods: Influenza surveillance based on a primary care sentinel surveillance, virological indicators systematic sampling of ILI attended and severe influenza confirmed cases (SHLCI) admitted to hospital. Analysis of data by Chi-squared, ANOVA, multiple regression and negative control test or case to case for vaccine effectiveness assessment in primary care and SHLCI respectively. Results: Moderate-high intensity and early onset season with predominance of influenza B virus (IVB) (63%) followed by an increase of circulation of influenza A virus (IVA). A total of 419 IV from primary care samples. Vaccine effectiveness (VE) in primary care setting was 14% (95%CI: 0-47%). 1306 severe cases (adjusted cumulative incidence 18.54/100,000 inhabitants (95%CI: 17.54-19.55)). The highest proportion of severe cases were in the >64 (65.1%) (aOR 15.70; 95%CI: 12.06-20.46; p < 0.001) followed by 45-64 yo (25.4%) (aOR 6.03; 95%CI: 4.57-7.97). VE in preventing intensive care unit (ICU) admission was 35% (95%CI: 10-54%). Final outcome death while hospitalized occurred in 175 SHLCI cases with a case fatality rate of 13.4%. Conclusions: 2017-2018 influenza season was an unusual epidemic season with an early onset, great predominance of influenza B (Yamagata strain) virus with a high hospitalization rate of severe cases among elderly stressing the need to upgrade vaccine uptake in this age group. Conclusiones: La temporada de gripe 2017-2018 fue una temporada epidémica inusual con un inicio temprano, gran predominio del VGB (cepa Yamagata) con una elevada tasa de hospitalización de casos graves en ancianos, lo que subraya la necesidad de mejorar la aceptación de la vacuna en este grupo de edad.
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Vacunas Original Seasonal influenza surveillance: Observational study on the 2017-2018 season with predominant B influenza virus circulation