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Aging is identified as a significant risk factor for severe coronavirus disease-2019 (COVID-19), often resulting in profound lung damage and mortality. Yet, the biological relationship between aging, aging-related comorbidities, and COVID-19 remains incompletely understood. This study aimed to elucidate the age-related COVID19 pathogenesis using an Hutchinson-Gilford progeria syndrome (HGPS) mouse model, a premature aging disease model, with humanized ACE2 receptors. Pathological features were compared between young, aged, and HGPS hACE2 mice following SARS-CoV-2 challenge. We demonstrated that young mice display robust interferon response and antiviral activity, whereas this response is attenuated in aged mice. Viral infection in aged mice results in severe respiratory tract hemorrhage, likely contributing a higher mortality rate. In contrast, HGPS hACE2 mice exhibit milder disease manifestations characterized by minor immune cell infiltration and dysregulation of multiple metabolic processes. Comprehensive transcriptome analysis revealed both shared and unique gene expression dynamics among different mouse groups. Collectively, our studies evaluated the impact of SARS-CoV-2 infection on progeroid syndromes using a HGPS hACE2 mouse model, which holds promise as a useful tool for investigating COVID-19 pathogenesis in individuals with premature aging.
Asunto(s)
Envejecimiento Prematuro , Enzima Convertidora de Angiotensina 2 , COVID-19 , Modelos Animales de Enfermedad , Progeria , SARS-CoV-2 , Animales , COVID-19/virología , COVID-19/patología , Envejecimiento Prematuro/virología , Envejecimiento Prematuro/genética , Ratones , Enzima Convertidora de Angiotensina 2/metabolismo , Enzima Convertidora de Angiotensina 2/genética , SARS-CoV-2/patogenicidad , Progeria/genética , Progeria/patología , Humanos , Pulmón/patología , Pulmón/virología , FemeninoRESUMEN
Objective:To explore the clinical efficacy of different doses of apatinib combined with chemotherapy in patients with advanced non-small cell lung cancer (NSCLC) and the adverse reactions.Methods:A total of 69 patients with NSCLC diagnosed in the No. 901 Hospital of the Chinese People′s Liberation Army Joint Logistics Support Force were selected from January 2018 to June 2020, and were divided into chemotherapy alone group (docetaxel+ cisplatin was used), apatinib group A [apatinib (0.25 g)+ docetaxel+ cisplatin was used] and apatinib group B [apatinib (0.50 g)+ docetaxel+ cisplatin was used] according to random number table method, with 23 cases in each group. The objective response rate (ORR), disease control rate (DCR), median overall survival (OS), median progression-free survival (PFS), and incidences of adverse reactions were compared between the three groups of patients.Results:One patients in the apatinib group B withdrew from the study due to acute myocardial infarction. After 4 cycless of treatment, the ORR of the patients in the chemotherapy alone group, apatinib group A and apatinib group B were 17.39% (4/23), 47.83% (11/23) and 54.55% (12/22) respectively, with a statistically significant difference ( χ2=7.41, P=0.024). The ORR of the apatinib group B was higher than that of the chemotherapy alone group, with a statistically significant difference ( χ2=6.77, P=0.009). There were no statistically significant differences in ORR between the apatinib group A and chemotherapy alone group, the apatinib group A and apatinib group B ( χ2=4.85, P=0.028; χ2=0.20, P=0.652). The DCR of the patients in the three groups were 47.83% (11/23), 78.26% (18/23) and 86.36% (19/22) respectively, with a statistically significant difference ( χ2=9.03, P=0.011). The DCR of the apatinib group B was higher than that of the chemotherapy alone group, with a statistically significant difference ( χ2=7.52, P=0.006). There were no statistically significant differences in DCR between the apatinib group A and the chemotherapy alone group, the apatinib group A and apatinib group B ( χ2=4.57, P=0.033; χ2=0.51, P=0.477). The median OS of the patients in the three groups were 6.8, 9.2 and 9.9 months respectively, with a statistically significant different ( χ2=8.91, P=0.022). Compared with the chemotherapy alone group, the median OS of the apatinib group A and apatinib group B were significantly prolonged, with statistically significant differences ( χ2=7.25, P=0.036; χ2=8.60, P=0.029). Compared with the apatinib group A, the median OS of the apatinib group B was prolonged, but there was no statistically significant different ( χ2=1.54, P=0.201). The median PFS of the patients in the three groups were 5.2, 7.7 and 8.2 months respectively, with a statistically significant different ( χ2=8.79, P=0.026). Compared with the chemotherapy alone group, the median PFS of the apatinib group A and apatinib group B were significantly prolonged, with statistically significant differences ( χ2=7.01, P=0.039; χ2=8.36, P=0.031). Compared with the apatinib A group, the median PFS of the apatinib group B was prolonged, but there was no statistically significant different ( χ2=1.68, P=0.186). There were statistically significant differences in the incidences of fatigue [34.78% (8/23) vs. 65.22% (15/23) vs. 72.73% (16/22), χ2=7.50, P=0.024], hypertension [4.35% (1/23) vs. 34.78% (8/23) vs. 68.18% (15/22), χ2=20.07, P<0.001], hand-foot syndrome [4.35% (1/23) vs. 43.48% (10/23) vs. 72.73% (16/22), χ2=22.28, P<0.001] and oral mucositis [8.70% (2/23) vs. 39.13% (9/23) vs. 72.73% (16/22), χ2=19.26, P<0.001] among the three groups. Compared with the chemotherapy alone group, the incidences of hypertension and hand-foot syndrome in the apatinib group A and the incidences of fatigue, hypertension, hand-foot syndrome and oral mucositis in the apatinib group B were increased, with statistically significant differences ( χ2=6.77, P=0.009; χ2=9.68, P=0.002; χ2=6.51, P=0.011; χ2=20.00, P<0.001; χ2=22.37, P<0.001; χ2=19.21, P<0.001). Conclusion:Apatinib (0.50 g) combined with chemotherapy has better short-term efficacy than chemotherapy alone in advanced NSCLC. Apatinib (0.25 g) and apatinib (0.50 g) can prolong the survival of patients, but increasing the treatment dose can not achieve longer survival benefit.
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The recent outbreak of coronavirus disease (COVID-19) caused by SARS-CoV-2 infection in Wuhan, China has posed a serious threat to global public health. To develop specific anti-coronavirus therapeutics and prophylactics, the molecular mechanism that underlies viral infection must first be confirmed. Therefore, we herein used a SARS-CoV-2 spike (S) protein-mediated cell-cell fusion assay and found that SARS-CoV-2 showed plasma membrane fusion capacity superior to that of SARS-CoV. We solved the X-ray crystal structure of six-helical bundle (6-HB) core of the HR1 and HR2 domains in SARS-CoV-2 S protein S2 subunit, revealing that several mutated amino acid residues in the HR1 domain may be associated with enhanced interactions with HR2 domain. We previously developed a pan-coronavirus fusion inhibitor, EK1, which targeted HR1 domain and could inhibit infection by divergent human coronaviruses tested, including SARS-CoV and MERS-CoV. We then generated a series of lipopeptides and found that the EK1C4 was the most potent fusion inhibitor against SARS-CoV-2 S protein-mediated membrane fusion and pseudovirus infection with IC50s of 1.3 and 15.8 nM, about 241- and 149-fold more potent than that of EK1 peptide, respectively. EK1C4 was also highly effective against membrane fusion and infection of other human coronavirus pseudoviruses tested, including SARS-CoV and MERS-CoV, as well as SARSr-CoVs, potently inhibiting replication of 4 live human coronaviruses, including SARS-CoV-2. Intranasal application of EK1C4 before or after challenge with HCoV-OC43 protected mice from infection, suggesting that EK1C4 could be used for prevention and treatment of infection by currently circulating SARS-CoV-2 and emerging SARSr-CoVs.
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A new coronavirus (CoV) identified as COVID-19 virus is the etiological agent responsible for the 2019-2020 viral pneumonia outbreak that commenced in Wuhan1-4. Currently there is no targeted therapeutics and effective treatment options remain very limited. In order to rapidly discover lead compounds for clinical use, we initiated a program of combined structure-assisted drug design, virtual drug screening and high-throughput screening to identify new drug leads that target the COVID-19 virus main protease (Mpro). Mpro is a key CoV enzyme, which plays a pivotal role in mediating viral replication and transcription, making it an attractive drug target for this virus5,6. Here, we identified a mechanism-based inhibitor, N3, by computer-aided drug design and subsequently determined the crystal structure of COVID-19 virus Mpro in complex with this compound. Next, through a combination of structure-based virtual and high-throughput screening, we assayed over 10,000 compounds including approved drugs, drug candidates in clinical trials, and other pharmacologically active compounds as inhibitors of Mpro. Six of these inhibit Mpro with IC50 values ranging from 0.67 to 21.4 M. Ebselen also exhibited promising antiviral activity in cell-based assays. Our results demonstrate the efficacy of this screening strategy, which can lead to the rapid discovery of drug leads with clinical potential in response to new infectious diseases where no specific drugs or vaccines are available.
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This paper is concerned with the problem of state estimation for a class of discrete-time chaotic systems with or without time delays. A unified model consisting of a linear dynamic system and a bounded static nonlinear operator is employed to describe these systems, such as chaotic neural networks, Chua's circuits, Hénon map, etc. Based on the H∞ performance analysis of this unified model using the linear matrix inequality approach, H∞ state estimator are designed for this model with sensors to guarantee the asymptotic stability of the estimation error dynamic systems and to reduce the influence of noise on the estimation error. The parameters of these filters are obtained by solving the eigenvalue problem. As most discrete-time chaotic systems with or without time delays can be described with this unified model, H∞ state estimator design for these systems can be done in a unified way. Three numerical examples are exploited to illustrate the effectiveness of the proposed estimator design schemes.