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Transition metal tellurides (TMTes) have received extensive attention for high specific energy sodium-ion batteries (SIBs) due to their high volumetric specific capacity. However, the continuous capacity attenuation arising from the huge volumetric strain during sodiation/desodiation impedes practical applications. Here, we report a "sandwich-type" carbon confinement strategy that entraps cobalt ditelluride (CoTe2) nanocrystals between two carbon layers. Porous cellulose-derived fibres were employed as the inner carbon framework to construct fast conductive circuits and provide an abundant site for anchoring CoTe2 nanocrystals. Polyvinylpyrrolidone (PVP)-derived carbon layers act as carbon armour to encapsulate CoTe2 nanocrystals, inhibiting their volume change and structural pulverization during repeated sodium intercalation/deintercalation. Benefiting from the exquisite structural design, the N-C@CoTe2@C electrode exhibits excellent cycling stability for over 3000 cycles at 2.0 A g-1 and rate performance (113.8 mA h g-1 at 5.0 A g-1). Moreover, ex situ XRD/TEM and kinetic tests revealed a multistep conversion reaction mechanism and a battery-capacitive dual-model Na-storage process. This work provides a new perspective on the development of low-cost and straightforward techniques for fabricating long-life commercial SIB anode materials.
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OBJECTIVE: Coronavirus disease 2019 (COVID-19) has caused considerable morbidity and mortality, especially in patients with underlying health conditions. A precise prognostic tool to identify poor outcomes among such cases is desperately needed. METHODS: Total 400 COVID-19 patients with underlying health conditions were retrospectively recruited from 4 centers, including 54 dead cases (labeled as poor outcomes) and 346 patients discharged or hospitalized for at least 7 days since initial CT scan. Patients were allocated to a training set (n = 271), a test set (n = 68), and an external test set (n = 61). We proposed an initial CT-derived hybrid model by combining a 3D-ResNet10 based deep learning model and a quantitative 3D radiomics model to predict the probability of COVID-19 patients reaching poor outcome. The model performance was assessed by area under the receiver operating characteristic curve (AUC), survival analysis, and subgroup analysis. RESULTS: The hybrid model achieved AUCs of 0.876 (95% confidence interval: 0.752-0.999) and 0.864 (0.766-0.962) in test and external test sets, outperforming other models. The survival analysis verified the hybrid model as a significant risk factor for mortality (hazard ratio, 2.049 [1.462-2.871], P < 0.001) that could well stratify patients into high-risk and low-risk of reaching poor outcomes (P < 0.001). CONCLUSION: The hybrid model that combined deep learning and radiomics could accurately identify poor outcomes in COVID-19 patients with underlying health conditions from initial CT scans. The great risk stratification ability could help alert risk of death and allow for timely surveillance plans.
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COVID-19 , Aprendizaje Profundo , Interpretación de Imagen Radiográfica Asistida por Computador/métodos , Tomografía Computarizada por Rayos X/métodos , Anciano , Anciano de 80 o más Años , COVID-19/diagnóstico por imagen , COVID-19/mortalidad , Comorbilidad , Femenino , Humanos , Imagenología Tridimensional , Pulmón/diagnóstico por imagen , Masculino , Persona de Mediana Edad , Pronóstico , Curva ROC , Estudios Retrospectivos , SARS-CoV-2RESUMEN
Rationale: Given the rapid spread of COVID-19, an updated risk-stratify prognostic tool could help clinicians identify the high-risk patients with worse prognoses. We aimed to develop a non-invasive and easy-to-use prognostic signature by chest CT to individually predict poor outcome (death, need for mechanical ventilation, or intensive care unit admission) in patients with COVID-19. Methods: From November 29, 2019 to February 19, 2020, a total of 492 patients with COVID-19 from four centers were retrospectively collected. Since different durations from symptom onsets to the first CT scanning might affect the prognostic model, we designated the 492 patients into two groups: 1) the early-phase group: CT scans were performed within one week after symptom onset (0-6 days, n = 317); and 2) the late-phase group: CT scans were performed one week later after symptom onset (≥7 days, n = 175). In each group, we divided patients into the primary cohort (n = 212 in the early-phase group, n = 139 in the late-phase group) and the external independent validation cohort (n = 105 in the early-phase group, n = 36 in the late-phase group) according to the centers. We built two separate radiomics models in the two patient groups. Firstly, we proposed an automatic segmentation method to extract lung volume for radiomics feature extraction. Secondly, we applied several image preprocessing procedures to increase the reproducibility of the radiomics features: 1) applied a low-pass Gaussian filter before voxel resampling to prevent aliasing; 2) conducted ComBat to harmonize radiomics features per scanner; 3) tested the stability of the features in the radiomics signature by several image transformations, such as rotating, translating, and growing/shrinking. Thirdly, we used least absolute shrinkage and selection operator (LASSO) to build the radiomics signature (RadScore). Afterward, we conducted a Fine-Gray competing risk regression to build the clinical model and the clinic-radiomics signature (CrrScore). Finally, performances of the three prognostic signatures (clinical model, RadScore, and CrrScore) were estimated from the two aspects: 1) cumulative poor outcome probability prediction; 2) 28-day poor outcome prediction. We also did stratified analyses to explore the potential association between the CrrScore and the poor outcomes regarding different age, type, and comorbidity subgroups. Results: In the early-phase group, the CrrScore showed the best performance in estimating poor outcome (C-index = 0.850), and predicting the probability of 28-day poor outcome (AUC = 0.862). In the late-phase group, the RadScore alone achieved similar performance to the CrrScore in predicting poor outcome (C-index = 0.885), and 28-day poor outcome probability (AUC = 0.976). Moreover, the RadScore in both groups successfully stratified patients with COVID-19 into low- or high-RadScore groups with significantly different survival time in the training and validation cohorts (all P < 0.05). The CrrScore in both groups can also significantly stratify patients with different prognoses regarding different age, type, and comorbidities subgroups in the combined cohorts (all P < 0.05). Conclusions: This research proposed a non-invasive and quantitative prognostic tool for predicting poor outcome in patients with COVID-19 based on CT imaging. Taking the insufficient medical recourse into account, our study might suggest that the chest CT radiomics signature of COVID-19 is more effective and ideal to predict poor outcome in the late-phase COVID-19 patients. For the early-phase patients, integrating radiomics signature with clinical risk factors can achieve a more accurate prediction of individual poor prognostic outcome, which enables appropriate management and surveillance of COVID-19.
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Betacoronavirus , Infecciones por Coronavirus/diagnóstico por imagen , Neumonía Viral/diagnóstico por imagen , Tomografía Computarizada por Rayos X/métodos , Adulto , Anciano , COVID-19 , China/epidemiología , Estudios de Cohortes , Infecciones por Coronavirus/epidemiología , Infecciones por Coronavirus/terapia , Cuidados Críticos , Femenino , Humanos , Pulmón/diagnóstico por imagen , Masculino , Persona de Mediana Edad , Modelos Biológicos , Pandemias , Neumonía Viral/epidemiología , Neumonía Viral/terapia , Pronóstico , Interpretación de Imagen Radiográfica Asistida por Computador/métodos , Interpretación de Imagen Radiográfica Asistida por Computador/estadística & datos numéricos , Respiración Artificial , Estudios Retrospectivos , Factores de Riesgo , SARS-CoV-2 , Nanomedicina Teranóstica , Tomografía Computarizada por Rayos X/estadística & datos numéricos , Resultado del TratamientoRESUMEN
BACKGROUND: Coronavirus disease 2019 (COVID-19) has been a global pandemic disease, with more than 4 million cases and nearly 300,000 deaths. Little is known about COVID-19 in patients with chronic obstructive pulmonary disease (COPD). We aimed to evaluate the influence of preexisting COPD on the progress and outcomes of COVID-19. METHODS: This was a multicenter, retrospective, observational study. We enrolled 1,048 patients aged 40 years and above, including 50 patients with COPD and 998 patients without COPD, and with COVID-19 confirmed via high-throughput sequencing or real-time reverse transcription-polymerase chain reaction, between December 11, 2019 and February 20, 2020. We collected data of demographics, pathologic test results, radiologic imaging, and treatments. The primary outcomes were composite endpoints determined by admission to an intensive care unit, the use of mechanical ventilation, or death. RESULTS: Compared with patients who had COVID-19 but not COPD, those with COPD had higher rates of fatigue (56.0% vs. 40.2%), dyspnea (66.0% vs. 26.3%), diarrhea (16.0% vs. 3.6%), and unconsciousness (8.0% vs. 1.7%) and a significantly higher proportion of increased activated partial thromboplastin time (23.5% vs. 5.2%) and D-dimer (65.9% vs. 29.3%), as well as ground-glass opacities (77.6% vs. 60.3%), local patchy shadowing (61.2% vs. 41.4%), and interstitial abnormalities (51.0% vs. 19.8%) on chest computed tomography. Patients with COPD were more likely to develop bacterial or fungal coinfection (20.0% vs. 5.9%), acute respiratory distress syndrome (ARDS) (20.0% vs. 7.3%), septic shock (14.0% vs. 2.3%), or acute renal failure (12.0% vs. 1.3%). Patients with COPD and COVID-19 had a higher risk of reaching the composite endpoints [hazard ratio (HR): 2.17, 95% confidence interval (CI): 1.40-3.38; P=0.001] or death (HR: 2.28, 95% CI: 1.15-4.51; P=0.019), after adjustment. CONCLUSIONS: In this study, patients with COPD who developed COVID-19 showed a higher risk of admission to the intensive care unit, mechanical ventilation, or death.
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BACKGROUND: Crucial roles of hematologic and immunologic responses in progression of coronavirus disease 2019 (COVID-19) remain largely unclear. OBJECTIVE: We sought to address the dynamic changes in hematologic and immunologic biomarkers and their associations with severity and outcomes of COVID-19. METHODS: A retrospective study including 548 patients with COVID-19 with clarified outcome (discharged or deceased) from a national cohort in China was performed. Cross-sectional and longitudinal variations were compared and the associations with different severity and outcomes were analyzed. RESULTS: On admission, the counts of lymphocytes, T-cell subsets, eosinophils, and platelets decreased markedly, especially in severe/critical and fatal patients. Increased neutrophil count and neutrophils-to-lymphocytes ratio were predominant in severe/critical cases or nonsurvivors. During hospitalization, eosinophils, lymphocytes, and platelets showed an increasing trend in survivors, but maintained lower levels or dropped significantly afterwards in nonsurvivors. Nonsurvivors kept a high level or showed an upward trend for neutrophils, IL-6, procalcitonin, D-dimer, amyloid A protein, and C-reactive protein, which were kept stable or showed a downward trend in survivors. Positive correlation between CD8+ T-cell and lymphocytes count was found in survivors but not in nonsurvivors. A multivariate Cox regression model suggested that restored levels of lymphocytes, eosinophils, and platelets could serve as predictors for recovery, whereas progressive increases in neutrophils, basophils, and IL-6 were associated with fatal outcome. CONCLUSIONS: Hematologic and immunologic impairment showed a significantly different profile between survivors and nonsurvivors in patients with COVID-19 with different severity. The longitudinal variations in these biomarkers could serve to predict recovery or fatal outcome.
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Biomarcadores/sangre , Infecciones por Coronavirus/sangre , Infecciones por Coronavirus/inmunología , Neumonía Viral/sangre , Neumonía Viral/inmunología , Adulto , Anciano , Betacoronavirus , COVID-19 , China , Estudios de Cohortes , Infecciones por Coronavirus/mortalidad , Estudios Transversales , Progresión de la Enfermedad , Femenino , Humanos , Estudios Longitudinales , Masculino , Persona de Mediana Edad , Pandemias , Neumonía Viral/mortalidad , Pronóstico , Estudios Retrospectivos , SARS-CoV-2RESUMEN
BACKGROUND: The novel coronavirus disease 2019 (COVID-19) has become a global health emergency. The cumulative number of new confirmed cases and deaths are still increasing out of China. Independent predicted factors associated with fatal outcomes remain uncertain. RESEARCH QUESTION: The goal of the current study was to investigate the potential risk factors associated with fatal outcomes from COVID-19 through a multivariate Cox regression analysis and a nomogram model. STUDY DESIGN AND METHODS: A retrospective cohort of 1,590 hospitalized patients with COVID-19 throughout China was established. The prognostic effects of variables, including clinical features and laboratory findings, were analyzed by using Kaplan-Meier methods and a Cox proportional hazards model. A prognostic nomogram was formulated to predict the survival of patients with COVID-19. RESULTS: In this nationwide cohort, nonsurvivors included a higher incidence of elderly people and subjects with coexisting chronic illness, dyspnea, and laboratory abnormalities on admission compared with survivors. Multivariate Cox regression analysis showed that age ≥ 75 years (hazard ratio [HR], 7.86; 95% CI, 2.44-25.35), age between 65 and 74 years (HR, 3.43; 95% CI, 1.24-9.5), coronary heart disease (HR, 4.28; 95% CI, 1.14-16.13), cerebrovascular disease (HR, 3.1; 95% CI, 1.07-8.94), dyspnea (HR, 3.96; 95% CI, 1.42-11), procalcitonin level > 0.5 ng/mL (HR, 8.72; 95% CI, 3.42-22.28), and aspartate aminotransferase level > 40 U/L (HR, 2.2; 95% CI, 1.1-6.73) were independent risk factors associated with fatal outcome. A nomogram was established based on the results of multivariate analysis. The internal bootstrap resampling approach suggested the nomogram has sufficient discriminatory power with a C-index of 0.91 (95% CI, 0.85-0.97). The calibration plots also showed good consistency between the prediction and the observation. INTERPRETATION: The proposed nomogram accurately predicted clinical outcomes of patients with COVID-19 based on individual characteristics. Earlier identification, more intensive surveillance, and appropriate therapy should be considered in patients at high risk.
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Aspartato Aminotransferasas/sangre , Enfermedades Cardiovasculares/epidemiología , Infecciones por Coronavirus , Disnea , Pandemias , Neumonía Viral , Polipéptido alfa Relacionado con Calcitonina/sangre , Anciano , Betacoronavirus/aislamiento & purificación , COVID-19 , China/epidemiología , Infecciones por Coronavirus/sangre , Infecciones por Coronavirus/diagnóstico , Infecciones por Coronavirus/mortalidad , Infecciones por Coronavirus/fisiopatología , Correlación de Datos , Disnea/epidemiología , Disnea/etiología , Femenino , Humanos , Masculino , Nomogramas , Neumonía Viral/sangre , Neumonía Viral/diagnóstico , Neumonía Viral/mortalidad , Neumonía Viral/fisiopatología , Pronóstico , Medición de Riesgo/métodos , Factores de Riesgo , SARS-CoV-2 , Análisis de SupervivenciaRESUMEN
BACKGROUND: During the outbreak of coronavirus disease 2019 (COVID-19), consistent and considerable differences in disease severity and mortality rate of patients treated in Hubei province compared to those in other parts of China have been observed. We sought to compare the clinical characteristics and outcomes of patients being treated inside and outside Hubei province, and explore the factors underlying these differences. METHODS: Collaborating with the National Health Commission, we established a retrospective cohort to study hospitalised COVID-19 cases in China. Clinical characteristics, the rate of severe events and deaths, and the time to critical illness (invasive ventilation or intensive care unit admission or death) were compared between patients within and outside Hubei. The impact of Wuhan-related exposure (a presumed key factor that drove the severe situation in Hubei, as Wuhan is the epicentre as well the administrative centre of Hubei province) and the duration between symptom onset and admission on prognosis were also determined. RESULTS: At the data cut-off (31 January 2020), 1590 cases from 575 hospitals in 31 provincial administrative regions were collected (core cohort). The overall rate of severe cases and mortality was 16.0% and 3.2%, respectively. Patients in Hubei (predominantly with Wuhan-related exposure, 597 (92.3%) out of 647) were older (mean age 49.7 versus 44.9â years), had more cases with comorbidity (32.9% versus 19.7%), higher symptomatic burden, abnormal radiologic manifestations and, especially, a longer waiting time between symptom onset and admission (5.7 versus 4.5â days) compared with patients outside Hubei. Patients in Hubei (severe event rate 23.0% versus 11.1%, death rate 7.3% versus 0.3%, HR (95% CI) for critical illness 1.59 (1.05-2.41)) have a poorer prognosis compared with patients outside Hubei after adjusting for age and comorbidity. However, among patients outside Hubei, the duration from symptom onset to hospitalisation (mean 4.4 versus 4.7â days) and prognosis (HR (95%) 0.84 (0.40-1.80)) were similar between patients with or without Wuhan-related exposure. In the overall population, the waiting time, but neither treated in Hubei nor Wuhan-related exposure, remained an independent prognostic factor (HR (95%) 1.05 (1.01-1.08)). CONCLUSION: There were more severe cases and poorer outcomes for COVID-19 patients treated in Hubei, which might be attributed to the prolonged duration of symptom onset to hospitalisation in the epicentre. Future studies to determine the reason for delaying hospitalisation are warranted.
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Infecciones por Coronavirus/mortalidad , Hospitalización , Neumonía Viral/mortalidad , Adulto , Anciano , Betacoronavirus , COVID-19 , Enfermedades Cardiovasculares/epidemiología , China , Estudios de Cohortes , Comorbilidad , Infecciones por Coronavirus/complicaciones , Infecciones por Coronavirus/diagnóstico por imagen , Tos/etiología , Diabetes Mellitus/epidemiología , Brotes de Enfermedades , Disnea/etiología , Fatiga/etiología , Femenino , Fiebre/etiología , Geografía , Humanos , Hipertensión/epidemiología , Unidades de Cuidados Intensivos/estadística & datos numéricos , Pulmón/diagnóstico por imagen , Masculino , Persona de Mediana Edad , Pandemias , Faringitis/etiología , Neumonía Viral/complicaciones , Neumonía Viral/diagnóstico por imagen , Pronóstico , Modelos de Riesgos Proporcionales , Respiración Artificial/estadística & datos numéricos , Estudios Retrospectivos , SARS-CoV-2 , Índice de Severidad de la Enfermedad , Factores de Tiempo , Tiempo de Tratamiento/estadística & datos numéricos , Tomografía Computarizada por Rayos XRESUMEN
BACKGROUND: The coronavirus disease 2019 (COVID-19) outbreak is evolving rapidly worldwide. OBJECTIVE: To evaluate the risk of serious adverse outcomes in patients with COVID-19 by stratifying the comorbidity status. METHODS: We analysed data from 1590 laboratory confirmed hospitalised patients from 575 hospitals in 31 provinces/autonomous regions/provincial municipalities across mainland China between 11 December 2019 and 31 January 2020. We analysed the composite end-points, which consisted of admission to an intensive care unit, invasive ventilation or death. The risk of reaching the composite end-points was compared according to the presence and number of comorbidities. RESULTS: The mean age was 48.9â years and 686 (42.7%) patients were female. Severe cases accounted for 16.0% of the study population. 131 (8.2%) patients reached the composite end-points. 399 (25.1%) reported having at least one comorbidity. The most prevalent comorbidity was hypertension (16.9%), followed by diabetes (8.2%). 130 (8.2%) patients reported having two or more comorbidities. After adjusting for age and smoking status, COPD (HR (95% CI) 2.681 (1.424-5.048)), diabetes (1.59 (1.03-2.45)), hypertension (1.58 (1.07-2.32)) and malignancy (3.50 (1.60-7.64)) were risk factors of reaching the composite end-points. The hazard ratio (95% CI) was 1.79 (1.16-2.77) among patients with at least one comorbidity and 2.59 (1.61-4.17) among patients with two or more comorbidities. CONCLUSION: Among laboratory confirmed cases of COVID-19, patients with any comorbidity yielded poorer clinical outcomes than those without. A greater number of comorbidities also correlated with poorer clinical outcomes.
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Betacoronavirus , Infecciones por Coronavirus/epidemiología , Neumonía Viral/epidemiología , Adulto , COVID-19 , China/epidemiología , Comorbilidad , Infecciones por Coronavirus/diagnóstico , Femenino , Humanos , Masculino , Persona de Mediana Edad , Pandemias , Neumonía Viral/diagnóstico , Pronóstico , Factores de Riesgo , SARS-CoV-2RESUMEN
BACKGROUND: Since December 2019, when coronavirus disease 2019 (Covid-19) emerged in Wuhan city and rapidly spread throughout China, data have been needed on the clinical characteristics of the affected patients. METHODS: We extracted data regarding 1099 patients with laboratory-confirmed Covid-19 from 552 hospitals in 30 provinces, autonomous regions, and municipalities in mainland China through January 29, 2020. The primary composite end point was admission to an intensive care unit (ICU), the use of mechanical ventilation, or death. RESULTS: The median age of the patients was 47 years; 41.9% of the patients were female. The primary composite end point occurred in 67 patients (6.1%), including 5.0% who were admitted to the ICU, 2.3% who underwent invasive mechanical ventilation, and 1.4% who died. Only 1.9% of the patients had a history of direct contact with wildlife. Among nonresidents of Wuhan, 72.3% had contact with residents of Wuhan, including 31.3% who had visited the city. The most common symptoms were fever (43.8% on admission and 88.7% during hospitalization) and cough (67.8%). Diarrhea was uncommon (3.8%). The median incubation period was 4 days (interquartile range, 2 to 7). On admission, ground-glass opacity was the most common radiologic finding on chest computed tomography (CT) (56.4%). No radiographic or CT abnormality was found in 157 of 877 patients (17.9%) with nonsevere disease and in 5 of 173 patients (2.9%) with severe disease. Lymphocytopenia was present in 83.2% of the patients on admission. CONCLUSIONS: During the first 2 months of the current outbreak, Covid-19 spread rapidly throughout China and caused varying degrees of illness. Patients often presented without fever, and many did not have abnormal radiologic findings. (Funded by the National Health Commission of China and others.).
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Betacoronavirus , Infecciones por Coronavirus , Brotes de Enfermedades , Pandemias , Neumonía Viral , Adolescente , Adulto , Anciano , COVID-19 , Niño , China/epidemiología , Infecciones por Coronavirus/complicaciones , Infecciones por Coronavirus/diagnóstico , Infecciones por Coronavirus/epidemiología , Infecciones por Coronavirus/terapia , Femenino , Fiebre/etiología , Humanos , Masculino , Persona de Mediana Edad , Gravedad del Paciente , Neumonía Viral/complicaciones , Neumonía Viral/diagnóstico , Neumonía Viral/epidemiología , Neumonía Viral/terapia , SARS-CoV-2 , Adulto JovenRESUMEN
Uniform Lu2O3:Eu3+ nanowire arrays were successfully prepared by the sol-gel process using anodic aluminum oxide (AAO) templates. The as-synthesized nanowires are homogeneous, highly ordered, and dense and have a uniform diameter of ~300 nm defined by the AAO templates. The X-ray diffraction and selected area electron diffraction results show that the Lu2O3:Eu3+ nanowires have a polycrystalline cubic structure, and the crystallite size of the Lu2O3:Eu3+ nanowires is confined by the AAO template. The nanowires within the AAO template showed good photoluminescence and X-ray-excited optical luminescence performances for Lu2O3:Eu3+. The emission peaks were attributed to the 5D0 â 7FJ transitions of Eu3+ (J = 0, 1, 2, 3).
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Under excitation of high-energy and low-flux density of X-ray beam, a 1-µm system spatial resolution was initially achieved by using an 18-µm thickness ZnO nanorod array as the scintillator layer in X-ray imaging beamline at Shanghai Synchrotron Radiation Facility. The decay time measurements indicated the ultraviolet and visible emissions of the arrays were subnanosecond and nanosecond, respectively. Through hydrogen annealing treatment, the ultraviolet luminescence was intensively enhanced and the visible luminescence was remarkably suppressed simultaneously. In conclusion, it can be determined that the ZnO-based nanorod arrays are the decent candidates for applications in ultrafast and high-spatial-resolution X-ray imaging systems.
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OBJECTIVES: To study the roles of STARD13 in cellular apoptosis of hepatocellular carcinoma (HCC). RESULTS: Quantitative real-time PCR and immunohistochemistry analyses showed that the expression levels of STARD13 and Fas were lower in clinical HCC tissues than in normal tissues and were positively correlated, which is consistent with the results analyzed by The Cancer Genome Atlas (TCGA) data. Patients with higher STARD13 or Fas expression levels had longer overall survival. Additionally, STARD13 3'-UTR enhanced cellular apoptosis and the 3'-UTRs of STARD13 and Fas were predicted to harbor nine similar miRNA binding sites. And STARD13 3'-UTR promoted Fas expression in a 3'-UTR- and miRNA-dependent way and increased the sensitivity of HCC cells to chemotherapy. Importantly, the coding sequence of STARD13 did not increase Fas expression. CONCLUSIONS: STARD13 3'-UTR promotes HCC apoptosis through acting as a ceRNA for Fas.
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Carcinoma Hepatocelular/metabolismo , Neoplasias Hepáticas/genética , Neoplasias Hepáticas/metabolismo , ARN/genética , Proteínas Supresoras de Tumor/metabolismo , Receptor fas/genética , Apoptosis/genética , Apoptosis/fisiología , Carcinoma Hepatocelular/genética , Ciclo Celular/genética , Ciclo Celular/fisiología , Línea Celular Tumoral , Proteínas Activadoras de GTPasa , Regulación Neoplásica de la Expresión Génica/genética , Células Hep G2 , Humanos , MicroARNs/genética , ARN Largo no Codificante/genética , ARN Mensajero/genética , Proteínas Supresoras de Tumor/genéticaRESUMEN
In order to investigate the inhibitory effect of plasmid-mediated short hairpin RNA targeting vascular endothelial growth factor (VEGF) on the expression of VEGF mRNA in human gastric cancer cells, a plasmid vector for transcribing specific short hairpin RNA targeting VEGF (pU6-VEGF) was constructed, and then transfected into human gastric cancer cells using Lipofectamine2000. The VEGF mRNA expression level was detected by RT-PCR. RPMI1640 was used for blank control, and pSilencer 1.0-U6 empty plasmid for the negative control. Results showed the clone and sequence analysis revealed that the recombinant plasmid vector of pU6-VEGF was successfully constructed. The VEGF mRNA expression levels in blank control group, experimental group (pU6-VEGF) and negative control group (pSilencer1.0-U6) were 100%, 49% and 94%, respectively, indicating VEGF mRNA expression in the cells transfected with pU-VEGF vector was inhibited significantly as compared with blank control group and negative control group. It was concluded that the short hairpin RNA could significantly inhibit the expression of VEGF mRNA, which provided an experimental basis for treating human cancer with anti-angiogenesis.