RESUMO
Faced with the current large-scale public health emergency, collecting, sorting, and analyzing biomedical information related to the "coronavirus" should be done as quickly as possible to gain a global perspective, which is a basic requirement for strengthening epidemic control capacity. However, for human researchers studying the viruses and the hosts, the vast amount of information available cannot be processed effectively and in a timely manner, particularly when the scientific understanding may be limited, which can further lower the information processing efficiency. We present TWIRLS, a method that can automatically acquire, organize, and classify information. Additionally, independent functional data sources can be added to build an inference system using a machine-based approach, which can provide relevant knowledge to help human researchers quickly establish subject cognition and to make more effective decisions. TWIRLS can automatically analyze more than three million words in more than 14,000 literature articles in only 4 hours. Combining with generalized gene interaction databases creates a data interface that can help researchers to further analyze the information. Using the TWIRLS system, we found that an important regulatory factor angiotensin-converting enzyme 2 (ACE2) may be involved in the host pathological changes on binding to the coronavirus after infection. After triggering functional changes in ACE2/AT2R, an imbalance in the steady-state cytokine regulatory axis involving the Renin-Angiotensin System and IP-10 leads to a cytokine storm.
RESUMO
Faced with the current large-scale public health emergency, collecting, sorting, and analyzing biomedical information related to the "coronavirus" should be done as quickly as possible to gain a global perspective, which is a basic requirement for strengthening epidemic control capacity. However, for human researchers studying the viruses and the hosts, the vast amount of information available cannot be processed effectively and in a timely manner, particularly when the scientific understanding may be limited, which can further lower the information processing efficiency. We present TWIRLS, a method that can automatically acquire, organize, and classify information. Additionally, independent functional data sources can be added to build an inference system using a machine-based approach, which can provide relevant knowledge to help human researchers quickly establish subject cognition and to make more effective decisions. TWIRLS can automatically analyze more than three million words in more than 14,000 literature articles in only 4 hours. Combining with generalized gene interaction databases creates a data interface that can help researchers to further analyze the information. Using the TWIRLS system, we found that an important regulatory factor angiotensin-converting enzyme 2 (ACE2) may be involved in the host pathological changes on binding to the coronavirus after infection. After triggering functional changes in ACE2/AT2R, an imbalance in the steady-state cytokine regulatory axis involving the Renin-Angiotensin System and IP-10 leads to a cytokine storm.
RESUMO
Objective To give an empirical study on the interests claims of employees in public hospitals. Methods By questionnaire investigation, to sum up data using factor analysis and pairedsamples T test, and to compare difference between different kinds of patients using ANOVA. Results The interests claims of employees can be summed up to seven factors and there is some significant difference between different kinds of employees. Conclusion At current stage, public hospitals need pay more attention to material interests claims of employees.
RESUMO
Objective To give an empirical study on the interests claims of patients in public hospitals. Methods By questionnaire investigation, to sum up data using factor analysis and pairedsamples T test, and to compare difference between different kinds of patients using ANOVA. Results The interests claims of patients can be summed up to six factors and there is no significant difference between different kinds of patients. Conclusion At current stage, public hospitals need improve medical technique and cut down medical expenses.
