The impact of COVID-19 on the employment status and psychological expectations of college graduates: Empirical evidence from the survey data of Chinese recruitment websites

Based on the big data and survey data of online recruitment platform, this paper empirically tests the impact of COVID-19 on the employment status and psychological expectations of college graduates. The results show that: under the impact of COVID-19 epidemic, both supply and demand sides of college graduates’ employment market are affected, such as the decline of recruitment demand, the rise of the employment supply, and the obvious decrease of employment market prosperity. The impacts of COVID-19 epidemic on college graduates’ employment status and psychological expectation in different cities are heterogeneous. In the short term, the epidemic has a negative impact on the employment of graduates, but the employment situation is gradually improving with the support of national policies. Under the influence of COVID-19 epidemic, graduates will change their employment location and expected salary, and they tend to choose “temporary non-employment,” and their proportions of getting offers and signing contracts are significantly reduced. This paper suggests: Firstly, we should continue to push forward the action plan of “expanding jobs in graduation season to promote employment,” and strengthen the persistence and permanence of employment promotion policies for college graduates;Secondly, encourage college students to change their employment concept and rationally adjust their employment expectations;Thirdly, to promote the development of flexible employment of college graduates, it is necessary to strengthen the propaganda of flexible employment, so that students can understand relevant policies;Fourthly, strengthen employment guidance services for graduates from poor families to ensure the continuity and stability of employment assistance policies.

Novel approach by natural language processing for COVID-19 knowledge discovery.

BACKGROUND: The impact of COVID-19 on public health has mandated an 'all hands on deck' scientific response. The current clinical study and basic research on COVID-19 are mainly based on existing publications or our knowledge of coronavirus. However, efficiently retrieval of accurate, relevant knowledge on COVID-19 can pose significant challenges for researchers. METHODS: To improve quality in accessing important literature findings, we developed a novel natural language processing (NLP) method to automatically recognize the associations among potential targeted host organ systems, associated clinical manifestations, and pathways. We further validated these associations through clinician experts' evaluations and prioritize candidate drug targets through bioinformatics network analysis. RESULTS: We found that the angiotensin-converting enzyme 2 (ACE2), a receptor that SARS-CoV-2 required for cell entry, is associated with cardiovascular and endocrine organ system and diseases. Furthermore, we found SARS-CoV-2 is associated with some important pathways such as IL-6, TNF-alpha, and IL-1 beta-induced dyslipidemia, which are related to inflammation, lipogenesis, and oxidative stress mechanisms, suggesting potential drug candidates. CONCLUSION: We prioritized the list of therapeutic targets involved in antiviral and immune modulating drugs for experimental validation, rendering it valuable during public health crises marked by stresses on clinical and research capacity. Our automatic intelligence pipeline also contributes to other novel and emerging disease management and treatments in the future.

Reprogrammed CRISPR-Cas13b suppresses SARS-CoV-2 replication and circumvents its mutational escape through mismatch tolerance.

The recent dramatic appearance of variants of concern of SARS-coronavirus-2 (SARS-CoV-2) highlights the need for innovative approaches that simultaneously suppress viral replication and circumvent viral escape from host immunity and antiviral therapeutics. Here, we employ genome-wide computational prediction and single-nucleotide resolution screening to reprogram CRISPR-Cas13b against SARS-CoV-2 genomic and subgenomic RNAs. Reprogrammed Cas13b effectors targeting accessible regions of Spike and Nucleocapsid transcripts achieved >98% silencing efficiency in virus-free models. Further, optimized and multiplexed Cas13b CRISPR RNAs (crRNAs) suppress viral replication in mammalian cells infected with replication-competent SARS-CoV-2, including the recently emerging dominant variant of concern B.1.1.7. The comprehensive mutagenesis of guide-target interaction demonstrated that single-nucleotide mismatches does not impair the capacity of a potent single crRNA to simultaneously suppress ancestral and mutated SARS-CoV-2 strains in infected mammalian cells, including the Spike D614G mutant. The specificity, efficiency and rapid deployment properties of reprogrammed Cas13b described here provide a molecular blueprint for antiviral drug development to suppress and prevent a wide range of SARS-CoV-2 mutants, and is readily adaptable to other emerging pathogenic viruses.