Heritage tourism evolution in Guangfu Ancient City, Hebei Province, China: an analysis with the improved creative destruction model

Ancient cities and towns are popular tourism destinations worldwide. In this paper, Guangfu Ancient City in Yongnian County, Hebei Province, China, is taken as the case study and the modified creative destruction model is applied as the analytical framework to evaluate the multiactor dynamics of heritage tourism development. A mixed method approach is adopted, including a local resident survey, in-depth interviews with staff of the Guangfu Ancient City tourism site and government officials responsible for the heritage conservation and tourism development of the site, and a review of online tourist reviews, relevant government documents and reports. Based on the modified creative destruction model, local residents’ attitudes towards tourism development, changes in tourist numbers, the level of business and government investments, and the motivations of different stakeholders in tourism development are assessed by synthesising on-site research, historical data and other materials. Then, the tourism development stages for Guangfu Ancient City are identified as the precommodification stage before 2006, the early commodification stage from 2006 to 2011 and the advanced commodification stage from 2012 to 2017. The findings indicate that with rapid increases in investments from both corporate and government sources and in the number of tourists, the attitude of local residents towards tourism development remained positive. The results show that instead of entering the initial destruction stage, Guangfu Ancient City is in the transition stage from advanced commodification to creative enhancement given the government’s dominant role in tourism development, the heritage conservation motives of tourism entrepreneurs, the benefits to residents from tourism development ensured by government policies, and the shift in tourist type to postmodern tourists with double demands. The applicability of the modified creative destruction model is further discussed, and policy and management recommendations are generated to support the sustainable development of Guangfu Ancient City after the COVID-19 pandemic.

Predictive Score of Risk Associated with Progression of Patients with COVID-19 Pneumonia in Wuhan, China: the ALA Score.

Background The Coronavirus Disease 2019 (COVID-19) had become a Public Health Emergency of International Concern with more than 90 million confirmed cases worldwide. Therefore, this study aims to establish a predictive score model of progression to severe type in patients with COVID-19. Methods This is a retrospective cohort study of 151 patients with COVID-19 diagnosed by nucleic acid test or specific serum antibodies from February 13, 2020, to March 14, 2020, hospitalized in a COVID-19-designed hospital in Wuhan, China. Results Of the 151 patients with average age of 63 years, 64 patients were male (42.4%), and 29 patients (19.2%) were classified as severe group. Multivariate analysis showed that age > 65 years (odds ratio [OR] = 9.72, 95%CI: 2.92-32.31, P < 0.001), lymphocyte count ≤ 1.1 × 109/L (OR = 3.42, 95%CI: 1.24-9.41, P = 0.017) and AST > 35 U/L (OR = 3.19, 95%CI: 1.11-9.19, P = 0.032) were independent risk factors for the disease severity. The area under curve (AUC) of receiver operating characteristic curve of the probabilities of the composite continuous variable (age + lymphocyte + AST) is 0.796. Finally, a predictive score model called ALA was established, and its AUC was 0.83 (95%CI: 0.75-0.92). Using a cutoff value of 9.5 points, the positive and negative predictive values were 54.1% (38-70.1%) and 92.1% (87.2-97.1%), respectively. Conclusion The ALA score model can quickly identify severe patients with COVID-19, so as to help clinicians to better choose accurate management strategy.

Factors Associated with a Positive Severe Acute Respiratory Syndrome Coronavirus 2 Testing in Suspected Cases Presenting with Pneumonia: A Retrospective Cohort Study in a Single Medical Center.

BACKGROUND: Coronavirus disease 2019 (COVID-19) has become a global emerging infectious disease. OBJECTIVES: To analyze the initial clinical characteristics of COVID-19 suspected and confirmed patients on admission in order to find out which kinds may be more likely to get positive nucleic acid testing results, and to explore the risk factors associated with all-cause death. METHODS: Medical records from 309 highly suspected cases with pneumonia were collected from February 13, 2020, to March 14, 2020, in a COVID-19-designated hospital of Wuhan. The majority of the clinical data were collected on the first day of hospital admission. RESULTS: Of 309 patients with median age 64 years (interquartile ranges [IQR], 53-72 years), 111 patients (35.9%) were confirmed by nucleic acid testing (median age 64 years, IQR: 56-71 years; 48 males). Of those 111 patients, 13 (11.7%) patients died. In multivariate analysis, factors associated with positive testing included fatigue (odds ratios [OR] = 3.14; 95% confidence interval [CI]: 1.88-5.24, p < 0.001), cough (OR = 0.55; 95% CI: 0.32-0.95, p = 0.032), no less than 1 comorbidity (OR = 1.77; 95% CI: 1.06-2.98, p = 0.030), and severe pneumonia (OR = 2.67; 95% CI: 1.20-5.97, p = 0.016). Furthermore, age, dyspnea, noneffective antibiotic treatment, white blood cell, lymphocyte, platelets, and organ dysfunction (e.g., higher lactate dehydrogenase) were significantly associated with all-cause in-hospital death in patients with COVID-19. CONCLUSION: Patients with severe forms of this disease were more likely to get positive results. Age and organ dysfunction were associated with a greater risk of death.

UL36 Encoded by Marek's Disease Virus Exhibits Linkage-Specific Deubiquitinase Activity.

(1) Background: Deubiquitinase (DUB) regulates various important cellular processes via reversing the protein ubiquitination. The N-terminal fragment of a giant tegument protein, UL36, encoded by the Marek's disease (MD) virus (MDV), encompasses a putative DUB (UL36-DUB) and shares no homology with any known DUBs. The N-terminus 75 kDa fragment of UL36 exists in MD T lymphoma cells at a high level and participates in MDV pathogenicity. (2) Methods: To characterize deubiquitinating activity and substrate specificity of UL36-DUB, the UL36 N-terminal fragments, UL36(323), UL36(480), and mutants were prepared using the Bac-to-Bac system. The deubiquitinating activity and substrate specificity of these recombinant UL36-DUBs were analyzed using various ubiquitin (Ub) or ubiquitin-like (UbL) substrates and activity-based deubiquitinating enzyme probes. (3) Results: The results indicated that wild type UL36-DUBs show a different hydrolysis ability against varied types of ubiquitin chains. These wild type UL36-DUBs presented the highest activity to K11, K48, and K63 linkage Ub chains, weak activity to K6, K29, and K33 Ub chains, and no activity to K27 linkage Ub chain. UL36 has higher cleavage efficiency for K48 and K63 poly-ubiquitin than linear ubiquitin chain (M1-Ub4), but no activity on various ubiquitin-like modifiers. The mutation of C98 and H234 residues eliminated the deubiquitinating activity of UL36-DUB. D232A mutation impacted, but did not eliminated UL36(480) activity. The Ub-Br probe can bind to wild type UL36-DUB and mutants UL36(480)H234A and UL36(480)D232A, but not C98 mutants. These in vitro results suggested that the C98 and H234 are essential catalytic residues of UL36-DUB. UL36-DUB exhibited a strict substrate specificity. Inhibition assay revealed that UL36-DUB exhibits resistance to the Roche protease inhibitor cocktail and serine protease inhibitor, but not to the Solarbio protease inhibitor cocktail. (4) Conclusions: UL36-DUB exhibited a strict substrate preference, and the protocol developed in the current study for obtaining active UL36-DUB protein should promote the high-throughput screening of UL36 inhibitors and the study on the function of MDV-encoded UL36.