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Cmes-Computer Modeling in Engineering & Sciences ; 2023.
Article in English | Web of Science | ID: covidwho-20238752


In recent years, the soft subspace clustering algorithm has shown good results for high-dimensional data, which can assign different weights to each cluster class and use weights to measure the contribution of each dimension in various features. The enhanced soft subspace clustering algorithm combines interclass separation and intraclass tightness information, which has strong results for image segmentation, but the clustering algorithm is vulnerable to noisy data and dependence on the initialized clustering center. However, the clustering algorithm is susceptible to the influence of noisy data and reliance on initialized clustering centers and falls into a local optimum;the clustering effect is poor for brain MR images with unclear boundaries and noise effects. To address these problems, a soft subspace clustering algorithm for brain MR images based on genetic algorithm optimization is proposed, which combines the generalized noise technique, relaxes the equational weight constraint in the objective function as the boundary constraint, and uses a genetic algorithm as a method to optimize the initialized clustering center. The genetic algorithm finds the best clustering center and reduces the algorithm's dependence on the initial clustering center. The experiment verifies the robustness of the algorithm, as well as the noise immunity in various ways and shows good results on the common dataset and the brain MR images provided by the Changshu First People's Hospital with specific high accuracy for clinical medicine.

Science Translational Medicine ; 15(677), 2023.
Article in English | Web of Science | ID: covidwho-2246782


SARS-CoV-2 continues to accumulate mutations to evade immunity, leading to breakthrough infections after vaccination. How researchers can anticipate the evolutionary trajectory of the virus in advance in the design of next-generation vaccines requires investigation. Here, we performed a comprehensive study of 11,650,487 SARS-CoV-2 sequences, which revealed that the SARS-CoV-2 spike (S) protein evolved not randomly but into directional paths of either high infectivity plus low immune resistance or low infectivity plus high immune resistance. The viral infectivity and immune resistance of variants are generally incompatible, except for limited variants such as Beta and Kappa. The Omicron variant has the highest immune resistance but showed high infectivity in only one of the tested cell lines. To provide cross-clade immunity against variants that undergo diverse evolutionary pathways, we designed a new pan-vaccine antigen (Span). Span was designed by analyzing the homology of 2675 SARS-CoV-2 S protein sequences from the NCBI database before the Delta variant emerged. The refined Span protein harbors high-frequency residues at given positions that reflect cross-clade generality in sequence evolution. Compared with a prototype wild-type (Swt) vaccine, which, when administered to mice, induced serum with decreased neutralization activity against emerging variants, Span vaccination of mice elicited broad immunity to a wide range of variants, including those that emerged after our design. Moreover, vaccinating mice with a heterologous Span booster conferred complete protection against lethal infection with the Omicron variant. Our results highlight the importance and feasibility of a universal vaccine to fight against SARS-CoV-2 antigenic drift.

Fudan University Journal of Medical Sciences ; 48(5):603-610, 2021.
Article in Chinese | Scopus | ID: covidwho-1471036


Objective: To evaluate the impact of COVID-19 epidemic on anxiety status of active psychological counselors in Shanghai, China. Methods: We collected the demographic information of participants, cognition and attention to COVID-19, attitude towards the disappearance of COVID-19 and answers to the State-Trait Anxiety Inventory (STAI) on the Shanghai online psychological counseling platform from Feb 4th, 2020 to Mar 11st, 2020.Multiple Logistic regression was used to analyze the associations between COVID-19 epidemic and State-anxiety and Trait-anxiety. Results: Of 704 participants with an average age of 33.24 years (ranging from 18 to 73 years), the mean State-scores and Trait-scores were 44.49±6.31 and 46.19±5.22, respectively.In multivariate Logistic regression analysis, after gender stratification and adjustment of related variables, we found that for males, engaging in relevant prevention and control work was associated with a lower risk for medium or high State-anxiety (OR=0.28, 95%CI:0.09-0.89), and holding a intensively positive attitude was associated with a lower risk for medium or high Trait-anxiety (OR=0.25, 95%CI:0.07-0.87);while for females, those with medical background had a lower risk for State-anxiety (OR=0.17, 95%CI:0.03-0.92), and those paying moderate attention to epidemic had a lower risk for Trait-anxiety (OR=0.22, 95%CI:0.07-0.69). Conclusion: COVID-19 epidemic had different effects on the anxiety status of psychological counselors with different characteristics.Psychological counselors who have poor cognition of the epidemic, excessive attention to the epidemic, low hope for the disappearance of the epidemic, and non-disease prevention and control profession are more susceptible to greater anxiety, which are the key objects of protection in the event of public health emergencies. © 2021, Editorial Department of Fudan University Journal of Medical Sciences. All right reserved.