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1.
J Comput Sci Technol ; 37(6): 1464-1477, 2022.
Article in English | MEDLINE | ID: covidwho-2311860

ABSTRACT

Generating molecules with desired properties is an important task in chemistry and pharmacy. An efficient method may have a positive impact on finding drugs to treat diseases like COVID-19. Data mining and artificial intelligence may be good ways to find an efficient method. Recently, both the generative models based on deep learning and the work based on genetic algorithms have made some progress in generating molecules and optimizing the molecule's properties. However, existing methods need to be improved in efficiency and performance. To solve these problems, we propose a method named the Chemical Genetic Algorithm for Large Molecular Space (CALM). Specifically, CALM employs a scalable and efficient molecular representation called molecular matrix. Then, we design corresponding crossover, mutation, and mask operators inspired by domain knowledge and previous studies. We apply our genetic algorithm to several tasks related to molecular property optimization and constraint molecular optimization. The results of these tasks show that our approach outperforms the other state-of-the-art deep learning and genetic algorithm methods, where the z tests performed on the results of several experiments show that our method is more than 99% likely to be significant. At the same time, based on the experimental results, we point out the insufficiency in the experimental evaluation standard which affects the fair evaluation of previous work. Supplementary Information: The online version contains supplementary material available at 10.1007/s11390-021-0970-3.

2.
NPJ Parkinsons Dis ; 9(1): 7, 2023 Jan 21.
Article in English | MEDLINE | ID: covidwho-2211956

ABSTRACT

Clinical practice guidelines support resilience training and exercise for patients with Parkinson's disease (PD). This assessor-blinded, randomized clinical trial aimed to compare the effects of a modified mindfulness meditation program versus stretching and resistance training exercise (SRTE) in patients with mild-to-moderate PD. A total of 126 potential participants were enrolled via convenience sampling, of which 68 eligible participants were randomized 1:1 to receive eight weekly 90-min sessions of mindfulness meditation or SRTE. Compared to the SRTE group, generalized estimating equation analyses revealed that the mindfulness group had significantly better improvement in outcomes, particularly for improving depressive symptoms (d, -1.66; 95% CI, -3.31 to -0.02) at week 8 and maintaining emotional non-reactivity at week 20 (d, 2.08; 95% CI, 0.59 to 3.56). Both groups demonstrated significant immediate, small-moderate effects on cognition (effect size [d] = 0.36-0.37, p = 0.006-0.011). Compared with the SRTE, mindfulness meditation appeared to be a feasible and promising strategy for managing depressive symptoms and maintaining emotional stability, with comparable benefits on cognitive performance. To combat the psychospiritual and cognitive sequelae of social unrest and COVID-19 pandemic, the integration of mindfulness training into motor-oriented PD rehabilitation protocols is recommended to strengthen the resilience and minimize the psycho-cognitive comorbidities among patients with mild-to-moderate PD.Trial Registration: HKU Clinical Trials Registry identifier: HKUCTR-2681.

3.
Journal of computer science and technology : Duplicate, marked for deletion ; 37(6):1464-1477, 2022.
Article in English | EuropePMC | ID: covidwho-2170225

ABSTRACT

Generating molecules with desired properties is an important task in chemistry and pharmacy. An efficient method may have a positive impact on finding drugs to treat diseases like COVID-19. Data mining and artificial intelligence may be good ways to find an efficient method. Recently, both the generative models based on deep learning and the work based on genetic algorithms have made some progress in generating molecules and optimizing the molecule's properties. However, existing methods need to be improved in efficiency and performance. To solve these problems, we propose a method named the Chemical Genetic Algorithm for Large Molecular Space (CALM). Specifically, CALM employs a scalable and efficient molecular representation called molecular matrix. Then, we design corresponding crossover, mutation, and mask operators inspired by domain knowledge and previous studies. We apply our genetic algorithm to several tasks related to molecular property optimization and constraint molecular optimization. The results of these tasks show that our approach outperforms the other state-of-the-art deep learning and genetic algorithm methods, where the z tests performed on the results of several experiments show that our method is more than 99% likely to be significant. At the same time, based on the experimental results, we point out the insufficiency in the experimental evaluation standard which affects the fair evaluation of previous work. Supplementary Information The online version contains supplementary material available at 10.1007/s11390-021-0970-3.

4.
biorxiv; 2022.
Preprint in English | bioRxiv | ID: ppzbmed-10.1101.2022.08.10.503531

ABSTRACT

The SARS-CoV-2 virus is the causal agent of the ongoing pandemic of coronavirus disease 2019 (COVID-19). There is an urgent need for potent, specific antiviral compounds against SARS-CoV-2. The 3C-like protease (3CLpro) is an essential enzyme for the replication of SARS-CoV-2 and other coronaviruses, and thus is a target for coronavirus drug discovery. Nearly all inhibitors of coronavirus 3CLpro reported so far are covalent inhibitors. Here, we report the development of specific, non-covalent inhibitors of 3CLpro. The most potent one, WU-04, effectively blocks SARS-CoV-2 replications in human cells with EC 50 values in the 10-nM range. WU-04 also inhibits the 3CLpro of SARS-CoV and MERS-CoV with high potency, indicating that it is a pan-inhibitor of coronavirus 3CLpro. WU-04 showed anti-SARS-CoV-2 activity similar to that of PF-07321332 (Nirmatrelvir) in K18-hACE2 mice when the same dose was administered orally. Thus, WU-04 is a promising drug candidate for coronavirus treatment. One-Sentence Summary A oral non-covalent inhibitor of 3C-like protease effectively inhibits SARS-CoV-2 replication.


Subject(s)
COVID-19
5.
Surg Innov ; : 15533506221108858, 2022 Jun 23.
Article in English | MEDLINE | ID: covidwho-1902316

ABSTRACT

BACKGROUND: As the 2019 Coronavirus Disease (COVID-19) repeated, the prevention and treatment will be normalized in a period. "Large number of patients" and " Turnover quickly" of the day surgery ward greatly increased the difficulty of policy formulation and implementation. The normalization also had a huge negative psychological impact on patients/family members. This study aims to introduce effective epidemic prevention and control measures in day surgery wards, and to clarify the influencing factors of anxiety and subjective discomfort of patients and their families during the normalization of COVID-19. METHODS: To prepare for normalization of epidemic, research discuss improvements in the management of staff, environment, process. A total of 148 patients admitted to West China Hospital from December 2021 to March 2022 and their relatives were asked to complete a questionnaire effectively. Using the Self-rating Anxiety Scale, Social Support Rating Scale and Subjective Units of Distress scales to analyze anxiety and its risk factors. RESULTS: Under normalized control measures, no staff was infected. The subjective discomfort score was higher in people with lower body mass index (BMI). Young and high social support score were risk factors for anxiety (P < .05), and social support was positively correlated with anxiety. CONCLUSION: The normalization of epidemic is an inevitable trend in a period. A stable and safe medical environment needs to fully eliminate the policy defects, to fit the people and focus on mental health of the people. For patients/family members, who are younger,a lower BMI and higher social support should be attention more.

6.
Journal of the Operations Research Society of China ; : 1-16, 2022.
Article in English | EuropePMC | ID: covidwho-1842698

ABSTRACT

The pandemic of COVID-19 initiated in 2019 and spread all over the world in 2020 has caused significant damages to the human society, making troubles to all aspects of our daily life. Facing the serious outbreak of the virus, we consider possible solutions from the perspectives of both governments and enterprises. Particularly, this paper discusses several applications of supply chain management, public resource allocation, and pandemic prevention using optimization and machine learning methods. Some useful insights in mitigating the pandemic and economy reopening are provided at the end of this paper. These insights might help governments to reduce the severity of the current pandemic and prevent the next round of outbreak. They may also improve companies’ reactions to the increasing uncertainties appearing in the business operations. Although the coronavirus imposes challenges to the entire society at the moment, we are confident to develop new techniques to prevent and eradicate the disease.

7.
Front Public Health ; 9: 741812, 2021.
Article in English | MEDLINE | ID: covidwho-1775898

ABSTRACT

Background: With the rapid urbanization, citizenization of migrants is becoming the development tendency in China. It is significant to analyze the determining factors of the settlement intention of migrants. Methods: The data we used were taken from the China Migrants Dynamic Survey (CMDS) in 2017. Multilevel mixed-effects logistic regression was used to analyze the relationship between air pollution, economic advantages, and settlement intention between different migrants and the moderating effect of social welfare. Results: At the individual level, being female, married, urban and other ethnic, having higher education, older, and health associated with likelihood of settlement intention of migrants. Higher health education, social integration, and, have a health record were positively associated with the likelihood of settlement intention. Higher educated, urban areas, and Han migrants were willing to reduce their pursuit of health for economic development. Conclusion: Health education and more social organizational participation can reduce the negative effect of air pollution and increase the positive effect of economic advantages on settlement intention of migrants. But, in less economically advantaged areas, it has no obvious effect. In the choice of health and wealth, the settlement intention of migrants shows difference, and unfairness and social welfare, in particular health education, can narrow this difference.


Subject(s)
Transients and Migrants , China , Female , Humans , Intention , Social Welfare
8.
Influenza Other Respir Viruses ; 16(3): 395-401, 2022 05.
Article in English | MEDLINE | ID: covidwho-1526375

ABSTRACT

BACKGROUND: The pandemic of COVID-19 has a persistent impact on global health, yet its sequelae need to be addressed at a wide scale around the globe. This study aims to investigate the characteristics, prevalence, and risk factors for mid-term (>6 months) clinical sequelae in a cohort of COVID-19 survivors. METHODS: Totally 715 COVID-19 survivors discharged before April 1, 2020, from three medical centers in Wuhan, China, were included. The longitudinal study was conducted by telephone interviews based on a questionnaire including the clinical sequelae of general, respiratory, and cardiovascular systems. Demographics and some characteristics of clinical sequelae of the survivors were recorded and analyzed. Multivariate logistic regression analysis was applied to explore the risk factors for the sequelae. RESULTS: The median time interval from discharge to telephone interview was 225.0 days. The COVID-19 survivors' median ages were 69 years, and 51.3% were male. Among them, 29.9% had at least one clinical sequela. There were 19.2%, 22.7%, and 5.0% of the survivors reporting fatigue, respiratory symptoms, and cardiovascular symptoms, respectively. Comorbidities, disease severity, the application of mechanical ventilation and high-flow oxygen therapy, and the history of re-admission were associated with the presence of clinical sequelae. CONCLUSIONS: Our study provides further evidence for the prevalence and characteristics of clinical sequelae of COVID-19 survivors, suggesting long-term monitoring and management is needed for their full recovery.


Subject(s)
COVID-19 , Aged , COVID-19/complications , COVID-19/epidemiology , China/epidemiology , Humans , Longitudinal Studies , Male , Pandemics , SARS-CoV-2 , Survivors
9.
Nat Struct Mol Biol ; 28(9): 755-761, 2021 09.
Article in English | MEDLINE | ID: covidwho-1406396

ABSTRACT

Bradykinin and kallidin are endogenous kinin peptide hormones that belong to the kallikrein-kinin system and are essential to the regulation of blood pressure, inflammation, coagulation and pain control. Des-Arg10-kallidin, the carboxy-terminal des-Arg metabolite of kallidin, and bradykinin selectively activate two G protein-coupled receptors, type 1 and type 2 bradykinin receptors (B1R and B2R), respectively. The hyperactivation of bradykinin receptors, termed 'bradykinin storm', is associated with pulmonary edema in COVID-19 patients, suggesting that bradykinin receptors are important targets for COVID-19 intervention. Here we report two G protein-coupled complex structures of human B1R and B2R bound to des-Arg10-kallidin and bradykinin, respectively. Combined with functional analysis, our structures reveal the mechanism of ligand selectivity and specific activation of the bradykinin receptor. These findings also provide a framework for guiding drug design targeting bradykinin receptors for the treatment of inflammation, cardiovascular disorders and COVID-19.


Subject(s)
Bradykinin/metabolism , COVID-19/pathology , Kallidin/metabolism , Receptors, Bradykinin/metabolism , Cryoelectron Microscopy , Enzyme Activation/physiology , Humans , Protein Structure, Tertiary , Pulmonary Edema/pathology , Pulmonary Edema/virology , SARS-CoV-2
10.
J Raman Spectrosc ; 52(5): 949-958, 2021 May.
Article in English | MEDLINE | ID: covidwho-1095641

ABSTRACT

The outbreak of COVID-19 coronavirus disease around the end of 2019 has become a pandemic. The preferred method for COVID-19 detection is the real-time polymerase chain reaction (RT-PCR)-based technique; however, it also has certain limitations, such as sample-dependent procedures with a relatively high false negative ratio. We propose a safe and efficient method for screening COVID-19 based on Raman spectroscopy. A total of 177 serum samples are collected from 63 confirmed COVID-19 patients, 59 suspected cases, and 55 healthy individuals as a control group. Raman spectroscopy is adopted to analyze these samples, and a machine learning support-vector machine (SVM) method is applied to the spectrum dataset to build a diagnostic algorithm. Furthermore, 20 independent individuals, including 5 asymptomatic COVID-19 patients and 5 symptomatic COVID-19 patients, 5 suspected patients, and 5 healthy patients, were sampled for external validation. In these three groups-confirmed COVID-19, suspected, and healthy individuals-the distribution of statistically significant points of difference showed highly consistency for intergroups after repeated sampling processes. The classification accuracy between the COVID-19 cases and the suspected cases is 0.87 (95% confidence interval [CI]: 0.85-0.88), and the accuracy between the COVID-19 and the healthy controls is 0.90 (95% CI: 0.89-0.91), while the accuracy between the suspected cases and the healthy control group is 0.68 (95% CI: 0.67-0.73). For the independent test dataset, we apply the obtained SVM model to the classification of the independent test dataset to have all the results correctly classified. Our model showed that the serum-level classification results were all correct for independent test dataset. Our results suggest that Raman spectroscopy could be a safe and efficient technique for COVID-19 screening.

11.
biorxiv; 2020.
Preprint in English | bioRxiv | ID: ppzbmed-10.1101.2020.08.25.266775

ABSTRACT

The global spread of SARS-CoV-2 is posing major public health challenges. One unique feature of SARS-CoV-2 spike protein is the insertion of multi-basic residues at the S1/S2 subunit cleavage site, the function of which remains uncertain. We found that the virus with intact spike (Sfull) preferentially enters cells via fusion at the plasma membrane, whereas a clone (Sdel) with deletion disrupting the multi-basic S1/S2 site instead utilizes a less efficient endosomal entry pathway. This idea was supported by the identification of a suite of endosomal entry factors specific to Sdel virus by a genome-wide CRISPR-Cas9 screen. A panel of host factors regulating the surface expression of ACE2 was identified for both viruses. Using a hamster model, animal-to-animal transmission with the Sdel virus was almost completely abrogated, unlike with Sfull. These findings highlight the critical role of the S1/S2 boundary of the SARS-CoV-2 spike protein in modulating virus entry and transmission.

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