The Omicron variant is rapidly becoming the dominant SARS-CoV-2 virus circulating globally. It is important to define reductions in virus neutralizing activity in the serum of convalescent or ...vaccinated individuals to understand potential loss of protection against infection by Omicron. We previously established that a 50% plaque reduction neutralization antibody titer (PRNT
) ≥25.6 in our live virus assay corresponded to the threshold for 50% protection from infection against wild-type (WT) SARS-CoV-2. Here we show markedly reduced serum antibody titers against the Omicron variant (geometric mean titer (GMT) < 10) compared to WT virus 3-5 weeks after two doses of BNT162b2 (GMT = 218.8) or CoronaVac vaccine (GMT = 32.5). A BNT162b2 booster dose elicited Omicron PRNT
titers ≥25.6 in 88% of individuals (22 of 25) who previously received 2 doses of BNT162b2 and 80% of individuals (24 of 30) who previously received CoronaVac. However, few (3%) previously infected individuals (1 of 30) or those vaccinated with three doses of CoronaVac (1 of 30) met this threshold. Our findings suggest that countries primarily using CoronaVac vaccines should consider messenger RNA vaccine boosters in response to the spread of Omicron. Studies evaluating the effectiveness of different vaccines against the Omicron variant are urgently needed.
Background
The coronavirus disease 2019 (COVID-19) pandemic is having a profound impact on the health and development of children worldwide. There is limited evidence on the impact of COVID-19 and ...its related school closures and disease-containment measures on the psychosocial wellbeing of children; little research has been done on the characteristics of vulnerable groups and factors that promote resilience.
Methods
We conducted a large-scale cross-sectional population study of Hong Kong families with children aged 2–12 years. Parents completed an online survey on family demographics, child psychosocial wellbeing, functioning and lifestyle habits, parent–child interactions, and parental stress during school closures due to COVID-19. We used simple and multiple linear regression analyses to explore factors associated with child psychosocial problems and parental stress during the pandemic.
Results
The study included 29,202 individual families; of which 12,163 had children aged 2–5 years and 17,029 had children aged 6–12 years. The risk of child psychosocial problems was higher in children with special educational needs, and/or acute or chronic disease, mothers with mental illness, single-parent families, and low-income families. Delayed bedtime and/or inadequate sleep or exercise duration, extended use of electronic devices were associated with significantly higher parental stress and more psychosocial problems among pre-schoolers.
Conclusions
This study identifies vulnerable groups of children and highlights the importance of strengthening family coherence, adequate sleep and exercise, and responsible use of electronic devices in promoting psychosocial wellbeing during the COVID-19 pandemic.
Atopic dermatitis (AD) is a common allergic skin disease, characterized by dryness, itchiness, thickening and inflammation of the skin. Infiltration of eosinophils into the dermal layer and presence ...of edema are typical characteristics in the skin biopsy of AD patients. Previous in vitro and clinical studies showed that the Pentaherbs formula (PHF) consisting of five traditional Chinese herbal medicines, Flos Lonicerae, Herba Menthae, Cortex Phellodendri, Cortex Moutan and Rhizoma Atractylodis at w/w ratio of 2:1:2:2:2 exhibited therapeutic potential in treating AD. In this study, an in vivo murine model with oxazolone (OXA)-mediated dermatitis was used to elucidate the efficacy of PHF. Active ingredients of PHF water extract were also identified and quantified, and their in vitro anti-inflammatory activities on pruritogenic cytokine IL-31- and alarmin IL-33-activated human eosinophils and dermal fibroblasts were evaluated. Ear swelling, epidermis thickening and eosinophils infiltration in epidermal and dermal layers, and the release of serum IL-12 of the murine OXA-mediated dermatitis were significantly reduced upon oral or topical treatment with PHF (all p < 0.05). Gallic acid, chlorogenic acid and berberine contents (w/w) in PHF were found to be 0.479%, 1.201% and 0.022%, respectively. Gallic acid and chlorogenic acid could suppress the release of pro-inflammatory cytokine IL-6 and chemokine CCL7 and CXCL8, respectively, in IL-31- and IL-33-treated eosinophils-dermal fibroblasts co-culture; while berberine could suppress the release of IL-6, CXCL8, CCL2 and CCL7 in the eosinophil culture and eosinophils-dermal fibroblasts co-culture (all p < 0.05). These findings suggest that PHF can ameliorate allergic inflammation and attenuate the activation of eosinophils.
The SARS-CoV-2 pandemic poses the greatest global public health challenge in a century. Neutralizing antibody is a correlate of protection and data on kinetics of virus neutralizing antibody ...responses are needed. We tested 293 sera from an observational cohort of 195 reverse transcription polymerase chain reaction (RT-PCR) confirmed SARS-CoV-2 infections collected from 0 to 209 days after onset of symptoms. Of 115 sera collected ≥61 days after onset of illness tested using plaque reduction neutralization (PRNT) assays, 99.1% remained seropositive for both 90% (PRNT
) and 50% (PRNT
) neutralization endpoints. We estimate that it takes at least 372, 416 and 133 days for PRNT
titres to drop to the detection limit of a titre of 1:10 for severe, mild and asymptomatic patients, respectively. At day 90 after onset of symptoms (or initial RT-PCR detection in asymptomatic infections), it took 69, 87 and 31 days for PRNT
antibody titres to decrease by half (T
) in severe, mild and asymptomatic infections, respectively. Patients with severe disease had higher peak PRNT
and PRNT
antibody titres than patients with mild or asymptomatic infections. Age did not appear to compromise antibody responses, even after accounting for severity. We conclude that SARS-CoV-2 infection elicits robust neutralizing antibody titres in most individuals.
Neighborhood rough sets based attribute reduction, as a common dimension reduction method, has been widely used in machine learning and data mining. Each attribute has the same weight (the degree of ...importance) in the existing neighborhood rough set models. In this work, we introduce different weights into neighborhood relations and propose a novel approach for attribute reduction. The main motivation is to fully mine the correlation between attributes and decisions before calculating neighborhood relations, and the attributes with high correlation are assigned higher weights. We first construct a Weighted Neighborhood Rough Set (WNRS) model based on weighted neighborhood relations and discuss its properties. Then WNRS based dependency is defined to evaluate the significance of attribute subsets. We design a greedy search algorithm based on WNRS to select an attribute subset which has both strong correlation and high dependency. Furthermore, we use isometric search to find the optimal neighborhood threshold. Finally, ten datasets from UCI machine learning repository and ELVIRA Biomedical data set repository are used to compare the performance of WNRS with those of other state-of-the-art reduction algorithms. The experimental results show that WNRS is feasible and effective, which has higher classification accuracy and compression ratio.
•The existing researches on neighborhood rough sets use the same attribute weights.•The attributes that are highly related to decisions should be highlighted.•We introduce partition coefficients of attributes to re-assign weights of attributes.•The results show WNRS can get higher classification accuracy and compression ratio.
Attribute reduction is one of the most important preprocessing steps in machine learning and data mining. As a key step of attribute reduction, attribute evaluation directly affects classification ...performance, search time, and stopping criterion. The existing evaluation functions are greatly dependent on the relationship between objects, which makes its computational time and space more costly. To solve this problem, we propose a novel separability-based evaluation function and reduction method by using the relationship between objects and decision categories directly. The degree of aggregation (DA) of intraclass objects and the degree of dispersion (DD) of between-class objects are first defined to measure the significance of an attribute subset. Then, the separability of attribute subsets is defined by DA and DD in fuzzy decision systems, and we design a sequentially forward selection based on the separability (SFSS) algorithm to select attributes. Furthermore, a postpruning strategy is introduced to prevent overfitting and determine a termination parameter. Finally, the SFSS algorithm is compared with some typical reduction algorithms using some public datasets from UCI and ELVIRA Biomedical repositories. The interpretability of SFSS is directly presented by the performance on MNIST handwritten digits. The experimental comparisons show that SFSS is fast and robust, which has higher classification accuracy and compression ratio, with extremely low computational time.
We examine how social capital dimensions of networks affect the transfer of knowledge between network members. We distinguish among three common network types: intracorporate networks, strategic ...alliances, and industrial districts. Using a social capital framework, we identify structural, cognitive, and relational dimensions for the three network types. We then link these social capital dimensions to the conditions that facilitate knowledge transfer. In doing so, we propose a set of conditions that promote knowledge transfer for the different network types.
Superspreading events (SSEs) have characterized previous epidemics of severe acute respiratory syndrome coronavirus (SARS-CoV) and Middle East respiratory syndrome coronavirus (MERS-CoV) infections
. ...For SARS-CoV-2, the degree to which SSEs are involved in transmission remains unclear, but there is growing evidence that SSEs might be a typical feature of COVID-19
. Using contact tracing data from 1,038 SARS-CoV-2 cases confirmed between 23 January and 28 April 2020 in Hong Kong, we identified and characterized all local clusters of infection. We identified 4-7 SSEs across 51 clusters (n = 309 cases) and estimated that 19% (95% confidence interval, 15-24%) of cases seeded 80% of all local transmission. Transmission in social settings was associated with more secondary cases than households when controlling for age (P = 0.002). Decreasing the delay between symptom onset and case confirmation did not result in fewer secondary cases (P = 0.98), although the odds that an individual being quarantined as a contact interrupted transmission was 14.4 (95% CI, 1.9-107.2). Public health authorities should focus on rapidly tracing and quarantining contacts, along with implementing restrictions targeting social settings to reduce the risk of SSEs and suppress SARS-CoV-2 transmission.
Abstract
SARS-CoV-2 infection of children leads to a mild illness and the immunological differences with adults are unclear. Here, we report SARS-CoV-2 specific T cell responses in infected adults ...and children and find that the acute and memory CD4
+
T cell responses to structural SARS-CoV-2 proteins increase with age, whereas CD8
+
T cell responses increase with time post-infection. Infected children have lower CD4
+
and CD8
+
T cell responses to SARS-CoV-2 structural and ORF1ab proteins when compared with infected adults, comparable T cell polyfunctionality and reduced CD4
+
T cell effector memory. Compared with adults, children have lower levels of antibodies to β-coronaviruses, indicating differing baseline immunity. Total T follicular helper responses are increased, whilst monocyte numbers are reduced, indicating rapid adaptive co-ordination of the T and B cell responses and differing levels of inflammation. Therefore, reduced prior β-coronavirus immunity and reduced T cell activation in children might drive milder COVID-19 pathogenesis.
•We propose two multi-label learning approaches with LIFT reduction.•The idea of fuzzy rough set attribute reduction is adopted in our approaches.•Sample selection improves the efficiency in feature ...dimension reduction.
In multi-label learning, since different labels may have some distinct characteristics of their own, multi-label learning approach with label-specific features named LIFT has been proposed. However, the construction of label-specific features may encounter the increasing of feature dimensionalities and a large amount of redundant information exists in feature space. To alleviate this problem, a multi-label learning approach FRS-LIFT is proposed, which can implement label-specific feature reduction with fuzzy rough set. Furthermore, with the idea of sample selection, another multi-label learning approach FRS-SS-LIFT is also presented, which effectively reduces the computational complexity in label-specific feature reduction. Experimental results on 10 real-world multi-label data sets show that, our methods can not only reduce the dimensionality of label-specific features when compared with LIFT, but also achieve satisfactory performance among some popular multi-label learning approaches.