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What is already known about this topic?: Both the decline in immunity over time and the evolution of the virus play a role in the level of protection offered by a prior infection. What is added by this report?: Point estimates indicated variations in protection levels based on the initial infecting variant and the reinfecting variant. There was a consistent correlation between real-world protection, antigenic distance, and humoral immunity levels. Specifically, shorter antigenic distances and higher humoral immunity levels corresponded to enhanced real-world protection. What are the implications for public health practice?: Our findings suggest that virological and immunological studies could help identify and assess the epidemic risk posed by new variants before they become dominant. Prompt incorporation of the latest variants into the antigen components of the coronavirus disease 2019 (COVID-19) vaccines can significantly contribute to effective epidemic prevention and control measures.
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In 2021, China's domestically produced coronavirus disease 2019 (COVID-19) vaccines received approval from regulatory bodies and were administered worldwide. Due to a low number of infections within China during that period, it became imperative to evaluate the vaccines' real-world effectiveness through international studies. To facilitate this, China CDC launched the COVID-19 Vaccines Evaluation Program (COVEP). This program formed research collaboration agreements with health institutes across five World Health Organization regions, addressing key questions about vaccine performance through ten cooperative agreements. The findings from COVEP projects reinforced confidence, both domestically and globally, in the effectiveness of the vaccines produced in China. Moreover, the outcomes observed internationally were frequently mirrored by later studies conducted within China. COVEP thus pioneered a novel approach for fostering cross-national research collaborations, addressing significant public health issues and exemplifying a framework for international cooperation. This approach is in line with the strategic objectives and other development efforts of China CDC's national disease control and prevention initiatives.
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Background: Several COVID-19 vaccines were developed and approved in China. Of these, the BIBB-CorV and CoronaVac inactivated whole-virion vaccines were widely distributed in China and developing countries. However, the performance of the two vaccines in the real world has not been summarized. Methods: A living systematic review based on findings from ongoing post-licensure studies was conducted, applying standardized algorithms. Articles published between 1 May 2020 and 31 May 2022 in English and Chinese were searched for in Medline, Embase, WanFang Data, medRxiv, bioRxiv, arXiv, SSRN, and Research Square, using SARS-CoV-2, COVID-19, and vaccine as the MeSH terms. Studies with estimates of safety, immunogenicity, and effectiveness from receiving the BIBB-CorV or CoronaVac vaccine that met the predefined screening criteria underwent a full-text review. The Joanna Briggs Institute's Critical Appraisal Checklist and the Cochrane risk of bias were used for assessment of the quality. A random-effects meta-regression model was applied to identify the potential impact factors on the vaccines' effectiveness. Results: In total, 32578 articles were identified, of these, 770 studies underwent a full-text review. Eventually, 213 studies were included. The pooled occurrence of solicited and unsolicited adverse events after any dose of either vaccine varied between 10% and 40%. The top five commonly reported rare adverse events were immunization stress-related responses (211 cases, 50.0%), cutaneous responses (43 cases, 10.2%), acute neurological syndrome (39 cases, 9.2%), anaphylaxis (17 cases, 4.0%), and acute stroke (16 cases, 3.8%). The majority (83.3%) recovered or were relieved within several days. The peak neutralization titers against the ancestral strain was found within 1 month after the completion of the primary series of either vaccine, with a GMT (geometric mean titer) of 43.7 (95% CI: 23.2-82.4), followed by a dramatic decrease within 3 months. At Month 12, the GMT was 4.1 (95% CI: 3.8-4.4). Homologous boosting could restore humoral immunity, while heterologous boosting elicited around sixfold higher neutralization titers in comparison with homologous boosting. The effectiveness of receiving either vaccine against death and severe disease was around 85% for both shortly after the primary series. At Month 12, the protection against death did not decline, while the protection against severe disease decreased to ~75%. Conclusions: Both the BIBP-CorV and CoronaVac inactivated vaccines are safe. Sustained vaccine effectiveness against death was determined 12 months after the primary series, although protection against severe disease decreased slightly over time. A booster dose could strengthen the waning effectiveness; however, the duration of the incremental effectiveness and the additional benefit provided by a heterologous booster need to be studied.
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A novel core-shell structured alginate-based hydrogel bead modified by co-gelatinizing with starch and protocatechuic acid (PA), was designed to modulate physical properties of beads, release behavior and antioxidant stability of encapsulated bioactives. Core was fabricated by ionotropic gelation, and its formulation (ratio of sodium alginate/starch) was determined by particle size/starch distribution, texture and bioactive encapsulation capacity of core. Then, coating core with shell-forming solution co-gelatinized with different doses of PA, and subsequently cross-linked with Ca2+ to obtain core-shell structured beads. Surface microstructure, mechanical characteristics, and swelling ratio of beads were affected by concentrations of PA. Besides, core-shell structure containing PA could enhance delivery and sustained release of encapsulated phenolic bioactives during in vitro digestion, and improve their antioxidant potential stability. Furthermore, interaction between PA and polysaccharide components was elucidated by FTIR and TGA. The present information was beneficial for the advancement of functional food materials and bioactive delivery systems.
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BACKGROUND: Proteins play a pivotal role in the diverse array of biological processes, making the precise prediction of protein-protein interaction (PPI) sites critical to numerous disciplines including biology, medicine and pharmacy. While deep learning methods have progressively been implemented for the prediction of PPI sites within proteins, the task of enhancing their predictive performance remains an arduous challenge. RESULTS: In this paper, we propose a novel PPI site prediction model (DGCPPISP) based on a dynamic graph convolutional neural network and a two-stage transfer learning strategy. Initially, we implement the transfer learning from dual perspectives, namely feature input and model training that serve to supply efficacious prior knowledge for our model. Subsequently, we construct a network designed for the second stage of training, which is built on the foundation of dynamic graph convolution. CONCLUSIONS: To evaluate its effectiveness, the performance of the DGCPPISP model is scrutinized using two benchmark datasets. The ensuing results demonstrate that DGCPPISP outshines competing methods in terms of performance. Specifically, DGCPPISP surpasses the second-best method, EGRET, by margins of 5.9%, 10.1%, and 13.3% for F1-measure, AUPRC, and MCC metrics respectively on Dset_186_72_PDB164. Similarly, on Dset_331, it eclipses the performance of the runner-up method, HN-PPISP, by 14.5%, 19.8%, and 29.9% respectively.
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Redes Neurais de Computação , Mapeamento de Interação de Proteínas/métodos , Biologia Computacional/métodos , Proteínas/química , Proteínas/metabolismo , Aprendizado Profundo , Bases de Dados de Proteínas , Aprendizado de MáquinaRESUMO
This study discusses interaction differences between three phenols (protocatechuic acid, naringin and tannic acid) and starch helix, investigates influences of phenols at different doses on properties of maize starch, and further determines their effects on quality and function of maize-starchy foods. Simulated results indicate variations of phenolic structure (phenolic hydroxyl group amount, glycoside structure and steric hindrance) and dose induce phenols form different complexes with starch helix. Formation of different starch-phenols complexes alters gelatinization (1.65-5.63 J/g), pasting form, water binding capacity (8.83-12.69 g/g) and particle size distribution of starch. Meanwhile, differences in starch-phenols complexes are reflected in fingerprint area (R1045/1022: 0.920 to 1.047), crystallinity (8.3% to 17.0%), rheology and gel structure of starch. Additionally, phenols change texture and color of cold maize cake, giving them different antioxidant capacity and lower digestibility. Findings are beneficial for understanding interaction between starch and different phenols and their potential application.
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Fenóis , Amido , Zea mays , Zea mays/química , Amido/química , Fenóis/química , Qualidade dos Alimentos , Reologia , Antioxidantes/química , Tamanho da PartículaRESUMO
Background: Hemorrhagic fever with renal syndrome (HFRS) is a zoonotic infectious disease commonly found in Asia and Europe, characterized by fever, hemorrhage, shock, and renal failure. China is the most severely affected region, necessitating an analysis of the temporal incidence patterns in the country. Methods: We employed Autoregressive Integrated Moving Average (ARIMA), Long Short-Term Memory (LSTM), Convolutional Neural Network (CNN), Nonlinear AutoRegressive with eXogenous inputs (NARX), and a hybrid CNN-LSTM model to model and forecast time series data spanning from January 2009 to November 2023 in the mainland China. By comparing the simulated performance of these models on training and testing sets, we determined the most suitable model. Results: Overall, the CNN-LSTM model demonstrated optimal fitting performance (with Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), and Mean Absolute Error (MAE) of 93.77/270.66, 7.59%/38.96%, and 64.37/189.73 for the training and testing sets, respectively, lower than those of individual CNN or LSTM models). Conclusion: The hybrid CNN-LSTM model seamlessly integrates CNN's data feature extraction and LSTM's recurrent prediction capabilities, rendering it theoretically applicable for simulating diverse distributed time series data. We recommend that the CNN-LSTM model be considered as a valuable time series analysis tool for disease prediction by policy-makers.
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Febre Hemorrágica com Síndrome Renal , Humanos , Febre Hemorrágica com Síndrome Renal/epidemiologia , Incidência , Fatores de Tempo , Simulação por Computador , China/epidemiologiaRESUMO
Effects of Epiphyllum oxypetalum (DC.) Haw polysaccharide (EP) on physicochemical/digestive properties of tapioca starch (TS) were investigated, and its effects on final quality of TS-based foods were further determined. Results showed EP significantly decreased gelatinization enthalpy (3.92 to 2.11 J/g) and increased breakdown (302 to 382 cp), thereby inducing the gelatinization of TS. Meanwhile, EP decreased setback viscosity (324 to 258 cp), suggesting the retrogradation of TS paste was inhibited. Rheological determination results suggested EP had an impact on the viscoelasticity of TS paste. Moreover, particle size distribution showed EP increased size of TS by cross-linking. Additionally, the suitable addition of EP ameliorated the microstructure and decreased the crystal diffraction peak area of TS gel. Infrared spectroscopy results revealed EP modified the above properties of TS by hydrogen bonds and non-covalent forces. Furthermore, EP inhibited the in vitro digestion of TS paste. Using taro balls as TS-based food model, appropriate addition of EP (0.10 %) improved texture properties, frozen storage stability and color of samples. The present results can not only facilitate the understanding of the modification mechanism of EP on the properties of TS, but also induce the burgeoning of starchy products and the possible application of EP in foods.
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Manihot , Manihot/química , Amido/química , Viscosidade , Alimentos , TermodinâmicaRESUMO
BACKGROUND: Gonorrhea has long been a serious public health problem in mainland China that requires attention, modeling to describe and predict its prevalence patterns can help the government to develop more scientific interventions. METHODS: Time series (TS) data of the gonorrhea incidence in China from January 2004 to August 2022 were collected, with the incidence data from September 2021 to August 2022 as the validation. The seasonal autoregressive integrated moving average (SARIMA) model, long short-term memory network (LSTM) model, and hybrid SARIMA-LSTM model were used to simulate the data respectively, the model performance were evaluated by calculating the mean absolute percentage error (MAPE), root mean square error (RMSE), and mean absolute error (MAE) of the training and validation sets of the models. RESULTS: The Seasonal components after data decomposition showed an approximate bimodal distribution with a period of 12 months. The three models identified were SARIMA(1,1,1) (2,1,2)12, LSTM with 150 hidden units, and SARIMA-LSTM with 150 hidden units, the SARIMA-LSTM model fitted best in the training and validation sets, for the smallest MAPE, RMSE, and MPE. CONCLUSIONS: The overall incidence trend of gonorrhea in mainland China has been on the decline since 2004, with some periods exhibiting an upward trend. The incidence of gonorrhea displays a seasonal distribution, typically peaking in July and December each year. The SARIMA model, LSTM model, and SARIMA-LSTM model can all fit the monthly incidence time series data of gonorrhea in mainland China. However, in terms of predictive performance, the SARIMA-LSTM model outperforms the SARIMA and LSTM models, with the LSTM model surpassing the SARIMA model. This suggests that the SARIMA-LSTM model can serve as a preferred tool for time series analysis, providing evidence for the government to predict trends in gonorrhea incidence. The model's predictions indicate that the incidence of gonorrhea in mainland China will remain at a high level in 2024, necessitating that policymakers implement public health measures in advance to prevent the spread of the disease.
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Gonorreia , Humanos , Fatores de Tempo , Gonorreia/epidemiologia , China/epidemiologia , Governo , Saúde Pública , ConvulsõesRESUMO
The canine mammary tumor model is more suitable for studying human breast cancer, and the safety concentrations of matrine and the biotin-labeled matrine probe were determined in canine primary mammary epithelial cells, and then selected canine mammary tumor cell lines CHMm and CHMp were incubated with matrine, and cell viability was detected by CCK-8. The biotin-labeled matrine probe was used to pull-down the targets of matrine in canine mammary tumor cells, and the targets were screened in combination with activity-based protein profiling (ABPP) and Genecards database, and verified by qPCR and western blot. The results showed that the maximum non-cytotoxic concentrations of matrine and biotin-labeled matrine probe in canine primary mammary epithelial cells were 250 µg/mL and 500 µg/mL, respectively. Matrine and biotin-labeled matrine probe had a proliferation inhibitory effect time-dependently on CHMm and CHMp cells within a safe concentration range, and induced autophagy in cells. Then BTF3 targets were obtained by applying ABPP and Genecards screening. Cellular thermal shift assay (CETSA) findings indicated that matrine could increase the heat stability of BTF3 protein. Pull-down employing biotin-labeled matrine probe with CHMm and CHMp cell lysates revealed that BTF3 protein was detected in the biotin-labeled matrine probe group and that BTF3 protein was significantly decreased by the addition of matrine. The qPCR and western blot findings of CHMm and CHMp cells treated with matrine revealed that matrine decreased the expression of the BTF3 gene and protein with the extension of the action time, and the impact was more substantial at the protein level, respectively.
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Neoplasias Mamárias Animais , Matrinas , Humanos , Animais , Cães , Biotina , Neoplasias Mamárias Animais/tratamento farmacológico , Neoplasias Mamárias Animais/genética , Células Epiteliais , Sobrevivência CelularRESUMO
Importance. The great success in vaccine-preventable diseases has been accompanied by vaccine safety concerns. This has caused vaccine hesitancy to be the top 10 in threats to global health. The comprehensive understanding of adverse events following immunization should be entirely based on clinical trials and postapproval surveillance. It has increasingly been recognized worldwide that the active surveillance of vaccine safety should be an essential part of immunization programs due to its complementary advantages to passive surveillance and clinical trials.Highlights. In the present study, the framework of vaccine safety surveillance was summarized to illustrate the importance of active surveillance and address vaccine hesitancy or safety concerns. Then, the global progress of active surveillance systems was reviewed, mainly focusing on population-based or hospital-based active surveillance. With these successful paradigms, the practical and reliable ways to create robust and similar systems in China were discussed and presented from the perspective of available databases, methodology challenges, policy supports, and ethical considerations.Conclusion. In the inevitable trend of the global vaccine safety ecosystem, the establishment of an active surveillance system for vaccine safety in China is urgent and feasible. This process can be accelerated with the consensus and cooperation of regulatory departments, research institutions, and data owners.
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On 31 March 2013, the National Health and Family Planning Commission, China notified the World Health Organization of three cases of human infection with avian influenza A(H7N9) from Shanghai and Anhui.1 By 8 May, 131 cases, including 26 deaths, had been notified from 11 provinces/municipalities.1,2 The majority (81%) of reported cases were from Shanghai municipality and Zhejiang and Jiangsu provinces. Available data indicate that more than three quarters of cases (59/77, 76%) had recent exposure to animals. Among these, 58% (34/59) had direct contact with chickens and 64% (38/59) visited a live bird market (LBM).3 Provincial and national authorities in China have collected more than 80 000 samples from LBMs, poultry slaughter houses, poultry farms, wild bird habitats, pig slaughter houses and their environments. As of 7 May, 50 samples were positive for avian influenza A(H7N9): 39 samples from poultry from LBMs in Anhui, Jiangsu, Jiangxi, Guangdong, Shanghai and Zhejiang provinces/municipalities (26 chickens, three ducks, four pigeons, six unknown) and 11 environmental samples from LBMs in Shanghai, Henan and Shandong provinces.4 None of the samples from poultry farms or pigs were positive