Assessing the determinants of corporate environmental investment: a machine learning approach.

In recent years, experts and academics in the environmental management field have developed an interest in the factors and evaluation techniques that influence corporate environmental investment decisions. However, there are substantial differences between studies employing the most recent evaluation methodologies and those that use indicator systems. To explore the mechanisms that influence corporate environmental investment, this study investigated the determinants of environmental investment through the perspectives of firm, board, chair, and chief executive officer (CEO) characteristics using a machine learning approach. Based on a large-scale data sample from Chinese-listed companies, the results indicated that the extreme gradient boosting (XGBoost) model had an accuracy of up to 97.63%, thus performing the best. Additionally, the model that used SHapley Additive exPlanations (SHAP) to interpret XGBoost showed that a company's sales performance was the most important factor that influenced environmental investment, followed by CEO tenure, board independence, board gender diversity, chair academic experience, and the company's level of internationalization. Furthermore, when examining the sample of heavily polluting enterprises, sales, board gender diversity, CEO tenure, chair academic experience, board independence, and chair-CEO duality, all were found to play crucial roles in predicting environmental investment. Overall, this study aids in evaluating the factors that influence corporate environmental investment decisions and provides policymakers and practitioners with a machine learning approach for use when assessing these factors.

Occurrence, distribution and ecological risk assessment of herbicide residues in cropland soils from the Mollisols region of Northeast China.

The first systematic and comprehensive investigation of herbicide residues was conducted by identifying their spatial distribution, influencing factors and ecological risk in cropland soils from the Mollisols region covering 109 million hm2 in Northeast China. Fifty-six herbicides were detected with total herbicide concentrations ranging from 1.01 to 1558.13 µg/kg (mean: 227.45). Atrazine, its degradates deethyl atrazine (DEA) and deisopropyl atrazine (DIA), trifluralin and butachlor were the most frequently detected herbicides, while DEA, clomazone, nicosulfuron, fomesafen, and mefenacet exhibited the highest concentrations. Despite being less frequently reported in Chinese soils, fomesafen, nicosulfuron, clomazone, and mefenacet were found widely present. Although most of the compounds posed a minimal or low ecological risk, atrazine, nicosulfuron and DEA exhibited medium to high potential risks. The key factors identified to regulate the fate of herbicides were soil chemical properties, amount of herbicides application, and the crop type. The soybean soils showed highest herbicide residues, while the soil mineral contents likely adsorbed more herbicides. This study provides a valuable large-scale dataset of herbicide residues across the entire Mollisols region of China along with fine-scale characterization of the ecological risks. Mitigation and management measures are needed to reduce the herbicide inputs and residues in the region.

Enzymatic synthesis of pharmacologically relevant chiral sulfoxides by improved CbBVMO variants.

Baeyer-Villiger monooxygenases (BVMOs) are able to catalyse the asymmetric oxidation of sulfides. This property has made them attractive catalysts for the synthesis of chiral sulfoxide drugs. Here, we have designed and synthesised an exhaustive combinatorial mutant library of the previously identified lansoprazole sulfide monooxygenase CbBVMOV1. From this synthetic combinatorial mutant library, the best mutant, CbBVMOV3, was selected with a specific activity of approximately 1 U mg-1 for lansoprazole sulfoxides. We then optimised the reaction conditions of a two-phase system, achieving the enzymatic asymmetric synthesis of (R)-lansoprazole in a space-time yield of 213 g L-1 d-1 and an enantiomeric excess of >99% (R) with no detectable by-products. In addition, CbBVMOV3 showed higher activity towards other prazole sulfides. These results indicate the potential application of CbBVMO in the chiral sulfoxide drug industry.

Performance of iCare quantitative computed tomography in bone mineral density assessment of the hip and vertebral bodies in European spine phantom.

BACKGROUND: Osteoporosis is a systemic bone disease which can increase the risk of osteoporotic fractures. Dual-energy X-ray absorptiometry (DXA) is considered as the clinical standard for diagnosing osteoporosis by detecting the bone mineral density (BMD) in patients, but it has flaws in distinguishing between calcification and other degenerative diseases, thus leading to inaccurate BMD levels in subjects. Mindways quantitative computed tomography (Mindways QCT) is a classical QCT system. Similar to DXA, Mindways QCT can directly present the density of trabecular bone, vascular or tissue calcification; therefore, it is more accurate and sensitive than DXA and has been widely applied in clinic to evaluate osteoporosis. iCare QCT osteodensitometry was a new phantom-based QCT system, recently developed by iCare Inc. (China). It has been gradually applied in clinic by its superiority of taking 3-dimensional BMD of bone and converting BMD values to T value automatically. This study aimed at evaluating the osteoporosis detection rate of iCare QCT, compared with synchronous Mindways QCT (USA). METHODS: In this study, 131 patients who underwent hip phantom-based CT scan were included. Bone mineral density (BMD) of the unified region of interests (ROI) defined at the European spine phantom (ESP, German QRM) including L1 (low), L2 (medium), and L3 (high) vertebral bodies was detected for QCT quality control and horizontal calibration. Every ESP scan were taken for 10 times, and the mean BMD values measured by iCare QCT and Mindways QCT were compared. Hip CT scan was conducted with ESP as calibration individually. T-scores gained from iCare QCT and Mindways QCT were analyzed with Pearson correlation test. The detection rates of osteoporosis were compared between iCare QCT and Mindways QCT. The unified region of interests (ROI) was delineated in the QCT software. RESULTS: The results showed that there was no significant difference between iCare QCT and Mindways QCT in the evaluation of L1, L2, and L3 vertebrae bodies in ESP. A strong correlation between iCare QCT and Mindways QCT in the assessment of hip T-score was found. It was illustrated that iCare QCT had a higher detection rate of osteoporosis with the assessment of hip T-score than Mindways QCT did. In patients < 50 years subgroup, the detection rate of osteoporosis with iCare QCT and Mindways QCT was equal. In patients ≥ 50 years subgroup, the detection rate of osteoporosis with iCare QCT (35/92, 38.0%) was higher than that with Mindways QCT. In female subgroup, the detection rate of osteoporosis with iCare QCT was significantly higher than Mindways QCT. In male subgroup, the detection rate of osteoporosis with iCare QCT was also markedly higher than Mindways QCT. The detection rate of osteoporosis by iCare QCT was higher than Mindways QCT with hip bone assessment. Of course, the results of the present study remain to be further verified by multicenter studies in the future.

Is there more to bitcoin mining than carbon emissions?

Critics decry cryptocurrency mining as a huge waste of energy, while proponents insist on claiming that it is a green industry. Is Bitcoin mining really worth the energy it consumes? The high power consumption of cryptocurrency mining has become the latest global flashpoint. In this paper, we define the Mining Domestic Production (MDP) as a method to account for the final outcome of the Bitcoin mining industry's production activities in a certain period time, calculate the carbon emission per unit output value of the Bitcoin mining industry in China, and compare it with three other traditional industries. The results show that Bitcoin mining does not always have the highest when compared with others. The contribution of this paper is that we give a new perspective on thinking whether Bitcoin mining is more efficient to make more profit, in terms of the same amount of carbon emissions per unit compared to other industries. Moreover, it could even be argued that Bitcoin may present an opportunity for some developing countries to build out their electrical capacity and generate revenue.

Large-Scale Qualitative and Quantitative Assessment of Dityrosine Crosslinking Omics in Response to Endogenous and Exogenous Hydrogen Peroxide in Escherichia coli.

Excessive hydrogen peroxide causes oxidative stress in cells. The oxidation of two tyrosine residues in proteins can generate o,o'-dityrosine, a putative biomarker for protein oxidation, which plays critical roles in a variety of organisms. Thus far, few studies have investigated dityrosine crosslinking under endogenous or exogenous oxidative conditions at the proteome level, and its physiological function remains largely unknown. In this study, to investigate qualitative and quantitative dityrosine crosslinking, two mutant Escherichia coli strains and one mutant strain supplemented with H2O2 were used as models for endogenous and exogenous oxidative stress, respectively. By integrating high-resolution liquid chromatography-mass spectrometry and bioinformatic analysis, we created the largest dityrosine crosslinking dataset in E. coli to date, identifying 71 dityrosine crosslinks and 410 dityrosine loop links on 352 proteins. The dityrosine-linked proteins are mainly involved in taurine and hypotaurine metabolism, citrate cycle, glyoxylate, dicarboxylate metabolism, carbon metabolism, etc., suggesting that dityrosine crosslinking may play a critical role in regulating the metabolic pathways in response to oxidative stress. In conclusion, we have reported the most comprehensive dityrosine crosslinking in E. coli for the first time, which is of great significance in revealing its function in oxidative stress.

Primary assessment of the diversity of Omicron sublineages and the epidemiologic features of autumn/winter 2022 COVID-19 wave in Chinese mainland.

With the recent ongoing autumn/winter 2022 COVID-19 wave and the adjustment of public health control measures, there have been widespread SARS-CoV-2 infections in Chinese mainland. Here we have analyzed 369 viral genomes from recently diagnosed COVID-19 patients in Shanghai, identifying a large number of sublineages of the SARS-CoV-2 Omicron family. Phylogenetic analysis, coupled with contact history tracing, revealed simultaneous community transmission of two Omicron sublineages dominating the infections in some areas of China (BA.5.2 mainly in Guangzhou and Shanghai, and BF.7 mainly in Beijing) and two highly infectious sublineages recently imported from abroad (XBB and BQ.1). Publicly available data from August 31 to November 29, 2022 indicated an overall severe/critical case rate of 0.035% nationwide, while analysis of 5706 symptomatic patients treated at the Shanghai Public Health Center between September 1 and December 26, 2022 showed that 20 cases (0.35%) without comorbidities progressed into severe/critical conditions and 153 cases (2.68%) with COVID-19-exacerbated comorbidities progressed into severe/critical conditions. These observations shall alert healthcare providers to place more resources for the treatment of severe/critical cases. Furthermore, mathematical modeling predicts this autumn/winter wave might pass through major cities in China by the end of the year, whereas some middle and western provinces and rural areas would be hit by the upcoming infection wave in mid-to-late January 2023, and the duration and magnitude of upcoming outbreak could be dramatically enhanced by the extensive travels during the Spring Festival (January 21, 2023). Altogether, these preliminary data highlight the needs to allocate resources to early diagnosis and effective treatment of severe cases and the protection of vulnerable population, especially in the rural areas, to ensure the country's smooth exit from the ongoing pandemic and accelerate socio-economic recovery.

Burden of liver complications related to non-alcoholic fatty liver disease in China from 2005 to 2019: Observations from the Global Burden of Disease Study, 2019.

AIM: To assess the burden of liver complications related to non-alcoholic fatty liver disease (LC-NAFLD) from 2005 to 2019 in China. MATERIALS AND METHODS: We used data from the Global Burden of Disease, Injuries, and Risk Factors Study, 2019, to present contemporary and varying profiles of China's LC-NAFLD burden. The Joinpoint Regression model and Gaussian process regression were, respectively, used to estimate the annual percentage change in prevalence rates and disability-adjusted life-year (DALY) rates, and the relationship between the sociodemographic index (SDI) and age-standardized rates of LC-NAFLD. RESULTS: In 2019, China had 293.42 million (95% uncertainty interval [UI]: 263.69-328.44) LC-NAFLD cases with a prevalence rate and DALYs of 20.63 (95% UI: 23.09-18.54) per 1000 people and 591.03 thousand (95% UI: 451.25-737.33), respectively. North China had the highest prevalence but the lowest DALYs of LC-NAFLD, whereas Southwest China had the lowest prevalence but the highest DALYs. LC-NAFLD were more common in men than in women (male: female ratio, 1.27) in 2019. From 2005 to 2019, the prevalence of NAFLD cases increased by 68.32% (from 174.32 million in 2005 to 293.42 million in 2019), mainly because of an age-specific prevalence rate increase. CONCLUSION: The LC-NAFLD burden in China is substantial and has increased markedly over the past 15 years. Effective measures for low SDI regions and men are needed to address the rapidly increasing NAFLD burden.

COVID-19, traffic demand, and activity restriction in China: A national assessment.

The global COVID pandemic of 2020, affected travel patterns across the world. The level of impact was influenced not only by the virus itself, but also by the nature, extent, and duration of governmental restriction on commerce and personal activity to limit its spread. This paper focuses on the interaction between COVID-19 transmission and traffic volume and further explores the impact of traffic control policies on the interaction. Roadway traffic volume was used to quantify and assess the Chinese response to the pandemic; specifically, the relationship between government restrictions, travel activity, and COVID-19 progression across 29 provinces. Space and time distributions of traffic volume across China during the first half of 2020, were used to quantity the response and recovery of travel during the critical initial onset period of the virus. Most revealing of these trends were the impact of the Chinese restriction policies on both travel and the virus as well as the relationship of traffic trends during the closure period with the speed and extent of the recovery "bounce" across individual provinces based on location, economic activity, and restriction policy. These suggest that the most significant and rapid declines in traffic volume during the restriction period resulted in the most pronounced returns to normal (or more) demand levels. Based on these trends a Susceptible Infection Recovery model was created to simulate a range of outbreak and restriction policies to examine the relationship between COVID-19 spread and traffic volume in China.

Assessment of three-dimensional rotation of the shoulder complex and scapulohumeral rhythm during sagittal movement.

BACKGROUND: Due to the influence of spinal and respiratory movements, it is difficult to accurately measure the range of motion of each joint. OBJECTIVE: To conduct a three-dimensional (3D) measurement of each joint in the shoulder complex in different postures in the sagittal plane of the upper extremity. METHODS: Thirteen healthy adults with no history of shoulder surgery for trauma or chronic pain were enrolled in the present study. The computed tomography (CT) imaging data of the shoulder complex were acquired in four postures via the reconstruction and alignment of 3D images. The angles of the postural changes were measured, and rotation vectors were used for descriptions and statistical analyses. RESULTS: There was a statistical difference in the rotation angles between the dominant and non-dominant sides of the sternoclavicular joint when the posture changed from a resting position to a posterior inferior position. During the postural change from a resting position to a horizontal position, the regression coefficient (ß) of the humerothoracic joint to the sternoclavicular joint was 0.191, and the ß of the humerothoracic joint to the glenohumeral joint was 0.621. During the postural change from the horizontal position to the rear upper position, the ß of the humerothoracic joint to the sternoclavicular joint was 0.316, and the ß of the humerothoracic joint to the glenohumeral joint was 0.845. During the postural change from the resting position to the rear lower position, the ß of the humerothoracic joint to the glenohumeral joint was 0.991. CONCLUSION: The application of the image alignment technique enabled the direct and accurate measurement of the bony structures of the shoulder joint. The helical approach accurately described the scapulohumeral rhythm during 3D motion. There was a scapulohumeral rhythm of the shoulder complex during 3D composite sagittal movement, with different ratios for different joints and postures.

Evolution and Simulation of Terrestrial Ecosystem Carbon Storage and Sustainability Assessment in Karst Areas: A Case Study of Guizhou Province.

Against the background of "carbon neutrality" and sustainable development goals, it is of great significance to assess the carbon storage changes and sustainability of terrestrial ecosystems in order to maintain the coordinated sustainable development of regional ecological economies and the balance of terrestrial ecosystems. In this study, the terrestrial ecosystem carbon storage in Guizhou from 2010 to 2020 was assessed with the InVEST model. Using the PLUS model, the distribution of terrestrial ecosystem carbon storage by 2030 and 2050 was predicted. The current sustainable development level of the terrestrial ecosystem of Guizhou was evaluated after establishing an index system based on SDGs. The results showed the following: (1) From 2010 to 2020, the terrestrial ecosystem carbon storage decreased by 1106.68 × 104 Mg. The area and carbon storage of the forest and farmland ecosystems decreased while the area and carbon storage of the grassland and settlement ecosystems increased. (2) Compared with 2020, the terrestrial ecosystem carbon storage will be reduced by 4091.43 × 104 Mg by 2030. Compared with 2030, the terrestrial ecosystem carbon storage will continue to decrease by 3833.25 × 104 Mg by 2050. (3) In 2020, the average score of the sustainable development of the terrestrial ecosystem was 0.4300. Zunyi City had the highest sustainable development score of 0.6255, and Anshun had the lowest sustainable development score of 0.3236. Overall, the sustainable development of the terrestrial ecosystem of Guizhou was found to be high in the north, low in the south, high in the east, and low in the west. The sustainable regional development of the terrestrial ecosystem of Guizhou was found to be unbalanced, and the carbon storage of the terrestrial ecosystem will keep decreasing in the future. In order to improve the sustainable development capacity of the terrestrial ecosystem, the government needs to take certain measures, such as returning farmland to forests and grasslands, curbing soil erosion, and actively supervising.

A forced cough sound based pulmonary function assessment method by using machine learning.

Pulmonary function testing (PFT) has important clinical value for the early detection of lung diseases, assessment of the disease severity, causes identification of dyspnea, and monitoring of critical patients. However, traditional PFT can only be carried out in a hospital environment, and it is challenging to meet the needs for daily and frequent evaluation of chronic respiratory diseases. In this study, we propose a novel method for accurately assessing pulmonary function by analyzing recorded forced cough sounds by mobile device without time and location restrictions. In the experiment, 309 clips of cough sound segments were separated from 133 patients who underwent PFT by using Audacity software. There are 247 clips of training samples and 62 clips of testing samples. Totally 52 features were extracted from the dataset, and principal component analysis (PCA) was used for feature reduction. Combined with biological attributes, the normalized features were regressed by using machine learning models with pulmonary function parameters (i.e., FEV1, FVC, FEV1/FVC, FEV1%, and FVC%). And a 5-fold cross-validation was applied to evaluate the performance of the regression models. As described in the experimental result, the result of coefficient of determination (R2) indicates that the support vector regression (SVR) model performed best in assessing FVC (0.84), FEV1% (0.61), and FVC% (0.62) among these models. The gradient boosting regression (GBR) model performs best in evaluating FEV1 (0.86) and FEV1/FVC (0.54). The result confirmed that the proposed method was capable of accurately assessing pulmonary function with forced cough sound. Besides, the cough sound sampling by a smartphone made it possible to conduct sampling and assess pulmonary function frequently in the home environment.

Influenza A(H7N9) Pandemic Preparedness: Assessment of the Breadth of Heterologous Antibody Responses to Emerging Viruses from Multiple Pre-Pandemic Vaccines and Population Immunity.

Influenza A(H7N9) viruses remain as a high pandemic threat. The continued evolution of the A(H7N9) viruses poses major challenges in pandemic preparedness strategies through vaccination. We assessed the breadth of the heterologous neutralizing antibody responses against the 3rd and 5th wave A(H7N9) viruses using the 1st wave vaccine sera from 4 vaccine groups: 1. inactivated vaccine with 2.8 µg hemagglutinin (HA)/dose + AS03A; 2. inactivated vaccine with 5.75 µg HA/dose + AS03A; 3. inactivated vaccine with 11.5 µg HA/dose + MF59; and 4. recombinant virus like particle (VLP) vaccine with 15 µg HA/dose + ISCOMATRIX™. Vaccine group 1 had the highest antibody responses to the vaccine virus and the 3rd/5th wave drifted viruses. Notably, the relative levels of cross-reactivity to the drifted viruses as measured by the antibody GMT ratios to the 5th wave viruses were similar across all 4 vaccine groups. The 1st wave vaccines induced robust responses to the 3rd and Pearl River Delta lineage 5th wave viruses but lower cross-reactivity to the highly pathogenic 5th wave A(H7N9) virus. The population in the United States was largely immunologically naive to the A(H7N9) HA. Seasonal vaccination induced cross-reactive neuraminidase inhibition and binding antibodies to N9, but minimal cross-reactive antibody-dependent cell-mediated cytotoxicity (ADCC) antibodies to A(H7N9).

Development and assessment of deep learning system for the location and classification of rib fractures via computed tomography.

PURPOSE: The purpose of this study was to evaluate the performance of a deep learning system for the automatic diagnosis and classification of rib fractures. METHODS: This retrospective study analyzed computed tomography (CT) data of patients diagnosed with a rib fracture between 1 January 2019 and 23 July 2020 in two hospitals, including 591 patients from Suzhou TCM hospital and 75 patients from Jintan TCM hospital. A deep learning system (Dr.Wise@ChestFracture v1.0) based on a convolutional neural network framework was used as a diagnostic tool, and a human-model comparison experiment was designed to compare the diagnostic efficiencies of the deep learning system and radiologists. Furthermore, a secondary classification model was established to distinguish the different types of fracture. First, a classification model to differentiate between fresh and old fractures was developed. Second, a submodel to determine any misalignment in fresh fractures was established. RESULTS: For all fracture types, the detection efficiency (recall) of the system was statistically significantly better than that of radiologists with different levels of experience (all p < 0.0167 except for senior radiologists). The F1-score of the system for diagnosing rib fractures was similar to that of the radiologists. The system was much faster than the radiologists in assessing rib fractures (all p < 0.0167). The two classification models can distinguish between fresh and old fractures (accuracy = 87.63%) and determine whether there is any misalignment in fresh fractures (accuracy = 95.22%) or not. CONCLUSION: The use of a deep learning system can accurately, automatically, and rapidly diagnose and classify rib fractures, helping doctors improve the diagnostic efficiency and reducing their workload. The classification models can distinguish different types of rib fracture well.

Benefit-Risk Assessment of Dietary Patterns by Bioavailable Metals, Gut Microbes, and Their Interaction for Human Health.

The high-carbohydrate, low-fat, low-protein (HC-LFP) and low-carbohydrate, high-fat, high-protein (LC-HFP) diets are the main dietary patterns worldwide. The influence of dietary patterns on bioavailable metals, gut microbes, and their interaction is still unknown. A biomimetic digestive tract with full functions is constructed to transform the diets into chyme, and the gut microbes are cultured with the corresponding chyme. The diet species-specificity in bioavailable metal content and the positive and negative correlations between bioavailable metals and microbial reproductions are disclosed. The safe dosage and maximum consumption are 369.5 and 858.6 g/d and 268.6 and 3119.0 g/d for LC-HFP and HC-LFP, respectively. When replacing HC-LFP with LC-HFP for 21 days, the bioavailability of Fe and Cr is increased 83.2% and 268.4%, respectively; the reproductions of harmful and benefical microbes are significantly increased and decreased. The prevalences of obesity, inflammation, septicemia, and cancer are increased, and then the risk of dietary pattern shift is disclosed.

Point and interval prediction of crude oil futures prices based on chaos theory and multiobjective slime mold algorithm.

Crude oil is the most important energy source in the world, and fluctuations in oil prices can significantly influence investors, companies, and governments. However, crude oil prices have numerous characteristics, including randomness, sudden structural changes, intrinsic nonlinearity, volatility, and chaotic nature. This makes the accurate forecasting of crude oil prices a difficult and challenging task. In this paper, a hybrid prediction model for crude oil futures prices is proposed, the accuracy and robustness of which are demonstrated via controlled experiments and sensitivity analysis. This study uses a new data denoising method for data processing to improve the accuracy and stability of the predictions of crude oil prices. Furthermore, the chaotic time-series prediction method, shallow neural networks, linear model prediction methods, and deep learning methods are adopted as submodels. The results of interval forecasts with narrow widths and high prediction accuracies are derived by introducing a confidence interval adjustment coefficient. The results of the simulation experiments indicate that the proposed hybrid prediction model exhibits higher accuracy and efficiency, as well as better robustness of the forecasting than the control models. In summary, the proposed forecasting framework can derive accurate point and interval forecasts and provide a valuable reference for the price forecasting of crude oil futures.

[Investigation and health risk assessment of veterinary drug residues in chickens and eggs sold in Ningxia from 2016 to 2020].

OBJECTIVE: To understand the monitoring status of veterinary drug residues in chickens and eggs sold in Ningxia from 2016 to 2020, and to evaluate the health risks of human intake. METHODS: A total of 303 chicken and 237 eggs were collected from 2016 to 2020, and the veterinary drug residues in chickens and eggs sold in Ningxia were detected and analyzed by high performance liquid chromatography-tandem mass spectrometry. The food safety index method was used to assess the health risks in combination with the dietary intake of residents. RESULTS: The detection rate of veterinary drug residues in chicken was 38.0%(115/303), and the over-standard rate was 7.6%(23/303). The detection rate of veterinary drug residues in eggs was 26.6%(63/237), and the over-standard rate was 19.8%(47/237). The food safety index of doxycycline in chicken was 4.59, and the food safety indexes of doxycycline, flumequine and flufenicol in eggs were 7.09, 26.5 and 2.33, respectively, all of which were much higher than 1, suggesting that there were health risks. The food safety indexes of other substances were all less than 1, and the food safety indexes were all acceptable. CONCLUSION: Veterinary drugs were widely detected in chicken and eggs in Ningxia from 2016 to 2020. Some veterinary drugs had hidden health risks.

Early assessment of the safety and immunogenicity of a third dose (booster) of COVID-19 immunization in Chinese adults.

Inducing durable and effective immunity against severe acute respiratory syndrome Coronavirus 2 (SARS-CoV-2) via vaccination is essential to combat the current pandemic of coronavirus disease 2019 (COVID-19). It has been noticed that the strength of anti-COVID-19 vaccination-induced immunity fades over time, which calls for an additional vaccination regime, as known as booster immunization, to restore immunity among previously vaccinated populations. Here we report a pilot open-label trial of a third dose of BBIBP-CorV, an inactivated SARS-CoV-2 vaccine (Vero cell), on 136 participants aged between 18 to 63 years. Safety and immunogenicity in terms of neutralizing antibody titers and cytokine/chemokine responses were analyzed as the main endpoint until day 28. While systemic reactogenicity was either absent or mild, SARS-CoV-2-specific neutralizing antibody titers rapidly arose in all participants within 4 weeks, surpassing the peak antibody titers elicited by the initial two-dose immunization regime. Broad increases of cellular immunity-associated cytokines and chemokines were also detected in the majority of participants after the third vaccination. Furthermore, in an exploratory study, a newly developed recombinant protein vaccine, NVSI-06-08 (CHO Cells), was found to be safe and even more effective than BBIBP-CorV in eliciting humoral immune responses in BBIBP-CorV-primed individuals. Together, these results indicate that a third immunization schedule with either homologous or heterologous vaccine showed favorable safety profiles and restored potent SARS-CoV-2-specific immunity, providing support for further trials of booster vaccination in larger populations.