Comprehensive identification and risk assessment of regulated and emerging mycotoxins in infant foods and related raw materials and risk management advice: A case study of an infant food company in China.

This study evaluated muti-mycotoxins in 199 samples including processed infant foods and raw materials collected randomly from an infant food company and assessed their role in dietary exposure in infants and young children via probabilistic risk assessment. Approximately 79.6 % (74/93) of the processed infant foods and 65.1 % (69/106) of the raw materials were contaminated by mycotoxins, with a mean occurrence level of 3.66-321.8 µg/kg. Deoxynivalenol (DON) and tenuazonic acid (TeA) were the more prevalent mycotoxins detected, based on their higher frequencies and levels across samples. Co-occurrence of more than two mycotoxins was detected in 61.3 % (57/93) of the processed infant foods and 53.8 % (57/106) of the raw materials. Wheat flour and derived products (e.g., infant noodles and infant biscuits) were contaminated with higher contamination levels and a greater variety of mycotoxins than other samples (e.g., infant cereal and rice grains). The estimated daily exposure to OTA, DON, ZEN, and TEN was lower than the corresponding reference health-based guidance values, indicating acceptable health risks. However, the estimated dietary exposure to alternariol monomethyl ether (AME), alternariol (AOH), and tenuazonic acid (TeA) exceeded the corresponding thresholds of toxicological concern values, indicating potential dietary intake risks. Among the various samples, cereals and cereal-based infant foods emerged as the primary contributors to mycotoxin exposure. Further research is advised to address the uncertainties surrounding the toxicity associated with emerging Alternaria mycotoxins and to conduct cumulative risk assessments concerning multiple mycotoxin exposure in infants and young children.

Decision analysis of PPP project's parties based on deep consumer participation.

Although PPP(Public-private partnership) mode has been applied for a long time in infrastructural project, the success rate is not very high. The sustainability of PPP projects is still influenced by many factors. In order to examine the evolutionary stable strategies (ESSs) of social capital, government, and paying consumers, a tripartite evolutionary game model is established in this work. In order to further promote consumer participation, it is necessary to make the assumption that customer oversight and review can have an impact on service prices. The results show: i)The strategy choice of consumer depends on the comparison between supervision cost of consumer and price coefficient for consumer to social capital. ii)Consumer supervision can promote the provision of high-quality services by social capital. iii)The difference between high-quality cost and low-quality cost, subsidy coefficient, price coefficient and supervision cost of consumer are critical factors influencing both evolutionary results and trajectories. This paper also puts forward policy implications for the three stakeholders to promote social capital's high-quality strategy so as to maintain the sustainability of PPP projects.

Nomogram-based risk assessment model for left ventricular hypertrophy in patients with essential hypertension: Incorporating clinical characteristics and biomarkers.

Left ventricular hypertrophy (LVH) is a hypertensive heart disease that significantly escalates the risk of clinical cardiovascular events. Its etiology potentially incorporates various clinical attributes such as gender, age, and renal function. From mechanistic perspective, the remodeling process of LVH can trigger increment in certain biomarkers, notably sST2 and NT-proBNP. This multicenter, retrospective study aimed to construct an LVH risk assessment model and identify the risk factors. A total of 417 patients with essential hypertension (EH), including 214 males and 203 females aged 31-80 years, were enrolled in this study; of these, 161 (38.6%) were diagnosed with LVH. Based on variables demonstrating significant disparities between the LVH and Non-LVH groups, three multivariate stepwise logistic regression models were constructed for risk assessment: the "Clinical characteristics" model, the "Biomarkers" model (each based on their respective variables), and the "Clinical characteristics + Biomarkers" model, which amalgamated both sets of variables. The results revealed that the "Clinical characteristics + Biomarkers" model surpassed the baseline models in performance (AUC values of the "Clinical characteristics + Biomarkers" model, the "Biomarkers" model, and the "Clinical characteristics" model were .83, .75, and .74, respectively; P < .0001 for both comparisons). The optimized model suggested that being female (OR: 4.26, P <.001), being overweight (OR: 1.88, p = .02) or obese (OR: 2.36, p = .02), duration of hypertension (OR: 1.04, P = .04), grade III hypertension (OR: 2.12, P < .001), and sST2 (log-transformed, OR: 1.14, P < .001) were risk factors, while eGFR acted as a protective factor (OR: .98, P = .01). These findings suggest that the integration of clinical characteristics and biomarkers can enhance the performance of LVH risk assessment.

Carbon trade-off and energy budgeting under conventional and conservation tillage in a rice-wheat double cropping system.

Amid rising energy crises and greenhouse gas (GHG) emissions, designing energy efficient, GHG mitigation and profitable conservation farming strategies are pertinent for global food security. Therefore, we tested a hypothesis that no-till with residue retaining could improve energy productivity (EP) and energy use efficiency (EUE) while mitigating the carbon footprint (CF), water footprint (WF) and GHG emissions in rice-wheat double cropping system. We studied two tillage viz., conventional and conservation, with/without residue retaining, resulting as CT0 (puddled-transplanted rice, conventional wheat -residue), CTR (puddled-transplanted rice, conventional wheat + residue), NT0 (direct seeded rice, zero-till wheat -residue), and NTR (direct seeded rice, zero-till wheat + residue). The overall results showed that the NTR/NT0 had 34% less energy consumption and 1.2-time higher EP as compared to CTR/CT0. In addition, NTR increased 19.8% EUE than that of CT0. The grain yield ranged from 8.7 to 9.3 and 7.8-8.5 Mg ha-1 under CT and NT system, respectively. In NTR, CF and WF were 56.6% and 17.9% lower than that of CT0, respectively. The net GHG emissions were the highest (7261.4 kg CO2 ha-1 yr-1) under CT0 and lowest (4580.9 kg CO2 ha-1 yr-1) under NTR. Notably, the carbon sequestration under NTR could mitigate half of the system's CO2-eq emissions. The study results suggest that NTR could be a viable option to offset carbon emissions and water footprint by promoting soil organic carbon sequestration, and enhancing energy productivity and energy use efficiency in the South Asian Indo-Gangetic Plains.

Advancing sustainable financial management in greening companies through big data technology innovation.

Incorporating sustainability into financial management procedures has emerged as a critical component in the modern business landscape for organizations looking to strengthen their environmental stewardship while guaranteeing financial viability. The study "Advancing Sustainable Financial Management in Greening Companies through Big Data Technology Innovation" explains the crucial role that big data technologies play in empowering businesses to incorporate environmental sustainability into their financial management strategies. The research the strong link between big data analytics and the optimization of sustainable financial management in businesses from year 1990 to 2022. The study's findings show that big data analytics enables firms to make data-driven decisions, significantly increasing the effectiveness of their sustainability activities. With the enormous amounts of data that big data technologies can analyze, businesses can access actionable insights that make it easier to identify and reduce environmental impacts, use resources more efficiently, and streamline supply chains to support sustainability. To emphasizes the businesses can match their financial goals with sustainability objectives through big data technology without sacrificing profitability. Big data analytics may help businesses assess environmental risks and find possibilities for sustainable investment, enabling them to make well-informed financial decisions consistent with their commitment to environmental stewardship. The conclusion emphasizes the businesses to adopt big data technology focusing on long-term financial management strategically. The growing environmental problems that endanger the world's ecosystems underscore even more how crucial it is to include these advancements. Therefore, integrating sustainability into financial management using big data technology is not just a choice but a requirement for businesses to succeed in this century. The study demonstrated that the businesses, decision-makers, and other stakeholders to understand and use big data technologies' potential to advance sustainable financial management and build more resilient and sustainable corporate environments.

Multi-parametric MRI assessment of melatonin regulating the polarization of microglia in rats after cerebral ischemia/reperfusion injury.

OBJECTIVES: Multi-parametric magnetic resonance imaging (MRI) can provide comprehensive and valuable information for precise diagnosis and treatment evaluation of a number of diseases. In this study, the neuroprotective effects of melatonin (Mel) on a rat model of cerebral ischemia/reperfusion injury (CIRI) were assessed by multi-parametric MRI combined with histopathological techniques for longitudinal monitoring of the lesion microenvironment. METHODS: Sixty Sprague Dawley (SD) rats were randomly divided into three groups: the Sham, CIRI and CIRI + Mel groups. At multiple time points after ischemia, MRI scanning was performed on a 7.0 Tesla MRI scanner. Multi-parametric MRI includes T2-weighted imaging (T2WI), diffusion weighted imaging (DWI), and chemical exchange saturation transfer (CEST)-MRI. CEST effects were calculated by the Lorentzian difference method, 3.5 ppm indicates amide protons of mobile proteins/peptide (Amide-CEST) and 2.0 ppm indicates amine protons (Guan-CEST). Multiple histopathological techniques were used to examine the histopathological changes and explore the therapeutic effects of Mel. RESULTS: T2WI and DWI-MRI could localize the infarct foci and areas in CIRI rats, which was further validated by staining, 2, 3, 5-triphenyl tetrazolium chloride (TTC) staining, hematoxylin and eosin (H&E) staining, and terminal deoxynucleotidyl transferase-mediated deoxyuridine triphosphate-biotin nick end labelling (TUNEL) staining. After Mel treatment, T2WI and DWI-MRI showed smaller infarct volume, and neurons displayed improved morphology with less apoptosis rates. Notably, Amide-CEST and Guan-CEST signal decreased as early as 2 h after CIRI (all P <0.001), reflecting the change of pH after ischemia. After Mel treatment, both Amide-CEST and Guan-CEST signal increased in ischemic cortex and striatum compared with control group (all P < 0.001). The immunofluorescence staining and western blotting analysis suggested the expression of M2 microglia increased after Mel treatment; While，after Mel treatment the inflammatory factor interleukin-1ß (IL-1ß) decreased compared with control CIRI rats. CONCLUSIONS: Multi-parametric MRI was shown to be an effective method to monitor the brain damage in a rat model of CIRI and assess the therapeutic effects of Mel treatment. Amide-CEST and Guan-CEST were especially sensitive to the changes in brain microenvironment during the early stage after CIRI. Furthermore, the neuroprotective effect of Mel treatment is associated with its promotion of the microglia polarized to M2 type in CIRI rats.

Economic Burden of Hand, Foot, and Mouth Disease - Beijing Municipality, China, 2016-2019.

What is already known about this topic?: Current research regarding hand, foot, and mouth disease (HFMD) has primarily concentrated on the economic impacts, drawing from retrospective or sentinel hospital-based data. This approach often overlooks cases that were either not consulted or were misdiagnosed. What is added by this report?: This research systematically examined the iceberg phenomenon of HFMD and its economic implications in Beijing. Our findings indicate that each confirmed case represents 9.1 actual infections, imposing financial burdens of 25.58 United States dollars (USD) per unconsulted individual, 265.75 USD per misdiagnosed individual, 366.50 USD per individual with mild cases, and 2355.89 USD per individual with severe cases. The annual economic losses attributed to HFMD in the area range from 7.03 million USD to 13.31 million USD. What are the implications for public health practice?: This study offers insight into the actual prevalence of HFMD in Beijing, as well as conducting an economic burden analysis on a per-case, per-category basis. This could facilitate a cost-effectiveness analysis of prevention and control strategies for HFMD.

Development and validation of machine learning models for venous thromboembolism risk assessment at admission: a retrospective study.

Introduction: Venous thromboembolism (VTE) risk assessment at admission is of great importance for early screening and timely prophylaxis and management during hospitalization. The purpose of this study is to develop and validate novel risk assessment models at admission based on machine learning (ML) methods. Methods: In this retrospective study, a total of 3078 individuals were included with their Caprini variables within 24 hours at admission. Then several ML models were built, including logistic regression (LR), random forest (RF), and extreme gradient boosting (XGB). The prediction performance of ML models and the Caprini risk score (CRS) was then validated and compared through a series of evaluation metrics. Results: The values of AUROC and AUPRC were 0.798 and 0.303 for LR, 0.804 and 0.360 for RF, and 0.796 and 0.352 for XGB, respectively, which outperformed CRS significantly (0.714 and 0.180, P < 0.001). When prediction scores were stratified into three risk levels for application, RF could obtain more reasonable results than CRS, including smaller false positive alerts and larger lower-risk proportions. The boosting results of stratification were further verified by the net-reclassification-improvement (NRI) analysis. Discussion: This study indicated that machine learning models could improve VTE risk prediction at admission compared with CRS. Among the ML models, RF was found to have superior performance and great potential in clinical practice.

Occurrence of N-nitrosodimethylamine in roasted Alaska pollock fillets during processing and storage and preliminary cancer risk assessment.

BACKGROUND: Dried and salt-fermented fish products are important sources of N-nitrosodimethylamine (NDMA) exposure for human. As a potent carcinogen, NDMA was frequently detected in roasted Alaska pollock fillet products (RPFs), which is among the most common fish products in China. Until now, the occurrence and development of NDMA and its precursors (nitrites, nitrates and dimethylamine) in RPFs during processing and storage were not well elucidated, and safety evaluation of this fish product is also urgently needed. RESULTS: The presence of precursors in the raw material was verified and significant increase of nitrates and nitrites during processing was observed. NDMA was found generated during pre-drying (3.7 µg kg-1 dry basis) and roasting (14.6 µg kg-1 dry basis) process. Continuous increase in NDMA content can also be found during storage, especially at higher storage temperature. The 95th percentile of Monte Carlo simulated cancer risk (3.73 × 10-5 ) surpassed the WHO threshold (1.00 × 10-5 ) and sensitivity analysis implies the risk was mainly attributable to NDMA level in RPFs. CONCLUSION: The occurrence of NDMA in RFPs was mainly a result of endogenous factors originating in Alaska pollock during processing and storage rather than exogenous contamination, and temperature played a pivotal role. The preliminary risk assessment results suggest that long-term consumption of RPFs would impose potential health risks for consumers. © 2023 Society of Chemical Industry.

Levels, distribution, childhood exposure assessment, and influencing factors of polybrominated diphenyl ethers (PBDEs) in household dust from nine cities in China.

Household dust is an important source of premature exposure to polybrominated diphenyl ethers (PBDEs), especially for children. In this onsite study, 246 dust samples were collected from 224 households in nine Chinese cities during 2018-2019. Questionnaires were administered to explore the association between household-related information and PBDEs in household dust. The median concentration of Σ12PBDEs in household dust from 9 cities was 138 ng/g (94-227 ng/g), with the arithmetic mean of 240 ± 401 ng/g. Among the nine cities, the highest median concentration of Σ12PBDEs in household dust was found in Mianyang (295.57 ng/g), while the lowest was found in Wuxi (23.15 ng/g). BDE-71 was the most dominant congener, ranging from 42.08 % to 98.15 % of the 12 PBDE congeners among 9 cities. Three potential sources for the indoor environment were Penta-BDE, Octa-BDE commercial products, and photolytic bromine from Deca-BDEs based on the largest contribution (81.24 %). Under the moderate exposure scenario, the exposure levels through ingestion and dermal absorption for children were 7.30 × 10-1 ng/kg BW/day and 3.26 × 10-2 ng/kg BW/day, respectively. Temperature, CO2, years of residence, income, family size, household size, use of computers, heating, use of insecticide, and use of humidifiers were influential factors for PBDE concentrations in household dust. Based on the evidence of the correlation between PBDEs and these household parameters, it can be applied to reduce PBDE concentrations in household dust, which is a basis for controlling PBDEs pollution in Chinese households and protecting population health.

A New Antibody Binding Test for Potency Assessment of the Human Rabies Vaccine.

This study established a new protocol of the antibody binding test to evaluate the potency of the rabies vaccine containing the final bulk and the product. The principle of this experiment is to combine rabies vaccine with quantitative anti-rabies virus neutralizing antibody. After combination, the remaining rabies vaccine is combined with the quantitative fluorescent labeled rabies virus. After this, observe the remaining fluorescent labeled rabies virus, calculate the fluorescence area with fluorescence observation equipment, then calculate the potency of rabies vaccine by Reed and Muench method. The test results of many batches of rabies vaccine final bulk and finished products showed that the potency detected by this method was consistent with that of National Institute of Health method.

Cost-effectiveness Analysis of Dienogest Compared with Combined Oral Contraceptives after Surgery for Endometriosis.

STUDY OBJECTIVE: To assess the cost-effectiveness of different strategies, including the dienogest (DNG) and combined oral contraceptives (COC) therapy, for the prevention of endometriosis recurrence after surgery. DESIGN: A decision tree model was created. The analysis was based on data from a healthcare provider in China. Model inputs were derived from published data. The end points included incremental cost effectiveness ratio, net monetary benefit (NMB), and incremental NMB associated with prevention of recurrence. The uncertainty was assessed through one way and probabilistic sensitivity analysis. The Consolidated Health Economic Evaluation Reporting Standards 2022 checklist was used to assess quality of the reporting. SETTING: China healthcare system. PATIENTS: Individuals undergoing laparoscopic surgery for endometriosis. INTERVENTIONS: DNG vs COC. MEASUREMENTS AND MAIN RESULTS: The base case analysis showed that hormone supression via DNG resulted in 0.7493 quality-adjusted life years (QALYs) at a cost of $1625.49 compared with COC, which resulted in 0.7346 QALYs at a cost of $343.61. The incremental cost effectiveness ratio was $87 679.89 per additional QALY gained and the DNG treatment was associated with an incremental NMB of -$731.39. Probabilistic sensitivity analysis indicated that DNG is not cost-effective in most cases at a threshold consistent with World Health Organisation recommendations of $37 653/QALY. CONCLUSION: The result of our present analysis suggests that the DNG might not be cost-effective for the prevention of endometriosis recurrence after surgery in China.

Occurrence, distribution and risk assessment of antibiotics at various aquaculture stages in typical aquaculture areas surrounding the Yellow Sea.

The pollution of antibiotics commonly existed throughout the entire aquaculture process, but the residues of antibiotics at different aquaculture stages have rarely been studied. This study investigated the occurrence, distribution and risk assessment of antibiotics at different aquaculture stages (the non-aquaculture stage, the early aquaculture stage, the middle aquaculture stage, and the late aquaculture stage) in two typical marine aquaculture areas (Mahegang River and Dingzi Bay) surrounding the Yellow Sea. Fluoroquinolones and tetracyclines were commonly used antibiotics in the aquaculture of these areas with high detection frequencies (17% to 83%). Compared among four aquaculture stages, the highest concentration of antibiotics (9032.08 ng/L) in aquaculture ponds was detected at the late aquaculture stage. And the antibiotic pollution level of natural water was directly related to the aquaculture stages. Similarly, at the aquaculture stages, the detection frequency of antibiotics in sediments was higher than that at the non-aquaculture stage. Based on the correlation analysis, the concentration of main antibiotics in water showed a positive correlation with total nitrogen (p<0.05) and chlorophyll a (p<0.01), while it showed a negative correlation with salinity (p<0.01) in coastal water of the Dingzi Bay. According to the risk assessment, with the development of aquaculture stages, the selection pressure of fluoroquinolones and tetracyclines on resistant bacteria had increased. And the ecological risks caused by sulfonamides and tetracyclines to aquatic organisms had also increased markedly. Overall, this study may provide a reference for formulating regulatory policies regarding antibiotic use at different aquaculture stages.

Magnetic Resonance Imaging Combined with Histological Techniques for Dynamic Assessment of Cytotoxic Edema after Cerebral Ischemia-Reperfusion Injury.

BACKGROUND: Reperfusion therapy after ischemic cerebral stroke may cause cerebral ischemia-reperfusion injury (CIRI), and cerebral edema is an important factor that may aggravate CIRI. Our study aimed to dynamically monitor the development of early cytotoxic edema after CIRI by magnetic resonance imaging (MRI) and to validate it using multiple histological imaging methods. METHODS: Male Sprague Dawley rats were divided into sham and CIRI groups. T2-weighted imaging (T2WI) and diffusion-weighted imaging (DWI)-MRI scans were performed in the sham and CIRI groups after reperfusion. Relative apparent diffusion coefficient (rADC) values were calculated and the midline shift (MLS) was measured. A series of histological detection techniques were performed to observe changes in the cerebral cortex and striatum of CIRI rats. Correlation analysis of rADC values with aquaporin-4 (AQP4) and sodium-potassium-chloride cotransport protein 1 (Na+-K+-2Cl-- cotransporter 1; NKCC1) was performed. RESULTS: rADC values began to increase and reached a relatively low value in the cerebral cortex and striatum at 24 h after reperfusion, and the MLS reached relatively high values at 24 h after reperfusion (all p < 0.05). Hematoxylin-eosin (HE) staining showed that the nerve cells in the cortex and striatum of the sham group were regular in morphology and neatly arranged, and in the CIRI-24 h group were irregular, disorganized, and loosely structured. Using terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) staining, the number of TUNEL+ cells in the ischemic cortex and striatum in CIRI-24 h group was shown to increase significantly compared with the sham group (p < 0.05). Transmission electron microscopy showed that the perivascular astrocytic foot processes were swollen in the cortex and striatum of the CIRI-24 h group. Pearson correlation analysis demonstrated that rADC values were negatively correlated with the number of anti-glial fibrillary acidic protein (GFAP)+AQP4+ and GFAP+NKCC1+ cells of the CIRI rats. CONCLUSIONS: MRI combined with histological techniques can dynamically assess cytotoxic edema after CIRI, in a manner that is clear and intuitive for scientific researchers and clinicians, and provides a scientific basis for the application of MRI techniques for monitoring the dynamic progress of CIRI.

Exploring the Relationship between Ecosystem Services under Different Socio-Economic Driving Degrees.

The large-scale transformation of natural ecosystems to socio-economic development land types under human activities was a primary reason for the decline of regional ecosystem services. It is a key issue for regional ecosystem planning and management to reveal the relationship between ecosystem services of different land use types under different socio-economic driving degrees. However, the current related research was not in-depth. Based on the land use data of Wuhan City in 1980, 1990, 2000, 2010, and 2020, this study classified land use into three categories according to the different degrees of human activities on natural ecosystem development: the land use of a natural ecosystem (LUNE), the land use of a productive ecosystem (LUPE), and the land use of a socio-economic system (LUSE). The InVEST model was used to simulate five ecosystem services (grain yield, water yield, carbon storage, habitat quality, and water purification), and the spatio-temporal distribution and functional transformation of the three land use types were analyzed. Results showed that with the intensified urban expansion in Wuhan, the LUSE types increased to 2.7 times that of the original. However, the natural land types basically maintained a stable area, coupling with the large-scale transformation between the LUPE and LUSE types. Land use change resulted in significant spatial changes of five ecosystem services, especially carbon storage and habitat quality. The correlation analysis indicated that the five kinds of ecosystem services mainly showed a synergistic relationship, meanwhile the LUSE type denoted the most significant correlation with ecosystem services among these three category types. This study indicated that besides the protection of natural ecosystems, the LUSE type would become the key land use type in the planning and management of improving regional ecological function.

Application of a Markov chain Monte Carlo method for robust quantification in chemical exchange saturation transfer magnetic resonance imaging.

Background: Chemical exchange saturation transfer (CEST) magnetic resonance imaging can provide surrogate biomarkers for disease diagnosis. However, endogenous CEST effects are always diluted and contaminated by competing effects, which results in unwanted signal contributions that lessen the specificity of CEST to underlying biochemical exchange processes. The aim of this study was to examine a method for the accurate quantification of CEST effects. Methods: A Markov chain Monte Carlo (MCMC)-based Bayesian inference approach was proposed to estimate the exchange parameters, and CEST effects could be fitted using these estimations. This approach was tested in Bloch simulation and ischemic stroke rat experiments, and its performance was evaluated using quantification maps and numerical metrics. Results: With 12 groups of simulations, the MCMC method achieved satisfactory fittings on both 2-pool and 5-pool models. The sum of squares error values and the root mean square error of the fitted Z-spectra were smaller than 10-3, and the coefficient of determination (R-squared) values were close to 1. The corresponding CEST quantification M T R R e x C E S T spectra were also well fitted and successfully separated the mixed CEST effects. The estimated parameters showed little bias relative to the ground truth, with errors between the true and estimated values of each parameter of less than 0.5%. In the animal experiments, M T R R e x A m i d e fitted using the MCMC method showed obvious contrast between ischemic and contralateral regions at the early stage. Compared with other quantification methods, it displayed the highest contrast-to-noise ratios (3.9, 2.73, and 3.93) and the lowest coefficient of variation values (0.181, 0.2224, and 0.2897) in all three stroke periods. Conclusions: The MCMC method provided an efficient approach for parameter estimation and CEST effect quantification. The method may therefore be useful in achieving an accurate pathological diagnosis.

Investment strategy for blockchain technology in a shipping supply chain.

In the post-COVID-19 pandemic era, how to promote blockchain technology to improve the efficiency of port customs clearance and logistics transparency has become a hot research question in the shipping industry. In this paper, we investigate the value of blockchain-based vertical cooperation led by a port or a shipping company in a one-to-two shipping service competition model. A status quo scenario and two different investment scenarios led by different stakeholders are constructed, and equilibrium solutions of the Stackelberg game in three scenarios are proposed. Meanwhile, consumer surplus and social welfare under different cooperation frameworks are discussed. We find that i) investment in blockchain technology can significantly increase the profits of shipping supply chain participants. ii) From the point of view of profit, when the investment efficiency of the port and the shipping company satisfies a certain relationship, there is a balanced strategy for both parties to invest in blockchain technology. iii) The more intense the competition for the services of shipping companies, the lower the level of blockchain technology to improve the logistics capabilities of the shipping supply chain participants. iv) The port's investment in blockchain technology brings more consumer surplus and social welfare. The abovementioned findings can provide managerial insights for ports and shipping companies and present decision support for the government to formulate blockchain technology promotion policies.

Investigation of Immune Responses to Oxidation, Deamidation, And Isomerization in Therapeutic Antibodies using Preclinical Immunogenicity Risk Assessment Assays.

Product- and process- related critical quality attributes have the potential to impact pharmacokinetics, immunogenicity, potency, and safety of biotherapeutics. Among these critical quality attributes are chemical degradations, specifically oxidation, deamidation, and isomerization. These degradations can be induced by stressors such as light, pH, or temperature; they can also occur naturally under normal conditions. The immunogenicity risk of chemical degradations, particularly in the absence of aggregation, has not been thoroughly understood. In this study, model antibodies with known labile residues were stressed to induce each of the three chemical degradation classes. Aggregate-free and chemically modified antibody species were fractionalized and characterized, followed by testing in standardized and qualified preclinical immunogenicity risk assessment assays for dendritic cell internalization and presentation, monocyte activation, and pre-existing reactivity. Preclinical immunogenicity risk was assessed holistically in vitro based on changes in innate activation risk, CD4 T cell risk, and B cell risk compared to corresponding native antibody. The results of this study suggest an overall moderate increase in immune activation potential for the antibody with isomerization, with only slight increases observed in oxidized and deamidated antibodies. These findings could lend understanding to the immunogenicity risk of chemical degradations in therapeutic antibodies and therefore inform optimization engineering at particular labile residues and risk assessment under the Quality by Design framework.

Conditional effect of governance quality on the finance-environment nexus in a multivariate EKC framework: evidence from the method of moments-quantile regression with fixed-effects models.

This paper investigates the mitigating effect of governance quality on the finance-environment nexus in a multivariate EKC framework in 123 selected countries during the 1990-2017 period. We mainly employ the method of moments-quantile regression (MM-QR) with the fixed-effects model, among others. First, the MM-QR estimator reveals that financial development reduces environmental quality more significantly in countries with initially higher levels (the 75th and 90th quantiles) of CO2 emissions than in other countries (the 25th and 10th quantiles). Second, the attenuating effect of governance quality on the finance-environment nexus is more remarkable in nations with low initial levels (the 25th and 10th quantiles) of CO2 emissions. Third, we find that the marginal positive effect of financial development on CO2 emissions is smaller under a good regulatory framework than under corruption control and the rule of law, especially in the top emitters (the 75th and 90th quantiles). Fourth, unlike oil, which has a considerable negative impact on the environmental quality of the major emitters, renewable energy usage reduces CO2 emissions in countries in all quantiles, primarily in the lowest quantiles. Fifth, the findings also show that urbanization dramatically worsens environmental quality in all economies, particularly those in the lowest quantiles. Finally, we confirm that the EKC hypothesis holds in all countries across different quantiles. The study's final section discusses policy implications for sustainable development in all countries.

The influence of weather conditions on the COVID-19 epidemic: Evidence from 279 prefecture-level panel data in China.

Studying the influence of weather conditions on the COVID-19 epidemic is an emerging field. However, existing studies in this area tend to utilize time-series data, which have certain limitations and fail to consider individual, social, and economic factors. Therefore, this study aimed to fill this gap. In this paper, we explored the influence of weather conditions on the COVID-19 epidemic using COVID-19-related prefecture-daily panel data collected in mainland China between January 1, 2020, and February 19, 2020. A two-way fixed effect model was applied taking into account factors including public health measures, effective distance to Wuhan, population density, economic development level, health, and medical conditions. We also used a piecewise linear regression to determine the relationship in detail. We found that there is a conditional negative relationship between weather conditions and the epidemic. Each 1 °C rise in mean temperature led to a 0.49% increase in the confirmed cases growth rate when mean temperature was above -7 °C. Similarly, when the relative humidity was greater than 46%, it was negatively correlated with the epidemic, where a 1% increase in relative humidity decreased the rate of confirmed cases by 0.19%. Furthermore, prefecture-level administrative regions, such as Chifeng (included as "warning cities") have more days of "dangerous weather", which is favorable for outbreaks. In addition, we found that the impact of mean temperature is greatest in the east, the influence of relative humidity is most pronounced in the central region, and the significance of weather conditions is more important in the coastal region. Finally, we found that rising diurnal temperatures decreased the negative impact of weather conditions on the spread of COVID-19. We also observed that strict public health measures and high social concern can mitigate the adverse effects of cold and dry weather on the spread of the epidemic. To the best of our knowledge, this is the first study which applies the two-way fixed effect model to investigate the influence of weather conditions on the COVID-19 epidemic, takes into account socio-economic factors and draws new conclusions.