Report from the World Health Organization's immunization and vaccines-related implementation research advisory committee (IVIR-AC) meeting, virtual gathering, 26 February-1 March 2024.

The Immunization and Vaccine-related Implementation Research Advisory Committee (IVIR-AC) is the World Health Organization's key standing advisory body to conduct an independent review of research, particularly of transmission and economic modeling analyses that estimate the impact and value of vaccines. From 26th February-1st March 2024, at its first of two semi-annual meetings, IVIR-AC provided feedback and recommendations across four sessions; this report summarizes the proceedings and recommendations from that meeting. Session topics included modeling of the impact and cost-effectiveness of the R21/Matrix-M malaria vaccine, meta-analysis of economic evaluations of vaccines, a global analysis estimating the impact of vaccination over the last 50 years, and modeling the impact of different RTS,S malaria vaccine dose schedules in seasonal settings.

Artificial intelligence-based assessment of PD-L1 expression in diffuse large B cell lymphoma.

Diffuse large B cell lymphoma (DLBCL) is an aggressive blood cancer known for its rapid progression and high incidence. The growing use of immunohistochemistry (IHC) has significantly contributed to the detailed cell characterization, thereby playing a crucial role in guiding treatment strategies for DLBCL. In this study, we developed an AI-based image analysis approach for assessing PD-L1 expression in DLBCL patients. PD-L1 expression represents as a major biomarker for screening patients who can benefit from targeted immunotherapy interventions. In particular, we performed large-scale cell annotations in IHC slides, encompassing over 5101 tissue regions and 146,439 live cells. Extensive experiments in primary and validation cohorts demonstrated the defined quantitative rule helped overcome the difficulty of identifying specific cell types. In assessing data obtained from fine needle biopsies, experiments revealed that there was a higher level of agreement in the quantitative results between Artificial Intelligence (AI) algorithms and pathologists, as well as among pathologists themselves, in comparison to the data obtained from surgical specimens. We highlight that the AI-enabled analytics enhance the objectivity and interpretability of PD-L1 quantification to improve the targeted immunotherapy development in DLBCL patients.

Measuring and decomposing natural capital use in Xinjiang from a regional-industry perspective.

Accurately portraying the mechanism of the flow of natural resource consumption between regions and its impact on ecology is of crucial value in deepening the understanding of the coordinated relationship between population, resources, environment and development. Consequently, this promotes the sustainable development of the natural economy and society. Based on a regional-industrial perspective, this study used a localized three-dimensional ecological footprint model to measure and decompose natural resources in Xinjiang from 2005 to 2020. In doing so, the study clarified the supply, demand, and flow utilization of natural capital in Xinjiang, the balance of spatial and temporal allocation of resources, the coupling between economic growth and resource consumption, and the coordination between industrial structure and ecological environment. The results showed that (1) Xinjiang's per capita ecological deficit grew from 2.096 to 11.667 in 2005-2020. Moreover, the energy footprint was a decisive part of the ecological deficit throughout the study period. Furthermore, the trend of increased ecological pressure was higher in northern and eastern Xinjiang than in southern Xinjiang. (2) The overall Gini coefficient of Xinjiang's ecological carrying capacity was at the critical value of spatial equilibrium (0.4), with differences between the groups: Northern & Southern Xinjiang > Northern & Eastern Xinjiang > Eastern & Southern Xinjiang. The reasons for this inter-regional economic disparity are related to fiscal expenditure/GDP, level of urbanization, and regional industrial output. Overall, the decoupling relationship between environmental pressures and economic growth was optimistic. (3) From an industrial perspective, the levels of industrial structural efficiency and the industrial ecological harmony index were still relatively low, but the overall trend was on the rise. (4) Resource endowment, economic development, consumption structure, and population had significant driving effects on the ecological footprint, whereas environmental protection, science, and technology could inhibit its growth to a certain extent. This study aimed to provide an in-depth analysis of the current situation and problems of natural resource use in Xinjiang and provide theoretical and practical references for sustainable development in the region.

Life cycle assessment for evaluation of novel solvents and technologies: A case study of flavonoids extraction from Ginkgo biloba leaves.

Innovative solvents such as deep eutectic solvents (DESs) and process intensification technologies assisted by ultrasound have been demonstrated to be promising pathways for enhancing solid-liquid extraction. Nevertheless, quantitative and systematic knowledge of their environmental impact is still limited. In this work, a case study of flavonoids extraction from Ginkgo biloba leaves was evaluated by using life cycle assessment (LCA) for comparison of three extraction scenarios. The first used DES as extractant (DESE), and the other two adopted ethanol, including heat reflux extraction (HRE), and ultrasound-assisted extraction (UAE). Among eight key midpoints investigated, all these from UAE were 10.0 %-80.0 % lower than from DESE and HRE except water consumption. The UAE was the eco-friendliest option due to its higher extraction yield, shorter duration and lower solvent consumption. The DESE exhibited the lowest water consumption, the highest freshwater ecotoxicity and human carcinogenic toxicity, while HRE had the highest impacts for the other 6 midpoints. Moreover, solvent production was the key contributor for all the categories. The standardized sensitivity analysis showed that the overall environmental footprint can be further decreased by 15.4 % for DESE pathways via substituting choline chloride/glycerine with choline chloride/ethylene glycol. Furthermore, all pathways using DESs had higher standardized impacts than those employing ethanol from sugarcane or wood. Replacing ethanol from maize with other feedstocks can significantly lessen the overall impacts, among which the UAE using ethanol from sugarcane demonstrated the least environmental impacts. The promotion of DESs as "green and sustainable" alternative to traditional solvents requires careful consideration.

Precision co-composting of multi-source organic solid wastes provide a sustainable waste management strategy with high eco-efficiency: a life cycle assessment.

With the increase of organic solid wastes (OSWs), current waste management practices, such as landfill, incineration, and windrow composting, have shown weaknesses in both resource recycling and environmental protection. Co-composting has been used to achieve nutrient and carbon recycling but is accused of high ammonia emission and low degradation efficiency. Therefore, this study developed a precision co-composting strategy (S3, which adds functional bacteria generated from food processing waste to a co-composting system) and compared it with the current OSW treatment strategy (S1) and traditional co-composting strategy (S2) from a life cycle assessment (LCA) perspective. The results showed that compared with S1, the eco-efficiency increased by 31.3% due to the higher economic profit of S2 but did not directly reduce the environmental cost. The addition of bacterial agents reduced ammonia emissions and shortened composting time, so compared with S1 and S2, the environmental cost of S3 was reduced by 37.9 and 43.6%, while the economic profit increased by 79.8 and 24.4%, respectively. The changes in environmental costs and economic benefits resulted in a huge improvement of S3's eco-efficiency, which was 189.6 and 121.7% higher than S1 and S2. Meanwhile, the adoption of S3 at a national scale in China could reduce the emission of 1,4-dichlorobenzene by 99.9% compared with S1 and increase profits by 6.58 billion USD per year. This study proposes a novel approach that exhibits high eco-efficiency in the treatment of OSWs.

Food Insecurity and Premature Mortality and Life Expectancy in the US.

Importance: Food insecurity has been linked to multiple causes of disease and premature mortality; however, its association with mortality by sex and across racial and ethnic groups remains unknown in the US. Objective: To investigate the associations of the entire range of food security with all-cause premature mortality and life expectancy across racial and ethnic and sex groups in US adults. Design, Setting, and Participants: This cohort study included adults (aged ≥18 years) who participated in the National Health and Nutrition Examination Survey from 1999 to 2018, with linkage to the National Death Index through December 31, 2019. Data analysis was performed from August to November 2023. Exposures: Levels of food security were assessed with the US Department of Agriculture Adult Food Security Survey Module (full, marginal, low, and very low). Main Outcomes and Measures: All-cause premature mortality (death that occurs before age 80 years) and life expectancy. Results: The study included 57 404 adults (weighted mean [SE] age, 46.0 [0.19] years; 51.8% female; 12 281 Black individuals [21.4%]; 10 421 Mexican individuals [18.2%]; 4627 Other Hispanic individuals [8.1%]; 24 817 White individuals [43.2%]; and 5258 individuals of other races, including multiracial [9.2%]). During a median (IQR) of 9.3 (5.0-14.3) years of follow-up, 4263 premature deaths were documented. Compared with the full food security group, the adjusted hazard ratios were 1.50 (95% CI, 1.31-1.71), 1.44 (95% CI, 1.24-1.68), and 1.81 (95% CI, 1.56-2.10) across marginal, low, and very low food security groups, respectively (P < .001 for trend). The corresponding life expectancy at age 50 years in each group was 32.5 (95% CI, 32.4-32.6), 29.9 (95% CI, 28.9-30.9), 30.0 (95% CI, 28.9-31.0), and 28.0 (95% CI, 26.8-29.2) years. Equivalently, adults with marginal, low, or very low food security lived on average 2.6 (95% CI, 1.5-3.7), 2.5 (95% CI, 1.4-3.7), or 4.5 (95% CI, 3.2-5.8) fewer years at age 50 years, respectively, compared with those with full food security. The associations appeared to be stronger in women than in men (hazard ratios comparing very low food security with full food security, 2.29 [95% CI, 1.83-2.86] in women and 1.46 [95% CI, 1.19-1.78] in men; P = .009 for interaction) and stronger in White adults than in Black adults (hazard ratios comparing very low food security with full food security, 2.07 [95% CI, 1.70-2.53] in White adults and 1.33 [95% CI, 1.01-1.75] in Black adults; P < .001 for interaction) or in Hispanic adults (hazard ratios comparing very low food security with full food security, 1.06 [95% CI, 0.71-1.58]; P < .001 for interaction). Conclusions and Relevance: In this cohort study, although the association of food security and life expectancy varied across sex and racial and ethnic groups, overall, lower levels of food security were associated with a higher risk of premature mortality and a shorter life expectancy. The findings of this study highlight the potential importance of improving food security in promoting population health and health equity.

Cost-of-illness of gastroenteritis caused by rotavirus in Chinese children less than 5 years.

Acute gastroenteritis (AGE) caused by rotavirus (RV) remains a public health issue in China. To accelerate the mass rotavirus vaccination, it is important to inform the policy maker, and the public of the economic burden caused by rotavirus infection. A meta-analysis was conducted applying standardized algorithms. Articles published before January 1, 2023, in English and Chinese were searched through PubMed, CNKI, and WanFang Data. Studies with cost analysis of RV AGE were included. A random-effects model was applied to synthesize the total cost of RV AGE from the societal perspective. A prospective survey aimed to measure the cost of RV AGE was conducted in 2021 and 2022 in Shaoxing city, Zhejiang province, that can represent the developed region. The cost data was applied as deviation indicator, in comparison with the pooled estimate generated from meta-analysis. Totally 286 articles were identified, and eventually 12 studies were included. The pooled total social cost of RV AGE was US$282.1 (95%CI: US$213.4-350.7). The pooled private cost of RV AGE was US$206.4 (95%CI: US$155.2-257.5). RV AGE hospitalized and RV AGE incurred in developed regions caused remarkable higher burden (US$631.2 [95%CI: US$512.6-749.8], and US$333.6 [95%CI: US$234.1-433.2] respectively), compared to RV AGE treated at outpatient, and incurred in less developed regions. Our study demonstrates that RV AGE causes a significant economic burden in China. Given the promising effectiveness and highly cost-effective, introduction of rotavirus vaccines in national immunization programs could substantially reduce the economic burden in China.

Global, regional, and national burden of liver cancer due to non-alcoholic steatohepatitis, 1990-2019: a decomposition and age-period-cohort analysis.

BACKGROUND: Identifying past temporal trends in non-alcoholic steatohepatitis (NASH)-associated liver cancer (NALC) can increase public awareness of the disease and facilitate future policy development. METHODS: Annual deaths and age-standardized death rates (ASDR) for NALC from 1990 to 2019 were collected from the Global Burden of Disease (GBD) 2019 study. The long-term trend and the critical inflection of mortality of NALC were detected by Joinpoint analysis. Age-period-cohort analysis was employed to evaluate the effects of age, period, and cohort. Last, decomposition analysis was used to reveal the aging and population growth effects for NALC burden. RESULTS: Between 1990 and 2019, the ASDR of NALC witnessed an overall declining trend on a global scale, with a decrease in females and a stable trend in males. However, the global ASDR demonstrated a significant upward trend from 2010 to 2019. Southern sub-Saharan Africa and Southeast Asia have the highest NALC burdens, while high socio-demographic index (SDI) region experienced the fastest escalation of NALC burdens over 30 years. The decomposition analysis revealed that population growth and aging were the primary catalysts behind the increase in global NALC deaths. Age-period-cohort analyses showed that NALC mortality declined the fastest among females aged 40-45 years in high SDI region, accompanied by a deteriorating period effect trend during the period of 2010-2019. CONCLUSION: The global absolute deaths and ASDR of NALC have witnessed a rise in the past decade, with populations exhibiting considerable disparities based on sex, age, and region. Population growth, aging, and metabolism-related factors were the main factors behind the increase in global NALC deaths.

Assessment of the shift in the precipitation-streamflow relationship influenced by multiyear drought, Yellow River basin, China.

Climate change intensification (e.g., long-term drought) dramatically triggers catchment property changes, which introduces larger uncertainties for describing catchment hydrological behavior. In this study, hydrological behavior responses to multiyear drought were explored, and then causes were explained. The hydrological response to multiyear drought was explored using a magnitude of shift (M) in describing the relationship between precipitation (P) and streamflow (Q) in different catchment states, and a novel method, the trigonometric function decomposition method within the Budyko framework (the TFD method), was applied to assess the causes of Q changes. Several conclusions can be drawn: (i) multiyear drought mainly caused insignificant and significant upward (p < 0.05) changes in the P-Q relationship among 95.45 % of the studied catchments (p < 0.05); (ii) more server drying, lower leaf area index (LAI) and slope can induce a higher M via multiyear drought. In particular, catchment water storage, indicated by the deep soil layer in the Loess Plateau, can effectively mitigate the Q reduction and resulted in a 77.27 % (17/22) upward shift compared with the expected Q reduction; (iii) an asymmetric effect was caused by a multiyear P deficit, that is, (P-Q)/P increase and catchment property parameter (n) decrease were induced by the increases in ratio between potential evapotranspiration and P (Ep/P), suggesting that the catchment properties can mitigate the Q reduction; and (iv) catchment properties had negative effects on the Q reduction (7.76 mm a-1), and partially offset Q reduction (-21.32 mm a-1) resulted from climate change during the multiyear drought period. All of these results indicated that multiyear drought triggered Q reduction, while catchment behavior in the changeable induction mechanism induced a nonlinear Q response to P reduction, which is important for accurate Q projections and appropriate adaptation strategies for droughts.

Predicting cardiovascular risk in a Chinese primary Sjögren's syndrome population: development and assessment of a predictive nomogram.

Background: Patients with primary Sjögren's syndrome (pSS) are at increased risk of cardiovascular morbidity as compared with the general population. Objectives: A retrospective study on 349 Chinese patients with pSS was conducted to identify potential risk factors for cardiovascular events and develop a cardiovascular risk nomogram. Design: This is a retrospective observational study. Methods: The study included 349 patients who were diagnosed with pSS at Tongji Hospital, School of Medicine, Tongji University, China from January 2010 to March 2022. The least absolute shrinkage and selection operator (LASSO) was used to select features for the cardiovascular risk model. The features selected in LASSO were used to build the cardiovascular risk model in a multivariate logistic regression analysis. C-index, receiver operating characteristic (ROC) curve, calibration plot, and decision curve analysis were used to assess the predictive model. Internal validation was performed by bootstrapping. Results: Sex, joint pain as an initial symptom, dry mouth, oral ulcers, dental caries, Raynaud's phenomenon, fatigue, diabetes, elevated thyroid-stimulating hormone (TSH) level, and elevated systolic blood pressure were included in the nomogram for the prediction of cardiovascular risk. Our model had good discrimination (C-index: 0.824, 95% confidence interval: 0.712-0.936) and good calibration (C-index in the interval validation: 0.8). Decision curve analysis indicated that our nomogram demonstrated clinical usefulness for intervention in a cardiovascular disease possibility threshold of 3%. Conclusion: The cardiovascular risk nomogram incorporating sex, initial joint pain, dry mouth, oral ulcer, dental caries, Raynaud's phenomenon, fatigue, diabetes, elevated TSH, and systolic blood pressure could be used in the prediction of cardiovascular risk in patients with pSS and the guidance of further treatment.

SACTI model in prediction and assessment of large scale natural draft cooling tower environmental impact of nuclear power plant.

Large Scale Natural Draft Cooling Tower has become a hot topic in China because it is an important part of the nuclear power plant, and its environmental impacts include shading, solar energy loss, water deposition and salt deposition. In China, there is no built large-scale natural draft cooling tower of nuclear power plant. Therefore, model prediction becomes an effective way to solve this problem. This paper introduces the basic principles and structure of SACTI (Seasonal and Annual Cooling Tower Impact) model. SACTI is a cooling tower assessment model developed by Argonne National Laboratory, USA. A comparative case study between China's Pengze Nuclear Power Plant and the US Amos Power Plant is also presented. Calculations were carried out for the Pengze and Amos power plants, and the results showed that the maximum value of salt deposition at the Pengze plant was about 166.5 kg/(km2-month) at a distance of 800 m from the cooling tower. The maximum value of salt deposition at the Amos plant was about 92.85 kg/(km2-month) at a distance of 600 m from the cooling tower. Conclusions show that the research work can provide a useful solution in future work, the simulation results of the SACTI model have a potential mean in the absence of monitoring data. This research provides a way to generate simulation data through SACTI program in the design process of nuclear power plant cooling tower, and designers can use these data to determine how the cooling tower will affect the natural environment and manage within an appropriate range to reduce the impact on the environment.

Discussion of "The Asymmetric Impact of COVID-19: A Novel Approach to Quantifying Financial Distress across Industries".

The COVID-19 pandemic crisis and the associated lockdown measures have exerted significantly adverse effects on corporate sectors globally. Archanskaia et al. (2023) provide a novel empirical strategy to timely assess corporate financial distress in the EU. The contribution is two-fold. First, this paper's notion of financial distress considers both the equity position and corporate indebtedness. Second, the methodology proposed in this paper allows the authors to estimate corporate financial distress in the EU at a highly granular level and link micro-level simulations to sectoral macroeconomic outcomes. The methodology employed by Archanskaia et al. (2023) consists of three steps. First, the authors apply a nowcasting model to acquire monthly industrial turnover data. Second, they feed the obtained monthly industrial turnover into a profit-generating process via an accounting identity to estimate monthly firm profits at the firm level. Third, the authors use the estimated firm profits with a snapshot of information on pre-existing liquid assets to deduce the firm-level liquidity needs and the depletion of equity through the focus period during COVID-19. These estimated results on firm equity position and indebtedness enable the authors to quantity corporate financial distress in the EU via various angles (e.g., country-level heterogeneity, industry heterogeneity, and the targeting of COVID support policies). The primary advantage of this approach is that it deals with large datasets at the granular level and produces firm-level results almost in real-time. Therefore, it can help policymaking track the effects of crises over time. However, one can quickly critique this three-step approach for its susceptibility to the usual Lucas critique. That said, since the objective here is to estimate firm-level financial distress, a large structural model being more or less aggregate in nature, though able to mitigate the Lucas critique concern, will encounter significant challenges in estimating firm-level results with the requisite level of granularity offered by the available data. Therefore, I broadly concur with the authors' position that 'the specific contribution of this paper consists in striking a better balance between the need to carry out a multi-country evaluation of the pandemic's effects on industrial activity in a strongly integrated region like the EU and the difficulty of capturing time, industry, and country variation in turnover with sufficient granularity.'

Breaking the traditional: a survey of algorithmic mechanism design applied to economic and complex environments.

The mechanism design theory can be applied not only in the economy but also in many fields, such as politics and military affairs, which has important practical and strategic significance for countries in the period of system innovation and transformation. As Nobel Laureate Paul said, the complexity of the real economy makes it difficult for "Unorganized Markets" to ensure supply-demand balance and the efficient allocation of resources. When traditional economic theory cannot explain and calculate the complex scenes of reality, we require a high-performance computing solution based on traditional theory to evaluate the mechanisms, meanwhile, get better social welfare. The mechanism design theory is undoubtedly the best option. Different from other existing works, which are based on the theoretical exploration of optimal solutions or single perspective analysis of scenarios, this paper focuses on the more real and complex markets. It explores to discover the common difficulties and feasible solutions for the applications. Firstly, we review the history of traditional mechanism design and algorithm mechanism design. Subsequently, we present the main challenges in designing the actual data-driven market mechanisms, including the inherent challenges in the mechanism design theory, the challenges brought by new markets and the common challenges faced by both. In addition, we also comb and discuss theoretical support and computer-aided methods in detail. This paper guides cross-disciplinary researchers who wish to explore the resource allocation problem in real markets for the first time and offers a different perspective for researchers struggling to solve complex social problems. Finally, we discuss and propose new ideas and look to the future.

ShrewdAttack: Low Cost High Accuracy Model Extraction.

Machine learning as a service (MLaaS) plays an essential role in the current ecosystem. Enterprises do not need to train models by themselves separately. Instead, they can use well-trained models provided by MLaaS to support business activities. However, such an ecosystem could be threatened by model extraction attacks-an attacker steals the functionality of a trained model provided by MLaaS and builds a substitute model locally. In this paper, we proposed a model extraction method with low query costs and high accuracy. In particular, we use pre-trained models and task-relevant data to decrease the size of query data. We use instance selection to reduce query samples. In addition, we divided query data into two categories, namely low-confidence data and high-confidence data, to reduce the budget and improve accuracy. We then conducted attacks on two models provided by Microsoft Azure as our experiments. The results show that our scheme achieves high accuracy at low cost, with the substitution models achieving 96.10% and 95.24% substitution while querying only 7.32% and 5.30% of their training data on the two models, respectively. This new attack approach creates additional security challenges for models deployed on cloud platforms. It raises the need for novel mitigation strategies to secure the models. In future work, generative adversarial networks and model inversion attacks can be used to generate more diverse data to be applied to the attacks.

Biosimilarity Assessment of the Biosimilar Teriparatide Candidate and the Reference Drug in Healthy Subjects.

SAL001, a recombinant form of parathyroid hormone, is a biosimilar drug to teriparatide and is planned to be used in osteoporosis treatment. A single-dose, randomized, open-label, 2-way crossover trial was conducted in healthy subjects to compare the pharmacokinetics (PK) and safety between SAL001 and the reference drug. Sixty-four subjects were enrolled in the study, and 61 subjects completed the study. In each period, 20 µg of the test or reference formulation was administered subcutaneously. SAL001 was administered by autoinjector pen, whereas the reference drug was administered by a self-matched injection pen. Serial blood samples were obtained for the analyses of PK and serum calcium concentration. Geometric mean ratios with 90%CIs for the maximum plasma concentration (Cmax ) and area under the plasma concentration-time curve (AUC) were estimated. The safety of these 2 formulations was also evaluated. Overall, the 90%CIs for the geometric mean ratios of Cmax , AUC from time 0 to the last quantifiable time point, and AUC from time 0 extrapolated to infinity of the test or reference product were within 80.0%-125.0% of biosimilarity criteria. Other PK parameters, serum calcium concentration, and safety profiles had no significant differences between the 2 formulations. SAL001 demonstrated PK similarity to the reference drug, and the serum calcium concentration and safety profiles of SAL001 were also considered comparable to the reference drug.

Optimization of initial dose regimen of tacrolimus in paediatric lung transplant recipients based on Monte Carlo simulation.

WHAT IS KNOWN AND OBJECTIVES: The initial tacrolimus dose regimen in paediatric lung transplant recipients is unknown. The present study optimized the initial tacrolimus dose regimen for paediatric lung transplant recipients. METHODS: This study was based on a published population pharmacokinetic model of tacrolimus in lung transplant recipients and used Monte Carlo simulations to recommend an initial dose regimen of tacrolimus in paediatric lung transplant recipients. RESULTS: Without voriconazole, the tacrolimus doses recommended for paediatric lung transplant recipients who were not CYP3A5*1 carriers were 0.02, 0.03, and 0.04 mg/kg/day, split into two doses, for weights of 10-16, 16-30, and 30-40 kg, respectively. For paediatric lung transplant recipients who were CYP3A5*1 carriers, the tacrolimus doses of 0.03, 0.04, 0.05, and 0.06 mg/kg/day, split into two doses, were recommended for weights of 10-16, 16-25, 25-30, and 30-40 kg, respectively. With voriconazole, the tacrolimus dose recommended for paediatric lung transplant recipients who were not CYP3A5*1 carriers was 0.02 mg/kg/day, split into two doses, for weights of 10-40 kg. For paediatric lung transplant recipients who were CYP3A5*1 carriers, tacrolimus doses of 0.02 and 0.03 mg/kg/day, split and two doses, were recommended for weights of 10-24 and 24-40 kg, respectively. WHAT IS NEW AND CONCLUSIONS: This study developed tacrolimus dose regimens for the first time for paediatric lung transplant recipients using Monte Carlo simulation and optimized initial dosage in paediatric lung transplant recipients.

Modeling and Analyzing the Impact of the Internet of Things-Based Industry 4.0 on Circular Economy Practices for Sustainable Development: Evidence From the Food Processing Industry of China.

The Industry 4.0 concept proposes that new cutting-edge technologies, such as the Internet of Things (IoT), will grow. The acceptance of IoT in the circular economy (CE) is still in its infancy, despite its enormous potential. In the face of growing environmental affairs, IoT based Industry 4.0 technologies are altering CE practices and existing business models, according to the World Economic Forum. This research investigates the function of IoT-based Industry 4.0 in circular CE practices, as well as their impact on economic and environmental performance, which in turn influences overall organizational performance. China-based enterprises provide information for the study, which includes data from 300 companies. Utilizing a structural equation modeling framework known as partial least squares structural equation modeling (PLS-SEM). The major findings are presented in the study: (I) the IoT significantly improves the activities of the CE; (II) the IoT significantly improves the practices of the CE; and (III) the IoT meaningfully advances the practices of CE (green manufacturing, circular design, remanufacturing, and recycling). Moreover, the findings shows that environmentally friendly business practices help enhance environmental performance of firm, while also stimulating their economic performance; and improved environmental performance has a significant positive influence on firm performance. This research lays the groundwork for contributing nations/companies to attain economic and long-term sustainability goals at the same time by incorporating IoT-based Industry 4.0 technology into CE practices.

Diet structure and academic achievement of children from difficult families: a cross-sectional study of Chinese children.

OBJECTIVES: Welfare policy focuses on vulnerable populations, such as children with difficult family backgrounds. Education is a crucial way to reduce poverty. This study explored the relationship between children's diet structure and academic achievement and compared these across different family backgrounds. DESIGN: A cross-sectional study was conducted to survey the health status of children from difficult families based on a random sampling method in 2018. Survey data were collected from children and their guardians with a questionnaire. A multi-sample latent class model and an ordinal logistic model were applied for data analysis. SETTING: This study was conducted in 31 provinces nationwide. Two provinces in the Central (Shandong and Jiangxi), Eastern (Hebei and Henan) and Western (Chongqing and Shanxi) regions and one province in the Northeast (Liaoning) were selected considering different stratum of economic development. PARTICIPANTS: A total of 2099 children with difficult family backgrounds and 666 children from ordinary families were surveyed. RESULTS: The dietary structure of children from ordinary families was significantly better than that of children with difficult or unstable family backgrounds ([Formula: see text] =9.178, p<0.01). Children from difficult families had an intake of dairy products and fruits below dietary standards. The difference in academic achievement between children in the balanced and deprived groups was statistically significant (OR=0.640, 95% CI 0.429 to 0.955). Other determinants of the academic achievement of children in difficult families were parents' education level (OR=1.331, 95% CI 1.162 to 1.525), family economic status (OR=0.835, 95% CI 0.748 to 0.932) and parents' academic concern (OR=0.373, 95% CI 0.252 to 0.553). CONCLUSIONS: To address the differences between children from difficult families and ordinary families, policymakers should develop support policies for difficult children, guide the formation of a reasonable dietary structure. Besides, enhancing family closeness and fostering family nurturing behaviours are the keys to promote the good academic development of children from difficult families.

Advanced composting technologies promotes environmental benefits and eco-efficiency: A life cycle assessment.

Growing demand for intensive animal farms and increased public awareness of environmental friendliness, have led to continuous iteration and refinement of the initially crude composting technology. However, the impact of the composting facility and energy input on eco-efficiency is limited. In this study, a LCA approach was conducted to investigate the eco-efficiency of four widely applied composting strategies: static heaps (SH), windrow composting (WC), membrane-covered composting (MC) and reactor composting (RC). The results showed that the environmental benefits of RC's were decreased by 11.3%, 21.7%, and 6.5% compared to SH, WC, and MC, respectively. Advanced composting technologies didn't substantially reduce direct economic costs, however, the eco-efficiency of RC was increased by 296.9%, 54.7%, and 87.6% compared to SH, WC, and MC, respectively. Overall, the results demonstrate that RC is a promising solution with high ecological efficiency that can contribute to the sustainable development of intensified livestock production.

Disease Burden and Attributable Risk Factors of Ovarian Cancer From 1990 to 2017: Findings From the Global Burden of Disease Study 2017.

Aim: We aimed to estimate the disease burden and risk factors attributable to ovarian cancer, and epidemiological trends at global, regional, and national levels. Methods: We described ovarian cancer data on incidence, mortality, and disability-adjusted life-years as well as age-standardized rates from 1990 to 2017 from the Global Health Data Exchange database. We also estimated the risk factors attributable to ovarian cancer deaths and disability-adjusted life-years. Measures were stratified by region, country, age, and socio-demographic index. The estimated annual percentage changes and age-standardized rates were calculated to evaluate temporal trends. Results: Globally, ovarian cancer incident, death cases, and disability-adjusted life-years increased by 88.01, 84.20, and 78.00%, respectively. However, all the corresponding age-standardized rates showed downward trends with an estimated annual percentage change of -0.10 (-0.03 to 0.16), -0.33 (-0.38 to -0.27), and -0.38 (-0.32 to 0.25), respectively. South and East Asia and Western Europe carried the heaviest disease burden. The highest incidence, deaths, and disability-adjusted life-years were mainly in people aged 50-69 years from 1990 to 2017. High fasting plasma glucose level was the greatest contributor in age-standardized disability-adjusted life-years rate globally as well as in all socio-demographic index quintiles and most Global Disease Burden regions. Other important factors were high body mass index and occupational exposure to asbestos. Conclusion: Our study provides valuable information on patterns and trends of disease burden and risk factors attributable to ovarian cancer across age, socio-demographic index, region, and country, which may help improve the rational allocation of health resources as well as inform health policies.