Consolidated Health Economic Evaluation Reporting Standards for Interventions That Use Artificial Intelligence (CHEERS-AI).

OBJECTIVES: Economic evaluations (EEs) are commonly used by decision makers to understand the value of health interventions. The Consolidated Health Economic Evaluation Reporting Standards (CHEERS 2022) provide reporting guidelines for EEs. Healthcare systems will increasingly see new interventions that use artificial intelligence (AI) to perform their function. We developed Consolidated Health Economic Evaluation Reporting Standards for Interventions that use AI (CHEERS-AI) to ensure EEs of AI-based health interventions are reported in a transparent and reproducible manner. METHODS: Potential CHEERS-AI reporting items were informed by 2 published systematic literature reviews of EEs and a contemporary update. A Delphi study was conducted using 3 survey rounds to elicit multidisciplinary expert views on 26 potential items, through a 9-point Likert rating scale and qualitative comments. An online consensus meeting was held to finalize outstanding reporting items. A digital health patient group reviewed the final checklist from a patient perspective. RESULTS: A total of 58 participants responded to survey round 1, 42, and 31 of whom responded to rounds 2 and 3, respectively. Nine participants joined the consensus meeting. Ultimately, 38 reporting items were included in CHEERS-AI. They comprised the 28 original CHEERS 2022 items, plus 10 new AI-specific reporting items. Additionally, 8 of the original CHEERS 2022 items were elaborated on to ensure AI-specific nuance is reported. CONCLUSIONS: CHEERS-AI should be used when reporting an EE of an intervention that uses AI to perform its function. CHEERS-AI will help decision makers and reviewers to understand important AI-specific details of an intervention, and any implications for the EE methods used and cost-effectiveness conclusions.

A Blueprint for Multi-use Disease Modeling in Health Economics: Results from Two Expert-Panel Consultations.

BACKGROUND: The current use of health economic decision models in HTA is mostly confined to single use cases, which may be inefficient and result in little consistency over different treatment comparisons, and consequently inconsistent health policy decisions, for the same disorder. Multi-use disease models (MUDMs) (other terms: generic models, whole disease models, disease models) may offer a solution. However, much is uncertain about their definition and application. The current research aimed to develop a blueprint for the application of MUDMs. METHODS: We elicited expert opinion using a two-round modified Delphi process. The panel consisted of experts and stakeholders in health economic modelling from various professional backgrounds. The first questionnaire concerned definition, terminology, potential applications, issues and recommendations for MUDMs and was based on an exploratory scoping review. In the second round, the panel members were asked to reconsider their input, based on feedback regarding first-round results, and to score issues and recommendations for priority. Finally, adding input from external advisors and policy makers in a structured way, an overview of issues and challenges was developed during two team consensus meetings. RESULTS: In total, 54 respondents contributed to the panel results. The term 'multi-use disease models' was proposed and agreed upon, and a definition was provided. The panel prioritized 10 potential applications (with comparing alternative policies and supporting resource allocation decisions as the top 2), while 20 issues (with model transparency and stakeholders' roles as the top 2) were identified as challenges. Opinions on potential features concerning operationalization of multi-use models were given, with 11 of these subsequently receiving high priority scores (regular updates and revalidation after updates were the top 2). CONCLUSIONS: MUDMs would improve on current decision support regarding cost-effectiveness information. Given feasibility challenges, this would be most relevant for diseases with multiple treatments, large burden of disease and requiring more complex models. The current overview offers policy makers a starting point to organize the development, use, and maintenance of MUDMs and to support choices concerning which diseases and policy decisions they will be helpful for.

A literature review of quality assessment and applicability to HTA of risk prediction models of coronary heart disease in patients with diabetes.

This literature review had two objectives: to identify models for predicting the risk of coronary heart diseases in patients with diabetes (DM); and to assess model quality in terms of risk of bias (RoB) and applicability for the purpose of health technology assessment (HTA). We undertook a targeted review of journal articles published in English, Dutch, Chinese, or Spanish in 5 databases from 1st January 2016 to 18th December 2022, and searched three systematic reviews for the models published after 2012. We used PROBAST (Prediction model Risk Of Bias Assessment Tool) to assess RoB, and used findings from Betts et al. 2019, which summarized recommendations and criticisms of HTA agencies on cardiovascular risk prediction models, to assess model applicability for the purpose of HTA. As a result, 71 % and 67 % models reporting C-index showed good discrimination abilities (C-index >= 0.7). Of the 26 model studies and 30 models identified, only one model study showed low RoB in all domains, and no model was fully applicable for HTA. Since the major cause of high RoB is inappropriate use of analysis method, we advise clinicians to carefully examine the model performance declared by model developers, and to trust a model if all PROBAST domains except analysis show low RoB and at least one validation study conducted in the same setting (e.g. country) is available. Moreover, since general model applicability is not informative for HTA, novel adapted tools may need to be developed.

Tools for assessing quality of studies investigating health interventions using real-world data: a literature review and content analysis.

OBJECTIVES: We aimed to identify existing appraisal tools for non-randomised studies of interventions (NRSIs) and to compare the criteria that the tools provide at the quality-item level. DESIGN: Literature review through three approaches: systematic search of journal articles, snowballing search of reviews on appraisal tools and grey literature search on websites of health technology assessment (HTA) agencies. DATA SOURCES: Systematic search: Medline; Snowballing: starting from three articles (D'Andrea et al, Quigley et al and Faria et al); Grey literature: websites of European HTA agencies listed by the International Network of Agencies for Health Technology Assessment. Appraisal tools were searched through April 2022. ELIGIBILITY CRITERIA FOR SELECTING STUDIES: We included a tool, if it addressed quality concerns of NRSIs and was published in English (unless from grey literature). A tool was excluded, if it was only for diagnostic, prognostic, qualitative or secondary studies. DATA EXTRACTION AND SYNTHESIS: Two independent researchers searched, screened and reviewed all included studies and tools, summarised quality items and scored whether and to what extent a quality item was described by a tool, for either methodological quality or reporting. RESULTS: Forty-nine tools met inclusion criteria and were included for the content analysis. Concerns regarding the quality of NRSI were categorised into 4 domains and 26 items. The Research Triangle Institute Item Bank (RTI Item Bank) and STrengthening the Reporting of OBservational studies in Epidemiology (STROBE) were the most comprehensive tools for methodological quality and reporting, respectively, as they addressed (n=20; 17) and sufficiently described (n=18; 13) the highest number of items. However, none of the tools covered all items. CONCLUSION: Most of the tools have their own strengths, but none of them could address all quality concerns relevant to NRSIs. Even the most comprehensive tools can be complemented by several items. We suggest decision-makers, researchers and tool developers consider the quality-item level heterogeneity, when selecting a tool or identifying a research gap. OSF REGISTRATION NUMBER: OSF registration DOI (https://doi.org/10.17605/OSF.IO/KCSGX).

Perspectives on how to build bridges between regulation, health technology assessment and clinical guideline development: a qualitative focus group study with European experts.

OBJECTIVE: Improving synergy among regulation, health technology assessment (HTA) and clinical guideline development is relevant as these independent processes are building on shared evidence-based grounds. The two objectives were first to assess how convergence of evidentiary needs among stakeholders may be achieved, and second, to determine to what extent convergence can be achieved. DESIGN: Qualitative study using eight online dual-moderator focus groups. SETTING: Discussions had a European focus and were contextualised in four case studies on head and neck cancer, diabetes mellitus, multiple sclerosis and myelodysplastic syndromes. PARTICIPANTS: Forty-two experienced (over 10 years) European regulators, HTA representatives and clinicians participated in the discussion. INTERVENTIONS: Participants received information on the case study and research topic in advance. An introductory background presentation and interview guide for the moderators were used to steer the discussion. RESULTS: Convergence may be achieved through improved communication institutionalised in multistakeholder early dialogues, shared definitions and shared methods. Required data sets should be inclusive rather than aligned. Deliberation and decision-making should remain independent. Alignment could be sought for pragmatic clinical trial designs and patient registries. Smaller and lower-income countries should be included in these efforts. CONCLUSION: Actors in the field expressed that improving synergy among stakeholders always involves trade-offs. A balance needs to be found between the convergence of processes and the institutional remits or geographical independence. A similar tension exists between the involvement of more actors, for example, patients or additional countries, and the level of collaboration that may be achieved. Communication is key to establishing this balance.

Factors influencing the satisfaction of community senior care services in China: an analysis based on an extended Anderson model.

Community-based senior care, as a convenient and promising care model, has gradually been accepted by the public. However, community services developed to facilitate older adults often fail to achieve the expected effect. With the fast-growing aging population in China, the problems of underutilization and low service satisfaction of senior care facilities need to be resolved urgently. In this study, we further developed an extended Anderson behavior model by incorporating social psychological factors, and the vertical and horizontal fairness perceptions. In addition, a binary logistic regression model was used to analyze factors affecting the satisfaction of older adults in life care services, health care services, and mental and spiritual comfort services. The study used data from a survey of 322 urban area seniors in Shaanxi Province. The results showed that factors influencing older adults' satisfaction of different service categories are different. Moreover, with the addition of the social psychological factors, we observed that the vertical fairness perception of the survey respondents affected their satisfaction of senior care services significantly more than the horizontal fairness perception.

Cost-Effectiveness of SGLT2 Inhibitors in a Real-World Population: A MICADO Model-Based Analysis Using Routine Data from a GP Registry.

OBJECTIVE: Sodium-glucose cotransporter 2 inhibitors (SGLT2i) have been shown to reduce the risk of cardiovascular complications, which largely drive diabetes' health and economic burdens. Trial results indicated that SGLT2i are cost effective. However, these findings may not be generalizable to the real-world target population. This study aims to evaluate the cost effectiveness of SGLT2i in a routine care type 2 diabetes population that meets Dutch reimbursement criteria using the MICADO model. METHODS: Individuals from the Hoorn Diabetes Care System cohort (N = 15,392) were filtered to satisfy trial inclusion criteria (including EMPA-REG, CANVAS, and DECLARE-TIMI58) or satisfy the current Dutch reimbursement criteria for SGLT2i. We validated a health economic model (MICADO) by comparing simulated and observed outcomes regarding the relative risks of events in the intervention and comparator arm from three trials, and used the validated model to evaluate the long-term health outcomes using the filtered cohorts' baseline characteristics and treatment effects from trials and a review of observational studies. The incremental cost-effectiveness ratio (ICER) of SGLT2i, compared with care-as-usual, was assessed from a third-party payer perspective, measured in euros (2021 price level), using a discount rate of 4% for costs and 1.5% for effects. RESULTS: From Dutch individuals with diabetes in routine care, 15.8% qualify for the current Dutch reimbursement criteria for SGLT2i. Their characteristics were significantly different (lower HbA1c, higher age, and generally more preexisting complications) than trial populations. After validating the MICADO model, we found that lifetime ICERs of SGLT2i, when compared with usual care, were favorable (< €20,000/QALY) for all filtered cohorts, resulting in an ICER of €5440/QALY using trial-based treatment effect estimates in reimbursed population. Several pragmatic scenarios were tested, the ICERs remained favorable. CONCLUSIONS: Although the Dutch reimbursement indications led to a target group that deviates from trial populations, SGLT2i are likely to be cost effective when compared with usual care.

Prediction of complications in health economic models of type 2 diabetes: a review of methods used.

AIM: Diabetes health economic (HE) models play important roles in decision making. For most HE models of diabetes 2 diabetes (T2D), the core model concerns the prediction of complications. However, reviews of HE models pay little attention to the incorporation of prediction models. The objective of the current review is to investigate how prediction models have been incorporated into HE models of T2D and to identify challenges and possible solutions. METHODS: PubMed, Web of Science, Embase, and Cochrane were searched from January 1, 1997, to November 15, 2022, to identify published HE models for T2D. All models that participated in The Mount Hood Diabetes Simulation Modeling Database or previous challenges were manually searched. Data extraction was performed by two independent authors. Characteristics of HE models, their underlying prediction models, and methods of incorporating prediction models were investigated. RESULTS: The scoping review identified 34 HE models, including a continuous-time object-oriented model (n = 1), discrete-time state transition models (n = 18), and discrete-time discrete event simulation models (n = 15). Published prediction models were often applied to simulate complication risks, such as the UKPDS (n = 20), Framingham (n = 7), BRAVO (n = 2), NDR (n = 2), and RECODe (n = 2). Four methods were identified to combine interdependent prediction models for different complications, including random order evaluation (n = 12), simultaneous evaluation (n = 4), the 'sunflower method' (n = 3), and pre-defined order (n = 1). The remaining studies did not consider interdependency or reported unclearly. CONCLUSIONS: The methodology of integrating prediction models in HE models requires further attention, especially regarding how prediction models are selected, adjusted, and ordered.

Distribution fractions and potential ecological risk assessment of heavy metals in mangrove sediments of the Greater Bay Area.

The restoration of mangrove in coastal wetlands of China has been started since the 1990s. However, various pollutants, especially for heavy metals (HMs), contained in wastewater might present a significant risk to mangrove forests during the restoration. In this study, sediments of five typical mangrove wetlands with varying restoration years and management measures in the Greater Bay Area were collected to evaluate the distribution fractions and potential ecological risk of HMs. Cd (0.2-1.6 mg/kg) was found in high concentrations in the exchangeable fraction (37.8-71.5%), whereas Cu (54.2-94.8 mg/kg), Zn (157.6-332.6 mg/kg), Cr (57.7-113.6 mg/kg), Pb (36.5-89.9 mg/kg), and Ni (29.7-69.5 mg/kg) primarily presented in residual fraction (30.8-91.9%). According to the geo-accumulation index (Igeo) analysis, sediment Cd presented a high level of pollution (3 ≤ Igeo ≤ 4), while Zn and Cu were associated with moderately pollution (1 ≤ Igeo ≤ 2). Besides, high ecological risk of Cd was found in sediments of five mangroves, with risk assessment code (RAC) ranging from 45.9 to 84.2. Redundancy analysis revealed that the content of NO3--N was closely related to that of HMs in sediments and, pH value and NO3--N concentration affected the distribution of HMs geochemical fractions. High concentration of HMs in QA and NS sampling sites was caused by the formerly pollutants discharge, resulting in these sediments still with a higher HM pollution level after the plant of mangrove for a long period. Fortunately, strict drainage standards for industrial activities in Shenzhen significantly availed for decreasing HMs contents in mangrove sediments. Therefore, future works on mangrove conversion and restoration should be linked to the water purification in the GBA.

Abundance, spatial distribution, and characteristics of microplastics in agricultural soils and their relationship with contributing factors.

Agro-ecosystem contamination with microplastics (MPs) is of great concern. However, limited research has been conducted on the agricultural soil of tropical regions. This paper investigated MPs in the agro-ecosystem of Hainan Island, China, as well as their relationships with plastic mulching, farming practices, and social and environmental factors. The concentration of MPs in the study area ranged from 2800 to 82500 particles/kg with a mean concentration of 15461.52 particles/kg. MPs with sizes between 20 and 200 µm had the highest abundance of 57.57%, fragment (58.16%) was the most predominant shape, while black (77.76%) was the most abundant MP colour. Polyethylene (PE) (71.04%) and polypropylene (PP) (19.83%) were the main types of polymers. The mean abundance of MPs was significantly positively correlated (p < 0.01) with all sizes, temperature, and shapes except fibre, while weakly positively correlated with the population (p = 0.21), GDP (p = 0.33), and annual precipitation (p = 0.66). In conclusion, plastic mulching contributed to significant contamination of soil MPs in the study area, while environmental and social factors promoted soil MPs fragmentation. The current study results indicate serious contamination with MPs, which poses a concern regarding ecological and environmental safety.

The impact of zero markup drug policy on patients' healthcare utilization and expense: An interrupted time series study.

Objective: To curb the unreasonable growth of pharmaceutical expenditures, Beijing implemented the zero markup drug policy (ZMDP) in public hospitals in 2017, which focused on separating drug sales from hospital revenue. The purpose of this study is to evaluate the impacts of ZMDP on healthcare expenditures and utilization for inpatients. Methods: The Beijing claims data of inpatients diagnosed with ischemic heart disease (IHD), chronic renal failure (CRF), and lung cancer (LC) was extracted from the China Health Insurance Research Association (CHIRA) database. The study employed an interrupted time series to evaluate the impacts of ZMDP on healthcare expenditures and utilization. Results: The changes in total hospitalization expenses, health insurance expenses, and out-of-pocket expenses were not statistically significant neither in level change nor in trend change for inpatients diagnosed with IHD, CRF, or LC after implementing ZMDP (all P > 0.05). The Western medicine expenses for the treatment of inpatients diagnosed with IHD significantly decreased by 1,923.38 CNY after the reform (P < 0.05). The Chinese medicine expenses of inpatients diagnosed with CRF instantaneously increased by 1,344.89 CNY (P < 0.05). The service expenses of inpatients diagnosed with IHD and LC instantaneously increased by 756.52 CNY (p > 0.05) and 2,629.19 CNY (p < 0.05), respectively. However, there were no significant changes (P > 0.05) in out-of-pocket expenses, medical consumables, imaging, and laboratory test expenses of inpatients diagnosed with IHD, CRF, or LC. The initiation of the intervention immediately increased the number of inpatient admissions with LC by 2.293 per month (p < 0.05). Conclusions: The ZMDP was effective in reducing drug costs, and the effects on healthcare utilization varied across diseases type. However, the increase in medical service and Chinese medicine expenses diminished the effect of containing healthcare expenses and relieving the financial burdens of patients. Policymakers are advised to take multiple and long-lasting measures, such as provider payment methods reform, volume-based drug procurement, and drug price negotiation to improve the affordability of patients thoroughly.

Inequality in Accessibility of Proton Therapy for Cancers and Its Economic Determinants: A Cross-Sectional Study.

Background: Cancer is a leading cause of death in the world, and the estimated new cancer cases were 19 million and the estimated cancer deaths were around 10 million worldwide in 2020. Proton therapy (PT) is a promising treatment for cancers; however, only few patients with cancer received PT due to limited number of PT centers worldwide, especially in low- and middle-income countries. Methods and Results: Cross-sectional country level data were collected from publicly available information. Lorenz curves and Gini coefficient were used to assess the inequality in accessing to PT, and zero-inflated Poisson models were used to investigate the determinants of number of PT facilities in each country. The Gini coefficients were 0.96 for PT centers and 0.96 for PT chambers, which indicated high level of inequality. Total GDP had a significant impact on whether a country had a practical PT center, whereas total GDP and GDP per capita had significant impacts on the number of PT centers. Conclusion: Extremely high inequality exists in accessibility of PT centers among all countries in the world. Economic development was the most important factor determining the adoption of PT; thus, with the growth in global economics, more PT centers can be expected in near future.

Examining the Temporal and Spatial Models of China's Circular Economy Based upon Detailed Data of E-Plastic Recycling.

Examining the circular economy model is crucial to enable the scaling up of industry and anthropogenic circularity practice. Electrical and electronic waste plastic (e-plastic) has become the focus of urban mining and circular economy due to its rapid growth, valuable resource and potential risks. This article focuses on the recycling companies' experience in China from 2012 to 2017. The average recycling rate was 33.3% and the recycling amount in 2017 was 558 kt. A two-dimensional coupling model of economic development and renewable resources is firstly constructed. Eventually, four typical resource-based regional models are summarized, namely for demonstration regional model, commissioned regional model, traditional model and potential regional model. It also puts forward differentiated suggestions in terms of maintaining demonstration, strengthening policies, promoting transformation, and tapping potential. At the same time, it is recommended to explore the construction of large-region resource-based recycling centers and big data centers in resource-based demonstration areas.

Prediction of water quality based on SVR by fluorescence excitation-emission matrix and UV-Vis absorption spectrum.

As a result of economic development, the pollution of freshwater resources in urban areas of China is becoming more and more serious. Therefore, it is urgent and necessary to develop a real-time monitoring method for the water quality of urban streams and rivers. In this study, a novel method (CFFA) Combined by peak-picking method, Fluorescence spectral indexes, Fluorescence regional integration, and Absorption spectral indexes were designed to extract wide-ranging information from the combination of the excitation-emission matrix (EEM) and absorption spectrum (Abs) of water samples. More than 600 freshwater samples were collected at 180 sections of 60 rivers in the Yangzhou urban region from April 2018 and May 2019. The CFFA inputs form was applied to establish the prediction models of water quality indexes (CODCr, CODMn, NH3-N, TP, TN, and BOD5) based on ε-Support Vector Regression (ε-SVR). To examine the performance of the prediction models, contrastive analysis among CFFA and the other three input models was carried out. Results show that CFFA input models have shorter modeling time, lower RMSE and MAPE, and higher R2 in both training and testing sets, and each constituent part of CFFA is important to the precise prediction on the basis of the ablating analysis. Our study highlights that SVR models with the CFFA input trained by numerous and various water samples could effectively predict multiple indexes for real-time water quality monitoring.

Ratio of Overhydration and Extracellular Water Versus Ratio of Extracellular Water and Body Cell Mass in the Assessment of Fluid Status in Patients With Acute Kidney Injury Requiring Kidney Replacement Therapy: A Cohort Study.

OBJECTIVES: The aim of this study is to analyze the association between the ratio of overhydration and extracellular water (OH/ECW) and the ratio of extracellular water and body cell mass (ECW/BCM) measured by bioelectrical impedance and outcomes of patients with acute kidney injury (AKI) requiring kidney replacement therapy (KRT). METHODS: Patients with severe AKI treated with KRT in our hospital between September 2016 and August 2018 were enrolled. These patients were assessed using a body composition monitor before KRT, and on the 3rd day and the 7th day after initiation of KRT. The predictors mainly included OH/ECW and ECW/BCM. The association between all-cause mortality and predictors were analyzed using Cox regression. RESULTS: A total of 152 patients were included in this study with a median follow-up of 39 (interquartile range 8-742) days. The 28-day mortality, 90-day mortality, and 1-year mortality were 46.7%, 54.6%, and 60.5%, respectively. A high ratio of OH/ECW (adjusted hazard ratio per standard deviation, 1.45; 95% confidence interval = 1.15-1.82, P = .002) and a high ratio of ECW/BCM (adjusted hazard ratio per standard deviation, 1.33, 95% confidence interval = 1.07-1.64, P = .009) before KRT were associated with all-cause mortality during follow-up. Higher ECW/BCM rather than OH/ECW at 7th day was associated with poorer outcomes. Furthermore, a reduction of OH/ECW with an increase of ECW/BCM had higher 1-year mortality as compared to others (85.7% vs. 51.2%, P = .004) in patients who survived 7 days after KRT initiation. CONCLUSIONS: ECW/BCM performed better than OH/ECW in assessment of fluid status in AKI patients requiring KRT. This study suggested that a simple reduction of OH/ECW without decreasing ECW/BCM may not improve outcomes.

Progress and challenges of network meta-analysis.

In the past years, network meta-analysis (NMA) has been widely used among clinicians, guideline makers, and health technology assessment agencies and has played an important role in clinical decision-making and guideline development. To inform further development of NMAs, we conducted a bibliometric analysis to assess the current status of published NMA methodological studies, summarized the methodological progress of seven types of NMAs, and discussed the current challenges of NMAs.

Changes of air quality and its associated health and economic burden in 31 provincial capital cities in China during COVID-19 pandemic.

With outbreak of the novel coronavirus disease (COVID-19), immediate prevention and control actions were imposed in China. Here, we conducted a timely investigation on the changes of air quality, associated health burden and economic loss during the COVID-19 pandemic (January 1 to May 2, 2020). We found an overall improvement of air quality by analyzing data from 31 provincial cities, due to varying degrees of NO2, PM2.5, PM10 and CO reductions outweighing the significant O3 increase. Such improvement corresponds to a total avoided premature mortality of 9410 (7273-11,144) in the 31 cities by comparing the health burdens between 2019 and 2020. NO2 reduction was the largest contributor (55%) to this health benefit, far exceeding PM2.5 (10.9%) and PM10 (23.9%). O3 instead was the only negative factor among six pollutants. The period with the largest daily avoided deaths was rather not the period with strict lockdown but that during February 25 to March 31, due to largest reduction of NO2 and smallest increase of O3. Southwest, Central and East China were regions with relatively high daily avoided deaths, while for some cities in Northeast China, the air pollution was even worse, therefore could cause more deaths than 2019. Correspondingly, the avoided health economic loss attributable to air quality improvement was 19.4 (15.0-23.0) billion. Its distribution was generally similar to results of health burden, except that due to regional differences in willingness to pay to reduce risks of premature deaths, East China became the region with largest daily avoided economic loss. Our results here quantitatively assess the effects of short-term control measures on changes of air quality as well as its associated health and economic burden, and such information is beneficial to future air pollution control.

Assessment of Zeolite, Biochar, and Their Combination for Stabilization of Multimetal-Contaminated Soil.

In this study, the natural zeolite and rice husk biochar were mixed as a combination amendment for metal immobilization in a Cd, Pb, As, and W co-contaminated soil. A 90 day incubation study was conducted to investigate the effects of amendments on toxic metal in soil. Zeolite, biochar, and their combination application increased the soil pH and cation exchange capacity. A combination of amendments decreased the bioavailability of Cd, Pb, As, and W. Besides, the potential drawback of biochar application on As and W release was overcome by the combination agent. Zeolite, biochar, and combination treatment decreased total bioavailability toxicity from 335.5 to 182.9, 250.5, and 143.4, respectively, which means that combination was an optimum amendment for soil remediation. The results of the Community Bureau of Reference sequential extraction and scanning electron microscopy-energy-dispersive spectrometry images confirmed the Cd and Pb adsorption onto biochar. However, As and W immobilization was dominantly controlled by zeolite. It appears that the combination of amendments is an efficient amendment to remediate Cd, Pb, As, and W co-contamination in soil, although the combination of amendments has a lower stabilization rate for W than for zeolite.

An atom-economical design of PET tracer for imaging αvß3 integrin via utilizing the three-in-one function of 64Copper.

In this study, αvß3 integrin in U87 tumor cells was imaged with a 64Cu-peptidic probe, in which the linear peptide GHRGDHG is used as a pre-ligand, while 64Cu bears three functional roles that include generation of the PET signal, coordination with two GH moieties of the pre-ligand, and cyclizing the linear pre-ligand into an active cyclic-RGD form (termed as 64Cu-Cyclo-RGD) for αvß3 integrin.