Organisation For Economic Co-operation And Development Research Articles

Do military expenditures have an impact on the adoption of renewable energy in OECD nations? Evidence from a panel cointegration test approach

Purpose Today, many industries are implementing creative approaches in response to increasing environmental awareness. It is of great importance to answer the question of whether the military sector, one of the most important sectors, can support renewable energy (RE) adaptation. This study aims to examine how military spending affects the supply of RE in 27 Organization for Economic Cooperation and Development (OECD) nations as well as the regulatory function of factors such as innovation, international trade and oil prices between 1990 and 2021. Design/methodology/approach The study examines the effects of military spending, income, green innovation, international trade, oil prices and the human development index on the supply of RE using various econometric approaches, which are the cointegration test, moments quantile regression and robustness test. Findings The findings demonstrate that all factors, excluding military spending, quite likely affect the expansion of the renewable supply. Military spending negatively influences the RE supply; specifically, a 1% increase in military spending results in a 0.88 reduction in the renewable supply. In addition, whereas income elasticity, trade and human development index in OECD nations are higher in the last quantiles of the regression than in the first quantiles, the influence of military spending and innovation on renewable supply is about the same in all quantiles. Practical implications OECD nations must consider the practical implications, which are essential to assess and update the military spending of OECD countries from a green energy perspective to transition to clean energy. Based on the study’s overall findings, the OECD countries should incorporate the advantages of innovation, economic growth and international trade into their clean energy transition strategies to lessen the impact of military spending on renewables. Originality/value The study aims to fill a gap in the literature regarding the role of military expenditures in the RE development of an OECD country. In addition, the results of the methodological analysis can be used to guide policymakers on how military spending should be in the field of RE.

Toward a Greener Future: Investigating the Environmental Quality of Non-Green Trading in OECD Countries

International trade is recognized as a key contributor to environmental degradation. However, researchers and policymakers do not distinguish between the trade of green and non-green products. The Non-Green Trade Openness Index was developed to examine the effect of non-green products on environmental quality. This study examines the effect of trading non-green products on environmental quality for 37 member countries of the Organization for Economic Co-operation and Development (OECD) from 2003 to 2016 in the context of the Environmental Kuznets Curve (EKC) framework. The results of the long-run estimation techniques employed (FMOLS, DOLS, Fixed and Random effects) confirm the EKC hypothesis and show a negative relationship between the Non-Green Trade Openness Index and greenhouse gas emissions, which serves as a proxy for environmental quality. This implies that when there is more non-green trade in OECD member countries, greenhouse gas emissions within these countries decrease. Dividing green and non-green products is important, empowering practitioners and policymakers to make informed choices and define a strategy for a sustainable future. Additionally, policy recommendations are provided to support policymakers in their efforts to combat climate change.

Cross-country comparisons in health price growth over time.

To examine how the United States compares in terms of health price growth relative to four other countries - Australia, Canada, France, and the Netherlands. Secondary data on health expenditure were extracted from international and national agencies spanning the years 2000-2020. International price indices specific to health were constructed using available international expenditure data and compared to existing health-specific national and general international price indices. Health expenditure data were extracted from the Organization for Economic Cooperation and Development (OECD) database. We obtained a time series of health price indices from the national agencies in each of the study countries. We find meaningful variation across countries in the rate at which health prices grow relative to general prices. The United States had the highest cumulative health price growth compared to general price growth over the years 2000-2020 at 14%, followed by Canada and the Netherlands. Unlike the other study countries, health prices in France grew consistently in line with general prices. Price growth for health care paid for by public funds and households grew at different rates across countries, where price growth was higher for public payers. US households faced the greatest mean annual price growth. The choice of price index has major implications for comparative analysis. Despite their widespread use internationally, general price indices likely underestimate the contribution of price growth to overall health expenditure growth. We find that in addition to its reputation for having high health price levels compared to other high-income countries, the United States also faces health price growth for goods and services paid for by government and households in excess of general price growth. Furthermore, US households are exposed to greater health price growth than households in comparator countries.

Hybrid Machine Learning and Experimental Studies of Antiviral Potential of Ionic Liquids against P100, MS2, and Phi6.

Viruses are a group of widespread organisms that are often responsible for very dangerous diseases, as most of them follow a mechanism to multiply and infect their hosts as quickly as possible. Pathogen viruses also mutate regularly, with the result that measures to prevent virus transmission and recover from the disease caused are often limited. The development of new substances is very time-consuming and highly budgeted and requires the sacrifice of many living organisms. Computational chemistry methods allow faster analysis at a much lower cost and, most importantly, reduce the number of living organisms sacrificed experimentally to a minimum. Ionic liquids (ILs) are a group of chemical compounds that could potentially find a wide range of applications due to their potential virucidal activity. In our study, we conducted a complex computational analysis to predict the antiviral activity of ionic liquids against three surrogate viruses: two nonenveloped viruses, Listeria monocytogenes phage P100 and Escherichia coli phage MS2, and one enveloped virus, Pseudomonas syringae phage Phi6. Based on experimental data of toxic activity (logEC90), we assigned activity classes to 154 ILs. Prediction models were created and validated according to the Organization for Economic Co-operation and Development (OECD) recommendations using the Classification Tree method. Further, we performed an external validation of our models through virtual screening on a set of 1277 theoretically generated ionic liquids and then selected 10 active ionic liquids, which were synthesized to verify their activity against the analyzed viruses. Our study proved the effectiveness and efficiency of computational methods to predict the antiviral activity of ionic liquids. Thus, computational models are a cost-effective alternative approach compared with time-consuming experimental studies where live animals are involved.

Digital Progression and Economic Growth: Analyzing the Impact of ICT Advancements on the GDP of European Union Countries

This research thoroughly examines the dynamic relationship between the European Union’s economic growth and rapid advancements in Information and Communication Technology (ICT). Specifically, it assesses how certain ICT indicators are associated with significant economic growth. Utilizing an extensive dataset from the Digital Economy and Society Index 2022 (DESI), the Statistical Office of the European Union (EUROSTAT), and the Organisation for Economic Co-operation and Development (OECD), this study encompasses data from all 27 European Union member states. Employing structural equation modelling, our analysis illustrates the positive correlation between ICT development and the Gross Domestic Product (GDP) index. Our findings highlight the critical role of swiftly evolving technological landscapes, emphasizing the growing influence of new Artificial Intelligence (AI) technologies in business sectors. Furthermore, this study showcases the need to enhance human capital and expedite the growth of e-government technologies. These advancements are pivotal in strengthening the infrastructure supporting citizens and public enterprises across European countries, thereby contributing to their economic vitality.

Does the healthcare decentralization provide better public health security capacity and health services satisfaction? An analysis of OECD countries

PurposeDecentralization has profound implications for many health systems. This study investigates the effect of health system decentralization in Organization for Economic Co-operation and Development (OECD) countries on public health security capacity and health service satisfaction.Design/methodology/approachMultiple linear regression analyses were employed for variables related to the level of health security capacity and satisfaction with the healthcare system while controlling for all socio-demographic variables from the European Social Survey, including over 44,000 respondents from 25 OECD countries. The Health Systems in Transition series of countries were used for assessing the decentralization level.FindingsThe result of multiple linear regression analyses showed that the level of decentralization in health systems was significantly associated with higher health security capacity (ß-coefficient 3.722, 95% confidence interval (CI) [3.536 3.908]; p=<0.001) and health service satisfaction (ß-coefficient 1.463, 95% CI [1.389 1.536]; p=<0.001) in the study. Countries with a higher level of decentralization in health policy tasks and areas were significantly likely to have higher health services satisfaction, whereas this satisfaction had a significant negative relation with the lower level of decentralization status of secondary/tertiary care services in OECD countries (ß-coefficient −5.250, 95% CI [−5.757–4.743]; p = 0.001).Originality/valueThis study contributes to a better understanding of the extent to which decentralization of health services affects public health safety capacity and satisfaction with health services, whereas the level of decentralization in OECD countries varies considerably. Overall, the findings highlight the importance of public health security and satisfaction with health care delivery in assessing the effects of decentralization in health services.

Limited impact of hydrogen co-firing on prolonging fossil-based power generation under low emissions scenarios

Climate change mitigation generally require rapid decarbonization in the power sector, including phase-out of fossil fuel-fired generators. Given recent technological developments, co-firing of hydrogen or ammonia, could help decarbonize fossil-based generators, but little is known about how its effects would play out globally. Here, we explore this topic using an energy system model. The results indicate that hydrogen co-firing occurs solely in stringent mitigation like 1.5 °C scenarios, where around half of existing coal and gas power capacity can be retrofitted for hydrogen co-firing, reducing stranded capacity, mainly in the Organization for Economic Co-operation and Development (OECD) countries and Asia. However, electricity supply from co-firing generators is limited to about 1% of total electricity generation, because hydrogen co-firing is mainly used as a backup option to balance the variable renewable energies. The incremental fuel cost of hydrogen results in lower capacity factor of hydrogen co-fired generators, whereas low-carbon hydrogen contributes to reducing emission cost associated with carbon pricing. While hydrogen co-firing may play a role in balancing intermittency of variable renewable energies, it will not seriously delay the phase-out of fossil-based generators.

Science-based evidence on pathways and effects of human exposure to micro- and nanoplastics.

Human exposure to plastic particles has raised great concern among all relevant stakeholders involved in the protection of human health due to the contamination of the food chain, surface waters, and even drinking water as well as due to their persistence and bioaccumulation. Now more than ever, it is critical that we understand the biological fate of plastics and their interaction with different biological systems. Because of the ubiquity of plastic materials in the environment and their toxic potential, it is imperative to gain reliable, regulatory-relevant, science-based data on the effects of plastic micro- and nanoparticles (PMNPs) on human health in order to implement reliable risk assessment and management strategies in the circular economy of plastics. This review presents current knowledge of human-relevant PMNP exposure doses, pathways, and toxic effects. It addresses difficulties in properly assessing plastic exposure and current knowledge gaps and proposes steps that can be taken to underpin health risk perception, assessment, and mitigation through rigorous science-based evidence. Based on the existing scientific data on PMNP adverse health effects, this review brings recommendations on the development of PMNP-specific adverse outcome pathways (AOPs) following the AOP Users' Handbook of the Organisation for Economic Cooperation and Development (OECD).

Article: Anti-Avoidance Jurisprudence in Direct Taxation: The CJEU Between Politics and Certainty

Over a span of several years, the Court of Justice of the European Union (CJEU) developed a framework for anti-abuse in the context of European law and particularly established criteria for justifying restrictions on the fundamental freedoms in the tax context. In tax cases on anti-avoidance that are more recent, however, the court has demonstrated a notable change in its stance towards this issue that represents a disruption in the consistent development of its jurisprudence on abuse. While the court covers the contradictions in its case law by passing an impression of continuity between disparate decisions, it is remarkable how recent rulings draw from Organisation for Economic Co-operation and Development (OECD) language. This reliance on concepts from a non-EU institution, however, leads to legitimacy concerns. The increasing importance of international organizations and public opinion – for example, in reaction to the Panama Papers – in shaping the international tax landscape is undeniable. While high-profile projects like Base Erosion and Profit Shifting (BEPS) and Global Anti-Base Erosion (GloBE) highlight international tax issues, they also exert political pressure on judicial bodies such as the CJEU which leads to less methodological decisions that will align the court with political interests. In this context, the CJEU’s acting as a political player at the borderline of its competences is to be viewed critically, especially regarding the recent shift in its case law on abuse and tax avoidance that leads to concerns over legal certainty. Anti-abuse principle, anti-avoidance jurisprudence, CJEU, international organizations, international taxation, legal certainty, legitimacy, political influence

Development of tax administration in the Russian Federation in the context of digital transformation

The digital transformation of business and the public sector has had a significant impact on business activities. New types of business have emerged, mainly carried out in the digital space. In addition, new means of payment have emerged: cryptocurrencies and digital financial assets. These facts are shocks to tax administration models created to interact with taxpayers engaged in traditional activities. In this regard, in 2020, the Organization for Economic Co-operation and Development (OECD) at the XIII plenary meeting of the Forum on Tax Administration proposed the concept of digital transformation of tax administration “Tax Administration 3.0: Digital transformation of tax administration.” Taking into account the noted factors, the article provides a theoretical analysis of the risks caused by digital transformation for the purposes of tax administration, and also considers the best practices for leveling risks, including through the digitalization of tax administration. The subject of the study is the digital transformation of tax administration in the Russian Federation. The purpose of the study is to develop proposals for the development of tax administration in the Russian Federation, taking into account the best global practices, as well as using advanced technologies of the digital economy. As part of the study, the following research methods were used: retrospective analysis, synthesis, comparison and forecasting. The article provides a general analysis of the phenomenon of digital transformation and the associated risks for the purposes of tax administration; OECD proposals for the digital transformation of tax administration were reviewed, including their advantages and disadvantages; actual approaches to the transformation of the tax administration model used in the Russian Federation are noted. The scientific novelty of the work is expressed in the proposed further directions for the development of tax administration in the Russian Federation, including: the development of electronic document management; expanding the use of Blockchain technology; using the capabilities of smart contracts to automate the process of calculating and paying taxes. The solutions proposed in the study can be used in the practical implementation of measures to develop tax administration in the Russian Federation.

Environmental impact of PFAS: Filling data gaps using theoretical quantum chemistry and QSPR modeling

Per- and polyfluorinated alkyl substances (PFAS), known for their widespread environmental presence and slow degradation, pose significant concerns. Of the approximately 10,000 known PFAS, only a few have undergone comprehensive testing, resulting in limited experimental data. In this study, we employed a combination of physics-based methods and data-driven models to address gaps in PFAS bioaccumulation potential. Using the COnductor-like Screening MOdel for Realistic Solvents (COSMO-RS) method, we predicted n-octanol/water partition coefficients (logKOW), crucial for PFAS bioaccumulation. Our developed Quantitative Structure-Property Relationship (QSPR) model exhibited high accuracy (R2 = 0.95, RMSEC = 0.75) and strong predictive ability (Q2LOO = 0.93, RMSECV = 0.83). Leveraging the extensive NORMAN, we predicted logKOW for over 4,000 compounds, identifying 244 outliers out of 4519. Further categorizing the database into eight Organisation for Economic Co-operation and Development (OECD) categories, we confirmed fluorine atoms role in enhanced bioaccumulation. Utilizing predicted logKOW, water solubility logSW, and vapor pressure logVP values, we calculated additional physicochemical properties that are responsible for the transport and dispersion of PFAS in the environment. Parameters such as Henry’s Law (kH), air–water partition coefficient (KAW), octanol–air coefficient (KOA), and soil adsorption coefficient (KOC) exhibited favorable correlations with literature data (R2 > 0.66). Our study successfully filled data gaps, contributing to the understanding of ubiquitous PFAS in the environment and estimating missing physicochemical data for these compounds.

Methanol leaf extract of Leptadenia hastata ameliorates chronic, unpredictable, mild stress-induced depression

Leptadenia hastata (Pers) Decne is a tropical herb widely used in the phytotherapy of neuropsychiatric disorders, including depression. Despite the availability of synthetic antidepressant drugs, depression remains a major medical problem. The study aimed to evaluate the effect of methanol leaf extract of Leptadenia hastata (LHME) on chronic unpredictable mild stress-induced depression. Acute toxicity of Leptadenia hastata was determined using Organization for Economic Co-operation and Development (OECD) guidelines. The chronic unpredictable mild stress (CUMS) model-induced depression involves the evaluation of baseline behavioural changes in the sucrose preference test, open field test, and tail suspension test. The brain-derived neurotrophic factor (BDNF) concentrations and serum cortisol were assessed using an enzyme-linked immunosorbent assay (ELISA). The levels of superoxide dismutase (SOD) and malondialdehyde (MDA) were also assessed using standard procedure. The median lethal dose (LD50) value was &gt; 5000 mg/kg. LHME at doses of 250 – 1000 mg significantly (p&lt;0.01) decreased CUMS-induced depression in a dose-dependent manner. LHME significantly (p&lt;0.01) reversed depression associated weight loss from 14.00±0.62 g in week two to 22.57±1.13 g in week five of the experiment. It also increased sucrose consumption in the sucrose preference test (SPT) from 4.29±0.52 ml in week two to 9.71±0.68 ml in week five. The LHME also significantly (p&lt;0.01) decreased the duration of immobility from 190.00±4.55 sec in week two to 158.00±3.83 sec in week five in the tail suspension test (TST). Furthermore, LHME at the tested dose significantly (p&lt;0.01) increased the locomotor activity from 36.29±1.25 sec in week two to 62.43±1.73 sec in week five in the open field test (OFT). LHME significantly (p&lt;0.01) and dose-dependently increased the levels of BDNF (204.74±22.97 pg/ml) and decreased the levels of plasma cortisol (0.98±0.06 ng/ml). However, treatment with LHME and the standard drug imipramine did not significantly change SOD activity and the MDA level in CUMS-induced mice. The findings demonstrated that LHME ameliorates CUMS-induced depressive-like behaviours, and its effect is possibly mediated via the neuroendocrine (cortisol) and neurotrophic (BDNF).

Housing affordability indicators and the sustainability paradigm in OECD countries

The present study aimed to analyse the housing affordability indicators (HAI) and sustainability paradigm (SP) of 23 Organisation for Economic Co-operation and Development (OECD) countries for the period of 2010–2019. The study used different estimators to overcome the heterogeneity and endogeneity problems of panel data and adopted many diagnostic tests to increase robustness. The findings of panel least square, generalized least square, and instrumental variables of the two-stage least squares regression approach showed that three HAI proxies - households' housing-related expenditures, housing costs, and housing market proxies - had a significant positive impact on the sustainability paradigm. In contrast, the final two HAI proxies - housing allowance and housing quality – significantly negatively impacted the sustainability paradigm. Regarding the control variables, population density had a significant positive impact on the sustainability paradigm indicators. However, GDP per capita growth had a significant negative impact on most of the sustainability paradigm indicators. The main conclusion is that decision-makers should prioritize making housing more affordable. This could be achieved by controlling rents and low-cost buildings. The OECD should explore alternative methods of support, such as providing low-interest loans or targeted assistance, to help families bear housing costs without negatively impacting their financial sustainability.

The impact of digitalization, technological and financial innovation on environmental quality in OECD countries: Investigation of N-shaped EKC hypothesis

This research article aims to determine the interrelationships between digitalization, technological and financial innovation, and environmental quality in selected Organization for Economic Cooperation and Development (OECD) countries. This study also tests the validity of the N-shaped Environmental Kuznets Curve (EKC) hypothesis. To this end, we utilize a rigorous three-stage panel data econometrics approach. The empirical outcomes entail that financial innovation decreases carbon emissions, whereas technological innovation and digitalization increase carbon emissions in the OECD countries. The results further underscore that across all models, the first level of gross domestic product (GDP) harms environmental quality. On the flip side, the second level of GDP tends to improve environmental quality. However, the third level of GDP deteriorates environmental quality. In conclusion, the empirical findings corroborate the N-shaped EKC hypothesis in OECD countries, urging policymakers to adopt more sustainable development practices.

An artificial intelligence platform for automated PFAS subgroup classification: A discovery tool for PFAS screening

Since structural analyses and toxicity assessments have not been able to keep up with the discovery of unknown per- and polyfluoroalkyl substances (PFAS), there is an urgent need for effective categorization and grouping of PFAS. In this study, we presented PFAS-Atlas, an artificial intelligence-based platform containing a rule-based automatic classification system and a machine learning-based grouping model. Compared with previously developed classification software, the platform's classification system follows the latest Organization for Economic Co-operation and Development (OECD) definition of PFAS and reduces the number of uncategorized PFAS. In addition, the platform incorporates deep unsupervised learning models to visualize the chemical space of PFAS by clustering similar structures and linking related classes. Through real-world use cases, we demonstrate that PFAS-Atlas can rapidly screen for relationships between chemical structure and persistence, bioaccumulation, or toxicity data for PFAS. The platform can also guide the planning of the PFAS testing strategy by showing which PFAS classes urgently require further attention. Ultimately, the release of PFAS-Atlas will benefit both the PFAS research and regulation communities.

Association between retirement age and depressive symptoms among Korean retirees: Results from Korean Retirement and Income Panel Study

BackgroundThe effective age of retirement in South Korea is higher than the average of Organization for Economic Co-operation and Development (OECD) countries. Early retirement in Asia may affect mental health differently compared to western countries. Thus, we examined the association between retirement age and depressive symptoms among South Korean retirees. MethodsWe used data from the 2011, 2013, 2015, 2017, and 2019 Korean Retirement and Income Panel Study, including a total of 2998, 3152, 3203, 3154, and 3055 participants, respectively. We excluded those younger than 50 years, non-retirees, those without information on the Center for Epidemiological Studies-Depression (CES-D) scale, and those with other missing values. We used a generalized estimating equation model to identify the association between retirement age and depressive symptoms measured using the CES-D. ResultsParticipants who retired at age < 50 years had significantly higher CES-D scores (β = 1.764, P = 0.0003) compared to those who retired at age ≥ 70 years. The negative effects of early retirement on depressive symptoms were greater among male participants, heads of households, young involuntary retirees, those who retired within the past 20 years, and those who had no difficulties in activities of daily living. LimitationsSince we evaluated the association between retirement age and depressive symptoms in one direction, there is a possibility of reverse causality. ConclusionOur findings highlight the importance of managing depressive symptoms in early retirees, especially young involuntary retirees and those burdened with family care.

Assessing the dynamic impacts of climate change adaptation and clean energy innovations on economic growth in OECD countries

AbstractThis paper examines whether accelerating climate change adaptation and clean energy innovations is an effective way to promote sustainable development and mitigate environmental risks. Based on this, the main purpose of this study is to investigate the potential effect of climate change adaptation and clean energy innovations with casual factors of social, political, human development, environmental, and climatic determinants as drivers of economic growth in 38 Organization for Economic Co‐operation and Development (OECD) countries from 1990 to 2020. Employing the system‐generalized method of moments (GMM) method, this study shows that causal factors of social, political, educational, and environmental development have a positive effect on the economic growth process. Additionally, the interaction between climate change adaptation and temperature has a constant positive impact on economic growth. The findings highlight that policymakers should thoroughly evaluate the potential impacts of the climate change adaptation process and clean energy innovations in all aspects and implement measures and approaches that promote sustainable development, increase the adoption of environmentally friendly technologies, and address the challenges posed by climate change.

Medie- och informationskunnighet är mer än bara källkritik och tekniskt kunnande. Vilka behov är det som behöver mötas och hur?

The same day as the invasion of Ukraine started, the two biggest TVnews channels in Sweden and the prime minister pointed out the problem with source criticism of media and that it is difficult to know what a reliable source is and why it is very important to be critical (SVT, 2022; TV4, 2022). This article dwells on source criticism in mainly digital media within the school subject of civics, both as a problematizing text and as a discussion. The discussion has its basis in two studies. One is a study from the Swedish Schools Inspectorate that originates from an audit of the teaching of source criticism within civics classes, mainly in regards to digital media and where there is a criticism towards the content and teaching of the subject. The other study is a study from the Organisation for Economic Co-operation and Development (OECD) that was published in May 2021. It is a PISA study where it was noted that 15 year old pupils all over the world had difficulties in sorting facts from opinions in digital media. The Nordic Countries were ranked high, despite only around 50 percent of the pupils managing to differ between fact and opinion. The two studies are then brought up in conjunction with previous research, which mainly focuses on the teaching of source criticism within civic classes and the mediatization process that is ongoing in society, and which forms the basis for the discussion. Based on the problematization it is evident that there is a strong need to increase the knowledge of media and information among pupils, if they are to be brought up as citizens in a democracy. The three main questions are therefore, what kind of MIL do the pupils have and do the teachers in the schools have the opportunity to further their education to a required level and is it reasonable that student teachers in the subjects they are training for should also have time to educate themselves sufficiently in Media and information literacy to be able to strengthen the pupils MIK?

Improved QSAR models for PARP-1 inhibition using data balancing, interpretable machine learning, and matched molecular pair analysis.

The poly (ADP-ribose) polymerase-1 (PARP-1) enzyme is an important target in the treatment of breast cancer. Currently, treatment options include the drugs Olaparib, Niraparib, Rucaparib, and Talazoparib; however, these drugs can cause severe side effects including hematological toxicity and cardiotoxicity. Although in silico models for the prediction of PARP-1 activity have been developed, the drawbacks of these models include low specificity, a narrow applicability domain, and a lack of interpretability. To address these issues, a comprehensive machine learning (ML)-based quantitative structure-activity relationship (QSAR) approach for the informed prediction of PARP-1 activity is presented. Classification models built using the Synthetic Minority Oversampling Technique (SMOTE) for data balancing gave robust and predictive models based on the K-nearest neighbor algorithm (accuracy 0.86, sensitivity 0.88, specificity 0.80). Regression models were built on structurally congeneric datasets, with the models for the phthalazinone class and fused cyclic compounds giving the best performance. In accordance with the Organization for Economic Cooperation and Development (OECD) guidelines, a mechanistic interpretation is proposed using the Shapley Additive Explanations (SHAP) to identify the important topological features to differentiate between PARP-1 actives and inactives. Moreover, an analysis of the PARP-1 dataset revealed the prevalence of activity cliffs, which possibly negatively impacts the model's predictive performance. Finally, a set of chemical transformation rules were extracted using the matched molecular pair analysis (MMPA) which provided mechanistic insights and can guide medicinal chemists in the design of novel PARP-1 inhibitors.

Mental health indicators for children and adolescents in OECD countries: a scoping review.

This scoping review is a further step to build up the Mental Health Surveillance System for Germany. It summarizes and analyzes indicators used or described in Organization for Economic Co-operation and Development (OECD) countries for public mental health monitoring in children and adolescents aged 0-18 years. We searched PubMed-MEDLINE, PsycINFO, Cochrane Databases, and Google Scholar from 2000 to September 2022. The search used five general keyword categories: 1) "indicators/monitoring/surveillance" at the population level, 2) "mental/psychological," 3) "health/disorders," 4) "children and adolescents," and 5) 38 OECD countries. The search was complemented with an extensive grey literature search, including OECD public health institutions and an internet search using Google. A predefined set of inclusion and exclusion criteria was applied. Over 15,500 articles and documents were screened (scientific search N = 10,539, grey literature search more than 5,000). More than 700 articles and documents have been full-text assessed, with 382 being ultimately included. Out of 7,477 indicators extracted, an initial set of 6,426 indicators met our inclusion criteria for indicators. After consolidating duplicates and similar content, this initial set was categorized into 19 topics, resulting in a final set of 210 different indicators. The analysis highlighted an increasing interest in the topic since 2008, but indicators for the younger age, particularly those aged 0 to 2 years, were less readily available. Our research provides a comprehensive understanding of the current state of mental health indicators for children and adolescents, identifying both (1) indicators of public mental health noted in a previous scoping review on adults and (2) new indicators specific to this age group. These findings contribute to the development of effective public health surveillance strategies for children and adolescents and inform future research in this field.